Pertussis is a serious infectious disease in young infants, and severe cases frequently cause death. Our study explored risk factors for death from severe pertussis.A case-control study of infants with severe pertussis admitted to the paediatric intensive care unit (PICU) in the Children’s Hospital of Chongqing Medical University, China, from January 1, 2013, to June 30, 2019, was conducted. Pertussis was confirmed by clinical features and laboratory examinations. Severe pertussis was defined as patients with pertussis resulting in PICU admission or death. To understand the risk factors for death, we compared fatal and nonfatal cases of severe pertussis in infants aged < 120 days by collecting clinical and laboratory data.P = 0.001), leukocytosis (white blood cell (WBC) count≥30 × 109/L (P = 0.001) or ≥ 50 × 109/L (P = 0)), highest lymphocyte count (P = 0), pulmonary hypertension (P = 0.001), and length of PICU stay (P = 0.003). The multivariate analysis revealed that apnoea , leukocytosis  and pulmonary hypertension  were significantly associated with death.The participants included 63 infants < 120 days of age with severe pertussis. Fifteen fatal cases were confirmed and compared with 44 nonfatal severe pertussis cases, Four patients with termination of treatment were excluded. In the univariate analysis, the risk factors associated with death included apnoea (Leukocytosis and pulmonary hypertension exhibited the greatest associations with death in infants with severe pertussis admitted to the PICU. Vaccination is still the most effective protection method against pertussis. Bordetella pertussis and is characterized by paroxysmal coughing, coughing ending in a whooping sound, vomiting, apnoea or cyanosis [http://www.who.int/ith/diseases/pertussis/en/). However, even after widespread vaccination with the DTaP, reported pertussis cases substantially increased and are still increasing in China. The current programme for pertussis vaccination in China is administration of 1 dose at 3, 4, and 5 months of age and 1 increased dose at 18–24 months of age. At present, there is no programme for pertussis immunization during pregnancy [Pertussis is an acute respiratory infection caused by cyanosis . The WorB. pertussis by culture or detection of B. pertussis DNA by polymerase chain reaction (PCR) assays. Severe pertussis was defined as patients with pertussis resulting in PICU admission. The case group was defined as pertussis patients admitted to the PICU and dying from pertussis disease. The control group included pertussis patients admitted to the PICU and surviving pertussis disease.This was a case-control study of paediatric pertussis patients admitted to the PICU at the Children’s Hospital of Chongqing Medical University, China, from January 1, 2013 to June 30, 2019. The clinical features of pertussis included increasing frequency and severity of cough ending in a whooping sound or vomiting, apnoea or cyanosis. Some newborns had only cyanosis without cough. All cases were confirmed by isolation of 9/L.Hospital medical records were obtained, and data on birth factors; vaccination history; symptoms; course of illness; comorbidities; treatment including exchange transfusion (ET) or extracorporeal membrane oxygenation (ECMO); type of respiratory support; patient outcome; microbiology test results, such as full blood count; chest imaging reports by radiologists; and echocardiography findings were recorded. The birth weight and gestational age were obtained from birth records. Vaccination status was collected from the medical record or a copy of the vaccination record. Fever was defined as a tympanic or axillary temperature above 38 °C. The course of illness included the cough duration before hospitalization, PICU admission and the length of hospital and PICU stay, which were collected from the medical records. Pneumonia was defined by chest imaging. The highest white blood cell (WBC) count, platelet count, and lymphocyte count were recorded and analysed. Leucocytosis was defined as a WBC count ≥30 × 10c > 0.05. Variables with a P value of < 0.05 were included in the final regression model. All P values < 0.05 were considered statistically significant for all tests.SPSS v 23.0 software was used for the statistical analysis. The basic information and clinical characteristics of the two groups were compared by chi-square tests for categorical variables and Student’s t-tests or Mann Whitney U tests for continuous variables. For normally distributed continuous variables, Student’s t-test was used for comparisons; otherwise, a Mann Whitney U test was used. Univariate logistic regression analysis was performed to identify factors associated with death among infants with pertussis disease requiring admission to the PICU. Backward elimination stepwise multivariable logistic regression models were developed to identify independent risk factors for death among infants with pertussis disease requiring admission to the PICU. Th P-to-remove value was set as a From January 1, 2013 to June 30, 2019, 3280 pertussis patients were admitted to the Children’s Hospital of Chongqing Medical University, and 89 patients with severe pertussis were admitted to the PICU, including 63 patients who were < 120 days old. The 63 patients included 1 patient aged ≤1 month, 31 patients (49.2%) aged 1–2 months, 24 patients (38%) aged 2–3 months, and 7 patients (11.1%) aged 3–4 months, and the average age of cough onset was < 3 months. For 5 patients, treatment was terminated by their parents because the condition too serious to survive, and their parents were unable to accept the bad consequences. Among those who stopped receiving treatment, 4 patients died and 1 patient survived according to telephone follow-up. The 4 patients who died were excluded, and 59 cases were included in our study. The basic information, clinical symptoms and vaccination history of the patients are presented in Table n = 15) and nonfatal group (n = 44). Thirty-two (54.2%) infants were male, including 6 in the fatal group and 26 in the nonfatal group. The average weight was 5.13 ± 1.12 kg in the fatal group and 5.27 ± 1.07 kg in the nonfatal group. There were no differences in prematurity,birth weight and month age between two groups. The vaccination acceptance rate was generally low in our study, as the onset age for all the patients in our study was less than 3 months; the vaccination rate was 3.3%, and only 2 infants had received 1 dose of the vaccine in the fatal group. Almost all (57/59) infants had cough and cyanosis. Only 2 patients had only cyanosis without coughing which one was newborn.Fifteen of the 59 patients died (25.4%). We divided the patients into two groups: the fatal group (n = 49) received echocardiograms, and congenital heart disease (CHD) (n = 20) and pulmonary hypertension (n = 11) were present in some infants. Although some patients had CHD, such as an atrial septal defect , or patent ductus arteriosus  without complex CHD or cardiac dysfunction, the rate of CHD was not significantly different between the fatal and nonfatal groups. Five patients in the fatal group and 3 patients in the nonfatal group had CHD and pulmonary hypertension. All 8 patients had an ASD. In addition to CHD, 16 patients had other comorbidities including bronchopulmonary dysplasia (n = 4), hypoxic ischaemic encephalopathy (n = 4), rotavirus enteritis (n = 4), Down syndrome (n = 1), hypoplasia of the laryngeal cartilage, adenovirus encephalitis, and epilepsy. Although the majority of patients had more than one comorbidity, none of the comorbidities were the main cause of death in our study.The clinical manifestations of pertussis, main laboratory indexes, complications and treatments are presented in Table n = 13), Klebsiella pneumoniae (n = 13), Haemophilus influenzae (n = 13), adenovirus (n = 3), and influenza B (n = 3). The majority of patients had more than one pathogen infection. However, the rates of coinfection with specific pathogens were not significantly different between the fatal and nonfatal groups.All patients underwent chest imaging, and pneumonia and respiratory pathogens were detected by culture and PCR assays performed on sputum; serological examination was performed supplementally. Fifty-one patients (86%) had coinfections with clear pathogeny on admission; coinfections included respiratory syncytial virus (RSV)  required respiratory support (36 were intubated and 4 required noninvasive ventilation). All fatal cases required intubation. Five patients were treated with ETs, and 3 died. The peak WBC count in patients in the fatal group with ET ranged from 70.44 × 109/L on admission and peaked at 135.58 × 109/L. The case was complicated with pulmonary hypertension, acute respiratory distress syndrome (ARDS), and multiorgan failure prior to the ECMO procedure. Finally, pulmonary haemorrhage and brain hernia occurred, and the patient died soon after.Only 1 patient in the fatal group received ECMO for 2 days and received respiratory support and haemodialysis  at the same time. The infant’s WBC count was 97.22 × 10P = 0.001), highest lymphocytosis count (P = 0), WBC counts ≥30 × 109/L (P = 0.001) and ≥ 50 × 109/L(P = 0), pulmonary hypertension (P = 0.001), and length of PICU stay (days) (P = 0.003). The multivariate analysis of risk factors related to death is shown in Table P = 0.004), leukocytosis  and pulmonary hypertension  were significantly associated with death. WBC counts ≥30 × 109/L or ≥ 50 × 109/L and pulmonary hypertension were significantly associated with death.The univariate analysis of risk factors related to death is shown in Table Pertussis resurgence has been observed in recent years, and severe pertussis and death due to pertussis have gradually increased. According to other research, age ≤ 3 months is a risk factor for severe and death in pertussis cases –9, and 79/L. This infant was coinfected with RSV and diagnosed with severe pneumonia and ARDS. The second infant was admitted after cardiopulmonary resuscitation due to asphyxia. Pertussis was diagnosed after admission. The maximum WBC count was 23.19 × 109/L. It is possible that asphyxia and leukocytosis were significantly related to pertussis infection. Both patients died of respiratory failure without pulmonary hypertension.We found that apnoea, leukocytosis, and pulmonary hypertension were significantly associated with death in severe pertussis cases. Currently, in severe pertussis cases, leukocytosis and lymphocytosis are commonly observed and are significantly correlated with death , 12–15. Of greatest importance in the treatment of pertussis is the administration of a macrolide antibiotic. PICU management of infant pertussis cases has been limited , 19, 20.To date, the main preventive strategy for pertussis in China is a vaccination scheme with three doses starting at 3 months of age. According to previous reports, most patients with fatal outcomes were too young to receive their first dose of the DTaP vaccine . In our Because this is a retrospective study, it has some limitations, including a limited number of cases. All the patients in our study had varying degrees of hypoxemia and required respiratory support (59 invasive and 4 noninvasive); thus, their conditions were very serious, and a high mortality rate was observed, which explains why we had a limited number of cases. In addition, 10 infants did not undergo echocardiography, and heart and pulmonary artery conditions were unknown. Meanwhile, we could not collect the smoking habits of patients’ parents to determine whether any connection existed between pertussis and smoking.Throughout history, most pertussis deaths have occurred in infants. Leukocytosis and pulmonary hypertension are the greatest risk factors for death in infants with severe pertussis. Currently, the treatment of severe pertussis is limited and should be improved. ET and ECMO are also worth exploring as treatments, but additional data are needed. Vaccination is still the most effective protection method. Considering that ≤3 months of age is a risk factor for severe pertussis, our national vaccination schedule needs to be changed to protect infants in this age group.


Equivocal findings examining the influence of caffeine on performance and biological responses to exercise may be due to inter-individual variability in cardiorespiratory or neuromuscular fitness. This study examined whether the effects of caffeine ingestion on exercise performance and biological responses to prolonged intermittent exercise to exhaustion depend on cardiorespiratory or neuromuscular fitness.− 1) or placebo. Physical performance, cardiorespiratory and metabolic parameters and blood metabolites were evaluated.Twenty male soccer players, separated according to either cardiorespiratory fitness (high vs medium) or neuromuscular fitness (high vs medium) underwent two trials simulating the cardiovascular demands of a soccer game to exhaustion on treadmill after ingesting either caffeine (6 mg∙kg∙min− 1), mean arterial blood pressure (98 ± 8 vs 92 ± 10 mmHg), plasma glucose (5.6 ± 0.7 vs 5.3 ± 0.6 mmol∙l− 1) and lactate (3.3 ± 1.2 vs 2.9 ± 1.2 mmol∙l− 1) were higher, while rating of perceived exertion (12.6 ± 1.7 vs 13.3 ± 1.6) was lower with caffeine vs placebo (p < 0.01), independent of cardiorespiratory or neuromuscular fitness level. Reaction time; plasma glycerol, non-esterified fatty acids and epinephrine; carbohydrate and fat oxidation rates; and energy expenditure were not affected by caffeine (p > 0.05).Time to exhaustion (719 ± 288 vs 469 ± 228 s), jump height (42.7 ± 4.2 vs 38.6 ± 4.4 cm), heart rate (163 ± 12 vs 157 ± 13 bCaffeine was effective in improving endurance and neuromuscular performance in athletes with either high or medium cardiorespiratory and neuromuscular fitness. Cardiorespiratory and neuromuscular fitness do not appear to modulate the ergogenic effects of caffeine supplementation in well-trained athletes. Over the past three decades, caffeine has been one of the most popular ergogenic aids, used by athletes performing a variety of endurance and speed/power sports . NeverthCaffeine has been found to increase anaerobic performance  and Wing2max of 57.5 ml∙kg− 1∙min− 1) but not in recreationally active participants (mean VO2max of 46.5 ml∙kg− 1∙min− 1). On the other hand, Shen et al.  or on neuromuscular fitness . Time to exhaustion was longer with caffeine compared with placebo (719 ± 288 vs 469 ± 228 s). However, time to exhaustion was not different between groups, and there was no treatment-by-group interaction (p > 0.05).There was a significant main effect of treatment (caffeine vs placebo) on time to exhaustion Fig.  regardleThree of the participants who performed the caffeine trial after the placebo trial noticed their longer times to exhaustion and guessed they had taken caffeine. None of the other participants made any presumption related to what they were taking.p < 0.001, ES = 0.559] and time  main effects on CMJ  for the cardiorespiratory fitness classification. CMJ was higher with caffeine compared to placebo .There were significant treatment , treatment , and time , while there was no interaction (p > 0.05). There was no significant main effect or interaction in RT .For the neuromuscular fitness classification, Fig. b CMJ exhp = 0.002, ES = 0.417] and a time  main effect on MAP  = 18.51, p < 0.001, ES = 0.507] main effect on MAP. There was no significant group effect or interaction for either classification (p > 0.05).When the data were analyzed based on cardiorespiratory fitness level, there was a treatment  and time , as well as an interaction between treatment and time  for the cardiorespiratory fitness classification. HR was higher with caffeine than with placebo . For the neuromuscular fitness classification  = 14.39, p < 0.001, ES = 0.473]. There was no significant group effect for either classification (p > 0.05).Average HR during each of the four periods of the treadmill protocol Table  showed sime  and time , as well as an interaction between treatment and time  for the cardiorespiratory fitness classification on RPE  = 107.01, p < 0.001, ES = 0.856], as well as an interaction between treatment and time  on RPE. There was no significant group effect for either classification (p > 0.05).There were significant main effects of treatment , as well as an interaction between treatment and time . Plasma glucose was higher with caffeine than with placebo . Similarly, when analysis was based on neuromuscular fitness level, there were also a treatment effect , a time effect , and an interaction between treatment and time . There was no significant group effect with either classification (p > 0.05).When data were analyzed based on cardiorespiratory fitness level, plasma glucose Fig. a exhibitp = 0.01, ES = 0.311] and time , as well as an interaction between treatment and time  in plasma lactate . Within the neuromuscular fitness level analysis, there was also a treatment effect , a time effect , and an interaction between treatment and time .Within the cardiorespiratory fitness level analyses, there were significant main effects of treatment  and for the neuromuscular fitness classification , as well as a main effect of group on epinephrine for the neuromuscular fitness classification . The time effect was due to a general increase in all three parameters from the beginning to the end of the trials, and the group effect was due to epinephrine being higher in the MNF group.With regard to plasma glycerol Fig. c, NEFA d, and epp = 0.049] or body mass and body fat were used as covariates . These finding show that body mass and body fat had no influence on the caffeine responses.When body mass, body fat, or both variables were added to the analysis as covariates, all statistical outcomes but one were qualitatively the same. That is, all significant outcomes of ANOVA remained significant with ANCOVA and all non-significant outcomes of ANOVA remained non-significant with ANCOVA, with the exception of NEFA, which, although not significantly different between the HCF and MCF groups according to ANOVA, became significantly different  when body fat [F = 4.49, ES = 0.209, − 1, was effective in improving time to exhaustion, CMJ, and RPE of male soccer players in a trial simulating the cardiovascular demands of a soccer game regardless of differences in cardiorespiratory or neuromuscular fitness. Thus, these parameters do not appear to modulate the ergogenic effects of caffeine supplementation. These findings complement those of our previous study [The novel finding of the present study is that caffeine, at a dose of 6 mg∙kgus study , which, 2max values) following caffeine supplementation [2max, which is mainly determined by cardiac output and the ability of the working muscles to take up oxygen [The ergogenicity of caffeine on endurance performance found in the present study cannot be attributed to metabolic effects, since substrate utilization during the final stage of the time-to-exhaustion protocol was not different between the caffeine and placebo trials. A more probable explanation is a stimulatory effect on the central and peripheral nervous systems, since caffeine crosses the blood-brain barrier and acts as an adenosine receptor antagonist, increasing central motivation to exercise, peripheral neuromuscular activation, heart rate, myocardial oxygen consumption, and blood flow , 25. Thientation . It appep oxygen , is not 2+ release from the sarcoplasmic reticulum [+/K+ pump activity [The present study revealed a CMJ improvement following caffeine ingestion relative to placebo. This effect was independent of CMJ performance. Individual differences in CMJ performance could result from interaction of multiple factors such as fiber type proportions, muscle size, speed of neural activation of the musculature, rate of force development, and maximum strength –30. Baseeticulum  and/or iactivity .The positive effect of caffeine on plasma glucose found in the present study may indicate that caffeine stimulated liver and skeletal muscle glycogenolysis, resulting in increased release to and reduced uptake from the bloodstream during exercise . LikewisThis study offers novel insight into the effects of caffeine on biological responses and exercise performance relative to different fitness levels of the athletes. However, we should point out that, since our sample consisted of active soccer players, even the medium fitness groups had fairly high cardiorespiratory and neuromuscular fitness levels. Consequently, there may be a false negative for detection of differences between high and low attributes in the broader sports population. In addition, while performing a series of tests imitating a soccer game in the laboratory offers the advantage of strict control over the test variables, it should not be underestimated that results during actual game might be different due to uncontrolled variables . Another limitation is the relatively small sample size of the groups. This was imposed by the inability to find more well-trained professional soccer players and by the high cost of the analyses. Finally, although body mass and body fat did not influence the caffeine responses, we acknowledge that the stratification employed produced groups that were fairly different in body mass and significantly different in body fat. This should be controlled in the future for increased validity of the findings.The results of our study show that caffeine was effective in improving endurance and neuromuscular performance in high-intensity exercise regardless of cardiorespiratory or neuromuscular fitness level in well-trained young athletes. Hence, the ergogenicity of caffeine seems not to depend on cardiorespiratory or neuromuscular factors.


MicroRNAs play an important role in many fundamental biological and pathological processes. Defining the microRNAs profile underlying the processes by beneficial and detrimental lifestyles, including caloric restriction (CR), exercise and high-fat diet (HF), is necessary for understanding both normal physiology and the pathogenesis of metabolic disease. We used the microarray to detect microRNAs expression in livers from CR, EX and HF mice models. After predicted potential target genes of differentially expressed microRNAs with four algorithms, we applied GO and KEGG to analyze the function of predicted microRNA targets.We describe the overall microRNAs expression pattern, and identified 84 differentially expressed microRNAs changed by one or two or even all the three lifestyle modifications. The common and different enriched categories of gene function and main biochemical and signal transduction pathways were presented.We provided for the first time a comprehensive and thorough comparison of microRNAs expression profiles in liver among these lifestyle modifications. With this knowledge, our findings provide us with an overall vision of microRNAs in the molecular impact of lifestyle on health as well as useful clues for future and thorough research of the role of microRNAs.The online version contains supplementary material available at 10.1186/s12864-021-07507-3. Overweight and obesity have been recognized as risk factors for many chronic diseases such as the metabolic syndrome, diabetes, and cardiovascular diseases . The maiGenes (mRNA) involved in the process and intervention of obesity have been studied. However, the role of finer post-transcriptional gene regulatory mechanisms has not been comprehensively explored. MicroRNAs are a class of short non-coding RNAs which primarily interact with 3′ untranslated region (3’UTR) of mRNA, leading to either translational repression or mRNA degradation . These sRecent years, the number of microRNA profiling studies has increased rapidly. MicroRNAs profiles in several different tissues were investigated after CR, EX or HF, including adipose tissue, skeletal muscle, heart, especially circulating microRNAs –16. Therp < 0.01) , and in HF group it is lower  than in AL group. In EX group (64.8 ± 2.7%), it also has no significant difference with AL group , visceral fat mass (2.18 ± 0.15 g), total fat mass (3.55 ± 0.17 g) and total lean mass (11.86 ± 0.67 g) in CR group are significantly lower than in AL group   microRNAs using microarray technique. A total of 601 mature mouse microRNAs were profiled from the livers. Among them, 328 microRNAs were accepted as expressed genes in liver after filtering and were subjected to DE microRNAs analysis , cellular component (the location in the cell where a gene product is active), and molecular function  , 37. KEGAlthough there are some limitations in our study, such as a relatively small sample size, we confirmed some of the DE microRNAs and predicted targets with RT-qPCR. Differences of identified DE microRNAs do exist between our study and previous studies –27. One In conclusion, this study provided for the first time a comprehensive and thorough comparison of microRNAs expression profiles in liver among beneficial and detrimental lifestyles, including CR, EX and HF. We presented similarity and differences of DE microRNAs among them. Besides, the data revealed that, through the interaction and regulation of related genes, DE microRNAs participate in related specific biological processes and pathways that may contribute to the effects of these lifestyles. While our findings provide us with an overall vision of microRNAs in the molecular impact of lifestyles on health, further studies are required to decipher the underlying molecular mechanisms of these DE microRNAs.This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The protocol was approved by the Biomedical Ethics Committee of Beijing Hospital and Beijing Institute of Geriatrics, Beijing, China. Staff veterinarians monitored mice on a regular basis, finding no pathogens. All efforts were made to minimize suffering.n = 7 in each group): ad libitum, normal-fat diet group (AL); ad libitum, high-fat diet group (HF) [Male C57BL/6 mice were purchased from the Vital River (Charles River China) at two months of age. After a one-week acclimation, all mice were randomly assigned to the following groups and treated for 3 months (oup (HF) , 20; noroup (HF) , 49, 50;oup (HF) , 51. AllLivers were isolated, snap frozen in liquid nitrogen, ground into powder with mortar and pestle in liquid nitrogen and then stored at − 80 °C. Total RNA was isolated from 20 to 30 mg liver using TRIzol® reagent  and RNasey Mini Kit  following the manufacturer’s instructions. The residual DNA was removed by TURBO DNA free kit . Yield and purity of RNA were determined by NanoDrop ND-1000 spectrophotometer . RNA integrity and genomic DNA contamination were tested by denaturing agarose gel electrophoresis.MicroRNA expression levels were assessed using a microRNA microarray (miRCURY LNA™ microRNA Array (v.11.0), Exiqon, Vedbæk, Denmark), based on the method of locked nucleic acid . All chin = 5 in each group). The amplification program was as follows: 95 °C for 10s, 40 cycles at 95 °C for 5 s and 60 °C for 20s, with a final melting curve at 95 °C for 60s, 55 °C for 30s, and 95°Cfor 30s. A U6 snRNA, detected with primers supplied with the kit, was used as an internal control to calculate the relative expression of microRNAs using the 2–ΔΔCt method.Validity of the microRNAs expression array was confirmed by RT-qPCR. A Mir-X microRNA First-Strand Synthesis Kit  was used to synthesize first-strand cDNA according to the manufacturer’s instructions. QPCRs of microRNAs were then conducted in iQ5 Real-Time PCR system  using a Mir-X microRNA qRT-PCR SYBR Kit  (n = 5 in each group). The amplification program was as follows: 95 °C for 30s, 40 cycles at 95 °C for 5 s and 60 °C for 30s. After amplification, a thermal denaturing cycle was added as above. Hmbs was used as an internal control [–ΔΔCt method.Candidate predicted target mRNAs were also confirmed by RT-qPCR. First-strand cDNA was synthesized from total RNA using a 20 μl reverse transcription system . QPCRs were conducted using a TB Green® Premix Ex Taq™ II Kit   were calculated to correct the p value. Only terms with both a p value and an FDR < 0.05 were considered to be significant. Pathway analysis was based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database [2 test to identify significant pathways, and terms with both a p value and an FDR < 0.05 were considered to be significant.The predicted targets of DE microRNAs of each group were separately submitted to DAVID for annotation and enrichment analyses. The main components of annotation in Gene Ontology (GO) mainly provided the cellular locations and biological functions of validated microRNA targets . The GO-database ; similarp < 0.05. GraphPad Prism 6  was used for graph plotting.Data are expressed as group mean ± standard error (SE). SPSS software (version 17.0) was used for statistical analysis. Means of two groups were compared and analyzed using the Student’s t-test. One-way analysis of variance (ANOVA) was used to estimate difference among groups, followed by Tukey’s post-hoc test. Differences were reported as statistically significant when Additional file 1.


We report a case of acute eosinophilic pneumonia (AEP) triggered by coronavirus disease 2019 (COVID‐19) infection. A 77‐year‐old man experienced left‐sided chest pain and shortness of breath. Reverse transcription‐polymerase chain reaction (RT‐PCR) for severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) revealed a positive result, and he was treated with favipiravir, ciclesonide, and lascufloxacin, but he showed poor improvement. On the other hand, computed tomography (CT) images were atypical for COVID‐19 infection, and the elevation of eosinophil was found in blood and the fluid obtained by bronchoscopy. So, we clinically diagnosed this case as AEP. Administration of prednisolone dramatically improved the patient's clinical condition and chest radiograph findings, which were consistent with the clinical course of AEP. This case suggests the importance of considering the complications of AEP when treating patients with COVID‐19 infection. We report a case of acute eosinophilic pneumonia (AEP) triggered by coronavirus disease 2019 (COVID‐19) infection. This case suggests the importance of considering the complications of AEP when treating patients with COVID‐19 infection. Acute eosinophilic pneumonia (AEP) is an acute rare lung disease characterized by respiratory failure and consolidation and diffuse ground‐glass opacities on chest computed tomography (CT). AEP has been described in association with drugs, smoking, and infectious diseases, including viral infections, or otherwise as idiopathic. In this report, we describe the first case of AEP accompanied with coronavirus disease 2019 (COVID‐19), which is caused by the severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2).3/μL , haemoglobin (Hb) 15.2 g/dL, platelets 30 × 104/μL, Na 138 mEq/L, K 4.4 mEq/L, Cl 105 mEq/L, C‐reactive protein (CRP) 5.93 mg/dL, blood urea nitrogen (BUN) 23 mg/dL, creatinine (Cre) 0.80 mg/dL, aspartate aminotransferase (AST) 15 IU/L, alanine aminotransferase (ALT) 11 IU/L, and lactate dehydrogenase (LDH) 149 U/L. These data indicated a typical finding in the early stages of COVID‐19 infection, except that there was a slight elevation in the eosinophil count on admission. Chest CT showed ground‐glass attenuations (GGA) and consolidation  result for SARS‐CoV‐2. On examination, his body temperature was 37.7°C, heart rate was 105 beats/min, and oxygen saturation was 98% (room air). Blood examination showed the following results: white blood cells (WBC) 8.4 × 10After hospitalization, ciclesonide (800 μg/day) and favipiravir, which is one of the antiviral drug, were started with the consent of the patient, as he was relatively old and had respiratory complications. The dose of favipiravir was 3600 mg (1800 mg twice daily (bd)) on day 1, followed by 1600 mg (800 mg bd) from day 2. As shown in Figure As we could not relate the deteriorated radiological changes and the eosinophilia to COVID‐19‐associated pneumonia alone and increased eosinophils were found in fluid obtained by a bronchoscopy Fig. , we clinSeveral COVID‐related complications have been reported till date, and it has been indicated that primarily systemic inflammation and pulmonary complications can lead to significant morbidity and mortality. On the other hand, AEP is one of the pulmonary complications that has not yet been reported, as observed in the present case. The clinical course in this case was slightly different from that of general COVID‐19 cases, suggesting the possibility of AEP. In general, AEP develops with the symptoms of fever, dry cough, dyspnoea, chest pain, and elevation of CRP levels in the blood test. In our case, we clinically diagnosed as AEP based on his clinical symptoms, blood test results, increased eosinophils in fluid obtained by a bronchoscopy, and the improved response to PSL. Although drug‐induced eosinophilic pneumonia (EP) caused due to favipiravir or lascufloxacin should be considered in the differential diagnosis, its possibility can be excluded as there was no radiological improvement and reduction of eosinophil count after stopping the medication. Considering these findings together, we concluded that this case was AEP triggered by COVID‐19 infection.It is well known that EP is caused by viral infection . EosinopImportantly, no eosinophil enrichment into the pulmonary tissue has been observed in samples from patients with COVID‐19 infection during the early stages of disease or in post‐mortem analyses . In our Corticosteroids are not routinely recommended for COVID‐19 treatment and might exacerbate COVID‐19‐associated lung injury. Furthermore, we hypothesize that the use of corticosteroids is associated with sustained detection of SARS‐CoV‐2. Nevertheless, it is necessary to consider steroid treatment in patients with COVID‐19 infection when complicated with AEP or cryptogenic organizing pneumonia.This case suggests that the comorbidity of AEP should also be considered when treating patients with COVID‐19 infection.Appropriate written informed consent was obtained for publication of this case report and accompanying images.


Adjuvant chemotherapy benefits early‐stage breast cancer (BC) patients. Older women receive guideline‐adherent treatment less frequently and experience treatment delays more frequently. We evaluated factors associated with delaying adjuvant chemotherapy and the delays’ survival impact in a large population–based cohort of elderly BC patients.Patients age >66 years diagnosed 2001‐2015 with localized or regional BC were identified in the SEER‐Medicare and Texas Cancer Registry‐Medicare databases. Time from surgery to chemotherapy (TTC) was categorized into four groups: 0‐30, 31‐60, 61‐90, and >90 days. We identified predictors of delays, estimated overall (OS) and BC‐specific (BCSS) survival, and determined the association between TTC and outcome adjusting for other variables.Among 28,968 women (median age 71 years), median TTC was 43 days. 10.7% of patients experienced TTC >90 days. Older age, Black or Hispanic race/ethnicity, unmarried status, more comorbidities, hormone receptor‐positivity, mastectomy, Oncotype DX testing, and full state buy‐in were associated with increased risk of delay. Five‐year OS estimates by TTC group were 0.82, 0.81, 0.80, and 0.74, respectively (p<.001). BCSS demonstrated a similar trend (p<.001). Chemotherapy delay was associated with worse OS  and BCSS . In subgroup analysis, delayed chemotherapy was associated with worse OS and BCSS among patients with hormone receptor–positive , HER2‐positive , and triple‐negative  tumors.Chemotherapy delays are associated with worse survival in older BC patients. Providers should avoid delays and initiate chemotherapy ≤90 days after surgery regardless of patients’ BC subtype or age. We evaluated the factors associated with delays in the initiating adjuvant chemotherapy and the survival impact of delays in a large population‐based cohort of elderly breast cancer patients. We found chemotherapy delays beyond 90 days after surgery negatively affected survival, and delays were associated with clinical and socioeconomic factors. Female patients diagnosed with localized or regional BC from 2001 to 2015 and age ≥66 years at the time of diagnosis were identified. We included patients for whom BC was their first primary cancer and excluded those with a second histology‐confirmed cancer within 12 months of their BC diagnosis. To ensure data completeness, we included only patients who had continuous Medicare Part A & B coverage without health maintenance organization enrollment 12 months before and 12 months after diagnosis. All included patients had a mastectomy or lumpectomy and received adjuvant chemotherapy within 9 months of primary breast surgery. Patients who received neoadjuvant chemotherapy were excluded. The final cohort included 28 968 patients  and breast cancer‐specific survival (BCSS) as the time from date of diagnosis to date of death (for OS) or date of death due to BC (for BCSS), or date of last follow‐up. Patients who did not die or did not die due to breast cancer‐specific cause (for BCSS) were censored at the last follow‐up time. The last follow‐up date for OS was 31 December 2017 using the date of death documented by Medicare. However, since the cause of death was obtained from SEER, the last follow‐up date for BCSS was 31 December 2015.Clinical and demographic variables including region, year and age of diagnosis, race, marital status, stage, state buy‐in (as a proxy for poverty), and level of education were extracted from the SEER or TCR patient enrollment file. We estimated the percentage of non‐high school education based on 2000 census tract. We used physician, inpatient, and outpatient claims in the 12 months before diagnosis to calculate Charlson Comorbidity Index score.2.2Descriptive statistics were used; we used the Chi‐square test to compare categorical variables. Multivariable logistic regression model was used to identify predictors of delayed chemotherapy. Variables in the model included: year of diagnosis, age at diagnosis, race, marital status, Charlson comorbidity index, tumor size, lymph node status, grade, hormone receptor status, type of surgery, Oncotype DX test, administration of radiation therapy prior to chemotherapy, state buy‐in, residence, and education. In addition, we included emergency room visits/hospitalization/surgical complication between date of surgery and first chemotherapy claim as an additional variable.We calculated and plotted the five‐year OS and BCSS estimates using the Kaplan‐Meier product‐limit method and Cox proportional hazards models were used to determine the association of delayed chemotherapy with OS and BCSS, adjusting for the previously mentioned covariates. We included emergency room visits/hospitalization/surgical complication as a time‐varying covariate in the model. We expressed results in hazard ratios (HR) and 95% CIs. We adjusted for potential selection bias by the inverse probability treatment weighted (IPTW) method. To obtain the probability of patients falling in each of the three TTC groups, we implemented three separate logistic regression models using TTC 0‐30 days as the reference group. We obtained propensity scores (PS) for each model and defined the IPTW weights as PS/(1‐PS) for patients in each of the three groups , assigning patients initiating chemotherapy in 0‐30 days a weight of 1.P < .05 statistically significant. We used SAS version 9.4 (SAS Institute), and R version 3.5.1. We received Institutional Review Board exception based on the code of regulations.We evaluated the association between TTC and survival outcomes within subgroups stratified by hormone receptor status and stage. In addition, we performed a subgroup analysis among patients diagnosed from 2010 to 2015 in whom information on HER2 status was available. We evaluated the association of chemotherapy delays and survival outcomes stratified by BC subtype. We considered 3P < .001); 3102 (10.7%) patients overall delayed chemotherapy. Before weighting, all variables across the different TTC groups were significantly different (P < .001). After IPTW adjustment, greater balances were achieved, with standardized difference <10%.In total, 28 968 women were included. Table 3.1Factors statistically associated with delayed TTC included older age , Black  or Hispanic race , higher comorbidity score , positive hormone receptor status , mastectomy with immediate reconstruction , having Oncotype DX testing or radiation before chemotherapy , and full state buy‐in . Patients experiencing surgical complications or having emergency room visits/hospitalizations after surgery had and increased risk TTC delay . The full multivariable model is shown in Table 3.2P < .001)  . 5‐year BCSS estimates were 89%, 88%, 86%, and 81%, respectively (P < .001).Median follow‐up time was 6.2 years (range 0.1‐17 years) for OS and 5.3 years (range 0.1‐15 years) for BCSS. Overall, there were 10 425 total deaths, and 3582 of them were BC‐related. The weighted 5‐year OS and BCSS estimates for the entire cohort were 79% and 88%, respectively. On univariate log‐rank analysis, the weighted 5‐year OS estimates were 82%, 81%, 80%, and 74% for TTC 0‐30, 31‐60, 61‐90, and >90 days, respectively  Figure . The 5‐y) Figure . To furtIn multivariable Cox proportional hazards model analysis, after weighting and covariate adjustment Table , patient4Our study demonstrates in a large and representative cohort of BC patients that delaying TTC in older women is associated with statistically significant worse OS and BCSS. The association between TTC and survival was evident across all BC subtypes irrespective of extent of disease. Our findings are crucially important since women aged ≥65 comprised approximately 59% of all new BC cases in 2019.Suboptimal treatment among older patients has important implications in cancer outcomes. BC mortality decreased from 1975‐2000While we observed adverse outcomes among all BC subtypes, our study suggests that the impact of TTC on survival is greater among women with hormone receptor‐negative and HER2‐positive disease, compared those with hormone receptor‐positive disease. TNBC and HER2‐positive BC have a more aggressive biology.Our group reported an association between TTC and survival in a prior study using data from the CCRIn this study, we were able to identify demographic and clinical factors associated with delayed TTC. Patients with hormone receptor‐negative tumors were less likely to experience TTC delays compared with hormone receptor‐positive patients, it is possible that there was likely a greater sense of urgency among providers to initiate chemotherapy in patients with these tumor types given their more aggressive behavior. We also observed that patients whose tumors were sent for Oncotype DX testing and who received adjuvant radiation before chemotherapy were more likely to experience delays. Given the worse survival outcomes associated with adjuvant chemotherapy delays, providers should engage proactively other members of their patients’ multidisciplinary care teams to coordinate diagnostics and treatment modalities efficiently. It is possible that delays with increasing age are associated with concerns about older patients’ ability to tolerate chemotherapy without significant adverse events.This is the largest study evaluating the impact of TTC among older BC patients. We provide clear evidence that timely chemotherapy administration is crucial and delays are associated with worse OS and BCSS regardless of BC subtype. Our observations are strengthened by the large number of patients, long follow‐up time, and use of the IPTW method to adjust for potential selection bias. Our study, however, is limited by its retrospective nature. Despite the methodological limitations inherent to claims‐based research, observational studies are of clinical value and they provide real‐life data that is generalizable allowing identification of patters of care and areas where cancer care delivery can be improved. Given the study design limitations and ethical considerations associated to the evaluation of treatment delays, observational studies from real word data might be the only way to examine the impact of delayed chemotherapy on survival.Our study is limited by the variables available in the databases. We could not account for delays in diagnosis, delays in initiating adjuvant endocrine therapy or distance from patient's home to the nearest hospital. Additionally, BCSS information could be inaccurate due to misclassification of cause of death in the SEER‐Medicare and TCR‐Medicare databases. Oncotype DX results for those who had testing was not available. This information would have allowed us to stratify further hormone receptor‐positive and HER2‐negative patients to determine if the survival effect of TTC was more pronounced among patients with high recurrence scores. Furthermore, it is possible that longer follow‐up would reveal that TTC delays has a more pronounced survival impact in patients with hormone receptor‐positive BC where recurrence risk tends follow a longer course compared to HER2‐positive BC and TNBC.Another limitation is the exclusion of a significant proportion of patients because they were enrolled in HMO. Previous studies have shown a correlation between insurance type and TTC, and it is not something we were able to fully assess. However, we believe that our study is still fairly representation of the older adult population given the inclusion of patients enrolled in Medicare, which provides medical care for the vast majority of older Americans.In conclusion, our study adds to the body of evidence and confirms that delayed TTC is associated with worse survival among BC patients >65. Decreased OS was also seen with TTC > 60 days in patients with regional disease and those with HER2‐positive or TNBC. This data should encourage providers to take appropriate steps to ensure timely initiation of chemotherapy. In addition to medical factors and age, we found that socioeconomic factors such as race and marital status were associated with delays in care. Future studies should attempt to determine the reasons such disparities exist in order to develop effective strategies to decrease gaps in cancer care delivery.None.Demetria Smith‐Graziani contributed to investigation, visualization, writing—original draft, writing—review and editing. Xiudong Lei contributed to conceptualization, data curation and formal analysis, investigation, writing—review and editing. Sharon Giordano contributed to conceptualization, funding acquisition, writing—review and editing. Hui Zhao contributed to data curation and formal analysis, investigation, methodology, writing—review and editing. Meghan Karuturi contributed to writing—review and editing. Mariana Chavez‐MacGregor contributed to conceptualization, data curation and formal analysis, funding acquisition, methodology, supervision, writing—original draft, writing—review and editing.Supplementary MaterialClick here for additional data file.


Phase angle (PA), measured by bioelectrical impedance analysis (BIA) has been studied as indicator of nutritional status or muscle function in hemodialysis (HD) patients. It remains unclear if the phase angle is associated protein-energy wasting (PEW) or frailty, which are common complication in hemodialysis patients. The aim of this study is to determine whether BIA-derived PA is a marker of PEW or frailty in HD patients.This retrospective observational study included 116 adult HD patients  in a single dialysis center. Patients were classified according to the PA quartiles into four groups; 1) first quartile: PA < 3.7°, 2) second quartile: PA 3.7–4.1°, 3) third quartile: PA 4.2–4.9°and 4) forth quartile: PA ≥ 5.0°. International Society of Renal Nutrition and Metabolism (ISRNM) criteria and Japanese version of Cardiovascular Health Study (J-CHS) criteria were used to identify PEW and frailty.p = 0.032), frailty . In multivariate logistic regression analysis, the first quartile group was at a significantly greater risk of both PEW and frailty compared with the fourth quartile group after adjusting for other confounding factors.The lower PA group was associated with a greater risk of PEW (35% vs. 24% vs. 21% vs. 3%; Lower PA was associated with a greater risk of PEW and frailty in HD patients. Protein-energy wasting (PEW), defined as the loss of somatic and circulation body protein and energy reserves, is a common complication among hemodialysis (HD) patients . FrailtyBioimpedance electrical analysis (BIA) is a noninvasive, safe and quick methods, and validated assessment of hydration status and body composition. The clinical use of BIA in HD patients is currently increasingly used in dry weight and nutritional status management. Phase angle (PA) measured by BIA reflects the resistance and reaction of the body in response to the application of an external current. PA is the most clinically relevant impedance parameter, an index of cell membrane integrity and vitality. Phase angle is a direct measure of BIA and therefore not influenced by assumptions that can affect body composition or hydration assessments. A lower PA level indicates decreased cell integrity or cell death, whereas higher PA suggests large quantities of intact cell membranes . MoreoveThe present study included 116 adult HD patients  from a single unit of the Meisei-kai Toyo Clinic Yachimata, Chiba, Japan between January 2018 and March 2018. Patients were eligible to participate if they were over 18 years of age, had received maintenance HD at least 3 times per week for more than 6 months, and had no contraindications for BIA including patients with pacemakers or were not limbless. The exclusion criteria of present study were comorbidities active malignancy and recent hospital admission within 3 months that might influence nutritional or functional status. Study collaborators interviewed patients before or during a HD session, obtained recent clinical and laboratory data from medical records, and measured muscle strength and physical performance prior to the start of the HD session. In addition, study collaborators measured the body composition using a BIA after a midweek dialysis session.Cardiovascular (CV) risk score was calculated using new risk model developed by Japan Dialysis Outcomes and Practice Patterns Study (J-DOPPS) . This CV2 or unintentional weight loss (5% over 3 months or 10% over 6 months); sCr/BSA, 380 μmol/L/m2; and nPNA, 0.8 g/kg per day. The diagnosis of PEW was defined at least 3 of the 4 listed categories.International Society of Renal Nutrition and Metabolism (ISRNM) recommended the diagnosis of PEW . PEW invFrailty was evaluated based on the Japanese version of Cardiovascular Health Study (J-CHS) criteria consisting of 5 components: weight loss, exhaustion, low physical activity, slowness and weakness . (1) WeiBIA measurements was performed by seca mBCA515 , which is a multifrequency bioimpedance device. The 8-electrode texhniqu enables segmental impedance measurement of the arm and legs. All the patients were in a standing position. The PA was calculated using the following equation:π)), is related to body cell mass and soft tissue composition.PA(degree) = arctan(Xc/R) × , and the patients were classified in four groups: first quartile group (PA < 3.7°), second quartile group (3.7 ≤ PA < 4.2°), third quartile group (4.2 ≤ PA < 5.0°), and fourth quartile group (PA ≥ 5.0°).To examine the PA values adjusting for age, sex, and body mass index, the PA values were converted into s.d. score by the following equation:Standard deviation score(SDS) = (X – average X)/s. d.Where X is the observed value, average X is the mean of the normal value at the respective age, sex, and body mass index, and s.d. is the standard deviation from the mean. BIA-derived body components such as extracellular water (ECW) , total bp < 0.05 was considered statistically significant.Continuous variables are expressed at mean ± standard deviation and as counts and percentages as appropriate. For the comparison of continuous variables among PA groups, one-way analysis of variance was used, and for categorical variables, the Pearson chi-square test was performed. To adjust for effects due to potential confounders for PA, multivariate logistic regression models of PEW, and frailty were performed, and odds ratios (ORs) and 95% confidence intervals (95% CI) were determined. The PA ≥ 5.0° (fourth quartile group) was considered the reference for this analysis. In the analysis for the CV event risk, we compared the CV event risk model score among PA groups using Kruskal-Wallis test. Statistical analyses were performed using SPSS software, version 21, and in all statistical calculations, a two-tailed The average age of HD patients in the analysis was 64 ± 12 years; 35% of patients were female; dialysis vintage was 7 ± 6 years; PA score was 4.3 ± 1.1°, and PA SDS was − 1.1 ± 1.8; 65% of the patients had PA SDS < − 1 s.d., and 17% had PA SDS between − 1 and 0 s.d and 18% had PA SDS > 0 s.d..p = 0.032). Moreover, the prevalence of frailty was 59% in the first quartile group, 40% in the second quartile group, 21% in the third quartile group, and 3% in the fourth quartile group (p < 0.001). The remaining clinical variables were not significantly different among PA groups. We evaluated the prediction accuracy of several variables measured by BIA. The area under the curve (AUC) value of a PA is large in predicting frailty and PEW compared with other values measured by BIA  and second quartile group  were at significantly greater risk of PEW compared with fourth quartile group. Moreover, multivariate logistic regression analysis showed that first quartile group remained a predictor of PEW after adjusting for other confounding factors, compared to the fourth quartile group .Table p = 0.001) and the second quartile group  were at a significantly greater risk of frailty compared with the 4th quartile group. In multivariate analysis, the first quartile group  and the second quartile group  remained predictors of frailty after adjusting for age, sex, and HD vintage compared with fourth quartile group (model 2). Similarly, the first quartile group  was significantly associated with frailty after adjusting for age, sex, HD vintage, diabetes mellitus, hemoglobin level, grip strength than the fourth quartile group (model 3).Table p = 0.004 and p < 0.001).Figure PEW and frailty are common complication associated with functional decline, and worse prognosis in HD patients , 10, 11.The biological meaning of the PA remains uncertain; however, it seems to reflect body cell mass, or cell membrane function . IncreasFew studies have evaluated the association between PA and mortality or CV event in HD patients. More recently, Bansal et al. and Segall et al. demonstrated that PA was significantly associated with mortality in CKD patients  and HD pThus, we propose that regular screening would be essential to monitor the progression of PEW or frailty over time, and to avoid the development of the vicious cycle of PEW or frailty. Regular screening may help in the early identification of patients accompanied by PEW or frailty when they are the most treatable as well as provide prognostic information. We therefore suggest that PA could be a useful, simple indicator to predict PEW, frailty, and CV event risk among HD patients.Several limitations of our present study should be noted. First, our findings are limited to a relatively small number of patients at a single HD center, though most of the results are comparable to those from prior clinical studies. We have done sample size power calculation, a sample size of 122 patients was chosen based on the recommended method . Thus, our sample size is modest; further large number of studies are therefore needed in the future. Second, it has suggested that PEW is cachexia and should be termed kidney disease cachexia as a continuum with PEW first followed by cachexia. Our findings are limited to a small number of patients with severe PEW or kidney disease cachexia, therefore we could not assess the relationship between phase angle and severity of PEW including kidney disease cachexia. Future research needs to evaluate the diagnostic, prognostic, and predictive accuracy of phase angle on severe PEW or kidney disease cachexia status.PA could be a useful, simple indicator to predict PEW and frailty among HD patients. Lower PA was associated with a greater risk of PEW and frailty in hemodialysis patients.


Fluid overload is a risk factor for morbidity, mortality, and prolonged ventilation time after surgery. Patients on maintenance hemodialysis might be at higher risk. We hypothesized that fluid accumulation would be directly associated with extended ventilation time in patients on hemodialysis, as compared to patients with chronic kidney disease not on dialysis (CKD3–4) and patients with normal renal function (reference group).This is a prospective observational study that included patients submitted to isolated and elective coronary artery bypass surgery, divided in 3 groups according to time on mechanical ventilation: < 24 h, 24-48 h and > 48 h. The same observer followed patients daily from the surgery to the hospital discharge. Cumulative fluid balance was defined as the sum of daily fluid balance over the first 5 days following surgery.Patients requiring more than 48 h of ventilation (5.3%) had a lower estimated glomerular filtration rate, were more likely to be on maintenance dialysis, had longer anesthesia time, needed higher dobutamine and noradrenaline infusion following surgery, and had longer hospitalization stay. Multivariate analysis revealed that the fluid accumulation, scores of sequential organ failure assessment in the day following surgery, and the renal function  were independently associated with time in mechanical ventilation. Among patients on hemodialysis, the time from the surgery to the first hemodialysis session also accounted for the time on mechanical ventilation.Fluid accumulation is an important risk factor for lengthening mechanical ventilation, particularly in patients on hemodialysis. Future studies are warranted to address the ideal timing for initiating dialysis in this scenario in an attempt to reduce fluid accumulation and avoid prolonged ventilation time and hospital stay. Coronary artery bypass grafting (CABG) is indicated as a treatment of ischemic heart disease for patients with chronic kidney disease  (CKD), aHemodynamic instability after cardiovascular surgery is a situation often managed with fluid administration. However, establishing goals of volume management in patients with renal failure on maintenance hemodialysis is challenging. Since these patients are usually anuric, fluid accumulation is not uncommon. The association between positive fluid balance and deleterious effects on lung function and prolonged mechanical ventilation has been described , 8. IndeAnuria and the high prevalence of comorbidities such as hypertension, diabetes and advanced age increase the odds of a positive fluid balance, and PMV in these patients . The goaPatients were recruited at the Instituto do Coração (InCor), Universidade de São Paulo. Inclusion criteria were as follow: consecutive adult patients submitted to an elective CABG in the period between July 2015 and March 2017. Flow diagram for patient inclusion and exclusion is shown in a supplementary file .Clinical, biochemical and demographic data were prospectively collected from charts including age, gender, weight, presence of diabetes, and serum creatinine. Postoperative data collected included: aortic cross-clamping time (min), cardiopulmonary bypass time (min), surgery time (min), use of intra-aortic balloon pump (% of patients), anesthesia time (min), ventilation time , sequential organ failure assessment - SOFA (scores) and use of dobutamine and noradrenaline.Renal function was expressed as estimated glomerular filtration rate (eGFR), calculated by the Chronic Kidney Disease Epidemiology - CKD-EPI 2009 equation . PatientThe same observer followed each patient daily from the surgery to the hospital discharge. To identify the potential risk of mortality, the SOFA score was applied. In addition, we calculated the same score without taking into account the renal component. Daily fluid balance was calculated during intensive care unit (ICU) as the difference in intakes and outputs, not including insensible losses, taking into account: volume of fluid intake , and losses  .A positive balance defined fluid accumulation. Cumulative fluid balance was defined as the sum of daily fluid over the first 5 days after CABG . Fluid overload (FO) was defined as 10% after adjustment for body weight (FO/body weight) and it was calculated as following: % fluid overload = /admission body weight × 100), expressed as percentage .p < 0.05 to enter and p > 0.1 to remove in the group of patients on hemodialysis to test age, SOFA scores without the renal component, and the accumulated fluid balance . Analyses were performed with the use of SPSS 22.0  and GraphPad® Prism 8.0 . Two-sided P values < 0.05 were considered statistically significant.Continuous data are expressed as mean ± standard deviation (SD) or median , whereas categorical data are expressed as frequencies and percentages. Comparison among the 3 groups was done by ANOVA  or Kruskall-Wallis . Categorical data were compared by Fisher’s exact test or chi-squared, as appropriate. Relationships between single variables were examined by Spearman. Multivariate regression analyses were used to assess factors associated with ventilation time and independent variables were selected from univariate analysis. We also performed a stepwise linear regression, with In the study population, 77.3% of patients did not require ventilation for more than 24 h, while 17.4 and 5.3% were on mechanical ventilation 24–48 h and > 48 h, respectively. Baseline characteristics of patients according to time on mechanical ventilation are shown in Table p = 0.045) and SOFA scores upon admission (p = 0.035) than those from the same group that did not required dialysis.Five patients  developed an impairment of renal function and required dialysis during hospitalization. These patients were characterized by higher serum creatinine , as shown in Fig. p = 0.0001).We found than only 10 patients presented FO (> 10%). FO was found in 4 (1.8%), 2 (4.1%) and 4 (26.7%) patients on mechanical ventilation for < 24 h, 24–48 and > 48 h, respectively , SOFA at admission  and on the first day after surgery with and without the renal component , hospitalization time  and ICU stay . There was no significant association between time on mechanical ventilation and pneumonia (p = 0.389), diabetes (p = 0.453), hypertension (p = 0.752), dyslipidemia (p = 0.373), obesity (p = 0.624), history of previous cardiac surgery (p = 0.464), ischemic cardiomyopathy (p = 0.718), history of previous myocardium infarction (p = 0.874), history of cancer (p = 0.372), urinary infection (p = 0.843), and operative site infection (p = 0.105).Ventilation time correlated with eGFR (p = 0.011), group of patients (p = 0.039), and the SOFA on the first day after surgery (p = 0.0001), in a model adjusted for anesthesia time, noradrenaline and dobutamine dosage  that together accounted for 52.4% in the variability of the time on mechanical ventilation  we could not adjust for acute renal failure that occurred in the CKD3–4 group, and finally, due to the study design we were not able to access if early dialysis initiation would short the time on mechanical ventilation. The strength of our study was its prospective design and the daily follow-up by the same observer.This study is subject to some limitations: first, the acid-base equilibrium was not analyzed; second, the moment to initiate dialysis was dependent on the physician in charge; third, the daily weight was not available; fourth, due to a limited sample size (Our findings suggest that prolonged ventilation time in patients on maintenance hemodialysis might be directly dependent on the fluid overload and the time spent until the first hemodialysis session.


Widespread use of angiotensin receptor blocker and neprilysin inhibitor (ARNI) remains low, and many patients are unable to tolerate the medication due to hypotension at the currently recommended starting dose.The aim of this study is to assess if lower than standard doses of ARNI, sacubitril/valsartan (S/V), significantly reduces NT‐proBNP and leads to any change in diuretic dose, serum potassium, or creatinine.n = 10): very low dose S/V , Group 2 (n = 10): very low dose titrated to low dose S/V, and Group 3 (n = 25): low dose S/V (24/26 mg BID). NT‐proBNP, diuretic dose, serum potassium, and creatinine were compared before and after initiation of S/V.In a retrospective study of 278 patients who were started on a low dose S/V at a single medical center, 45 patients were selected for the study cohort. Patients were subcategorized to Group 1 . In addition, there was a significant reduction in diuretic dose across all groups combined , with 17.8% (8/45) patients being able to discontinue their diuretic completely. There was no significant change in potassium or creatinine.Lower than standard dose of S/V significantly reduces NT‐proBNP and diuretic requirement without change in potassium or creatinine, which provides hope that patients who cannot tolerate standard doses of S/V due to hypotension may be able to receive the benefits of S/V therapy. Its influence is far reaching, affecting patient morbidity and mortality as well as overall healthcare costs. It is estimated that over 6.5 million adults suffer from HF in the United States and nearly 40 million adults affected worldwide.In the PARADIGM‐HF trial, a 20% reduction in cardiovascular death or hospitalization for HF in the PARADIGM‐HF led to the approval of S/V from the US Food and Drug Administration (FDA) as well as the European Commission in July 2015 and November 2015, respectively.22.1Using a retrospective observational analysis at a single medical center, NT‐proBNP levels were compared before and during S/V therapy, as a surrogate indicator for S/V therapy efficacy. Electronic medical record (EMR) data were queried for patients on S/V therapy between October 2015 and January 2018. Data were collected from EMR, Medicare Severity Diagnosis Related Groups (MS‐DRG) and IBM COGNOS, v.10 . All patients starting S/V at either very low dose  (VLDS/V), or low dose (24/26 mg tablet BID) (LDS/V) were included. Patients were excluded if there were no NT‐proBNPs obtained before or after implementation of S/V therapy, or if patients were lost to follow up in clinic. Patients were divided into three groups based on S/V dosing. Group 1 patients received VLDS/V throughout the evaluation period, Group 2 patients received VLDS/V and were titrated to LDS/V, and Group 3 patients received LDS/V throughout the evaluation period. Patients were evaluated for a minimum of 2 weeks, with no maximum monitoring periods stipulated. The study protocol received an approval of the Scripps Clinic Institutional Review Board.2.2Primary endpoint was the mean change in NT‐proBNP values between the baseline and last value at a follow‐up. Baseline NT‐proBNP values were obtained within 30 days prior to the S/V therapy initiation. Duration of therapy referred to the time between initiation of S/V and a follow‐up serial NT‐proBNP level. The secondary endpoints included mean changes in loop diuretic dose, serum potassium, and creatinine. Loop diuretic doses were converted to furosemide equivalents  for standardization of pharmaceutical therapy, as previously described.2.3All statistical analyses were performed using the Wilcoxon Rank‐Sum test using GraphPad Prism software, Version . Analysis for NT‐proBNP level was performed between the baseline and final assessment after therapy. Difference in diuretic dosing was assessed for statistical significance as well with the Wilcoxon Rank‐Sum test. Significance was assessed by p ≤ .05. All analyses were conducted at the two‐tailed level, and the significance was set at α ≤ .05.3n = 10 (VLDS/V); Group 2, n = 10 (VLDS/V to LDS/V), and Group 3 n = 25 (LDS/V)  Figure . NT‐proB3.2Of the total cohort, 69% 31/45) received a loop diuretic therapy prior to S/V . An average daily dose of loop diuretics decreased significantly after initiation of S/V . Statistical significance was driven by Group 2 and 3 as there was no significant change in daily diuretic dosing in Group 1  (Table 4This study demonstrates an improvement in NT‐proBNP in patients who are unable to tolerate the minimum recommended initiation dose of S/V. Additionally, significant reduction in diuretic dosing after initiation of S/V is observed. Despite rapid Class I recommendation status in the AHA/ACC treatment guidelines, previous studies have shown that only 12% of medical practice patients who were indicated for S/V were receiving therapy.It is not surprising that older patients would either be on LDS/V or not receive the agent at all.NT‐proBNP has proven to be a valuable prognostic biomarker in HF. Zile et al demonstrated that patients with NT‐proBNP levels <1000 in the PARADIGM‐HF study had a significantly better prognosis compared to >1000 and had a similar risk of cardiovascular death or hospitalization as those who started with similar lower NT‐proBNP levels.In addition, patients were able to achieve reduction in diuretic dosing on S/V therapy, with some being able to discontinue all diuretic therapy. Reduction in diuretic therapy may be tied to the natriuresis resulting from increased circulating NP levels.As yet there is minimal data on the efficacy of S/V at doses below the target dose of PARADIGM‐HF. One study reported that patients in PRADIGM‐HF who were down‐titrated to reduced doses of S/V did better than those on reduced doses of enalapril, although the reduction was from high dose to moderate dose S/V therapy.Our study has several limitations especially since it is a small single‐center, retrospective study and clinical outcomes were not assessed. The purpose of the study was to determine if initiation and continuation of lower than recommended doses of S/V produced a salutary effect on NT‐proBNP in a cohort with low systemic blood pressure.5S/V is a hallmark therapy that reduces mortality and morbidity in HFrEF patients as evidenced in PARADIGM‐HF trial. Usage of S/V in clinical practice remains low, in part limited by hypotension. This study supports the concept that patients who may not have received S/V due to low blood pressure can tolerate VLDS/V and LDS/V, which results in a significant reduction of NT‐proBNP without any significant change in serum potassium or creatinine. Moreover, in patients who were able to tolerate LDS/V, there was a significant decrease in their diuretic dose and some were able to stop their diuretic completely. While our study demonstrates a significant biomarker response to lower than standard dose of S/V, further investigation is needed to confirm clinical benefit with non‐target doses of S/V.Amitabh C. Pandey, Derek Jer, Ruth S. Kuo, David H. Yoo, Antonio Christophy, Ajay V. Srivastava, Rajeev C. Mohan have no relevant disclosures; James Thomas Heywood—Speaker and consultant of Novartis.


Interstitial lung disease (ILD) in patients with non‐small cell lung cancer (NSCLC) worsens the prognosis for overall survival (OS) due to chemotherapy‐triggered acute exacerbation (AE)‐ILD. The Glasgow Prognostic Score (GPS), which is based on serum C‐reactive protein and albumin levels, has been suggested as a reliable prognostic tool for mortality in cancer patients, including NSCLC. In this study, we investigated whether GPS is a predictor for chemotherapy‐triggered AE‐ILD and the prognosis in patients with NSCLC and pre‐existing ILD.We conducted a retrospective review on 56 NSCLC and ILD patients at our hospital who received platinum agent‐based treatment as first‐line chemotherapy between June 2010 and May 2019. We categorized these patients according to their GPS (0–2) and compared the incidence of chemotherapy‐triggered AE‐ILD and OS.P < 0.05).The GPS 0, 1, and 2 groups included 31, 16, and nine patients, respectively, out of 56. A total of 12 (21.4%) patients showed chemotherapy‐triggered AE‐ILD. The median OS was at 11.5 months . The incidence of chemotherapy‐triggered AE‐ILD within the first year of chemotherapy in the GPS 0, 1, and 2 groups was three (9.6%), four (25.0%), and five (55.5%), and the median OS time was 16.9, 9.8 and 7.6 months, respectively. Univariate and multivariate analyses indicated that only GPS 2 could predict both chemotherapy‐triggered AE‐ILD and OS (GPS assessment of patients with NSCLC and pre‐existing ILD is a valuable prognostic tool for predicting chemotherapy‐triggered AE‐ILD and OS.We found that GPS 2 was an independent risk factor for chemotherapy‐triggered AE‐ILD and prognosis in patients with ILD associated with NSCLC.GPS may potentially enable the discrimination of patients tolerant of chemotherapy from those at an increased risk of AE‐ILD and predict the prognosis in patients with NSCLC and ILD receiving chemotherapy. We assessed GPS and AE‐ILD/prognosis in patients with NSCLC and ILD. Interstitial lung disease (ILD), including idiopathic pulmonary fibrosis (IPF), is concomitant in 10%–30% of patients with lung cancer.A recent meta‐analysis of lung cancer pharmacotherapy showed that ILD has increased the cause of treatment‐related deaths.et al. et al. The inflammation‐based Glasgow Prognostic Score (GPS), is calculated by the C‐reactive protein (CRP) and albumin (Alb) levels and serves as a reliable long‐term prognostic indicator of solid cancers, including lung cancers; a higher GPS score denotes a worse prognosis.The ethical committee of Tokyo Medical University approved this retrospective study protocol  and waived the requirement for informed consent, although patients could choose not to participate. All methods were performed in accordance with relevant guidelines/regulations. We analyzed the medical records of consecutive NSCLC and ILD patients receiving chemotherapy at the Tokyo Medical University Hospital between June 2010 and May 2019. The study excluded concerned patients who did not receive chemotherapy, were transferred to other medical centers before chemotherapy, were diagnosed with cancer accompanied by obstructive pneumonia, or had clinical evidence of infections. Physicians diagnosed the metastasis stage and tumor nodes according to the Tumor, Node, Metastasis classification (eighth edition).The GPS scores of patients were determined the day before initializing first‐line chemotherapy treatment and were based on serum CRP and Alb levels. Patients were classified into one of the three groups based on their GPS designation: GPS 0: CRP ≦10 mg/L and Alb ≧35 g/L; GPS 1: CRP >10 mg/L or Alb <35 g/L; and GPS 2: CRP >10 mg/L; and Alb <35 g/L.Two pulmonologists (R.K and T.T) independently evaluated high‐resolution computed tomography (HRCT) chest images acquired before the administration of first‐line chemotherapy without knowledge of patient outcomes. ILD diagnosis was determined by findings of reticulation shadow, ground‐glass attenuation (GGA), and/or honeycombing in both lung fields. Computer tomography (CT) findings of ILD were categorized into one of two groups according to the recent guidelines for IPFAE‐ILD included all acute respiratory events with newly appearing, bilateral ground‐glass opacification (GGO) and/or interstitial shadows that could not be explained by infectious disease, cardiac failure, or fluid overload.P‐values < 0.05 were considered statistically significant. Statistical analyses were performed using SPSS software version 26.0 .The data were described either as percentages or medians (range). Kruskal–Wallis and chi‐square tests were used for comparison of baseline patient characteristics. Logistic regression univariate and multivariate analyses determined the chemotherapy‐triggered AE‐ILD incidence rate. Independent risk factors for survival were determined by the Cox proportional hazards regression model using univariate and multivariate analyses. A Kaplan–Meier analysis estimated median survival, and a log‐rank test determined patient survival within the GPS groups 0–2. A total of 74 patients with NSCLC and concomitant ILD were admitted to our hospital during the study period. A total of 18 patients were excluded because of secondary ILD of known etiology, lack of measurement of CRP or Alb, not using platinum‐based chemotherapy as first‐line treatment, no chemotherapy, transferring to another hospital before chemotherapy, infectious condition, administering gemcitabine, or using erlotinib. We analyzed data from 56 patients as summarized in Fig Fifty‐six patients diagnosed with NSCLC and pre‐existing ILD were treated with chemotherapy, and their baseline and clinicopathological characteristics are summarized in Table n = 31), GPS 1 (n = 16), and GPS 2 (n = 9) (Table P < 0.05) and neutrophil levels  .A total of 12 of the 56 patients (21.4%) experienced chemotherapy‐triggered AE‐ILD during the study. The incidence of chemotherapy‐triggered AE‐ILD within the first year of chemotherapy were three (9.6%), four (25.0%), and five (55.5%) in the GPS groups of 0, 1, and 2, respectively . A GPS score of 2 was the only predictor that exhibited a significant association with the incidence of chemotherapy‐triggered AE‐ILD, as revealed by multivariate analysis .We determined the risk factors for chemotherapy‐triggered AE‐ILD using univariate and multivariate analyses of each variable Table . UnivariThe chemotherapy regimens are shown in Table P = 0.002)  Fig .P = 0.020); HR of GPS 1: 2.59, 95% CI: 1.17–5.72 (P = 0.018); and HR of GPS 2: 5.27, 95% CI: 2.04–13.58 (P = 0.001). In multivariate analysis, only GPS 1 and GPS 2 were independent prognostic factors for OS in chemotherapy‐receiving NSCLC patients with pre‐existing ILD: HR of GPS 1: 2.34, 95% CI: 1.04–5.26 (P = 0.039) and HR of GPS 2: 4.61, 95% CI: 1.74–12.2 (P = 0.002). Although PS exhibited a trend toward association with OS, the results were not statistically significant .Univariate and multivariate analyses of the relationship between OS and each factor are shown in Table GPS is a proven systemic inflammatory response‐based scoring system, measuring serum CRP and Alb levels.et al. et al. Based on the 2016 International Working Group Report, AE‐IPF is categorized as an acute exacerbation that can be idiopathic or triggered DOC‐triggered AE‐ILD occurred in 32% of the cases, the highest frequency among chemotherapy drugs Table . Althouget al. There is a controversy about the involvement of inflammation in the chronic phase of ILD. In contrast, most reports suggest the involvement of inflammation in the acute phase of ILD.et al.Alb is an indicator of the systemic nutritional status.Our study revealed an inverse relationship between the GPS and median OS rate in patients Fig : as the It has been reported that the following six indicators can help predict the prognosis for patients with IPF: %predicted FVC, %predicted carbon monoxide diffusing capacity (DLCO), pulmonary hypertension, fibrosis score (degree of fibrosis and honeycomb lung in HRCT), modified Medical Research Council (mMRC) scale, and KL‐6.This study has some limitations. First, this was a nonrandomized retrospective study in a small number of patients. Different kind of biases and other confounding factors might be included in this study. However, to date, no large‐scale Phase 3 studies of pharmacotherapy have been conducted in NSCLC patients with ILD. Moreover, previous studies had sample sizes ranging from 21 to 114 patients,To conclude, the GPS is a valuable predictive tool for the risk of chemotherapy‐triggered AE‐ILD and a useful prognostic tool in lung cancer patients with pre‐existing ILD who receive chemotherapy. It is a simple and objective score calculated based on the serum CRP and Alb levels, and validation studies can be readily carried out. A prospective large‐scale multicenter study with a validation cohort is necessary to confirm the validity of our results.The authors declare there are no competing interests.Table S1 Frequency of chemotherapy regimens during the clinical course.Table S2. Incidence of chemotherapy triggered AE‐ILD in each chemotherapy.Table S3. Univariate analysis of overall survival in patients who underwent carbon monoxide diffusing capacity.Click here for additional data file.Figure S1. Patient recruitment flow chart. NSCLC, non‐small cell lung cancer; ILD, interstitial lung disease; GPS, Glasgow Prognostic Score.Click here for additional data file.


Although a high density of CD8+ T cells at the invasive front correlated best with patient survival, CD8 ratio in the mucosa could also predict patient outcome. In conclusion, CD8 and PD‐L1 ratios measured by pathologist‐aided DIA predicted survival more accurately than WSI analyses and ROIs at the invasive front correlated best with patient outcome.Automatic quantification of biomarkers such as tumor‐infiltrating lymphocytes and PD‐L1 is one of the most studied topics in digital pathology image analysis (DIA). However, direct comparison between the DIA of a whole‐slide image (WSI) and that of regions of interest (ROIs) chosen by pathologists has not been performed. In this study, we aimed to compare the prognostic value of tumor microenvironment markers CD8 and PD‐L1, measured by DIA of WSIs and ROIs. We selected 153 primary gastric cancer tissues and stained them with CD8 and PD‐L1. All IHC slides were scanned at ×200 magnification and ratios of CD8 and PD‐L1 were measured in WSIs and ROIs from the invasive front, within the tumor, and the mucosa. Patients with high CD8 and PD‐L1 ratios showed more favorable outcomes compared to those with low ratios. Pathologist‐aided DIA predicted the survival of patients more accurately than WSI analysis (CD8,  The relationship between tumors and their microenvironments has been actively investigated , and immIn addition to predicting prognosis, tumor microenvironment (TME) subtypes based on PD‐L1 status and TILs have emerged as promising biomarkers to predict responses to PD‐1/PD‐L1 pathway blockade . ImmunotDigital image analysis (DIA) is a rising source of big data for machine learning . AutomatIn the present study, we selected ROIs from the invasive front, within the tumor, and the mucosa of 153 gastric adenocarcinomas and compared the results with WSI.We randomly selected 153 patients who underwent gastrectomy for primary GC at the Samsung Medical Center between 2004 and 2008 and whose data had been used for prior studies (IRB no. 2010‐12‐088) , 37. AllIHC staining was performed using Benchmark XT  on representative 3 μm sections of formalin‐fixed paraffin‐embedded GC tissues from 153 patients. Each section was deparaffinized in xylene and incubated with rabbit monoclonal anti‐CD8  using a Ventana BenchMark XT autostainer or pharmDx 22C3 PD‐L1  using a Dako Autostainer Link 48 as previously described .MU), intratumoral (ROIIT), and invasive front (ROIIF) tumor areas for CD8 . For DIA, we analyzed WSIs and ROIs selected by a pathologist (SJB). For the selection of ROIs, tumor‐rich areas were included, and normal tissue, necrotic tissue, and stroma‐rich areas were excluded. For each slide image, the ROI included mucosal . In this study, two clusters (k = 2) was selected, which showed the most significant results.R software (version 3.4.4) was used for the statistical analysis. We used the third quartile value of CD8 ratio, CD3 ratio, and PD‐L1 ratio to divide patients into high‐ and low‐CD8 ratio and PD‐L1 ratio groups , 0.146 (0.011–0.820), 0.128 (0.010–0.828), and 0.077 (0.009–0.698), respectively. The CD8 ratio in WSIs correlated highly with the CD8 ratio in ROIs  and correlated most significantly with invasive front (ROIIF) regions  and with ROIs selected by a pathologist (DIA‐ROI) were available for all 153 GC cases. The total cell counts ranged from 485 123 to 2 934 741 409 395  for whole slide images and from 1091 to 216 246  for ROIs. The results of the measurements are summarized in Table www.r-project.org/) was used to determine the optimal cut‐off points for continuous variables. The third quantile value was chosen for dividing patients into high‐ and low‐CD8 and PD‐L1 ratio groups. After adjusting cut‐off values to the number of cells/mm2 area, the results were as follows: 0.06 for PD‐L1 WSI and 0.15 for PD‐L1 ROI; and 619 for CD8 WSI and 1037 for CD8 ROI. As PD‐L1 had fewer positive cells than did CD8 in the analyzed area, the cut off values were very different.The MaxStat  package of the R programming language  and disease‐free survival (DFS) than the CD8LOW group using DIA‐ROISUM (p = 0.025 in OS and 0.0044 in DFS) and all DIA‐ROI. This difference was most significant in the DIA‐ROIIF data (p = 0.00046 for OS and 0.00013 for DFS)   Figure . Analysi) Figure .HIGH group showed significantly longer OS and DFS using both DIA‐ROI and DIA‐whole data  than for results from DIA‐whole (p = 0.2 for OS and 0.1 for DFS).The PD‐L1a Figure . HoweverIF, ROIIT, and ROIMU) and PD‐L1 ROI, we clustered two patient groups using the k‐means clustering method. [p = 0.0073 for OS and 0.0019 for DFS) , were available in 196 GC cases from the Asian Cancer Research Group (ACRG) study cohort  and the HIGH group showed significantly longer OS and DFS than the CD8LOW group using DIA‐ROISUM (p = 0.004 for OS and 0.0067 for DFS) and all DIA‐ROI. This difference was most significant in the DIA‐ROIIF data (p = 0.0036 for OS and 0.004 for DFS). However, there were no differences between the CD3HIGH and CD3LOW groups.The CD8k‐means clustering method to test classification using CD3 ROIs  and CD8 ROIs . The cluster 2 group had significantly longer OS and DFS than the cluster 1 group (p = 0.0053 for OS and 0.0222 for DFS)  and DFS  than ROISUM, ROIMU, or ROIIT  and DFS   and DFS .The CD8 ratio and PD‐L1 in DIA‐ROI, EBV positive and TNM stages were all independent prognostic factors predicting patient outcomes in the univariate analysis and HR forest plot Table . For the9) Table . For mulDIA is a new source of big data for machine learning in medicine . Howeveret al. [IF, CD3 IT, CD8 IF, CD45RO IT, and CD66b IF data from 879 consecutive patients. They showed clinical significance of the immune cells, but their prediction model requires manual interpretation by two pathologists with at least 89% agreement, five representative areas, and five IHC procedures. The abundance of immune and other cells in the TME has been estimated by computational methods using gene expression data [in silico immune context is critical for successful immunotherapy. Therefore, we tried to classify the TME in GCs to better understand tumor–immune interactions and facilitate patient selection for future immunotherapy using CD8+ T cells and PD‐L1 that are currently measured using manual interpretation by pathologists [The relationship between a tumor and its TME is critical for tumor growth and metastasis and has therefore been actively investigated . The cliet al.  developeion data , 47. Howologists  and compologists . We usedologists , 49. Altet al. [p = 0.01). In colorectal cancer, Nosho et al. [p = 0.007). The density of CD8+ TILs in non‐small cell lung cancer (NSCLC) has also been studied as a promising prognostic tool. A study with 797 NSCLC patients using four different cohorts from Norway and Denmark [p < 0.001). A recent study addressing the role of CD8 in predicting response to nivolumab showed significantly longer progression‐free survival (p = 0.0002) while PD‐L1 expression was not associated with survival benefits [The prognostic role of CD8+ TILs has been actively investigated in many tumor types. Piras et al.  evaluateo et al.  utilized Denmark  scored tbenefits . Moreovebenefits .IF was the most significant factor for predicting longer OS and DFS. In addition, we are the first to identify that ROIMU could also be a good immunomarker to predict patient outcomes.Recent studies on GC have shown that the high density of CD8+ T cells at the tumor invasive margin correlates highly with patient survival , 42. GivWith this direct comparison study on gastric adenocarcinomas, the prediction of prognosis was superior in DIA‐ROI than in DIA‐whole. This result is attributable to enriched tumor cells, so the diluting effects of normal tissue, necrotic tissue, and stromal cells are diminished, and thus this result provides more useful information about the disease state. Moreover, we found that confining the image analysis region from WSI to ROI creates an accurate and computationally viable method for tissue image analysis. Based on these observations, we could prove that pathologists with the knowledge of biology, histology, pathology, pathophysiology, biomarker expression, and comparative anatomy play an important role in the era of DIA and artificial intelligence (AI).The present study has several limitations. Although we validated the results of CD8 analysis in different cohorts from the same institute, we could not validate our results in patients with gastric cancer at other centers. Moreover, during the measurement of WSI, we did not filter the morphological or technical artefacts (bubbles or folded tissue), or parts of the normal tissue such as normal gastric mucosa or lymphoid follicles, which interfere with the results. Although DIA provided accurate and reproducible quantitative data, different analytic methods, and selection of variable ROIs, would affect the cutoff values and alter the clinical significance.IF was the most significant factor to predict prognosis, ROIMU also predicts patient outcomes.In conclusion, DIA‐ROI was superior to DIA‐whole and although ROIYJH, TL, SYK, SYH and K‐MK designed the study. S‐JB selected ROIs for digital analysis. EJK scanned slides. HCS and BK selected patients and collected clinical information. YJH performed digital pathology analysis and statistical analysis. YJH, TL and K‐MK wrote the manuscript. All the authors interpreted and discussed the results and provided critical comments to the manuscript.Figure S1. Correlation between whole slide images (WSIs) and regions of interest (ROIs)Figure S2. Kaplan–Meier survival curves for the PD‐L1 and CD8 ratiosFigure S3. Kaplan–Meier survival curves for the CD3 and CD8 ratios from the ACRG cohortFigure S4. Forest plot of the Cox proportional hazard modelTable S1. Patient demographics used for this studyTable S2. Association of CD3+ and CD8+ T cells with clinicopathologic features in the ACRG cohortClick here for additional data file.


To determine the prognostic risk factors of patients with hepatitis B virus related acute‐on‐chronic liver failure (HBV‐ACLF) treated with plasma exchange (PE)‐based artificial liver support system (ALSS), and create a prognostic predictive model.A total of 304 HBV‐ACLF patients who received PE‐based ALSS were retrospectively analyzed. Potential prognostic factors on admission associated with survival were investigated. Of note, 101 additional patients were analyzed to validate the performance of the prognostic models.According to 28‐day survival, a total of 207 patients who survived and 97 non‐survivors were identified in the derivation group. Overall, 268 (88.2%) ACLF cases were caused by reactivation of HBV. Cox proportional hazards regression model revealed that age, total bilirubin, ln , encephalopathy (HE) score, sodium level, and international normalized ratio (INR) were independent risk factors of short‐term prognosis. We built a model named ALSS‐prognosis model (APM) to predict the 28‐day survival of HBV‐ACLF patients with ALSS; the model APM showed potentially better predictive performance for both the derivation and validation groups than MELD, MELD‐Na, and CLIF‐C ACLF score.Low AFP was found to be an independent risk factor for high mortality in HBV‐ACLF patients treated with PE‐based ALSS. We generated a new model containing AFP, namely APM, which showed potentially better prediction performance than MELD, MELD‐Na, and CLIF‐C ACLF score for short‐term outcomes, and could aid physicians in making optimal therapeutic decisions. Various prognostic models including the Model for End‐stage Liver Disease (MELD),In the present study, we investigated the prognosis, and factors affecting prognosis, in patients with HBV‐ACLF treated using PE‐based ALSS. Furthermore, we propose a novel model that could predict prognosis in these patients.22.1Liver failure patients who received ALSS at our hospital between January 2015 and July 2017 were identified retrospectively. The operating guide for ALSSs was strictly applied to identify patients for ALSS treatment.In the derivation group, a total of 628 patients with chronic hepatitis B (CHB),Additional 101 patients were enrolled in the validation group between August 2017 and December 2017 from First Affiliated Hospital of Zhejiang University and Shulan (Hangzhou) Hospital; all of them met the aforementioned inclusion and exclusion criteria.2.2As proposed by the Asian Pacific Association for the Study of the Liver,Assessment of different prognostic models was performed according to different criteria and researches.2.3The baseline characteristics recorded consisted of encephalopathy score , plus laboratory parameters including alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TB), albumin, ferritin, alpha‐fetoprotein (AFP), sodium, glucose, creatinine, international normalized ratio (INR), and white blood cell (WBC), hemoglobin, and platelet counts. Furthermore, calculation of MELD, MELD‐Na, CLIF‐C ACLF, and COSSH‐ACLF scores was performed.2.4Circulatory access was established via the patients' femoral vein and PE was performed using the EC‐40W membrane separation method . The total exchange volume was 2500 to 3500 mL, which composed 1500 to 2500 mL of fresh frozen plasma (FFP) and 500 to 1000 mL of 5% albumin. FFP was provided by the local Blood Transfusion Service, which was obtained by voluntary blood donation. The PE rate was set to 20 to 25 mL/min with an adjusted blood flow rate of 100 to 130 mL/min. Five milligram of dexamethasone was injected routinely to prevent allergic reactions. Based on the prothrombin time prior to PE, approximately 20 to 60 mg of heparin and 10 to 30 mg of protamine sulfate were administered every session. PE‐centered ALSS included the utilization of PE alone or in combination with hemofiltration (HF) or plasma perfusion (PP). HF was performed following PE, which used a BLS816G column  at a filtrate flow rate of 50 mL/kg/h for 6 to 8 hours. PP was performed using EC‐40W for plasma separation and two adsorption columns  for toxin removal. The methods were performed according to patient condition. HF is suitable for encephalopathy, acute kidney injury, and water‐electrolyte imbalance. Bilirubin adsorption is utilized for hyperbilirubinemia with mild coagulation dysfunction (INR <2). ALSS treatment was performed every 2 to 3 times per week and was discontinued if bleeding or circulatory complications occurred.l‐ornithine aspartate; fluid replacement was applied in patients with low mean arterial pressure and/or vasoconstrictors in those with circulatory dysfunction; and persistent low‐flow oxygen therapy (2‐4 L/min) was administered to patients with a PaO2 < 80 mm Hg, with mechanical ventilation provided when severe respiratory dysfunction occurred.All patients received standard medical therapy (SMT), including bed rest, adequate nutritional support, and oral antiviral drugs. Complications were also treated, as follows: ascites were treated with sodium and water restriction and/or diuretics, and peritoneocentesis combined with intravenous albumin when necessary; broad‐spectrum antibiotics were given initially to patients with bacterial infections and later modified based on culture and/or antibiotic sensitivity results; acute GI bleeding was treated with intravenous somatostatin, pituitrin, proton pump inhibitors, and endoscopic therapy when needed; HE patients received lactulose and 2.5t test, Mann‐Whitney U test, or Wilcoxon rank‐sum test, and categorical variables by χ2 test. Survival rates were estimated by Kaplan‐Meier analysis and compared by the log‐rank test. Patients who received LT were censored at the time of survival analysis. Potential predictors of prognosis were identified by univariate and multivariate analysis using the Cox proportional hazards regression model. Multivariate logistic regression was used to establish the new model and the performance of the prognostic scores was assessed by comparison of receiver operating characteristic (ROC) curves using the z test (Delong's method). A P value <.05 was considered statistically significant.All data were analyzed using the SPSS software . Continuous variables were expressed as the mean ± SD or median  and were compared using Student's 33.1Table P < .0001), number of HBeAb positive patients (P = .005), presence of GI bleeding (P < .0001), bacterial infection (P = .007), and level of ALP (P = .015) were significantly higher in the derivation group than in the validation group. Meanwhile, the number of patients presented with HE (<.0001), the MELD (P = .006), MELD‐Na score (P = .009) and COSSH‐ACLF score (P = .049), albumin level (P = .011), and INR value (P < .0001) were significantly less in the derivation group compared to the validation group.The age (3.2P < .0001), had substantially lower levels of TB (P < .001), INR (P < .001), D‐dimer (P < .001), ferritin (P = .015) and WBC counts (P < .001), as well as lower MELD, MELD‐Na, CLIF‐C ACLF and COSSH‐ACLF scores , but had higher AFP levels (P < .001) at admission compared to HBV‐ACLF patients who did not survive.According to survival at day 28, patients were allocated into survival and non‐survival groups Table . Patientr = −.219; P = .0001; Figure r = .334, P < .001) and AST levels . ROC curve showed that ln(AFP) had the second largest AUROC, superior to TB, HE score, age, and sodium Figure . Accordi3.3P = .0003), MELD‐Na , and CLIF‐C ACLF , but not compared to COSSH‐ACLF  for the derivation group.Using logistic regression model, we generated a new prognostic model, the ALSS‐prognosis model (APM), using a four factor multivariate logistic regression: 0.042 × age + TB (mg/dL) × 0.094 + 1.228 × INRP = .0308), but no significant difference was observed compared to MELD, CLIF‐C ACLF, and COSSH‐ACLF.The established models were further verified in the validation group. Consistent with the derivation group, APM had the highest AUROC value among all prognostic models. As a result of the small sample size in the verification group, APM was significantly different to MELD‐Na  (logarithmic transformed). Ferritin was positively correlated with serum ALT (A) (logarithmic transformed) and AST (B). r, spearman's correlation coefficient; P values indicate the significance of correlations (two‐tailed).Click here for additional data file.Table S1 Clinical characteristics of survivors and non‐survivors groups of HBV‐ACLF patients treated with PE‐based ALSS at admissionClick here for additional data file.