Furthermore, we divided CKD patients into two groups (eGFR< or ≥60 mL/min/1.73 m2). Patients with eGFR < 60 mL/min/1.73 m2 had higher eryptosis levels (p < 0.001). MPO, CU/Zn SOD and IL-6 resulted significantly differently between groups (p < 0.001). Significant positive correlations were reported between eryptosis and MPO  and IL-6  and Cu/Zn SOD. Spearman’s rho = 0.6, p = 0.03). Conclusions. In patients with CKD, different factors are involved in the pathogenesis of eryptosis, in particular uremic toxins and oxidative stress and inflammatory markers. The progressive impairment of renal function may be associated with the increase in eryptosis levels, probably due to the accumulation of oxidative stress factors, inflammatory cytokines and uremic toxins.Background. Eryptosis is the programmed death of red blood cells; it may contribute to worsening anemia in chronic kidney disease (CKD). In this clinical condition, different factors induce eryptosis, such as oxidative stress, energy depletion and uremic toxins. In our study, we investigated if the progression of CKD may influence erythrocyte death levels and its relationship with oxidative stress and inflammation. Methods. We evaluated eryptosis levels in 25 CKD patients (five for each stage), as well as markers of oxidative stress and inflammation: myeloperoxidase (MPO), copper/zinc superoxide dismutase (Cu/Zn SOD) and interleukin-6 (IL-6) were evaluated in plasma samples. Results. Higher cell death rate was reported in the highest CKD stages ( Eryptosis, which is the programmed death of red blood cells (RBCs), is characterized by cell shrinkage and membrane scrambling with phosphatidylserine (PS) exposure at the erythrocyte surface . These mrophages . Indeed,rophages ,6.It has been demonstrated that, in patients undergoing hemodialysis, eryptosis levels are higher compared with healthy individuals . In patiMoreover, in CKD uremic toxins and reactive oxygen species (ROS) promote inflammation and oxidative stress through the stimulation of polymorphonuclear lymphocytes, leading to the release of inflammatory cytokines. End-stage renal disease is also characterized by a suppression of the antioxidant system which exacerbates oxidative stress. All these factors are responsible for the impairment of RBC membrane structures in patients with CKD ,12.In this study, we investigated if the progression of CKD may influence erythrocyte death levels and its relationship with oxidative stress and inflammation.2). Moreover, CKD patients were divided into three groups: normal renal function, CKD with GFR ≥ 60 mL/min/1.73 m2 and CKD with GFR < 60 mL/min/1.73 m2. Serum creatinine (SCr) was measured by an enzymatic method, isotope dilution mass spectrometry traceable by an automatic analyzer , and eGFR was calculated with the CKD-EPI equation [Our study was approved by the ethics committee of San Bortolo Hospital in Vicenza (n° 58/17). In this in vitro study, we evaluated eryptosis levels in 25 CKD patients (5 for each stage). Dialysis patients were excluded. We recruited blood samples from 25 CKD patients (5 for each stage) who came to our center  for a routine check-up. CKD stages were defined according to the KDIGO  2012 guidelines . In partequation . DemograHaemoglobin (Hb), heamatocrit (Hct), ferrum (Fe) and ferritin have been evaluated.g. We tested all samples with hemolysis index to avoid samples with hemolysis that could confuse subsequent analysis. This blood collection was performed by a medical doctor and the handling of samples was performed under highly strict aseptic conditions, in order to prevent any contamination of samples.Blood was collected in one single 4.5 mL ethylenediaminatetra-acetic acid (EDTA tube) and processed within 1 h after venipuncture. Samples were centrifuged for 10 min at 1600× 2 and then stained with 1 μL of AnnexinV-FITC-conjugated  for 20 min in the dark. Then 400 μL of Ringer was added to each tube. Analysis was performed by Navios Flow Cytometer  to identify the subpopulations of the eryptotic RBCs within 1 h. RBCs were gated and enumerated by identifying those cells that exposured PS at RBC surface. In the following, the forward scatter (FSC) of the cells was determined, and Annexin-V fluorescence intensity was measured with an excitation wavelength of 488 nm and an emission wavelength of 530 nm. A minimum 100,000 events were collected on each sample.For the CKD population, we directly measured eryptosis in freshly isolated RBCs from the different groups in parallel. PS avidly binds Annexin-V, which is thus employed to identify eryptotic cells. Thus, PS exposure at RBC surface was estimated from FITC-AnnexinV binding using flow cytometric analyses. 1 μL of isolated RBCs was washed in 400 μL Ringer solution containing 2 mM CaClA quantitative determination of oxidative stress was performed in the plasma samples of all CKD patients.Quantitative determination of plasma MPO concentration was performed by Human Instant ELISA kit . Preliminary plasma dilution 1:100 was performed for each sample with specific Sample Diluent . MPO determination was performed according to the manufacturer’s protocol and instructions. Optical density was read by using a VICTORX4 Multilabel Plate Reader  at 450 nm. The levels of this molecule were calculatedfrom the standard curve based on the manufacturer’s protocol. Standard samples ranged from 0.16–10.0 ng/mL. Human MPO Instant ELISA Kit sensitivity is 0.03 pg/mL. All tests were performed in triplicate.Quantitative determination of Cu/ZnSOD concentration in plasma samples was performed by Human ELISA kit . Preliminary plasma dilution 1:20 was performed for each sample with specific Sample Diluent . Cu/ZnSOD determination was performed based on manufacturer’s protocol and instructions. Optical density was read by using a VICTORX4 Multilabel Plate Reader  at 450 nm. The levels of these molecules were calculated from the standard curve according to the manufacturer’s protocol. Standard samples ranged from 0.08–5.0 ng/mL. Human Cu/ZnSODInstant ELISA Kit sensitivity is 0.04 ng/mL. All the tests were performed in triplicate.Quantitative determination of IL-6 in plasma samples was performed by Human Instant ELISA kit . Cytokine determination was performed according to manufacturer’s protocol and instructions. Optical density was read by using a VICTORX4 Multilabel Plate Reader  at 450 nm. The levels of this molecule were calculated from standard curves, according to the manufacturer’s protocol. All the tests were performed in triplicate. Standard samples for IL-6 ranged from 3.1 to 200 ng/mL and the sensitivity of this test was 0.92 ng/mL.p-value of <0.05 was considered statistically significant. Results are presented as percentages, or media and standard deviation (parametric variables) or medians and interquartile ranges (nonparametric variables). The Mann–Whitney U test or T test was used for comparison of the two groups when appropriate. The Kruskal–Wallis test or ANOVA test for multiple comparisons were applied to compare the groups when appropriate. Correlation coefficients were calculated with the Spearman’s rank or Pearson’s test, as appropriate.Statistical analysis was performed using the SPSS Software package and Excel. A A total of 25 CKD patients were enrolled in this study. Fourteenpatients were male and 11 were females, with a mean age of 57 ± 17 years old. In the study population, end-stage renal disease (ESRD) was attributed to diabetic nephropathy (seven patients), to hypertension (eight patients), nephroangiosclerosis (three patients), polycystic kidney disease (two patients), other causes (three patients) or unknown causes (two patients).Demographic features of all 25 patients and kidney diseases responsible for CKD are listed in Eryptosis is characterized by cell shrinkage, cell membrane scrambling and PS exposure at RBC surface. In order to investigate cell membrane scrambling, cell shrinkage and PS exposure at RBC surface, eryptotic RBCs were identified by FS (cell volume dimension) and AnnexinV binding using flow cytometric analyses.p < 0.001). In p < 0.001) (p < 0.05). Eryptosis resulted lower in RBCs from patients with CKD stage G1, while it was higher in RBCs from patients with CKD stage G5. Similar levels of eryptosis were reported between CKD G1 and CKD G2 and CKD G3. In addition, eryptosis levels resulted similarly between CKD G2 and CKD G3 and CKD G3 and CKD G4. Eryptosis levels resulted significantly higher in CKD G5 compared with all CKD stages (p < 0.001). Furthermore, we divided CKD patients intotwogroups (eGFR< or ≥60 mL/min/1.73 m2). Patients with eGFR < 60 mL/min/1.73 m2 were characterized by higher eryptosis levels (p < 0.001)  showed eryptosis levels significantly lower than other groups (p < 0.001).RBCs of CKD patients were dramatically deranged in their morphology and the average FS, reflecting cell volume, was significantly higher in erythrocytes from patients with CKD stage G4 and G5 (< 0.001) . In part< 0.001) . Moreovep < 0.05)  .p < 0.001) (p < 0.05). Cu/Zn SOD levels resulted similarly in CKD patients in stage G1 and G2 (p = 0.36) and significantly differently in other comparison between stages . We observed a significant positive correlation between eryptosis and MPO  and IL-6  and Cu/Zn SOD. Spearman’s rho = 0.6, p = 0.03) (< 0.001) . MPO and = 0.03) .2 and CKD patients with GFR < 60 mL/min/1.73 m2) to compare eryptosis levels in patients with mild CKD (G1) with patients with more severe CKD, since in our study a healthy population is missing. Even though patients with CKD G1 showed lower levels of eryptosis compared with patients with more severe CKD, they had higher levels of eryptosis compared to healthy individuals in a previous study  [In this study, eryptosis levels were higher in patients with advanced chronic kidney disease (stage G4 and stage G5) compared to patients with early stages of chronic renal damage . In addition, we decided to divide patients into three groups  .Indeed, different factors influence eryptosis levels in chronic kidney disease, such as oxidative stress, energy depletion, and uremic toxins . All of In particular, uremic toxins have been associated with increased levels of eryptosis in chronic kidney disease. Indoxyl sulfate has been reported to increase cytosolic calcium concentration and to stimulate erythrocyte cell membrane scrambling, thus resulting in phosphatidylserine exposure on the surface of RBCs . In the In our study, we reported higher levels of markers of oxidative stress and inflammation, MPO, CU/Zn SOD and IL-6, in more severe stages of chronic kidney disease (stages G4 and G5). A positive correlation between these molecules and eryptosis levels was also demonstrated.Our data are supported by previous studies, which have shown that oxidative stress is inversely correlated with glomerular filtration rate and directly with duration of dialysis . In end-Moreover, oxidant species can also directly cause renal ischemia and glomerular damage, thus contributing to the progression of renal damage . HemodiaOxidative stress is responsible for the impairment of RBC membrane structures. ROS induce an injury to the lipids and proteins of RBC membranes, thus resulting in the rearrangement of the erythrocyte skeleton and the reduction of cell membrane stability and deformability . MoreoveUremic toxins and ROS promote inflammation and oxidative stress through the stimulation of polymorphonuclear lymphocytes, thus inducing the release of inflammatory cytokines, such as interleukin-1β and interleukin-8, tumor necrosis factor α .The positive correlation between MPO, CU/Zn SOD and IL-6 and eryptosis levels in our study population highlights the role of oxidative stress and inflammatory cytokines in the pathogenesis of RBCs’ programmed death in patients with chronic kidney disease.Our study has some limitations. First of all, the small number of subjects in each group and the lack of a healthy population as control group. Second, we are not able to account for other potential confounders, such age. For these reasons, our data may show an association between the progression of CKD and erythrocyte death levels and its relationship with oxidative stress and inflammation.In patients with chronic kidney disease, different factors are involved in the pathogenesis of eryptosis, in particular uremic toxins and oxidative stress and inflammatory markers. The progressive impairment of renal function seems to be associated with the increase in eryptosis levels, probably due to the accumulation of oxidative stress factors, inflamamtory cytokines and uremic toxins. The identification of the factors responsible for RBCs’ programmed death may represent an important tool in the management of renal anemia in patients with chronic kidney disease.


Telomeres are DNA–protein complexes that protect chromosome ends from DNA damage and are surrogate biomarkers of cellular aging. Current evidence, almost entirely from cross-sectional observations, supports negative associations between leukocyte telomere length (LTL) and adverse lifestyle factors and cardiometabolic risk factors. Polycystic ovary syndrome (PCOS), the most common gynecological endocrine disorder, is associated with inflammation and oxidative stress, both factors associated with accelerated telomere attrition. We therefore hypothesized that LTL would be shorter and decrease more rapidly in women with PCOS in comparison to a control population.n = 190; age 46, n = 207) and referent women  with data on LTL.This is a population-based cohort study comprising women of Northern Finland Birth Cohort 1966, with clinical examinations at ages 31 and 46. The sample included self-reported PCOS . The mean LTL change between ages 31 and 46 did not differ between groups (P = 0.19). However, we observed a significant LTL attrition between ages 31 and 46 in the reference population (P < 0.001), but not in women with PCOS (P = 0.96).Women with PCOS had similar mean LTL at ages 31 and 46 (This finding may suggest a difference in the LTL attrition rate in women with PCOS, an unexpected finding that might affect their risk of age-related disease. Further research is needed to clarify the underlying mechanisms. Telomeres are specialized DNA–protein complexes located at the ends of all linear chromosomes . VertebrDue to its guanine-rich sequence, telomeric DNA is vulnerable to oxidative damage, such as single-strand breaks and erosion, when exposed to free radicals or oxidants . Thus, iPolycystic ovary syndrome (PCOS) is the most common endocrine disorder among reproductive-aged women, affecting 6–18% of this population . The synLeukocyte telomere length (LTL) has attracted increasing interest as a potential biomarker in the field of reproduction and fertility , 30. InfIn the present study, we studied a unique, large cohort of women born in 1966 as they turned 46 years. Our aim was two-fold: first, to clarify in a cross-sectional design whether TL differed between women with self-reported PCOS and non-PCOS controls (reference population). The second aim was to perform a longitudinal, follow-up study to determine whether change in LTL between age 31 and pre-menopause differed between PCOS and referent women.The study population consisted of the prospective Northern Finland Birth Cohort 1966 (NFBC1966) which comprised all individuals born alive during 1966  . At agesThe study followed the principles of the Declaration of Helsinki. The Ethics Committee of the Northern Ostrobothnia Hospital District (EETTMK decision number 94/2011) approved the research on September 17, 2012. All participants took part on a voluntary basis and signed an informed consent to use all the data.n = 330) reported isolated oligo/amenorrhea, 10.9% (n = 321) isolated hirsutism and 4.1% (n = 125) both oligomenorrhea and hirsutism (OA+H), after excluding pregnant women and those using hormonal preparations (n = 1459) or denying data usage (n = 41). The postal questionnaire at age 46 included the question: ‘Have you ever been diagnosed as having polycystic ovaries and/or polycystic ovary syndrome (PCOS) during your life?’ to which 180 participants responded ‘yes.’At age 31, the postal questionnaire included questions on oligomenorrhea  longer than 35 days?’) and excessive body hair . Of the women who responded to these questions, 11.2% (n = 279). The validity of this questionnaire to distinguish PCOS cases has already been shown in our previous studies from the same cohort, as they presented the typical metabolic, hormonal and psychological profile of PCOS (n = 1577).Consequently, women who reported both OA+H at age 31 and/or diagnosis of PCOS by age 46 were considered as self-reported PCOS cases  and at age 46 (n = 207), and reference population at age 31 (n = 1054) and at age 46 (n = 1324). The follow-up data to investigate LTL attrition between ages 31 and 46 included 152 PCOS cases and 913 referent women  and 0.995 (s.d. = 0.002) for telomere and albumin amplicons, respectively. Mean inter-run CV as calculated from calibrator Cq values was 2.77% for telomere and 1.36% for albumin.Genomic DNA was extracted from the blood samples by phenol–chloroform extraction at 31 years and by QIAsymphony DSP DNA Midi Kit (Qiagen) at 46 years. TL was measured from the peripheral blood leukocytes due to sample availability; however, LTL is believed to be a good proxy for TL in other tissues , 38. LTLt method . Mean R2Detailed information about laboratory methods for hormonal and metabolic parameters has been published previously . At age At both ages, the serum levels of total testosterone were measured using Agilent triple quadrupole 6410 LC/MS equipment with an electrospray ionization source operating in positive-ion mode (Agilent Technologies).Fasting plasma glucose was analyzed by an enzymatic dehydrogenase method . Fasting serum insulin was analyzed by a chemiluminometric immunoassay . The high-sensitivity C-reactive protein (CRP) was analyzed by an immune-nephelometric assay . The samples were analyzed at NordLab Oulu, a testing laboratory (T113) accredited by the Finnish Accreditation Service (EN ISO 15189).BMI values at both ages  were combined to create a variable where clinically measured BMI was used if available and self-reported BMI was used in other cases .s.d. (LTL)) separately for each measurement.Since LTL was measured at different times and by using a different reference DNA sample at ages 31 and 46, they were standardized (z-score =(LTL − mean (LTL))/t-test was used to compare LTL between the study groups. The association between LTL and PCOS was analyzed by using linear regression models adjusted for Model 1: BMI and Model 2: BMI, smoking, alcohol consumption and socioeconomic status at the corresponding age. Potential effects between PCOS and these adjusting covariates were assessed by using interaction terms between PCOS, BMI, smoking, alcohol consumption and socioeconomic status in linear regression analysis.At both ages, the two independent samples t-test was used to analyze the longitudinal change in LTL between ages 31 and 46 within each study group. The association between LTL attrition rate and PCOS was analyzed by linear regression models adjusted for Model 1: BMI at both ages 31 and 46 and Model 2: BMI, smoking, alcohol consumption and socioeconomic status at both ages 31 and 46.Paired samples t-test was used to compare the longitudinal change of LTL between ages 31 and 46 between the study groups.Two independent samples P-value < 0.05 was considered significant. Analyses were performed with SPSS software, version 25 (SPSS). Benjamini–Hochberg corrections were used to adjust P-values for multiple testing.All probability values were two-sided, and At both ages, women with PCOS had significantly higher BMI, waist circumferences and serum levels of testosterone, CRP, insulin and fasting glucose and greater insulin resistance than reference women .P = 0.56) or at age 46 (P = 0.41) (Mean LTL did not differ between women with PCOS and the reference population at age 31 ( = 0.41) .Table 1P = 0.59) . Similarly, there was no statistically significant association between LTL and PCOS at age 46 (P = 0.41) and the results did not change after adjustments  .LTL was not associated with PCOS at age 31 ( = 0.59)  and the  = 0.71) . The levP < 0.001) (P = 0.96) (P = 0.19).Since telomeres shorten with age, we explored the degree of change in LTL over the 15 years study period, in affected and unaffected women. We observed a significant negative mean difference (MD) of LTL z-scores between ages 31 and 46 in the reference population , < 0.001) , whereas = 0.96) . HoweverP = 0.19)  . The resThe mean LTL did not differ significantly between women with PCOS and the reference population either at the age of 31 or 46, despite the unfavorable metabolic profile observed in women with PCOS. No statistically significant association between LTL and PCOS was found at the ages of 31 or 46. The results did not change after adjustments. In contrast to our original hypothesis, the mean change in LTL z-scores between ages 31 and 46 was not significantly different in the PCOS group from the reference population, despite demonstrating the expected age-related, statistically significant decline in the reference population.To our knowledge, this is the first longitudinal population-based study prospectively investigating the changes in LTL over time in women with PCOS compared to non-PCOS reference population. Interestingly, the MD of LTL between ages 31 and 46 years was negative in the reference population, but not in the PCOS group suggesting a slower telomere shortening rate in PCOS women. This observation does not support our original hypothesis, as previous studies by our group and others have established that PCOS women are at risk for adverse cardiometabolic disorders  , 44, 45 While replication in additional cohorts is needed, there are some interesting possible explanations for our findings. In some studies, PCOS women have been reported to experience menopause later than the reference population , 49. Repn = 698) compared to the control group (n = 611) after adjusting for age  vs reference group: n  = 523 (33.2%), P = 0.37) but was significantly greater in the PCOS group at age 46 (PCOS: n  = 72 (25.8%) vs reference population: n  = 253 (16.0%), P < 0.001). This feature could have decreased the significance of the analyses in the PCOS group. The symptoms and diagnosis of PCOS were self-reported. Consequently, our study population probably involved women with milder hormonal and metabolic disorders in comparison to women diagnosed with PCOS attending infertility clinics for example. This study feature may have decreased the significance of the association between PCOS and LTL and prevented us from generalizing to all phenotypes of PCOS. We acknowledge that hirsutism might be over-reported and ovarian ultrasonography was not available to aid the diagnosis of PCOS. However, this definition is consistent with the National Institutes of Health, the Rotterdam and the New Guidelines criteria for diagnosis of PCOS (This study also has some limitations. The total number of women with missing telomere data did not differ between the study groups at age 31 (PCOS:  of PCOS , 16. Mor of PCOS , 35, 36, of PCOS . However of PCOS . AnotherThis study made two important observations: First, it does not support evidence for a risk of shorter LTL in women with PCOS. Secondly, the 15-year shortening rate of LTL appeared not to be faster in women with PCOS compared to the rest of the population. These results were observed despite the presence of a less favorable metabolic profile in women with PCOS. This was an unexpected finding that might affect their risk of age-related disease. However, because of the aforementioned limitations of our study and before concluding whether there is a causal association between PCOS and LTL or not, further research is needed to clarify the underlying mechanisms and compare these associations with other biomarkers of biological aging.European Journal of Endocrinology. Terhi T Piltonen was not involved in the review or editorial process for this paper, on which he/she is listed as an author. The other authors declare that they do not have any conflict of interest.Terhi T Piltonen is on the editorial board of the The follow up of the NFBC1966 study received financial support from University of Oulu Grant no. 65354, 24000692; Oulu University Hospital Grant no. 2/97, 8/97, 24301140; Ministry of Health and Social Affairs Grant no. 23/251/97, 160/97, 190/97; National Institute for Health and Welfare, Helsinki Grant no. 54121; Regional Institute of Occupational Health, Oulu, Finland Grant no. 50621, 54231; ERDF European Regional Development Fund Grant no. 539/2010 A31592. S S, M R J, A B and J R acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement n°633595, DynaHEALTH; S S, M R J, J R received additional support from the following: H2020-733206 LifeCycle, H2020-824989 EUCANCONNECT, H2020-873749 LongITools, and the JPI HDHL, PREcisE project, ZonMw the Netherlands no. P75416. T P acknowledges funding from the Academy of Finland under grant number 315921and 321763.J P: study design, execution, analysis, manuscript drafting and critical discussion. P P: study design, execution, analysis, manuscript drafting and critical discussion. J R: study design, analysis, manuscript drafting and critical discussion. A I B: manuscript drafting and critical discussion. J L B: manuscript drafting and critical discussion. J S T: manuscript drafting and critical discussion. S F: manuscript drafting and critical discussion. T P: manuscript drafting and critical discussion. S S: study design, analysis, manuscript drafting and critical discussion. L M-P: study design, execution, manuscript drafting and critical discussion.


To investigate the role of gut microbiota and metabolites in POCD in elderly orthopedic patients, and screen the preoperative diagnostic indicators of gut microbiota in elderly POCD.40 elderly patients undergoing orthopedic surgery were enrolled and divided into Control group and POCD group following neuropsychological assessments. Gut microbiota was determined by 16S rRNA MiSeq sequencing, and metabolomics of GC–MS and LC–MS was used to screen the differential metabolites. We then analyzed the pathways enriched by metabolites.There was no difference in alpha or beta diversity between Control group and POCD group. There were significant differences in 39 ASV and 20 genera bacterium in the relative abundance. Significant diagnostic efficiency analyzed by the ROC curves were found in 6 genera bacterium. Differential metabolites in the two groups including acetic acid, arachidic acid, pyrophosphate etc. were screened out and enriched to certain metabolic pathways which impacted the cognition function profoundly.Gut microbiota disorders exist preoperatively in the elderly POCD patients, by which there could be a chance to predict the susceptible population.http://www.chictr.org.cn/edit.aspx?pid=133843&htm=4], identifier [ChiCTR2100051162].[ Some stPOCD is known to be similar to AD in terms of pathogenesis, clinical presentation, and morphopathological changes within the central nervous system . However2.2.1.This was a prospective case–control study to collect fecal samples from elderly patients undergoing orthopedic surgery, to compare changes in gut microbiota and metabolites between POCD and control patients. The study was approved by the Medical Ethics Committee of Tongji Hospital affiliated to Tongji Medical College, Huazhong University of Science and Technology. All patients in the research signed informed consent before sample collection.Inclusion criteria: Patients undergoing elective internal fixation of lower limb fractures, knee replacement or hip replacement by general anesthesia, American Society of Anesthesiologists (ASA) classification I – II, age 66–84 years old, and conscious in perioperative period were enrolled.Exclusion Criteria: Patients suffered from one of following terms were excluded: central nervous system diseases or psychological disorders, long-term use of sedatives or antidepressants within the last year, Parkinson’s disease, severe hearing or visual impairment, drug dependence, alcoholism, inability to communicate with a physician.The PASS 15 software was applied to calculate the sample size. The study is a diagnostic test and test for One Receiver Operating Characteristic (ROC) curve was applied. Existing studies show that the incidence of POCD in the elderly is about 40%, the sample size of the positive group was set at 40%, the AUC was 0.8, the type I error α was 0.05, the type II error β was 0.1 and the drop out rate was 20%, resulting in a positive sample size of 16 cases and a negative sample size of 24 cases for the study. The total sample size for this study was 40 cases.2.2.The necessarily general information and medical history were collected with permission of each patient before surgery. Information about vital signs during the operation period, postoperative pain score and antibiotics treatment were also collected.2.3.Neuropsychological assessments were performed to each patient 1 day before surgery, 1 day after surgery, 3 days after surgery and 28 days after surgery. The cognitive function of patients were assessed using the Mini-mental state examination (MMSE), Montreal cognitive assessment-basic (MoCA-B) and the Brief mental status assessment (Mini-Cog) and all the participant were divided into POCD and Control groups based on the assessment results. All the assessments above were performed by the same anesthetist. Adapted questions of MoCA-B facilitate the detection of mild cognitive impairment in subjects who are illiterate or possess a low education level. MoCA-B assesses executive function, language, orientation, calculation, etc., and is available for clinical research from official website.2.4.Fecal samples (about weight 2 g) were collected 1 day before surgery, suspended in fecal storage solution  and then snap frozen and stored at −80°C. Bacterial DNA was isolated from the fecal samples using a MagPure Soil DNA LQ Kit  following the manufacturer’s instructions. DNA concentration and integrity were measured by a NanoDrop 2000 spectrophotometer  and agarose gel electrophoresis, respectively. PCR amplification of the V3-V4 hypervariable regions of the bacterial 16S rRNA gene was carried out in a 25 μl reaction using universal primer pairs . The reverse primer contained a sample barcode and both primers were connected with an Illumina sequencing adapter.2.5.The Amplicon quality was visualized using gel electrophoresis. The PCR products were purified with Agencourt AMPure XP beads  and quantified using Qubit dsDNA assay kit. The concentrations were then adjusted for sequencing which was performed on an Illumina NovaSeq6000with two paired-end read cycles of 250 bases each .Raw sequencing data were in FASTQ format. Paired-end reads were then preprocessed using cut adapt software to detect and cut off the adapter. After trimming, paired-end reads were filtering low quality sequences, denoised, merged and detect and cut off the chimera reads using DADA2  with the2.6.2.6.1.The samples were analyzed on an Agilent 7890B gas chromatography system coupled to an Agilent 5977AMSD system . ADB-5MS fused silica capillary column  was utilized to separate the derivatives. Helium (>99.999%) was used as the carrier gas at a constant flow rate of 1 ml/min through the column.2.6.2.A Dionex Ultimate 3,000 RS UHPLC fitted with Q-Exactive plus quadrupole-Orbitrap mass spectrometer equipped with heated electrospray ionization (ESI) source  was used to analyze the metabolic profiling in both ESI positive and ESI negative ion modes. An ACQUITY UPLC HSS T3 column  were employed in both positive and negative modes.3.post hoc Tukey tests or Fisher’s exact tests. Normal distribution data were analyzed using one-way ANOVA, whereas non-normal distribution data were analyzed using Fisher’s exact test. Comparisons of numbers of variables in the general information between groups were performed by Chi-square test and Fisher’s exact test. Diagnostic cut-offs, AUC, sensitivity and specificity were determined by ROC curve analysis. p-value <0.05 is considered to be a significant difference.Statistical analysis was performed using SPSS 17.0 . Values presented were expressed as mean ± standard error of the mean (S.E.M.), comparisons between groups were performed using one-way analysis of variance (ANOVA) followed by The representative read of each ASV was selected using QIIME 2 package. All representative reads were annotated and blasted against Silva database Version 138 (16 s rDNA) using q2-feature-classifier with the default parameters. The microbial diversity in fecal samples was estimated using the alpha diversity that include Chao1 index, Shannon index and ACE index. The Unifrac distance matrix performed by QIIME2 software was used for unweighted Unifrac Principal coordinates analysis (PCoA) and phylogenetic tree construction. The 16S rRNA gene amplicon sequencing and analysis were conducted by OE Biotech Co., Ltd. .p value >1 for the first principal component of the OPLS-DA model and value of p <0.05 for the T-test.Multiple statistical analyses were performed using principal component analysis (PCA), partial least squares analysis (PLS-DA) and orthogonal partial least squares analysis (OPLS-DA) to find the differential metabolites between groups. Student’s T test and a Fold change analysis were used to compare metabolites between the two groups. A combination of multidimensional and unidimensional analyses was used to screen for differential metabolites. Metabolic pathways enrichment analysis of differential metabolites were performed based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The screening criteria was VI4.4.1.General information and medical history were listed in 4.2.The total data volume of raw reads after sequencing ranged from 78,268 to 81,928, clean tags after quality control ranged from 59,473 to 73,165, clean tags after removing chimeras to obtain valid tags ranged from 42,922 to 70,784. The number of ASVs in each sample ranged from 103 to 533. Comparisons between the two groups using Wilcoxon rank sum test, significant differences were observed in 39 ASVs and 20 genus.Bacteroidota, Firmicutes, Proteobacteria, Actinobacteriota, Fusobacteria were the top abundance at the phylum level (Alistipes (p = 0.008), Helicobacter (p = 0.007), Lysobacter (p = 0.011), Barnesiella (p = 0.017), Macrococcus (p = 0.049), etc. , etc. . Relativp = 0.098). The Shannon index (p = 0.065) and ACE index (p = 0.110) indicated species diversity and evenness, did not show significant differences either , p value, sensitivity, specificity of gut bacteria for the diagnosis of POCD are listed in ROC curve analysis was performed to evaluate the diagnostic efficiency of the 20 differential genera gut bacteria in POCD . The dia4.4.R2 = 0.961, Q2 = −0.268; T-test and visualized by volcano plots  and Ciliatine (p = 0.002), and positive correlated to L-lysine (p = 0.025) and L-alanine (p = 0.040). While Sutterella was positive correlated to Methanephosphonothioic acid (p = 0.003) and Ciliatine (p = 0.002). [Eubacterium]_coprostanoligenes_group was negative correlated to 5-aminovaleric acid (p = 0.0003), Talose (p = 0.0008), etc. , etc. .5.In this study we investigated the gut microbiota from elderly patients undergoing orthopedic surgery. Considering confounding factors, the general information of participants including relevant previous history, laboratory test results and postoperative pain NRS were collected, and there were no differences in variables age, gender, type of surgery, blood glucose, BUN, INR, LVEF, NRS, number of hypertension, diabetes, HLP, stroke, ECG ST segment ischemia between the two groups. The variable age was divided into 4 sections with a 5-year interval. The majority is from 66 to 75 years old, and there was no difference in 4 sections between groups. Which indicated the morbidity of POCD in the elderly patients was equal in the 66–85 years interval. The patients’ gender, cardiac function, renal function, stroke history, blood glucose, lipid level and postoperative pain did not show influences in the POCD morbidity in this study, which excluded the confounding factor and provided us a focus on the role of gut microbiota.Helicobacter, Alistipes, Barnesiella, Lachnospiraceae_NK4A136_group, Prevotellaceae_NK3B31_group and Pediococcus were higher in POCD group than those in Control group, and all have got significantly diagnostic efficiency analyzed by the ROC curves, which might be potential target bacterium to diagnose or predict elderly POCD. The alterations above were consistent with the recent research. As is well known, Helicobacter pylori (H. pylori) is a Gram-negative bacterium resides in the gastrointestinal tract starting from early age. H. pylori infection might be a risk factor for cognitive decline in the elderly  which can form acetylCoA and participate the metabolism of carbohydrates and fats. It is produced and excreted by certain acetic acid bacteria, notably the Acetobacter genus and Clostridium acetobutylicum. Arachidic acid is an important component of neuronal membranes, and regulate neurotransmission, neuroinflammation, cell survival and cognition function . The oxiPyrophosphate was highly enriched to pathways of oxidative phosphorylation, parkinson disease, neurodegeneration – multiple diseases, and expression level was higher in POCD group. Bisphosphonates interact and regulate calcium ions which play a role in neurodegenerative diseases , the res6.Gut microbiota altered in the elderly POCD and some of the genera bacterium might be effective diagnosis indicators to predict POCD incidence before surgery. The differential metabolites including acetic acid, arachidic acid and pyrophosphate etc. played important roles in the cognition impairment in POCD patients.The limitation of this study is that although we have screened out the differential microbiota and metabolites which might be indicators of the POCD, a verification work has not been done yet. We planned to complete the work by fecal microbiota transplantation in future to investigate the therapeutic effect of the indicators.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The studies involving human participants were reviewed and approved by Medical Ethics Committee of Tongji Hospital affiliated to Tongji Medical College, Huazhong University of Science and Technology. The patients/participants provided their written informed consent to participate in this study.JB designed and supervised the project and obtained funding. JB, YX, DH, and XC collected samples and performed neurological assessments. FG provided samples. JB, SL, GZ, and JT extracted data and performed statistical analysis. JB drafted the manuscript. AL and HX revised the manuscript for important intellectual content. All authors contributed to the article and approved the submitted version.This study was supported by National Natural Science Foundation of China (82001161) and Braun Foundation for Scientific Research in Anesthesia (BBDF-2019-011).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


P < 0.001). In the lower respiratory tract, uniformity indices, richness indices, and the abundance-based coverage estimator were significantly higher in the mild group than in the severe group (P < 0.001). In patients with severe COVID-19, SDPGs were detected in 40.7% of upper and 63.2% of lower respiratory tract samples. In patients with mild COVID-19, only 10.8% of upper and 8.5% of lower respiratory tract samples yielded SDPGs. SDPGs were present in both upper and lower tracts in seven patients (35.0%), among which six (30.0%) patients possessed the same SDPG in the upper and lower tracts. However, no patients with mild infections had an SDPG in both tracts. Staphylococcus, Corynebacterium, and Acinetobacter were the main SDPGs. The number of SDPGs identified differed significantly between patients with mild and severe COVID-19 (P < 0.001). SDPGs in nasopharyngeal microbiota cause secondary bacterial infection in COVID-19 patients and aggravate pneumonia.Coronavirus disease 2019 (COVID-19) is a respiratory infectious disease responsible for many infections worldwide. Differences in respiratory microbiota may correlate with disease severity. Samples were collected from 20 severe and 51 mild COVID-19 patients. High-throughput sequencing of the 16S rRNA gene was used to analyze the bacterial community composition of the upper and lower respiratory tracts. The indices of diversity were analyzed. When one genus accounted for >50% of reads from a sample, it was defined as a super dominant pathobiontic bacterial genus (SDPG). In the upper respiratory tract, uniformity indices were significantly higher in the mild group than in the severe group (IMPORTANCE The nasopharyngeal microbiota is composed of a variety of not only the true commensal bacterial species but also the two-face pathobionts, which are one a harmless commensal bacterial species and the other a highly invasive and deadly pathogen. In a previous study, we found that the diversity of nasopharyngeal microbiota was lost in severe influenza patients. We named the genus that accounted for over 50% of microbiota abundance as super dominant pathobiontic genus, which could invade to cause severe pneumonia, leading to high fatality. Similar phenomena were found here for SARS-CoV-2 infection. The diversity of nasopharyngeal microbiota was lost in severe COVID-19 infection patients. SDPGs in nasopharyngeal microbiota were frequently detected in severe COVID-19 patients. Therefore, the SDPGs in nasopharynx microbiota might invade into low respiratory and be responsible for secondary bacterial pneumonia in patients with SARS-CoV-2 infection. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel human pathogen, caused the coronavirus disease 2019 (COVID-19) global pandemic that began at the end of 2019  in the nasopharynx of severe influenza patients . SDPGs aThe procalcitonin (PCT) and C-reactive protein (CRP) values of all mild patients included in this study were normal. For severe patients, PCT and CRP values were higher than normal at sampling time points.P < 0.001).A subsequent bacterial infection was diagnosed in patients displaying elevated levels of PCT or CRP or an isolated pathogenic bacterial species in blood, alveolar lavage fluid, air intubation, or sputum samples. Such infections were recorded for 71% of severe cases and 10% of mild cases  were obtained with a length range of 407 to 430 bp (mean 422.4 ± 4.5 bp) and 40,417 to 69,999  sequences/swab. After clustering sequences into operational taxonomic units (OTUs) and removing OTUs with RA <0.1%, the average number of OTUs per sample was 299.5 ± 159.4. The average numbers of OTUs in the mild upper, mild lower, and severe lower respiratory tract samples were 252.84 ± 36.08, 267.87 ± 36.13, and 386.09 ± 257.36, respectively.P < 0.001; P < 0.001; Six alpha diversity indices were used to analyze the diversity of the bacterial community in the respiratory tracts of the patients. In the upper respiratory tract, three uniformity indices  were significantly higher in the mild group than in the severe group , 39 classes (15 to 28 for each sample), 91 orders (27 to 56 for each sample), 159 families (36 to 99 for each sample), and 412 genera (58 to 178 for each sample) were annotated. The top three most abundant phyla were Proteobacteria, Firmicutes, and Bacteroidetes, together accounting for 81.4%, 76.8%, 91.2%, and 72.5% of the sequences in the lower respiratory tract of the mild group, the upper respiratory tract of the mild group, the lower respiratory tract of the severe group, and the upper respiratory tract of the severe group, respectively.According to the statistics for the top 15 abundant families, there were great differences between severe and mild patients, while differences between upper and lower respiratory tracts in the same symptom group were minimal .Burkholderia, Acinetobacter, Staphylococcus, Escherichia/Shigella, Morganella, and Corynebacterium in the severe COVID-19 group was significantly higher than in the mild group (P < 0.001).We next compared the relative abundance of the top 15 most dominant genera across the four groups. Similarly, the results showed that differences were great between severe and mild COVID-19 groups and small between upper and lower respiratory tracts within the same symptom groups . OverallPrevotella (n = 4), Staphylococcus (n = 1), unidentified Corynebacterium (n = 1), Escherichia/Shigella (n = 1) and Haemophilus (n = 1). Meanwhile, 40.7% of upper respiratory tract samples from severe patients carried an SDPG, including Staphylococcus (n = 4), Acinetobacter (n = 3), Corynebacterium (n = 2), and Burkholderia (n = 2). In total, 8.5% of mild patients included an SDPG in the lower respiratory tract, including Pseudomonas (n = 1), Flavobacterium (n = 1), Haemophilus (n = 1), and Myroides (n = 1). Meanwhile, 63.2% of lower respiratory tract samples of severe patients displayed an SDPG, including Burkholderia (n = 14), Acinetobacter (n = 8), Staphylococcus (n = 6), Escherichia/Shigella (n = 2), Stenotrophomonas (n = 1), Mycoplasma (n = 1), Neisseria (n = 1), Gemella (n = 1) and Corynebacterium , and the proportion of lower respiratory tracts of severe patients was significantly higher than that of upper respiratory tracts (P < 0.05). However, the proportion of lower respiratory tracts in mild patients was slightly lower than that of upper respiratory tracts (P = 0.833).If a genus was responsible for >50% of reads, it was defined as an SDPG. We found that 10.8% of upper respiratory tract samples from mild patients harbored an SDPG, including Burkholderia cepacia (n = 13), Acinetobacter baumannii (n = 5), Staphylococcus aureus (n = 4), Stenotrophomonas maltophilia (n = 3), Escherichia coli (n = 2), Enterobacter cloacae (n = 2), and Staphylococcus hominis (n = 1). Sequencing results were compared with culture results, and 86.7% (26/30) of bacterial pathogens isolated from severe lower respiratory tract samples were consistent with the sequencing results.Pathogens were isolated from 30 severe lower respiratory tract samples containing an SDPG (Table S4). The pathogens were Burkholderia (numbers S004 and S007), Staphylococcus (numbers S003 and S008), Acinetobacter (number S005), and Corynebacterium (number S001). Furthermore, in two cases (numbers S003 and S008), S. aureus cells with identical genome sequences were isolated from both the upper and lower respiratory tracts  had the same SDPG in the upper and lower respiratory tract . These Sy tracts .Viral pneumonia is a potentially fatal human disease with severe social and economic impacts, and its prevention and control are a challenge to infectious disease medicine and biosecurity , 11. CorSeveral approaches are critical for improving the treatment of patients with COVID-19 pneumonia. First, diagnostic research should be carried out on pathogens responsible for secondary infections in severely ill patients. Second, the characteristics and effects of mixed infections during treatment should be analyzed, and the diagnosis of mixed infections should be established. Third, drug-resistant bacteria should be detected . FinallyP < 0.05). Furthermore, there were seven severe COVID-19 patients with the same SDPG in the upper and lower respiratory tract. From these results, it could be proposed that the severity of COVID-19 in patients may be correlated with SDPGs in the respiratory flora. Additionally, SDPG persistence may aggravate the condition of COVID-19 patients. A similar conclusion was drawn for influenza patients  patients due to critical illness, low immune function, and other risk factors This result not only indicates that SDPG persistence may play a role in secondary bacterial infection after COVID-19 disease but also provides significant guidance for treating severe COVID-19 patients.There are some limitations to this study. First, the nasopharyngeal microbiota of COVID-19 patients before hospitalization was not clear. Thus, it was not possible to investigate whether these SDPGs were caused by the environment or by increases in the abundance of existing colonization strains. Second, due to the lack of samples from healthy people as control, it is impossible to compare the compositions of the microbiome in upper respiratory tracts between COVID-19 patients and healthy persons. However, there have already been several reports on COVID-19 patients with upper respiratory tract microbiome disorders , 18. ThiIn conclusion, most severe patients were found to possess an SDPG in their lower respiratory tract, and some were consistent with an SDPG in the upper respiratory tract, according to high-throughput sequencing of the 16S rRNA gene, bacterial culture, and genome analyses. Therefore, we propose that viral infection leads to dysbacteriosis of the upper respiratory tract, causing some pathogens to become SDPGs and then invade the lower respiratory tract, leading to secondary bacterial pneumonia. This is similar to what can occur in influenza patients . Therefo2)/inhaled oxygen concentration (FiO2) ≤300 mm Hg (1 mm Hg = 0.133 kPa); at high altitude (>1000 m), PaO2/FiO2 should be corrected according to the formula PaO2/FiO2 × (760/atmospheric pressure [mm Hg]); (iv) clinical symptoms progressively worsening, and lung imaging shows lesions progressing significantly (>50%) within 24 to 48 h.The studied cases were divided into mild and severe subgroups. All COVID-19 cases were classified as mild based on the COVID-19 Pneumonia Diagnosis and Treatment Plan issued by the National Health Commission of the people’s Republic of China, unless they possessed one or more of the following clinical manifestations, in which case they were classified as severe: (i) shortness of breath, respiratory rate (RR) ≥30 times/min; (ii) in the resting state when inhaling air, oxygen saturation is ≤93%; (iii) arterial blood oxygen partial pressure  and C-reactive protein (CRP) levels were abnormal and indicated bacterial infections. Fifteen severe patients provided throat swabs at least once during hospitalization, and each patient provided sputum and/or bronchoalveolar lavage fluid at least once during hospitalization. For pharyngeal swab samples, we selected the samples at the time of admission. For clinical samples, we collected samples when abnormal PCT and CRP values indicated bacterial infection. Under a 10× microscope, there are less than 10 squamous epithelial cells and more than 25 leukocytes in each field , which was regarded as qualified sputum samples. The 51 mild COVID-19 cases were from Shijiazhuang (25 patients), Sanya (11 patients), Taiyuan (6 patients), and Zigong (9 patients) between January and April 2020. Each mild case provided at least one nasopharyngeal swab during this period and every patient from Zigong provided sputum at least once.A total of 205 respiratory tract samples were obtained for analysis in this study, including 27 upper and 57 lower respiratory tract samples collected from severe cases  and 74 uThe studies involving human participants were reviewed and approved by the Ethics Committee of Beijing Ditan Hospital affiliated with Capital Medical University, China, No. (023) – 01. The patients/participants provided written informed consent to participate in this study.CCTAYGGGRBGCASCAG-3′) and R (5′-GGACTACNNGGGTATCTAAT-3′) with high-efficiency high-fidelity polymerase enzyme. A TruSeq DNA PCR-Free Sample Preparation kit was used to construct the library. The library was quantified using Qubit and Q-PCR, and NovaSeq6000 was used for sequencing. According to the barcode sequence and PCR primer sequence, data for each sample were separated from offline data. After removal of barcodes and primer sequences, reads were spliced using FLASH  to obtain Raw Tags. According to the QIIME tag quality control process , Raw Tags were strictly filtered to obtain high-quality tags (Clean Tags). The final effective data were obtained by removing chimera sequences (Effective Tags).The cetyltrimethylammonium bromide (CTAB) method was used to extract genomic DNA from samples. The V3−V4 region of the 16S rRNA gene was amplified by PCR for 30 cycles using primers F (5′-http://www.drive5.com/uparse/) was used to cluster all effective tags of all samples. Sequences were clustered into operational taxonomic units (OTUs) using a 97% identity threshold. According to the algorithm principle, the sequence with the highest frequency was selected as the representative sequence for each OTU. OTU sequences were annotated and analyzed using Mothur and the small subunit (SSU) rRNA database of SILVA132 (http://www.arb-silva.de/) with a threshold of 0.8 to 1. Taxonomic information was obtained, and the community composition of each sample was determined at each taxonomic level . The phylogenetic relationships of all OTUs were determined using MUSCLE software  to perform rapid multiple sequence alignment. Finally, data for each sample were normalized, and the sample with the least amount of data was used as the standard. Subsequent alpha and beta diversity analyses were based on the normalized data.Uparse software  was used to calculate uniformity indices , richness indices , and the abundance-based coverage estimator (ACE1). R software (version 2.15.3) was used to draw dilution, rank abundance, and species accumulation curves, and to analyze differences in alpha diversity between groups.2O, and 3 PBS samples. These blank control samples were used for bacterial genomic DNA extraction and sequencing using the same laboratory, equipment, and batch of reagents and consumables. Possible contamination based on the top 10 OTUs of negative controls was eradicated from the specimen sequence library.To eliminate possible contamination, quality control methods were implemented. OTUs with relative abundance (RA) <0.1% were filtered out. Furthermore, 16 negative controls were tested, including 10 swabs, 3 ddHPathogenic bacterial species from lower respiratory tract samples  and blood of severe patients were isolated and identified  using wh2 test with a row × column table (McNemar’s test). Differences in the number of bacteria were analyzed by a nonparametric test of independent samples using SPSS 11.5 software. Differences were considered significant at P < 0.05.The rates of subsequent bacterial infection between severe and mild cases were compared using the χhttps://www.ncbi.nlm.nih.gov/sra) and can be accessed through the BioProject ID PRJNA830536.Data are available in a public, open access repository. All sequence data from this study has been submitted to Sequence Read Archive (


Malaria in human immunodeficiency virus (HIV)-positive patients is an ever-increasing global burden for human health. The present meta-analysis summarizes published literature on the prevalence of malaria infection in HIV-positive children, pregnant women and adults.2 index and Cochran’s Q test. Publication and population biases were assessed with funnel plots, and Egger’s regression asymmetry test.This study followed the PRISMA guideline. The PubMed, Science Direct, Google Scholar, Scopus and Cochrane databases were searched for relevant entries published between 1 January 1983 and 1 March 2020. All peer-reviewed original papers evaluating the prevalence of malaria among HIV-positive patients were included. Incoherence and heterogeneity between studies were quantified by the I+ (cluster of differentiation 4) < 200 cells/µl and age < 40 years were associated with a significant increase in the odds of malaria infection . Antiretroviral therapy (ART) and being male were associated with a significant decrease in the chance of malaria infection in HIV-positive adults . In pregnant women with HIV, CD4+ count < 200 cells/µl was related to a higher risk for malaria infection .A total of 106 studies were included in this systematic review. The average prevalence of malaria among HIV-positive children, HIV-positive pregnant women and HIV-positive adults was 39.4% , 32.3% (95% CI = 26.3–38.6) and 27.3% (95% CI = 20.1–35.1), respectively. In adult patients with HIV, CD4+ count of < 200 cells/µl was a considerable risk factor for malaria infection.This systematic review demonstrates that malaria infection is concerningly common among HIV-positive children, pregnant women and adults. Among HIV-positive adults, ART medication and being male were associated with a substantial decrease in infection with malaria. For pregnant women, CD4The online version contains supplementary material available at 10.1186/s13071-022-05432-2. Plasmodium spp. infections are uncertain [Infectious diseases pose a concerning threat to the health systems of both developed countries and countries with limited resources such as, for example, sub-Saharan countries , 2. Withncertain , 4. Apprncertain , 6.Plasmodium parasites causing human malaria are transmitted mainly by mosquitoes (Anopheles spp.) serving as biological vectors, malaria can also be transmitted directly via blood transfusion, needle sticks with contaminated needles and vertical transmission [The human immunodeficiency virus (HIV) is an emerging infectious disease agent defined by cellular immune system impairment . HIV is smission , 10. Thesmission . Since Hsmission –15. Thersmission , 16. Thesmission . Since tsmission , 19.Although numerous studies have highlighted malaria prevalence in patients with HIV, there has been no comprehensive meta-analysis to demonstrate this prevalence in children, adults and pregnant women. Therefore, the aims of this systematic review and meta-analysis are to summarize malaria prevalence among HIV-positive children, pregnant women and adults, and to identify risk factors that increase the probability of HIV-positive patients being infected with malaria.Plasmodium” AND “prevalence” OR “epidemiology” OR “co-infection” AND “HIV” OR “AIDS” OR “acquired immune deficiency syndrome” OR “immunocompromised” OR “immunosuppressed” OR “immunodeficiency” AND “pregnancy women” OR “children” OR “adult” alone OR combined using “OR” and/or “AND”.For inclusion in the present systematic review, the PubMed, Science Direct, Google Scholar, Scopus and Cochrane databases were searched for relevant English-language, full-text articles and abstracts published between 1 January 1983 (date of HIV discovery) and 1 March 2020. As the aim was to evaluate the prevalence of positive test results for malaria among HIV-positive and HIV-negative individuals, the following Medical Subject Headings (MeSH) terms were used: “Malaria” OR “n > 10). Any article that did not satisfy the above criteria were excluded. The reference lists of the eligible articles were also browsed manually to identify relevant papers that were not initially identified in the database search. Finally, details of each study were extracted using a data extraction form, including country, year of publication, first author, number of HIV+ and malaria-positive cases, education status of patients, alcohol consumption status, number of partners, marital status, level of CD4+ (cluster of differentiation 4) in HIV-positive patients, ART  status, sex protection status and diagnostic method . The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to report the findings [After an initial search of the databases, subject-related topics and their abstracts were double-checked, and then full texts of potentially eligible articles were selected for downloading. All potentially relevant full texts were reviewed by three independent reviewers . Discrepancies were resolved by discussion and consensus. The studies were assessed for quality using the Joanna Briggs Institute (JBI) checklist  was used for analysis. The heterogeneity among subgroups was tested by meta-regression analysis. The relationship between prevalence, year of publication and sample size was estimated by meta-regression. Additionally, a funnel plot relying on the Egger’s regression asymmetry test was used to assess the small effects of the study and the population bias. For the meta-analysis, the included studies were evaluated as a random sample of each study population, and the analyses were performed using StatsDirect (version 2.7.2) statistical software .The point estimate and corresponding confidence interval (CI) for the prevalence of malaria in HIV-positive individuals for each study were calculated. Incoherence and heterogeneity among studies were assessed using the In = 103) and Asia (n = 3). The inclusion/exclusion criteria at each step of screening and eligibility and the number of selected papers are shown in Fig. The systematic search of the electronic databases identified 24,311 potentially relevant papers. The full-text of 212 articles was assessed, resulting in exclusion from the study of 106 papers due to their small sample size, the review or case report nature of the report, duplication and insufficient data. The remaining 106 papers fulfilled the inclusion criteria and were included in the present systematic review and meta-analysis. All of these 106 articles were published between 1983 and 2020 and present data from malaria-endemic regions in Africa . In adult HIV-positive patients, age < 40 years old was found to be associated with a significant increase in the odds of being infected with malaria . Also, for adult HIV-positive patients, being male and being treated with ART medication have been associated with a significant decrease in the odds of being infected with malaria . CD4+ count < 200 cells/µl was found to predispose pregnant women with HIV to malaria infection  , 27.3% (95% CI = 20.1–35.1) and 32.3% (95% CI = 26.3–38.6), respectively. In adult patients with HIV, receiving ART and having CD4+ count > 200 cells/µl were two factors significantly associated with malaria infection (P < 0.05).Although extensive studies have been conducted on both HIV and Due to widespread ART coverage, mortality due to HIV as the main cause of death has decreased drastically over the years . NotwithAlthough the incidence of malaria and mortality due to malaria declined significantly by 62% and 41%, respectively, between 2000 and 2015, WHO reported that malaria remained an endemic disease in 76 countries at the beginning of 2016 , with ap+ cell numbers is associated with attenuation of the cell immune system and an increased vulnerability to being infected with other infections [+ cell count < 200 cells/µl is linked to increased susceptibility to malaria infection  confirms this association. In essence, AIDS and malaria are each controlled by adaptive and innate immune mechanisms, and declining immunity caused by HIV infection will cause an increase in malaria severity. CD4+ cells are depleted by the HIV virus, which leads to an impaired immune response to many pathogens, including Plasmodium spp. [+ T cell count ≥ 500/µl, between 200 and 499/μl and < 200/μl was 57, 93 and 140 per 1000 person-year, respectively, in Uganda. It has been postulated that HIV increases malaria incidence in adults based on CD4+ cell count categories [According to the results of this systematic review and meta-analysis, the majority of published HIV/malaria studies to date have been in African countries. Socioeconomic conditions and a desirable climate for the biological vector, both of which can facilitate malaria transmission, may be the main reasons underlying this result . Based ofections . Our finium spp. . This paium spp.  who obsetegories .Plasmodium-infected red blood cells in the placental intervillous space, termed ‘placental malaria.’ The placenta is also the key interface in mother-to-child transmission of HIV, especially that involving in utero transfer [+ cell count and the probability of malaria infection (P > 0.05), possibly due to the small number of studies that have considered this factor.This meta-analysis also revealed the worrying situation of malaria infection among HIV-positive children. Approximately 39.4% of HIV-positive children in the analyzed studies were infected with malaria. This is a much higher prevalence than that observed in several studies investigating general children populations in African countries, with the prevalence in these studies ranging from 1% in Kenya to 22% in Uganda, with 14.5% prevalence in Tanzania and 20% in the Democratic Republic of Congo , 135. Thtransfer . No rema. [+ cell count of < 200 cells/µl predisposes HIV-positive adults to Plasmodium spp. infection . However, the association between malaria and HIV is more complex than expected. Some studies have corroborated that CD4+ T cells, as the prime targets for reproduction by HIV-1, play a vital role in immune responses to malaria [+ cell activation, thus providing the ideal microenvironment for the spread of the HIV virus among the CD4+ cells. On the other hand, the selective infection of CD4+ cells by HIV leads to the loss of these cells [+ cells [The present meta-analysis reveals that, on average, 27.3% of HIV-positive adults are infected with malaria in endemic countries. One of the consequences of this alarmingly high figure can be manifested in blood transfusion. With the ever-increasing need for a blood transfusion due to environmental and heredity diseases such as sickle cell anemia , the pre.  reported malaria , 139. Mase cells . It is a[+ cells , 141.Plasmodium spp. . This is an interesting finding when compared to individual studies that described a higher risk of malaria infections in males compared to females in the general population in north-east Tanzania, irrespective of their HIV status [+ T cell counts or viral loads translate to accelerated HIV disease progression or death in areas of stable malaria transmission.Age < 40 years has also been associated with a significant increase in the chance of HIV-positive adults becoming infected with malaria . In HIV-positive adults, being male and receiving ART have been associated with a significant decrease in the risk of being infected with V status . Thus, iThis is the first meta-analysis on malaria prevalence among HIV-positive patients. We broke down the data into three categories, namely infancy, pregnancy and adulthood, and identified the available risk factors for each group. Since there has been little research on the prevalence of malaria in HIV patients in malaria endemic areas, further studies are needed in this regard. Also, due to the incomplete data in the studies included in our meta-analysis, we were unable to evaluate some risk factors, including duration of illness, time of diagnosis and response to treatment. Unfortunately, no data on the health status of individuals having both malaria and HIV infection were provided in these studies. On the other hand, publication bias is one of the main concerns in systematic review studies. As expected, publication bias was observed in the analyzed studies. The main limitation of this systematic review and meta-analysis is related to the different study designs and varying laboratory methods used to determine infection status. Diagnostic methods have varying sensitivity and specificity and, therefore, the heterogeneous prevalence data reported may partially be caused by flaws in methodology. The use of an accurate, reliable and uniform diagnostic techniques would support the correct interpretation of results.+ cell count numbers in adults. Therefore, the related risk factors should be given appropriate attention in HIV/malaria co-infected patients. As HIV infection affects the host immune response, future studies are needed to elucidate the pathogenesis aspects of this co-infection, as well as the severity of its complications, and to investigate possible drugs and drug effectiveness.The current systematic review has revealed concerning prevalence data for malaria among HIV-positive persons, including children, adults and pregnant women. In view of the fact that malaria can quickly become a life-threatening condition in risk groups (e.g. people living with HIV), prevention, chemoprophylaxis, early diagnosis and treatment of clinical malaria are recommended. Recent information also indicates that malaria is associated with the availability of ART and CD4Additional file 1: Figure S1. Funnel plot of standard error by logit event rate to assess publication or other types of bias across prevalence studies. Studies based on the prevalence of malaria in HIV patients: children (A), adults (B), and pregnant women (C).Additional file 2: Table S1. Summary score for methodological quality of analytic cross-sectional studies.Additional file 3: Table S2. Summary score for methodological quality of analytic case–control studies.Additional file 4: Table S3. Summary score for methodological quality of analytic cohort studies.Additional file 5: Table S4. Summary score for methodological quality of analytic RCT studies.


We aimed to evaluate the outcomes of post-traumatic acute respiratory distress syndrome (ARDS) in young patients with and without Extracorporeal membrane oxygenation (ECMO) support. A retrospective analysis was conducted for trauma patients who developed ARDS at a level I trauma facility between 2014 and 2020. Data were analyzed and compared between ECMO and non-ECMO group. We identified 85 patients with ARDS . The two groups were comparable for age, sex, injury severity score, abbreviated injury score, shock index, SOFA score, and head injury. Kaplan Meier survival analysis showed that the survival in the ECMO group was initially close to that of the non-ECMO, however, during follow-up, the survival rate was better in the ECMO group, but did not reach statistical significance . Multivariable logistic regression analysis showed that acute kidney injury (AKI)  and brain edema  were independent predictors of mortality. Sub-analysis showed that in patients with severe Murray Lung Injury (MLI) scores, non-ECMO group had higher mortality than the ECMO group . Although ARDS is uncommon in young trauma patients, it has a high mortality. ECMO therapy was used in a quarter of ARDS cases. AKI and brain edema were the predictors of mortality among ARDS patients. ECMO use did not worsen the outcome in trauma patients; however, the survival was better in those who had severe MLI and ECMO support. Further prospective study is needed to define the appropriate selection criteria for the use of ECMO to optimize the outcomes in trauma patients. Around 10–20% of polytrauma patients may develop severe respiratory complications which necessitate ventilatory support4. Among such patients, acute respiratory distress syndrome (ARDS) remains a challenging complication which may occur in 6.5% of patients requiring mechanical ventilation for greater than 48 h5. Notably, ARDS is multifactorial that could be related to direct thoracic trauma and/or indirect injury caused by extrapulmonary trauma and its management such as massive transfusion, fluid overload, and ventilator-induced acute lung injury6.Trauma is the frequent cause of mortality in severely injured young patients secondary to hemorrhagic shock and cardiopulmonary dysfunction. Therefore, controlling active bleeding and maintaining arterial oxygenation are essential to improve the patients’ outcome9. For instance, it is challenging to apply adjunctive measures such as prone positioning with conventional ventilator management strategies for ARDS in patients with brain, spine, or pelvic injuries. Moreover, permissive hypercapnia may be difficult to effectively manage ARDS in patients with traumatic brain injury10.Despite advances in pulmonary critical care management with adoption of lung protective ventilation, the mortality rate remains high among trauma patients with ARDS (17–46%)11. Some studies have reported survival rates between 50–79% after the utilization of ECMO in trauma15. Although, the use of ECMO in non-trauma setting continues to expand, its utility in trauma patients remains controversial or inaccessible in many centers. Limited resources, bleeding, thrombosis, limb ischemia, traumatic brain injury, complicated pelvic fractures, major vascular injuries, and lack of technical expertise are the major factors affecting the widespread use of ECMO in trauma patients16. The use of ECMO in trauma patients is recently adopted in selected cases in our trauma center at Hamad Medical Corporation (HMC). To date, data on the use of ECMO in trauma patients are underreported in our region in the Arab Middle East. The present study aims to evaluate the outcomes of post-traumatic ARDS in young patients with and without the use of ECMO in a level-1 trauma center and to look for the role of acute kidney injury (AKI) in those patients as well. We hypothesized that the use of ECMO in trauma patients with ARDS is associated with better outcomes.Extracorporeal membrane oxygenation (ECMO) has been used as a salvage therapy in patients with unsuccessful or unsatisfactory conventional ventilatory support. It is effective in treating hypoxic respiratory failure caused by traumatic lung injury. This may be related to the benefit of warming, correction of acidosis, better oxygenation, and circulatory support2O and bilateral pulmonary infiltrates that are not entirely caused by cardiac failure17. Inquired data from the trauma registry included patient demographics, mechanism of injury (MOI), diagnoses, hemodynamic parameters, Glasgow coma scale (GCS), injury severity score (ISS), abbreviated injury scale (AIS) and associated injuries. Type of cannulation [veno-venous (VV) or veno-arterial (VA)], time from admission to ECMO, exploratory laparotomy, tracheostomy, thoracotomy, open reduction and internal fixation (ORIF) surgery, external fixation, intracranial pressure (ICP) monitoring, craniectomy, angioembolization, ventilatory days, ICU and hospital length of stay, complications and outcomes were recorded. Complications included sepsis, limb ischemia, disseminated intravascular coagulation (DIC), deep vein thrombosis (DVT), pulmonary embolism (PE), AKI, cerebrovascular accident (CVA), multiorgan failure (MOF), ventilator associated pneumonia (VAP), thrombocytopenia, and bleeding. Traumatic injuries were defined according to ICD-9 codes.A retrospective analysis of trauma patients who developed and treated for severe ARDS at the level I trauma facility at Hamad Medical Corporation between January 2014 and January 2020 was conducted. Medical records of adult patients of all genders with severe ARDS were reviewed. All ARDS patients were diagnosed based on the Berlin definition of hypoxemia PaO2/FIO2 < 200, FiO2 0.8–1.0, positive end-expiratory pressure ≥ 5 cm HThe primary outcome measure of the study was 30-day post-admission and > 30-day follow-up mortality.Secondary outcome measures included AKI in addition to hospital length of stay (LOS), ICU-LOS, ventilator days and multiorgan failure (MOF).18. MOF was defined as physiological abnormalities with dysfunction (reversible or irreversible) of two or more organs  and heart) that occurs simultaneously leading to longer stay in the intensive care unit and high risk of mortality20.AKI was defined according to the Kidney Disease Improving Global Outcomes (KDIGO) criteria22. The respiratory ECMO survival prediction (RESP) scores were calculated for each patient, which ranges between − 22 and 15. The survival rate varies according to RESP score from 92% in RESP class I, 76% class II, 57% class III, 33% class IV and 18% class V23. Also, Murray Lung Injury (MLI) scores were determined at the time of severe ARDS diagnosis; a MLI score of 3.0 or greater suggests that the patient is hypoxic and may benefit from ECMO support24.Shock index (SI), abbreviated injury score (AIS), Injury severity core (ISS), and Sequential Organ Failure Assessment (SOFA) score. SI was defined as admission heart rate divided by systolic blood pressure ARDSNet protocol goals were used as a general guideline for oxygenation, ventilation, pH, and airway pressure management. Initial modes of ventilation included both volume control and pressure control modes to maintain lung-protective ventilation . Additional adjuncts were initiated as deemed appropriate by the trauma and ECMO intensivist before the initiation of ECMO. The adjuncts included muscle relaxant, nitric oxide, and/or reverse I/E ventilation and prone positioning. Patients who were selected for ECMO therapy were those with severe ARDS and persistent hypoxia despite maximal mechanical ventilator support with or without adjuncts. All patients treated with ECMO for refractory hypoxia were transferred from the trauma intensive care unit to the medical intensive care unit. In case of traumatic brain injury (TBI), no heparin was given for 48–72 h post-trauma..This observational study has received expedited review and was approved by the Institutional Review Board, Medical Research Center (MRC-01-20-503) at Hamad medical corporation (HMC), Doha, Qatar which waived the need of informed consent due to retrospective nature of the study. All methods were performed in accordance with the relevant guidelines and regulations. Informed consent was not required as data were retrospectively and anonymously collected and kept confidential without direct contact with the patientsData were expressed as numbers, percentages, mean ± standard deviation or medians with range, whenever appropriate. Chi-square test was performed for the analysis of differences in categorical variables between ECMO vs. non-ECMO groups, and Fisher exact test was used when the observed cell values were < 5. The continuous variables between different groups were compared using student’s t test and the two-tailed p values < 0.05 were considered as significant. The ECMO group was matched with the non-ECMO group (1:3 matching ratio) in terms of age, sex, ISS and AIS. Multivariable logistic regression analysis was performed for predictors of mortality among trauma patients with ARDS using the following variables: age, ISS, GCS, SI, Murray score, ECMO use, sepsis, brain edema, extra-axial hematoma, and AKI. Data were expressed as odds ratio and 95% confidence interval (CI). Kaplan–Meier survival curve was used to analyze ‘time-to-event’ data. The outcome (event) was all-cause mortality. Data analysis was carried out using the Statistical Package for Social Sciences version 26 .During the study period, a total of 85 patients with severe ARDS (22 patients were treated with ECMO and 63 matched patients were managed without ECMO) were included in the study (1:3 matching ratio). Seventy-eight (91.8%) patients were males and the mean age of the cohort was 34.3 ± 14.9 years. The mean SI and ISS were 1.05 ± 0.47 and 30.4 ± 13.6, respectively . The overall mortality was 41.2% (57% within 30-day post-admission and 43% during follow-up period).VV ECMO was the main technique in the ECMO group except one, who received VA ECMO Table . Median There was no statistically significant difference between the two groups regarding age, MOI, SI, ISS, SOFA score, TBI, and AIS for head, chest, abdomen and pelvis Tables  and 3. WMLI score showed significant difference between the two groups . According to MLI score, ECMO group showed higher rate of severe lung injury  in comparison to non-ECMO group  , higher ICU length of stay (27.5 vs.17.5 days) and longer hospital LOS (39.5 vs. 25 days). Almost half of ECMO cases were transferred to long-term rehabilitation whereas, one third of non-ECMO cases did.The rate of AKI was higher in ECMO group   whereas, the pattern of mortality during follow-up period was reversed with a higher rate noticed among ECMO group (62.5% vs 37%). The differences in mortality were not statistically significant (Table Table According to Murray Lung Injury score (severe vs. mild-moderate lung injury), the rate of mortality was compared in Fig. This is a unique study from a rapidly developing country to evaluate the clinical characteristics, complications, and mortality in young patients with post-trauma ARDS managed with ECMO support versus conventional mechanical ventilation. During the study period, the rate of ARDS in trauma patients was 0.9%, of which one quarter of cases underwent ECMO therapy. Almost, one third of the ECMO group died with severe head injury whereas two thirds of non-ECMO died with head injury. The overall mean SOFA score (9.3 ± 3.4) and on-admission shock index (1.05 ± 0.47) were high which indicates the potential unfavorable outcome. MLI scoring was significantly higher in the ECMO group. The MLI scoring showed that ECMO use was associated with significantly higher survival in patients with severe lung injury than non-ECMO severe MLI group.25. In our cohort, the overall rate of mortality was 41% and the presence of brain edema and AKI were found to be the independent predictors of mortality. The 30-day survival rate was relatively better in the ECMO group and the long-term survival was better in the non-ECMO group, however these differences in survival were statistically not significant. Our findings indicate that early ECMO (≤ 2 days) was associated with better survival in comparison to delayed ECMO. The literature suggested an overall survival rate after VV ECMO in trauma patients ranges from 50 to 79%15 which agrees with our findings (64%). Also, Guirand et al.26 showed that ECMO was independently associated with improved survival as compared to the conventional ventilation matched group (age and ISS), however, acute intracranial hemorrhage patients were excluded from this study. An earlier study by Bosarge et al.27 reported significant reduction in mortality among the ECMO group (13.3%) compared to the conventional (64.3%) which were matched for age, ISS, TBI, SOFA and MLI scores. Similarly, an observational study reported significantly higher ICU and hospital survival rates in the traumatic extracorporeal life-support (ECLS) cohort as opposed to the non-traumatic ECLS group28. In contrast with our findings the EOLIA trial29, showed that patients with severe ARDS had no significant reduction in 60-day mortality from early ECMO, as compared to conventional mechanical ventilation.The selection of candidates for ECMO is challenging for intensivists due to heterogeneous patient population and the availability of expert team. Moreover, early identification of risk factors of mortality and analysis of long-term outcomes of survivors are necessary to predict the prognosis27 showed shorter mean ventilatory days were (7.5 ± 8.4 days) and patients were transitioned to ECMO in a relatively shorter period. Over 59% of our patients had ECMO started within 48 h of admission. On the contrary, in a study of 7 trauma patients by Strumwasser et al.30, the survivors had ECMO initiated later than non-survivors (15 vs 7.8 days).The ELSO registry study12, demonstrated the mean duration of extracorporeal life support was 8.8 ± 9.5 days which is slightly higher [median 9.5 (1–29) days] in our cohort.In our cohort, the duration of mechanical ventilation, ICU and hospital length of stay tends to be prolonged in the ECMO group. Contrarily, Bosarge et al.32. The mortality of AKI patients while on ECMO is around 62–68%32. A recent study by Chen et al.33 showed a higher rate of all-cause mortality in patients with D-AKI (52.3%) as compared to those without D-AKI (33.3%). Also, the long-term mortality in patients survived > 90 days after hospital discharge was significantly lower in patients without D-AKI (22.0%) than those required long-term dialysis (50.0%).The incidence of AKI in trauma patients varies from 1 to 50% whereas its incidence in patients treated with ECMO ranges between 26 and 85% based on several factors related to patients profiles (age and comorbidity), AKI definition, the clinical scenario, and type of ECMO cannulation (AKI was higher with VA than VV)In our cohort, AKI was reported in 38.8% of cases (n = 33), of them 13 cases had ECMO. AKI was associated with higher mortality in patients with (54%) and without ECMO therapy (80%). The ECMO group with AKI had higher mortality in comparison to those without AKI (11%).34. In the present study, over 81% of patients in the ECMO group had risk Class IV-V.Several studies have shown that the RESP score is a useful tool for prediction and discrimination of survival probabilities in ARDS patients treated with ECMO35. It has been suggested that the long-term functional limitation in ARDS survivors is not related to the degree of pulmonary dysfunction at admission, but rather to the consequences of invasive treatment at ICU and severity of illness36. In our study, 18% of ECMO and 25% of non-ECMO group were discharged home, while higher proportion of patients from ECMO group (50%) were transferred to long-term facility with variable degree of disability as opposed to non-ECMO group (25.4%). Swol et al.12 reported ECLS survivors, 23% were discharged home, 19% were transferred back to the referring hospital, and 58% were discharged to another facility.Comparison of the long-term outcomes of ARDS patients treated with ECMO and conventional ventilation strategies showed no significant difference in the 1-year survival, but the non-ECMO group had greater impairment of health-related quality of life38. Also, nosocomial infections are common in ECMO patients which ranges from 11.7–64%40. Occurrence of limb ischemia is an uncommon event in trauma patients12 which is also evident from our findings (1.2%). Luyt et al.41 reported cerebral bleeding (7.5%) and ischemic stroke (2%) as the neurological events in brain injury patients on VV-ECMO. However, in the present study, overall stroke was reported in 4 patients (4.7%), with only one patient in the ECMO group (4.5%).In our cohort, VAP, sepsis, gastrointestinal bleeding and thromboembolic events such as PE and DVT were the frequent in-hospital complications. Our findings are consistent with the previous studies reported bleeding, nosocomial infection and thromboembolic events as ECMO-related complications. Bleeding occurs in about 20–40% of patients on ECMO with various degrees of severity1. Parker et al.5 found that only the presence of hemorrhagic shock at admission was significantly associated with mortality in patients requiring ECMO, and not the age or TBI. However, ISS and admission shock index were not found to be independently associated with mortality in our study. The number of pre-ECMO organ dysfunctions has been used as an important prognostic factor. In previous studies, SOFA score was used as a surrogate for organ failure and pre-ECMO central nervous system dysfunction was associated with poor outcome in the RESP score43. Cheng et al.44, demonstrated that in adult VV-ECMO patients, pre-ECMO SOFA score > 9, ventilatory day > 4 and immunocompromised status were independent predictors of mortality. However, the mean SOFA score was comparable in patients with and without ECMO in our study.In our study, the presence of brain edema and AKI were found to be the independent predictors of mortality. While other studies suggested that ISS > 35 and refractory post-traumatic shock/cardiac arrest were independent predictors of hospital mortality1, studied TBI patients before ECMO. TBI was significant in 19 patients, and a heparin-free ECMO was provided to most patients. No TBI re-bleeding occurs, and only one in-hospital death was reported. In our study, 68% of ECMO group and 51% of non-ECMO group had TBI; no cerebral bleeding was observed but three patients with TBI died in ECMO group. According to the above-mentioned findings, ECMO with a heparin-free strategy seems to be safe in patients with minor or drained TBI1.The use of ECMO in patients with TBI remains controversial. Wu et al.This study has certain limitations that need to be addressed. It is a single center study with a retrospective nature and relatively small sample size. However, it is representative of the country as our trauma center is the only tertiary level 1 trauma center in the country that manages moderate to severe trauma cases including ECMO support (free of cost). Of note, the study cohort was younger in age compared with other studies. The study groups were matched for age, ISS, and AIS but not for MLI scoring, however, multivariable analysis and sub-analysis were performed to mitigate selection bias and to assess the impact of MLI on the outcome. ECMO was used in 3 cases with mild-moderate MLI because of difficulty of prone positioning in 1 abdominal injury case and difficulty in optimizing ventilatory setting in 2 cases with significant head injury. In addition, due to lack of standard treatment algorithm, some patients in both groups have received various treatments at the discretion of the attending physician. In the non-ECMO group, only 5 cases had official referral/consultation to the ECMO team which declined the ECMO support because of poor prognosis. Therefore, the reason of not using ECMO in the rest of the control group was not clearly stated in the data. Also, health-related quality of life post-discharge was not addressed.Although ARDS is uncommon in trauma patients, it has high mortality. ECMO therapy was used in a quarter of ARDS cases. AKI and brain edema rather than ECMO use were independent predictors of mortality in trauma patients with ARDS. Of note, even with associated TBI, trauma patients generally tolerate ECMO therapy. Moreover, ECMO use was associated with better survival in patients with severe lung injury according to MLI scoring. Further prospective study is needed to define the appropriate selection criteria for ECMO use, treatment algorithms and strategies in order to optimize outcomes in trauma patients who developed ARDS.