To analyze the clinical characteristics of patients with pancreatic cancer (PC) and diabetes and to explore the impact of diabetes duration, weight loss, and hypoglycemic drugs on the tumor biological behavior of PC.This is a retrospective study on patients with PC and diabetes. Subjects were grouped according to the onset age of PC, distant metastasis, duration of diabetes, degree of weight loss (∆Wt), and type of hypoglycemic drugs. Logistic regression analysis was used to evaluate the association between diabetes duration, weight loss, hypoglycemic drugs, and early‐onset PC, distant metastasis.p < 0.001), smoker, drinker, and more obvious weight loss . Patients with remote metastasis had an earlier diagnosis age, heavier weight loss, lower body mass index, and were more likely to be smokers but had cancer less likely to be localized in the head of pancreas. Regression analysis showed that new‐onset diabetes and weight loss were independently correlated to early‐onset PC: odds ratio (OR) = 3.38 , p = 0.003, respectively. In contrast, long‐term diabetes, and heavy weight loss were independently associated with remote metastasis: OR = 3.38 , p = 0.003, respectively.Compared with late‐onset PC, patients with early‐onset PC had a higher proportion of new‐onset DM (35 [79.5%] vs. 217 [46.9%], New‐onset diabetes and weight loss were common presentation and risk factors of early‐onset PC, which required more attention. Long‐term diabetes and heavy weight loss were risk factors contributing to distant metastases, indicating potential risk factors contributing to the adverse prognosis of patients with PC. HighlightsNew‐onset diabetes and weight losses were common presentation and risk factors of early‐onset PC, which required more attention.Long‐term diabetes and heavy weight loss were risk factors contributing to distant metastases and less radical surgery, which needed to be better treated. The degree of weight loss often reflects the rate of progression and degree of tumor’s malignancy. PC is highly malignant and is the fourth leading cause of tumor death in the United States, with a 5‐year survival rate less than 9%.In addition to the close relationship between DM and PC, many studies have found that antidiabetic drugs also affect the risk and survival of PC. Studies have shown that taking metformin reduced the risk of PC while taking sulfonylurea or insulin and its analogs significantly increased the risk of PC.In this study, we collected data of patients diagnosed with PC and DM in Peking Union Medical College Hospital in the past 35 years to analyze the clinical characteristics and tumor biological behavior of these patients. We grouped the populations according to the onset age of PC, with or without remote metastasis, duration of DM, the degree of weight loss, and the type of antidiabetic drugs. We tried to explore the impact of different risk factors on PC prognosis from the perspective of effects on tumor biological behavior.22.1n = 293), tumor recurrence(n = 7), or diagnosed with pancreatic tumor other than pancreatic ductal adrenal carcinoma , including intraductal papillary‐mucinous neoplasms (n = 25), pancreatic neuroendocrine tumors , mucinous cystic neoplasms (n = 12), cystadenocarcinoma (n = 5), adenosquamous carcinoma (n = 4), mucinous adenocarcinoma (n = 3), pancreatic small cell carcinoma (n = 2), multiple endocrine neoplasia, type1 (n = 1), acinar cell carcinoma (n = 1), and pancreatic polypeptide tumor (n = 1). Finally, 521 cases with histopathological confirmed PDAC with T2DM were included in this study , gestational diabetes (GDM), and other special types of DM, a total of 890 cases of PC with T2DM were retrieved. Data were collected by reviewing their medical records. Then patients were excluded who had incomplete data (2.22) was calculated by dividing body weight (kg) by the square of height (m). Weight loss was collected through medical records, and weight before PC onset was calculated by current weight plus weight loss. BMI before onset of PC was calculated by using a similar formula. Information about smoking, drinking, past medical histories like hypertension, dyslipidemia, chronic pancreatitis, and medication history, including antihypertensive drugs, lipid‐lowering drugs, and hypoglycemic drugs, as well as family histories like DM, PC, and other cancers, were collected. Glycosylated hemoglobin (HbA1c) and fasting blood glucose (FPG) was obtained to assess blood glucose control.Data were collected by searching electronic and paper medical records. Basic information including age, gender, height, body weight was obtained, and body mass index  staging, surgical methods, pathological grade, chemotherapy, and tumor markers like carbohydrate antigen 199 (CA 19‐9), carcinoembryonic antigen (CEA), and carbohydrate antigen 242 (CA 242). The tumor’s size was obtained through the enhanced computed tomography scan of the abdomen or observations in the operation records. Tumor staging was assessed according to the eighth edition staging criteria of the American Joint Committee on Cancer. The types of surgery were divided into radical surgery and palliative surgery. Radical surgery includes pancreaticoduodenectomy, distal pancreatectomy, and total pancreatectomy. Palliative surgery was performed to relieve obstructive or compression symptoms when patients were intolerant to radical surgery. The pathological classification was made according to the differentiation of tumor cells and was divided into three grades: well differentiated, moderately differentiated, and poorly differentiated.2.4Early‐onset PC was defined as the onset age of PC less than 50 years old. Because of the rapid progress and short medical history of PC, the onset age of PC was considered equal to the diagnosis age. Thus, patients were grouped into two groups according to the onset age of PC: early‐onset PC (onset age less than 50 years old) and late‐onset PC (onset age more than 50 years old). DM was defined as one of the following: FPG ≥ 7.0 mmol/L, oral glucose tolerance test 2 h plasma glucose ≥11.1 mmol/L, previously diagnosed DM, or antidiabetic treatment already prescribed. T1DM, GDM, and other types of DM were excluded. New‐onset DM was defined as diabetic duration within two years, and long‐standing DM was defined as a diabetic duration for more than two years. Patients were divided into two groups according to the median weight loss of the overall population (5 kg): heavy weight loss group (ΔWt ≥5 kg) and the control group with slight or no weight loss (ΔWt < 5 kg). The assessment of antidiabetic drugs includes four drugs: metformin, α‐glycosidase inhibitors (AGI), sulfonylureas, and insulin. Patients were categorized as user or nonuser group according to these four antidiabetic drugs. Other medications  were less commonly used by these patients and, therefore, were not included in the analyses.2.5t test was used to assess differences between groups. Nonnormally distributed data were expressed as the median , and differences between groups were assessed using the Mann‐Whitney U test. Categorical variables were expressed as counts/percentiles (%), and Pearson’s χ2‐test was used to compare the difference between groups. Multivariable logistic regression analysis with forward variable selection procedure was conducted to explore the effect of variable factors, including DM duration, weight loss, and antidiabetic drugs on early‐onset PC, remote metastasis, and radical surgery. Confounding factors like age, gender, BMI, smoking, alcohol, FPG, hypertension, dyslipidemia, and family history of PC and DM were adjusted. All statistical analyses were performed using IBM SPSS Statistics 23.0 . A p value <0.05 was considered significant.Normality was assessed for all continuous variables. Normally distributed data were expressed as the mean ± SD, and Student’s 33.1p < 0.001), though the BMI was similar between the two groups. More patients with early‐onset PC were smoker and drinker and were more likely to had family history of PC and DM than those with late‐onset PC. Compared with late‐onset PC patients, those with early onset age suffered larger tumor size . A higher proportion of PC patients with early‐onset age received chemotherapy, whereas a lower proportion of those patients underwent radical surgery, though with no statistical significance . The level of CA 19‐9, CEA, and CA 242 was higher in the metastatic group than the localized group . The proportions of antidiabetic drugs, including metformin, AGI, sulfonylureas, and insulin, were significantly higher in the long‐term DM group than in the new‐onset DM group. Patients with long‐term DM were more likely to have hypertension and dyslipidemia and take medications like antihypertensive drugs and lipid‐lowering drugs than the new‐onset DM group . In terms of tumor related characteristics, compared with the control group, more patients in the heavy weight loss group had distant metastasis and advanced TNM stage, and fewer patients underwent radical surgery   kg, whereas the median weight loss in the control group was 0  kg. Compared with the control group, the heavy weight loss group had lower BMI, higher proportion of smoker and drinker, earlier diagnosed age of PC, higher proportion of early‐onset PC, shorter duration of DM, and higher proportion of new‐onset DM. Concerning the use of hypoglycemic drugs, metformin was more common in the heavy weight loss group than in the control group  .The regression analysis showed that new‐onset DM and weight loss were independent risk factors for early‐onset PC. This is consistent with another study showing that the duration of DM is positively correlated with the onset age of PC.Some researchers have proposed a PC risk prediction model in patients with new‐onset DM, a high‐risk population of PC. The risk of PC can be calculated and predicted based on the patient’s age, BMI, change of BMI, smoking, medication, and other biochemical indicators to calculate the risk of PC.The regression analysis in this study showed that long‐term DM was an independent risk factor for distant metastasis and reduced chance of radical surgery, suggesting that long‐term DM may be a poor prognostic risk factor for patients with PC. This is consistent with the results of a study that included three prospective cohorts. In this study, the author found that long‐term DM reduced the overall survival of patients with PC, whereas new‐onset DM had no adverse effect on the overall survival.Weight loss is a common clinical manifestation of PC. The causes of weight loss include malnutrition caused by anorexia and pancreatic enzyme deficiency and cachexia caused by metabolic changes and inflammation.Different hypoglycemic drugs have different effects on tumor biological behavior. Patients taking metformin were more likely to have a less malignant tumor, including smaller tumor size, earlier TNM stage, and lower proportion of distant metastasis. This is consistent with other studies showing that patients with PC taking metformin have better overall tumor survival than those not taking metformin.Limitations and disadvantages: this study is a cross‐sectional study, which can only infer the correlation but could not determine the causal relationship. Therefore, cohort studies are needed to explore the influence of DM duration and weight loss on onset age and tumor biological behavior with PC. Besides, all the patients included in this study were diagnosed with PC and DM, but patients without PC and DM were not included. In addition, because of the cross‐sectional study, we could not access the survival and prognosis of patients with PC directly but only to assess the impact of factors on the biological behavior of tumors like onset age, distant metastasis, and radical surgery rate to infer the effects on tumor prognosis indirectly.In summary, new‐onset DM and heavy weight loss were both common manifestations and independent risk factors of early‐onset PC. Therefore, it is necessary to pay special attention to the potential possibility of PC in newly diagnosed DM with obvious weight loss, especially those with other risk factors of PC. Long‐term DM and heavy weight loss might increase the risk of distant metastasis, reduce the chance of radical surgery, and thus may have adverse effects on the prognosis of patients with PC.The authors declare no conflict of interest.Appendix S1. Supplementary InformationClick here for additional data file.


C9orf72 account for a large proportion of cases of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration. There have been occasional reported cases associated with this expansion but also additional extrapyramidal clinical features. However, only very rarely has there been pathological confirmation of a parkinsonian syndrome associated with a C9orf72 repeat expansion. To date, as far as we are aware, there have been no reported pathologically confirmed cases of ALS with C9orf72 mutation and multiple system atrophy (MSA). We report a case of a man who initially presented with extrapyramidal features, including cogwheel rigidity, and, therefore, was clinically considered likely to have Parkinson's disease or a parkinsonian syndrome. Subsequent examination six months later revealed additional abnormal upper and lower motor neuron signs, raising the strong possibility of ALS. He had a rapid clinical decline and died 16 months after the first presentation. It was noted that his father also had ALS, and that his mother had a parkinsonian syndrome, suggestive of progressive supranuclear palsy. The macroscopic and microscopic examination of the brain and spinal cord revealed ALS pathology with neuronal loss, especially of the anterior horns of the cord and the motor cortex. This was associated with numerous neuronal cytoplasmic inclusions immunoreactive for phosphorylated transactivation response DNA‐binding protein of 43 Da (TDP43). There were additional pathological features, including p62‐immunoreactive cerebellar neuronal cytoplasmic inclusions, fully in keeping with a C9orf72 repeat expansion, and this was confirmed on molecular analysis. However, there was also α‐synuclein pathology in the form of oligodendroglial cytoplasmic inclusions in the basal ganglia, cerebellum, and brainstem, indicative of MSA. To our knowledge, this is the first reported case of pathologically confirmed combined ALS‐C9orf72 and MSA.Hexanucleotide repeat expansions in  C9orf72 gene (C9orf72) have been identified as a major cause of familial and sporadic amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD).C9orf72 repeat expansion type pathology. This to our knowledge is the first report of a pathologically proven case with this combination of diseases.Expansions of the hexanucleotide repeat GGGGCC in the A 60‐year‐old man first presented with a history of falls. On examination, the patient showed prominent extrapyramidal features with cogwheel rigidity and reduced pendulum of the right arm as well as slight torticollis and negative glabellar sign. There was no evidence of postural instability or cerebellar signs. A subsequent magnetic resonance imaging provided unremarkable results, because there was no hallmark “hot cross bun” sign in the pons on T2‐weighted images and no hyperintense signal of the putaminal rim. In addition, no cerebellar atrophy was noted. Dopamine transporter, so‐called DaT scan, revealed features consistent with loss of presynaptic dopaminergic terminals. This was supportive of a parkinsonian disorder, including Parkinson's disease (PD). Subsequent neuropsychological assessment only exposed mild behavioral changes with some attentive and visual memory problems. Further clinical examination six months later, however, revealed upper and lower motor neuron signs characterized by tongue fasciculation, wasting of intrinsic muscles, and spasticity and hyper‐reflexia of the upper limbs. The lower limbs showed bilateral extensor plantor response and increased muscle tone. Again, the patient showed none of the cerebellar signs, postural instability, or autonomic instability. There was no evidence of further cognitive decline, including frontotemporal dementia. Electromyography revealed marked denervation of striated muscles in bulbar, cervical, thoracic, and lumbar segments. Based on these observations, the patient was diagnosed as having ALS. He had previously been prescribed levodopa (L‐dopa), to which he had a poor response. Given the amended diagnosis, the patient's treatment was subsequently changed to riluzole. The patient's father had had ALS and had died within one to two years after the diagnosis. There was also a suggestion that his mother had had a parkinsonian disorder, possibly PSP, and died five to six years after the diagnosis. The patient had a brother who had had no known neurological abnormalities. However, no other familial information was available. The patient died 16 months after the first presentation, with the cause of death being stated as ALS. A limited postmortem was performed.The right half of the brain and some spinal cord segments were fixed in 10% buffered formalin. The left half of the brain and other spinal cord segments were frozen. The fixed right cerebral hemisphere weighed 709 g, and the right brainstem and cerebellum weighed 93 g. Macroscopic examination revealed mild cerebral atrophy with some moderate widening of the lateral ventricle. The basal ganglia, thalamus, and hippocampus appeared normal. Pigment was lost in the substantia nigra Fig.  and much2O2. Cell nuclei were counterstained with Harris' alum hematoxylin. The immunohistochemical findings are summarised in Table Microscopic samples were taken from the cerebrum, brainstem, cerebellum, and spinal cord. Formalin‐fixed, paraffin‐embedded sections were stained with hematoxylin and eosin (HE). Sections from the spinal cord and motor cortex were also stained with Luxol fast blue/cresyl violet, so‐called Klüver‐Barrera (KB). Section thickness was 14 μm for KB staining and 7 μm for other staining. On the relevant sections, immunohistochemistry was performed with primary antibodies against hyperphosphorylated tau (p‐tau) , p62 , α‐synuclein , amyloid‐β (Aβ) , transactivation response DNA‐binding protein of 43 kDa phosphorylated at serine residues 409 and 410 (p‐TDP43) , and glial fibrillary acidic protein (GFAP) . Sections were deparaffinized, rehydrated, and rinsed in phosphate‐buffered saline (PBS), pH 7.6and quenched for endogenous peroxidase activity. Leica BONDMAX  epitope retrieval sets were used for p‐TDP43 (ER1 for 30 min), tau (ER1 for 20 min), GFAP (ER1 for 5 min), and p62 (ER2 for 20 min). For both α‐synuclein and Aβ, 80% formic acid pretreatment for 1 h was used. After incubation with the primary antibodies followed by rinsing phosphate‐buffered saline (PBS), pH 7.6, sections were incubated with appropriate biotinylated secondary antibodies (Dako), followed by the avidin‐biotin‐enzyme complex using a Vectastain Elite ABC Kit . Finally, sections were incubated for 5–10 min with 0.5 mg/mL 3,3′‐diaminobenzidine  as the chromogen in Tris‐buffered saline (TBS), pH 7.6, containing 0.05% HC9orf72 repeat expansion. In addition, immunohistochemistry for α‐synuclein revealed several immunoreactive GCIs in the basal ganglia, especially the putamen, cerebellar white matter ).The spinal cord sections showed neuronal loss and gliosis of the anterior horn, including a surviving neuron containing Bunina bodies. The motor cortex and hypoglossal nerve nuclei showed mild‐to‐moderate neuronal loss and gliosis. The substantia nigra and the basal ganglia, particular the putamen, showed moderate neuronal loss and mild gliosis. By contrast, other regions, including the pontine nuclei and inferior olivary nuclei, appeared preserved. No significant gliosis was evident in the transverse pontine fibers. Both the Purkinje cell layer and granule cell layer of the cerebellum showed good preservation of the neurons. However, the cerebellar white matter, including the middle cerebellar peduncles, showed mild gliosis. In the spinal cord, there were p‐TDP43‐immunoreactive abnormal structures, such as neuronal cytoplasmic inclusions (NCIs), including skein‐like inclusions Fig. , and gliter Fig. , midbraiter Fig. , medullater Fig. . The intter Fig.  and the ter Fig. . The immC9orf72 repeat expansion is the most common mutation associated with familial ALS and the familial FTLD‐ALS spectrum, including ALS, ALS‐dementia complex, ALS‐FTLD, and FTLD. Neuropathologically, there are characteristic p62‐positive, p‐TDP43‐negative inclusions in the brain, most notably in the cerebellum and hippocampus.C9orf72 repeat expansions could be associated with parkinsonian disorders such as PD, dementia with Lewy bodies, PSP, CBD, and MSA. On testing clinically diagnosed parkinsonian patients for C9orf72 repeat expansions, Lesage et al. found that of 1446 subjects, including 25 with clinically diagnosed MSA, five carried the repeat expansion, including three patients with PD, one with CBD, and one with PSP.C9orf72 repeat expansions in 100 pathologically confirmed cases of MSA.et al. described one case of clinically diagnosed mixed ALS‐MSA phenotype with evidence of a C9orf72 repeat expansion; however, it was not pathologically confirmed.C9orf72 repeat expansion pathology together with typical MSA α‐synuclein pathology. The early parkinsonian clinical features of cogwheel rigidity and decreased arm swinging together with poor response to L‐dopa were most likely to be explained by neuronal loss, gliosis, and α‐synuclein oligodendroglial pathology in the putamen and substantia nigra, thus giving a parkinsonian subtype of MSA, also known as MSA‐P. Similarly, neuronal preservation of the Purkinje cell and granule cell layers of the cerebellum, pontine nuclei, and inferior olivary nuclei probably explained the lack of cerebellar signs, despite both the cerebellar white matter α‐synuclein pathology and the separate C9orf72 repeat expansion‐associated p62 pathology in the granule layer. The lack of dysautonomic signs may have resulted from a relatively small number of α‐synuclein immunopositive GCIs present in the intermediolateral columns. The later appearance of the additional upper and lower motor ALS‐type clinical features, including muscle weakness, spasticity, and dysphagia was more likely caused by motor neuronal loss of the motor cortex, medullary hypoglossal nerve nucleus, and spinal cord anterior horn together with associated p‐TDP43 pathology. Interestingly, the substantia nigra contained abundant p‐TDP43, α‐synuclein, and p62 deposits, suggesting involvement in the motor signs of both the parkinsonian and ALS disease processes. Presumably, the relatively rapid nature of loss of the upper and lower motor neurons was the reason that the neurological ALS components predominated on the later clinical examinations.The C9orf72 GGGGCC expansion from his father, the explanation of the MSA‐type clinical and pathological features is somewhat problematic. Although it would be tempting to suggest that the patient's mother actually had MSA but not PSP, there is no actual pathological evidence to confirm this. Furthermore, MSA, unlike ALS‐C9orf72, has been shown to only very rarely be inherited in an autosomal dominant or recessive manner.SNCA), copy number variants of SNCA, mutations in the coenzyme Q2 gene (COQ2), and even some mutations in the microtubule‐associated protein tau gene (MAPT) and the glucosylceramidase beta 1 gene (GBA1).There was evidence of a family history of ALS, from the father, and a possible parkinsonian syndrome, from the mother. In addition to early extrapyramidal signs, more atypical ALS‐type neurological and neurophysiological features were detected later. Although it is evident that the patient inherited the ALS‐associated C9orf72 mutation separately inherited from the father exacerbated the effects of the MSA‐associated variants to cause MSA‐type symptoms and pathology. There is some circumstantial evidence that C9orf72 repeat expansions may have these effects. We previously described a patient with a C9orf72 repeat expansion and a usually non‐pathogenic MAPT variant that, nevertheless, presented with an FTLD pattern mainly associated with tau and p62 pathologies and less p‐TDP43 pathology.et al. also showed evidence that FTLD‐C9orf72 had an increased propensity for tau pathology compared to FTLD associated with progranulin mutations but not sporadic FTLD.C9orf72 repeat expansions.C9orf72 repeat expansions can “unmask” or “promote” otherwise less or non‐pathogenic variants of MAPT or SNCA remains an intriguing possibility.It is also possible to speculate that the The authors declare no conflicts of interest for this article.


Inclusion of prebiotic compounds as indigestible dietary fiber in wheat bread has grown rapidly considering the increased public awareness about their impact on health. However, through their incorporation, the technological characteristics may adversely be influenced by gluten dilution impacts. This study was done to evaluate the impacts of long chain, native and short chain inulin  at 8%, 10%, 12%, 14%, and 16% w/w as Inulin Reconstituted Wheat Flour (IRWF) with similar gluten: carbohydrate ratio of wheat flour  on technological and nutritional value of wheat bread. Results indicated that despite no gluten dilution induced by IRWF supplementation, technological characteristics were adversely influenced especially at higher substitution level of L‐type‐containing formulations which is attributed to their higher water absorption index (WAI). Reversely, the nutritional value was positively influenced in which the lowest hydrolysis index (26.64%); predicted Glycemic Index (51.93%) and fructan loss content (25.42%) were found at L‐type inulin‐containing IRWF at the highest substitution level (20% w/w). As the nutritional value of wheat bread as staple foodstuff is important, optimizing the bread‐making process to decrease all reverse impacts induced by L‐inulin‐type inclusion seems to be required. Impact of inulin incorporation as a strategy of wheat bread fortification is investigated. Inulin reconstituted wheat flour is used to postpone its gluten dilution impact. Technological characteristics of wheat bread are determined by water absorption index of formulations. Nutritional characteristics of fortified wheat bread are influenced by polymerization degree of inulin. Regarding World Health Organization (WHO) recommendation, the per capita consumption of bread is estimated at about 250 g per day Serrem, . HoweverBread is prepared in different shapes, sizes, and textures through the world using the combination of flour, water, salt, and yeast (sourdough)  in response to a test and reference food consumed by one on different days and standard situations. AUC is an indicator of blood glucose response  was provided by SENSUS (Netherland). All flours had at least inulin content of more than 99.5% w/w. Wheat flour and vital gluten protein were purchased from Roshan and Hedia companies , respectively. Wheat flour contained moisture, ash, and protein in quantities of about 13.95%, 0.23%, and 10.93% w/w, respectively. Yeast was obtained by Khuzestan Yeast Company  and the other constituents  were provided from the local supermarket. All chemicals including sodium hydroxide, potassium hydroxide, hydrochloric acid, sodium borohydride, parahydroxybenzoic acid, sodium acetate, acetic acid, maleic acid, tris‐maleate buffer (pH 6.9), D‐fructose, α‐amylase, sucrase, and sodium carbonate were obtained by Merck Company (Germany). Pancreatic ɑ amylase, sucrase, β‐amylase, pepsin, pullulanase, inulinase, invertase, α‐glucosidase, and α‐cellulose were also provided by Sigma‐Aldrich company (America).2.2This study with the aim of studying the potential of Inulin incorporation in reconstitution of wheat bread from technological characteristics and nutritional value perspective was set in full factorial experimental design. So, the impact of inulin DP  and substitution level of inulin reconstituted wheat flour (IRWF) was investigated as demonstrated in Table 2.3Brabender farinograph  was used to determine the quantity of water to reach the consistency of 500 BU according to the AACC Method 54‐21A. In this regard, the gluten and inulin were mixed well with wheat flour into the 300 g mixing bowl of farinograph which was operated at 30 ± 0.2°C. Farinograph curves were used for determination of the water absorption (percentage of water needed to provide a dough consistency of 500 BU), dough development time (time to reach a consistency of 500 BU), stability time (time in which the dough consistency is over 500 BU) and falling quality number were obtained.2.4Bread preparation on the basis of formulations represented in Table 2.52.5.1Rape Seed displacement method was used for volume determination of loaves according to AACC 109 method 10–05. After volume and weight determination, specific volume was determined by their ratio as follows:2.5.2Instrumental texture profile analysis of breads was done and followed using texture profile analyzer . Regarding, a 5 kg loading cell and cylinder probe (diameter of 43 mm), bread crumb with dimension of 20 × 20 × 25 mm was pressed up to its half height at speed ratio of 1 mm/s. The analysis was done in five replicates at room temperature. Texture profile analysis curves were assessed for hardness, springiness, and chewiness determination . Results are expressed as L* (brightness/darkness), a* (redness/greenness), and b* (yellowness/blueness) indices . So, encoded bread samples were served randomly. The panelist's healthiness  and eagerness to be participated were also considered  was added and incubation was done at 37°C.In vitro method was used to determine the pGI on the basis of the procedure proposed by  and incubated at 60°C for 45 min. Afterward, distilled water was used for the volume adjustment to 10 ml. The solution (0.1 ml) was transferred into glass test tubes for glucose quantification by GODPOD kit and absorbance at 510 nm. The hydrolysis index (HI) was estimated as the ratio of total released glucose of samples and standard glucose . The mixture was filtered and treated with 1 ml sucrase/amylase solution (sucrase (50 U), β‐amylase (500 U), pullulanase (100 U), and maltase (1000 U) in 22 ml sodium maleate buffer (pH 6.4) to remove sucrose, starch and reducing sugars). Afterward, alkaline borohydride (10 mg/ml sodium borohydride in 50 mM NaOH) was added and incubated at 40°C for 30 min and the excess was removed using acetic acid (100 mM) to reach the pH equal to 4.5. Quantification of fructan was done by fructanase (350 U/ml exo‐inulinase and 35 U/ml endo‐inulinase) for 20 min at 40°C. The fructan content (%) was estimated as:A: absorbance of 0.2 ml of the reactive solutions read against the reagent blank.F: equal to 54.5, factor used to convert the absorbance value to μg fructose.V: volume of used extractant.M: weight of test portion.2.9anova and Kruskal–Wallis for parametric and non‐parametric tests, respectively, by spss V.21 software at a significance level of 0.05.Quantitative characteristics were described using mean and standard deviation. All examinations were done in triplicate. Data analysis was performed using two‐way 33.1The viscoelastic network formation of dough is influenced greatly by the other ingredients . In other words, while the ability to absorb water is remained quite unaffected at formulation containing 8% w/w S‐type inulin‐containing IRWF (F1) (p > .05), it has been increased in the presence of 8% w/w L‐type inulin‐containing one (F10) compared to control (F16). The WA enhancement at formulations supplemented with IRWF‐containing long chain inulin is mainly attributed to their ability to provide a gel‐like structure potentially able to restore water as reported by  enhancement of DDT at all IRWF‐containing formula depending on polymerization degree of inulin and IRWF supplementation level (p < .05) (Table p < .05) found by increasing the DP of incorporated inulin in IRWF formulation, is also attributed to higher susceptibility of L‐type inulin to interact with gluten proteins and prevent their hydration and development and consequently lead to DDT enhancement  is also found to be influenced by IRWF supplementation. DDT is the required time for flour to be hydrated, developed, and provided consistent dough equal to 500 Brabender Unit (BU) consistencies. Results indicated significant (5) Table . DDT enh5) Table . IncreasStability time (ST) as stability indicator of dough is significantly influenced by dough constituents. As depicted, the lowest and highest ST are found in F16 (control) and F15 (long chain inulin‐containing IRWF at 20% w/w) with contents equal to 8.73 and 19.23 min, respectively. In other words, wheat dough supplementation using IRWF enhanced the ST significantly on the basis of its supplementation level and polymerization degree of incorporated inulin. In this regard, it seems that dough samples with higher IRWF incorporation level had higher ST and consequently mixing resistance compared to the control sample. Previously, it has been stated that differently originated proteins in dough mixtures are not fully hydrated and behaved as dispersed particles which reinforce the gluten network and consequently increase their derived dough ST , about 48.30% w/w decreased is found in SV of F15 compared to control sample (p < .05) at. As SV is affected by dough strength and its prospective in restoring gases through bread‐making  is significantly influenced by supplementation level and the type of incorporated inulin. In other words, despite no significant difference between F16 (Control sample) and F1 (containing S inulin type and supplementation level at 10% w/w) (p < .05). Considering the impact of inulin on crumb hardness, however, it has previously stated that its incorporation in wheat bread provides a coarse crumb structure with higher hardness  lower L*, and higher a* and b* in crust compared to the control bread. Considering the polymerization degree of inulin, the highest variation is found in S‐type inulin samples. In other words, the lowest L* value is found in F5 at 72.18. The lightness reduction via low DP inulin incorporation has been previously stated by . In other words, the highest and lowest L* are found in F15 (supplemented by 20% w/w L‐type inulin‐containing IRWF) and F5 (supplemented by 20% w/w S‐type inulin‐containing IRWF) with values at 79.12 and 89.15, respectively. It seems that higher susceptibility of S‐type inulin to be fermented by yeast leads to more release of carbon dioxide and air bubble expanding through bread‐making process which resulted in more light scattering and consequently decreased L* value. Increased L* in F15 is accompanied by the highest b* and harness values which are in accordance with .Considering the flavor sensation, the highest score is found in samples containing S‐type inulin which can be attributed to higher metabolites of Millard reaction as described by , Resistant Starch (RS), Digestible Starch (DS), Hydrolysis Index (HI), Predicted Glycemic Index (PGI), and fructan loss is presented in Table p < .05) decreased the HI which are also decreased more sharply at formulations containing higher IRWF supplementation level. The decreased HI induced by increasing the level of IRWF and polymerization degree of incorporated inulin is attributed to decreased starch gelatinization ratio and its preventative impacts on hydrolyzing enzymes  which is calculated by comparison of glucose released from sample and standard glucose through the digestion process and its corresponding pGI is considerably influenced by the supplementation process. As depicted in Table Inulin is incorporated as a functional ingredient in this study through its prebiotic role. Consequently, its stability through bread making process is considerably important, as influensive prebiotics needs to be entered intact to upper intestinal tract. As the incorporation level of inulin was different, monitoring the fructan loss in IRWF‐supplemented formulations indicate a progressive fructan loss through processing in the range of 25.42%–43.01% w/w. In other words, the highest and lowest fructan loss is found in F15 and F1, respectively, which indicate the enhanced prebiotic loss by decreasing its incorporation level and polymerization degree. The enhanced inulin loss by decreasing its polymerization degree is attributed to its higher susceptibility to be used by yeast and take part in Millard reaction. This finding is in accordance with  seems to be applicable from nutritional perspective, especially at formulations containing long‐chain inulin type. However, despite gluten inclusion at formulations to conquer gluten dilution impacts, adverse impacts on technological characteristics are still restricting in industrially production of them especially long‐chain inulin‐containing ones which are attributed to their higher water absorption content, accelerated gluten network formation, and decreased starch gelatinization. However, long‐chain inulin incorporation significantly improves the nutritional characteristics of wheat considering resistant starch content, hydrolysis index, predicted Glycemic index, and fructan loss parameters. Consequently, whole bread‐making process as the type of fermentation, time: temperature ratio of fermentation process and increasing ratio of temperature through baking process should be optimized to formulate optimized formulation from both nutritional and technological perspective.None declared.The Ethical aspects of this study are evaluated and approved by the Institutional Review Board of Shahid Sadoughi University of Medical Sciences.


Hypercoagulability in lung cancer patients is associated with a high incidence of mortality and morbidity in the world. Therefore, this meta‐analysis aimed to explore the correlation of the basic coagulation abnormalities in lung cancer patients compared with the control.PubMed, Scopus, and other sources were employed to identify eligible studies. The outcome variable was expressed using mean ± standard deviation (SD). Heterogeneity among studies and publication bias were evaluated. The quality of included studies was also assessed based on Newcastle–Ottawa Scale checklist.Finally, through a total of eight studies, prolonged prothrombin time , plasma D‐dimer value , fibrinogen , and platelet (PLT) count  were significantly higher in lung cancer patients when compared with the control group. The single‐arm meta‐analysis also showed that compared with control, lung cancer patients had high pooled PT 13.7 (95% CI:12.2–15.58) versus 11.79 (95% CI = 10.56–13.02), high D‐dimer 275.99 (95% CI:172.9–11735.9) versus 0.2 (95% CI:0.20–0.37), high plasma fibrinogen 5.50 (95% CI:4.21–6.79) versus 2.5 (95% CI:2.04–2.91), and high PLT count 342.3 (95% CI:236.1–448.5) versus 206.6 (95% CI:176.4–236.7).In conclusion, almost all the coagulation abnormalities were closely associated with lung cancer, and hence coagulation indexes provide an urgent clue for early diagnosis and timely management. Figure 1: Flowchart of search stratagem and study selection By the year 2018, about 2 million new cases of lung cancer were diagnosed and 1.8 million lung cancer‐related deaths were reported worldwide. It has the highest incidence in developing nations where cigarette smoking is most prevalent,Lung cancer is caused by numerous factors such as radon gas, asbestos, air pollution exposures, chronic infections, as well as genetic susceptibility. However, 90% of lung cancers are caused by smoking and the use of tobacco products.Ample of evidence has reported that lung cancer is associated with hypercoagulability by involving activation of coagulation and the fibrinolytic system at clinical or subclinical levels.Fibrinogen is the most abundant plasma coagulation factor synthesized mainly by hepatic cells. High level of plasma fibrinogen level was detected in lung cancer patients.Xi Zhang and Yuge Ran showed that thrombocytosis was recognized as predictor of high‐risk progression and poor prognosis in lung cancer patients.Furthermore, the other key indicator associated with mortality in lung cancer patients is increased D‐dimer, the degradation product of fibrin, which signals hyperfibrinolysis in response to clot activation and fibrin formation.Notably, coagulation function indexes include prolonged prothrombin time (PT), activated partial thromboplastin time (APTT), international normalized ratio (INR), increased D‐dimer, and fibrinogen, as well as PLT count, are independent prognostic markers of lung cancer. However, the results remain inconclusive among studies. Therefore, the aim of this systematic review and meta‐analysis was to delineate the correlation of basic coagulation abnormalities with lung cancer patients as compared to normal controls. Hence, this aggregate of data will help health‐care providers to confine the lung cancer complication by early detection and proper management nationwide.22.1Regarding the language restriction, all studies included in this study were published in English. Whereas articles without study outcomes, lacking control groups, and studies did not report in the form of mean ± SD or median‐interquartile range (IQR), as well as comparative studies between before and after treatment, were excluded. Additionally, studies not presenting original data such as systematic reviews, meta‐analyses, case–control, and poster presentation were excluded from the study.2.2This systematic review was conducted following the PRISM2020 guideline2.3Based on the abovementioned eligibility criteria, two independent investigators separately retrieved the publication after the screening of the title, abstract, and full text, and evaluated the eligible studies. Any discrepancies from the investigators were resolved by consulting the third investigator. Extracted data elements from each included study were the name of the first author, country, publication year, study design, total sample size, and sample size from the two wings, the value of PT, APTT, INR, D‐dimer, fibrinogen, and PLT count. Mean ± SD was applied to present the continuous variables. Whereas any variables represented by median and IQR were converted to the form of mean ± SD accordingly.2.4The quality of included studies was assessed based on the NOS checklist for case–control studies. The NOS checklist for case–control studies were categorized into three main components including selection, comparability, and exposure and each of them contains 4, 1, and 3 questions, respectively. One star* and no star* were awarded for each equation, which were assigned 1 and 0, respectively. Then, a study with a score ≥7 was considered a high‐quality study2.5p‐value >0.05 indicated better prognosis.All selected studies were managed using EndNote version 9.2 software and duplicates of studies were removed. All the statistical analyses were performed with the STATA software version 11.0. Standard mean difference (SMD) with a 95% confidence interval (CI) was analyzed as a prognostic indicator of each prolonged coagulation values in the lung cancer patients. The combined SMD >0 and its 95% CI did not overlap 0 indicating that a higher level of PT, APTT, INR, plasma fibrinogen, and D‐dimer could be a poorer prognostic factor in lung cancer patients, whereas the combined SMD <0 and 95% CI contain 0 this means that the 2 index.I2 was employed to evaluate statistical heterogeneity with I2 values of <25%, 25%–75%, and >75%, respectively, indicating low, moderate, and high heterogeneity. I2 test is an indicator for the choice of the proper effect model whether the fixed effect model or random effect model was applied. I2 < 50% or p‐value <0.10 were considered no significant heterogeneity between studies, and thus the fixed‐effects model was applied. Otherwise, the random‐effects model was applied. Furthermore, sensitivity analysis was performed to validate the stability of the pooled results by omitting the studies one by one. Meta‐regression was also conducted to explore the effect of continuous covariates on differences in the coagulation parameters between lung cancer patients and control groups.Statistical heterogeneity of included studies was determined with the I2.6p‐value <0.05 was used to indicate a statistically significant publication bias between included studies.The potential for publication bias was assessed by performing a funnel plot test. Publication bias was determined by the shape of the funnel plot, where a symmetrical shape represented relatively low publication bias, while an asymmetrical shape indicated relatively high publication bias. Meanwhile, Eggers's regression test was applied to make a quantitative analysis of publication bias, and a 33.1A total of 1296 articles were initially identified through the PubMed database and other sources. After eliminating duplicate articles as well as detailed reading of the title and abstract of each article, 22 relevant articles were screened out for full‐text assessment based on eligibility criteria. Finally, for the pooled analysis, eight studies were included , the random effect model was adopted for the statistical analysis of PT. The result showed that prolonged PT was significantly higher in lung cancer patients than in control groups , INR values were higher among lung cancer patients than the control group  demonstrated that the plasma D‐dimer value was significantly higher in lung cancer patients  when compared with the control group  as compared with the control with high heterogeneity (I2 = 93.2%) in the random effect model , the PLT count was significantly higher in lung cancer patients than the control group , D‐dimer , and fibrinogen  were steady with the exclusion of any of the studies  were evaluated to assess the difference in coagulation abnormality among lung cancer patients and the normal control group. The result showed that prolonged PT, increased PLT count, high level of plasma D‐dimer, as well as high plasma fibrinogen, were significantly higher in lung cancer patients than in control groups. However, prolonged APTT and INR were higher in lung cancer patients than the control group without significant differences. Prolongation of PT was significantly higher and associated with poor prognosis among lung cancer patients as compared with normal control in this meta‐analysis. This prolonged PT signifies a deficiency of coagulation factors or the presence of specific factor inhibitors involved in the coagulation cascade.Hypercoagulability was the most common event in lung cancer patients.The relationship and underlying mechanisms between increased PLT count and lung cancer were not well described yet. Despite this fact, PLT plays a significant role in cancer cell growth, progression, and metastasis. First, PLT releases various cytokines, including vascular endothelial growth factor and PLT ‐derived growth factor, from a‐granules, dense granules, and lysosomes, which affect tumor cell proliferation and angiogenic activity. Moreover, PLT promote the formation of the capillary‐like structure by interacting with vascular endothelial cells, via tumor cell surface integrins mediating cell–cell adhesion. But blocking of integrins GPIIb/IIIa and inhibition of endothelial ab3 integrins significantly decreased angiogenesis and subsequently reduced tumor cell growth.The finding from this meta‐analysis was consistent with other meta‐analyses published previously that showed elevated PLT counts were significantly associated with poor prognosis among lung cancer patients.Many studies showed that the elevation of plasm fibrinogen was predictive of thromboembolic disease at the early diagnosis of lung cancer before any therapy.Even though the clear pathophysiological mechanism of the prognostic significance of higher plasma fibrinogen levels in lung cancer patients was not well understood, recent studies have demonstrated that fibrinogen could play a key role in tumor progression.p = 0.000) when compared with the control group using seven studies. The single‐arm meta‐analysis on seven studies with a total of 1488 lung cancer patients and 328 control groups revealed that the pooled D‐dimer was 275.99 (95% CI:172.9–11735.9) as compared with the control group 0.2 (95% CI:0.20–0.37). The finding is similar to another meta‐analysis conducted by Ma et al. which showed that high plasma D‐dimer level is an independent factor of poor prognosis in patients with lung cancer.The tumor microenvironment constituted by immune cells and stromal cells with other “niche” cells leads to cancer patients' tumor‐associated coagulation abnormalities, which increases plasma D‐dimer concentration, one of the fibrin degradation products. Furthermore, D‐dimer is associated with lymph node metastases in NSCLC.5This meta‐analysis pointed out that prolonged PT, increased PLT count, and high levels of plasma D‐dimer and plasma fibrinogen were significantly higher in lung cancer patients than in control groups, which provides the hallmark indicators of lung cancer disease. Therefore, in the future, physician pays attention to the early screening of coagulation function indexes for lung cancer patients to reduce further complications.BB; Conceptualized, designed the study, and write‐up all the manuscript. TA and SG; accomplished the statistical analysis as well as critically revised the manuscript. MA: provided supervision and critically revised the manuscript. All authors approved the final version of the manuscript and agreed accountability for all aspects of the manuscript.All the authors declared that no conflict of interest for this work.Figure S1Click here for additional data file.Table S1Click here for additional data file.Table S2Click here for additional data file.Appendix S1Click here for additional data file.Appendix S2Click here for additional data file.Appendix S3Click here for additional data file.


The hospital management of patients diagnosed with COVID-19 can be hampered by heterogeneous characteristics at entry into the emergency department. We aimed to identify demographic, clinical and laboratory parameters associated with higher risks of hospitalisation, oxygen support, admission to intensive care and death, to build a risk score for clinical decision making at presentation to the emergency department.We carried out a retrospective study using linked administrative data and laboratory parameters available in the initial phase of the pandemic at the emergency department of the regional reference hospital of Pescara, Abruzzo, Italy, March–June 2020. Logistic regression and Cox modelling were used to identify independent predictors for risk stratification. Validation was carried out collecting data from an extended timeframe covering other variants of concern, including Alpha (December 2020–January 2021) and Delta/Omicron (January–March 2022).3/μL ; for intensive care, end stage renal disease , lactate dehydrogenase≥334 U/L , D-dimer≥2.37 mg/L , monocyte distribution width ≥ 25 ; for death, procalcitonin≥0.2 ng/mL  and saturation < 96% . Risk scores derived from predictive models using optimal thresholds achieved values of the area under the curve between 81 and 91%. Validation of the scoring algorithm for the evolving virus achieved accuracy between 65 and 84%.Several clinical and laboratory parameters were significantly associated to the outcomes of interest, independently from age and gender. The strongest predictors were: for hospitalisation, monocyte distribution width ≥ 22  and diabetes ; for oxygen support: saturation < 95% , lactate dehydrogenase≥237 U/L  and lymphocytes< 1.2 × 10A set of parameters that are normally available at emergency departments of any hospital can be used to stratify patients with COVID-19 at risk of severe conditions. The method shall be calibrated to support timely clinical decision during the first hours of admission with different variants of concern.The online version contains supplementary material available at 10.1186/s12913-022-08421-4. Between December 2019 and April 2021, the coronavirus SARS-CoV2 affected at least 130 Million people diagnosed with COVID-19 in 223 different countries, of which almost 2.9 Million died .Clinical symptoms range from pauci-symptomatic states presenting fever, cough and fatigue, to more severe forms including acute respiratory distress syndrome (ARDS) and/or other critically severe conditions . MortaliTimely identification of COVID-19 patients at higher risk of severe complications may enable early hospitalisation, risk-tailored clinical treatment and optimal allocation of human and technical resources . In thesThe triage of COVID-19 patients requires multiple parameters to be assessed by a multidisciplinary team at presentation to the Emergency Department (ED) . CharactIn the framework of everyday care provided during the first wave of the outbreak, our aim was to identify patients diagnosed with COVID-19 with a higher risk of four key outcomes: hospital admission, mechanical ventilation, admission to Intensive Care Unit (ICU) and death.Which demographic, clinical and laboratory parameters are associated with a higher risk for each of the key outcomes identified?How accurate are predictive models using only characteristics available at presentation to the ED?The present study is a retrospective review of all consecutive cases presented at the ED over 3 months, addressing the following key research questions:We performed a retrospective analysis of all consecutive patients presented with a confirmed diagnosis of COVID-19 at the ED of the General Hospital of Pescara , between 1st march – 30th June 2020. The diagnosis was confirmed through a swab test performed by the hospital personnel in the same occasion. The time frame follows the start of the outbreak of COVID-19 in Italy . At thatThe Pescara General Hospital (PGH) is an urban 650-bedded tertiary facility of regional reference for adult traumas, acute diseases of neurosurgical interest, and COVID-19. It includes two ICUs: an 11-bedded facility, receiving critically ill patients from other EDs in the region and most of the other wards in the same hospital, and a 24-bedded COVID Unit, specifically opened to respond to the emergency of the pandemic.Data were merged from records available at different sources, including the hospital discharge abstract database, the computerized hospital information system including personal health records of laboratory measurements, and paper-based clinical abstracts, from which other characteristics were manually extracted.Two additional samples were collected for external validation, using a large subset of entries to the same ED between December 2020–January 2021 (corresponding to the transition from the “Wild” lineage of COVID-19 to the “Alpha” variant)  and JanuThe study was conducted according to the Declaration of Helsinki (amended version). The local Health Administrative Board reviewed and approved the study plan submitted by the Infectious Diseases Unit, the Emergency Department and the Laboratory Staff of PGH. The use of anonymised clinical and laboratory data for institutional research purposes was granted through signed informed consent upon hospital admission by all patients included in the study. Specific consent for the conduction of the study was not considered required, as confidentiality was guaranteed, and no specific interventions were performed beyond the ordinary good standard clinical practices.The study targeted four different outcomes after presentation to the ED: hospitalisation, oxygen support, admission to the ICU, and death . By definition, not all combinations were possible, e.g. a patient can be discharged at home and experience a fatal event or can progress through all transitions from hospitalisation. Some states directly implied others e.g. a patient receiving oxygen support or admitted to the ICU must be hospitalised.Demographic and clinical characteristics, signs and symptoms and laboratory measurements were considered as potential predictors for the selected outcomes.Age and gender were used as the only demographic characteristics of interest. For clinical variables, we considered a history of six comorbid conditions: diabetes, cardiovascular diseases (CVD), obesity, cancer, End Stage Renal Disease (ESRD), chronic obstructive pulmonary disease (COPD) and hypertension. These characteristics were recorded as part of routine clinical practice, using standardized definitions adopted by all hospitals in Italy.Signs and symptoms related to COVID-19 were also considered, e.g. fever, cough, asthenia, diarrhea and dyspnea. Accurate recording was ensured by a standard national protocol applied routinely to monitor patients diagnosed with COVID-19.Finally, eight device-assisted and laboratory parameters were considered as potential predictors of patients’ prognosis, based on high/low levels considered as potential correlates to the severity of the disease : procalcWe investigated hospitalisation and death in/out of hospital through follow-up of all patients in the study population. Oxygen support and admission to intensive care included only those hospitalised with less than 70 years, to avoid potential bias of deaths occurring before either option as a competing risk . The chop values. Forest plots were used to visualize results.Descriptive analysis included the calculation of mean and standard deviation for continuous variables and absolute and relative frequencies for categorical variables. Optimal thresholds for hospitalisation and oxygen support were used to calculate frequencies for the reference population in the overall sample and among those aged<70y hospitalised. Logistic regression was used for univariate and multivariate odds ratios (OR) of non-fatal outcomes . Survivap value ≥0.20, ≥0.10 and ≥ 0.05.Predictive factors using a fully automated four-step backward elimination process in all multivariate regressions. Age and gender were forced in all models, with all other variables sequentially excluded in three consecutive rounds using a odds/hazard ratios < 1 were turned into their reciprocal value and assigned a negative sign;odds/hazard ratios greater or equal to 1.5 were rounded to their next integer value (to reflect increased risk by a multiplicative factor);odds/hazard ratios between 1 and 1.5 were transformed into their difference from 1 .Predictive formulas were defined using the regression coefficients as follows :odds/hazTotal risk scores for each patient in the database were computed separately for each outcome, adding up all coefficients indicated above for all significant variables. A ROC analysis was performed using a separate 2 × 2 “confusion matrix” for every possible threshold applied to the total score . The besThe same measures were produced for both the study sample and the additional datasets collected for external validation. Survival results for validation samples were only available as odds ratios, as Cox proportional hazards was not applicable due to the unavailability of time of negative swab test.Reliability analysis of the predictive formula was summarized using ROC curves showing optimal thresholds and sensitivity, specificity, AUC with point estimates and 95% confidence intervals. All statistical analyses were carried out by developing ad hoc software in the R language .A total of 536 consecutive admissions with a positive molecular assay to SARS-CoV2 were recorded at the ED in the reference period. The samples collected for validation were equal to 224 out of 639 (35%) for December 2020 – January 2021 and 375 out of a total of 872 (43%) for January–March 2022.Among subjects hospitalised in the baseline study sample, a total of 174 consecutive admissions involved patients aged less than 70 years. The samples used for validation were equal to 95 out of 226 (42%) for December 2020 – January 2021 and 56 out of a total of 135 (41%) for January–March 2022.All details of the association including risk ratios and 95% confidence intervals for the total population admitted to the ED at baseline and those hospitalised below 70 are reported in Tables 3/μL (44.6%), D-dimer≥0.72 mg/L (43.3%), LDH ≥ 240 U/L (41.2%), CRP ≥ 21 mg/L (37.3%) and MDW ≥ 22 (28.2%).The mean age (standard deviation) was 63.2 (19.1) y, with 50.7% of males. The most frequent comorbidities were hypertension (36.2%), CVD (25.9%) and diabetes (16.0%). The most frequent symptom was diarrhea (87.1%), followed by fever (79.9%), cough (43.7%) and dyspnea (43.3%). The parameter that was most frequently abnormal was prothrombin time < 95% (68.5%), followed by saturation < 96% (46.1%), lymphocytes< 1 × 103/μL. Moderate association was found for dyspnea, COPD, CVD, cough and cancer. Patients with diarrhea were over 50% less likely to be hospitalised.A total of 365 subjects (68.1%) were hospitalised after presentation to the ED. Among the main baseline characteristics observed, only cough and asthenia were not significantly associated with hospitalisation. An additional year of age was associated with a 6% increased risk of hospitalisation, while males were almost 70% more likely to be hospitalised. An over ten fold association with increased risk was found for CRP ≥ 21 mg/L, obesity, ESRD and saturation < 96%. Associated risk was over five fold for MDW ≥ 22, D-dimer ≥0.72 mg/L, diabetes, hypertension, LDH ≥ 240 U/L and lymphocytes< 1 × 103/μL, LDH ≥ 307 U/L, dyspnea, prothrombin time < 77% and hypertension. Moderate increased risk was found for diabetes and MDW. On the other hand, three conditions were found to be associated with survival after diagnosis with COVID-19: patients with diarrhea were 80% less likely to die, with almost a 50% risk reduction also observed for those presented with asthenia and cough.A total of 136 subjects (25.4%) died in or out of hospital in the reference timeframe, following presentation to the ED with a confirmed diagnosis of COVID-19. Among the main characteristics, gender, obesity, fever and cancer were not significantly associated with survival. An additional year of age was associated with a 8% increased risk of death, and an over threefold increase for procalcitonin≥0.2 ng/mL, D-dimer≥1.04 mg/L, ESRD, saturation < 96%, CVD, CRP ≥ 43 mg/L and COPD. Risk was more than doubled for lymphocytes< 0.7 × 103/μL (67.8%), MDW ≥ 24 (67.2%), D-dimer≥0.55 mg/L (64.9%), CRP ≥ 42 mg/L (62.6%) and prothrombin time < 88% (55.7%). Less than half of the patients had a saturation < 95% (47.7%) and procalcitonin ≥0.2 ng/mL (24.7%).The mean age (standard deviation) was 54.3 (10.1) y, with 64.4% of males. The most frequent comorbidities were hypertension (33.9%) and diabetes (18.4%). The most frequent symptoms were fever (92.5%) and cough (60.9%). The parameter found most frequently abnormal was LDH ≥ 237 U/L (74.7%), followed by lymphocytes < 1.2 × 103/μL. Over three-fold association was found for procalcitonin≥0.2 ng/mL. D-dimer and prothrombin time were not associated with oxygen support.A total of 129 subjects (74.1%) received oxygen after hospitalisation. None of the demographic and clinical characteristics were significantly associated with such treatment. Among relevant parameters, a level of increased risk between four and fifteen-fold was found for saturation < 95%, LDH ≥ 237 U/L, MDW ≥ 24, CRP ≥ 42 mg/L and lymphocytes< 1.2 × 103/μL. Procalcitonin, D-dimer and prothrombin time were not associated with admission to ICU.A total of 51 subjects (29.3%) aged below 70 were admitted to the ICU after hospitalisation. Among subject characteristics, only age and CVD were associated with increased risk of intensive care. Among laboratory and device-assisted measurements, risk was at least five times higher for LDH ≥ 334 U/L and saturation < 92%, more than tripled for MDW ≥ 25 and CRP ≥ 68 mg/L, more than doubled for lymphocytes< 0.7 × 10The results of multivariate analysis are shown along with those obtained from validation over different samples in Fig. Among adjustment terms, only age (unit increase) was associated with a higher risk of experiencing three of the four outcomes of interest, namely hospitalisation , intensive care  and death .Taking into account all potential confounders, further eight characteristics were significantly associated to an increased risk of hospitalisation. The risk was over four fold for patients with MDW ≥ 22 , and over three fold for people with diabetes . All other significant characteristics had a risk between two and three times higher than their reference category: saturation < 96% , CRP ≥ 21 mg/L , procalcitonin≥0.2 ng/mL , D-dimer≥0.72 mg/L , dyspnea  and prothrombin time < 95% .Only one clinical characteristic was associated with an increased risk of death: ESRD . Other four categories with abnormal levels were significantly associated with an increased risk: procalcitonin≥0.2 ng/mL , saturation < 96% , D-dimer≥1.04 mg/L  and LDH ≥ 307 U/L .3/μL .After hospitalisation, oxygen support was over ten times more likely for saturation < 95% , almost six times higher for LDH ≥ 237 U/L  and over four times higher for lymphocytes< 1.2 × 103/μL .Admission to ICU recorded the highest level of association found for a clinical characteristic, being almost sixty times more likely for ESRD . Other independent risk factors were LDH ≥ 334 U/L , D-dimer≥2.37 mg/L , MDW ≥ 25  and lymphocytes< 0.7 × 10Several variables among those presented above were not significant in the validation over the extended timeframe.Risk scores were directly derived from predictive models, according to the method outlined above. The predictive accuracy of the algorithms is presented in Table For hospitalisation, an optimal cut point equal to 12 achieved sensitivity of 80% (95%CI: 75–83%) and specificity of 87% (81–92%). The overall performance was very high , suggesting that the predictive model may be suitable for regular use at ED.The same performance was achieved with a cut-off equal to 10 by the mortality predictive model , with a higher sensitivity , but lower specificity .Similar levels were obtained using a cut-off of 8 for oxygen support, achieving a sensitivity of 87% (80–91%) and a specificity of 77% (63–87%), with a slightly lower overall performance .Finally, admission to ICU recorded the lowest performance with a cut-off equal to 10 and a sensitivity = 82% (70–90%), specificity = 71% (63–79%), and AUC = 81% (73–89%).The external validation denoted an optimism in the accuracy measured by the AUC ranging between 3 and 19%.An overall ROC analysis of the performance achieved by all predictive models is presented in Fig. The Italian National Health System  delivers national guidelines for the standard provision of health services across the country. However, when Italy was first hit by the coronavirus, hospitals experienced a rapid increase of hospitalisations, followed by an exceptional shortage of medical equipment and a limited set of recommendations regarding best practices . The sitOur results are consistent with those obtained by other studies carried out on different outcomes, including mortality, progression to severe/critical status, recovery, length of hospital stay, admission to ICU, intubation, duration of mechanical ventilation, acute distress respiratory, cardiac injury and thrombotic complications. Evidence showed predictive factors including age, comorbidities, vital signs, image features, gender, lymphocyte count and C-reactive protein .In this study, we considered specific predictors, e.g. optimal cutoffs for MDW, which have not been previously considered by algorithms for COVID outcomes using data available during the early phase of admission, to support clinical decision in the Emergency Department.We identified eight known targets of hospital management to be significantly associated with hospitalisation independently from age and gender: diabetes, dyspnea, procalcitonin≥0.2 ng/mL, MDW ≥ 22, saturation < 96%, D-dimer≥0.72 mg/L, prothrombin time < 95% and CRP ≥ 21 mg/L. Among them, MDW deserves to be presented in more detail. MDW is a novel haematological parameter recently introduced for the diagnosis of sepsis , 27, whi3/μL as adequate targets for oxygen therapy.As a first relevant transition after hospitalisation, we focused on oxygen support among patients with COVID-19 aged less than 70 years. In this group of subjects, dyspnea, chest distress and respiratory rate were found to be highly associated with oxygen therapy, suggesting strict monitoring for parameters that can be highly associated with clinical deterioration and adverse outcomes . In addi3/μL. Other studies found heart disease, COPD and heart rate to be significantly associated with ICU, in addition to ESRD [Hospitalized patients aged<70y had a higher risk of being admitted to ICU if one of the following cases applied: ESRD, LDH ≥ 334 U/L, MDW ≥ 25, D-dimer≥2.37 mg/L and Lymphocytes< 0.7 × 10 to ESRD . The dom to ESRD . A high  to ESRD , 42. Lym to ESRD . Lymphop to ESRD . Reduced to ESRD . T -cell to ESRD .Several characteristics at entry to the ED were predictive of mortality in or out of hospital, independently from age and gender, including ESRD, procalcitonin≥0.2 ng/mL, LDH ≥ 307 U/L, saturation < 96% and D-dimer≥1.04 mg/L. We did not find known any significant predictive factor associated with increased mortality, differently from other reports addressing male gender, symptoms < 10 days prior to hospital admission, diabetes, coronary heart disease, chronic liver disease , white cRegarding our second research question, we were able to identify accurate risk scores, based on significant coefficients extracted from predictive models. The risk scores showed an average performance ranging from moderate to very high. The performance was very high for hospitalisation, with AUC = 91% (89–94%) and PPV = 94% (90–96%), mortality prediction, with an AUC = 91% (87–94%) and a low PPV = 60% (53–66%), as well as for oxygen support, with AUC = 87% (82–92%) and PPV = 92% (86–95%). The performance was slightly lower for admission to ICU, with AUC = 81% (73–89%) and PPV = 54% (43–65%). Notably, the NPV was high for death  and admission to ICU , indicating that a value of the score below the threshold, particularly for ICU, may be effective in ruling out major complications and considering oxygen therapy as a viable solution.The comparison between predictive models estimated in our study and other scientific reports may be challenging. Predictive models use different types of cohorts to investigate a variety of outcomes including confirmed diagnosis, disease severity, ICU and mortality. Studies are conducted in different hospital environments, using different laboratory standards and applying heterogeneous inclusion/exclusion criteria e.g. tuberculosis, influenza and bronchitis . VariablTo better respond to our second research question, we evaluated the accuracy of our predictive models under real life conditions during the second wave in late 2020.We found that the overall performance was fairly robust for oxygen support, hospitalisation and death. On the other hand, the results were less satisfactory for admission to ICU . A possible explanation may be related to the heterogeneous characteristics of patients admitted during the second wave, which changed the prognosis and thus the predictive ability of models specified under different conditions.In summary, we identified a set of key parameters that can be translated into risk scores to inform clinical practice. The advantage of this approach is that it can be directly applied to the next patient entering the ED, even with a pocket calculator. A substantial barrier for the continuous update and adaptation of this method is the limited interoperability of health databases in most European contexts, which makes the process of data acquisition particularly burdensome. Improving the digitalization and standardization of health information at hospitals across Europe will be paramount to strengthen our preparedness to future outbreaks and favour the adoption of research methods in clinical practice –55.Finally, several limitations of our study are worth to be outlined, along with their consequences on the future use of the algorithms.Firstly, this is a retrospective study carried out at a single hospital, enrolling a limited number of patients during the initial phase of the COVID-19 outbreak in Italy. Consequently, the results may not equally apply to other jurisdictions and/or institutions. However, our report provides a focused stratification of subjects entering the ED that can be informative for clinical practice on a global scale.Secondly, among the outcomes identified, only death represents a clinically objective measure, while all others reflect decisions made by clinicians at the hospital. Therefore, we cannot infer on the validity of the same models under different settings and variable conditions. However, it is a specific feature of the approach to be able to identify factors orienting practices, so that pragmatic guidelines can be offered when they are not readily available. This feature implies a repeated application of the method to make it locally relevant.Thirdly, we searched for predictive variables among measures readily available at presentation to the ED. As for all observational studies, we may have missed a subset of characteristics that could be potentially predictive either at entry or in the subsequent follow up in and out of hospital. Nevertheless, we kept our focus on measures that are used in normal practice, so that they can be realistically applied.Fourthly, the statistical models adopted did not take into account transitions between states e.g. oxygen support followed by intensive care. Our choice was based on the need to facilitate interpretation, rather than enhancing the statistical properties of our methods.Finally, the stability of the algorithms should be considered in the broader perspective of a continuously evolving virus, in which the continuous update of the vaccination status may blunt the clinical response. This consideration triggers important closing reflections.https://vaccinetracker.ecdc.europa.eu/public/extensions/COVID-19/vaccine-tracker.html#uptake-tab). Therefore, while obviously vaccination was not an issue in 2020, it is also fair to assume that all patients included in the “Wild/Alpha” sample in Dec 2020-Jan 2021 were not vaccinated, while the majority of those included in the “Delta/Omicron” sample could be considered vaccinated. On this ground, we can fairly assume that the vaccination status may have biased estimates obtained for the Omicron sample. On the other hand, the fact that this characteristic is not continuously available in routine hospital databases makes it a difficult candidate for risk evaluation in everyday practice . Therefore, in practical usage, it could be appropriate to consider it as a non- observable confounder, thus incorporating its effect in the association found for other variables.The vaccination status of individuals in our samples could not be ascertained from the available data. However, vaccination in Italy ramped up only in February–March 2021, reaching over 90% for those 60+ in early 2022 . Therefore, the method seems still generally useful to pick subjects at significantly increased risk.The significance of specific variables in predictive models may also highlight differences in their relevance according to the lineage of the virus. The measurement of MDW, D Dimer, and Prothrombin did not appear as relevant in the evolution of COVID-19 for matters related to hospitalisation. On the other hand, saturation retained its predictive value for hospitalisation and oxygen therapy, while it was not significant to predict survival in the “Delta/Omicron” sample. These aspects seem to indicate changes in the characteristics of the population affected by different variants, reflecting the higher incidence of oxygen therapy and intensive care in the Wild/Alpha, as opposed to a sharp decrease in the incidence of all events under the Delta/Omicron variants . On the other hand, the Wild/Alpha sample showed an increased 50% admission to intensive therapy, as opposed to the baseline population. Only few variables could be considered relevant for the new variants of COVID-19, primarily for hospitalisation  and death .Since the model was estimated on the original virus, we may assume that our scoring algorithms will continue to be particularly relevant for any future new SARS-type respiratory diseases, where severe cases of pneumonia are more frequent in the absence of vaccination. The same model could be possibly continuously updated, estimating the weights of significant variables repeatedly over time.We identified demographic, clinical and laboratory parameters associated to hospitalisation, oxygen support, ICU admission and death in a population admitted to a large regional hospital with a confirmed diagnosis of COVID-19. Risk scores derived from multivariate models showed moderate to high predictive accuracy in flagging subjects with more severe prognosis, based upon the early evaluation of personal characteristics at the ED. The method can be conveniently applied to support clinical decisions under different conditions, using targeted data collection at a single point of entry. Recalibration of the scoring algorithms will be needed to cope with the continuous evolution of the virus in different contexts.Additional file 1: Supplementary Table 1. Validation of the Algorithms for the calculation of scores.


Freezing of gait is a complex paroxysmal phenomenon that is associated with a variety of sensorimotor, cognitive and affective deficits, and significantly impacts quality of life in patients with Parkinson's disease (PD). Despite a growing body of evidence that suggests anxiety may be a crucial contributor to freezing of gait, no research study to date has investigated neural underpinnings of anxiety‐induced freezing of gait.Here, we aimed to investigate how anxiety‐inducing contexts might “set the stage for freezing,” through the ascending arousal system, by examining an anxiety‐inducing virtual reality gait paradigm inside functional magnetic resonance imaging (fMRI).We used a virtual reality gait paradigm that has been validated to elicit anxiety by having participants navigate a virtual plank, while simultaneously collecting task‐based fMRI from individuals with idiopathic PD with confirmed freezing of gait.First, we established that the threatening condition provoked more freezing when compared to the non‐threatening condition. By using a dynamic connectivity analysis, we identified patterns of increased “cross‐talk” within and between motor, limbic, and cognitive networks in the threatening conditions. We established that the threatening condition was associated with heightened network integration. We confirmed the sympathetic nature of this phenomenon by demonstrating an increase in pupil dilation during the anxiety‐inducing condition of the virtual reality gait paradigm in a secondary experiment.Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder SocietyIn conclusion, our findings represent a neurobiological mechanistic pathway through which heightened sympathetic arousal related to anxiety could foster increased “cross‐talk” between distributed cortical networks that ultimately manifest as paroxysmal episodes of freezing of gait. © 2022 The Authors.  Anxiety has recently been recognized as a crucial trigger for freezing of gait (FOG).One model that incorporates the multiple features of FOG is the “cross‐talk” model,Although individuals with Parkinson's disease (PD) are well‐known to have dysfunctional dopaminergic systems, and dopamine is often thought to promote effective systems‐level functioning in the brain,In contrast to these beneficial cognitive effects, heightened tonic LC activity has been implicated in the stress response, via its connections within the broader sympathetic circuit, which together produce acute changes in the physiology and responsiveness of neurotransmission.It is inherently challenging to non‐invasively measure LC activity because the nucleus is small, elongated, and embedded deep in the brainstem. All of these factors make it difficult to isolate the LC with traditional neuroimaging methods.To date, no neuroimaging studies have used fMRI to interrogate the dynamic fluctuations in network‐level connectivity, during anxiety‐inducing contexts that can predispose individuals to freeze. Testing these ideas empirically has remained fundamentally challenging, due in part to the difficulty associated with manipulating “affective load” in combination with whole brain imaging of an immobile patient. To remedy this issue, we used a previously validated anxiety‐inducing VR gait taskoff state (off Parkinson's medication for 12–24 hours prior). Exclusion criteria were: (1) participants with any identified pathological abnormalities from radiologist's assessment; (2) any participants with additional neurological comorbidities. The study received ethical approval from the University of Sydney Human Research Ethics Committee. All participants provided written informed consent.Twenty‐nine participants with idiopathic PD and FOG participated in this study at the Brain and Mind Centre, University of Sydney. The inclusion criteria were: (1) clinical diagnosis of PD, which was confirmed using the Movement Disorder Society‐Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS‐UPDRS); (2) score of ≥1 on question 3 of the Freezing of Gait Questionnaire; (3) clinically observed freezing, confirmed by neurologist (S.J.G.L); and (4) completion of virtual‐gait paradigm in MRI scanner during o corner would reveal either a normal corridor or a corridor with a plank to cross. The plank condition contained two types; a narrow and a wide plank.Participants lay supine inside the MRI scanner with a mirror mounted to the head coil for participants to see projections of VR gait task. The alternative depression of the foot pedals allowed the participant to maneuver forward through the virtual environment and encoded binary inputs corresponding to left and right footsteps were recorded on the computer. The virtual environment consisted of a series of corridors (first‐person view), that after turning a 90t tests were performed on the differences between the narrow and wide plank conditions (P > 0.05). Given that no differences were found between the wide and narrow planks across multiple FOG measures, we pooled the two plank conditions by calculating the sum of the narrow and wide plank measures for all sessions and calculated the average of the pooled plank measures across each participant. We performed pairwise t tests to compare the pooled plank (threatening) conditions to the normal walking (non‐threatening) conditions.We calculated the percentage of time spent freezing and the footstep latency coefficient of variation for both the plank and normal walking conditions. A set of pairwise 2‐weighted echo‐planar functional images, acquired in sequential order with: repetition time = 3000 ms; echo‐time = 40 ms; flip‐angle = 90°; 40 axial slices covering the entire brain; interslice gap = 0.4 mm; field of view = 220 mm; and the raw voxel size = 3.9 × 3.9 × 4.0 mm. A high‐resolution 3D T1‐weighted anatomic image with voxel size = 0.4 × 0.4 × 0.9 mm was obtained for co‐registration with functional scans. Precautions were taken to control for the impact of head motion: all participants were instructed to keep their head motionless, and cushions were placed between participant's head and head coil to limit physical movement of head. Pre‐processing of images was performed using FMRIPREP  was used to collect TWe selected a set of predefined regions of interest (ROIs) relating to motor, limbic, and cognitive networks based on previous work.T, which quantifies the extent that a region connects across modules, was calculated for each time‐resolved dynamic functional connectivity matrix .P < 0.05).Finally, we investigated the relationship between self‐reported anxiety measures and the difference in dynamic functional connectivity  between the plank and normal walking conditions. We calculated the Pearson's correlation between self‐reported anxiety and the difference between the dynamic functional connectivity between plank and normal walking conditions for each participant. Only significant correlations were reported that survived permutation testing  , number of freezing events (P = 2.45 × 10−6), and the duration of freezing events (P = 6.88 × 10−4). We did not observe any effect of plank width on the different outcome measures of FOG.We observed a significant increase in the percentage of time spent frozen during threatening compared to the non‐threatening condition (P < 0.05 following a non‐parametric permutation test). The connectivity changes were distributed, with substantial increased connectivity between the motor and cognitive networks, and decreased connectivity within the limbic network  with increased participation coefficient values (BT) in the threatening versus non‐threatening condition distributed across the bilateral motor network, the limbic network, and the cognitive control network . An average maximal difference in the normalized pupil diameter between the threatening and non‐threatening condition was 0.70  are involved in the diversity of symptoms of PD.Given that we were unable to measure anxiety and pupillometry simultaneously during the fMRI‐task because of equipment constraints, we were unable to draw direct causal relationships. However, future research will examine pupillometry during the same anxiety‐inducing VR‐gait paradigm inside the MRI scanner. Hence, we have used a VR gait paradigm that has been validated to induce anxiety‐provoked freezing in both the VR and in real‐life environment.Overall, FOG is a complex phenomenon that encompasses cognitive, motor, and anxiety features. Limited research has determined the interactions between all these features, specifically the interaction between anxiety and FOG. Our results suggest that a deeper understanding of the pathophysiology of PD may be augmented through an appreciation of the complex inter‐relationships that characterize the ascending noradrenergic arousal system and its impact on functional neural networks.(1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript: A. Writing of the First Draft, B. Review and Critique.N.L.T.: 1A, 1B, 1C, 2A, 2B, 2C, 3A, 3BG.W.: 2A, 2B, 2C, 3BD.Q.: 2A, 2B, 2CS.J.G.L.: 1A, 1B, 2A, 2C, 3BJ.M.S.: 1A, 1B, 2A, 2B, 2C, 3BK.A.E.M.: 1A, 1B, 1C, 2A, 2B, 2C, 3BThis study was supported by Parkinson Canada (K.A.E.M.) and an Early Career Research Development Grant (K.A.E.M.) from the Brain and Mind Centre, University of Sydney. N.L.T. is supported by the Australian Government Research Training Program Scholarship (RTP). G.W. is supported by the Becas Chile Scholarship by Ministry of Science, Chile. J.M.S. is supported by a National Health and Medical Research Council (NHMRC) Project Grant (1156536) and University of Sydney Robinson Fellowship. S.J.G.L. is supported by NHMRC Leadership Fellowship (1195830). K.A.E.M. is supported by a New Investigator Award from Parkinson Canada, and a Discovery grant from the National Sciences and Engineering Research Council of Canada.All the authors report no conflict of interests with this research study.Appendix S1 Supporting InformationClick here for additional data file.Figure S1. Freezing severity compared to summarized positive functional connectivity during plank versus normal walking conditions. Represents the summed positive functional connectivity values connectivity in plank versus normal walking conditions compared to the percentage of time‐spent frozen in the virtual‐reality gait paradigm (freezing severity). Functional connectivity was calculated using the multiplication of temporal derivatives. β values were calculated using a generalized linear model for plank (threatening), normal walking (non‐threatening), the positive β values were summed to produce a singular summary value of functional connectivity for each subject. The correlation was calculated using Pearson's correlation, and permutation testing for significance (P < 0.05). However, the summary measure used for the aforementioned correlation analysis  . The connectivity matrix represents the specific edges of significant correlation across the 150 brain regions that had increased coupling and were significantly correlated with the freezing severity. Functional connectivity was calculated using the multiplication of temporal derivatives. β values were calculated using a generalized linear model for plank (threatening), normal walking (non‐threatening). Positive (increased coupling) β values were correlated with percentage of time‐spent frozen.Click here for additional data file.Table S1. All the positive and negative functional connectivity for 150 regions , with specific subcortex connectivity in plank versus normal walking conditions, grouped into functional networks.Table S2. The table depicts the specific pairs of nodes with increased ‘cross‐talk’ (coupling) during the plank condition compared to the normal walking condition that were significantly positively correlated with each measure of the Parkinson's Anxiety Scale.Click here for additional data file.


Pulmonary‐renal syndrome (PRS) is defined as a combination of diffuse alveolar haemorrhage and glomerulonephritis. An 18‐year‐old woman visited our hospital with a 2‐day history of fever, dyspnoea, and leg edema. Laboratory investigations revealed an elevated inflammatory reaction, increased serum creatinine levels, and normocytic anaemia. Additionally, the anti‐streptolysin‐O titre was positive, and complement component‐3 levels were decreased. Urinalysis revealed proteinuria and hematuria. Bronchoalveolar lavage aliquots were progressively more hemorrhagic. These findings supported a diagnosis of PRS secondary to streptococcal infection. The patient was treated with high‐dose methylprednisolone and antibiotics. After 4 days of treatment, her respiratory symptoms and serum creatinine levels improved. Steroid tapering was performed over 15 days. The findings in this case indicate that streptococcal infection is a potential cause of PRS, and that short‐term steroid therapy is an effective treatment. We report a case of a pulmonary‐renal syndrome caused by streptococcal infection. This report highlights the facts that streptococcal infection is a relatively rare cause of pulmonary‐renal syndrome, and short‐term high‐dose steroid monotherapy may be sufficient for its treatment. Pulmonary‐renal syndrome (PRS) is a clinical syndrome characterized by diffuse alveolar haemorrhage and rapidly progressing glomerulonephritis. Occasionally, PRS can lead to severe respiratory failure requiring intensive medical treatment. Autoimmune diseases, including Goodpasture syndrome, antineutrophil cytoplasmic autoantibody (ANCA)‐related vasculitis, and systemic lupus erythematosus, are common causes of PRS.An 18‐year‐old female with uncontrolled atopic dermatitis and bronchial asthma presented to our hospital with a 2‐day history of fever, dyspnea on exertion, and leg edema. She denied hemoptysis or sore throat. She was using inhaled corticosteroids for bronchial asthma but no other medications or supplemental drugs. On arrival at the emergency room of our hospital, she was hypoxic , tachypneic, and febrile (38.5°C). On auscultation, inspiratory crackles were heard in the bilateral lung bases. Her bilateral lower legs showed pitting edema with many scratch scars, and the left leg was erythematous and hot. Pharyngeal redness, white moss, lymphadenopathy, arthritis, sensory disorders, and purpura were absent. Initial laboratory test results revealed an elevated white blood cell count , an elevated C‐reactive protein level (11.6 mg/dl), and slightly decreased haemoglobin level (10.6 g/dl). The serum blood urea nitrogen, creatinine, and brain natriuretic peptide levels were 22 mg/dl, 1.18 mg/dl, and 269 pg/ml, respectively. The activated partial thromboplastin time (25.8 s) and prothrombin time‐international normalized ratio (0.95) were within normal ranges. Further investigation revealed a high anti‐streptolysin‐O (ASLO) titre (950 IU/ml) and low complement component‐3 level (62 mg/dl). The complement component‐4 level was within the normal range, and test results for immunoglobulin (Ig) G, IgA, IgM, antinuclear antibody, perinuclear ANCA (p‐ANCA), cytoplasmic ANCA(c‐ANCA), and anti‐glomerular basement membrane antibody were all negative. Urinalysis revealed 3+ protein, 2+ hematuria, and granular casts. Chest radiography showed an enlarged heart shadow and bilateral diffuse infiltrates with geographic distribution Figure . ComputeLaboratory data, including high titers of ASLO, worsening renal function, and complement component‐3 hypocomplementemia, prompted us to diagnose post‐streptococcal acute glomerulonephritis (PSAGN) caused by cellulitis of the left lower leg. The patient was treated with intravenous cefazolin (3 g/day) and furosemide; however, her respiratory symptoms deteriorated. To investigate the possibility of diffuse alveolar haemorrhage and rule out other pulmonary infections, bronchoscopy was performed under intubation. Bronchoalveolar lavage fluid from the right superior lobar bronchus was red and progressively darkened from the first to the third time owing to bleeding, which was consistent with diffuse alveolar haemorrhage Figure . BronchoThese findings supported the diagnosis of PRS secondary to a skin infection. The patient was treated with intravenous methylprednisolone pulse therapy (1 g/day) for three consecutive days, which resulted in significant improvement in the respiratory symptoms and chest X‐ray findings Figure . MoreoveThis case highlights two important clinical lessons: (1) the patient developed PRS due to a streptococcal infection and (2) the patient was successfully treated with short‐term steroid therapy and remitted without recurrence.Only a handful of cases of PRS caused by streptococcal infections have been reported.Short‐term high‐dose steroid monotherapy may be sufficient to treat PRS caused by streptococcal infection. Steroids and immunosuppressive drugs  and plasma exchange, are potential treatment options for PRS. However, PRS generally has poor prognosis and requires long‐term treatment.In conclusion, streptococcal infection is a relatively rare cause of PRS, and short‐term high‐dose steroid monotherapy may be sufficient for its treatment.Junki Shimokawa drafted the original manuscript. Hiroaki Nagano and Yoshihiko Raita supervised the conduct of this report. All authors reviewed the manuscript draft and revised it critically for intellectual content. All authors approved the final version of the manuscript to be published.None declared.The authors declare that appropriate written informed consent was obtained for the publication of this manuscript and accompanying images.