Age-Related Risk Factors and Complications of Patients With COVID-19: A Population-Based Retrospective Study

Objective: To study the differences in clinical characteristics, risk factors, and complications across age-groups among the inpatients with the coronavirus disease 2019 (COVID-19).Methods: In this population-based retrospective study, we included all the positive hospitalized patients with COVID-19 at Wuhan City from December 29, 2019 to April 15, 2020, during the first pandemic wave. Multivariate logistic regression analyses were used to explore the risk factors for death from COVID-19. Canonical correlation analysis (CCA) was performed to study the associations between comorbidities and complications.Results: There are 36,358 patients in the final cohort, of whom 2,492 (6.85%) died. Greater age (odds ration [OR] = 1.061 [95% CI 1.057–1.065], p < 0.001), male gender (OR = 1.726 [95% CI 1.582–1.885], p < 0.001), alcohol consumption (OR = 1.558 [95% CI 1.355–1.786], p < 0.001), smoking (OR = 1.326 [95% CI 1.055–1.652], p = 0.014), hypertension (OR = 1.175 [95% CI 1.067–1.293], p = 0.001), diabetes (OR = 1.258 [95% CI 1.118–1.413], p < 0.001), cancer (OR = 1.86 [95% CI 1.507–2.279], p < 0.001), chronic kidney disease (CKD) (OR = 1.745 [95% CI 1.427–2.12], p < 0.001), and intracerebral hemorrhage (ICH) (OR = 1.96 [95% CI 1.323–2.846], p = 0.001) were independent risk factors for death from COVID-19. Patients aged 40–80 years make up the majority of the whole patients, and them had similar risk factors with the whole patients. For patients aged <40 years, only cancer (OR = 17.112 [95% CI 6.264–39.73], p < 0.001) and ICH (OR = 31.538 [95% CI 5.213–158.787], p < 0.001) were significantly associated with higher odds of death. For patients aged >80 years, only age (OR = 1.033 [95% CI 1.008–1.059], p = 0.01) and male gender (OR = 1.585 [95% CI 1.301–1.933], p < 0.001) were associated with higher odds of death. The incidence of most complications increases with age, but arrhythmias, gastrointestinal bleeding, and sepsis were more common in younger deceased patients with COVID-19, with only arrhythmia reaching statistical difference (p = 0.039). We found a relatively poor correlation between preexisting risk factors and complications.Conclusions: Coronavirus disease 2019 are disproportionally affected by age for its clinical manifestations, risk factors, complications, and outcomes. Prior complications have little effect on the incidence of extrapulmonary complications.

Effects of treatment with SGLT-2 inhibitors on arginine-related cardiovascular and renal biomarkers

Background In patients with type 2 diabetes (T2D) sodium-glucose cotransporter 2 (SGLT-2) inhibitors improve glycaemic control as well as cardiovascular and renal outcomes. Their effects on l-arginine (Arg) related risk markers asymmetric and symmetric dimethylarginine (ADMA and SDMA) and the protective biomarker L-homoarginine (hArg) linking T2D to cardiovascular and renal disease have not yet been reported. Methods Plasma and 24-h urine samples taken before and after 6 weeks of treatment were available from two prospective, randomized, double-blind, placebo-controlled, cross-over trials with empagliflozin (71 patients analyzed, NCT02471963) and dapagliflozin (59 patients analyzed, NCT02383238). In these samples, concentrations of hArg, Arg, ADMA, SDMA, and creatinine were determined by liquid-chromatography coupled to tandem mass-spectrometry. Additionally, intraindividual changes of the biomarkers in plasma were correlated with intraindividual changes of clinical parameters. Results Treatment with empagliflozin and dapagliflozin was associated with a reduction of plasma hArg by 17.5% and 13.7% (both p < 0.001), respectively, and increase in plasma SDMA concentration of 6.7% and 3.6%, respectively (p < 0.001 and p < 0.05), while plasma Arg and ADMA concentrations were not significantly altered. 24-h urinary excretion of ADMA was reduced by 15.2% after treatment with empagliflozin (p < 0.001) but not after dapagliflozin treatment, while excretion of the other markers was not significantly altered. Renal clearance of SDMA was reduced by 9.1% and 3.9% for both drugs (both p < 0.05). A reduction in ADMA clearance was observable after empagliflozin treatment only (− 15.5%, p < 0.001), but not after dapagliflozin. Renal clearance of hArg and Arg was not significantly altered. Treatment effects on l-arginine related biomarkers were not constantly correlated with effects on glycated hemoglobin, fasting plasma glucose, body mass index, and systolic blood pressure. Conclusions Treatment with SGLT-2 inhibitors has divergent effects on Arg-related biomarkers and could affect risk estimates associated with these markers. The observed effects are unlikely to explain the known cardiovascular and renal benefits of treatment with empagliflozin or dapagliflozin but still may indicate new therapeutic approaches in patients treated with SGLT-2 inhibitors. Trial registrationhttp://www.clinicaltrials.gov: NCT02471963 (registered 15th June 2015, retrospectively registered) and NCT02383238.

Study on clinical characteristics and related factors of schizophrenic patients with intestinal obstruction

Background There are still few studies on the clinical characteristics and related risk factors of schizophrenia patients with intestinal obstruction. Our aim is to explore the clinical characteristics and related risk factors of schizophrenia patients with intestinal obstruction. Methods This study focused on schizophrenia patients with intestinal obstruction who were hospitalized in the psychiatric department of a hospital in Wuhan from January 2007 to December 2020 as the main research object. We intend to retrospectively analyze the clinical characteristics and related risk factors of schizophrenia patients with intestinal obstruction. Results In the 1937 persons with schizophrenia included in this study, 97 patients were complicated with intestinal obstruction, and the incidence was 5.01%.The results of the study showed that patients with age ≥ 60 years old, visiting time ≥ 24 h, hospital stay ≥ 90 days, history of abdominal surgery, course of disease ≥ 5 years, male, and patients with cardiovascular and cerebrovascular diseases are prone to intestinal obstruction; Logistic multiple regression analysis showed that the related risk factors of schizophrenia patients with intestinal obstruction mainly included the patient's age, visiting time, length of hospital stay, history of abdominal surgery, course of disease and gender. Conclusion The older the age, the longer the hospital stay, the longer the course of the disease, the history of previous surgery, and the male schizophrenia who do not see a doctor within 24 h of the onset, the risk of intestinal obstruction is higher, and it is easy to be misdiagnosed and even life-threatening.

Quantitative Framework for Establishing Low-Risk Inter-District Travel Corridors During COVID-19

Aspirations to slow down the spread of novel Coronavirus (COVID-19) resulted in unprecedented restrictions on personal and work-related travels in various nations across the globe in 2020. As a consequence, economic activities within and across the countries were almost halted. As restrictions loosen and cities start to resume public and private transport to revamp the economy, it becomes critical to assess the commuters’ travel-related risk in light of the ongoing pandemic. The paper develops a generalizable quantitative framework to evaluate the commute-related risk arising from inter-district and intra-district travel by combining nonparametric data envelopment analysis for vulnerability assessment with transportation network analysis. It demonstrates the application of the proposed model for establishing travel corridors within and across Gujarat and Maharashtra, two Indian states that have reported many COVID-19 cases since early April 2020. The findings suggest that establishing travel corridors between a pair of districts solely based on the health vulnerability indices of the origin and destination discards the en-route travel risks from the prevalent pandemic, underestimating the threat. For example, while the resultant of social and health vulnerabilities of Narmada and Vadodara districts is relatively moderate, the en-route travel risk exacerbates the overall travel risk of travel between them. The study provides a quantitative framework to identify the alternate path with the least risk and hence establish low-risk travel corridors within and across states while accounting for social and health vulnerabilities in addition to transit-time related risks.

Sex Difference and Rupture Rate of Intracranial Aneurysms: An Individual Patient Data Meta-Analysis

Background and Purpose: In previous studies, women had a higher risk of rupture of intracranial aneurysms than men, but female sex was not an independent risk factor. This may be explained by a higher prevalence of patient- or aneurysm-related risk factors for rupture in women than in men or by insufficient power of previous studies. We assessed sex differences in rupture rate taking into account other patient- and aneurysm-related risk factors for aneurysmal rupture. Methods: We searched Embase and Pubmed for articles published until December 1, 2020. Cohorts with available individual patient data were included in our meta-analysis. We compared rupture rates of women versus men using a Cox proportional hazard regression model adjusted for the PHASES score (Population, Hypertension, Age, Size of Aneurysm, Earlier Subarachnoid Hemorrhage From Another Aneurysm, Site of Aneurysm), smoking, and a positive family history of aneurysmal subarachnoid hemorrhage. Results: We pooled individual patient data from 9 cohorts totaling 9940 patients (6555 women, 66%) with 12 193 unruptured intracranial aneurysms, and 24 357 person-years follow-up. Rupture occurred in 163 women (rupture rate 1.04%/person-years [95% CI, 0.89–1.21]) and 63 men (rupture rate 0.74%/person-years [95% CI, 0.58–0.94]). Women were older (61.9 versus 59.5 years), were less often smokers (20% versus 44%), more often had internal carotid artery aneurysms (24% versus 17%), and larger sized aneurysms (≥7 mm, 24% versus 23%) than men. The unadjusted women-to-men hazard ratio was 1.43 (95% CI, 1.07–1.93) and the adjusted women/men ratio was 1.39 (95% CI, 1.02–1.90). Conclusions: Women have a higher risk of aneurysmal rupture than men and this sex difference is not explained by differences in patient- and aneurysm-related risk factors for aneurysmal rupture. Future studies should focus on the factors explaining the higher risk of aneurysmal rupture in women.

NF-κB-Related Metabolic Gene Signature Predicts the Prognosis and Immunotherapy Response in Gastric Cancer

Background. Sufficient evidence indicated the crucial role of NF-κB family played in gastric cancer (GC). The novel discovery that NF-κB could regulate cancer metabolism and immune evasion greatly increased its attraction in cancer research. However, the correlation among NF-κB, metabolism, and cancer immunity in GC still requires further improvement. Methods. TCGA, hTFtarget, and MSigDB databases were employed to identify NF-κB-related metabolic genes (NFMGs). Based on NFMGs, we used consensus clustering to divide GC patients into two subtypes. GSVA was employed to analyze the enriched pathway. ESTIMATE, CIBERSORT, ssGSEA, and MCPcounter algorithms were applied to evaluate immune infiltration in GC. The tumor immune dysfunction and exclusion (TIDE) algorithm was used to predict patients’ response to immunotherapy. We also established a NFMG-related risk score by using the LASSO regression model and assessed its efficacy in TCGA and GSE62254 datasets. Results. We used 27 NFMGs to conduct an unsupervised clustering on GC samples and classified them into two clusters. Cluster 1 was characterized by high active metabolism, tumor mutant burden, and microsatellite instability, while cluster 2 was featured with high immune infiltration. Compared to cluster 2, cluster 1 had a better prognosis and higher response to immunotherapy. In addition, we constructed a 12-NFMG (ADCY3, AHCY, CHDH, GUCY1A2, ITPA, MTHFD2, NRP1, POLA1, POLR1A, POLR3A, POLR3K, and SRM) risk score. Followed analysis indicated that this risk score acted as an effectively prognostic factor in GC. Conclusion. Our data suggested that GC subtypes classified by NFMGs may effectively guide prognosis and immunotherapy. Further study of these NFMGs will deepen our understanding of NF-κB-mediated cancer metabolism and immunity.

Disease Progression Detection via Deep Sequence Learning of Successive Radiographic Scans

The highly rapid spread of the current pandemic has quickly overwhelmed hospitals all over the world and motivated extensive research to address a wide range of emerging problems. The unforeseen influx of COVID-19 patients to hospitals has made it inevitable to deploy a rapid and accurate triage system, monitor progression, and predict patients at higher risk of deterioration in order to make informed decisions regarding hospital resource management. Disease detection in radiographic scans, severity estimation, and progression and prognosis prediction have been extensively studied with the help of end-to-end methods based on deep learning. The majority of recent works have utilized a single scan to determine severity or predict progression of the disease. In this paper, we present a method based on deep sequence learning to predict improvement or deterioration in successive chest X-ray scans and build a mathematical model to determine individual patient disease progression profile using successive scans. A deep convolutional neural network pretrained on a diverse lung disease dataset was used as a feature extractor to generate the sequences. We devised three strategies for sequence modeling in order to obtain both fine-grained and coarse-grained features and construct sequences of different lengths. We also devised a strategy to quantify positive or negative change in successive scans, which was then combined with age-related risk factors to construct disease progression profile for COVID-19 patients. The age-related risk factors allowed us to model rapid deterioration and slower recovery in older patients. Experiments conducted on two large datasets showed that the proposed method could accurately predict disease progression. With the best feature extractor, the proposed method was able to achieve AUC of 0.98 with the features obtained from radiographs. Furthermore, the proposed patient profiling method accurately estimated the health profile of patients.