COVID-19 susceptibility and clinical outcomes in inflammatory bowel disease: An updated systematic review and meta-analysis.

The susceptibility, risk factors, and prognosis of COVID-19 in patients with inflammatory bowel disease (IBD) remain unknown. Thus, our study aims to assess the prevalence and clinical outcomes of COVID-19 in IBD. We searched PubMed, EMBASE, and medRxiv from 2019 to 1 June 2022 for cohort and case-control studies comparing the prevalence and clinical outcomes of COVID-19 in patients with IBD and in the general population. We also compared the outcomes of patients receiving and not receiving 5-aminosalicylates (ASA), tumour necrosis factor antagonists, biologics, systemic corticosteroids, or immunomodulators for IBD. Thirty five studies were eligible for our analysis. Pooled odds ratio of COVID-19-related hospitalisation, intensive care unit (ICU) admission, or death in IBD compared to in non-IBD were 0.58 (95% confidence interval (CI) = 0.28-1.18), 1.09 (95% CI = 0.27-4.47), and 0.67 (95% CI = 0.32-1.42), respectively. Inflammatory bowel disease was not associated with increased hospitalisation, ICU admission, or death. Susceptibility to COVID-19 did not increase with any drugs for IBD. Hospitalisation, ICU admission, and death were more likely with 5-ASA and corticosteroid use. COVID-19-related hospitalisation (Odds Ratio (OR): 0.53; 95% CI = 0.38-0.74) and death (OR: 0.13; 95% CI = 0.13-0.70) were less likely with Crohn's disease than ulcerative colitis (UC). In conclusion, IBD does not increase the mortality and morbidity of COVID-19. However, physicians should be aware that additional monitoring is needed in UC patients or in patients taking 5-ASA or systemic corticosteroids.

Early Biomarker Signatures in Surgical Sepsis.

INTRODUCTION: Sepsis has complex, time-sensitive pathophysiology and important phenotypic subgroups. The objective of this study was to use machine learning analyses of blood and urine biomarker profiles to elucidate the pathophysiologic signatures of subgroups of surgical sepsis patients. METHODS: This prospective cohort study included 243 surgical sepsis patients admitted to a quaternary care center between January 2015 and June 2017. We applied hierarchical clustering to clinical variables and 42 blood and urine biomarkers to identify phenotypic subgroups in a development cohort. Clinical characteristics and short-term and long-term outcomes were compared between clusters. A naïve Bayes classifier predicted cluster labels in a validation cohort. RESULTS: The development cohort contained one cluster characterized by early organ dysfunction (cluster I, n = 18) and one cluster characterized by recovery (cluster II, n = 139). Cluster I was associated with higher Acute Physiologic Assessment and Chronic Health Evaluation II (30 versus 16, P < 0.001) and SOFA scores (13 versus 5, P < 0.001), greater prevalence of chronic cardiovascular and renal disease (P < 0.001) and septic shock (78% versus 17%, P < 0.001). Cluster I had higher mortality within 14 d of sepsis onset (11% versus 1.5%, P = 0.001) and within 1 y (44% versus 20%, P = 0.032), and higher incidence of chronic critical illness (61% versus 30%, P = 0.001). The Bayes classifier achieved 95% accuracy and identified two clusters that were similar to development cohort clusters. CONCLUSIONS: Machine learning analyses of clinical and biomarker variables identified an early organ dysfunction sepsis phenotype characterized by inflammation, renal dysfunction, endotheliopathy, and immunosuppression, as well as poor short-term and long-term clinical outcomes.