Study of Characteristics of COVID-19 Patients with Fatal Outcome during Wave-2 from a Tertiary Care Center in Western India.

BACKGROUND: A large surge of intensive care unit (ICU) admissions leading to mortal outcome was observed in wave-2 of coronavirus disease 2019 (COVID-19) due to the higher virulence of the Delta variant of the COVID-19 virus, which led to the scarcity of resources in hospitals. This study was done to observe the clinical characteristics of COVID-19 patients with fatal outcomeMaterials and methods: We conducted a retrospective cross-sectional study in adults with COVID-19 pneumonia having fatal outcome during wave-2 of COVID-19, and their clinical characteristics were studiedResults: Out of 136 patients included in the study, the most common risk factors leading to adverse outcome were in the male gender, age (middle and elderly), with hypertension and diabetes mellitus (DM) as predominant comorbidities, early onset dyspnea, high C-reactive protein (CRP), high neutrophil to lymphocyte ratio (NLR), high D-dimer, bilateral lower zone involvement of lungs in chest X-ray (CXR), and development of acute kidney injury (AKI)Conclusion: The characteristics of the severely ill COVID-19 patients highlighted in the study could help clinicians in the early identification and management of high-risk patients. This study would help with resource planning and preparation for further COVID-19 waves and future pandemics.

Evaluation of a fast-and-frugal clinical decision algorithm ('pathways') on clinical outcomes in hospitalised patients with COVID-19 treated with anticoagulants.

RATIONALE, AIMS AND OBJECTIVES: Critics have charged that evidence-based medicine (EBM) overemphasises algorithmic rules over unstructured clinical experience and intuition, but the role of structured decision support systems in improving health outcomes remains uncertain. We aim to assess if delivery of anticoagulant prophylaxis in hospitalised patients with COVID-19 according to an algorithm based on evidence-based clinical practice guideline (CPG) improved clinical outcomes compared with administration of anticoagulant treatment given at individual practitioners' discretion. METHODS: An observational design consisting of the analysis of all acutely ill, consecutive patients (n = 1783) with confirmed COVID-19 diagnosis admitted between 10 March 2020 to 11 January 2022 to an US academic center. American Society of Haematology CPG for anticoagulant prophylaxis in hospitalised patients with COVID-19 was converted into a clinical pathway and translated into fast-and-frugal decision (FFT) tree ('algorithm'). We compared delivery of anticoagulant prophylaxis in hospitalised patients with COVID-19 according to the FFT algorithm with administration of anticoagulant treatment given at individual practitioners' discretion. RESULTS: In an adjusted analysis, using combination of Lasso (least absolute shrinkage and selection operator) and propensity score based weighting [augmented inverse-probability weighting] statistical techniques controlling for cluster data, the algorithm did not reduce death, venous thromboembolism, or major bleeding, but helped avoid longer hospital stay [number of patients needed to be treated (NNT) = 40 (95% CI: 23-143), indicating that for every 40 patients (23-143) managed on FFT algorithm, one avoided staying in hospital longer than 10 days] and averted admission to intensive-care unit (ICU) [NNT = 19 (95% CI: 13-40)]. All model's selected covariates were well balanced. The results remained robust to sensitivity analyses used to test the stability of the findings. CONCLUSIONS: When delivered using a structured FFT algorithm, CPG shortened the hospital stay and help avoided admission to ICU, but it did not affect other relevant outcomes.