ABSTRACT
Severe COVID-19 frequently features a systemic deluge of cytokines. Circulating cytokines that can stratify risks are useful for more effective triage and management. Here, we ran a machine-learning algorithm on a dataset of 36 plasma cytokines in a cohort of severe COVID-19 to identify cytokine/s useful for describing the dynamic clinical state in multiple regression analysis. We performed RNA-sequencing of circulating blood cells collected at different time-points. From a Bayesian Information Criterion analysis, a combination of interleukin-8 (IL-8), Eotaxin, and Interferon-γ (IFNγ) was found to be significantly linked to blood oxygenation over seven days. Individually testing the cytokines in receiver operator characteristics analyses identified IL-8 as a strong stratifier for clinical outcomes. Circulating IL-8 dynamics paralleled disease course. We also revealed key transitions in immune transcriptome in patients stratified for circulating IL-8 at three time-points. The study identifies plasma IL-8 as a key pathogenic cytokine linking systemic hyper-inflammation to the clinical outcomes in COVID-19.
Subject(s)
COVID-19 , Interleukin-8 , Humans , Bayes Theorem , Cytokines , Disease ProgressionABSTRACT
OBJECTIVES: This study aims to describe the demographic and clinical profile and ascertain the determinants of outcome among hospitalised COVID-19 adult patients enrolled in the National Clinical Registry for COVID-19 (NCRC). METHODS: NCRC is an on-going data collection platform operational in 42 hospitals across India. Data of hospitalized COVID-19 patients enrolled in NCRC between 1st September 2020 to 26th October 2021 were examined. RESULTS: Analysis of 29,509 hospitalised, adult COVID-19 patients [mean (SD) age: 51.1 (16.2) year; male: 18752 (63.6%)] showed that 15678 (53.1%) had at least one comorbidity. Among 25715 (87.1%) symptomatic patients, fever was the commonest symptom (72.3%) followed by shortness of breath (48.9%) and dry cough (45.5%). In-hospital mortality was 14.5% (n = 3957). Adjusted odds of dying were significantly higher in age-group ≥60 years, males, with diabetes, chronic kidney diseases, chronic liver disease, malignancy, and tuberculosis, presenting with dyspnea and neurological symptoms. WHO ordinal scale 4 or above at admission carried the highest odds of dying [5.6 (95% CI: 4.6, 7.0)]. Patients receiving one [OR: 0.5 (95% CI: 0.4, 0.7)] or two doses of anti-SARS CoV-2 vaccine [OR: 0.4 (95% CI: 0.3, 0.7)] were protected from in-hospital mortality. CONCLUSIONS: WHO ordinal scale at admission is the most important independent predictor for in-hospital death in COVID-19 patients. Anti-SARS-CoV2 vaccination provides significant protection against mortality.
ABSTRACT
Venous thromboembolism (VTE) and disseminated intravascular coagulation (DIC) are frequent cardiovascular and/or respiratory complications among hospitalized patients of COVID-19 infection. A relatively high mortality of severe coronavirus disease 2019 (COVID-19) is worrying, and the application of heparin in COVID-19 has been assessed and recommended with some expert consensus because of the risk of DIC and venous thromboembolism. However, "Risk Benefit Analysis" on the aspect of safety in using low molecular weight heparin (LMWH) in COVID-19 patients for thrombosis prophylaxis has been explained below with a few case studies and detailed information from various clinical evidence. COVID-19 infection has been associated with inflammation and a prothrombotic state, with increase in fibrin, fibrin degradation products, fibrinogen, and D-dimers. Heparin treatment including unfractionated and low molecular weight heparin appears to be associated with better prognosis in severe COVID-19 patients with coagulopathy. Major studies since the onset of this pandemic, found better prognosis in severe COVID-19 patients meeting SIC criteria or with markedly elevated D-dimer, by approaching thrombosis prophylaxis with LMWH.