ABSTRACT
BackgroundLung ultrasound is a popular point of care test that correlates well with computed tomography for lung pathologies. While previous studies have shown its ability to detect COVID-19 related lung pathology, we aimed to evaluate the utility of lung ultrasound in the triage and prognostication of COVID-19 patients by determining its ability to predict clinical severity and outcomes. MethodsThis was a prospective, cross-sectional, observational, single centre study done at JPNATC and AIIMS, New Delhi, India. Consenting eligible patients aged 18 years or more were included if hospitalised with microbiologically confirmed COVID-19 and classified as mild, moderate (respiratory rate >24/min OR SpO2<94% on room air) and severe COVID-19 (respiratory rate >30/min OR SpO2<90% on room air) at the time of enrolment. The lungs were systematically assessed with ultrasound after division into 14 zones (4 anteriorly, 4 axillary and 6 posteriorly). Clinical and laboratory parameters including arterial blood gas analysis at the time of evaluation were recorded. Patients were followed till death or discharge. The primary objective was to determine the correlation between clinical severity and lung ultrasound profiles (no. of A, B and C profiles, and the total number of areas involved). Secondary objectives included assessment of the correlation between lung ultrasound profiles and clinical outcomes and development of a statistical model incorporating ultrasound and clinical parameters to allow prediction of COVID-19 related severity and outcomes. FindingsBetween October 1, 2020, and January 31,2021, patients were screened for inclusion and total n=60 patients were evaluated and included in the final analysis. The most common abnormality seen were B lines, seen in at least one zone in n=53 (88.33%) of cases. A median of 9 (IQR: 5-12) zones of the 14 assessed had a B-profile. The total number of abnormal areas (zones with a B or C profile) correlated significantly with the PaO2/FiO2 ratio ({rho}= -0.7232, p<0.0001) and SpO2/FiO2 ratio ({rho}= -0.6866, p<0.0001), and differed significantly between mild and moderate vs severe cases (p=0.0026 mild vs moderate, p<0.0001 mild vs severe, p=0.0175 moderate vs severe). The total number of B lines were predictors of mortality (p=0.0188, OR 1.03, 95% CI 1.003-1.060). Statistical models that incorporated total number of B-lines, CRP and anticoagulation use could predict mortality (p=0.0124, pseudo R2=0.1740) with an AUC= 0.7682 (95% CI=0.6176-0.9188), and the total number of involved areas and LDH levels could distinguish severe disease from mild/moderate disease (p<0.0001, Pseudo R2=0.3822), AUC = 0.8743 (95% CI=0.7752-0.9733). A simplified cut off of [≥]6 involved areas (of the 14 assessed) was 100% sensitive and 52% specific for differentiating severe disease from mild and moderate ones. InterpretationIn patients with COVID-19, increasing involvement of the lungs as assessed by ultrasonography correlates significantly with clinical severity and outcomes. These findings may be utilized in future prospective studies to validate the use of lung ultrasound to triage and prognosticate patients with COVID-19 infection. Author ApprovalAll authors have seen and approved the manuscript Competing interestsThere are no potential competing interests Data availability StatementAll data referred to in the manuscript shall be provided when asked for. DisclaimersThe authors have nothing to disclose Funding statementNo funding source was involved.
ABSTRACT
BackgroundSeroprevalence of IgG antibodies against SARS-CoV-2 is an important tool to estimate the true extent of infection in a population. However, seroprevalence studies have been scarce in South East Asia including India, which, as of now, carries the third largest burden of confirmed cases in the world. The present study aimed to estimate the seroprevalence of anti-SARS-CoV-2 IgG antibody among hospitalized patients at one of the largest government hospital in India. MethodThis cross-sectional study, conducted at a tertiary care hospital in North India, recruited consecutive patients who were negative for SARS-CoV-2 by RT-PCR or CB-NAAT. Anti-SARS-CoV-2 IgG antibody levels targeting recombinant spike receptor-binding domain (RBD) protein of SARS CoV-2 were estimated in serum sample by the ELISA method. ResultsA total of 212 hospitalized patients were recruited in the study with mean age ({+/-}SD) of 41.2 ({+/-}15.4) years and 55% male population. Positive serology against SARS CoV-2 was detected in 19.8% patients(95% CI 14.7-25.8). Residency in Delhi conferred a higher frequency of seropositivity 26.5% (95% CI 19.3-34.7) as compared to that of other states 8% (95% CI 3.0-16.4) with p value 0.001. No particular age groups or socio-economic strata showed a higher proportion of seropositivity. ConclusionAround, one-fifth of hospitalized patients, who were not diagnosed with COVID-19 before, demonstrated seropositivity against SARS-CoV-2. While there was no significant difference in the different age groups and socio-economic classes; residence in Delhi was associated with increased risk (relative risk of 3.62, 95% CI 1.59-8.21)
