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ObjectivesTo determine association of biomarkers high sensitivity C-reactive protein (hsCRP), D-dimer, interleukin-6 (IL-6), lactic dehydrogenase (LDH), ferritin and neutrophil-lymphocyte ratio (NLR) at hospital admission with clinical features and outcomes in Covid-19. MethodsSuccessive virologically confirmed Covid-19 patients hospitalized from April 2020 to July 2021 were recruited in a prospective registry. Details of clinical presentation, investigations, management and outcomes were recorded. All the biomarkers were divided into tertiles to determine associations with clinical features and outcomes. Numerical data are presented in median and interquartile range (IQR 25-75). Univariate and multivariate (age, sex, risk factor, comorbidity adjusted) odds ratio (OR) and 95% confidence intervals (CI) were calculated to determine association of deaths with each biomarker. ResultsWe identified 3036 virologically confirmed Covid-19 patients during the study period, 1215 were hospitalized and included in the present study. Men were 70.0%, aged >60y 44.8%, hypertension 44.8% diabetes 39.6% and cardiovascular disease 18.9%. Median symptom duration was 5 days (IQR 4-7) and SpO2 95% (90-97). Total white cell count was 6.9x103/{micro}l, (5.0-9.8), neutrophils 79.2% (68.1-88.2) and lymphocytes 15.8% (8.7-25.5). Medians (IQR) for biomarkers were hsCRP 6.9 mg/dl (2.2-18.9), D-dimer 464 ng/dl (201-982), IL-6 20.1 ng/dl (6.5-60.4), LDH 284 mg/dl (220-396) and ferritin 351 mg/dl (159-676). Oxygen support at admission was in 38.6%, and non-invasive or invasive ventilatory support in 11.0% and 11.6% respectively. 173 (13.9%) patients died and 15 (1.2%) transferred to hospice care. For each biomarker, those in the second and third tertiles, compared to the first, had worse clinical and laboratory abnormalities, and greater oxygen and ventilatory support. Multivariate adjusted OR (95% CI) for deaths in second and third vs first tertiles, respectively, were for hsCRP 2.29(1.14-4.60) and 13.39(7.23-24.80); D-dimer 3.26(1.31-7.05) and 13.89(6.87-28.27); IL-6 2.61(1.31-5.18) and 10.96(5.88-20.43); ferritin 3.19(1.66-6.11) and 9.13(4.97-16.78); LDH 1.85(0.87-3.97) and 10.51(5.41-20.41); and NLR 3.34(1.62-6.89) and 17.52(9.03-34.00) (p<0.001). ConclusionsIn Covid-19, high levels of biomarkers-hsCRP, D-dimer, IL-6, LDH, ferritin and NLR are associated with more severe illness and significantly greater in-hospital mortality. NLR, a simple, widely available and inexpensive investigation provides prognostic information similar to the more expensive biomarkers.
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Background & ObjectiveCovid-19 pandemic has led to multiple waves secondary to mutations in SARS-CoV-2 and emergence of variants of concern (VOC). Clinical characteristics of delta (B.1.617.2) VOC are not well reported. To compare demographic, clinical and laboratory features and outcomes in the second Covid-19 wave in India (delta VOC) with the previous wave we performed a registry-based study. MethodsSuccessive SARS-CoV-2 reverse transcriptase-polymerase chain reaction (RT-PCR) confirmed Covid-19 patients presenting to our Advanced Covid Care hospital were prospectively recruited. In the first phase (wave) from March-December 2020, 1395 of 7476 (18.7%) suspected patients tested positive and 863 (61.89%) hospitalized, while in second wave from January-July 2021 out of 1641 confirmed cases out of 8680 (19.4%) suspected 388 (23.6%) were hospitalized. Details of clinical and laboratory features at admission to hospital, management and outcomes in the two waves have been compared. ResultsIn both cohorts, majority were men and 20% less than 40 years. Prevalence of hypertension, diabetes and cardiovascular diseases was more than 20%. Second wave patients had similar pre-hospitalization symptom duration but had significantly greater cough, fever and shortness of breath and lower SpO2 at presentation with greater lymphopenia, C-reactive proteins, interleukin-6, ferritin, lactic dehydrogenase and transaminases. In the second vs first wave patients, requirement of supplementary oxygen (47.9% vs 34.3%), prone positioning (89.2 vs 38.6%), high flow nasal oxygen(15.7 vs 9.1%), non-invasive ventilation (14.4 vs 9.5%), invasive ventilation (16.2 vs 9.5%), steroids (94.1 vs 85.9%), remdesivir (91.2 vs 76.0%) and anticoagulants (94.3 vs 76.0%) was greater (p<0.001). Median (IQR) length of stay [8 (6-10) vs 7 (5-10) days] as well as ICU stay [9 (5-13) vs 6 (2-10) days] was more in second wave (p<0.001). In-hospital deaths occurred in 173 patients (13.9%) and were significantly more in the second wave, 75 (19.3%), compared to the first, 98 (11.5%); unadjusted odds ratio (95% CI) 1.84 (1.32-2.55) which did not change significantly with adjustment for age and sex (2.03, 1.44-2.86), and age, sex and comorbidities (2.09, 1.47-2.95). Greater disease severity at presentation was associated with mortality in both the waves. ConclusionsCovid-19 patients hospitalized during the second wave of the epidemic (delta variant) had more severe disease with greater dyspnea, hypoxia, hematological and biochemical abnormalities compared to first wave patients. They had greater length of stay in intensive care unit, oxygen requirement, non-invasive and invasive ventilatory support. The in-hospital mortality in the second wave was double of the first.
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ObjectiveGreater COVID-19 related mortality has been reported among persons with various non-communicable diseases (NCDs). We performed an ecological study to determine the association of state-level cases and deaths with NCD risk factors and healthcare and social indices. MethodsWe obtained cumulative national and state-level data on COVID-19 cases and deaths from publicly available database www.covid19india.org from February to end November 2020. To identify association with major NCD risk factors, NCDs, healthcare related and social variables we obtained data from public sources. Association was determined using univariate and multivariate statistics. ResultsMore than 9.5 million COVID-19 cases and 135,000 deaths have been reported in India at end November 2020. There is significant positive correlation (Pearsons r) of state-level COVID-19 cases and deaths per million, respectively, with NCD risk factors- obesity (0.64, 0.52), hypertension (0.28, 0.16), diabetes (0.66, 0.46), literacy, NCD epidemiological transition index (0.58, 0.54) and ischemic heart disease mortality (0.22, 0.33). Correlation is also observed with indices of healthcare access and quality (0.71, 0.61), urbanization (0.75, 0.73) and human (0.61, 0.56) and sociodemographic (0.70, 0.69) development. Multivariate adjusted analyses shows strong correlation of COVID-19 burden and deaths with NCD risk factors (r2=0.51, 0.43), NCDs (r2=0.32, 0.16) and healthcare related factors (r2=0.52, 0.38). ConclusionsCOVID-19 disease burden and mortality in India is ecologically associated with greater state-level burden of NCDs and risk factors, especially obesity and diabetes. KEY MESSAGESO_LIThere is significant state-level variability in COVID-19 cases and deaths in India. C_LIO_LIIn a macrolevel statistical analysis we find that Indian states with better human and sociodemographic indices, more literacy, longer age, greater burden of non-communicable diseases and risk factors have greater COVID-19 case burden and mortality. C_LIO_LINon-communicable disease risk factors- obesity and diabetes are the most important determinants on multivariate analyses. C_LI
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Background & ObjectiveThe covid-19 epidemic is rapidly escalating in India and unlike developed countries there is no evidence of plateau or decline in the past 6 months. To evaluate association of state-level sociodemographics with incident cases and deaths we performed an ecological study. MethodsPublicly available data sources were used. Absolute number of covid-19 cases and deaths were obtained and cases and deaths/million in each state calculated from February to July 2020. To assess association of state level disease burden with sociodemographic variables (urbanization, human development, healthcare availability, healthcare access and quality etc.) we determined Pearsons correlation and logarithmic trends. ResultsCovid-19 in India has led to >2,000,000 cases and 45,000 deaths by end July 2020. There is large variation in state-level cases/million ranging from 7247 (Delhi), 3728 (Goa) and 3427 (Maharashtra) to less than 300/million in a few. Deaths/million range from 212 (Delhi), 122 (Maharashtra) and 51 (Tamilnadu) to 2 in north-eastern states. Most of the high burden states (except Delhi) are reporting increasing burden and deaths with the largest increase in July 2020. There is a significant positive correlation of urbanization with covid-19 cases (r=0.65, R2=0.35) and deaths (r=0.60, R2=0.28) and weaker correlation with other sociodemographic variables. From March to July 2020, stable R2 value for urbanization is observed with cases (0.37 to 0.39) while it is increasing for deaths (0.10 to 0.28). ConclusionsCovid-19 epidemic is escalating in India and cases as well as deaths are significantly greater in more urbanized states. Prevention, control and treatment should focus on urban health systems.
