Risk factors for Coronavirus disease-associated mucormycosis.

BACKGROUND: The epidemiology of the Coronavirus-disease associated mucormycosis (CAM) syndemic is poorly elucidated. We aimed to identify risk factors that may explain the burden of cases and help develop preventive strategies. METHODS: We performed a case-control study comparing cases diagnosed with CAM and taking controls as recovered COVID 19 patients who did not develop mucormycosis. Information on comorbidities, glycemic control, and practices related to COVID-19 prevention and treatment was recorded. Multivariate regression analysis was used to identify independent predictors. RESULTS: A total of 352 patients (152 cases and 200 controls) diagnosed with COVID-19 during April-May 2021 were included. In the CAM group, symptoms of mucormycosis began a mean of 18.9 (SD 9.1) days after onset of COVID-19, and predominantly rhino-sinus and orbital involvement was present. All, but one, CAM cases had conventional risk factors of diabetes and steroid use. On multivariable regression, increased odds of CAM were associated with the presence of diabetes (adjusted OR 3.5, 95% CI 1.1-11), use of systemic steroids (aOR 7.7, 95% CI 2.4-24.7), prolonged use of cloth and surgical masks (vs. no mask, aOR 6.9, 95%CI 1.5-33.1), and repeated nasopharyngeal swab testing during the COVID-19 illness (aOR 1.6, 95% CI 1.2-2.2). Zinc therapy was found to be protective (aOR 0.05, 95%CI 0.01-0.19). Notably, the requirement of oxygen supplementation or hospitalization did not affect the risk of CAM. CONCLUSION: Judicious use of steroids and stringent glycemic control are vital to preventing mucormycosis. Use of clean masks, preference for N95 masks if available, and minimizing swab testing after the diagnosis of COVID-19 may further reduce the incidence of CAM.

SARS-CoV-2 Reinfection Rate and Estimated Effectiveness of the Inactivated Whole Virion Vaccine BBV152 Against Reinfection Among Health Care Workers in New Delhi, India.

Importance: A surge of COVID-19 occurred from March to June 2021, in New Delhi, India, linked to the B.1.617.2 (Delta) variant of SARS-CoV-2. COVID-19 vaccines were rolled out for health care workers (HCWs) starting in January 2021. Objective: To assess the incidence density of reinfection among a cohort of HCWs and estimate the effectiveness of the inactivated whole virion vaccine BBV152 against reinfection. Design, Setting, and Participants: This was a retrospective cohort study among HCWs working at a tertiary care center in New Delhi, India. Exposures: Vaccination with 0, 1, or 2 doses of BBV152. Main Outcomes and Measures: The HCWs were categorized as fully vaccinated (with 2 doses and ≥15 days after the second dose), partially vaccinated (with 1 dose or 2 doses with <15 days after the second dose), or unvaccinated. The incidence density of COVID-19 reinfection per 100 person-years was computed, and events from March 3, 2020, to June 18, 2021, were included for analysis. Unadjusted and adjusted hazard ratios (HRs) were estimated using a Cox proportional hazards model. Estimated vaccine effectiveness (1 - adjusted HR) was reported. Results: Among 15 244 HCWs who participated in the study, 4978 (32.7%) were diagnosed with COVID-19. The mean (SD) age was 36.6 (10.3) years, and 55.0% were male. The reinfection incidence density was 7.26 (95% CI: 6.09-8.66) per 100 person-years (124 HCWs [2.5%], total person follow-up period of 1696 person-years as time at risk). Fully vaccinated HCWs had lower risk of reinfection (HR, 0.14 [95% CI, 0.08-0.23]), symptomatic reinfection (HR, 0.13 [95% CI, 0.07-0.24]), and asymptomatic reinfection (HR, 0.16 [95% CI, 0.05-0.53]) compared with unvaccinated HCWs. Accordingly, among the 3 vaccine categories, reinfection was observed in 60 of 472 (12.7%) of unvaccinated (incidence density, 18.05 per 100 person-years; 95% CI, 14.02-23.25), 39 of 356 (11.0%) of partially vaccinated (incidence density 15.62 per 100 person-years; 95% CI, 11.42-21.38), and 17 of 1089 (1.6%) fully vaccinated (incidence density 2.18 per 100 person-years; 95% CI, 1.35-3.51) HCWs. The estimated effectiveness of BBV152 against reinfection was 86% (95% CI, 77%-92%); symptomatic reinfection, 87% (95% CI, 76%-93%); and asymptomatic reinfection, 84% (95% CI, 47%-95%) among fully vaccinated HCWs. Partial vaccination was not associated with reduced risk of reinfection. Conclusions and Relevance: These findings suggest that BBV152 was associated with protection against both symptomatic and asymptomatic reinfection in HCWs after a complete vaccination schedule, when the predominant circulating variant was B.1.617.2.

Mortality and Clinical Outcomes among Patients with COVID-19 and Diabetes.

Background Diabetes mellitus (DM) is a decisive risk factor for severe illness in coronavirus disease 2019 (COVID-19). India is home to a large number of people with DM, and many of them were infected with COVID-19. It is critical to understand the impact of DM on mortality and other clinical outcomes of COVID-19 infection from this region. Aims The primary objective of our study was to analyze the mortality rate in people with DM infected with COVID-19. The secondary objectives were to assess the effect of various comorbidities on mortality and study the impact of DM on other clinical outcomes. Methods This is a retrospective study of COVID-19 infected patients admitted to a tertiary care hospital in north India in the early phase of the pandemic. Results Of the 1211 cases admitted, 19 were excluded because of incomplete data, and 1192 cases were finally considered for analysis. DM constituted 26.8% of total patients. The overall mortality rate was 6.1%, and the rate was 10.7% in the presence of diabetes (p < 0.01, OR 2.55). In univariate analysis, increased age, chronic kidney disease (CKD), coronary artery disease (CAD), stroke, and cancer were associated with mortality. On multiple logistic regression, the independent predictors of mortality were CAD, CKD, and cancer. Breathlessness and low SpO2 at presentation, extensive involvement in CXR, and elevated ANC/ALC ratio were also significantly associated with mortality. Conclusions The presence of comorbidities such as DM, hypertension, CAD, CKD, and cancer strongly predict the risk of mortality in COVID-19 infection. Early triaging and aggressive therapy of patients with these comorbidities can optimize clinical outcomes.

A systematic review of clinical and laboratory parameters of 3,000 COVID-19 cases.

The coronavirus disease 2019 (COVID-19) has spread worldwide. It is still a pandemic and poses major health problem across the globe. In our review, clinical characteristics and laboratory parameters of COVID-19 patients were compiled systematically, with special reference to pregnant women in order to understand the disease course. An extensive literature search on various scientific databases for relevant manuscripts was conducted, which yielded 7 manuscripts for final analysis. The most common symptoms were fever (85%), cough (70.63%), chest tightness (37.36%), expectoration (33.27%), fatigue (32%), dyspnea (31.95%), and shortness of breath (31.19%), while hemoptysis (1.0%) was the least common. The associated comorbidities were hypertension (21.6%) and diabetes (10.0%). In terms of hematological parameters, lower total leukocyte counts were observed in 65% of cases and biochemical parameters, patients demonstrated elevated levels of albumin (53.72%), lactate dehydrogenase (45.71%), and natriuretic peptide (34.84%); however, total bilirubin was elevated in only 8% of cases. In the acute inflammatory cytokine profile, C-reactive protein (59.0%), tumor necrosis factor (58.0%), erythrocyte sedimentation rate (57.0%), interleukin-2 (IL- 2, 54.0%), and IL-6 (52.0%) levels were increased, while prolactin levels (6.5%) were minimally elevated. The recovery rate was approximately 41%, and mortality was about 6.5%. The study also concluded that the clinical symptoms of COVID-19 were similar among pregnant and non-pregnant women. There was no evidence of vertical transmission of COVID-19 infection. This review critically analyzed COVID-19 as a public health hazard in order to help policy makers, health care givers, and primary physicians to promote early diagnosis and prevention.