Microbiology Clinical Culture Diagnostic Yields and Antimicrobial Resistance Proportions before and during the COVID-19 Pandemic in an Indian Community Hospital and Two US Community Hospitals.

Studies comparing the impact of the COVID-19 pandemic on diagnostic microbiology culture yields and antimicrobial resistance proportions in low-to-middle-income and high-income countries are lacking. A retrospective study using blood, respiratory, and urine microbiology data from a community hospital in India and two community hospitals (Hospitals A and B) in St. Louis, MO, USA was performed. We compared the proportion of cultures positive for selected multi-drug-resistant organisms (MDROs) listed on the WHO's priority pathogen list both before the COVID-19 pandemic (January 2017-December 2019) and early in the COVID-19 pandemic (April 2020-October 2020). The proportion of blood cultures contaminated with coagulase-negative Staphylococcus (CONS) was significantly higher during the pandemic in all three hospitals. In the Indian hospital, the proportion of carbapenem-resistant (CR) Klebsiella pneumoniae in respiratory cultures was significantly higher during the pandemic period, as was the proportion of CR Escherichia coli in urine cultures. In the US hospitals, the proportion of methicillin-resistant Staphylococcus aureus in blood cultures was significantly higher during the pandemic period in Hospital A, while no significant increase in the proportion of Gram-negative MDROs was observed. Continuity of antimicrobial stewardship activities and better infection prevention measures are critical to optimize outcomes and minimize the burden of antimicrobial resistance among COVID-19 patients.

Development and Validation of the RCOS Prognostic Index: A Bedside Multivariable Logistic Regression Model to Predict Hypoxaemia or Death in Patients with SARS-CoV-2 Infection.

Introduction: Previous COVID-19 prognostic models have been developed in hospital settings and are not applicable to COVID-19 cases in the general population. There is an urgent need for prognostic scores aimed to identify patients at high risk of complications at the time of COVID-19 diagnosis. Methods: The RDT COVID-19 Observational Study (RCOS) collected clinical data from patients with COVID-19 admitted regardless of the severity of their symptoms in a general hospital in India. We aimed to develop and validate a simple bedside prognostic score to predict the risk of hypoxaemia or death. Results: 4035 patients were included in the development cohort and 2046 in the validation cohort. The primary outcome occurred in 961 (23.8%) and 548 (26.8%) patients in the development and validation cohorts, respectively. The final model included 12 variables: age, systolic blood pressure, heart rate, respiratory rate, aspartate transaminase, lactate dehydrogenase, urea, C-reactive protein, sodium, lymphocyte count, neutrophil count, and neutrophil/lymphocyte ratio. In the validation cohort, the area under the receiver operating characteristic curve (AUROCC) was 0.907 (95% CI, 0.892-0.922), and the Brier Score was 0.098. The decision curve analysis showed good clinical utility in hypothetical scenarios where the admission of patients was decided according to the prognostic index. When the prognostic index was used to predict mortality in the validation cohort, the AUROCC was 0.947 (95% CI, 0.925-0.97) and the Brier score was 0.0188. Conclusions: The RCOS prognostic index could help improve the decision making in the current COVID-19 pandemic, especially in resource-limited settings with poor healthcare infrastructure such as India. However, implementation in other settings is needed to cross-validate and verify our findings.