Predictors and patterns of empirical antibiotic therapy and associated outcomes in COVID-19 patients: a retrospective study in a tertiary care facility in South India.

BACKGROUND: The coronavirus disease (COVID-19) led to a global health crisis. Inappropriate use of antibiotics in COVID-19 patients has been a concern, leading to antimicrobial resistance. This study evaluated the patterns and predictors of empirical antibiotic therapy in COVID-19 patients and associated outcomes. METHODS: A hospital-based retrospective study was conducted with 525 patients admitted to Kasturba Hospital, Manipal, India, with moderate and severe COVID-19 from 1 March to 1 August 2021. They were divided based on empirical therapy, and predictors of antibiotic usage were assessed by logistic regression. RESULTS: Four hundred and eighty (91.4%) COVID-19 patients received at least one course of antibiotics, with 440 (83.8%) initiating empirical therapy. Patients with severe COVID-19 manifestations were more likely to be prescribed empirical antibiotics. Multivariable analysis showed that patients initiated on empirical antibiotics had significantly elevated levels of procalcitonin [OR: 3.91 (95% CI: 1.66-9.16) (p = 0.001)], invasive ventilation [OR: 3.93 (95% CI: 1.70-9.09) (p = 0.001)], shortness of breath [OR: 2.25 (95% CI: 1.30-3.89) (p = 0.003)] and higher CRP levels [OR: 1.01 (95% CI: 1.00-1.01) (p = 0.005)]. Most antibiotics (65.9%) were prescribed from the 'Watch' group, the highest being ceftriaxone. Only 23.8% of the patients had microbiologically confirmed infections. CONCLUSION: The study identified predictors for initiating empirical antibacterial therapy in our setting.

Bioinformatics-guided disproportionality analysis of sevoflurane-induced nephrogenic diabetes insipidus using the FDA Adverse Event Reporting System database.

AIMS: Sevoflurane is an ether-based inhalational anaesthetic that induces and maintains general anaesthesia. Our study aimed to detect sevoflurane-induced nephrogenic diabetes insipidus using data mining algorithms (DMAs) and molecular docking. The FAERS database was analysed using OpenVigil 2.1 for disproportionality analysis. METHODS: We analysed FAERS data from 2004 to 2022 to determine the incidence of nephrogenic diabetes insipidus associated with sevoflurane. Reporting odds ratios (RORs) and proportional reporting ratios (PRRs) with 95% confidence intervals were calculated. We also used molecular docking with AutoDock Vina to examine sevoflurane's binding affinity to relevant receptors. RESULTS: A total of 554 nephrogenic diabetes insipidus cases were reported in FAERS, of which 2.5% (14 cases) were associated with sevoflurane. Positive signals were observed for sevoflurane with ROR of 76.012 (95% CI: 44.67-129.35) and PRR of 75.72 (χ2 : 934.688). Of the 14 cases, 50% required hospitalization, 14% resulted in death, and the remaining cases were categorized as other outcomes. Molecular docking analysis showed that sevoflurane exhibited high binding affinity towards AQP2 (4NEF) and AVPR2 (6U1N) with docking scores of -4.9 and -5.3, respectively. CONCLUSIONS: Sevoflurane use is significantly associated with the incidence of nephrogenic diabetes insipidus. Healthcare professionals should be cautious when using this medication and report any adverse events to regulatory agencies. Further research is needed to validate these findings and identify risk factors while performing statistical adjustments to prevent false-positives. Clinical monitoring is crucial to validate potential adverse effects of sevoflurane.

Purine antimetabolites associated Pneumocystis jirovecii pneumonia.

PURPOSE: To detect the possible safety signal of purine antimetabolites associated with Pneumocystis jirovecii pneumonia through disproportionality analysis in the FDA Adverse Event Reporting System (FAERS) Database. METHODS: A case/non-case retrospective disproportionality analysis was performed in the publicly available FAERS database using AERSmine (2004Q1-2021Q3). Four models were developed to explore the signal strength of PAs among different populations with possible confounding factors. Reporting odds ratio (ROR) and Proportional reporting ratio (PRR) was used as the data mining algorithm for the analysis. A value of ROR-1.96SE > 1 and PRR ≥ 2 with an associated X2 value of 4 or more was considered the threshold for a signal. RESULTS: A total of 7073 reports associated with Pneumocystis jirovecii pneumonia were present in the database, of which 899 reports were associated with purine antimetabolites. A crude signal strength of ROR 15.76(14.70-16.91) was obtained for purine antimetabolites associated PJP, with the highest signal strength reported with fludarabine and thioguanine [ROR 19.63(17.42-22.13); 19.45(13.21-28.63)]. Stratifying the cases based on autoimmune disorders and the cancer population revealed an ROR of 3.33(2.46-4.50) and 2.93(2.26-3.79) respectively. The highest risk of PJP with use of PAs was observed amongst children with a higher risk of nearly 2 times than the adult population [ROR 11.57(9.16-14.62)]. CONCLUSIONS: Our study provided evidence on the occurrence of PJP with the use of purine antimetabolites among the autoimmune and cancer population. We identified signals for PJP with azathioprine, mercaptopurine, thioguanine, cladribine, fludarabine, and clofarabine. More research with a superior epidemiological study design of a defined population is required to validate these findings.