Empirical Antibiotic Prescribing in COVID-19 Patients in Central India, 2020-2021

90% of 951 hospitalized COVID-19 patients in rural Central India received empirical antibiotics, with 46% receiving two agents. This retrospective observational study from March 2020 to December 2021 analyzed prescribing patterns using WHO ATC/DDD methodology and identified predictors like elevated C-reactive protein. The dataset was authored by Manju Purohit and shared under a CC-BY-4.0 license.

Use Cases

• Model predictors of empirical antibiotic use based on patient characteristics like age, comorbidities, and C-reactive protein levels.
• Analyze the association between antibiotic use and clinical outcomes such as hospital length of stay and mortality.
• Study the prevalence of WHO 'Watch' and 'Reserve' group antibiotic prescriptions in a resource-constrained setting.

Strengths

• Includes 951 patient records with detailed clinical outcomes like mortality (26%) and oxygen requirement (74%).
• Provides specific metrics on antibiotic use, including Drug Utilization 90% (DU90%) segment analysis and defined daily doses (DDDs).
• Identifies a strong statistical predictor for antibiotic use with an adjusted odds ratio of 29.28 for elevated C-reactive protein.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the underlying data tables is unknown, which may limit suitability assessment.
• The 15.3 KB file size suggests the dataset has a limited scope, likely containing summary statistics rather than raw patient-level data.

Provenance

Source

figshare

Collection Method

Retrospective observational study of hospitalized patients.

Time Range

March 2020 to December 2021

Freshness

Last updated 2026-05-20 13:35:06; freshness should be verified.

Geography

Rural Central India