ArticleAntibiotics (Basel, Switzerland)2022
Predicting In-Hospital Antibiotic Use in the Medical Department: Derivation and Validation Study.
Article in Antibiotics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 1 citations in OpenAlex.
- Identifying hospital-level predictors for antibiotic use: a Global Point Prevalence Survey study among Belgian, Philippine and South African hospitals.JAC-antimicrobial resistance · 2026Article
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8 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundThe rise of multi-drug-resistant pathogens and nosocomial infections among hospitalized patients is partially attributed to the increased use of antibiotic therapy. A prediction model for in-hospital antibiotic treatment could be valuable to target preventive strategies.
methodsThis was a retrospective cohort study, including patients admitted in 2018 to medical departments and not treated with antibiotics during the first 48 h. Data available at hospital admission were used to develop a logistic model to predict the probability of antibiotic treatment during hospitalization. The performance of the model was evaluated in two independent validation cohorts.
resultsIn the derivation cohort, antibiotic treatment was initiated in 454 (8.1%) out of 5592 included patients. Male gender, lower functional capacity, prophylactic antibiotic treatment, medical history of atrial fibrillation, peripheral vascular disease, solid organ transplantation, chronic use of a central venous catheter, urinary catheter and nasogastric tube, albumin level, mental status and vital signs at presentation were identified as predictors for antibiotic use during hospitalization and were included in the prediction model. The area under the ROC curve (AUROC) was 0.72 (95% CI 0.70-0.75). In the highest probability group, the percentage of antibiotic treatment was 18.2% (238/1,307). In the validation cohorts, the AUROC was 0.73 (95% CI 0.68-0.77) and 0.75 (95% CI 0.72-0.78). In the highest probability group, the percentage of antibiotic treatment was 12.5% (66/526) and 20.7% (244/1179) of patients.
conclusionsOur prediction model performed well in the validation cohorts and was able to identify a subgroup of patients at high risk for antibiotic treatment.
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