ArticleFrontiers in public health2026
Predicting length of hospital stay in community-acquired pneumonia using clinical and treatment factors: a retrospective study with restricted cubic spline and piecewise regression analysis.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Community-acquired pneumonia (CAP) remains a leading cause of hospitalization worldwide. Accurate prediction of length of stay (LOS) is crucial for optimizing hospital bed turnover, improving clinical resource allocation, and facilitating the development of individualized discharge plans, thereby reducing the strain on healthcare systems. Methods: We retrospectively analyzed 423 adults hospitalized with CAP from January 2022 to December 2023. Clinical characteristics, laboratory data, comorbidities, and treatment variables were extracted from electronic health records. Univariate and multivariable linear regression models were initially employed to identify independent predictors of LOS. The predictive performance of the final multivariable model was assessed using R Results: The final model showed strong performance (R Conclusions: Multiple clinical and treatment-related factors were associated with LOS in CAP. Antibiotic duration showed a pronounced non-linear pattern, with treatment beyond 1 week linked to markedly longer hospitalization. These findings may help identify patients at risk of prolonged LOS and support more efficient clinical decision-making.
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