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

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: , Akaike Information Criterion, and 10-fold cross-validation. To further explain the complex relationship between specific treatment factors and LOS, restricted cubic splines and piecewise regression were utilized, specifically to evaluate non-linear associations and identify clinical inflection points. Results: < 0.05). Piecewise regression identified an inflection point at 7.398 days, after which LOS increased more rapidly. 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.