# Analyzing the nonlinear association between length of hospital stay and post-stroke pneumonia risk a secondary analysis of the Henan Province stroke registry

## TL;DR

This study finds that longer hospital stays increase the risk of post-stroke pneumonia, with the highest risk in the first 17 days.

## Contribution

The study identifies a nonlinear relationship and a critical inflection point at 17 days for post-stroke pneumonia risk.

## Key findings

- Each additional hospital day increases SAP risk by 8.3%.
- Risk increases sharply until 17 days, then slows down.
- A significant two-phase relationship was confirmed with an inflection point at 17 days.

## Abstract

Post-stroke pneumonia (SAP) is a common and serious complication in patients with acute ischemic stroke, associated with poor outcomes. Length of hospital stay (LOS) may influence SAP risk, but the dose–response relationship remains unclear. This study aimed to investigate the nonlinear association between LOS and SAP and identify potential inflection points.

This secondary analysis of the Henan Province Stroke Registry included 926 acute ischemic stroke patients admitted to the First Affiliated Hospital of Zhengzhou University from January 2009 to December 2012. Multivariable logistic regression models were used to assess the association between LOS and SAP. A two-piecewise linear model was applied to detect threshold effects, with multiple imputation for missing data.

The overall SAP incidence was 20.4%. After adjusting for age, sex, comorbidities, and NIHSS score, each additional day of LOS increased SAP risk by 8.3% (adjusted OR = 1.083; 95% CI: 1.057–1.110). Nonlinear analysis revealed a significant two-phase relationship with an inflection point at 17 days: OR = 1.182 (95% CI: 1.098–1.273) for LOS < 17 days, and OR = 1.049 (95% CI: 1.015–1.084) for ≥17 days (P for log-likelihood ratio test = 0.010).

LOS is positively associated with SAP in a nonlinear manner, with a steeper risk increase during the first 17 days of hospitalization. These findings suggest intensified respiratory monitoring early in admission and optimized hospitalization strategies to reduce infection risk.