Predictors of Prolonged Hospital Length of Stay in Patients With Odontogenic Infections in Ghana.

Authors

Kwame Adu Okyere Boadu, Lydia Sarponmaa Asante, Paul Frimpong, Elijah Kwegyir Johnson, Victor Wireko Adu, Richard Okyere Boadu

Published in

BioMed research international. Volume 2026. Issue 1. Pages e6612139.

Abstract

Poor outcomes of odontogenic infections usually increase the length of stay (LOS) in hospitals, and the cost of treatment increases substantially. The LOS of patients with odontogenic infections is not set in stone. In clinical practice, it is observed that cost, certain medications and treatments, age and a plethora of factors influence this. However, it is unclear which factors have direct effects on it. As such, evidence-based interventions become difficult.
The study utilised a retrospective observational approach and a total population sampling technique to investigate 286 out of the 811 patients admitted at the allied ward of STH from 2021 to 2025. Data was extracted from the Lightwave Health Information Management System and analysed with IBM SPSS 27, Claude (Anthropic, version Sonnet 4.6) and Python (Version 3.12).
A total of 286 patients were included, with a mean hospital length of stay (HLOS) of 9.28 ± 4.21 days. Necrotising fasciitis and Ludwig's angina were associated with the longest admissions. On proportional odds ordinal logistic regression, severe infection classification (OR 25.39, 95% CI: 4.21-153.32) and necrotising fasciitis (OR 9.36, 95% CI: 3.87-22.61) were the strongest independent predictors of prolonged HLOS (all p < 0.001). HIV/AIDS, diabetes mellitus, hypertension, Ludwig's angina and male sex were also significant independent predictors. The model demonstrated strong explanatory power (Nagelkerke R² = 0.686, p < 0.001). All predictor variance inflation factors were below 2.5, indicating no multicollinearity concerns.
Infection severity, primary diagnosis, immunocompromising comorbidities and surgical interventions were the principal independent determinants of prolonged HLOS. Multispace involvement showed a crude association with extended HLOS but did not emerge as an independent predictor in the adjusted ordinal regression model. Early diagnosis and prompt, multidisciplinary management are crucial to reducing hospitalisation and improving patient outcomes.

PMID:
42363752
Bibliographic data and abstract were imported from PubMed on 27 Jun 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.