Predictors of Prolonged Hospital Length of Stay in Patients With Odontogenic Infections in Ghana.
Background: 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...
| Publicado en: | BioMed Research International Vol. 2026; pp. 1 - 15 |
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| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
6/27/2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194947188&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 194947188 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 6/27/2026 vid: 2026 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 194947188 194947188 194947188 10.1155/bmri/6612139 194947188 ppf: 1 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Predictors of Prolonged Hospital Length of Stay in Patients With Odontogenic Infections in Ghana. aug: au: Okyere Boadu, Kwame Adu Asante, Lydia Sarponmaa Frimpong, Paul Johnson, Elijah Kwegyir Adu, Victor Wireko Boadu, Richard Okyere Banerjee, Baisakhi affil: Department of Public Health,, School of Public Health and Allied Sciences,, Catholic University of Ghana,, Fiapre, Ghana sug: subj: Length of Stay Tooth Diseases Prognosis Infection Prognosis Treatment Duration Human Male Female Ghana Retrospective Design Nonexperimental Studies Tertiary Health Care Inpatients Risk Assessment Health Care Costs Data Analysis Software Logistic Regression Tooth Diseases Therapy Odds Ratio Confidence Intervals Fasciitis, Necrotizing Human Immunodeficiency Virus Acquired Immunodeficiency Syndrome Diabetes Mellitus Hypertension Ludwig's Angina Sex Factors Severity of Illness Immunocompromised Host Male Female ab: Background: 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. Methodology: 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). Results: 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. Conclusion: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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