Assessment of Inflammatory Scores in Severity Prediction for Elderly Patients with Odontogenic Infections.

Dent J (Basel)

Discipline of Oral and Maxillo-Facial Surgery, Faculty of Dental Medicine, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square 2, 300041 Timisoara, Romania.

Published: November 2024

Odontogenic infections (OIs) can lead to severe complications, especially in elderly patients due to age-related physiological changes and comorbidities. This study aims to evaluate the predictive accuracy of inflammatory scores-APACHE II, CURB-65, SOFA, and NEWS2-in determining the severity of odontogenic infections among elderly patients (>70 years) compared to younger patients (<70 years). A retrospective cohort study was conducted on patients diagnosed with an OI at the Maxillofacial Surgery Department between January 2018 and January 2024. Patients were divided into two groups: elderly patients (>70 years, n = 49) and younger patients (<70 years, n = 64). The Symptom Severity score (SS) of odontogenic infections was calculated for all patients. Inflammatory scores-APACHE II, CURB-65, SOFA, and NEWS2-were assessed at admission and correlated with infection severity. Additional subgroup analyses were performed based on comorbidities and infection sites. Elderly patients exhibited significantly higher SS scores (mean 12.47 ± 2.93) compared to younger patients (mean 7.82 ± 2.17, < 0.001). APACHE II, CURB-65, SOFA and NEWS2 scores were significantly elevated in the elderly group (all < 0.001). The SOFA score demonstrated the highest predictive accuracy for severe OIs in elderly patients, with an area under the curve (AUC) of 0.89 (95% CI: 0.82-0.95). Subgroup analyses revealed that comorbidities such as diabetes mellitus and cardiovascular disease significantly influenced infection severity ( < 0.05). Inflammatory scores, particularly SOFA, are effective in predicting the severity of odontogenic infections in elderly patients. The integration of these scores into clinical practice may enhance early identification of high-risk patients and improve management strategies.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11592852PMC
http://dx.doi.org/10.3390/dj12110371DOI Listing

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