Clinical oral investigations · 2023
Impact of oral/dental disease burden on postoperative infective complications: a prospective cohort study.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
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Suenaga Hanako, Schifter Mark, Chen Nancy, Ali Farheen, Byth Karen, Peck Chris
Аннотация
OBJECTIVES: This prospective cohort study aimed to assess the association between dental disease burden and postoperative infective complications (POICs) in patients undergoing major surgical procedures under general anaesthesia.
METHODS: Pre-surgical dental assessment was undertaken on patients planned for major surgery. Demographic and surgical variables including putative risk factors for POICs and POIC status were documented. The univariable association between POIC status and each factor was examined. Those variables associated at P value ≤ 0.2 were candidates for inclusion in multiple logistic regression models. Backward stepwise variable selection was used to identify the independent predictors for POIC in the best fitting logistic regression model. The area under the receiver operating curve (AUC) was used to quantify the model's global classification performance.
RESULTS: Among the 285 patients, 49 patients (17.2%) had POICs. The independent predictors for POIC were expected length of hospital stay (4-6 days; odds ratio [OR] = 4.80, 95% confidence internal [CI]: 1.30-17.70, P = 0.018, 7-9 days; OR = 5.42, 95% CI: 1.51-19.41, P = 0.009, ≥ 10 days; OR = 28.80, 95% CI: 4.12-201.18, P < 0.001), four or more decayed teeth (OR = 6.03, 95% CI: 2.28-15.94, P < 0.001) and visible tongue plaque (OR = 3.21, 95% CI: 1.54-6.70, P = 0.002). The AUC was 0.78 (95% CI: 0.71-0.85) indicating good discrimination. A simple screening tool for POIC was developed.
CONCLUSIONS/CLINICAL RELEVANCE: In addition to systemic/surgical factors, this study identified clinically detected decayed teeth and visible tongue plaque as independent predictors for POICs. Preoperative dental assessment/care might be beneficial to assess risk for POICs and improve postoperative outcomes.
METHODS: Pre-surgical dental assessment was undertaken on patients planned for major surgery. Demographic and surgical variables including putative risk factors for POICs and POIC status were documented. The univariable association between POIC status and each factor was examined. Those variables associated at P value ≤ 0.2 were candidates for inclusion in multiple logistic regression models. Backward stepwise variable selection was used to identify the independent predictors for POIC in the best fitting logistic regression model. The area under the receiver operating curve (AUC) was used to quantify the model's global classification performance.
RESULTS: Among the 285 patients, 49 patients (17.2%) had POICs. The independent predictors for POIC were expected length of hospital stay (4-6 days; odds ratio [OR] = 4.80, 95% confidence internal [CI]: 1.30-17.70, P = 0.018, 7-9 days; OR = 5.42, 95% CI: 1.51-19.41, P = 0.009, ≥ 10 days; OR = 28.80, 95% CI: 4.12-201.18, P < 0.001), four or more decayed teeth (OR = 6.03, 95% CI: 2.28-15.94, P < 0.001) and visible tongue plaque (OR = 3.21, 95% CI: 1.54-6.70, P = 0.002). The AUC was 0.78 (95% CI: 0.71-0.85) indicating good discrimination. A simple screening tool for POIC was developed.
CONCLUSIONS/CLINICAL RELEVANCE: In addition to systemic/surgical factors, this study identified clinically detected decayed teeth and visible tongue plaque as independent predictors for POICs. Preoperative dental assessment/care might be beneficial to assess risk for POICs and improve postoperative outcomes.