Abstract

The present study was focused on evaluating the clinical predictors of hypoxemia and establishing a multivariable, predictive model for hypoxemia in painless bronchoscopy. A total of 244 patients were enrolled in the study, and data were collected using a self-designed data collection. The retrospective data collected in this study included the relevant data of patients undergoing the painless bronchoscopy, and we used univariate analysis to deal with these influencing factors. Multivariate logistic regression analysis was used to establish the prediction equation, and receiver operating characteristic curve analysis was carried out. Receiver operating characteristic curves and the Hosmer-Lemeshow test were used to evaluate the model performance. P < .05 was considered to indicate statistical significance. Multivariate logistic regression indicated that body mass index (BMI) (odds ratio [OR]: 1.169; 95% confidence interval [CI]: 1.070-1.277), arterial partial pressure of oxygen (PaO2) (OR: 4.279; 95% CI: 2.378-7.699), alcohol consumption (OR: 2.021; 95% CI: 1.063-3.840), and whether the bronchoscope operation time exceeds 30 minutes (OR: 2.486; 95% CI: 1.174-5.267) were closely related to the occurrence of hypoxemia. The prediction model developed by the logistic regression equation was -4.911 + 1.454 (PaO2) + 0.156 (BMI) + 0.703 (Alcohol consumption) + 0.911 (time > 30th minutes). The prediction model showed that the area under the receiver operating characteristic curve was 0.687. The predictive model was well calibrated with a Hosmer-Lemeshow x2 statistic of 4.869 (P = .772), indicating that our prediction model fit well. The accuracy (number of correct predictions divided by the number of total predictions) was 75%. The prediction model, consisting of BMI, PaO2, alcohol consumption, and whether the bronchoscope operation time exceeds 30 minutes. It is an effective predictor of hypoxemia during sedation for painless bronchoscopy.

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