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find Keyword "prediction effect" 1 results
  • Construction of nosocomial pulmonary infection prediction model for acute pesticide poisoning

    Objective To explore the risk factors of nosocomial pulmonary infection in acute pesticide poisoning. Methods The clinical data of patients with acute pesticide poisoning hospitalized in the Emergency Department of the First Affiliated Hospital of Wannan Medical College and the Second Affiliated Hospital of Wannan Medical College between January 1, 2021 and September 30, 2023 were retrospectively analyzed. Patients were divided into pulmonary infection group and non-pulmonary infection group according to whether they had pulmonary infection during hospital. Multiple logistic regression was used to analyze the independent risk factors of nosocomial pulmonary infection in patients with acute pesticide poisoning, and a risk prediction model (nomogram) was constructed. The predictive efficacy of nomogram and independent predictors in nosocomial pulmonary infection were analyzed by using the receiver operating characteristic curve. Calibration curve and decision curve were used to evaluate the differentiation and clinical application value of the model. Results A total of 189 patients with acute pesticide poisoning were included in the study, with an average age of (58.12±18.45) years old, 98 males (51.85%) and 91 females (48.15%). There were 36 cases (19.05%) of pulmonary infection. Multiple logistic regression analysis showed that age [odds ratio (OR)=1.030, 95% confidence interval (CI) (1.001, 1.060), P=0.040], type 2 diabetes mellitus [OR=2.770, 95%CI (1.038, 7.393), P=0.042], ischemic cerebrovascular disease [OR=3.213, 95%CI (1.101, 9.376), P=0.033], white blood cell count [OR=1.080, 95%CI (1.013, 1.152), P=0.019], activities of daily living score [OR=0.981, 95%CI (0.965, 0.998), P=0.024] were independent predicting factors for nosocomial pulmonary infection in acute pesticide poisoning. The area under the curve of nosocomial pulmonary infection in patients with acute pesticide poisoning predicted by nomogram based on the above factors was 0.813 (P<0.001). The calibration curve showed that the prediction probability was consistent with the actual occurrence probability (P=0.912), and the decision curve showed that the nomogram had good clinical application value. Conclusions Age, activities of daily living score, type 2 diabetes mellitus, ischemic cerebrovascular disease, and white blood cell count are independent predictors of nosocomial pulmonary infection in acute pesticide poisoning. The nomogram constructed based on them has good differentiation and consistency, which can provide basis for early identification and intervention of clinical staff.

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