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Prognostic model of hospital acquired pneumonia in the elderly based on geriatric nutritional risk index |
Maihefureti·Wufuer ZHANG Jiali Muyesai·Nijiati▲ |
Emergency Center, People’s Hospial of Xinjiang Uygur Autonomous Region, Xinjiang Uygur Autonomous Region, Urumgi 830001, China |
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Abstract Objective To explore the value of the geriatric nutritional risk index (GNRI) in evaluating the prognosis of patients with hospital-acquired pneumonia (HAP) in geriatric patients, and a histogram model was established to predict the prognosis of elderly HAP patients. Methods A total of 411 patients in the Emergency Center of the People’s Hospital of Xinjiang Uygur Autonomous Region from January 2013 to January 2020 were included in this study. All patients were divided into modeling group (308 cases) and validation group (103 cases) in a 3∶1 ratio by simple randomization method. Multivariate logistic regression analysis was used to analyze the independent risk factors for poor prognosis in elderly HAP patients. R software was used to construct a histogram model to predict the risk of poor prognosis in elderly HAP patients, and the model was verified. Results Univariate regression analysis showed that age, gender, systolic blood pressure, diastolic blood pressure, heart rhythm, congestive heart failure, chronic kidney disease, fasting blood glucose, low density lipoprotein cholesterol, GNRI scores were associated with poor prognosis in elderly HAP patients (P < 0.05), multivariate regression analysis showed that age, gender, congestive heart failure, and GNRI score were independent risk factors for poor prognosis in elderly HAP patients (P < 0.05). The model was validated internally and externally, and the AUC value in the modeling group was 0.854 (95%CI: 0.827-0.881), AUC value in the validation group was 0.841 (95%CI: 0.803-0.879), Hosmer-Lemeshow test results indicate that the prediction model has good stability: modeling queue (P = 0.739) and validation queue (P = 0.469). Conclusion The prediction model established in this study can accurately predict the individual risk of poor prognosis in elderly HAP patients, and has a high potential clinical application value.
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