Development and validation of a prediction model for the risk of hospital-acquired multidrug-resistant bacteri-al infections in patients with malignant tumors
Development and validation of a prediction model for the risk of hospital-acquired multidrug-resistant bacteri-al infections in patients with malignant tumors
Objective To develop and validate a nomogram model to predict the risk of hospital-acquired infection by multidrug-resistant organisms(MDRO)in patients with malignant tumors.Methods This study retrospectively analyzed the data of patients who received malignant tumor treatment in Wenzhou People's Hospital from October,2017 to April,2023.The least absolute shrinkage and selection operator(LASSO)regression model was used to select variables and de-termine the best predictive factors included in the nomogram.Based on these factors,a nomogram prediction model was constructed using multivariate logistic regression analysis.The C-index and calibration curve were used to evaluate the discrimination and calibration of the prediction model.Results The LASSO regression selected four predictive factors to construct the nomogram prediction model including age,percutaneous pleural drainage tube placement,NRS-2002 score,and days of antimicrobial drug use.The C-index of the development cohort and 0.77 in the validation cohort was 0.74 and 0.77,respctively,indicating high discriminative ability.Calibration plots demonstrated good consistency between pre-dicted probabilities and actual probabilities.Conclusion The nomogram model established in this study is a clinically valuable individualized prediction model,which can help to identify high-risk patients of hospital-acquired infection by MDRO in patients with malignant tumors.
维普
万方数据