Clinical prediction nomogram model for the efficacy of azithromycin treatment in pediatric mycoplasma pneumonia
Objective To evaluate the efficacy of azithromycin in the treatment of mycoplasma pneumoniae pneumonia(MPP),identify the independent risk factors affecting the efficacy of azithromycin,and establish a clinical prediction model for the efficacy of az-ithromycin in order to provide precise reference for clinical decision-making.Methods 157 pediatric patients with MPP were selected.The data of clinical,laboratory and imaging were collected for comparison.Logistic regression analysis was used to identify the risk fac-tors affecting the efficacy of azithromycin in treating MPP,and a clinical prediction nomogram was constructed to assess azithromycin effi-cacy.Results The average age of the children was(7.8±2.5)years,and their average weight was(27.1±9.6)kg.Azithromycin was effective in 95 cases(60.5％)and ineffective in 62 cases(39.5％).The results of univariate analysis and multivariate logistic regres-sion model indicated that the number of MP-resistant gene sequences,duration of fever,age,length of hospital stay,and alveolar lavage fluid were significantly associated with azithromycin efficacy.The final established nomogram model included these five variables and had a concordance index of 0.852 and an AUC of 0.867(95％CI:0.795～0.923).The sensitivity of the model was 0.895,specificity was 0.800,and decision curve analysis suggested that when the threshold probability was between 0.00 and 1.00,the net benefit rate predic-ted by the model exceeded 5.6％.Conclusion The nomogram model based on the number of MP-resistant gene sequences,duration of fever,age,length of hospital stay,and alveolar lavage fluid has good clinical application value for predicting the efficacy of azithromycin treatment in pediatric patients of MPP.
万方数据
维普
