Objective To explore the nursing practice of children with diarrhea complicated with myocardial damage based on mind map combined with quantitative prediction model.

Methods A total of 168 children with diarrhea were selected as the study subjects. LASSO regression analysis was used to screen for predictive factors for diarrhea complicated with myocardial damage, logistic regression analysis was used to identify independent risk factors for diarrhea complicated with myocardial damage, and nomogram prediction model and mind map were established for diarrhea complicated with myocardial damage.

Results Among the 168 children with diarrhea, 62 cases experienced myocardial damage, with an incidence rate of 36.90% (62/168). The results of logistic regression analysis showed that age≤1 year old, hypokalemia, anemia, metabolic acidosis, moderate to severe dehydration, hypoalbuminemia, and infectious diarrhea were risk factors for diarrhea complicated with myocardial damage (P < 0.05 to P < 0.01). The results of the nomogram model indicated that the C-index of the model was 0.799 (95%CI: 0.763-0.836), and the calibration curve had a good fit with the ideal curve.The AUC was 0.782 (95%CI: 0.748-0.816), with a sensitivity of 81.30% and a specificity of 74.50%. The decision curve displayed that when the threshold probability was 6%-88%, there was a higher net benefit value using this nomogram to predict diarrhea complicated with myocardial damage. The established mind map could clearly display the risk indicators and risk stratification of diarrhea complicated with myocardial damage.

Conclusions The established nomogram of diarrhea complicated with myocardial damage has good predictive ability and clinical utility, which combined mind map can help medical staffs understand and remember the clinical significance of the model.