Construction and comparison of short-term prognosis prediction model based on machine learning in acute ischemic stroke

Objective: To construct and compared the short-term prognosis prediction models of acute ischemic stroke (AIS) by machine learning (ML). Methods: Retrospectively study. The group W (mRS≤3) was clustered, and combined with group P (mRS>3) to form the post-clustering dataset for modeling. The “glmnet”, “rpart”, “xgboost”, “randomForest”, “neuralnet” packages were used to construct ML models. The accuracy, sensitivity, specificity, positive predict value (PPV), negative predict value (NPV) among the models were compared. Four external clinical datasets were used for external clinical validation. The optimal prediction model was determined by variable screening ability, model visualization, and external clinical validation performance. Results: The post-clustering dataset contains 139 patients (group W) and 122 patients (group P). The neutrophil multiplied by D-dimer (NDM) has predictive value in all ML prediction models in this study. In the decision tree model, NDMQ occupies the first tree node, When NDM≤5.62 and the age5.62 and accompanied by pneumonia, the incidence of poor prognosis of AIS is about 90 %. In the Random Forest (RF) model, NDMQ had the highest Gini index. The variable combination screened by the RF model had the best performance in the neural network, and the accuracy, sensitivity, specificity, PPV, and NPV of the external validation were 0.800, 0.774, 0.833, 0.857, and 0.741, respectively. The RF model had the best performance in the external clinical validation datasets, with accuracies of 0.646, 0.697, 0.695, and 0.713, respectively. Conclusions: NDM shows predictive value for AIS short-term prognosis in all ML models in this study. The optimal model in screening characteristic variables and the performance of in external clinical datasets was RF model. In the analysis of medical data with small sample size and outcome as categorical variables, RF could be used as the main algorithm to build a model

The screening process of AIS patient enrollment.

The screening process of AIS patient enrollment.</p

The detection materials and methods for laboratory subitems.

(DOCX)</p

The ROC curves.

A: ROC of TIA, Cardiac disease, Pneumonia, Babinski sign +, NEU# (quintile), LYMPH# (quintile), D-DIMER (quintile) to poor prognosis of AIS patients. NEU# (quintile): Neutrophil count in 5 quintiles, LYMPH# (quintile): Lymphocyte count in 5 quintiles, D-DIMER (quintile): D-dimer in 5 quintiles. B: ROC of NLR: The ratio of neutrophil count to lymphocyte count, DLR: The ratio of D-dimer to lymphocyte count, NDM: Neutrophil count multiplied by D-dimer, TIA: Transient Ischemic Attacks, Cardiac disease, Pneumonia, Babinski sign +, Predicted probability-NLR, Predicted probability-DLR, Predicted probability-NDM.</p

Regression analysis of significant relative subitems to poor prognosis in AIS.

Regression analysis of significant relative subitems to poor prognosis in AIS.</p

Compared result of significant subitems between Group W and Group P (<i>P</i><0.05*, median with 95 CI).

Items marked in dark blue are items higher in Group P than in Group W, and items marked in light blue are items lower in Group P than in Group W. This figure only shows the items with statistical significance.</p

The basic information of the AIS patients in the study.

The basic information of the AIS patients in the study.</p

Regression analysis of significant relative subitems to poor prognosis in AIS in step A, B, C.

A: Enter method to check single item. B: Only significant laboratory items were included for forward likelihood ratio detection. C: Only clinically significant items were included for forward likelihood ratio test. “/” indicates that the factor is not included in the operation. NEU#: Absolute neutrophil count, LYMPH#: Absolute lymphocyte count, MONO#: Absolute monocyte count, ESO#: Absolute eosinophil count, RDW: Red blood cell distribution width, PLT: Platelet, PDW: Platelet distribution width, PT: Prothrombin time, PTA: Prothrombin activity, PTINR: International Normalized Ratio, FIB: Fibrinogen, D-DIMER: D-dimer, HCY: Homocysteine, ALB: Albumin, PAB: Proalbumin, TG: Triglyceride, APOA/APOB ratio: The ratio of APOA to APOB, Lpa: Lipoprotein a. “OR”: Odds ratio. “C.I.”: Confidence interval. (DOCX)</p

Compared result of significant subitems between Group W and Group P.

Compared result of significant subitems between Group W and Group P.</p