Novel predictors of infection‐related rehospitalization in older patients with heart failure in Japan

Figures

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  Figure 1. Shapley additive explanation (SHAP) values for each variable were calculated from the individual values of each patient within the prediction model. Each data point is represented by a dot with a color based on the variable value. The red dots indicate high values for a particular patient's variable, whereas the blue dots indicate low values. For binary categorical variables, a blue dot indicates the absence of the category, and a red dot indicates its presence. By visualizing these patient‐specific SHAP values, the relationship between the value of each variable (indicated by the dot color) and its impact on the model output becomes clear. BMI, body mass index; BNP, brain natriuretic peptide; COPD, chronic obstructive pulmonary disease; eGFR, estimated glomerular filtration rate; GNRI, Geriatric Nutritional Risk Index; J‐CHS, Japanese Cardiovascular Health Study; MRA, mineralocorticoid receptor antagonist; NYHA, New York Heart Association; SBP, systolic blood pressure.

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  Figure 2. Shapley additive explanation (SHAP) main effect value for the (a) Japanese Cardiovascular Health Study (J‐CHS) score and (b) estimated glomerular filtration rate (eGFR). SHAP values for each variable were calculated from the individual values of each patient within the prediction model. Each data point is represented by a dot with a color based on the variable value. By visualizing these patient‐specific SHAP values, the relationship between each variable value (indicated by the dot color) and its impact on the model output becomes clear. (c) The interaction effects of J‐CHS score influence the predicted probability of infection‐related hospitalization based on age. The SHAP interaction values quantify these effects and show the interaction between age and the J‐CHS score. When the SHAP interaction values (y axis) are plotted as a function of patient age (x axis) and the value of the interacting variable (indicated by the color of the dot—red for a J‐CHS score of ≥3 and blue for a J‐CHS score of <2), trends in variables and their values that have a greater interaction effect emerge. In the case of age, an interaction effect with a J‐CHS score of ≥3 becomes apparent at…

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  Figure 3. Decision tree analysis used to stratify the probability of infection‐related hospitalization. Patients were classified into the high‐risk (Japanese Cardiovascular Health Study [J‐CHS] score ≥3; n = 394), medium‐risk (J‐CHS score <3; eGFR ≤35.0; n = 83) and low‐risk groups (J‐CHS score <3; eGFR >35.0; n = 252). CDs, cardiovascular deaths; eGFR, estimated glomerular filtration rate; NCDs, non‐cardiovascular deaths.