Modelling clinicians' decisions to adjust loop diuretic dose based on patient-reported symptoms to inform decision-aids in daily care of chronic heart failure

Abstract

Abstract Background To relieve congestion and prevent decompensation in chronic heart failure patients with reduced ejection fraction, the guidelines by the European Society of Cardiology recommend the use of loop diuretics.[1] The patient is encouraged to take an active role by tracking their symptoms and adjusting their dose accordingly.[1] Purpose To develop an exploratory prediction model of clinicians’ decisions to titrate loop diuretics based on patient-reported symptoms to create decision-aids. Methods We conducted a post hoc analysis of TIME-CHF.[2] Of the randomised participants at baseline, we selected those who did not withdraw consent during follow-up, had a furosemide-equivalent diuretic dose ≤600 mg at baseline and the first follow-up moment approximately 1 month after baseline, and had a recommendation registered on diuretic titration at the first follow-up. We developed logistic regression models for two outcomes at the first follow-up: up-titration versus no change, and down-titration versus no change. Predictors considered were: age, gender, furosemide-equivalent loop diuretic dose, NYHA class, angina, orthopnoea, paroxysmal nocturnal dyspnoea, nocturia, dry cough, dizziness, orthostasis, syncope, oedema, body mass index, systolic, diastolic, and systolic minus diastolic blood pressure, heart rate, jugular veins assessment, rales, hepatomegaly, third heart sound, serum-creatinine. These predictors separately and the intervention allocation (NT-proBNP versus symptom-guided therapy) were used to predict the outcomes. We explored symptoms occurring simultaneously with the outcome and change in symptoms between baseline and first follow-up. Ordinal predictors were modelled at the nominal and scale measurement level. We then selected a group of predictors deemed suitable in a daily care context per outcome. Analyses were performed based on complete cases and after multiple imputation. Performance metrics were R²Nagelkerke and C-statistics (apparent values and 95% confidence intervals via bootstrap). Results Of the 622 patients randomised at baseline, 500 fulfilled the selection criteria. There were 101 recommendations to up-titrate, 338 to keep the dose unchanged, and 61 to down-titrate. The complete case analysis did not differ substantively from analysis after multiple imputation due to the low number of missing values, therefore only the complete case analysis is reported here. Table 1 presents the results of the patient-reported symptoms modelled separately, collected simultaneously with the outcomes. For ordinal predictors, the scale measurement level is reported. Table 2 presents the results of the analysis using the groups of predictors. Conclusions This analysis may shape decision-aids by suggesting symptom importance in clinicians’ decisions. Oedema, NYHA class, and orthopnoea are tentatively the most important patient-reported symptoms in recommending up-titration, and orthostasis in recommending down-titration.