Predicting high excess risk of hyponatraemia among thiazide users

European Journal of Preventive Cardiology

30 July 2025
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ESC Journals CARDIOVASCULAR PHARMACOLOGY HYPERTENSION PREVENTIVE CARDIOLOGY Risk Factors and Prevention

Abstract

AbstractAims

Hyponatraemia is a potential serious adverse drug reaction to treatment with thiazide diuretics. This study aimed to determine whether individuals at high risk of developing thiazide-induced hyponatraemia can be identified before treatment initiation.

Methods and results

A population-based cohort study was conducted in Denmark among individuals aged ≥40 years from 2014 to 2020. Moderate-to-severe hyponatraemia (plasma sodium <130 mmol/L) within 120 days of treatment was compared in new users of thiazide or non-thiazide antihypertensive drugs. Using the causal forest method, models to predict individual-level risk of thiazide-induced hyponatraemia were trained in a development cohort (n = 185 699; 2014–18) and validated in a separate cohort (n = 75 030; 2019–20). Individual-level excess risk could be parsimoniously described by a four-covariate model that included information on age and baseline plasma sodium, haemoglobin, and C-reactive protein levels with good calibration and concordance-for-benefit [0.66; 95% confidence interval (CI), 0.66–0.67] in the validation cohort. The average 120 day excess risk of hyponatraemia among thiazide-treated patients was 1.8% (95% CI, 1.3–2.2%), with individual-level heterogeneity ranging from −1.6% to 15.9%. For the 10% of thiazide-treated with the highest excess risk of hyponatraemia, the average excess risk was 7.4% (95% CI, 4.4–10.5%). Reassigning this high-risk group to non-thiazide drugs would reduce the excess risk within the thiazide-treated population by 0.7% (95% CI, 0.4–1.0%), corresponding to a 42% relative reduction.

Conclusion

The population-level burden of thiazide-induced hyponatraemia can potentially be markedly reduced by identifying and prescribing alternative antihypertensive drugs to high-risk patient groups using a simple set of baseline information.