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Phenotyping of Heart Failure in CKD Using Electrocardiography Features
Qandeel H Soomro1, Niveda Shekar1, Shahidul Islam2
1Nephrology Division, New York University Grossman School of Medicine, New York, New York.
Insights
Standard electrocardiogram (ECG) features, not heart rate variability (HRV), can predict heart failure (HF) hospitalization in chronic kidney disease (CKD) patients. This study identified key ECG markers for improved HF risk prediction in this population.
Area of Science:
- Cardiology
- Nephrology
- Medical Informatics
Background:
- Predictive tools for heart failure (HF) in patients with chronic kidney disease (CKD) are limited.
- This study investigated the utility of standard electrocardiogram (ECG) features and heart rate variability (HRV) parameters in predicting de novo HF hospitalization in individuals with CKD.
Purpose of the Study:
- To determine if standard ECG parameters or HRV can predict incident HF hospitalization in CKD patients.
- To identify specific ECG features associated with increased HF hospitalization risk.
Main Methods:
- A cohort of 11,409 CKD patients from the NYU ECG database (2012-2021) was analyzed.
- Standard ECG features and HRV parameters were extracted from baseline ECGs prior to dialysis, ESKD, or transplant.
- LASSO-penalized Cox regression and Fine-Gray competing risk models were used to identify predictors of HF hospitalization.
Main Results:
- 880 patients (8%) experienced HF hospitalization. Models integrating ECG and clinical data showed strong discrimination (C-statistic 0.73-0.76).
- PR interval, corrected QT, and T axis on ECG were independently associated with higher HF hospitalization risk (p<0.01).
- History of arrhythmia, valvular disease, and diabetes were significant clinical predictors; HRV parameters were not independently associated with HF.
Conclusions:
- Standard ECG features, specifically PR interval, corrected QT, and T axis, are associated with HF hospitalization risk in CKD patients.
- ECG-derived HRV indices did not independently predict HF hospitalization in this cohort.
Key Points:
Electrocardiography features have incremental value in prediction of heart failure in CKD beyond clinical features. Comparison and integration in existing risk scores is needed.
Background:
Tools for predicting heart failure in patients with CKD remain limited. We aimed to study whether standard electrocardiography (ECG) features or heart rate variability parameters predict de novo heart failure hospitalization in individuals with CKD.
Methods:
Using a large New York University ECG database linked with electronic health records (2012-2021), we analyzed a cohort of patients with preexisting CKD. Besides standard ECG features, we extracted heart rate variability (measures the time between consecutive heart beats in milliseconds) features from the ECGs as predictors. The index ECG was the first ECG performed after the index eGFR date (baseline) and was required to be performed before initiation of dialysis, ESKD, or transplant. The primary outcome was time to index heart failure hospitalization (≥30 days after the index ECG) on the basis of discharge International Classification of Diseases, Tenth Revision codes. Least absolute shrinkage and selection operator-penalized Cox regression was used to identify predictors. Sensitivity analyses used Fine-Gray competing risk models for death and ESKD.
Results:
Among 11,409 individuals (median age: 72 years; approximately 50% men) with a median of 976 days, 880 individuals (8%) experienced an index heart failure hospitalization. Models incorporating ECG and clinical parameters had excellent discrimination ( C -statistic 0.76 in the training set and 0.73 in the validation set). Among ECG features, the PR interval, corrected QT, and T axis were independently associated with higher risks of index heart failure hospitalization ≥30 days after the index ECG in both primary models ( P < 0.001 for all), and in models accounting for competing risks ( P < 0.01 for all). History of arrhythmia (hazard ratio [HR], 1.60; 95% confidence interval [CI], 1.36 to 1.88), valvular disease (HR, 1.51; 95% CI, 1.27 to 1.81), and diabetes (HR, 1.41; 95% CI, 1.22 to 1.65) were the strongest clinical predictors. Heart rate variability parameters were not independently associated with heart failure.
Conclusions:
Although ECG-derived heart rate variability indices were not independently associated with risk of heart failure, several standard ECG features are associated with heart failure hospitalization in patients with CKD.
Podcast:
This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/K360/2026_07_30_KID0000001175.mp3.
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