{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T20:32:02Z","timestamp":1786480322636,"version":"build-2736575974"},"reference-count":31,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"7","license":[{"start":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T00:00:00Z","timestamp":1774310400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":["Kidney360"],"published-print":{"date-parts":[[2026,7]]},"abstract":"\n Key Points<\/jats:title>\n \n \n \n Electrocardiography features have incremental value in prediction of heart failure in CKD beyond clinical features.<\/jats:p>\n <\/jats:list-item>\n \n Comparison and integration in existing risk scores is needed.<\/jats:p>\n <\/jats:list-item>\n <\/jats:list>\n <\/jats:p>\n <\/jats:sec>\n \n Background<\/jats:title>\n \n 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\n de novo<\/jats:italic>\n heart failure hospitalization in individuals with CKD.\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Using a large New York University ECG database linked with electronic health records (2012\u20132021), 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 (\u226530 days after the index ECG) on the basis of discharge International Classification of Diseases, Tenth Revision codes. Least absolute shrinkage and selection operator\u2013penalized Cox regression was used to identify predictors. Sensitivity analyses used Fine\u2013Gray competing risk models for death and ESKD.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n 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 (\n C<\/jats:italic>\n -statistic 0.76 in the training set and 0.73 in the validation set). Among ECG features, the PR interval, corrected QT, and\n T<\/jats:italic>\n axis were independently associated with higher risks of index heart failure hospitalization \u226530 days after the index ECG in both primary models (\n P<\/jats:italic>\n < 0.001 for all), and in models accounting for competing risks (\n P<\/jats:italic>\n < 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.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Podcast<\/jats:title>\n This article contains a podcast at https:\/\/dts.podtrac.com\/redirect.mp3\/www.asn-online.org\/media\/podcast\/K360\/2026_07_30_KID0000001175.mp3<\/jats:p>\n <\/jats:sec>","DOI":"10.34067\/kid.0000001175","type":"journal-article","created":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T16:03:19Z","timestamp":1774368199000},"page":"1588-1600","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":1,"title":["Phenotyping of Heart Failure in CKD Using Electrocardiography Features"],"prefix":"10.34067","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3182-7225","authenticated-orcid":false,"given":"Qandeel H.","family":"Soomro","sequence":"first","affiliation":[{"name":"Nephrology Division, New York University Grossman School of Medicine, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7700-3481","authenticated-orcid":false,"given":"Niveda","family":"Shekar","sequence":"additional","affiliation":[{"name":"Nephrology Division, New York University Grossman School of Medicine, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9385-101X","authenticated-orcid":false,"given":"Shahidul","family":"Islam","sequence":"additional","affiliation":[{"name":"Biostatistics Unit, Office of Academic Affairs, Northwell Health, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6054-2678","authenticated-orcid":false,"given":"Chinyere","family":"Okpara","sequence":"additional","affiliation":[{"name":"Department of Surgery, NYU Grossman Long Island School of Medicine, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3465-3539","authenticated-orcid":false,"given":"Soo Young","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Foundations of Medicine, Center for Population and Health Services Research, NYU Grossman Long Island School of Medicine, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0120-7620","authenticated-orcid":false,"given":"Jasmin","family":"Divers","sequence":"additional","affiliation":[{"name":"Department of Foundations of Medicine, Center for Population and Health Services Research, NYU Grossman Long Island School of Medicine, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7695-3583","authenticated-orcid":false,"given":"David M.","family":"Charytan","sequence":"additional","affiliation":[{"name":"Nephrology Division, New York University Grossman School of Medicine, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,3,24]]},"reference":[{"issue":"4","key":"B1-20260731","first-page":"e005336","article-title":"CKD progression risk and subsequent cause of death: a population-based cohort study","volume":"5","author":"Rai","year":"2017","journal-title":"Kidney Med."},{"issue":"5","key":"B2-20260731","doi-asserted-by":"crossref","first-page":"e005336","DOI":"10.1161\/JAHA.116.005336","article-title":"Risk factors for heart failure in patients with chronic kidney disease: the CRIC (chronic renal insufficiency cohort) 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