{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T16:26:11Z","timestamp":1788279971910,"version":"build-2803163510"},"reference-count":25,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2024,12,28]],"date-time":"2024-12-28T00:00:00Z","timestamp":1735344000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Intern Med"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Fluid overload remains critical in managing patients with end\u2010stage kidney disease. However, there is limited empirical understanding of fluid overload's impact on mortality. This study analyzes fluid overload trajectories and their association with mortality in hemodialysis patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods and patients<\/jats:title><jats:p>This longitudinal study included 9332 incident hemodialysis patients from the EuCliD database, treated in Fresenius Medical Care NephroCare dialysis centers across seven countries between January 2016 and December 2019, with follow\u2010up until May 2023. Fluid overload was assessed using bioimpedance spectroscopy, and patients were grouped based on fluid overload trajectories using group\u2010based trajectory modeling. Cox regression models, adjusted for potential confounders, were used to investigate the relationship between trajectory groups and mortality.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Four distinct fluid overload trajectories were identified. Patients in the highest trajectory group (8.5% of the cohort) had more frequent background cardiovascular complications, lower BMI and serum albumin, and their adjusted mortality risk was 2.20 times higher than the lowest trajectory. There was a dose\u2013response relationship between trajectories and mortality. The incidence rate of death increased with the degree of fluid overload, from 8.6 deaths per 100 person\u2010years in the lowest trajectory to 18.6 in the highest.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>This longitudinal study highlights the significant risk of chronic fluid overload in hemodialysis patients. Latent trajectory analysis provides novel information into the dynamic nature of fluid overload and its impact on mortality in the hemodialysis population.<\/jats:p><\/jats:sec>","DOI":"10.1111\/joim.20049","type":"journal-article","created":{"date-parts":[[2024,12,28]],"date-time":"2024-12-28T20:54:23Z","timestamp":1735419263000},"page":"201-212","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Fluid overload trajectories and mortality in hemodialysis patients"],"prefix":"10.1111","volume":"297","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6616-1996","authenticated-orcid":false,"given":"Carmine","family":"Zoccali","sequence":"first","affiliation":[{"name":"Renal Research Institute  New York New York USA"},{"name":"Institute of Molecular Biology and Genetics (Biogem)  Ariano Irpino Italy"},{"name":"Associazione Ipertensione Nefrologia Trapianto Renale (IPNET) c\/o Nefrologia Grande Ospedale Metropolitano  Reggio Calabria Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanni","family":"Tripepi","sequence":"additional","affiliation":[{"name":"CNR\u2010IFC Institute of Clinical Physiology Research Unit of Clinical Epidemiology  Reggio Calabria Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paola","family":"Carioni","sequence":"additional","affiliation":[{"name":"Fresenius Medical Care Global Medical Office  Crema Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca","family":"Mallamaci","sequence":"additional","affiliation":[{"name":"CNR\u2010IFC Institute of Clinical Physiology Research Unit of Clinical Epidemiology  Reggio Calabria Italy"},{"name":"Nephrology Dialysis and Transplantation Unit, Azienda Ospedaliera \u201cBianchi\u2010Melacrino\u2010Morelli\u201d Grande Ospedale Metropolitano of Reggio Calabria  Reggio Calabria 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