{"doi":"10.1016/j.ekir.2025.07.034","title":"Kidney Function Trajectories With Mechanical Circulatory Support","abstract":"Introduction Adverse long-term kidney outcomes with left ventricular assist devices (LVADs) are common but little understood. Estimated glomerular filtration rate from creatinine (eGFR) is used clinically in this setting but is of uncertain validity, and tends to change non-linearly after LVAD implantation with an early peak followed by decline. We investigated non-linear eGFR trajectories over 90 days following LVAD implantation and the relationships with patient factors and outcomes. Methods We used two complementary cohorts of LVAD recipients, a single-center cohort (n=190) and a US national cohort (n=10794). Segmented linear regression with two segments was compared to other trajectory models. Relationships of trajectory parameters with patient factors and clinical outcomes were assessed. Results Segmented linear regression resulted in the best fit, yielding these parameters: early and late trajectory slopes, breakpoint time, and breakpoint eGFR. Patient factors were associated with trajectory parameters. For late trajectory slope, female sex was associated with change of -1.11 (-1.54 to -0.66) ml/min/1.73m 2 per 30 days and older age (per 10 years) of -0.80 (-0.94 to -0.66) ml/min/1.73m 2 per 30 days in the national cohort. All four trajectory parameters were associated with survival in unadjusted models, and breakpoint eGFR and late trajectory slope associations remained significant following adjustment. Conclusion Kidney function trajectory following LVAD implantation can be modeled with linear early and late phases separated by a variable breakpoint, yielding metrics associated with survival and pre-implantation patient and hemodynamic factors. These trajectory metrics may help investigations of causes of adverse kidney outcomes and interventions in LVAD recipients.","journal":"Kidney International Reports","year":2025,"id":553694,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.963,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":934169,"name":"Harveen K. Lamba","orcid":"0000-0002-0611-1030","position":1,"is_corresponding":false},{"id":552526,"name":"Ajith Nair","orcid":"0000-0002-3755-4985","position":2,"is_corresponding":false},{"id":934170,"name":"Andrew B. Civitello","orcid":"0000-0003-0731-1891","position":3,"is_corresponding":false},{"id":934172,"name":"Nandan K. Mondal","orcid":"0000-0003-2999-8567","position":4,"is_corresponding":false},{"id":934173,"name":"Kenneth K. Liao","orcid":"0000-0002-2101-4925","position":5,"is_corresponding":false},{"id":236350,"name":"Sankar D. Navaneethan","orcid":"0000-0002-4953-7795","position":6,"is_corresponding":false},{"id":241198,"name":"Carl P. Walther","orcid":"0000-0003-0219-2870","position":0,"is_corresponding":true}],"reference_count":37,"raw_metadata":null,"created_at":"2026-07-19T02:54:45.872391Z","pmid":"41141536","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}