Enhancing Kidney Failure Analysis: Web Application Development for Longitudinal Trajectory Clustering

Kidney failure is a critical health condition with significant impact on patient well-being and healthcare systems worldwide. Analyzing the longitudinal trajectory of kidney function is crucial for understanding disease progression, predicting outcomes, and personalizing treatment strategies. This paper proposes a novel approach utilizing latent longitudinal trajectory clustering techniques by incorporating survival information to analyze kidney failure and explore patterns within patient populations. Besides, we also developed a web application to provide visualize and intuitive way to explore the relationship between estimated glomerular filtration rate (EGFR) progression and survival outcomes, helping researchers and clinicians gain valuable insights. By identifying distinct subgroups, this analysis can aid in early detection, risk stratification, and treatment optimization. The proposed methodology holds promise for improving patient care and outcomes in the field of nephrology. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study used only openly available human data that were originally located at: https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:124398/tab/2 I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced are available online at