Data · dataset · 2026
Longitudinal eGFR Trajectory and Survival Benchmark Dataset for Chronic Kidney Disease (SMART-C Cohort)
Listed in Teesside University Research Data Repository
1.
Description
Scientific Overview & Objective This benchmark dataset, developed under the Reproducible Longitudinal Dynamical Patterns (RLDP) framework, provides high-density, multi-year clinical time-series for evaluating continuous-time trajectory forecasting, state-space estimation, and out-of-sample prognostic risk models in Chronic Kidney Disease (CKD). Longitudinal modeling of renal function requires overcoming significant observational challenges, including sparse and irregularly spaced visits, analytical measurement noise, and non-linear trajectory decay.
This dataset establishes a standardized, fully reproducible benchmark for machine learning and dynamical systems in nephrology. 2. Cohort Specification & Clinical Design The dataset comprises N = 5,000 adult CKD patients prospectively tracked across a 3-year timeline (Days 1 to 1,096), generating 41,800 longitudinal laboratory evaluations (mean: 8.36 visits per patient; range: 2 to 14 visits). The primary continuous biomarker is Estimated Glomerular Filtration Rate (eGFR, mL/min/1.73m2).
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Baseline eGFR across the cohort is 55.70 +/- 17.97 mL/min/1.73m2 (range: 6.0 to 115.0 mL/min/1.73m2). Randomization is structured 1:1 into active intervention (n = 2,501) and control placebo (n = 2,499), stratified at screening by baseline disease severity into three clinical strata: - Screening eGFR 30 to <45 mL/min/1.73m2 (n = 1,497, 29.9%) - Screening eGFR 45 to <60 mL/min/1.73m2 (n = 1,466, 29.3%) - Screening eGFR 60 to <90 mL/min/1.73m2 (n = 2,037, 40.7%) Baseline concurrent GLP-1 receptor agonist therapy is documented in 24.9% of participants. 3.
File Structure & Data Dictionary The archive contains two harmonized CSV files: - baseline.csv (5,000 records): usubjid (patient ID), trt01pn (arm: 1=active, 0=placebo), randfl (randomized), ittfl (intent-to-treat), trtfl (treated), blgfr (baseline eGFR), blglp1 (baseline GLP-1 status), strata (screening renal category). - followup.csv (41,800 records): usubjid, randfl, ittfl, trtfl, anl01fl, aval (observed visit eGFR), base (baseline eGFR), paramcd (GFRBSCRT), param, ady (analysis day: 1 to 1096), avisitn, avisit (protocol visit name: BASELINE, WEEK 3, WEEK 13, etc.). 4.
Data Quality & Harmonization Audit Automated audit confirms: (a) 0.0% single-visit static records (all multi-year trajectories up to 3 years); (b) 0.0% acute ICU stays (<= 14 days); (c) 0.0% pediatric records (age >= 18); (d) hyperfiltration capped at eGFR <= 140; and (e) 0.0% missingness on protocol eGFR. 5. Intended Benchmark Applications Designed for benchmarking: (1) Sparse Functional Data Analysis (PACE / FPCA) via BLUP conditional expectation; (2) Continuous-Time State-Space Kalman Filtering (CT-SSM) with Maximum Likelihood estimation and closed-form uncertainty bounds; (3) Empirical Bayes Linear Mixed-Effects Models (EB-LMM); (4) Neural Velocity ODEs; and (5) Out-of-sample survival models for severe renal failure progression (eGFR < 30 mL/min/1.73m2).
Links
Where it is published
- DOI doi.org/10.17632/xkc9x7v2sr.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Disease 75% · Longitudinal study 65% · Oncology and carcinogenesis 71%
Provenance · 1 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/xkc9x7v2sr.1 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:group:3211 | enrichment · researchdata tees ac uk | taxonomy-embedding@1.0.0 | title+keywords+description (71%) |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[method].local:method:longitudinal-study | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |