Observational studyBMJ open2022
Analysis of eGFR index category and annual eGFR slope association with adverse clinical outcomes using real-world Japanese data: a retrospective database study.
Observational study in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Is eGFR Slope a Novel Predictor of Chronic Complications of Type 2 Diabetes Mellitus? A Systematic Review and Meta-Analysis.Journal of diabetes research · 2024Pooled it
- Long-Term Effect of Semaglutide on the Glomerular Filtration Rate Slope in High-Risk Patients with Diabetic Nephropathy: Analysis in Real-World Clinical Practice.Pharmaceutics · 2025Article
- Impaired renal function in patients with permanent hypoparathyroidism after thyroidectomy: analysis of a nationwide cohort in Spain.Endocrine · 2025Article
- Patient Management and Clinical Outcomes Associated with a Recorded Diagnosis of Stage 3 Chronic Kidney Disease: The REVEAL-CKD Study.Advances in therapy · 2023Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesReal-world clinical outcome data of patients with an above-normal estimated glomerular filtration rate (eGFR) and increasing eGFR over time (eGFR slope) are scarce. Although eGFR is commonly recorded, eGFR slopes are rarely used for adverse outcome risk categorisation in clinical practice. We investigated the association of above-normal/below-normal eGFR ranges and increasing/declining eGFR slopes with clinical outcomes in Japan.
designObservational cohort study.
settingPrimary and acute care hospitals; 423 centres.
participants57 452 patients aged ≥16 years with ≥3 eGFR values (latest available January 2013-December 2016) from the Japanese Medical Data Vision database were stratified into six index eGFR and six eGFR slope groups (slopes calculated using a linear mixed model). PRIMARY AND SECONDARY OUTCOME MEASURES: Time-to-event analyses of cardiovascular mortality, all-cause mortality (ACM), all-cause hospitalisation (ACH) and cardiovascular and major kidney events. eGFR and slope groups were analysed by Cox proportional hazard models with multivariable adjustment, using normal eGFR/little-to-no slope groups as reference.
resultsHigher risk of clinical outcomes was observed with declining eGFR slope groups versus the reference group; the HR (95% CI) for slope ≤-5 mL/min/1.73 m
conclusionPoorer clinical outcomes were observed not only for below-normal eGFR and declining eGFR slope groups but also for certain above-normal eGFR and increasing slope groups. eGFR and eGFR slope may, therefore, be useful for identifying patients at high risk of adverse clinical outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.