Observational studyPloS one2016
Morphometry Predicts Early GFR Change in Primary Proteinuric Glomerulopathies: A Longitudinal Cohort Study Using Generalized Estimating Equations.
Observational study in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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.
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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.
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Who cites it
14 citing papers in PubMed, 18 citations in OpenAlex.
- A brief review of some artificial intelligence methods in nephrology.Pediatric nephrology (Berlin, Germany) · 2026Review
- Morphometric analysis of chronicity on kidney biopsy: a useful prognostic exercise.Clinical kidney journal · 2024Review
- Comparative evaluation of glomerular morphometric techniques reveals differential technical artifacts between focal segmental glomerulosclerosis and normal glomeruli.Physiological reports · 2023Article
- AMPK mediates regulation of glomerular volume and podocyte survival.JCI insight · 2021Article
- AI applications in renal pathology.Kidney international · 2021Review
- A computational reproducibility study of PLOS ONE articles featuring longitudinal data analyses.PloS one · 2021Article
- Development and evaluation of deep learning-based segmentation of histologic structures in the kidney cortex with multiple histologic stains.Kidney international · 2021Article
- Digital pathology and computational image analysis in nephropathology.Nature reviews. Nephrology · 2020Review
- Comparative analysis of membranous and other nephropathy subtypes and establishment of a diagnostic model.Frontiers of medicine · 2019Article
- Using computer-assisted morphometrics of 5-year biopsies to identify biomarkers of late renal allograft loss.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2019Article
- CureGN Study Rationale, Design, and Methods: Establishing a Large Prospective Observational Study of Glomerular Disease.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2019Observational
- Interstitial fibrosis scored on whole-slide digital imaging of kidney biopsies is a predictor of outcome in proteinuric glomerulopathies.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2018Article
- Digital pathology in nephrology clinical trials, research, and pathology practice.Current opinion in nephrology and hypertension · 2017Review
- Digital pathology imaging as a novel platform for standardization and globalization of quantitative nephropathology.Clinical kidney journal · 2017Article
Corrections and comments
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Authors and funding
7 authors at 6 institutions in 1 country.
Funding
Abstract
objectiveMost predictive models of kidney disease progression have not incorporated structural data. If structural variables have been used in models, they have generally been only semi-quantitative.
methodsWe examined the predictive utility of quantitative structural parameters measured on the digital images of baseline kidney biopsies from the NEPTUNE study of primary proteinuric glomerulopathies. These variables were included in longitudinal statistical models predicting the change in estimated glomerular filtration rate (eGFR) over up to 55 months of follow-up.
resultsThe participants were fifty-six pediatric and adult subjects from the NEPTUNE longitudinal cohort study who had measurements made on their digital biopsy images; 25% were African-American, 70% were male and 39% were children; 25 had focal segmental glomerular sclerosis, 19 had minimal change disease, and 12 had membranous nephropathy. We considered four different sets of candidate predictors, each including four quantitative structural variables (for example, mean glomerular tuft area, cortical density of patent glomeruli and two of the principal components from the correlation matrix of six fractional cortical areas-interstitium, atrophic tubule, intact tubule, blood vessel, sclerotic glomerulus, and patent glomerulus) along with 13 potentially confounding demographic and clinical variables (such as race, age, diagnosis, and baseline eGFR, quantitative proteinuria and BMI). We used longitudinal linear models based on these 17 variables to predict the change in eGFR over up to 55 months. All 4 models had a leave-one-out cross-validated R2 of about 62%.
conclusionsSeveral combinations of quantitative structural variables were significantly and strongly associated with changes in eGFR. The structural variables were generally stronger than any of the confounding variables, other than baseline eGFR. Our findings suggest that quantitative assessment of diagnostic renal biopsies may play a role in estimating the baseline risk of succeeding loss of renal function in future clinical studies, and possibly in clinical practice.
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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.