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Distinguishing age-related from disease-related glomerulosclerosis on kidney biopsy: the Aging Kidney Anatomy study.

ABSTRACT: Global glomerulosclerosis is characteristic of chronic kidney disease and also occurs with normal aging. Our goal was to determine the upper limit of normal for number of globally sclerotic glomeruli.Core-needle biopsies of the renal cortex were obtained at the time of living kidney transplantation at three centers between 1998 and 2011. The number of globally sclerotic glomeruli was averaged across two biopsy sections. Quantile regression was used to estimate the 95th percentile for globally sclerotic glomeruli as the upper reference limit. There were 2052 donors (mean age 43 years, 41% male, 10% hypertensive), with a mean (SD) of 16.0 (9.7) glomeruli and 0.47 (0.99) globally sclerotic glomeruli on biopsy; only 2.6% had >5% fibrosis.In a multivariable model excluding hypertensive donors, independent predictors of the number of globally sclerotic glomeruli were age, total number of glomeruli and cortex area. A simplified model was used to estimate the 95th percentile for number of globally sclerotic glomeruli by total number of glomeruli and age. For a biopsy section with 17-32 total glomeruli, the 95th percentile ranged from 1 for a 20-year old to 5.5 for a 70-year old donor. Hypertensive donors were more likely to have an abnormal number of globally sclerotic glomeruli (OR = 1.79, P = 0.035).We have derived the 95% reference limit for number of globally sclerotic glomeruli in ostensibly healthy individuals accounting for age and the biopsy characteristics. Numbers of globally sclerotic glomeruli in a kidney biopsy that exceed these thresholds suggest chronic pathological injury in excess of that expected with normal aging.

SUBMITTER: Kremers WK

PROVIDER: S-EPMC4783459 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Distinguishing age-related from disease-related glomerulosclerosis on kidney biopsy: the Aging Kidney Anatomy study.

Kremers Walter K WK Denic Aleksandar A Lieske John C JC Alexander Mariam P MP Kaushik Vidhu V Elsherbiny Hisham E HE Chakkera Harini A HA Poggio Emilio D ED Rule Andrew D AD

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 20150416 12

<h4>Background</h4>Global glomerulosclerosis is characteristic of chronic kidney disease and also occurs with normal aging. Our goal was to determine the upper limit of normal for number of globally sclerotic glomeruli.<h4>Methods</h4>Core-needle biopsies of the renal cortex were obtained at the time of living kidney transplantation at three centers between 1998 and 2011. The number of globally sclerotic glomeruli was averaged across two biopsy sections. Quantile regression was used to estimate ...[more]

PMID: 25888387

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Project description:Background and objectivesPatients are informed of the risk of kidney biopsy-related complications using data from nonhospitalized patients, which may underestimate the risk for hospitalized patients. We evaluated the rate and risk factors of kidney biopsy-related complications in hospitalized patients with acute kidney disease (AKD) to better estimate the risk in this population.Design, setting, participants, & measurementsWe used data from the Yale biopsy cohort to evaluate rates of kidney biopsy-related complications including adjudicated procedure-related bleeding requiring blood transfusions or angiographic interventions, medium- or large-sized hematomas, reimaging after biopsy including abdominal ultrasonography or computed tomography, and death in hospitalized patients with AKD (including AKI). We evaluated univariable and multivariable association of risk factors with transfusions. We compared rates of complications between hospitalized and nonhospitalized patients.ResultsBetween 2015 and 2017, 159 hospitalized patients underwent a kidney biopsy for AKD evaluation, of which 80 (51%) had stage 1 AKI, 42 (27%) had stage 2 (or higher) AKI, and 27 (17%) had AKD (without AKI). Of these, 12 (8%; 95% confidence interval [95% CI], 5% to 15%) required a transfusion, three (2%; 95% CI, 1% to 5%) required an intervention, 11 (7%; 95% CI, 4% to 12%) had hematoma, and 31 (20%; 95% CI, 14% to 26%) required reimaging after biopsy. Of the four (3%; 95% CI, 1% to 6%) deaths during hospitalization, none were related to the biopsy. Female sex, lower platelet count, and higher BUN were associated with postbiopsy transfusions on univariable and multivariable analyses. Trainee as proceduralist and larger needle gauge were associated with transfusions in univariable, but not multivariable, analysis. Nonhospitalized patients had lower rates of transfusion than hospitalized patients, although the latter also had lower prebiopsy hemoglobin and greater surveillance after biopsy.ConclusionsHospitalized patients experience higher risk of postbiopsy complications than previously reported and several factors, such as lower platelet count, female sex, and higher BUN, are associated with this risk.

Project description:Rationale & objectiveAssessment of kidney biopsies provides crucial information for diagnosis and disease activity, as well as prognostic value. Kidney-biopsy specimens occasionally contain veno-muscular complex (VMC), which consists of muscle tissues around the kidney venous system in the corticomedullary region. However, the role of VMC and the clinical significance of VMC variants are poorly understood. In the present study, we investigated kidney prognostic values of VMC variants.Study designRetrospective cohort study.Setting & participantsAmong 808 patients who underwent a kidney biopsy from 2011 to 2019, 246 patients whose kidney biopsy specimens contained VMC were enrolled.PredictorsVMC variants; inflammatory-VMC (an infiltration of ≥80 inflammatory cells/mm2-VMC area) and VMC hypertrophy (hyper-VMC, a VMC average width ≥850 μm), and the interstitial fibrosis/tubular atrophy (IFTA) score.OutcomesA decline in estimated glomerular filtration rate (eGFR) ≥40% from the baseline or commencement of kidney replacement therapy.Analytical approachCox proportional hazards model.ResultsAmong 246 patients with data on VMC, mean baseline eGFR was 56.0±25.6 ml/min per 1.73 m2; 80 had high inflammatory-VMC, and 62 had VMC hypertrophy. There were 51 kidney events over median follow-up of 2.5 years. We analyzed 2 VMC variants. Multivariable logistic regression analysis revealed that eGFR negatively correlated with the presence of both inflammatory-VMC and hyper-VMC. A Cox proportional hazards analysis revealed that inflammatory-VMC (but not hyper-VMC) was independently associated with the primary outcome after adjustments for known risk factors of progression, including proteinuria, eGFR, and the interstitial fibrosis/tubular atrophy (IFTA) score (hazard ratio, 1.97; 95% confidence interval, 1.00-3.91).LimitationsSingle-center study and small sample size.ConclusionsAssessment of inflammatory-VMC provides additional kidney prognostic information to known indicators of kidney disease progression in patients who undergo kidney biopsy.Plain-language summaryAssessment of kidney biopsies provides crucial information for diagnosis, disease activity, and prognostic value. Kidney-biopsy specimens occasionally contain veno-muscular complex (VMC), which consists of muscle tissues around the kidney venous system. Currently, the role of VMC in kidney health and diseases and the clinical significance of VMC variants are poorly understood. In the present study, we have shown that an infiltration of ≥80 inflammatory cells/mm2-VMC area (inflammatory-VMC) is independently associated with kidney disease progression after adjustments for known risk factors of progression. Therefore, assessment of inflammatory-VMC provides additional kidney prognostic information to known indicators of kidney disease progression in patients who undergo kidney biopsy.

Project description:ImportanceA chronic shortage of donor kidneys is compounded by a high discard rate, and this rate is directly associated with biopsy specimen evaluation, which shows poor reproducibility among pathologists. A deep learning algorithm for measuring percent global glomerulosclerosis (an important predictor of outcome) on images of kidney biopsy specimens could enable pathologists to more reproducibly and accurately quantify percent global glomerulosclerosis, potentially saving organs that would have been discarded.ObjectiveTo compare the performances of pathologists with a deep learning model on quantification of percent global glomerulosclerosis in whole-slide images of donor kidney biopsy specimens, and to determine the potential benefit of a deep learning model on organ discard rates.Design, setting, and participantsThis prognostic study used whole-slide images acquired from 98 hematoxylin-eosin-stained frozen and 51 permanent donor biopsy specimen sections retrieved from 83 kidneys. Serial annotation by 3 board-certified pathologists served as ground truth for model training and for evaluation. Images of kidney biopsy specimens were obtained from the Washington University database (retrieved between June 2015 and June 2017). Cases were selected randomly from a database of more than 1000 cases to include biopsy specimens representing an equitable distribution within 0% to 5%, 6% to 10%, 11% to 15%, 16% to 20%, and more than 20% global glomerulosclerosis.Main outcomes and measuresCorrelation coefficient (r) and root-mean-square error (RMSE) with respect to annotations were computed for cross-validated model predictions and on-call pathologists' estimates of percent global glomerulosclerosis when using individual and pooled slide results. Data were analyzed from March 2018 to August 2020.ResultsThe cross-validated model results of section images retrieved from 83 donor kidneys showed higher correlation with annotations (r = 0.916; 95% CI, 0.886-0.939) than on-call pathologists (r = 0.884; 95% CI, 0.825-0.923) that was enhanced when pooling glomeruli counts from multiple levels (r = 0.933; 95% CI, 0.898-0.956). Model prediction error for single levels (RMSE, 5.631; 95% CI, 4.735-6.517) was 14% lower than on-call pathologists (RMSE, 6.523; 95% CI, 5.191-7.783), improving to 22% with multiple levels (RMSE, 5.094; 95% CI, 3.972-6.301). The model decreased the likelihood of unnecessary organ discard by 37% compared with pathologists.Conclusions and relevanceThe findings of this prognostic study suggest that this deep learning model provided a scalable and robust method to quantify percent global glomerulosclerosis in whole-slide images of donor kidneys. The model performance improved by analyzing multiple levels of a section, surpassing the capacity of pathologists in the time-sensitive setting of examining donor biopsy specimens. The results indicate the potential of a deep learning model to prevent erroneous donor organ discard.

Dataset Information

Distinguishing age-related from disease-related glomerulosclerosis on kidney biopsy: the Aging Kidney Anatomy study.

Publications

Distinguishing age-related from disease-related glomerulosclerosis on kidney biopsy: the Aging Kidney Anatomy study.

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