Dataset Information

Systematic reporting of medical kidney biopsies.

ABSTRACT: The medical kidney biopsy has an important added value in patient care in nephrology. In order to facilitate communication between the pathologist and the nephrologist and optimize patient care, both the content and form of the medical kidney biopsy report matter. With some exceptions, current guidelines in nephropathology focus on content rather than form and, not surprisingly, medical kidney biopsy reports mostly consist of unformatted and often lengthy free text. In contrast, in oncology, a more systematic reporting called synoptic reporting has become the dominant method. Synoptic formats enable complete, concise and clear reports that comply with agreed upon standards. In this review we discuss the possibilities of systematic reporting in nephropathology (including synoptic reporting). Furthermore, we explore applications of electronic formats with structured data and usage of international terminologies or coding systems. The benefits include the timely collection of high-quality data for benchmarking between centres as well as for epidemiologic and other research studies. Based on these developments, a scenario for future medical kidney biopsy reporting is drafted.

SUBMITTER: Leh S

PROVIDER: S-EPMC8757430 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Systematic reporting of medical kidney biopsies.

Leh Sabine S Dendooven Amélie A

Clinical kidney journal 20210723 1

The medical kidney biopsy has an important added value in patient care in nephrology. In order to facilitate communication between the pathologist and the nephrologist and optimize patient care, both the content and form of the medical kidney biopsy report matter. With some exceptions, current guidelines in nephropathology focus on content rather than form and, not surprisingly, medical kidney biopsy reports mostly consist of unformatted and often lengthy free text. In contrast, in oncology, a m ...[more]

PMID: 35035933

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Project description:BackgroundMany publications report the prevalence of chronic kidney disease (CKD) in the general population. Comparisons across studies are hampered as CKD prevalence estimations are influenced by study population characteristics and laboratory methods.MethodsFor this systematic review, two researchers independently searched PubMed, MEDLINE and EMBASE to identify all original research articles that were published between 1 January 2003 and 1 November 2014 reporting the prevalence of CKD in the European adult general population. Data on study methodology and reporting of CKD prevalence results were independently extracted by two researchers.ResultsWe identified 82 eligible publications and included 48 publications of individual studies for the data extraction. There was considerable variation in population sample selection. The majority of studies did not report the sampling frame used, and the response ranged from 10 to 87%. With regard to the assessment of kidney function, 67% used a Jaffe assay, whereas 13% used the enzymatic assay for creatinine determination. Isotope dilution mass spectrometry calibration was used in 29%. The CKD-EPI (52%) and MDRD (75%) equations were most often used to estimate glomerular filtration rate (GFR). CKD was defined as estimated GFR (eGFR) <60 mL/min/1.73 m(2) in 92% of studies. Urinary markers of CKD were assessed in 60% of the studies. CKD prevalence was reported by sex and age strata in 54 and 50% of the studies, respectively. In publications with a primary objective of reporting CKD prevalence, 39% reported a 95% confidence interval.ConclusionsThe findings from this systematic review showed considerable variation in methods for sampling the general population and assessment of kidney function across studies reporting CKD prevalence. These results are utilized to provide recommendations to help optimize both the design and the reporting of future CKD prevalence studies, which will enhance comparability of study results.

Project description:Background and objectivesUnfavorable histology on procurement biopsies is the most common reason for deceased donor kidney discard. We sought to assess the reproducibility of procurement biopsy findings.Design, setting, participants, & measurementsWe compiled a continuous cohort of deceased donor kidneys transplanted at our institution from 1/1/2006 to 12/31/2016 that had at least one procurement biopsy performed, and excluded cases with missing biopsy reports and those used in multiorgan transplants. Suboptimal histology was defined as the presence of advanced sclerosis in greater than or equal to one biopsy compartment (glomeruli, tubules/interstitium, vessels). We calculated κ coefficients to assess agreement in optimal versus suboptimal classification between sequential biopsy reports for kidneys that underwent multiple procurement biopsies and used time-to-event analysis to evaluate the association between first versus second biopsies and patient and allograft survival.ResultsOf the 1011 kidneys included in our cohort, 606 (60%) had multiple procurement biopsies; 98% had first biopsy performed at another organ procurement organization and their second biopsy performed locally. Categorical agreement was highest for vascular disease (κ=0.17) followed by interstitial fibrosis and tubular atrophy (κ=0.12) and glomerulosclerosis (κ=0.12). Overall histologic agreement (optimal versus suboptimal) was κ=0.15. First biopsy histology had no association with allograft survival in unadjusted or adjusted analyses. However, second biopsy optimal histology was associated with a higher probability of death-censored allograft survival, even after adjusting for donor and recipient factors (adjusted hazard ratio, 0.50; 95% confidence interval, 0.34 to 0.75; P=0.001).ConclusionsDeceased donor kidneys that underwent multiple procurement biopsies often displayed substantial differences in histologic categorization in sequential biopsies, and there was no association between first biopsy findings and post-transplant outcomes.

Project description:AimsWe conducted a systematic review assessing the reporting quality of studies validating models based on machine learning (ML) for clinical diagnosis, with a specific focus on the reporting of information concerning the participants on which the diagnostic task was evaluated on.MethodMedline Core Clinical Journals were searched for studies published between July 2015 and July 2018. Two reviewers independently screened the retrieved articles, a third reviewer resolved any discrepancies. An extraction list was developed from the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis guideline. Two reviewers independently extracted the data from the eligible articles. Third and fourth reviewers checked, verified the extracted data as well as resolved any discrepancies between the reviewers.ResultsThe search results yielded 161 papers, of which 28 conformed to the eligibility criteria. Detail of data source was reported in 24 of the 28 papers. For all of the papers, the set of patients on which the ML-based diagnostic system was evaluated was partitioned from a larger dataset, and the method for deriving such set was always reported. Information on the diagnostic/non-diagnostic classification was reported well (23/28). The least reported items were the use of reporting guideline (0/28), distribution of disease severity (8/28 patient flow diagram (10/28) and distribution of alternative diagnosis (10/28). A large proportion of studies (23/28) had a delay between the conduct of the reference standard and ML tests, while one study did not and four studies were unclear. For 15 studies, it was unclear whether the evaluation group corresponded to the setting in which the ML test will be applied to.ConclusionAll studies in this review failed to use reporting guidelines, and a large proportion of them lacked adequate detail on participants, making it difficult to replicate, assess and interpret study findings.Prospero registration numberCRD42018099167.

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Systematic reporting of medical kidney biopsies.

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Systematic reporting of medical kidney biopsies.

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