Evidence map›Paper›PMID 33145285›Full record

ArticleAnnals of translational medicine2020

The profiles of biopsy-proven renal tubulointerstitial lesions in patients with glomerular disease.

Jin Dong, Yanqin Li, Shuling Yue, Xiaoting Liu, Long Wang, Mengqi Xiong, Guobao Wang, Sheng Nie, Xin Xu

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.9field-weighted citation impact, top 22% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 17 citations in OpenAlex.

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  10. Nephrotic syndrome in the elderly: epidemiological aspects, clinical data, and renal biopsy findings.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Jin DongNational Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Yanqin LiNational Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Shuling YueDepartment of Pathology, King Medical Diagnostics Center, Guangzhou, China.
Xiaoting LiuDepartment of Pathology, King Medical Diagnostics Center, Guangzhou, China.
Long WangNational Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Mengqi XiongNational Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Guobao WangNational Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Sheng NieNational Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Xin XuNational Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Nanfang Hospital · CNSouthern Medical University · CNKingmed Diagnostics · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRenal tubules and interstitium are vulnerable to injury and play a central role in the progression of various chronic kidney diseases (CKDs). However, high quality epidemiologic study on the profiles of biopsy-proven tubulointerstitial lesions (TILs) is extremely limited.

methodsWe conducted a retrospective renal biopsy series including 62,569 native biopsies at 1,211 hospitals across China from 2015 to 2017. The TILs, including the shedding of tube epithelial, renal tubular atrophy, renal interstitial fibrosis, edema and inflammatory infiltration, were identified from the pathological report. We analyzed the severity and chronicity of TILs stratified by gender, age groups, biopsy indications, and concurrent glomerular diseases. We also examined the correlation between TIL and glomerulosclerosis.

resultsOf 56,880 patients with biopsy-proven glomerular disease, 79.5% had TILs. Renal interstitial inflammatory infiltration was the most common type of TIL (77.7%), followed by renal tubular atrophy (56.0%) and renal interstitial fibrosis (32.8%). Severe and chronic TILs were more common in adults than in children. The three glomerular diseases with the highest proportion of moderate-to-severe and chronic TIL were diabetic nephropathy, immunoglobulin A (IgA) nephropathy and focal segmental glomerulosclerosis. The severity of TILs was moderately correlated with glomerulosclerosis score (r=0.51). Moderate-to-severe and chronic TIL were more common in southern China. After adjusting for age, sex, hospital level, region, biopsy indication and type of concurrent glomerular diseases, adults with renal arteriole injury had a six-fold higher risk of moderate-to-severe TIL [odds ratio (OR), 7.12; 95% confidence interval (CI), 6.42 to 7.91] and a three-fold higher risk of chronic TIL (OR, 4.58; 95% CI, 4.37 to 4.79).

conclusionsTILs were common in patients with biopsy-proven glomerular disease. The type and severity of TILs varied with age, region and concurrent glomerular diseases. Renal arteriole injury and glomerulosclerosis was associated with a significantly increased risk of TIL.

Indexed as

Clinical epidemiologyglomerulosclerosiskidney tubulepathology injuryrenal arteriole injury

Identifiers

PMID33145285
PMCPMC7575977
OpenAlexW3083860943

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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.