Evidence map›Paper›PMID 23136634›Full record

ArticleKorean journal of urology2012

Clinical Assessment of Follow-Up Cystatin C-Based eGFR in Live Kidney Donors.

Hyun Ho Han, Kyung Hwa Choi, Seung Choul Yang, Woong Kyu Han

Open access · hybridAbstract read
In one paragraph

Article in Korean journal of urology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Observational
  2. Article
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

4 authors at 1 institution in 1 country.

Hyun Ho HanDepartment of Urology, Urological Science Institute, Yonsei University College of Medicine, Seoul, Korea.
Kyung Hwa Choi
Seung Choul Yang
Woong Kyu Han
Yonsei University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe aimed to compare the cystatin C-based estimated glomerular filtration rate (eGFR) and the serum creatinine-based eGFR and to investigate the clinical roles of the cystatin C-based eGFR in assessing the follow-up renal function of kidney donors. MATERIALS AND

methodsWe enrolled 121 healthy kidney donors who underwent live donor nephrectomy between October 2009 and December 2010 in a prospective manner. Serum creatinine and cystatin C were measured preoperatively and were followed after the surgery (1st, 4th, and 7th postoperative day and 1st, 3rd, 6th, and 12th postoperative month). We also compared the sensitivity and specificity of each eGFR method for predicting the development of chronic kidney disease (CKD) after donor nephrectomy.

resultsFor those who had a Modification of Diet in Renal Disease postoperative day 4 eGFR of less than 60 ml/min/1.73 m(2), the probability of developing CKD was 89.0% (Chronic Kidney Disease Epidemiology Collaboration eGFR, 66.0%; Cockcroft-Gault eGFR, 74.0%; cystatin C eGFR, 57.1%). A cystatin C eGFR of below 60 ml/min/1.73 m(2) at postoperative day 4 predicted CKD at 6 months with a specificity of 90.3%, which was the highest among the estimation methods used. Cystatin C eGFRs were generally higher than the creatinine-based eGFRs.

conclusionsWe conclude that cystatin C-based estimations of the GFR are helpful for predicting the recovery of renal function in kidney donors and could be added to the follow-up protocol of kidney donors who may develop CKD, especially patients whose immediate postoperative renal function is marginal.

Indexed as

Kidney function testsKidney transplantationLiving donorsNephrectomy

Identifiers

PMID23136634
PMCPMC3490094
OpenAlexW2102925091

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

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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.