Evidence map›Paper›PMID 29889895›Full record

Observational studyPloS one2018

Red cell distribution width and renal outcome in patients with non-dialysis-dependent chronic kidney disease.

Sayoko Yonemoto, Takayuki Hamano, Naohiko Fujii, Karin Shimada, Satoshi Yamaguchi, Ayumi Matsumoto, Keiichi Kubota, Nobuhiro Hashimoto, Tatsufumi Oka, Masamitsu Senda and 3 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
0.8field-weighted citation impact, top 23% 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

18 citing papers in PubMed, 27 citations in OpenAlex.

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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

13 authors at 2 institutions in 1 country.

Sayoko YonemotoDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.ORCID 0000-0001-7128-0482
Takayuki HamanoDepartment of Inter-Organ Communication Research in Kidney Disease, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Naohiko FujiiDepartment of Internal Medicine, Hyogo Prefectural Nishinomiya Hospital, Nishinomiya, Hyogo, Japan.
Karin ShimadaDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Satoshi YamaguchiDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Ayumi MatsumotoDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Keiichi KubotaDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Nobuhiro HashimotoDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Tatsufumi OkaDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Masamitsu SendaDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Yusuke SakaguchiDepartment of Inter-Organ Communication Research in Kidney Disease, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Isao MatsuiDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Yoshitaka IsakaDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
The University of Osaka · JPHyogo Prefectural Nishinomiya Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Higher red cell distribution width (RDW) has been reported to predict mortality among patients with various diseases, including chronic kidney disease (CKD). However, whether RDW is associated with renal outcome remains unclear. We investigated the relationship between RDW and renal outcome in patients with non-dialysis-dependent CKD (NDD-CKD). This prospective, observational study of patients with CKD was conducted at a single nephrology department. First, we performed regression analyses for the decline in estimated glomerular filtration rate (eGFR) during the first 3 months of observation to determine its short-term association with RDW. Next, we categorized baseline RDW into two groups by its median (13.5%) and performed Cox regression analyses to investigate whether higher RDW was an independent predictor of renal outcomes defined as a composite of the initiation of dialysis and doubling of the serum creatinine concentration. Furthermore, we repeated the analyses to confirm whether the transition of the RDW category during the first 3 months would also predict renal outcomes. We enrolled 703 patients. Baseline RDW showed a non-linear association with the eGFR decline during the first 3 months, with a greater negative correlation at the lower end of the RDW distribution. Over a median follow-up of 1.8 years, 178 patients (25.3%) reached the renal endpoint. Multivariable Cox regression analyses showed that patients with higher RDW had a higher risk of developing renal outcomes (adjusted hazard ratio [HR]: 1.47, 95% confidence interval [CI]: 1.05-2.07) than did those with lower RDW. Furthermore, patients with sustained, higher RDW demonstrated a significantly higher risk than did those with consistently lower RDW (adjusted HR: 1.65, 95% CI: 1.02-2.67). In conclusion, higher RDW was independently associated with worse renal outcome in patients with NDD-CKD. RDW could be an additional prognostic marker of the progression of CKD.

Indexed as

AgedCreatinineErythrocyte IndicesFemaleGlomerular Filtration RateHumansKidneyMaleMiddle AgedProportional Hazards ModelsProspective StudiesRenal Insufficiency, ChronicRisk FactorsSeverity of Illness IndexCreatinine

Identifiers

PMID29889895
PMCPMC5995355
OpenAlexW2808242680

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.