Evidence map›Paper›PMID 32973294›Full record

ArticleScientific reports2020

Low rather than high mean corpuscular volume is associated with mortality in Japanese patients under hemodialysis.

Hirokazu Honda, Miho Kimachi, Noriaki Kurita, Nobuhiko Joki, Masaomi Nangaku

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

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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

5 authors.

Hirokazu HondaDepartment of Medicine, Division of Nephrology, Showa University School of Medicine, 1-5-8, Hatanodai, Shinagawa-ku, Tokyo, 142-8666, Japan. hondah@med.showa-u.ac.jp.
Miho KimachiDepartment of Healthcare Epidemiology, School of Public Health in the Graduate School of Medicine, Koto University, Kyoto, Japan.
Noriaki KuritaDepartment of Clinical Epidemiology, Graduate School of Medicine, Fukushima Medical University, Fukushima, Japan.
Nobuhiko JokiDivision of Nephrology, Toho University Ohashi Medical Center, Tokyo, Japan.
Masaomi NangakuDivision of Nephrology and Endocrinology, The University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies have reported that high mean corpuscular volume (MCV) might be associated with mortality in patients with advanced chronic kidney disease (CKD). However, the question of whether a high MCV confers a risk for mortality in Japanese patients remains unclear. We conducted a longitudinal analysis of a cohort of 8571 patients using data derived from the Japan Dialysis Outcomes and Practice Patterns Study (J-DOPPS) phases 1 to 5. Associations of all-cause mortality, vascular events, and hospitalization due to infection with baseline MCV were examined via Cox proportional hazard models. Non-linear relationships between MCV and these outcomes were examined using restricted cubic spline analyses. Associations between time-varying MCV and these outcomes were also examined as sensitivity analyses. Cox proportional hazard models showed a significant association of low MCV (< 90 fL), but not for high MCV (102 < fL), with a higher incidence of all-cause mortality and hospitalization due to infection compared with 94 ≤ MCV < 98 fL (reference). Cubic spline analysis indicated a graphically U-shaped association between baseline MCV and all-cause mortality (p for non-linearity p < 0.001). In conclusion, a low rather than high MCV might be associated with increased risk for all-cause mortality and hospitalization due to infection among Japanese patients on hemodialysis.

Indexed as

Erythrocyte IndicesMortalityRenal DialysisBlood VesselsCohort StudiesFemaleHospitalizationHumansJapanMaleMiddle Aged

Identifiers

PMID32973294
PMCPMC7515877

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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.