Evidence map›Paper›PMID 30325739›Full record

ArticleAging2018

Inflammation markers are associated with frailty in elderly patients with coronary heart disease.

Ping Hou, Hui-Ping Xue, Xin-E Mao, Yong-Nan Li, Lin-Feng Wu, Yong-Bing Liu

Abstract read
In one paragraph

Article in Aging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
–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

35 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Ping HouSchool of Nursing, Yangzhou University, Yangzhou 225000, China.
Hui-Ping XueSchool of Nursing, Yangzhou University, Yangzhou 225000, China.
Xin-E MaoSchool of Nursing, Yangzhou University, Yangzhou 225000, China.
Yong-Nan LiSchool of Nursing, Yangzhou University, Yangzhou 225000, China.
Lin-Feng WuSchool of Nursing, Yangzhou University, Yangzhou 225000, China.
Yong-Bing LiuSchool of Nursing, Yangzhou University, Yangzhou 225000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The neutrophil-to-lymphocyte ratio (NLR) and red blood cell distribution width (RDW) are important indicators of adverse outcomes and have predictive value for many diseases; however, the relationships between frailty, and the NLR and RDW in patients with coronary heart disease (CHD) have not been determined. In this cross-sectional study, we investigated the association between frailty, and the NLR and RDW in elderly CHD patients ≥ 60 years of age. Frailty was defined according to frailty phenotype. Of 345 patients enrolled in the study, 22.6%, 58.3%, and 19.1% were characterized as robust, pre-frail, and frail, respectively. A significant positive correlation was observed between frailty and the NLR (r = 0.169) and RDW (r = 0.196). After adjusting for confounders, linear regression analyses showed that participants in the 4th quartile of the NLR or RDW were more likely to have a higher frailty phenotype score. Based on multivariable logistic regression, patients in the 4th quartile of the NLR and RDW, the fully-adjusted odds ratios for incident frailty were 2.894 (p = 0.011) and 2.494 (p = 0.040), respectively. Our findings indicate that frailty is associated with the NLR and RDW in elderly patients with CHD.

Indexed as

ErythrocytesLymphocytesNeutrophilsAgedAged, 80 and overAge FactorsAgingCoronary DiseaseCross-Sectional StudiesErythrocyte IndicesFrail ElderlyFrailtyHumansInflammationLymphocyte CountMalecoronary heart diseasefrailtyinflammation markersneutrophil to lymphocytered blood cell distribution width

Identifiers

PMID30325739
PMCPMC6224228

What OpenQuestion holds

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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.