Evidence map›Paper›PMID 31016186›Full record

ArticleBioMed research international2019

Relation between Red Cell Distribution Width and Mortality in Critically Ill Patients with Acute Respiratory Distress Syndrome.

Benji Wang, Yuqiang Gong, Binyu Ying, Bihuan Cheng

Abstract read
In one paragraph

Article in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 2 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

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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

48 citing papers in PubMed, 2 syntheses or guidelines 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

4 authors.

Benji WangDepartment of Anesthesiology, Critical Care and Pain Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China.
Yuqiang GongDepartment of Anesthesiology, Critical Care and Pain Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China.
Binyu YingDepartment of Anesthesiology, Critical Care and Pain Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China.
Bihuan ChengDepartment of Anesthesiology, Critical Care and Pain Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China.ORCID 0000-0001-5889-5685

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrently, evidence regarding the predictive significance of red blood cell distribution width (RDW) among patients with acute respiratory distress syndrome (ARDS) remains scarce. The aim of this study was to determine the prognostic value of RDW for critically ill patients with ARDS.

methodsWe studied all patients with ARDS from the Multiparameter Intelligent Monitoring in Intensive Care Database III (MIMIC-III) for whom RDW was available. The clinical outcomes were 30-day and 90-day mortality. Analyses included logistic multivariate regression model, Receiver Operating Characteristic (ROC) analysis, and subgroup analysis.

resultsA total of 404 eligible ARDS patients were included. After adjustment for several clinical characteristics related to 30-day mortality, the adjusted OR (95% CIs) for RDW levels ≥14.5% was 1.91 (1.08, 3.39). A similar trend was observed for 90-day mortality. The RDW levels ≥14.5% were also an independent predictor of 90-day mortality (OR, 2.56; 95% CI, 1.50 to 4.37;

conclusionsRDW appeared to be a novel, independent predictor of mortality in critically ill patients with ARDS.

Indexed as

AgedCritical IllnessErythrocyte IndicesErythrocytesFemaleHospital MortalityHumansLogistic ModelsMaleMiddle AgedPrognosisRespiratory Distress SyndromeRisk FactorsROC Curve

Identifiers

PMID31016186
PMCPMC6448335

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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.