Evidence map›Paper›PMID 33731740›Full record

SynthesisScientific reports2021

Prognostic value of neutrophil to lymphocyte ratio in acute ischemic stroke after reperfusion therapy.

Ying Bi, Jing Shen, Sheng-Cai Chen, Ji-Xiang Chen, Yuan-Peng Xia

Abstract readMeta-Analysis
In one paragraph

Synthesis in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 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

5 authors.

Ying BiDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Jing ShenDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Sheng-Cai ChenDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Ji-Xiang ChenDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China. 1983xh0564@hust.edu.cn.
Yuan-Peng XiaDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China. xiayuanpeng@hust.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to investigate whether baseline neutrophil to lymphocyte ratio (NLR) was an independent predictor for early symptomatic intracranial hemorrhage (sICH), poor functional outcome and mortality at 3 months after reperfusion therapy in acute ischemic stroke (AIS) patients. Using PubMed and EMBASE, we searched for literature published before January 19th, 2019. Two reviewers independently confirmed each study's eligibility, assessed risk of bias, and extracted data. One reviewer combined studies using random effects meta-analysis. 9 studies with 3651 patients were pooled in the meta-analysis. Overall, baseline NLR levels were greater in patients with poor outcome. The standardized mean difference (SMD) in the NLR levels between patients with poor functional outcome (mRS > 2) and good functional outcome (mRS ≤ 2) was 0.54 units (95% credible interval [CI] [0.38, 0.70]). Heterogeneity test showed that there were significant differences between individual studies (p = 0.02; I

Indexed as

Brain IschemiaCell CountCohort StudiesHumansIschemic StrokeLymphocytesNeutrophilsPrognosisReperfusionReperfusion InjuryRisk Factors

Identifiers

PMID33731740
PMCPMC7971057

What OpenQuestion holds

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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.