Evidence map›Paper›PMID 32489740›Full record

ArticleCureus2020

The Correlation of Routine Hematological Parameters with In-hospital Mortality and Length of Hospital Stay in Patients with Large Middle Cerebral Artery Infarction.

Muzaffer Güneş

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 49% 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

4 citing papers in PubMed, 5 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

1 author at 1 institution in 1 country.

Muzaffer GüneşNeurology, Aksaray University Training and Research Hospital, Aksaray, TUR.
Aksaray University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective Neutrophil-to-lymphocyte ratio (NLR) and red blood cell distribution width (RDW) reflect inflammation and these parameters have not been studied in patients with large cerebral artery infarction. This study investigated the correlation of these inflammation parameters with in-hospital mortality and length of hospital stay (LOS) in patients with large middle cerebral artery (MCA) infarction. Materials and methods The study was conducted with patients who had large MCA (M1 and M2 segments) infarction. Clinical data of the patients and laboratory results at presentation were obtained from our database and recorded for statistical analysis. Multivariate logistic regression analysis was used to investigate the prognostic factors. The correlation between hematological parameters and LOS was investigated using Spearman's Rho and Pearson correlation tests. Results A total of 143 patients (48 patients with hospital mortality, 95 patients without hospital mortality) were included in the study. The median LOS in patients with hospital mortality [10 (2-90) days] was significantly higher compared to the patients without [7 (2-30) days] (p = 0.024). RDW-SD was found to be a poor prognostic factor according to the multivariate logistic regression model (p = 0.004). There was a significant but weak and positive correlation between LOS and NLR (p = 0.003, r: 0.248) and a significant but weak and negative correlation between LOS and eosinophil count (p = 0.001, r: -0.278). Conclusions High RDW at presentation is a poor prognostic factor in terms of in-hospital mortality in patients with large MCA infarction. In addition, a positive correlation has been found between NLR and LOS.

Indexed as

acute ischemic strokehematological parametersin-hospital mortalitylength of hospital staymiddle cerebral artery infarction

Identifiers

PMID32489740
PMCPMC7255539
OpenAlexW3023898897

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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.