Evidence map›Paper›PMID 36846118›Full record

ArticleFrontiers in neurology2023

Systemic inflammation response index predicts 3-month outcome in patients with mild acute ischemic stroke receiving intravenous thrombolysis.

Min Chu, Yunhe Luo, Daosheng Wang, Yang Liu, Delong Wang, Yong Wang, Jing Zhao

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Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 3 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

25 citing papers in PubMed, 3 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

7 authors.

Min ChuDepartment of Neurology, Minhang Hospital, Fudan University, Shanghai, China.
Yunhe LuoDepartment of Neurology, Minhang Hospital, Fudan University, Shanghai, China.
Daosheng WangDepartment of Neurosurgery, Minhang Hospital, Fudan University, Shanghai, China.
Yang LiuDepartment of Neurology, Minhang Hospital, Fudan University, Shanghai, China.
Delong WangDepartment of Neurology, Minhang Hospital, Fudan University, Shanghai, China.
Yong WangDepartment of Neurology, Minhang Hospital, Fudan University, Shanghai, China.
Jing ZhaoDepartment of Neurology, Minhang Hospital, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A crucial aspect of stroke progression is the inflammatory response. As novel inflammatory and prognostic markers, the systemic immune inflammation index (SII) and the systemic inflammation response index (SIRI) have recently been studied. The objective of our study was to evaluate the prognostic value of SII and SIRI in mild acute ischemic stroke (AIS) patients following intravenous thrombolysis (IVT). Methods: Our study screened the clinical data of patients with mild AIS admitted to the Minhang Hospital of Fudan University for retrospective analysis. The SIRI and SII were examined by the emergency laboratory before IVT. Functional outcome was evaluated 3 months after the onset of stroke using the modified Rankin Scale (mRS). mRS ≥ 2 was defined as an unfavorable outcome. The relationship between SIRI and SII and the 3-month prognosis was determined using both univariate and multivariate analysis. Receiver operating characteristic curve was performed to evaluate the predictive value of SIRI for AIS prognosis. Results: A total of 240 patients were included in this study. Both SIRI and SII were higher in the unfavorable outcome group than in the favorable outcome group [1.28 (0.70-1.88) vs. 0.79 (0.51-1.08), Conclusions: Higher SIRI could be valuable in predicting poor clinical outcomes for patients with mild AIS following IVT.

Indexed as

3-month outcomeintravenous thrombolysismild acute ischemic strokesystemic immune inflammation indexsystemic inflammation response index

Identifiers

PMID36846118
PMCPMC9946296

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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.