Evidence map›Paper›PMID 37202593›Full record

ArticleNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2023

The metabolic score for insulin resistance as a predictor of clinical outcome in stroke patients treated by intravenous thrombolysis.

Mingzhe Wang, Zheng Dai, Xiaohao Zhang, Xiaochen Xu, Yan Sun, Fan Gong, Baofeng Qin, Jun Wang, Bin Liu, Haiyan Tang and 7 more

Abstract read
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In one paragraph

Article in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

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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

17 authors.

Mingzhe Wang *Department of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China.
Zheng Dai *Department of Neurology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu Province, 214023, China.
Xiaohao Zhang *Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, China.
Xiaochen XuDepartment of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China.
Yan SunDepartment of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China.
Fan GongDepartment of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China.
Baofeng QinDepartment of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China.
Jun WangDepartment of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China.
Bin LiuDepartment of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China.
Haiyan TangDepartment of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China.
Tingting LiDepartment of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China.
Jinsi ZhangDepartment of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China.
Jiecheng WangDepartment of Encephalopathy, Qinghai Provincial Hospital of Traditional Chinese Medicine, Xining, 810000, Qinghai Province, China.
Wenjie ChenDepartment of Neurology, Nanping People's Hospital Affiliated to Fujian University of Traditional Chinese Medicine, Nanping, 353000, Fujian Province, China.
Ling MaDepartment of Encephalopathy, Qinghai Provincial Hospital of Traditional Chinese Medicine, Xining, 810000, Qinghai Province, China.
Zhenxiang HanDepartment of Neurology and Rehabilitation, Seventh People's Hospital of Shanghai University of TCM, 200137, No 358 Datong Road, Shanghai, 200137, China. hanxiang798007@gmail.com.
Dezhi LiuDepartment of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China. liudz_neuro@126.com.ORCID http://orcid.org/0000-0002-1336-1994

Funding

2020LZ002 Traditional Chinese Medicine Research Program of Shanghai Municipal Health Commission
6 · The paper itself

Abstract

background and purposeInsulin resistance is associated with clinical outcomes among patients with ischemic stroke. We aimed to investigate the association between metabolic score for insulin resistance (METS-IR) and clinical outcomes in stroke patients treated by intravenous thrombolysis (IVT).

methodsWe recruited participants treated with IVT from a prospective registry including 3 stroke centers. Poor outcome was defined as a modified Rankin scale score ≥ 3 points at 90 days after the index stroke. We performed logistic regression models to investigate the association between METS-IR and the risk of poor outcome. We used the receiver operative characteristic to assess the discriminative ability and the restricted cubic spline to explore the relationship between METS-IR and the poor outcome.

resultsThis study enrolled a total of 1074 patients (median age, 68; 63.8% male). Three hundred sixty (33.5%) patients had poor outcome after IVT. METS-IR was associated with the risk of the poor outcome with the increase of confounding factors in models (odds ratio [OR], 1.078; 95% confidence interval [CI], 1.058-1.099; P < 0.001). The area under the curve for METS-IR for predicting the poor outcome was 0.790 (95% CI, 0.761-0.819). The restricted cubic spline revealed an increasing and non-linear association between METS-IR and the poor outcome (P for non-linearity < 0.001).

conclusionOur study found that METS-IR was associated with an increased risk of poor outcome after IVT. Further studies are warranted to investigate the efficacy of anti-diabetic agents regarding IR on clinical outcomes after IVT.

Indexed as

Brain IschemiaInsulin ResistanceStrokeAdministration, IntravenousAgedFemaleFibrinolytic AgentsHumansLogistic ModelsMaleThrombolytic TherapyTreatment OutcomeFibrinolytic AgentsInsulin resistanceIntravenous thrombolysisIschemic strokeMetabolic score for insulin resistance

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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.