Evidence map›Paper›PMID 37329177›Full record

ArticleAnnals of clinical and translational neurology2023

Nomogram to predict unfavorable outcome of endovascular thrombectomy for large ischemic core.

Nannan Han, Xiaobo Zhang, Yu Zhang, Yu Liu, Yongqin Zhang, Haojun Ma, Hanming Ge, Shilin Li, Xiao Zhang, Xudong Yan and 7 more

Abstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Radiomics to predict PNI in ESCC.Abdominal radiology (New York) · 2025
    Article
  7. Article
  8. Article
  9. Observational
  10. Application of radiomics in ischemic stroke.The Journal of international medical research · 2024
    Review
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.

Nannan HanDepartment of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.ORCID 0000-0002-0239-9313
Xiaobo ZhangThe College of Life Sciences, Northwest University, Xi'an, China.
Yu ZhangThe College of Life Sciences, Northwest University, Xi'an, China.
Yu LiuSchool of Information Science and Technology, Northwest University, Xi'an, China.ORCID 0000-0001-8148-8519
Yongqin ZhangSchool of Information Science and Technology, Northwest University, Xi'an, China.
Haojun MaDepartment of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Hanming GeDepartment of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Shilin LiDepartment of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Xiao ZhangXi'an Key Laboratory of Cardiovascular and Cerebrovascular Diseases, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Xudong YanDepartment of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Tengfei LiDepartment of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Bin GaoDepartment of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Chengxue DuDepartment of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Xinchao JiDepartment of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Wenzhen ShiXi'an Key Laboratory of Cardiovascular and Cerebrovascular Diseases, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Ye TianXi'an Key Laboratory of Cardiovascular and Cerebrovascular Diseases, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Mingze ChangDepartment of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe prognosis for patients presenting with a large ischemic core (LIC) following endovascular thrombectomy is relatively poor. This study aimed to construct and validate a nomogram for predicting 3-month unfavorable outcome in patients with anterior circulation occlusion-related LIC who underwent endovascular thrombectomy.

methodsA retrospective training cohort and a prospective validation cohort of patients with a large ischemic core were studied. The diffusion weighted imaging related radiomic features and pre-thrombectomy clinical features were collected. After the selection of relevant features, a nomogram predicting modified Rankin Scale score of 3-6 as an unfavorable outcome was established. The discriminatory value of the nomogram was evaluated with a receiver operating characteristic curve.

resultsA total of 140 patients (mean age 66.3 ± 13.4 years, 35% female) were included in this study, consisting of a training cohort (n = 95) and a validation cohort (n = 45). The percentage of patients with an mRS scores of 0-2 was 30%, 0-3 was 40.7%, and 32.9% were dead. Age, National Institute of Health Stroke Scale (NIHSS) score, and two radiomic features, Maximum2DDiameterColumn and Maximum2DDiameterSlice, were identified as factors associated with unfavorable outcome in the nomogram. The nomogram demonstrated an area under the curve of 0.892 (95% confidence interval [CI], 0.812-0.947) in the training dataset and 0.872 (95% CI, 0.739-0.953) in the validation dataset.

interpretationThis nomogram, which includes age, NIHSS score, Maximum2DDiameterColumn, and Maximum2DDiameterSlice, may predict the risk of unfavorable outcome in patients with LIC caused by anterior circulation occlusion.

Indexed as

Diffusion Magnetic Resonance ImagingNomogramsAgedFemaleHumansMaleMiddle AgedRetrospective StudiesROC CurveThrombectomy

Identifiers

PMID37329177
PMCPMC10424651

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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.