Evidence map›Paper›PMID 33911999›Full record

ArticleFrontiers in neuroscience2021

Baseline Cerebral Ischemic Core Quantified by Different Automatic Software and Its Predictive Value for Clinical Outcome.

Zhang Shi, Jing Li, Ming Zhao, Minmin Zhang, Tiegong Wang, Luguang Chen, Qi Liu, He Wang, Jianping Lu, Xihai Zhao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

20 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Observational
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Deep learning-based identification of acute ischemic core and deficit from non-contrast CT and CTA.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021
    Article
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

10 authors at 4 institutions in 1 country.

Zhang ShiDepartment of Radiology, Changhai Hospital, Naval Medical University, Shanghai, China.
Jing LiDepartment of Radiology, Changhai Hospital, Naval Medical University, Shanghai, China.
Ming ZhaoDepartment of Neurology, The 983th Hospital of Joint Logistics Support Forces of Chinese PLA, Tianjin, China.
Minmin ZhangDepartment of Neurology, Changhai Hospital, Naval Medical University, Shanghai, China.
Tiegong WangDepartment of Radiology, Changhai Hospital, Naval Medical University, Shanghai, China.
Luguang ChenDepartment of Radiology, Changhai Hospital, Naval Medical University, Shanghai, China.
Qi LiuDepartment of Radiology, Changhai Hospital, Naval Medical University, Shanghai, China.
He WangInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Jianping LuDepartment of Radiology, Changhai Hospital, Naval Medical University, Shanghai, China.
Xihai ZhaoDepartment of Biomedical Engineering, Center for Biomedical Imaging Research, Tsinghua University School of Medicine, Beijing, China.
Second Military Medical University · CNChanghai Hospital · CNFudan University · CNTsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aims to investigate the agreement of three software packages in measuring baseline ischemic core volume (ICV) and penumbra volume (PV), and determine their predictive values for unfavorable clinical outcome in patients with endovascular thrombectomy (EVT).

methodsPatients with acute ischemic stroke who underwent computed tomographic perfusion (CTP) were recruited. Baseline CTP measurements including ICV and PV were calculated by three software packages of IntelliSpace Portal (ISP), Rapid Processing of Perfusion and Diffusion (RAPID), and fast-processing of ischemic stroke (F-STROKE). All patients received EVT, and the modified Rankin scale (mRS) at 90 days after EVT was assessed to determine the clinical outcomes (favorable: mRS = 0-2; unfavorable: mRS = 3-6). The agreement of CTP measurements among three software packages was determined using intraclass correlation coefficient (ICC). The associations between CTP measurements and unfavorable clinical outcome were analyzed using logistic regression. Receiver operating characteristic curves were conducted to calculate the area under the curve (AUC) of CTP measurements in predicting unfavorable clinical outcome.

resultsOf 223 recruited patients (68.2 ± 11.3 years old; 145 males), 17.0% had unfavorable clinical outcome after EVT. Excellent agreement between F-STROKE and RAPID was found in measuring ICV (ICC 0.965; 95% CI 0.956-0.973) and PV (ICC 0.966; 95% CI 0.956-0.973). ICVs measured by three software packages were significantly associated with unfavorable clinical outcome before (odds ratios 1.012-1.018, all

conclusionsThe software of F-STROKE has excellent agreement with the widely used analysis tool of RAPID in measuring ICV and PV. The ischemic core volume measured by both F-STROKE and RAPID is a stronger predictor for unfavorable clinical outcome after EVT compared to ISP.

Indexed as

computed tomographyischemic strokeoutcomepenumbraperfusion imagingsoftware

Identifiers

PMID33911999
PMCPMC8072147
OpenAlexW3156786478

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.