Evidence map›Paper›PMID 34744465›Full record

ArticleRisk management and healthcare policy2021

Nomogram to Predict the Number of Thrombectomy Device Passes for Acute Ischemic Stroke with Endovascular Thrombectomy.

Shijie Yang, Kaixuan Zhao, Huan Xi, Zaixing Xiao, Wei Li, Yichuan Zhang, Zhiqiang Fan, Changqing Li, Erqing Chai

Open access · goldAbstract read
In one paragraph

Article in Risk management and healthcare policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

9 authors at 2 institutions in 1 country.

Shijie YangThe First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Gansu University of Chinese Medicine, Lanzhou, Gansu, People's Republic of China.
Kaixuan ZhaoClinical Medical College, Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
Huan XiThe First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Gansu University of Chinese Medicine, Lanzhou, Gansu, People's Republic of China.
Zaixing XiaoThe First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Gansu University of Chinese Medicine, Lanzhou, Gansu, People's Republic of China.
Wei LiThe First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Gansu University of Chinese Medicine, Lanzhou, Gansu, People's Republic of China.
Yichuan ZhangClinical Medical College, Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
Zhiqiang FanThe First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Gansu University of Chinese Medicine, Lanzhou, Gansu, People's Republic of China.
Changqing LiCerebrovascular Disease Center, Gansu Provincial Hospital, Lanzhou, Gansu, People's Republic of China.
Erqing ChaiCerebrovascular Disease Center, Gansu Provincial Hospital, Lanzhou, Gansu, People's Republic of China.
Gansu Provincial Hospital · CNNingxia Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to determine the risk factors associated with the number of thrombectomy device passes and establish a nomogram for predicting the number of device pass attempts in patients with successful endovascular thrombectomy (EVT).

methodsWe enrolled patients from a signal comprehensive stroke center (CSC) who underwent EVT because of large vessel occlusion stroke. Multivariate logistic regression analysis was used to develop the best-fit nomogram for predicting the number of thrombectomy device passes. The discrimination and calibration of the nomogram were estimated using the area under the receiver operating characteristic curve (AUC-ROC) and a calibration plot with a bootstrap of 1000 resamples. A decision curve analysis (DCA) was used to measure the availability and effect of this predictive tool.

resultsIn total, 130 patients (mean age 64.9 ± 11.1 years; 83 males) were included in the final analysis. Age (odds ratio [OR], 1.085; 95% confidence interval [CI], 1.005-1.172;

conclusionThe nomogram comprised age, baseline ASPECTS score, and homocysteine level, can predict a device pass number >3 in acute ischemic stroke (AIS) patients who are undergoing EVT.

Indexed as

acute ischemic strokeendovascular thrombectomynomogramstentriever

Identifiers

PMID34744465
PMCPMC8565981
OpenAlexW3208351334

What OpenQuestion holds

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LicenceCC BY-NC
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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.