Evidence map›Paper›PMID 24612485›Full record

ArticleCNS neuroscience & therapeutics2014

Risk assessment of deep-vein thrombosis after acute stroke: a prospective study using clinical factors.

Li-Ping Liu, Hua-Guang Zheng, David Z Wang, Yi-Long Wang, Mohammed Hussain, Hai-Xin Sun, An-Xin Wang, Xing-Quan Zhao, Ke-Hui Dong, Chun-Xue Wang and 3 more

Open access · bronzeAbstract readMulticenter StudyValidation Study
In one paragraph

Article in CNS neuroscience & therapeutics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 4 pooled it
1.1field-weighted citation impact, top 20% 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

32 citing papers in PubMed, 4 syntheses or guidelines pooled it, 59 citations in OpenAlex.

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  10. A composite risk assessment model for venous thromboembolism.Journal of vascular surgery. Venous and lymphatic disorders · 2025
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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

13 authors at 4 institutions in 2 countries.

Li-Ping LiuDepartment of Neurology, Beijing Tiantan Hospital affiliated Capital Medical University, Beijing, China.
Hua-Guang Zheng
David Z Wang
Yi-Long Wang
Mohammed Hussain
Hai-Xin Sun
An-Xin Wang
Xing-Quan Zhao
Ke-Hui Dong
Chun-Xue Wang
Wen He
Bin Ning
Yong-Jun Wang
Capital Medical University · CNBeijing Tian Tan Hospital · CNUniversity of Illinois Chicago · USWayne State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsDeep-vein thrombosis (DVT) represents a serious complication in acute stroke patients with pulmonary embolus (PE) as a potential outcome. Prediction of DVT may help with formulating a proper prevention strategy. To assess of the risk of deep venous thrombosis (DVT) in acute stroke patients, we developed and validated a clinical score in a cohort study.

methodsIncidence of Deep Venous Thrombosis after Acute Stroke in China (INVENT-China) is a multicenter prospective cohort study. The potential predictive variables for DVT at baseline were collected, and the presence of DVT was evaluated using ultrasonography on the 14 ± 3 days. Data were randomly assigned to either a training data set or a test data set. Multivariate logistic regression analysis was used to develop risk scores to predict DVT in the training data set and the area under the receiver operating characteristic curve to validate the score in the test data set.

resultsFrom 2006-2007, 862 hospital-based acute stroke patients were enrolled in China. The overall incidence of DVT after acute stroke within two weeks was 12.4% (95%CI 10.3-14.7%). A seven-point score derived in the training data set (age [≥65 years = 1], sex [female gender = 1]), obesity [BMI ≥ 25 kg/m(2) = 1], active cancer [yes = 2], stroke subtype [cerebral hemorraghe = 1], muscle weakness [≥2 on Lower limb NIHSS score = 1] was highly predictive of 14-day risk of DVT(c statistic = 0.70, 95% CI, 0.64-0.76, P < 0.001), in the overall study population(c statistic = 0.65, 95% CI 0.59-0.70, P < 0.001).

conclusionsThis clinical score may help identify acute stroke patients with high risk of DVT. In addition, it also serves as a platform to develop further models of DVT prediction in stroke patients based on clinical factors.

Indexed as

AgedChinaFemaleHumansIncidenceLogistic ModelsMaleMiddle AgedMultivariate AnalysisProspective StudiesRiskRisk AssessmentROC CurveStrokeUltrasonographyVenous ThrombosisAcute strokeclinical prediction scaledeep venous thrombosisprophylaxis

Identifiers

PMID24612485
PMCPMC6493054
OpenAlexW2092595948

What OpenQuestion holds

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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.