In one paragraphArticle in Journal of the American Heart Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
12 authors.
Yingjian PeiDepartment of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.ORCID 0009-0008-0648-0013 Guitao ZhangDepartment of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.ORCID 0000-0003-0337-705X Wenbo LiDepartment of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Yao FengDepartment of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.ORCID 0000-0001-7923-8158 Nan LiDepartment of Neurology WuAn First People's Hospital Handan Hebei Province China.
Na ZhaoDepartment of Radiology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Yajun MaDepartment of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Xinmin LiuDepartment of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.ORCID 0000-0001-5497-8491 Qilin ZhouDepartment of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.ORCID 0000-0003-4418-9290 Fei XuDepartment of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.ORCID 0000-0003-4211-6338 Yinghua ZhouDepartment of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.ORCID 0009-0000-7215-3987 Shujuan LiDepartment of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.ORCID 0000-0003-4740-9615 Funding
No grant is acknowledged in the PubMed record.
6 · The paper itselfAbstract
backgroundPostoperative acute ischemic stroke remains a critical complication of coronary artery bypass grafting. This study aimed to develop a novel Total Cerebral Atherosclerosis Burden (TCAB) score for predicting the risk of AIS post-coronary artery bypass grafting.
methodsA prospective cohort of patients undergoing coronary artery bypass grafting was enrolled. The TCAB score was calculated by summing stenosis severity grades (0: <50%, 1: 50-69%, 2: 70-99%, 3: 100%) across all intracranial and extracranial artery segments. Primary outcome was in-hospital ischemic stroke. Multivariable logistic regression models adjusted for key clinical covariates were used to evaluate the association between TCAB and clinical outcomes.
resultsAmong 909 included patients, the mean TCAB score was significantly higher in patients with in-hospital ischemic stroke compared with those without (8 versus 2,
conclusionsThe TCAB score, enhanced by machine learning, effectively predicted in-hospital ischemic stroke, 1-year ischemic stroke, and 1-year major adverse cardiovascular and cerebrovascular events post-coronary artery bypass grafting. It offers a practical tool for guiding preoperative revascularization and intraoperative embolic protection.
Indexed as
Coronary Artery BypassCoronary Artery DiseaseIntracranial ArteriosclerosisIschemic StrokeMachine LearningPostoperative ComplicationsAgedFemaleHumansMaleMiddle AgedPredictive Learning ModelsPredictive Value of TestsProspective StudiesRisk AssessmentRisk Factorsacute ischemic strokeatherosclerotic burdencoronary artery bypass graftingmachine learningrisk stratification
Identifiers
PMID41778551
PMCPMC13055656
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