Evidence map›Paper›PMID 36362595›Full record

ArticleJournal of clinical medicine2022

The Gupta Perioperative Risk for Myocardial Infarct or Cardiac Arrest (MICA) Calculator as an Intraoperative Neurologic Deficit Predictor in Carotid Endarterectomy.

Juliana Pereira-Macedo, Beatriz Lopes-Fernandes, Luís Duarte-Gamas, António Pereira-Neves, Joana Mourão, Ahmed Khairy, José Paulo Andrade, Ana Marreiros, João Rocha-Neves

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2022. 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
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

2 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Juliana Pereira-MacedoDepartment of General Surgery, Hospital Centre of Médio Ave, 4760-124 Vila Nova de Famalicão, Portugal.ORCID 0000-0001-9271-0277
Beatriz Lopes-FernandesFaculty of Medicine and Biomedical Sciences, University of Algarve, ABC, Algarve Biomedical Centre, 8005-139 Faro, Portugal.ORCID 0000-0002-9632-3992
Luís Duarte-GamasDepartment of Angiology and Vascular Surgery, University Hospital Centre of São João, 4200-319 Porto, Portugal.
António Pereira-NevesDepartment of Angiology and Vascular Surgery, University Hospital Centre of São João, 4200-319 Porto, Portugal.
Joana MourãoDepartment of Anesthesiology, University Hospital Centre of São João, 4200-319 Porto, Portugal.
Ahmed KhairyDepartment of Vascular and Endovascular Surgery, Assiut University Hospital, Assiut University, Assiut 71515, Egypt.ORCID 0000-0002-1849-9431
José Paulo AndradeCINTESIS@RISE, Faculty of Medicine, University of Porto, 4200-450 Porto, Portugal.ORCID 0000-0003-2585-200X
Ana MarreirosFaculty of Medicine and Biomedical Sciences, University of Algarve, ABC, Algarve Biomedical Centre, 8005-139 Faro, Portugal.ORCID 0000-0001-9410-4772
João Rocha-NevesDepartment of Angiology and Vascular Surgery, University Hospital Centre of São João, 4200-319 Porto, Portugal.ORCID 0000-0002-2656-8935
Universidade do Porto · PTAlgarve Biomedical Center · PTAssiut University · EG

Funding

National Funds through FCT-Fundação para a Ciência e a Tecnologia, I.P., within CINTESIS, R&D Unit UIDB/4255/2020the project RISE, Associated Laboratory LA/P/0053/2020
6 · The paper itself

Abstract

backgroundPatients undergoing carotid endarterectomy (CEA) may experiment intraoperative neurologic deficits (IND) during carotid cross-clamping. This work aimed to assess the impact of the Gupta Perioperative Myocardial Infarct or Cardiac Arrest (MICA) risk calculator in the IND.

methodsFrom January 2012 to April 2021, patients undergoing CEA with regional anaesthesia for carotid stenosis with IND and consecutively control operated patients without IND were selected. A regressive predictive model was created, and a receiver operating characteristic (ROC) curve was applied for comparison. A multivariable dependence analysis was conducted using a classification and regression tree (CRT) algorithm.

resultsA total of 97 out of 194 included patients developed IND. Obesity showed aOR = 4.01 (95% CI: 1.66-9.67) and MICA score aOR = 1.21 (1.03-1.43). Higher contralateral stenosis showed aOR = 1.29 (1.08-1.53). The AUROC curve was 0.656. The CRT algorithm differentiated obese patients with a MICA score ≥ 8. Regarding non-obese patients, the model identified the presence of contralateral stenosis ≥ 55% with a MICA ≥ 10.

conclusionMICA score might play an additional role in stratifying patients for IND in CEA. Obesity was determined as the best discrimination factor, followed by a score ≥ 8. A higher ipsilateral stenosis degree is suggested to have a part in avoiding procedure-related IND. Larger studies might validate the benefit of MICA score regarding the risk of IND.

Indexed as

atherosclerosiscarotid endarterectomycarotid stenosismajor adverse cardiovascular eventsMICA scoreperioperative strokesurvival analysis

Identifiers

PMID36362595
PMCPMC9653563
OpenAlexW4307944294

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Registered trials

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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.