MétaCan
Menu
Back to cohort
Record W3138013799 · doi:10.1177/17474930211006290

Malignant infarction after endovascular treatment: Incidence and prediction

2021· article· en· W3138013799 on OpenAlexaboutno aff
Marie Louise E. Bernsen, Frans Kauw, Jasper M. Martens, Aad van der Lugt, Lonneke S.F. Yo, Marianne AA van Walderveen, Yvo B.W.E.M. Roos, H. Bart van der Worp, Jan Willem Dankbaar, Jeannette Hofmeijer

Bibliographic record

VenueInternational Journal of Stroke · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersBracco ImagingMaastricht Universitair Medisch CentrumUniversiteit MaastrichtLivaNovaStryker
KeywordsMedicineStroke (engine)Logistic regressionReceiver operating characteristicConfidence intervalInfarctionIncidence (geometry)Collateral circulationInternal medicineOcclusionMyocardial infarctionCardiologySurgeryRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Early prediction of malignant infarction may guide treatment decisions. For patients who received endovascular treatment, the risk of malignant infarction is unknown and risk factors are unrevealed. AIMS: The objective of this study is to estimate the incidence of malignant infarction after endovascular treatment in patients with an occlusion of the anterior circulation, to identify independent risk factors, and to establish a model for prediction. METHODS: We analyzed patients who received endovascular treatment for a large vessel occlusion in the anterior circulation within 6.5 h after symptom onset, included in the Dutch MR CLEAN Registry between March 2014 and June 2016. We compared patients with and without malignant infarction. Candidate predictors were incorporated in a multivariable binary logistic regression model. The final prediction model was established using backward elimination. Discrimination and calibration were evaluated with the area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow test. RESULTS: Of 1445 patients, 82 (6%) developed malignant infarction. Independent predictors were lower age, higher National Institutes of Health Stroke Scale (NIHSS), lower alberta stroke program early CT score (ASPECTS), internal carotid artery occlusion, lower collateral score, longer times from onset to groin puncture, and unsuccessful reperfusion. The AUROC of a prediction model combining these features was 0.83 (95% confidence interval (CI): 0.79-0.88) and the Hosmer-Lemeshow test indicated appropriate calibration (P = 0.937). CONCLUSION: The risk of malignant infarction after endovascular treatment started within 6.5 h of stroke onset is approximately 6%. Successful reperfusion decreases the risk. A prediction model combining easily retrievable measures of age, ASPECTS, collateral status, and reperfusion shows good discrimination between patients who will develop malignant infarction and those who will not.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.255
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of StrokeSame topicAcute Ischemic Stroke ManagementFrench-language works237,207