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Record W175403714 · doi:10.1161/str.43.suppl_1.a58

Abstract 58: The Iscore Predicts Efficacy Of Thrombolytic Therapy For Acute Ischemic Stroke

2012· article· en· W175403714 on OpenAlexaffabout
Gustavo Saposnik, Jiming Fang, Moira K. Kapral, Jack V. Tu, Muhammad Mamdani, Peter C. Austin, Claiborn S Johnston

Bibliographic record

VenueStroke · 2012
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of TorontoInstitute for Clinical Evaluative SciencesSt. Michael's Hospital
Fundersnot available
KeywordsMedicineThrombolysisStroke (engine)Internal medicinePropensity score matchingFibrinolytic agentTissue plasminogen activatorMyocardial infarction

Abstract

fetched live from OpenAlex

Background: The iScore is a validated tool developed to estimate the risk of death and functional outcomes early after an acute ischemic stroke. It includes demographics, stroke severity and subtype, vascular risk factors, cancer, renal failure, and pre-admission functional status. Limited information is available to predict the clinical response after intravenous thrombolytic therapy (tPA). Objective: To determine the ability of the iScore to predict the clinical response and risk of hemorrhagic transformation after tPA. Methods: We applied the iScore ( www.sorcan.ca/iscore ) to patients presenting with an acute ischemic stroke at 11 stroke centres in Ontario, Canada, between 2003 and 2008, identified from the Registry of the Canadian Stroke Network (RCSN). We compared outcomes between patients receiving and not receiving tPA adjusting for differences in baseline characteristics through matching by propensity scores. Three groups were defined a priori as per the iScore (low risk 180). Outcome Measures: Poor outcome, the primary outcome measure, was defined as disability at discharge or death at 30 days. Secondary outcomes included disability at discharge, neurological deterioration and intracranial hemorrhage (any type and symptomatic). Results: Among 12,686 patients with an acute ischemic stroke, 1696 (13.4%) received intravenous thrombolysis. Overall, 589 tPA patients were matched with 589 non-tPA patients (low iScore risk), 682 tPA were matched with 682 non-tPA patients (medium iScore risk) and 419 tPA patients were matched with 419 non-tPA patients (high iScore risk). There was good matching in all three groups. Higher iScore was associated with poor functional outcome in both the tPA and non-tPA groups (p<0.001). Among those with low and medium iScore risk, tPA use was associated with lower risk of poor outcome (Low iScore RR 0.74; 95%CI 0.67-0.84; medium iScore RR 0.88; 95%CI 0.84-0.93). There was no difference in clinical outcomes between matched patients receiving and not receiving tPA in the highest iScore group (RR 0.97; 95%CI 0.94-1.01). Similar results were observed for disability at discharge and length of stay. The incident risk of neurological deterioration and hemorrhagic transformation (any or symptomatic) increased with the iScore risk ( Figure ). Conclusion: The iScore appears to predict clinical response and risk of hemorrhagic complications after tPA for an acute ischemic stroke. Patients with high iScores may not benefit from tPA and have higher risk of hemorrhagic transformation, though this finding should be validated independently (underway) before clinical use.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.305
Teacher spread0.280 · 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

Citations1
Published2012
Admission routes2
Has abstractyes

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