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Record W3136775577 · doi:10.1161/str.52.suppl_1.p17

Abstract P17: Outcomes After Thrombolysis for Ischemic Stroke in Costa Rica Compare Favorably With International Cohorts

2021· article· en· W3136775577 on OpenAlexaboutno aff
Pitchaiah Mandava, Gabriel Torrealba‐Acosta, Miguel A. Barboza, Huberth Fernández-Morales, Muhammad Qasim, Paul Litvak, Travis Rothlisberger, Georgios Tsivgoulis, Andrei V. Alexandrov, Thomas A. Kent

Bibliographic record

VenueStroke · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineThrombolysisStroke (engine)Randomized controlled trialIntracerebral hemorrhageIschemic strokeInternal medicineIschemiaMyocardial infarctionSubarachnoid hemorrhage

Abstract

fetched live from OpenAlex

Background: More than 70% of strokes occur in resource-poor countries. Outcomes are often not well documented. rt-PA for acute ischemic stroke was approved in 2012 for use in Costa Rica (CR). A hub and spoke model was initiated and a dataset established, the CR Stroke Registry Program (CRSRP) for conditional- and post-approval monitoring. Here, we compared CRSRP rt-PA outcomes to similarly treated subjects from the 1995 NINDS rt-PA trial and the 2019 CLOTBUST-ER control arm. Methods: Subjects were matched using a published pairing methodology and day 7-10/discharge modified Rankin Score (mRS), symptomatic intracerebral hemorrhages (SICH) and early mortality compared. A mortality model was generated from 15 randomized controlled trials (RCTs) and outcomes compared at similar baselines. SICH rates were compared with other cohorts: Get With The Guidelines (GWTG), a combined international IV thrombolysis trial pool, and 2 Ibero-American populations. Results: Of 424 CRSRP patients, 284 receiving rt-PA under 3 hrs were matched with 308 NINDS subjects. 131 non-diabetic CRSRP subjects, treated within 4.5 hrs, NIHSS 10 - 24 and Alberta Stroke Program Early CT Score (ASPECTS)>7, were matched with 300 CLOTBUST-ER subjects. Percent achieving either mRS 0-1 or 0-2 did not differ between CRSRP and either NINDS or CLOTBUST-ER (mRS 0-1: CRSRP:33.9% vs NINDS:33.6%; CRSRP:23.8% vs CLOTBUST-ER:27.0%, all p>=.05 / mRS 0-2: CRSRP:40.0% vs NINDS:41.4%; CRSRP:31.1% vs CLOTBUST-ER:36.1%, all p=>.05). Mortality was higher for CRSRP vs CLOTBUST-ER (6.6% vs 0.8%; p=0.05) but not vs NINDS (6.8% vs 4.3%; p=0.3). A predictive model (R 2 =0.39) showed neither cohort exceeded expected pooled mortality, with CLOTBUST-ER the lowest mortality. SICH rate was higher in CRSRP vs CLOTBUST-ER (7.3% vs 0.0% p=0.008) but not vs NINDS (5.7% vs 6.8% p=0.7)). SICH rates were not higher when compared with 4 international cohorts. Conclusion: Functional outcomes of Costa Rican patients receiving rt-PA compared favorably with 2 RCTs (NINDS and CLOTBUST-ER). SICH and mortality were higher than CLOTBUST-ER, although both were within expected range compared to other international cohorts. Systems of care development in order to further lower SICH and participate in the endovascular era are underway.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.279
Teacher spread0.265 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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