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Record W2149731197 · doi:10.1001/jamaneurol.2015.3106

Risks and Benefits Associated With Prestroke Antiplatelet Therapy Among Patients With Acute Ischemic Stroke Treated With Intravenous Tissue Plasminogen Activator

2015· article· en· W2149731197 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJAMA Neurology · 2015
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsMedicineStroke (engine)Internal medicineOdds ratioTissue plasminogen activatorModified Rankin ScaleCardiologyIschemic strokeIschemia

Abstract

fetched live from OpenAlex

IMPORTANCE: Intravenous tissue plasminogen activator (tPA) is known to improve outcomes in ischemic stroke; however, many patients may have been receiving antiplatelet therapy before acute ischemic stroke and could face an increased risk for bleeding when treated with tPA. OBJECTIVE: To assess the risks and benefits associated with prestroke antiplatelet therapy among patients with ischemic stroke who receive intravenous tPA. DESIGN, SETTING, AND PARTICIPANTS: This observational study used data from the American Heart Association and American Stroke Association Get With the Guidelines-Stroke registry, which included 85 072 adult patients with ischemic stroke who received intravenous tPA in 1545 registry hospitals from January 1, 2009, through March 31, 2015. Data were analyzed during the same period. EXPOSURES: Prestroke antiplatelet therapy before tPA administration for acute ischemic stroke. MAIN OUTCOMES AND MEASURES: Symptomatic intracranial hemorrhage (sICH), in-hospital mortality, discharge ambulatory status, and modified Rankin Scale score (range, 0 [no symptoms] to 6 [death]). RESULTS: Of the 85 072 registry patients, 38 844 (45.7%) were receiving antiplatelet therapy before admission; 46 228 patients (54.3%) were not. Patients receiving antiplatelet therapy were older (median [25th-75th percentile] age, 76 [65-84] vs 68 [56-80] years) and had a higher prevalence of cardiovascular risk factors. The unadjusted rate of sICH was higher in patients receiving antiplatelet therapy (5.0% vs 3.7%). After risk adjustment, prior use of antiplatelet agents remained associated with higher odds of sICH compared with no use (adjusted odds ratio [AOR], 1.18 [95% CI, 1.10-1.28]; absolute difference, +0.68% [95% CI, 0.36%-1.01%]; number needed to harm [NNH], 147). Among patients enrolled on October 1, 2012, or later, the highest odds (95% CIs) of sICH were found in 15 116 patients receiving aspirin alone (AOR, 1.19 [1.06- 1.34]; absolute difference [95% CI], +0.68% [0.21%-1.20%]; NNH, 147) and 2397 patients receiving dual antiplatelet treatment of aspirin and clopidogrel (AOR, 1.47 [1.16-1.86]; absolute difference, +1.67% [0.58%-3.00%]; NNH, 60). The risk for in-hospital mortality was similar between those who were and were not receiving antiplatelet therapy after adjustment (8.0% vs 6.6%; AOR, 1.00 [0.94-1.06]; nonsignificant absolute difference, -0.01% [-0.37% to 0.36%]). However, patients receiving antiplatelet therapy had a greater risk-adjusted likelihood of independent ambulation (42.1% vs 46.6%; AOR, 1.13 [1.08-1.17]; absolute difference, +2.23% [1.55%-2.92%]; number needed to treat, 43) and better functional outcomes (modified Rankin Scale score, 0-1) at discharge (24.1% vs 27.8%; AOR, 1.14; 1.07-1.22; absolute difference, +1.99% [0.78%-3.22%]; number needed to treat, 50). CONCLUSIONS AND RELEVANCE: Among patients with an acute ischemic stroke treated with intravenous tPA, those receiving antiplatelet therapy before the stroke had a higher risk for sICH but better functional outcomes than those who were not receiving antiplatelet therapy.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.233
Teacher spread0.214 · 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