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Record W2089212627 · doi:10.1001/jama.2014.9143

Perioperative Atrial Fibrillation and the Long-term Risk of Ischemic Stroke

2014· article· en· W2089212627 on OpenAlex
Gino Gialdini, Katherine Nearing, Prashant D. Bhave, Ubaldo Bonuccelli, Costantino Iadecola, Jeff S. Healey, Hooman Kamel

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJAMA · 2014
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsPopulation Health Research InstituteMcMaster University
FundersNational Institute of Neurological Disorders and StrokeBoston Scientific CorporationGenentechHeart and Stroke Foundation of CanadaBristol-Myers Squibb
KeywordsMedicineAtrial fibrillationPerioperativeStroke (engine)Internal medicineCardiologyRetrospective cohort studyCardiac surgeryEmergency medicineAnesthesia

Abstract

fetched live from OpenAlex

IMPORTANCE: Clinically apparent atrial fibrillation increases the risk of ischemic stroke. In contrast, perioperative atrial fibrillation may be viewed as a transient response to physiological stress, and the long-term risk of stroke after perioperative atrial fibrillation is unclear. OBJECTIVE: To examine the association between perioperative atrial fibrillation and the long-term risk of stroke. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study using administrative claims data on patients hospitalized for surgery (as defined by surgical diagnosis related group codes), and discharged alive and free of documented cerebrovascular disease or preexisting atrial fibrillation from nonfederal California acute care hospitals between 2007 and 2011. Patients undergoing cardiac vs other types of surgery were analyzed separately. MAIN OUTCOMES AND MEASURES: Previously validated diagnosis codes were used to identify ischemic strokes after discharge from the index hospitalization for surgery. The primary predictor variable was atrial fibrillation newly diagnosed during the index hospitalization, as defined by previously validated present-on-admission codes. Patients were censored at postdischarge emergency department encounters or hospitalizations with a recorded diagnosis of atrial fibrillation. RESULTS: Of 1,729,360 eligible patients, 24,711 (1.43%; 95% CI, 1.41%-1.45%) had new-onset perioperative atrial fibrillation during the index hospitalization and 13,952 (0.81%; 95% CI, 0.79%-0.82%) experienced a stroke after discharge. At 1 year after hospitalization for cardiac surgery, cumulative rates of stroke were 0.99% (95% CI, 0.81%-1.20%) in those with perioperative atrial fibrillation and 0.83% (95% CI, 0.76%-0.91%) in those without atrial fibrillation. At 1 year after noncardiac surgery, cumulative rates of stroke were 1.47% (95% CI, 1.24%-1.75%) in those with perioperative atrial fibrillation and 0.36% (95% CI, 0.35%-0.37%) in those without atrial fibrillation. In a Cox proportional hazards analysis accounting for potential confounders, perioperative atrial fibrillation was associated with subsequent stroke both after cardiac surgery (hazard ratio, 1.3; 95% CI, 1.1-1.6) and noncardiac surgery (hazard ratio, 2.0; 95% CI, 1.7-2.3). The association was significantly stronger for perioperative atrial fibrillation after noncardiac vs cardiac surgery (P < .001 for interaction). CONCLUSIONS AND RELEVANCE: Among patients hospitalized for surgery, perioperative atrial fibrillation was associated with an increased long-term risk of ischemic stroke, especially following noncardiac surgery.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.044
Threshold uncertainty score0.159

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.293
Teacher spread0.272 · 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