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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 OpenAlexafffund
Gino Gialdini, Katherine Nearing, Prashant D. Bhave, Ubaldo Bonuccelli, Costantino Iadecola, Jeff S. Healey, Hooman Kamel

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.

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)0.005
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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

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

Citations350
Published2014
Admission routes2
Has abstractyes

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