Chronic β Blockade Is Associated with a Better Outcome after Elective Noncardiac Surgery than Acute β Blockade
Bibliographic record
Abstract
BACKGROUND: Current guidelines on perioperative care recommend the prophylactic use of β blockers in high-risk patients undergoing noncardiac surgery. However, recent studies show that, in some instances, perioperative β blockade can cause harm. Furthermore, chronic β blockade, titrated to effect before surgery, may be superior to acute perioperative β blockade. The primary objective of this study was to compare major acute cardiac outcomes in patients who underwent surgery with chronic β blocker therapy with those in patients with acute β-blocker therapy. METHODS: Data were collected for 10,691 consecutive patients undergoing elective noncardiac surgery between April 1, 2008, and April 30, 2010. Propensity scores, estimating the probability of receiving a preoperative β blocker, were calculated to match (1:1) the patients with acute and chronic β-blocker therapy. The primary outcome was a composite of myocardial infarction, nonfatal cardiac arrest, and perioperative mortality. The rate of cardiac events was compared in the matched cohorts. RESULTS: A total of 962 patients were chronically treated with a β blocker before surgery; in 436 patients, the β blocker was administrated acutely. Propensity score matching created 301 patient pairs who were well-balanced for major comorbidities, concomitant drug use, and type of surgery. The primary outcome was observed in 9 (3.0%) chronic versus 24 (8.0%) acute β-blocked patients (relative risk, 2.67; 95% CI, 1.27-5.60; P = 0.011). CONCLUSIONS: Acute β blockade, initiated within the first 2 days after surgery, was associated with worse cardiac outcome compared with a matched cohort of patients who underwent surgery on chronic β blockade. These results should be validated in a larger prospective trial.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".