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.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".