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Record W2184853774

Prophylactic beta-blockade to prevent myocardial infarction perioperatively in high-risk patients who undergo general surgical procedures.

2003· article· en· W2184853774 on OpenAlexaffabout
Rebecca C. Taylor, Giuseppe Pagliarello

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicinePerioperativeMyocardial infarctionCoronary artery diseaseLaparotomySurgeryRandomized controlled trialAdverse effectAnesthesiaInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: The benefit of administering beta-adrenergic blocking agents perioperatively to surgical patients at high risk for myocardial ischemia has been demonstrated in several well-designed randomized controlled trials. These benefits have included a reduction in the incidence of myocardial complications and an improvement in overall survival for patients with evidence of or at risk for coronary artery disease (CAD). We designed a retrospective study at the Ottawa Civic Hospital to investigate the use of beta-blockers in the perioperative period for high-risk general surgery patients who underwent laparotomy and to explore the reasons for failure to prescribe or administer beta-blockers when indicated. METHODS: All 236 general surgery patients over the age of 50 years who underwent laparotomy for major gastrointestinal surgery between Jan. 1, 2001, and Dec. 31, 2001, were assigned a cardiac risk classification using the risk stratification described by Mangano and colleagues. The perioperative prescription and administration of beta-blockers were noted as were the patient's heart rate and blood pressure parameters for the first postoperative week, in-hospital adverse cardiac events and death. RESULTS: Of the 143 patients classified as being at risk for CAD or having definite evidence of CAD, 87 (60.8%) did not receive beta-blockers perioperatively. Of those who did, 43 were previously on beta-blockers and 13 had them ordered preoperatively. Patients with definite CAD were significantly more likely than others to receive beta-blockers perioperatively (p < 0.001), as were patients seen by an anesthesiologist or an internist preoperatively (p < 0.001). Twenty (33%) of the 61 patients who were already taking beta-blockers preoperatively had them inappropriately discontinued postoperatively. Once prescribed by the physician, beta-blockers were administered by the nurses irrespective of nil par os status. The mean heart rate and blood pressure parameters for patients receiving beta-blockers postoperatively was 82 beats/min and 110 mm Hg, respectively, and these values were not significantly different from the mean heart rate of patients not receiving beta-blockers. The number of postoperative cardiac events was significantly higher in patients with definite evidence of CAD, and among this group, the use of beta-blockers was associated with a significant reduction in postoperative cardiac events. This was not true for patients at risk for CAD or patients with no risk of CAD. CONCLUSIONS: A significant proportion (> 60%) of general surgery patients who were identified as having definite evidence of, or being at risk for, CAD were not prescribed beta-blockers preoperatively. More than 30% of patients who were on beta-blockers preoperatively did not have them reordered postoperatively. These results may reflect controversy surrounding the recommendations, miscommunication between surgeons and anesthesiologists and errors in postoperative ordering.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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 designRandomized trial
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

Citations17
Published2003
Admission routes2
Has abstractyes

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