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Record W2002241364 · doi:10.15273/dmj.vol32no1.4258

Perioperative Pain Management in the Cardiac Patient

2004· article· en· W2002241364 on OpenAlexvenueno aff
Teneille Gofton

Bibliographic record

VenueDalhousie Medical Journal · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePerioperativeNociceptorAnesthesiaCardiac surgeryIntensive care medicineCardiologyNociceptionInternal medicine

Abstract

fetched live from OpenAlex

Pain is the perception of an unpleasant sensation to warn the body of tissue injury. Nociceptors send stimuli to the central nervous system via neurons that enter the spinal cord via the dorsal horn. The signal is then processed, integrated, and relayed to higher centres for interpretation. Surgery stimulates pain pathways due to the tissue injury that it creates and in this way a neuroendocrine cascade is set into action as a protective mechanism by the body. Cardiac patients and patients with cardiac risk factors pose a special risk when undergoing surgery. They exist in a state of altered vascular responsiveness due to endothelial injury and chronic inflammation of the vasculature. The physiologic response to pain may put cardiac patients at risk for cardiac events in the perioperative period. More recent methods in pain control, such as epidural anaesthesia, can be used to decrease the risk of cardiac events in these patients. Pain transmission and analgesia will be explored in this paper. Furthermore, the current American College of Cardiology and American Heart Association Task Force guidelines on the management of cardiac patients undergoing noncardiac surgery as well as the literature published since the release of these guidelinte will be discussed.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.001
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 head0.009
GPT teacher head0.259
Teacher spread0.251 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations0
Published2004
Admission routes1
Has abstractyes

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