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Record W2904717953 · doi:10.1016/j.bja.2018.10.060

Cardiac vagal dysfunction and myocardial injury after non-cardiac surgery: a planned secondary analysis of the measurement of Exercise Tolerance before surgery study

2018· article· en· W2904717953 on OpenAlexafffund
Tom Abbott, Rupert M. Pearse, Brian H. Cuthbertson, Duminda N. Wijeysundera, Gareth L. Ackland

Bibliographic record

VenueBritish Journal of Anaesthesia · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsToronto General HospitalSt. Michael's HospitalHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersMedical Research CouncilCanadian Institutes of Health ResearchMonash UniversityNational Institute for Health and Care ResearchOntario Ministry of Health and Long-Term CareUniversity of TorontoBritish Heart FoundationNational Institute of Academic AnaesthesiaBritish Journal of AnaesthesiaEdwards LifesciencesAustralian and New Zealand College of AnaesthetistsOntario Ministry of Research, Innovation and ScienceMedtronicHeart and Stroke Foundation of CanadaOntario Ministry of Research and InnovationRoyal College of AnaesthetistsGlaxoSmithKline
KeywordsMedicineInternal medicineCardiologyPerioperativeTroponinSubarachnoid hemorrhageTroponin TProspective cohort studyNatriuretic peptideAnesthesiaMyocardial infarctionHeart failure

Abstract

fetched live from OpenAlex

Background The aetiology of perioperative myocardial injury is poorly understood and not clearly linked to pre-existing cardiovascular disease. We hypothesised that loss of cardioprotective vagal tone [defined by impaired heart rate recovery ≤12 beats min −1 (HRR ≤12) 1 min after cessation of preoperative cardiopulmonary exercise testing] was associated with perioperative myocardial injury. Methods We conducted a pre-defined, secondary analysis of a multi-centre prospective cohort study of preoperative cardiopulmonary exercise testing. Participants were aged ≥40 yr undergoing non-cardiac surgery. The exposure was impaired HRR (HRR≤12). The primary outcome was postoperative myocardial injury, defined by serum troponin concentration within 72 h after surgery. The analysis accounted for established markers of cardiac risk [Revised Cardiac Risk Index (RCRI), N-terminal pro-brain natriuretic peptide (NT pro-BNP)]. Results A total of 1326 participants were included [mean age (standard deviation), 64 (10) yr], of whom 816 (61.5%) were male. HRR≤12 occurred in 548 patients (41.3%). Myocardial injury was more frequent amongst patients with HRR≤12 [85/548 (15.5%) vs HRR>12: 83/778 (10.7%); odds ratio (OR), 1.50 (1.08–2.08); P =0.016, adjusted for RCRI). HRR declined progressively in patients with increasing numbers of RCRI factors. Patients with ≥3 RCRI factors were more likely to have HRR≤12 [26/36 (72.2%) vs 0 factors: 167/419 (39.9%); OR, 3.92 (1.84–8.34); P <0.001]. NT pro-BNP greater than a standard prognostic threshold (>300 pg ml −1 ) was more frequent in patients with HRR≤12 [96/529 (18.1%) vs HRR>12 59/745 (7.9%); OR, 2.58 (1.82–3.64); P <0.001]. Conclusions Impaired HRR is associated with an increased risk of perioperative cardiac injury. These data suggest a mechanistic role for cardiac vagal dysfunction in promoting perioperative myocardial injury.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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 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

Citations31
Published2018
Admission routes2
Has abstractyes

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