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Record W2138987921 · doi:10.1177/1054773812459753

Weight and Patients’ Decision to Undergo Cardiac Surgery

2012· article· en· W2138987921 on OpenAlex
Kathryn King‐Shier, Pamela LeBlanc, Charles Mather, Sarah Sandham, Cydnee Seneviratne, Andrew Maitland

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueClinical Nursing Research · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsMedicineIntensive care medicine

Abstract

fetched live from OpenAlex

Obese patients are less likely to have cardiac surgery than normal weight patients. This could be due to physician or patient decision-making. We undertook a qualitative descriptive study to explore the influence of obesity on patients' decision-making to have cardiac surgery. Forty-seven people referred for coronary artery bypass graft (CABG) surgery were theoretically sampled. Twelve people had declined cardiac surgery. Participants underwent in-depth interviews aimed at exploring their decision-making process. Data were analyzed using conventional content analysis. Though patients' weight did not play a role in their decision, their relationship with their cardiologist/surgeon, the rapidity and orchestration of the diagnosis and treatment, appraisal of risks and benefits, previous experience with other illness or others who had cardiac surgery, and openness to other alternatives had an impact. It is possible that there is a lack of comfort or acknowledgment by all parties in discussing the influence of weight on CABG surgery risks.

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.

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)0.007
metaresearch head score (Gemma)0.008
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 score0.249
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.137
GPT teacher head0.485
Teacher spread0.348 · 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