Development of a perioperative medicine research agenda: a cross sectional survey
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.
Bibliographic record
Abstract
BACKGROUND: Post-operative complications are a significant source of morbidity and mortality for patients undergoing surgery. However, there is little research in the emerging field of perioperative medicine beyond cardiac risk stratification. We sought to determine the research priorities for perioperative medicine using a cross sectional survey of Canadian and American general internists. METHODS: Surveys were electronically sent to 312 general internists from the Canadian Society of Internal Medicine and 130 internists from the perioperative medicine research interest group within the US based Society of General Internal Medicine. The questionnaire contained thirty research questions and respondents were asked to rate the priority of these questions for future study. RESULTS: The research topics with the highest ratings included: the need for tight control of diabetes mellitus postoperatively and the value of starting aspirin on patients at increased risk for postoperative cardiac events. Research questions evaluating the efficacy and safety of perioperative interventions had higher ratings than questions relating to the prediction of postoperative risk. Questions relating to the yield of preoperative diagnostic tests had the lowest ratings (p < 0.001 for differences across these categories). CONCLUSION: The results of this survey suggest that practicing general internists believe that interventions studies are a priority within perioperative medicine. These findings should help prioritize research in this emerging field.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it