Outcomes and Processes of Care Related to Preoperative Medical Consultation
Bibliographic record
Abstract
BACKGROUND: Preoperative consultations by internal medicine physicians facilitate documentation of comorbid disease, optimization of medical conditions, risk stratification, and initiation of interventions intended to reduce risk. Nonetheless, the impact of these consultations, which may be performed by general internists or specialists, on outcomes is unclear. METHODS: We used population-based administrative databases to conduct a cohort study of patients 40 years or older who underwent major elective noncardiac surgery in Ontario, Canada, between 1994 and 2004. Propensity scores were used to assemble a matched-pairs cohort that reduced differences between patients who did and did not undergo preoperative consultation by general internists or specialists. The association of consultation with mortality and hospital stay was determined within this matched cohort. As a sensitivity analysis, we evaluated the association of consultation with an outcome for which no difference would be expected: postoperative wound infection. RESULTS: Of 269,866 patients in the cohort, 38.8% (n=104,695) underwent consultation. Within the matched cohort (n=191,852), consultation was associated with increased 30-day mortality (relative risk [RR], 1.16; 95% confidence interval [CI], 1.07-1.25; number needed to harm, 516), 1-year mortality (1.08; 1.04-1.12; number needed to harm, 227), mean hospital stay (difference, 0.67 days; 0.59-0.76), preoperative testing, and preoperative pharmacologic interventions. Notably, consultation was not associated with any difference in postoperative wound infections (RR, 0.98; 95% CI, 0.95-1.02). These findings were stable across subgroups as well as sensitivity analyses that tested for unmeasured confounding. CONCLUSIONS: Medical consultation before major elective noncardiac surgery is associated with increased mortality and hospital stay, as well as increases in preoperative pharmacologic interventions and testing. These findings highlight the need to better understand mechanisms by which consultation influences outcomes and to identify efficacious interventions to decrease perioperative risk.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".