Association of Preoperative Medical Consultation With Reduction in Adverse Postoperative Outcomes and Use of Processes of Care Among Residents of Ontario, Canada
Bibliographic record
Abstract
Importance: It is uncertain whether preoperative medical consultation reduces adverse postoperative clinical outcomes. Objective: To investigate the association of preoperative medical consultation with reduction in adverse postoperative outcomes and use of processes of care. Design, Setting, and Participants: This was a retrospective cohort study using linked administrative databases from an independent research institute housing routinely collected health data for Ontario's 14 million residents, including sociodemographic features, physician characteristics and services, and receipt of inpatient and outpatient care. The study sample included Ontario residents aged 40 years or older who underwent their first qualifying intermediate- to high-risk noncardiac operation. Propensity score matching was used to adjust for differences between patients who did and did not undergo preoperative medical consultation with discharge dates between April 1, 2005, and March 31, 2018. The data were analyzed from December 20, 2021, to May 15, 2022. Exposures: Receipt of preoperative medical consultation in the 4 months preceding the index surgery. Main Outcomes and Measures: The primary outcome was 30-day all-cause postoperative mortality. Secondary outcomes included 1-year mortality, inpatient myocardial infarction and stroke, in-hospital mechanical ventilation, length of stay, and 30-day health system costs. Results: Of the total 530 473 individuals (mean [SD] age, 67.1 [10.6] years; 278 903 [52.6%] female) included in the study, 186 299 (35.1%) received preoperative medical consultation. Propensity score matching resulted in 179 809 well-matched pairs (67.8% of the full cohort). The 30-day mortality rate was 0.9% (n = 1534) in the consultation group and 0.7% (n = 1299) in the control group (odds ratio [OR], 1.19; 95% CI, 1.11-1.29). The ORs for 1 year mortality (OR, 1.15; 95% CI, 1.11-1.19), inpatient stroke (OR, 1.21; 95% CI, 1.06-1.37), in-hospital mechanical ventilation (OR, 1.38; 95% CI, 1.31-1.45), and 30-day emergency department visits (OR, 1.07; 95% CI, 1.05-1.09) were higher in the consultation group; however, the rates of inpatient myocardial infarction did not differ. The lengths of stay in acute care were a mean (SD) 6.0 (9.3) days in the consultation group and 5.6 (10.0) days in the control group (difference, 0.4 [95% CI, 0.3-0.5] days), and the median (IQR) total 30-day health system cost was CAD $317 ($229-$959) (US $235 [$170-$711]) higher in the consultation group. Preoperative medical consultation was associated with increased use of preoperative echocardiography (OR, 2.64; 95% CI, 2.59-2.69) and cardiac stress tests (OR, 2.50; 95% CI, 2.43-2.56) and higher odds of receiving a new prescription for β-blockers (OR, 2.96; 95% CI, 2.82-3.12). Conclusions and Relevance: In this cohort study, preoperative medical consultation was not associated with a reduction but rather with an increase in adverse postoperative outcomes, suggesting a need for further refinement of target populations, processes, and interventions related to preoperative medical consultation. These findings highlight the need for further research and suggest that referral for preoperative medical consultation and subsequent testing should be carefully guided by individual-level consideration of risks and benefits.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".