The Toronto General Hospital Transitional Pain Service: development and implementation of a multidisciplinary program to prevent chronic postsurgical pain
Why this work is in the frame
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Bibliographic record
Abstract
Chronic postsurgical pain (CPSP), an often unanticipated result of necessary and even life-saving procedures, develops in 5-10% of patients one-year after major surgery. Substantial advances have been made in identifying patients at elevated risk of developing CPSP based on perioperative pain, opioid use, and negative affect, including depression, anxiety, pain catastrophizing, and posttraumatic stress disorder-like symptoms. The Transitional Pain Service (TPS) at Toronto General Hospital (TGH) is the first to comprehensively address the problem of CPSP at three stages: 1) preoperatively, 2) postoperatively in hospital, and 3) postoperatively in an outpatient setting for up to 6 months after surgery. Patients at high risk for CPSP are identified early and offered coordinated and comprehensive care by the multidisciplinary team consisting of pain physicians, advanced practice nurses, psychologists, and physiotherapists. Access to expert intervention through the Transitional Pain Service bypasses typically long wait times for surgical patients to be referred and seen in chronic pain clinics. This affords the opportunity to impact patients' pain trajectories, preventing the transition from acute to chronic pain, and reducing suffering, disability, and health care costs. In this report, we describe the workings of the Transitional Pain Service at Toronto General Hospital, including the clinical algorithm used to identify patients, and clinical services offered to patients as they transition through the stages of surgical recovery. We describe the role of the psychological treatment, which draws on innovations in Acceptance and Commitment Therapy that allow for brief and effective behavioral interventions to be applied transdiagnostically and preventatively. Finally, we describe our vision for future growth.
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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 | 0.038 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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