Relationship between acute pain trajectories after an emergency department visit and chronic pain: a Canadian prospective cohort study
Bibliographic record
Abstract
OBJECTIVES: Inadequate acute pain management can reduce the quality of life, cause unnecessary suffering and can often lead to the development of chronic pain. Using group-based trajectory modelling, we previously identified six distinct pain intensity trajectories for the first 14-day postemergency department (ED) discharge; two linear ones with moderate or severe pain during follow-up (~40% of the patients) and four cubic polynomial order trajectories with mild or no pain at the end of the 14 days (low final pain trajectories). We assessed if previously described acute pain intensity trajectories over 14 days after ED discharge are predictive of chronic pain 3 months later. DESIGN: Prospective cohort study. SETTING: Tertiary care trauma centre academic hospital. PARTICIPANTS: This study included 18 years and older ED patients who consulted for acute (≤2 weeks) pain conditions that were discharged with an opioid prescription. Patients completed a 14-day diary in which they listed their daily pain intensity (0-10 numeric rating scale). OUTCOMES: Three months after ED visit, participants were questioned by phone about their current pain intensity (0-10 numeric rating scale). Chronic pain was defined as patients with current pain intensity ≥4 at 3 months. RESULTS: A total of 305 participants remained in the study at 3 months, 49% were women and a mean age of 55±15 years. Twelve per cent (11.9; 95% CI 8.2 to 15.4) of patients had chronic pain at the 3-month follow-up. Controlling for age, sex and pain condition, patients with moderate or severe pain trajectories and those with only a severe pain trajectory were respectively 5.1 (95% CI 2.2 to 11.8) and 8.2 (95% CI 3.4 to 20.0) times more likely to develop chronic pain 3 months later compared with patients in the low final pain trajectories. CONCLUSION: Specific acute pain trajectories following an ED visit are closely related to the development of chronic pain 3 months later. TRIAL REGISTRATION NUMBER: NCT02799004; Results.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".