Comparison of Older and Younger Patients Referred to a Non-interventional Community Pain Clinic in the Greater Toronto Area (GTA)
Bibliographic record
Abstract
AIM: To compare demographic and pain characteristics of older (≥ 65) vs younger (< 65) chronic non-cancer pain patients referred to a community pain clinic in the Greater Toronto Area (GTA), Ontario, Canada. METHODS: This is a retrospective study of 644 consecutive new patients with pain seen during 2016-2017 (older group n = 126; younger group n = 518). Demographic characteristics, Brief Pain Inventory pain ratings, and diagnosis were obtained using retrospective chart review. Patients were classified into group I (pure biomedical pathology), group II (mixed biomedical causes and psychological factors) and group III (no detectable physical pathology but psychological factors were considered important). RESULTS: Older patients comprised 19.6% of the overall population (higher than the average GTA older population). Regarding older vs younger group, male/female ratio was 1:1.3 vs 1:1.7 respectively, while 71% of the older patients were foreign born vs 37% of the younger group (p < 0.001). Low back was the most prevalent pain site for both groups; 70% of the older patients were classified as group I vs 35% of the younger patients (p < 0.0001), and only 6% as group III (vs 18% of the younger population, p < 0.05). CONCLUSION: The study points to considerable differences between younger and older patients with pain with the latter presenting with significant biomedical pathology but lesser psychopathology. The results are comparable to those obtained from a university pain clinic as well as a rural Northern Ontario clinic. Implications of the study for planning of pain care are discussed.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".