Retrospective analysis of laboratory testing at the chiropractic clinic of Université du Québec à Trois-Rivières (UQTR).
Bibliographic record
Abstract
This study provides data based on the clinical experience of the Université du Québec à Trois-Rivières (UQTR) chiropractic clinic justifying the use of laboratory tests in chiropractic practice. The data was gathered retrospectively over a 51 month period from January 22, 1997 to April 10, 2001. During this period, the UQTR Chiropractic Clinic opened 6571 patient files. The analysis reveals that of the 6571 patients, 1200 (18.27%) underwent laboratory processes or tests. Of these 1200 processes or tests, 676 (56.34%) showed abnormal findings. Of the 676 patients with abnormal findings, 122 (18.05%) cases were serious enough to justify a referral to a medical doctor (general practitioner or specialist) for immediate follow-up. Among these serious conditions, one was a bone neoplastic pathology and one was a case of leukemia. This study emphasizes the significant contribution of laboratory tests in chiropractic practice. Its importance rests not only with teaching purposes, but also rests with the proper assessment of clinical conditions frequently observed in chiropractic practice. Laboratory tests used in a proper context serve not only as a valuable instrument to identify primary and underlying abnormal physiological factors, but also assist the chiropractor in identifying more precisely those cases that require a medical referral. This study also demonstrates that laboratory testing of chiropractic patients is a necessary and essential clinical procedure for complete public protection. It also demonstrates that chiropractors are an essential part of the health team even when patients are under medical supervision.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".