A Survey of the McKenzie Classification System in the Extremities: Prevalence of Mechanical Syndromes and Preferred Loading Strategies
Bibliographic record
Abstract
BACKGROUND: Classification of patients with extremity problems is commonly based on patho-anatomical diagnoses, but problems exist regarding reliability and validity of the tests and diagnostic criteria used. Alternatively, a classification system based on patient response to repeated loading strategies can be used to classify and direct management. OBJECTIVE: The purpose of this study was to investigate the prevalence of McKenzie's classification categories among patients with extremity problems and the loading strategies used in their management. DESIGN: This was a prospective, observational study. METHODS: Thirty therapists among 138 invited (response rate=22%) with a Diploma in Mechanical Diagnosis and Therapy (MDT) were identified from the McKenzie Institute International registry and recruited worldwide to complete an e-mailed questionnaire. They provided data about their age, years qualified, years since gaining a diploma, and practice, and prospectively provided data on anatomical site and categorization for 15 consecutive patients with extremity problems. RESULTS: Data were gathered on 388 patients; classification categories were as follows: derangement (37%); contractile dysfunction (17%); articular dysfunction (10%); and "other" (36%), of which 20% were postsurgery or posttrauma. Exercise management strategies and syndrome application varied considerably among anatomical sites. Classification categories remained consistent in 85.8% of patients over the treatment episode. LIMITATIONS: These findings are not generalizable to therapists who are not experienced with use of MDT in the extremities. CONCLUSIONS: This study demonstrates that trained clinicians can classify patients with extremity problems into MDT classifications and that these classifications remain stable during the treatment episode. Further work is needed to test the efficacy of this system compared with other approaches, but if derangements are as common as this survey suggests, the findings have important prognostic implications because this syndrome is defined by its rapid response to repeated movements.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".