Bibliographic record
Abstract
Intertester reliability of the McKenzie evaluation in assessing patients with mechanical low back pain. (Sunny Brook & Women's College Health Sciences Centre, Toronto, Ontario, Canada) J Orthop Sports Phys Ther 2000;30:368–389. In this study, patients were assessed simultaneously by 2 physical therapists trained in the McKenzie evaluation system. The therapists were randomly assigned as examiner and observer. Agreement was estimated by Kappa statistics. Forty‐five subjects (47 ± 14 years), composed of 25 women and 20 men with acute, subacute, or chronic low back pain were examined. The agreement between raters for selection of the McKenzie syndromes was K = 0.70, and for the derangement subsyndromes was K = 0.96. Interrater agreement for the presence of lateral shift, relevance of lateral shift, relevance of lateral component, and deformity in the sagittal plane was K = 0.52, 0.85, 0.95, and 1.00, respectively. Intertester agreement on syndrome categories in 17 patients under 55 years of age was excellent with K = 1.00. Conclude that a form of low back evaluation, using patterns of pain response to repeated end range spinal test movements, was highly reliable when performed by 2 properly trained physical therapists. Comment by Karen Crawford, RPT. This article intends to address the ability for therapists to agree on a low back pain diagnosis using the McKenzie technique of classification. It is important for this study to select a clear clinical diagnosis in order to establish rationale for patient management and determine a prognosis. Another purpose for this study was to agree on the relevance of sagittal and frontal plane deformities using McKenzie methods in assessing patients with back pain. The subjects included adult patients with a history of acute, subacute, or chronic low back pain. Patients were referred by general practitioners or specialists for treatment at an outpatient department where the study was conducted. The examination consisted of taking a history, observational evaluation of the range of motion, and completion of a specified tests movements in the sagittal, frontal, and combined planes. Subjects were allowed to communicate only with the assessor. A total of 46 patients with a history of low back pain agreed to complete the assessment. Patients were divided into 2 groups, those 55 years of age and older and those younger than 55. McKenzie identifies only 3 mechanical syndromes: 1. Postural, 2. Dysfunction, 3. Derangement. Each of these syndromes were divided into separate subsyndromes according to location of the pain and presence or absence of spinal deformities. The study concluded that therapists trained in use of the McKenzie evaluation system can be highly reliable in reaching the same conclusion in respect to classifying patients into diagnostic syndromes and subsyndromes, especially in patients under the age of 55. In contrast to other published studies, the importance of advanced training for interpretation of symptom behavior definitely leads to selection of the correct diagnosis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.376 | 0.224 |
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".