The Current Perception Threshold Test Differentiates Categories of Mechanical Neck Disorder
Bibliographic record
Abstract
STUDY DESIGN: Cross-sectional discriminative analysis. OBJECTIVE: To determine whether current perception threshold (CPT) can differentiate between categories of patients with mechanical neck disorders (MNDs). BACKGROUND: Neck pain is the third most common musculoskeletal disorder and affects a third of all adults each year. It can present as neck pain without musculoskeletal signs, neck pain with musculoskeletal signs but no neurological signs, or neck pain with neurological signs. CPT testing can assess altered sensory perception that may reflect neurological changes. METHODS: Patients with MNDs (n = 106) were classified into 3 groups, based on a standardized musculoskeletal examination process performed by an experienced physiotherapist who was blinded to CPT scores. The 3 groups were defined as neck pain without musculoskeletal signs (MND I) (n = 60), neck pain with musculoskeletal signs (MND II) (n = 29), and neck pain with neurological signs (MND III) (n = 17). A rapid protocol of CPT testing was performed at 3 frequencies (5, 250, and 2000 Hz), using 3 dermatomal locations on the hand. A 1-way analysis of variance with post hoc comparison and effect sizes was calculated to compare the mean CPT scores between the groups. A binary logistic-regression model was used to predict probability of higher CPT in MND III and to create a receiver-operating-characteristic curve. RESULTS: Mean CPT differed significantly across the 3 MND groups (MND I, 9.7; MND II, 10.6; and MND III, 11.8; P<.001; η(2) = 0.6). Post hoc comparisons indicated differences between MND I and MND II (P = .05) and between MND II and MND III (P = .01) that had large effect sizes (MND I versus II, d = 1 and MND II versus III, d = 2.2). CPT testing was able to distinguish between MND II and III when a threshold value of greater than 11 was used to indicate MND III. The predicted probability of abnormal CPT in MND III had an estimated 73% sensitivity and 81% specificity; the odds ratio was 11.5 (P = .001) for the differentiation capacity of CPT between MND II and III, with a cutoff of 11. The area under the receiver-operating-characteristic curve was 0.84 (95% confidence interval: 0.72, 0.96; P<.001). CONCLUSION: CPT testing has moderate discriminatory accuracy, specificity, and sensitivity for classification of MND categories into neck pain with or without neurological signs. J Orthop Sports Phys Ther 2014;44(7):532-540. Epub 10 May 2014. doi:10.2519/jospt.2014.4691.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".