Within-Session Test-Retest Reliability of Pressure Pain Threshold and Mechanical Temporal Summation in Chronic Low Back Pain
Bibliographic record
Abstract
OBJECTIVES: To determine the absolute and relative within-session test-retest reliability of pressure pain threshold (PPT) and temporal summation of pain (TSP) at the low back and the forearm in individuals with chronic low back pain (CLBP) and to test the impact of different sequences of measurements on reliability metrics. MATERIALS AND METHODS: Twenty-eight adults with CLBP were recruited. Relative (intraclass correlation coefficient [ICC] and coefficient of variation) and absolute reliability (standard error of measurement and minimal detectable changes) were quantified at 4 sites (back: sacrum and lumbar erector spinae; wrist: hand dorsum and wrist flexors) for PPT and 2 sites (hand and low back) for TSP, for various sequences of measurements. RESULTS: Systematic differences were found between within test and retest for most PPT sequences at the lumbar erector spinae site and 1 TSP sequence (1-2-3) at back and hand sites, precluding reliability analyses for these data. Within-session PPT relative reliability was excellent at low back (ICC = 0.83 to 0.94) and wrist (ICC = 0.88 to 0.97) sites, whereas TSP showed good to excellent reliability at hand (ICC = 0.80 to 0.90) and low back (ICC = 0.73 to 0.89). In general, 2 and 3 measurements optimized absolute and relative reliability for TSP and PPT, respectively. DISCUSSION: Within-session reliability was generally excellent for PPT and TSP at the low back and hand sites among individuals with CLBP. We recommend using 3 measurements for PPT and 2 for TSP to optimize reliability. Caution is recommended when testing PPT of the painful lower back area since a systematic difference was present between the test and retest.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".