Reliability of conditioned pain modulation in healthy individuals and chronic pain patients: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Conditioned pain modulation (CPM) is a psychophysical parameter that is used to reflect the efficacy of endogenous pain inhibition. CPM reliability is important for research and potential clinical applications. The aim of this systematic review and meta-analysis was to evaluate the reliability of CPM tests in healthy individuals and chronic pain patients. METHODS: We searched three databases for peer-reviewed studies published from inception to October 2020: EMBASE, Web of Science and NCBI. Risk of bias and the quality of the included studies were assessed. A meta-analysis with a random effects model was conducted to estimate intraclass correlation coefficients (ICCs). RESULTS: =4). The highest CPM intra-session reliability was with pressure as test stimulus (TS) and ischemic pressure (IP) or cold pressor test (CPT) as conditioning stimulus (CS) in healthy individuals (ICC 0.64, 95% CI 0.45-0.77), and pressure as TS with CPT as CS in patients (ICC 0.77, 95% CI 0.70-0.82). The highest inter-session ICC was with IP as TS and IP or CPT as CS (ICC 0.51, 95% CI 0.42-0.59) in healthy subjects. The only data available in patients for inter-session reliability were with pressure as TS and CPT as CS (ICC 0.44, 95% CI 0.11-0.69). Quality ranged from very good to excellent using the QACMRR checklist. The majority of the studies (24 out of 25) scored inadequate in Kappa coefficient reporting item of the COSMIN-ROB checklist. CONCLUSIONS: Pressure and CPT were the TS and CS most consistently associated with good to excellent intra-session reliability in healthy volunteers and chronic pain patients. The inter-session reliability was fair or less for all modalities, both in healthy volunteers and chronic pain patients.
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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 | 0.022 | 0.066 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.040 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".