Assessing Validity of the Original and Rasch Versions of the Central Sensitization Inventory with Psychophysical Tests in People with Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To determine the extent of agreement between the original Central Sensitization Inventory (CSI) and the Rasch-calibrated version (RC-CSI) and to explore the association of both versions with psychophysical tests and their respective sensitivity and specificity. METHODS: Patients with knee osteoarthritis who were enrolled in a multicenter cohort study in Montreal, Canada, completed the original CSI, the RC-CSI, and psychophysical tests (i.e., pressure pain thresholds, temporal summation, conditioned pain modulation) according to standardized protocols. Bland-Altman analyses assessed the agreement between the original CSI and the RC-CSI; Spearman correlations and chi-squared analyses evaluated the association between the two CSI scores and the psychophysical tests. A CSI cut point of 40 and an RC-CSI cut point of 31.37 were used. Receiver operating characteristic curves and the resulting sensitivity and specificity with psychophysical tests were also analyzed. RESULTS: Two hundred ninety-three participants were included (58.7% female, mean age of 63.6 years, and body mass index 31.9 kg/m2). The original CSI and RC-CSI mean difference, 3.3/8.2, t(292) = 8.84 (P < 0.001), was significantly different and indicated a small bias. Small but significant inverse correlations were found for the original CSI and RC-CSI scores with pressure pain thresholds at the forearm and patella, with variance explained ranging from 0.01 to 0.12. The largest area under the curve suggested cut points of 23 (CSI) and 25 (RC-CSI) with 80.9% sensitivity and 38.5% specificity. CONCLUSIONS: Because of poor variance explained with psychophysical tests and high false positive rates, our results indicate that there is little clinical value of using either version of the CSI in people with knee osteoarthritis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".