Test–Retest Reliability of Quantitative Sudomotor Axon Reflex Testing
Bibliographic record
Abstract
PURPOSE: To determine the reliability of quantitative sudomotor axon reflex testing (QSART). METHODS: The QSART at four sites was performed at two time points (n = 20 healthy participants) to determine the intraclass correlation coefficient with 95% confidence intervals. The standard error of measurement and minimal detectable change for men and women was obtained from QSART values from a larger cohort (n = 67). RESULTS: Intraclass correlation coefficients (95% confidence intervals) for the forearm, proximal leg, distal leg and foot were 0.75 (0.46 to 0.89), 0.49 (0.07 to 0.77), 0.71 (0.38 to 0.88) and 0.48 (0.07 to 0.76). Standard error of measurements ranged from 0.666 to 0.978 µL for men and 0.273 to 0.653 µL for women. Minimal detectable changes ranged from ±1.847 to ±2.712 µL for men and ±0.756 to ±1.809 µL for women. CONCLUSIONS: We observed moderate test-retest reliability for QSART with a large standard error of measurements and minimal detectable changes for both men and women. The results of this study suggest limited utility of QSART for monitoring sudomotor function in longitudinal and interventional studies.
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 | 0.011 | 0.031 |
| 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 | 0.001 |
| 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 | 0.001 |
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".