The sensitivity and specificity of thermometry and plethysmography in the assessment of hand-arm vibration syndrome
Bibliographic record
Abstract
BACKGROUND: Finger plethysmography and thermometry are objective measures used to assess the vascular aspect of hand-arm vibration syndrome (HAVS). Research to date shows poor correlation between these tests and Stockholm Workshop Scale (SWS) vascular stage. Clinicians, researchers and compensation boards require objective means to diagnose and quantify HAVS. AIMS: To define the specificity and sensitivity of thermometry and plethysmography using the SWS as the reference criterion. A secondary goal was to consider cut points for the tests optimizing sensitivity and specificity. METHODS: A cross-sectional analysis was conducted on HAVS patients seen at an occupational medicine specialty clinic. Plethysmography and thermometry were analyzed using SWS vascular stage as the outcome variable. Logistic regression controlled for age, smoking and time since last vibration exposure and use of vasoactive medications. The sensitivity and specificity of the combined tests were calculated using varying cut points. RESULTS: A total of 139 patients consented to participate in the study. Plethysmography stage 1 or greater showed the highest sensitivity (sensitivity 94% and specificity 15%). Specificity was optimized combining plethysmography stage 3 and thermometry stage 3 (specificity 98% and sensitivity 23%). Maximal diagnostic accuracy was achieved by plethysmography alone setting the criteria for a positive test as being stage 1 or greater (70%). CONCLUSIONS: Neither plethysmography nor thermometry either alone or in combination demonstrated sufficient sensitivity and specificity to serve as an objective correlate for SWS vascular stage. All combinations of plethysmography and thermometry showed a lower specificity than sensitivity indicating that the SWS may be less sensitive in detecting vascular pathology than the objective tests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".