P.111 Initial validation of symptom scores derived from the Orthostatic Discriminant and Severity Scale
Bibliographic record
Abstract
Background: To develop a scale to quantify and discriminate orthostatic from non-orthostatic symptoms. We present initial validation and reliability of orthostatic and non-orthostatic symptom scores taken from the Orthostatic Discriminate and Severity Scale (ODSS). Methods: Validity and reliability were assessed in participants with and without orthostatic intolerance. Convergent validity was assessed by correlating symptoms scores with previously validated tools (Autonomic Symptom Profile (ASP) and the Orthostatic Hypotension Questionnaire (OHQ)). Clinical validity was assessed by correlating scores against standardized autonomic testing. Test-retest reliability was calculated using an intra-class correlation coefficient. Results:Convergent Validity: Orthostatic (OS) and Non-Orthostatic (NS) Symptom Scores from 77 controls and 67 patients with orthostatic intolerance were highly correlated with both the Orthostatic Intolerance index of the ASP (OS:r=0.903;NS:r=0.651; p<0.001) and the OHQ: (OS:r=0.800;NS:r=0.574; p<0.001). Clinical Validity: Symptom Scores were significantly correlated with the blood pressure change during head-up tilt (OS:r=-0.445;NS:r=-0.354; p<0.001). Patients with orthostatic intolerance had significantly higher symptom scores compared to controls (OS:66.5±18.1 vs. 17.4±12.9; NS:19.9±11.3 vs. 10.2±6.8; p<0.001, respectively). Test-retest reliability: Both symptom scores were highly reliable (OS:r=0.956;NS:r=0.574, respectively; p<0.001) with an internal consistency of 0.978 and 0.729, respectively. Conclusions: Our initial results demonstrate that the ODSS is capable of producing valid and reliable Orthostatic and Non-Orthostatic Symptom Scores.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".