An updated normative data set from the autonomic reflex screen representative of Southwestern Ontario
Bibliographic record
Abstract
In evaluating autonomic dysfunction, the autonomic reflex screen (ARS) is an established set of standardized tests to evaluate the presence and severity of autonomic dysfunction. Our laboratory previously reported normative data on 121 healthy individuals; however, the sample size in older individuals was reduced compared with other age groups. Therefore, the objective of the current study was to provide updated normative values representative of young, middle-aged, and older individuals from Southwestern Ontario. Two hundred and fifty-two healthy individuals completed quantitative sudomotor axon reflex testing, heart rate responses to deep breathing (HRDB), and Valsalva maneuver using standard protocols of the ARS. All 4 sweat sites demonstrated a significant effect of sex (p < 0.001). In addition, the proximal leg, distal leg, and foot were all significantly affected by age (p < 0.001). Cardiovagal parameters, measured via HRDB and Valsalva ratio revealed a significant regression with age (p < 0.001). These results show similar trends with previously reported normative data sets. All normative data as a function of age and sex, where appropriate, are expressed as percentiles (2.5th, 5th, 95th, 97.5th). The current study provides updated normative data describing autonomic functioning in healthy individuals obtained from the sudomotor and cardiovagal components of the ARS.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".