Normative data on cardiovascular autonomic function in Greenlandic Inuit
Bibliographic record
Abstract
INTRODUCTION: Diabetes is increasing among Greenlandic Inuit; however, the prevalence of cardiovascular autonomic neuropathy (CAN) is yet unknown. The assessment of CAN requires an ability to differentiate between normal and abnormal. The aim was to establish normative reference data of cardiovascular autonomic function in Greenlandic Inuit. RESEARCH DESIGN AND METHODS: and in the town Qasigiannguit in 2020. Assessment included cardiovascular autonomic reflex tests (CARTs) and power spectral analysis of heart rate variability (HRV). Normative reference limits were estimated by applying piecewise linear quantile regression models at the fifth percentile. Models were adjusted for age and sex. RESULTS: Based on examinations of 472 participants (61.7% females), normative reference data was established for all outcomes. Mean age was 54 years (SD 13.1). Higher age was inversely associated with all outcomes of CARTs and HRV. A linear fall in cardiovascular autonomic function tended to level off beyond age of 60 or 70 years for supine-to-upright position ratio and low frequency power. However, the number of observations in subjects older than 60 or 70 years was limited, which may have caused a flattening of the curve around that age. No other associations were found. CONCLUSIONS: The general level of the CARTs and HRV for all age groups is notably lower than in previous studies from other nationalities. We speculate that sociodemographic and cultural aspects of the Greenlandic Inuit population including body mass index, smoking, physical activity and alcohol consumption may have affected the cardiovascular autonomic function.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".