Relationship Of A Community Physical Activity Program With The Number Of Antihypertensive Drugs Used By Elderly Women With Arterial Hypertension: A Cross-Sectional Study
Bibliographic record
Abstract
Abstract Background: Physical activity is an important tool to manage systemic arterial hypertension. However, less is known about the relationship of physical activity with the number of antihypertensive drugs used by older adults. The aim of this study was to compare the number of antihypertensive drugs used by older female adults (aged ≥ 60 years) with a low level of physical activity with the number used by those with a high level of physical activity, and to verify how many participants used more than two antihypertensive drugs. The habitual level of physical activity was evaluated by the Baecke questionnaireMethods: Twenty-eight physically active older women with systemic arterial hypertension who participated in a physical activity program for community-dwelling older female adults were divided into two groups: participants who presented lower habitual physical activity levels were placed in group 1 and participants that presented higher habitual physical activity levels were placed in group 2, according to the Baecke questionnaire. In addition, the number of antihypertensive drugs used by participants was collected.Results: The number of prescribed antihypertensive tablets was 2.0 (median) for both groups investigated. There was no significant difference between groups regarding the number of antihypertensive tablets prescribed (p>0.05). There was no statistical difference in proportion of participants from the lower physical activity group used more than two antihypertensive drugs.Conclusions: The level of habitual physical activity did not affect the number of antihypertensive tablets used by hypertensive elderly women.
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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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".