Impact of the 2017 American College of Cardiology/American Heart Association Hypertension Guideline on the prevalence of hypertension in young Saudi women
Bibliographic record
Abstract
BACKGROUND: The diagnostic criteria for hypertension have recently been redefined by the American College of Cardiology/ American Heart Association (ACC/AHA). Data on the new prevalence of hypertension in different countries are emerging, but none, to date, from Saudi Arabia. AIMS: This study aimed to determine the impact of the 2017 ACC/AHA hypertension guideline on the prevalence and determinants of hypertension in young Saudi women. METHODS: 518 female college students, 17-29 years of age were prospectively enrolled in a survey during the period from January 1, 2016, to April 15, 2016 at Princess Nourah University. The participants completed a previously validated questionnaire, that assessed their risk factors for hypertension, and their blood pressure, weight and height were measured. RESULTS: Application of the 2017 ACC/AHA diagnostic criteria resulted in approximately 7-fold increase in the prevalence of hypertension, from 4.1% to 27.1% (P < 0.001). At a cut-off value of ≥140/90, hypertension was significantly associated with increased age, increased body mass index (BMI), increased heart rate, history of chronic illnesses, prior diagnosis with diabetes mellitus and family history of hypertension. Whereas, with the ≥130/80 cut-off value, only increased BMI and heart rate were significant predictors (P < 0.001). CONCLUSION: The prevalence of hypertension markedly increased among young adult Saudi women with the 2017 ACC/AHA classification for hypertension, and the main predictors were increased BMI and heart rate. Further studies on the new prevalence and predictors of hypertension in the Saudi population are warranted. This information is important for healthcare authorities to plan cost effective screening, prevention and control programmes.
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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 | 0.004 | 0.013 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".