Uncontrolled hypertension by the 2014 evidence-based guideline
Bibliographic record
Abstract
OBJECTIVES: To look at the prevalence of uncontrolled hypertension in the population using various hypertension guidelines [Seventh Joint National Committee (JNC 7), European Society of Hypertension (ESH)/European Society of Cardiology (ESC) and Canadian Hypertension Education Program (CHEP)] and to assess the predictors of being reclassified to controlled hypertension based on the 2014 evidence-based guideline (2014 EBG) in comparison to JNC 7. METHODS: Using the National Health and Nutrition Examination Survey for 2011-2012, the prevalence of uncontrolled hypertension in the population was ascertained using different guidelines, including 2014 EBG, JNC 7, ESH/ESC and CHEP. Prevalence of uncontrolled hypertension was further examined based on subgroups by age, sex, race and presence of chronic kidney disease or diabetes. Predictors to be reclassified to controlled hypertension by the 2014 EBG were assessed using multivariable logistic regression. RESULTS: Prevalence of uncontrolled hypertension was 12.8% by the 2014 EBG in comparison to 16.6% by JNC 7, 13.6% by ESH/ESC and 15.6% by CHEP (P < 0.001). As per JNC 7, 23.0% of those with uncontrolled hypertension were reclassified to controlled hypertension by the 2014 EBG. Those most likely to be reclassified to controlled hypertension were older, females and those with diabetes. CONCLUSION: On the basis of the updated 2014 evidence-based high blood pressure guideline, the percentage of the US population labeled as suffering from uncontrolled hypertension has changed from 16.6 to 12.8%. It is important to note that this change is a reflection of the modified blood pressure targets and not a change in the actual levels of blood pressure control in the population. The greatest impact of reclassification is on elderly, females and those with diabetes.
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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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".