Temporal Trends in Prevalence of Blood Pressure Screening and Hypertension After Introduction of Clinical Practice Guidelines on Hypertension in Canadian Children: A Time-Series Analysis
Bibliographic record
Abstract
Background: In 2016 & 2017 respectively, new Canadian & American guidelines for assessing pediatric hypertension (HTN) were introduced. It is unknown whether these guidelines have impacted blood pressure (BP) screening & HTN prevalence in primary care settings. Methods: The study included 438,297 children (3-18 years) from seven Canadian provinces with 1+ encounter in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) database between January 1, 2011 & December 31, 2019. The study cohort had 3 phases: Jan 1, 2011-Dec 31, 2015 (era 1), Jan 1, 2016 - Dec 31, 2017 (wash out) & Jan 1, 2018- Dec 31, 2019 (era 2). HTN was defined by NHLBI guideline up to December 31, 2017 & AAP 2017 guideline thereafter. We performed an interrupted time series analysis to assess impact of the guideline recommendations on BP screening and HTN prevalence. Results: 264,635 children in era 1 & 193,654 children in era 2 were evaluated. In era 1 and 2, there were 66,653 (25.2%) & 45,050 (23.3%) children, respectively with at least 1 BP measurement. Annual BP screening generally increased each year from 13.3% in 2011 to 20.2% in 2019. In Era 1, a total of 1.1% of children met HTN criteria with a mean onset age of 12.6 years (SD 4.1). In Era 2, a total of 2.0% of children met HTN criteria with a mean onset age of 14.1 years (SD 4.1). Time series analysis revealed a significant increase in BP screening and HTN after the guidelines’ introduction (p=0.04 and p=<0.0001 respectively). Conclusions: BP screening and HTN prevalence generally increased between 2011 and 2019, with a significant increase in post-guideline BP documentation and children meeting HTN criteria following guideline implementation.Proportion of children who received BP screening or who met HTN criteria from Jan 1, 2011 to Dec 31, 2019
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".