Physician follow-up and long-term use of evidence-based medication for patients with hypertension who were discharged from an emergency department: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: More than 25% of the population has hypertension. The number of patients seeking care for hypertension in emergency departments has increased by more than 60% in the last decade, with less than 10% of these patients subsequently admitted to hospital. Managing physicians recommend early follow-up to patients who are discharged from the emergency department, but there is a paucity of literature assessing the impact or timing of follow-up on patient outcomes. METHODS: Using a population-based cohort design, we included patients more than 65 years of age who were discharged from an Ontario emergency department with a primary diagnosis of hypertension between 2007 and 2014. We identified 2 cohorts: an incident cohort, and a cohort in which patients were on no more than 1 class of evidence-based antihypertensive medication at the time of presentation. Using logistic regression, we assessed the association of early follow-up care (within 7 d) and basic care (8-30 d), compared with no care within 30 days, on patient use of a new evidence-based antihypertensive medication 1 year later. RESULTS: Our study included 2088 patients with a new diagnosis of hypertension (the first cohort), and 6420 patients in the second cohort. Of patients with new diagnoses, 48.2% and 30.2% obtained early and basic follow-up care, respectively, compared with 50.0% and 30.9% of patients in the second cohort. Compared with patients without follow-up care within 30 days, the adjusted odds of filling an evidence-based antihypertensive medication prescription 1 year later in the incident group were 2.36 (95% confidence interval [CI] 1.86-2.99) for those who received early care, and 2.00 (95% CI 1.55-2.58) for those who received basic care. The adjusted odds in the second cohort were 2.12 (95% CI 1.84-2.43) and 1.96 (95% CI 1.69-2.27), respectively. INTERPRETATION: Early follow-up care after leaving an emergency department with a diagnosis of hypertension was associated with improved long-term use of evidence-based antihypertensive medication. As patients increasingly present to the emergency department for hypertension, a formal, timely follow-up care system could improve patient use of evidence-based antihypertensive medication.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".