A Gap in Post-Stroke Blood Pressure Target Attainment at Entry to Cardiac Rehabilitation
Bibliographic record
Abstract
BACKGROUND: Recurrent events account for approximately one-third of all strokes and are associated with greater disability and mortality than first-time strokes. Blood pressure (BP) is the most important modifiable risk factor. Objectives were to determine the proportion of post-stroke patients enrolled in cardiac rehabilitation (CR) meeting systolic and diastolic BP (SBP/DBP) targets and to determine correlates of meeting these targets. METHODS: A retrospective study of 1,804 consecutively enrolled post-stroke patients in a CR program was conducted. Baseline data (database records 2006-2017) included demographics, anthropometrics, clinical/medication history, and resting BP. Multivariate analyses determined predictors of achieving BP targets. RESULTS: Mean age was 64.1 ± 12.7 years, median days from stroke 210 (IQR 392), with most patients being male (70.6%; n = 1273), overweight (66.8%; n = 1196), and 64.2% diagnosed with hypertension (n = 1159), and 11.8% (n = 213) with sleep apnea. A mean of 1.69 ± 1.2 antihypertensives were prescribed, with 26% (n = 469) of patients prescribed 3-4 antihypertensives. SBP target was met by 71% (n = 1281) of patients, 83.3% (n = 1502) met DBP target, and 64.3% (n = 1160) met both targets. Correlates of meeting SBP target were not having diabetes, younger age, fewer prescribed antihypertensives, and more recent program entry. Correlates of meeting DBP target were not having diabetes, older age, fewer prescribed antihypertensives, and more recent stroke. CONCLUSIONS: Up to one-third of patients were not meeting BP targets. Patients with diabetes, and those prescribed multiple antihypertensives are at greater risk for poorly controlled SBP and DBP. Reasons for poor BP control such as untreated sleep apnea and medication non-adherence need to be investigated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".