Home blood pressure in target range as an additional therapeutic goal in hypertensive patients: a telemonitoring-based analysis
Bibliographic record
Abstract
Abstract Aim Guidelines recommend treating hypertension (HTN) keeping office blood pressure (BP) within the therapeutic range (TR) rather than aiming to achieve only cut-off value. Time of office BP values in TR is an independent predictor of cardiovascular events. However, data on home BP in TR are lacking. Telehealth simplify collection and structure home BP. We aim to find reliable proportion of home systolic (S) BP in TR (sBPiTR) and to evaluate its impact on overall BP control. Methods We used the data of HTN patients who participated in BP telemonitoring and counseling for 3 months. We divided sBPiTR (110–130 mmHg, all SBP readings except the very or every 1st day) by quartiles (< 25; 25 to 49; 50 to 74; >74). A weighted Cohen's kappa coefficient was an estimate of inter-rater reliability between sBPiTR and office SBP or home SBP in TR at 3 months. We used binomial logistic regression to evaluate the predictive value of sBPiTR on target office/home SBP achievement. Results A total of 123 patients were included (median age 54 years; 102 males) with a median office SBP of 140 mmHg. By 3 months it decreased to 130 mmHg (p < 0.001), and 60.2% patients achieved a target of 120–139 mmHg. More patients were in the upper sBPiTR quartiles (70% versus 30%). There was a slight agreement between office SBP in TR and sBPiTR ≥ 50% (k = 0.19, p < 0.035). The reliability increased when countered against home SBP in TR (k = 0.32–0.65], p < 0.0001). Patients with sBPiTR ≥ 50% were more likely to fall within office SBP TR (OR 2.41, 95% CI [1.06 to 5.51] and home SBP TR (OR 5.2 95% CI [2.06–13.12] after adjustment for baseline covariates. Conclusion The threshold of 50% of home SBP measurements within 110–130 mmHg has a slight agreement with office BP control and a fair agreement with home BP control. This variable may serve a predictor for achievement of target SBP both for in- and out-of office. Larger studies are needed to confirm these preliminary results.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".