Heterogeneity of the Effect of Telemedicine Hypertension Management Approach on Blood Pressure: A Systematic Review and Meta-analysis of US-based Clinical Trials
Bibliographic record
Abstract
Abstract Background Telemedicine management of hypertension (TM-HTN) uses home blood pressure (BP) to guide pharmacotherapy and telemedicine-based self-management support (SMS). Optimal approach to implementing TM-HTN in the US is unknown. Methods We conducted a systematic review and a meta-analysis to examine the effect of TM-HTN vs. usual clinic-based care on BP and assessed heterogeneity by patient- and clinician-related factors. We searched US-based randomized clinical trials among adults from Medline, Embase, CENTRAL, CINAHL, PsycInfo, and Compendex, Web of Science Core Collection, Scopus, and two trial registries to 7/7/2023. Two authors extracted, and a third author confirmed data. We used trial-level differences in systolic BP (SBP), diastolic BP (DBP) and BP control rate at ≥6 months using random-effects models. We examined heterogeneity of effect in univariable meta-regression and in pre-specified subgroups [clinicians leading pharmacotherapy (physician vs. non-physician), SMS (pharmacist vs. nurse), White vs. non-White patient predominant trials (>50% patients/trial), diabetes predominant trials (≥25% patients/trial) and in trials that have majority of both non-White patients and patients with diabetes vs. White patient predominant but not diabetes predominant trials. Results Thirteen, 11 and 7 trials were eligible for SBP, DBP and BP control, respectively. Differences in SBP, DBP and BP control rate were -7.3 mmHg (95% CI: - 9.4, -5.2), -2.7 mmHg (-4.0, -1.5) and 10.1% (0.4%, 19.9%), respectively, favoring TM-HTN. More BP reduction occurred in trials with non-physician vs. physician led pharmacotherapy (9.3/4.0 mmHg vs. 4.9/1.1 mmHg, P<0.01 for both SBP/DBP), pharmacist vs. nurses provided SMS (9.3/4.1 mmHg vs. 5.6/1.0 mmHg, P=0.01 for SBP, P<0.01 for DBP), and White vs. non-White patient predominant trials (9.3/4.0 mmHg vs. 4.4/1.1 mmHg, P<0.01 for both SBP/DBP), with no difference by diabetes predominant trials. Lower BP reduction occurred in both diabetes and non-White patient predominant trials vs. White patient predominant but not diabetes predominant trials (4.5/0.9 mmHg vs. 9.5/4.2 mmHg, P<0.01 for both SBP/DBP). Conclusions TM-HTN is more effective than clinic-based care in the US, particularly when non-physician led pharmacotherapy and pharmacist provided SMS. Non-White patient predominant trials seemed to achieve lesser BP reduction. Equity conscious, locally informed adaptation of TM-HTN is needed before wider implementation. Clinical Perspective What Is New? In this systematic review and meta-analysis of US-based clinical trials, we found that telemedicine management of hypertension (TM-HTN) was more effective in reducing and controlling blood pressure (BP) compared with clinic based hypertension (HTN) care. The BP reduction was more evident when pharmacotherapy was led by non-physician compared with physicians and HTN self-management support was provided by clinical pharmacists compared with nurses, Non-White patient predominant trials achieved lesser BP reductions than White patient predominant trials. What Are the Clinical Implications? Before wider implementation of TM-HTN intervention in the US, locally informed adaptation, such as optimizing the team-based HTN care approach, can provide more effective BP control. Without equity focused tailoring, TM-HTN intervention implemented as such can exacerbate inequities in BP control among non-White patients in the US.
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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 | 0.038 | 0.086 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.048 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 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".