The Prevalence of Nonadherence in Patients With Resistant Hypertension: A Systematic Review Protocol
Bibliographic record
Abstract
BACKGROUND: Resistant hypertension, usually defined as blood pressure remaining above goal despite the concurrent use of 3 or more antihypertensive agents of different classes, is common (about 10% prevalence) and known to be a risk factor for cardiovascular events. These patients also undergo more screening intensity for secondary hypertension. However, not all patients with apparent treatment-resistant hypertension have true resistant hypertension, with some of them being nonadherent to prescribed pharmacotherapy. The prevalence of nonadherence varies from about 5% to 80% in the published literature. However, the relative contributions of intentional and nonintentional nonadherence are not well described. Nonintentional nonadherence refers to occasional forgetfulness and/or carelessness and can sometimes be related to an inability to follow instructions, because of either cognitive or physical limitations. Intentional nonadherence refers to an active process in which a patient may choose to alter the prescribed medication regimen by discontinuing medications, skipping doses, or modifying doses or dosing intervals. OBJECTIVE: Our objective is to establish the overall prevalence of nonadherence in the apparent treatment-resistant hypertension population and evaluate the relative contributions of nonintentional and intentional nonadherence subtypes. DESIGN: We will conduct a systematic review and meta-analysis. SETTING: We will include observational studies and randomized controlled trials where adherence to antihypertensive medications is measured using a test of adherence, either direct or indirect. PATIENTS: We will include adult human participants aged 18 years or older with a diagnosis of resistant hypertension. MEASUREMENTS: Data extracted from individual studies will include title, first author, design, country, publication year, funding body, method of assessing adherence to antihypertensive medication, prevalence of medication nonadherence, definition of resistant hypertension, sample size, sex, mean age, and coexistent comorbidities. METHODS: A librarian will search the databases Medline, EMBASE, Cochrane, CINAHL, and Web of Science for studies meeting criteria for inclusion. Two reviewers will independently screen the titles and abstracts retrieved and assess the methodological quality of eligible full-text articles using the Cochrane Risk of Bias tool for clinical trials and the Newcastle-Ottawa Scale for observational studies. Summary estimates of prevalence will be generated using pooled analysis using the random-effects method. Subgroup analyses, sensitivity analyses, and evaluation of publication bias will also be performed. RESULTS: The outcomes of interest are the pooled prevalence of nonadherence to antihypertensive medication in apparent treatment-resistant hypertension and the prevalence of nonadherence based on different methods of assessing nonadherence (indirect vs direct), which will allow us to estimate the relative proportion of unintentional and intentional nonadherence subtypes in the overall phenomenon of medication nonadherence. LIMITATIONS: Possible limitations of this study include the finding of severe heterogeneity, the limitations of the literature search, publication bias, and the lack of granular data in the published studies for a study-level meta-analysis. CONCLUSIONS: This systematic review will provide a synthesis of current evidence on the prevalence of medication nonadherence in apparent treatment-resistant hypertension and on the relative contributions of nonintentional and intentional nonadherence subtypes. These findings will provide clinicians with a better understanding of the factors underlying treatment-resistant hypertension and will serve as a strong research base to guide future research on interventions to address medication nonadherence as well as the nonintentional and intentional subtypes. TRIAL REGISTRATION: This protocol has been registered with PROSPERO. We will add registration details once available.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".