Recognition and Management of Resistant Hypertension
Bibliographic record
Abstract
Despite improvements in hypertension awareness and treatment, 30%-60% of hypertensive patients do not achieve BP targets and subsequently remain at risk for target organ damage. This therapeutic gap is particularly important to nephrologists, who frequently encounter treatment-resistant hypertension in patients with CKD. Data are limited on how best to treat patients with CKD and resistant hypertension, because patients with CKD have historically been excluded from hypertension treatment trials. First, we propose a consistent definition of resistant hypertension as BP levels confirmed by both in-office and out-of-office measurements that exceed appropriate targets while the patient is receiving treatment with at least three antihypertensive medications, including a diuretic, at dosages optimized to provide maximum benefit in the absence of intolerable side effects. Second, we recommend that each patient undergo a standardized, stepwise evaluation to assess adherence to dietary and lifestyle modifications and antihypertensive medications to identify and reduce barriers and discontinue use of substances that may exacerbate hypertension. Patients in whom there is high clinical suspicion should be evaluated for potential secondary causes of hypertension. Evidence-based management of resistant hypertension is discussed with special considerations of the differences in approach to patients with and without CKD, including the specific roles of diuretics and mineralocorticoid receptor antagonists and the current place of emerging therapies, such as renal denervation and baroreceptor stimulation. We endorse use of such a systematic approach to improve recognition and care for this vulnerable patient group that is at high risk for future kidney and cardiovascular events.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".