Relevance of Personalized Health Care in Patients with Arterial Hypertension: Where are we now?
Bibliographic record
Abstract
Personalized health care (PHC) or precision medicine is a new medical concept that aids in treatment decisions for patients by tailoring them to their individual needs. It often employs genetic testing to select appropriate and optimal therapies (pharmacogenomics). Although this concept is widely applied in oncology, the field of hypertension is still in the early stages and “personalization” is currently limited to tailoring antihypertensive treatment according to age, comorbidities, and ethnicity. Despite the fact that incomplete/lack of treatment response occurs in 10–30% of hypertensive patients for angiotensin-converting enzyme (ACE) inhibitors and in 15–25% for β-blockers, major continental guidelines still recommend the use of antihypertensive agents in a “one-size-fits-all” approach, neglecting the 1977 postulation of the Joint National Committee that “all patients must receive individualized therapy programs.” The arrival of molecular testing offers new possibilities to differentiate monogenetic from polygenetic disorders and to identify associations between hypertension and drug response to corresponding genes. Up to 50% of the variation in blood pressure (BP) is attributable to genetic factors. Polymorphisms have been identified and studied in genes for BP-modifying receptors, such as ADBR (β-adrenergic receptors), and pharmacological pathways (GNB3, RAAS system). Approximately, one-quarter of the currently analyzed gene polymorphisms demonstrate significant pharmacogenetic effects (ADD1 Gly460Trp and the insertion/deletion [I/D] polymorphism in intron 16 of the ACE gene). Several large screening studies are currently ongoing to assess the impact on efficacy of antihypertensive medication of variants in hypertension-susceptibility genes. The GenHAT substudy of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) assessed the predictive validity of the ACE I/D genotype for coronary heart disease. The Family Blood Pressure Program included 11,079 participants to map genetic variants associated with hypertension. In this review chapter, we display the current body of knowledge regarding PHC in the treatment of hypertension. In particular, we highlight genetic variants associated with hypertension and response/non-response to antihypertensive substance classes. Second, we describe technological aspects of PHC and display the most recent example of a PHC marker used in preeclampsia (PlGF/sFlt-1/PlGF). We then present the results of a guideline review, which included six international guidelines (the European Society of Cardiology/the European Society of Hypertension (ESC/ESH), the Joint National Committee (JNC)8, the Canadian Hypertension Education Program (CHEP), the National Institute for Health and Care Excellence (NICE) and the American Heart Association (AHA)/the American College of Cardiology (ACC)/the Centers for Disease Control and Prevention (CDC) and the American Society of Hypertension (ASH)/the International Society of Hypertension (ISH)) on recommendations regarding PHC in arterial hypertension and address contemporary governmental health agency perspectives on PHC. Finally, we present the view of physicians on the development of PHC.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".