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Enregistrement W2792815694 · doi:10.1111/jch.13215

Towards better blood pressure: Do non‐pharmacological strategies provide the right path?

2018· letter· en· W2792815694 sur OpenAlexafffundabout
Swapnil Hiremath

Notice bibliographique

RevueJournal of Clinical Hypertension · 2018
Typeletter
Langueen
DomaineMedicine
ThématiqueBlood Pressure and Hypertension Studies
Établissements canadiensUniversity of Ottawa
Organismes subventionnairesUniversity of Ottawa
Mots-clésMedicinePath (computing)Blood pressureIntensive care medicineCardiologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

A scene like this plays out many times every day: A patient with newly diagnosed hypertension, confirmed with out-of-office readings, is seen in the clinic. What happens next depends on the patient, the doctor, and other less understood dynamics of that interaction. In most settings, the patient walks out with a plan to change their lifestyle, a prescription for a pill, or sometimes both. On one hand, most individuals demonstrate significant pill disutility, defined as the longevity gain desired by an individual to offset the inconvenience of taking a preventative tablet for life.1 This can vary considerably, ranging from >1 month for about two-thirds of patients, to 12% demonstrating extreme pill disutility (bordering on pill hatred),2 actually desiring ≥10 year increased life expectancy before taking any new medication.1 On the other hand, undoubtedly, giving a prescription for a medication is a much faster and easier option for the physician. Data from a large health maintenance organization, which has achieved an enviable 85% hypertension control, demonstrate that the path to lower blood pressure does go through optimal pharmacotherapy.3 Additionally, a successful non-pharmacological strategy should take into account the patient motivation for lifestyle changes and the pieces needed for actual execution, not just counselling for eating less salt. The paper by Liu et al tackle the latter aspect, using data from the National Health and Nutrition Examination Survey (NHANES) 1999-2004 survey of the 4000 hypertensive patients who reported that a recommendation from their doctor for any 1 (or more) of 4 non-pharmacologic strategies (less sodium, less alcohol, more physical activity, or weight loss).4 As expected, reducing sodium intake was the most common (68%) and alcohol reduction the most uncommon (26%) recommendation. The self-reported adoption rates of these strategies were very high (ranging from 59% to 87%), but despite this, almost half the patients (47%) still had uncontrolled hypertension. Blood pressure decreases quite nicely with changes in diet (decreased sodium and alcohol and increased potassium and fruits and vegetables), increased exercise, and successful weight loss. Indeed, data from interventional trials report ~4-7 mm Hg decrease with these lifestyle modifications. Unsurprisingly, the World Health Organization, Hypertension Canada, and the recently revised 2017 American Heart Association/American College of Cardiology (AHA/ACC) guidelines, all recommend most of these measures (Table).5-10 Diet such as DASH Stress management The second part, however, is more important: what change have these guidelines had in terms of physician and patient behavior? Unfortunately, the evidence suggests that along with the increasing prevalence of hypertension and obesity globally, there has not been much of a decrease in sodium intake, nor an appreciable increase in physical activity. The global burden of disease study shows an increasing prevalence of hypertension (defined as systolic blood pressure >140) from 17 307 to 20 526 per 100 000 in the last 25 years.11 Obesity has doubled in 70 of 195 countries and continuously increased in most others.12 The global mean sodium intake is also well over the 2000 mg recommended level, at 3.95 g/d, with the range being 2.18-5.51 g/d.13 Thus, not a single country studied averages a sodium intake in the desired level. This reflects the knowledge to implementation gap that still exists despite these well-intentioned guidelines.14 Some of this surely stems from the paucity of effectiveness that would help us more than the current crop of efficacy trials. Efficacy trials determine whether an intervention produces the expected result under ideal circumstances. Effectiveness trials measure the degree of beneficial effect under real world clinical settings.15 For these lifestyle modifications in hypertension, efficacy has been well established, but effectiveness less so. For diet, as an example, decreasing sodium intake is a robust and well-accepted lifestyle modification. However, most, if not all, trials of reduction in sodium intake were feeding trials, which did establish efficacy, but used interventions such as extended inpatient counselling sessions, cooking lessons, and/or provision of meals (eg, Dietary Approaches to Stop Hypertension [DASH] trial).16 Unsurprisingly, in the follow-up trial of the effects of comprehensive lifestyle modification with counseling instead of meal provision, the achieved sodium intake was 146 mmol/d (comparing unfavorably with 67 mmol/d achieved in the DASH-Sodium trial).17-19 Healthier diet is also more expensive (estimated at ~$1.50 daily), which compares unfavorably to a medication that may be covered by insurance.20 Similarly, for exercise, the interventions are of a supervised exercise program and not an exhortation to “do more exercise.” Last, the data on alcohol reduction is also based on successful reduction with intensive counseling and follow up. All of the 3 aspects in the first paradigm of the efficacy to effectiveness gap apply here: physician behavior, attention to adherence, and disparity in access to resources and care.15 Clearly interventions as described above are thus not feasible to be translated into routine clinical practice yet, and hence, it is unreasonable to expect a remarkable behavior change from mere counselling. If pragmatic trials of, say a physician recommendation, show a significant improvement in blood pressure and clinical outcomes, we can focus our efforts on improving physician behavior.21 If these pragmatic trials are not successful in changing patient lifestyle and improving blood pressure, our efforts should then be diverted to more efficiently finding and testing an implementation strategy that works. The 4000 patients included in this survey by Liu et al includes those who said “yes” to 1 of 4 questions on remembering their doctor-recommend lifestyle change. It does not follow that the other individuals in the NHANES cohort were not given such recommendations, and is hence subject to well-known recall bias. It also does mean that this assembled cohort would be enriched with patients who were attentive, knowledgeable, and motivated about changing their lifestyle. This is unlikely to be representative of the general hypertensive population, potentially limiting the external validity of these findings. Moreover, another under-appreciated facet of the patient-provider interaction is health literacy, or the lack thereof. Health literacy is defined as is the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions.22 Not surprisingly, limited health literacy is associated with poorer health, less efficient use of health care services, and higher mortality.23-27 Mere counseling by a doctor will not help spur change in the patient with poor health literacy. These individuals need strategies, such as a focus on “need-to-know” and “need-to-do” use of teach-back methods and using clearly written educational materials.28 Given the prevalence of inadequate health literacy at 36% in a large sample of adults in the US, it is very likely the prevalence in a cohort such as NHANES would be similarly high.29 With so much attention focused on sodium intake, what is often lost is the similar effect seen on blood pressure with an increase in potassium intake, whether through diet or as supplements.30-32 Indeed, the natriuretic effect of increased potassium intake is well known via its activation of the inwardly rectifying Kir1 channels in the distal tubule.33 Some of the benefit accrued with the DASH diet with respect to its effect on lowering blood pressure may indeed be mediated through the high potassium content (typically about 120 mmol/d) of the DASH diet.18, 19 Even amongst those unable to adhere to the DASH diet, increasing the intake of potassium alone may be easier than decreasing the intake of sodium, which is harder unless one is meticulous about buying the right ingredients and cooking themselves. Similarly, strong evidence from RCTs exist on the effect of blood pressure reduction from decreasing alcohol intake, at least down to 2 standard drinks a day.34 But, only a quarter of the patients in the analysis by Liu et al received a recommendation for reducing alcohol intake. Despite the clear deleterious effects of greater alcohol consumption not just on blood pressure, but on infections, cardiovascular disease, mental illnesses, trauma, and all-cause mortality, this reluctance for firm doctor-patient discussion might stem from multiple reasons. The responsible enjoyment of alcohol by cognitive elites (such as physicians), the muddied water from biased research on the benefits of moderate drinking, or a reluctance to sound puritanical might be some reasons that are worthy of further exploration.35-37 Overall, as is clear even within the existing restrictions of routine practice, there is plenty of room for improvement in the care of hypertensive patients. Pragmatic trials of interventions to drive change, such as the use of educational programs to enhance a physician's ability to dispense advice, as recommended by Liu et al,21 is the need of the hour. SH receives research salary support from the Department of Medicine, University of Ottawa. The ideas expressed in this editorial reflect many conversations over the years with Professors Marcel Ruzicka and George Fodor.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesIntégrité de la recherche
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,066
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0040,002
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0020,008
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,082
Tête enseignante GPT0,367
Écart entre enseignants0,285 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2018
Routes d'admission3
Résumé présentoui

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