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Enregistrement W2160823290 · doi:10.1093/qjmed/hcr043

The missing ethnicity in primary cardiovascular trials

2011· letter· en· W2160823290 sur OpenAlexafffund
Gustavo Saposnik

Notice bibliographique

RevueQJM · 2011
Typeletter
Langueen
DomaineMedicine
ThématiqueLipoproteins and Cardiovascular Health
Établissements canadiensResearch CanadaUniversity of TorontoSt. Michael's Hospital
Organismes subventionnairesCanadian Institutes of Health Research
Mots-clésMedicineStroke (engine)Incidence (geometry)Ethnic groupDiseaseDiabetes mellitusMyocardial infarctionInternal medicineDemographyGerontology

Résumé

récupéré en direct d'OpenAlex

Success is going from failure to failure without a loss of enthusiasm Winston Churchill (1874–1965) British politician and statesman Cardiovascular disease (CVD) is the most common and one of the most preventable causes of death worldwide. The incident risk of stroke, myocardial infarction and peripheral vascular disease vary among ethnic groups. For example, individuals with African or Caribbean background have a high incidence of stroke and end-stage renal failure compared with Caucasians. On the other hand, South Asians have higher incidence of CVD.1,2 The recently published guidelines for the primary stroke prevention highlighted the increased age-adjusted prevalence of stroke in Asian (1.8%/100 000), Blacks (4.6%/100 000) and Hispanics (1.9%/100 000) compared with whites.3 The underlying causes of these disparities are not well understood. Differences in dietary and genetic factors, prevalence of hypertension, diabetes, or dyslipidemia and the response to preventative treatment are some commonly attributed determinants.3 More interestingly, the Framingham score may underestimate the 10-year risk of CVD in some ethnic groups (e.g. South-Asians), as the data (over 20 years old) are mostly derived from Caucasians middle class North American population with limited ethnic representation or individuals from low socioeconomic subgroups.4,5 In this issue of QJ Med, Minocher Homji et al.6 conducted a systematic review that aims at identifying the proportion of immigrants and different ethnic groups reported in randomized clinical trial (RCTs) in primary cardiovascular prevention. Data sources included MEDLINE, EMBASE and Cochrane databases between 1980 and December 2009. Selection criteria also include studies with at least 100 participants. Among 44 RCTs that met the inclusion criteria, 10 [22.2%, 95% confidence interval (CI) 12.4–36.5] included and/or reported on the ethnic status of the participants (n = 130 969). Overall, the weighted proportion of non-white participants was 10.7% (95% CI 6.9–16.2), whereas Asian or Asian Pacific ancestry comprised 2.2% (95% CI 1.1–4.7) in the four trials that reported the ethnic background. Interestingly, no study analyzed the efficacy of the intervention stratified by ethnicity, and none reported on the number of participants who were immigrants. The risk of myocardial infarction, stroke and peripheral vascular disease vary among different ethnic groups. As known, the efficacy of different therapeutic alternatives differs among Caucasians, Blacks, Hispanics, African-Americans, South-Asians, etc. For example, the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT-BPLA) analyzed the effect of adding thiazide or perindopril to unchanged monotherapy (atenolol or amlodipine). Blood pressure levels in Black (n = 203) patients were significantly less responsive (mean systolic difference +1.7 mmHg) compared with White patients of European countries (n = 4368).7 Similarly, heart failure was significantly more common among Black than non-Black hypertensive patients (hazard ratio 2.30, 95% CI 1.24–4.28).8,9 Therefore, it is important to clearly describe the population target by also including the ethnic background in randomized clinical trials in CVD and cerebrovascular disease. The authors also argue that recent immigrants may differ from native born in dietary practices, and lower incident risk of vascular risk factors such as hypertension. The so-called ‘healthy immigrant effect’ may also affect the results of interventional trials. This may be an issue considering the lower expected absolute risk reduction due to the high pre-recruitment prevalence (and efficacy) of participants on combined antithrombotic, antihypertensive and lipid-lowering therapy in cardiovascular trials. Limitations to this study (and acknowledged by the authors) include publications only in the English literature. Publication bias, common to all systematic reviews, cannot be ruled out. Nevertheless, major trials in cardiovascular prevention have been included, and the potential exclusion of studies (likely smaller) published in other languages than English or non-indexed journals are unlikely to change these results. In the future, clinicians, readers, policymakers and editors should be aware of the scope of the trial and the specific efficacy of the interventions in primary and secondary cardiovascular prevention across ethnic groups. Heart and Stroke Foundation of Canada; Canadian Institutes for Health Research; Department of Research at St Michael’s Hospital and Connaught Foundation (University of Toronto) to G.S. Conflicts of interest: The authors report no commercial conflicts of interest. G.S. receives salary support from the Clinician-Scientist Award from the Heart and Stroke Foundation of Ontario.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,026
score de la tête « metaresearch » (Gemma)0,118
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,974
Score d'incertitude au seuil0,135

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0260,118
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0030,001
Bibliométrie0,0020,003
Études des sciences et des technologies0,0030,003
Communication savante0,0060,005
Science ouverte0,0020,002
Intégrité de la recherche0,0250,019
Charge utile insuffisante (le modèle a refusé de juger)0,0180,013

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 Opus0,076
Tête enseignante GPT0,297
Écart entre enseignants0,221 · 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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeObservationnel
DomaineMéthodes
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

Citations1
Publié2011
Routes d'admission2
Résumé présentoui

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