Frail by four different measures and new adverse events from lower blood pressure control in hypertensive older adults: a 2-year prospective study in The Irish Longitudinal Study on Ageing (TILDA)
Notice bibliographique
Résumé
Abstract Background The 2018 European Society of Cardiology/European Society of Hypertension (ESC/ESH) guidelines for management of hypertension in adults aged ≥65 years recommend a blood pressure (BP) treatment target of 130–139/70–79 mmHg if tolerated [1]. Randomised controlled trials have advocated for lower BP, but this may lead to adverse outcomes in the frail. Yet, different operationalisations of frailty exist in the literature [2,3]. Purpose We compared four frailty classifications in their ability to predict 2-year incident adverse outcomes (falls/fractures, syncope, transient ischaemic attack/stroke, heart attack, heart failure, hospitalisation, and mortality) associated with below-target BP control (<130/70 mmHg) in The Irish Longitudinal Study on Ageing (TILDA). Methods Data from participants aged ≥65 years treated for hypertension in Wave 1 (W1) was analysed. Frailty was identified by Frailty Phenotype (FP) [4], the Clinical Frailty Scale-classification tree (CFS) [5], a 32-item self-reported Frailty Index (FI) [6], and the 5-item FRAIL (Fatigue, Resistance, Ambulation, Illnesses & Loss of Weight) scale [7]. We formulated 16 participant groups at W1 based on frailty-BP combinations. Outcomes at wave 2 (W2) two years later were analysed with binary logistic regression models adjusted for age, sex, education, polypharmacy, classic orthostatic hypotension, Montreal Cognitive Assessment (MOCA) score and number of chronic diseases. Results Of 1920 W1 participants aged ≥65 years and treated for hypertension, 1229 had full BP/FP data, 1282 for BP/CFS, 1274 for BP/FI, and 1276 for BP/FRAIL. The non-frail groups in all 4 frailty classifications with BP treated below or above target did not have an increased risk of any of the adverse health outcomes at W2. For the frail treated below target, hospitalisation by W2 was significantly more likely in those who were frail by FP and FRAIL. The frail by FRAIL and BP treated below target were the only with increased risk of mortality by W2. The frail by FI and FRAIL with BP treated below target had increased risk of new heart failure and falls/fractures by W2. Conclusions Frailty was independently associated with adverse outcomes in hypertensive older adults treated below the ESC/ESH target. However, different frailty classifications had different prognostic implications. For those below BP target, frailty by FRAIL was associated with the highest number of risks (falls/fractures, heart failure, hospitalisation and mortality), followed by the frail by FI (falls/fractures, heart failure). Based on our results and frailty measures considered, we recommend that FRAIL and FI are regarded as the methods of choice to identify frailty when applying the ESC/ESH guideline. Models of frailty that do not explicitly measure comorbidities (such as FP and CFS) may be less useful to capture risk of adverse events from lower blood pressure control. Funding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): Irish Department of HealthIrish LifeAtlantic PhilanthropiesRoman Romero-Ortuno is funded by a grant from Science Foundation Ireland
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».