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Enregistrement W7023669661

Performance of activities of daily living after surviving a cardiac arrest

2025· other· en· W7023669661 sur OpenAlexaboutno aff

Notice bibliographique

Revuenon disponible
Typeother
Langueen
DomaineMedicine
ThématiqueCardiac Arrest and Resuscitation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésActivities of daily livingQuality of life (healthcare)Myocardial infarctionCardiopulmonary resuscitationEmergency medical servicesEmergency departmentCohortResuscitation
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Introduction: Out-of-hospital cardiac arrest (OHCA) is a major medical emergency with high mortality rates and significant long-term consequences for survivors. Advances in resuscitation and acute care have improved survival, yet many survivors face challenges after hospital discharge, related to activities of daily living (ADL) ability, the health-related quality of life (HRQoL), and the return to work. While previous research has largely focused on survival rates, physical and neurological outcomes, less attention has been given to outcomes beyond mortality and body structure impairments. Additionally, there is limited knowledge on the societal costs associated with OHCA survivors, including healthcare expenses and work absenteeism, making it essential to investigate these aspects. This dissertation aimed to investigate the impact of OHCA on survivors and society. More specifically, the aims were to: I. To describe the ADL ability among OHCA survivors at hospital discharge, examine characteristics of those with decreased ADL ability, and the changes in ADL ability over time. II. To assess whether ADL ability and cognitive function at hospital discharge are associated with post-discharge ADL ability, HRQoL and return to work. III. To evaluate the costs of OHCA survivors from a societal perspective, and to compare these costs to the costs of individuals with non-cardiac arrest myocardial infarction and individuals with no cardiac diseases. Methods: The dissertation comprised two studies investigating multiple aspects of OHCA consequences. Study I was a prospective clinical cohort study including 200 OHCA survivors, measuring self-reported and observed ADL ability from Activities of Daily Living Interview (ADL-I) and Assessment of Motor and Process Skills (AMPS) at hospital discharge and six months post-arrest. Cognitive function was assessed with Montreal Cognitive Assessment (MoCA) at discharge. Both personal ADL-I (PADL-I) and age-matched AMPS at discharge - alongside MoCA cut-off scores- were included as independent variables in association analyses with post-discharge ADL ability, HRQoL and return to work. Data were analysed using descriptive statistics and regression models, and missing data were handled with multiple imputation. Study II was a cost-of-illness study based on data from Danish national registers, estimating costs of healthcare utilisation and work absenteeism among 5,646 OHCA survivors compared to two matched control groups: a group with individuals with myocardial infarction and a group with individuals with no cardiac disease. Health care costs from the primary and secondary sector were included, alongside costs of sick leave, vocational rehabilitation, disability pension and unemployment. These costs were tracked over a six-year period, from one year before the cardiac arrest up to five years post-arrest. Results: In study I, a substantial proportion of OHCA survivors had decreased ADL ability at hospital discharge and six-months post-arrest, with those with below age norms having lower measures compared to survivors with age-matched ADL ability, both at discharge and at six-months follow-up. Both self-reported PADL-I and observed age-matched AMPS showed a statistically significant association with post-discharge ADL ability and HRQoL, whereas MoCA was significantly associated with HRQoL index scores only. Neither PADL-I, AMPS nor MoCA at discharge showed a statistically significantly association with return to work, although MoCA approached. In study II, healthcare costs for OHCA survivors were significantly higher than those of matched controls. The highest costs were observed in the first-year post-arrest with hospital costs accounting for the main economic burden. From the second year onwards, the economic burden shifted towards work absenteeism, with sick leave being the highest cost and later also disability pension. Conclusion: Early assessment, prior to hospital discharge, revealed decreased observed and self-reported ADL ability and despite some improvements during six months, a noteworthy proportion of participants were still challenged in daily and weekly tasks. Following this, OHCA survivors with an ADL ability below age-norm at hospital discharge had lower self-reported and observed ADL measures both at discharge and six months post-arrest compared to survivors with an age-matched ability at discharge. ADL measures and cognitive screening at hospital discharge showed potential as markers when identifying OHCA survivors at risk of poor post-discharge ADL ability and HRQoL. However, when identifying survivors at risk of not returning to work, additional factors should be considered. OHCA survivors have substantial costs related to health care use and work absenteeism, even when compared to MI controls and non-CD controls. Hospital costs were highest in the first-year post-arrest, but from the second-year sick leave accounted for the main economic burden, and later also disability pension.

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)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,025

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0080,001

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 Opus0,006
Tête enseignante GPT0,238
Écart entre enseignants0,232 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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