Bystander cardiopulmonary resuscitation and automated external defibrillator use after out-of-hospital cardiac arrest: uncovering differences in care and survival across the urban-rural spectrum
Notice bibliographique
Résumé
Abstract Background Despite regional variation in survival following out-of-hospital cardiac arrest (OHCA), few studies have investigated urban-rural differences in the provision of care and outcomes after OHCA. To better understand the role of pre-hospital care across the urban-rural spectrum, we compared the effects of bystander cardiopulmonary resuscitation (CPR) and automated external defibrillator (AED) use on survival after OHCA between geographical settings. Methods This retrospective study (2013–2019) used all adult, non-traumatic, and treated OHCAs registered in the Cardiac Arrest Registry to Enhance Survival. The urban/rural status of arrest locations were classified at the census tract level as urban, suburban, large rural, small town, or rural, using the Rural-Urban Commuting Area classification system (Figure). Bystander interventions were grouped into three categories, including no bystander intervention, bystander CPR alone, and bystander AED use (with CPR). The primary outcome of interest was survival to hospital discharge with good neurological outcome. Multivariable logistic regression models were developed to assess the association between bystander interventions and survival with good neurological outcome by urban/rural status, adjusting for relevant covariates. Results A total of 325,281 patients were included. Bystander CPR alone occurred most often in rural areas (50.8%), and least often in urban areas (35.4%). Bystander AED use varied by urban/rural status (1.7%-2.9%), with large rural (2.9%) and rural areas (2.4%) reporting the highest rates. Survival to hospital discharge with good neurological outcome differed for urban (8.1%), suburban (7.7%), large rural (9.1%), small town (7.1%), and rural areas (6.1%). In all areas, patients who received bystander AED use or bystander CPR alone were more likely to achieve survival with good neurological outcome than patients who received no bystander intervention. The effect of bystander AED use on survival was stronger than bystander CPR alone in urban, suburban, and rural areas (no overlap of confidence bands), whereas no significant differences between these two bystander intervention groups were observed in large rural areas or small towns (overlap of confidence bands) (Table). Conclusions Bystander CPR and AED use are critical components of the response to OHCA across the urban-rural spectrum. The relative impact of bystander interventions on survival varied based on the geographical location of arrests, despite adjusting for numerous potential confounding variables, such as response time. It is possible that unmeasured factors, such as time from collapse to bystander intervention, patient factors, AED accessibility, and CPR quality are contributing to these observed differences. Future research is needed to better understand the response to OHCA across the urban-rural spectrum, which may inform policies for community-specific emergency protocols and planning. Funding Acknowledgement Type of funding sources: None.
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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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».