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Enregistrement W4289745469 · doi:10.1111/cns.13931

To use stroke 911 to improve stroke awareness for countries where 911 is used as an emergency phone number

2022· editorial· en· W4289745469 sur OpenAlexaboutno aff
Renyu Liu, Jing Zhao, Xiaobin Li, Steven R. Messé, Marc Fisher, Anthony Rudd

Notice bibliographique

RevueCNS Neuroscience & Therapeutics · 2022
Typeeditorial
Langueen
DomaineMedicine
ThématiqueAcute Ischemic Stroke Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésStroke (engine)PhoneMedical emergencyMedicineEmergency medicineEngineering

Résumé

récupéré en direct d'OpenAlex

In 2020, stroke ranked as the third cause of death from non-communicable diseases (except injury) in the United States.1 World Health Organization data from 2019 indicated that stroke is the number two cause of death worldwide. Stroke is a preventable and now eminently treatable disease. However, partly due to poor awareness and significant prehospital delay, the majority of people with ischemic stroke arrive too late to receive available treatments like thrombolysis and thrombectomy, as these treatments are available only within certain time frame after a stroke. The acronym FAST (Face, Arm, Speech, and Time) is the most popular and effective tool for stroke awareness and recognition, predominantly for the English-speaking populations. However, as with any acronym, FAST does not effectively translate in a way for easy remembering for non-English speakers and the meaning of “fast action” may be lost. While English is the most spoken language followed by Chinese worldwide, only 400 million are native English speakers among approximately 7.8 billion people. To overcome the language barrier, we have proposed novel strategies that use emergency phone numbers as mnemonic tools for stroke signs and symptoms, including Stroke 120, Stroke 112, and Stroke 911.2-4 These strategies are based on the core concept of “FAST”. The acceptance and effectiveness of Stroke 120 and Stroke 112 have been demonstrated.3, 5 Here, we present a modified stroke 911 strategy to improve stroke awareness for countries and regions where 911 is used as an emergency phone number, especially for those whose first native language is not English as indicated in Figure 1.2 The major modification is to ask the potential stroke victim to repeat 911 to check speech disturbance in any language instead of asking spelling N-I-N-E to check speech disturbance. The advantages of the system include (1) it is based on the well-accepted stroke recognition FAST strategy; (2) it overcomes the language barrier since people do not need to remember all of the English words needed for the acronym of FAST; (3) It links the emergency phone number 911 to the common stroke signs and symptoms; and, (4) It can be translated into any language for educational purposes without losing its core meaning for stroke recognition and immediate action. A recent study indicated that Asian American patients manifested more severe ischemic strokes, were less likely to receive “clot buster” therapies such as IV tPA and had worse functional outcomes than white patients.6 For those with a verified onset to arrival time, Asian American patients took longer on average to arrive at the hospital after ischemic stroke onset (mean, 554.3 min) than white patients (mean, 471.5 min). Also, a lower percentage of Asian American patients than white patients arrived within 4.5 h from stroke onset (51.5% vs. 57.5%), which is the time window most patients could be treated with a thrombolytic. Stroke treatment is exquisitely time-sensitive. Delays to arrival and assessment are associated with a lower likelihood of being treated, and a lower likelihood of a good outcome among those who do receive treatment.7-9 Thus, delay in hospital arrival is one of the main reasons that Asians have worse outcomes from stroke than white patients. Racial and ethnic minority groups have been shown to have less knowledge about stroke, which could lead to disparities in timely stroke hospital presentation. Cultural tailoring of stroke education may, therefore, be an effective approach to improve stroke outcomes. The estimated number of Asian Americans is about 24 million. Chinese, Indian, and Filipino Americans make up the largest share of the Asian American population with 5, 4.3, and 4 million people, respectively, representing a diversity of languages. Among these different languages, there were 2.8 million people (age five and older) who spoke one of the Chinese dialects at home. Chinese is the third most common language in the United States. Based on the US Department of Health and Human Services Office of Minority Health, 42.0% percent of Chinese over the age of five who live in the United States do not speak English very well. Therefore, it is reasonable to first target the Chinese community using the Chinese language and a culture-adapted approach to improve stroke awareness and promote the immediate action of calling 911 to reduce stroke-related mortality and morbidity. As indicated in Figure 1B,C, we have translated the tool into both simplified Chinese and traditional Chinese. The tool has received enthusiastic support from our colleagues with native language capability to translate this tool to other languages. These include Japanese by Akira Nishisaki, MD; Korean by Si Ju Kim, CRNA, Vietnamese by Bao Ha, MD; Hmong by Kia Lor, MD; Hindi by Deepa Chen. You may contact Dr. Renyu Liu to obtain these materials or help us to translate these materials for other languages. To help implement the educational program we produced a short video for Stroke 911, which is available to the public via YouTube.10 The poster introduction is presented in Figure 2. After demonstrating the effectiveness in the US Chinese community we plan to expand to other minority communities by using a similar approach, adapting it to their unique languages and cultures, focusing on those communities with the lowest English proficiency. The proposed approach could potentially be implemented as professional guidelines for policy-making purposes to improve the health of minority populations and reduce disparity. Based on the World Population Review, 48 countries and regions including USA use 911 to call an emergency ambulance. Similar to the USA, Canada has a diversity of native languages. More than 40% of Canadian's native language is not English. Therefore, it is highly possible that this strategy could be used in other countries and regions with a simple translation. The Coalition of the Special Taskforces for Stroke (CSTS) will make the effort to achieve this. We will make all the educational materials available online through CSTS official website. National Natural Science Foundation of China; CIHR, Grant/Award Number: 81973157, PI: JZ. Funding from the University of Pennsylvania; Grant/Award Number: CREF-030, PI: RL. All authors have no conflict of interest to declare. The data that support the findings of this study are available from the corresponding author upon reasonable request.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,385
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0020,001
Intégrité de la recherche0,0010,001
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 Opus0,040
Tête enseignante GPT0,346
Écart entre enseignants0,306 · 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 tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

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

En bref

Citations8
Publié2022
Routes d'admission1
Résumé présentoui

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