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Emergency care providers perspectives of acute pain assessment and management in the prehospital setting, in the Western Cape, South Africa: A qualitative study
دیدگاه های ارائه دهندگان مراقبت های اورژانس ارزیابی درد و مدیریت درد حاد در محیط پیش دبستانی، در کیپ غربی، آفریقای جنوبی: یک مطالعه کیفی-2021 Introduction: A growing body of evidence suggests that pain knowledge and management are poor, perhaps more
so in the prehospital setting. The daily challenges that emergency care providers face in dealing with prehospital
pain remain unclear. This study aimed to gain a deeper understanding of acute prehospital pain assessment and
management in the Western Cape, South Africa.
Methods: A series of focus group discussions, using a constructivist paradigm and qualitative content analysis
were conducted.
Results: The key themes emerging from six focus groups (total 25 emergency care providers) related to the
difficulties of assessing pain in this setting, factors affecting clinical reasoning in this (hostile) setting, the re-
alities of prehospital pain care for non-advanced life support practitioners, along with emergency departments’
lack of understanding and appreciation of the prehospital environment, and participants’ suggestions to improve
pain practice.
Conclusion: Several barriers and enablers, some novel, to pain assessment and management in the South African
prehospital setting were identified. Our findings provide valuable insight and understanding of the challenges
related to pain care prehospital providers face, in other similar prehospital settings, but also to the global body of
knowledge on prehospital barriers and enablers of pain assessment and management. keywords: پیش بیمارستان | آمبولانس (مش) | خدمات اورژانس پزشکی (مش) | درد حاد (مش) | اندازه گیری درد (مش) | ضد درد (مش) | Prehospital | Ambulances (MeSH) | Emergency Medical Services (MeSH) | Acute pain (MeSH) | Pain Measurement (MeSH) | Analgesics (MeSH) |
مقاله انگلیسی |
2 |
Knowledge in pre-hospital emergency and risk management among outdoor adventure practitioners in East Africa afro-alpine mountains
دانش در اورژانس قبل از بیمارستان و مدیریت ریسک در میان تمرینکنندگان ماجراجویی در فضای باز در کوه های آفریقای شرقی آفریقا-2021 Introduction: The enjoyment of nature and other benefits of outdoor activities happen amid inherent hazards. This
calls for knowledge and competency in emergency and risk management. Practitioners in outdoor activities, such
as mountaineering, thus need to be knowledgeable on how to manage risks and attend to emergencies in their
practice. The study sought to establish the preparedness of East African mountaineering practitioners in pre-
hospital emergency and risk management. It sought to establish their knowledge on prehospital emergency and
risk management, based on their age, gender, level of education and refresher training.
Methods: The study purposively sampled one hundred and thirty six (N = 136) outdoor adventure practitioners
from the Afro-alpine mountain areas in East Africa. It was hypothesized that there would be no significant
relationship between the outdoor practitioners’ knowledge in prehospital emergency risk management and their
age, gender, level of education, refresher training. Somers’ d was used to test the hypotheses.
Results: It was established that the knowledge scores of prehospital emergency and risk management for the
mountaineering practitioners was low. It was also established that the knowledge scores of outdoor practitioners
were not dependent on their age, gender, and work experience. However, there was a significant relationship
between the outdoor adventure practitioners’ knowledge scores and their highest level of education as well as
refresher training.
Conclusions: The study concluded that there were gaps in the knowledge of prehospital risk management of the
East African Afro-alpine mountaineering practitioners. It recommends frequent and regular training and re-
certification among outdoor adventure practitioners in order to raise the knowledge in prehospital emergency
risk management.
African relevance
• Identifying prehospital emergency care knowledge by African out-
• Prehospital emergency care is not emphasized in the outdoor
• With inaccessible health care in African outdoors, there is need for
door practitioners can guide planning for training.
adventure practice in many African settings.
knowledge in prehospital emergency risk management. keywords: دانش | پیش بیمارستان | اضطراری | کوهنوردی | ماجرا | در فضای باز | Knowledge | Prehospital | Emergency | Mountaineering | Adventure | Outdoor |
مقاله انگلیسی |
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Outcome prediction of out-of-hospital cardiac arrest with presumed cardiac aetiology using an advanced machine learning technique
پیش بینی نتیجه ایست قلبی خارج از بیمارستان با اتیولوژی قلب فرضی با استفاده از یک روش پیشرفته یادگیری ماشین-2019 Background: Outcome prediction for patients with out-of-hospital cardiac arrest (OHCA) has the possibility to detect patients who could have been
potentially saved. Advanced machine learning techniques have recently been developed and employed for clinical studies. In this study, we aimed to
establish a prognostication model for OHCA with presumed cardiac aetiology using an advanced machine learning technique.
Methods and Results: Cohort data from a prospective multi-centre cohort study for OHCA patients transported by an ambulance in the Kanto area of
Japan between January 2012 and March 2013 (SOS-KANTO 2012 study) were analysed in this study. Of 16,452 patients, data for OHCA patients aged
18 years with presumed cardiac aetiology were retrieved, and were divided into two groups (training set: n = 5718, between January 1, 2012 and
December 12, 2012; test set: n = 1608, between January 1, 2013 and March 31, 2013). Of 421 variables observed during prehospital and emergency
department settings, 35 prehospital variables, or 35 prehospital and 18 in-hospital variables, were used for outcome prediction of 1-year survival using a
random forest method. In validation using the test set, prognostication models trained with 35 variables, or 53 variables for 1-year survival showed area
under the receiver operating characteristics curve (AUC) values of 0.943 (95% CI [0.930, 0.955]) and 0.958 (95% CI [0.948, 0.969]), respectively.
Conclusions: The advanced machine learning technique showed favourable prediction capability for 1-year survival of OHCA with presumed cardiac
aetiology. These models can be useful for detecting patients who could have been potentially saved. Keywords: Out-of-hospital cardiac arrest |Resuscitation | Outcome prediction | Machine learning |
مقاله انگلیسی |