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Guthrie Galbraith posted an update 6 months, 2 weeks ago
Globally, there has been an increase in the survival rate and the average age of survivors from out-of-hospital cardiac arrest (OHCA). However, little is known about the joint OHCA-associated experiences among older survivors and their spouses in a long-term perspective. The aim of this study was to explore how narrative sense-making processes following OHCA shapes everyday life in a long-term perspective among older survivors and their spouses.
Five older male survivors and their female spouses were interviewed individually using narrative methods. Arthur Frank’s theory on illness narratives informed the analysis. Participant observation at two meetings for survivors and relatives regarding cardiac arrest was used for qualification of the interview guide.
Five married couples participated. The mean age of the survivors and spouses was 70,4 and 71,4 years respectively, and time since OHCA varied from 12 to 66 months. Two themes of the dyadic experience emerged 1) experiences during OHCA, and 2) experiences in life following OHCA. Subthemes differed with survivors emphasising a desire to return to the same life as before the OHCA, and the spouses narrating feelings of anxiety. Potential complications of the OHCA were often explained with reference to ageing processes, and the OHCA was contextualised in relation to previous life-changing events.
In a long-term perspective, OHCA shapes the life trajectory of both the survivor and the spouse, and the relationship between them, underscoring a need for patient-centred care with a greater focus on the relationship of the dyads.
In a long-term perspective, OHCA shapes the life trajectory of both the survivor and the spouse, and the relationship between them, underscoring a need for patient-centred care with a greater focus on the relationship of the dyads.
The aim of this study was to assess the perceptions of medical students with respect to out-of-hospital cardiac arrests focusing on the frequency and survival and to identify potential problems in resuscitation education.
Fourth-year medical students in a six-year undergraduate educational system were asked to guess the number of out-of-hospital cardiac arrests with cardiac etiology per year in Japan, related data such as the one-month survival rate from out-of-hospital cardiac arrests with cardiac etiology and the number of deaths from traffic accidents for comparison. The guesses of students were compared with actual statistical data.
The incidence of out-of-hospital cardiac arrests was clearly underestimated by the students compared to the real statistics. The median guessed number of out-of-hospital cardiac arrests ranged from 6000 to 20,000 while the real statistics ranged from 73.023 to 78.302 by year (P<0.001 for all years). In contrast, the guessed number of deaths from traffic accidents was markedly overestimated the median guessed number ranged from 8000 to 20,000 and the real statistics were 3694 to 4438 (P<0.001 for all years). The one-month survival rate was also underestimated the guessed number was 50% and the real rate was 11.5 to 13.5% (P<0.001 for all years).
Out-of-hospital cardiac arrests are underestimated in frequency, and survival after an arrest is overestimated by medical students. To recognize and to understand the heuristic bias in perception of learners is needed for resuscitation education in addition to promote resuscitation skills of learners.
Out-of-hospital cardiac arrests are underestimated in frequency, and survival after an arrest is overestimated by medical students. To recognize and to understand the heuristic bias in perception of learners is needed for resuscitation education in addition to promote resuscitation skills of learners.
A patient’s survival from cardiac arrest is improved if they receive good quality chest compressions as soon as possible. During cardiopulmonary resuscitation (CPR) training subjective assessments of chest compression quality is still common. Recently manikins allowing objective assessment have demonstrated a degree of variance with Instructor assessment. The aim of this study was to compare peer-led subjective assessment of chest compressions in three groups of participants with objective data from a manikin.
This was a quantitative multi-center study using data from simulated CPR scenarios. Seventy-eight Instructors were recruited, from different backgrounds; lay persons, hospital staff and emergency services personnel. Each group consisted of 13 pairs and all performed 2min of chest compressions contemporaneously by peers and manikin (Brayden PRO®). The primary hypothesis was subjective and objective assessment methods would produce different test outcomes.
13,227 chest compressions were assessed. T
We evaluated the feasibility of optimising coronary perfusion pressure (CPP) during cardiopulmonary resuscitation (CPR) with a closed-loop, machine-controlled CPR system (MC-CPR) that sends real-time haemodynamic feedback to a set of machine learning and control algorithms which determine compression/decompression characteristics over time.
American Heart Association CPR guidelines (AHA-CPR) and standard mechanical devices employ a “one-size-fits-all” approach to CPR that fails to adjust compressions over time or individualise therapy, thus leading to deterioration of CPR effectiveness as duration exceeds 15-20min.
CPR was administered for 30min in a validated porcine model of cardiac arrest. Intubated anaesthetised pigs were randomly assigned to receive MC-CPR (6), mechanical CPR conducted according to AHA-CPR (6), or human-controlled CPR (HC-CPR) (10). MC-CPR directly controlled the CPR piston’s amplitude of compression and decompression to maximise CPP over time. In HC-CPR a physician controlled the piston amplitudes to maximise CPP without any algorithmic feedback, while AHA-CPR had one compression depth without adaptation.
MC-CPR significantly improved CPP throughout the 30-min resuscitation period compared to both AHA-CPR and HC-CPR. CPP and carotid blood flow (CBF) remained stable or improved with MC-CPR but deteriorated with AHA-CPR. HC-CPR showed initial but transient improvement that dissipated over time.
Machine learning implemented in a closed-loop system successfully controlled CPR for 30min in our preclinical model. MC-CPR significantly improved CPP and CBF compared to AHA-CPR and ameliorated the temporal haemodynamic deterioration that occurs with standard approaches.
Machine learning implemented in a closed-loop system successfully controlled CPR for 30 min in our preclinical model. https://www.selleckchem.com/products/gsk650394.html MC-CPR significantly improved CPP and CBF compared to AHA-CPR and ameliorated the temporal haemodynamic deterioration that occurs with standard approaches.
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