Deliberate practice in resuscitation training using a feedback device, and the effects of the physical characteristics of the rescuer on the acquisition and retention of cardiopulmonary resuscitation skills: Randomized clinical trial.

BACKGROUND: Cardiopulmonary resuscitation (CPR) skills decline rapidly and rescuers' physical characteristics could impact on their performance. Our aim was to analyse the effects of deliberate practice using a feedback device (FD) on the CPR performance of nursing students prior to, immediately after, and three months after training, considering their physical characteristics. METHOD: Sixty nursing students participated in this randomized clinical trial (control group n = 28; training group n = 32). Their physical characteristics (weight, height, forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC)% index, handgrip strength, and CPR position strength) were measured before starting the trial. The training group followed a CPR training programme based on deliberate practice, providing feedback on their performance using an FD. All participants were evaluated during two-minute CPR compression/ventilation cycles. RESULTS: The training group showed an improved ability to perform chest compressions (F(2, 115.2) = 13.3; p < .001; ω2p = 0.17) and ventilations (F(2, 115.3) = 102.1; p < .001; ω2p = 0.63), improving their overall quality of CPR (F(2, 115.2) = 40.1; p < .001; ω2p = 0.40). The physical characteristics of the participants did not affect CPR performance in any study phase. CONCLUSIONS: A structured training programme based on deliberate practice using an FD had a positive effect on the acquisition of CPR skills by participants, while their physical characteristics had no impact on performance.

Comparing formative and summative simulation-based assessment in undergraduate nursing students: nursing competency acquisition and clinical simulation satisfaction.

BACKGROUND: Formative and summative evaluation are widely employed in simulated-based assessment. The aims of our study were to evaluate the acquisition of nursing competencies through clinical simulation in undergraduate nursing students and to compare their satisfaction with this methodology using these two evaluation strategies. METHODS: Two hundred eighteen undergraduate nursing students participated in a cross-sectional study, using a mixed-method. MAES© (self-learning methodology in simulated environments) sessions were developed to assess students by formative evaluation. Objective Structured Clinical Examination sessions were conducted to assess students by summative evaluation. Simulated scenarios recreated clinical cases of critical patients. Students´ performance in all simulated scenarios were assessed using checklists. A validated questionnaire was used to evaluate satisfaction with clinical simulation. Quantitative data were analysed using the IBM SPSS Statistics version 24.0 software, whereas qualitative data were analysed using the ATLAS-ti version 8.0 software. RESULTS: Most nursing students showed adequate clinical competence. Satisfaction with clinical simulation was higher when students were assessed using formative evaluation. The main students' complaints with summative evaluation were related to reduced time for performing simulated scenarios and increased anxiety during their clinical performance. CONCLUSION: The best solution to reduce students' complaints with summative evaluation is to orient them to the simulated environment. It should be recommended to combine both evaluation strategies in simulated-based assessment, providing students feedback in summative evaluation, as well as evaluating their achievement of learning outcomes in formative evaluation.

Real-World Data and Machine Learning to Predict Cardiac Amyloidosis.

(1) Background: Cardiac amyloidosis or "stiff heart syndrome" is a rare condition that occurs when amyloid deposits occupy the heart muscle. Many patients suffer from it and fail to receive a timely diagnosis mainly because the disease is a rare form of restrictive cardiomyopathy that is difficult to diagnose, often associated with a poor prognosis. This research analyses the characteristics of this pathology and proposes a statistical learning algorithm that helps to detect the disease. (2) Methods: The hospitalization clinical (medical and nursing ones) records used for this study are the basis of the learning and training techniques of the algorithm. The approach consisted of using the information generated by the patients in each admission and discharge episode and treating it as data vectors to facilitate their aggregation. The large volume of clinical histories implied a high dimensionality of the data, and the lack of diagnosis led to a severe class imbalance caused by the low prevalence of the disease. (3) Results: Although there are few patients with amyloidosis in this study, the proposed approach demonstrates that it is possible to learn from clinical records despite the lack of data. In the validation phase, the algorithm first acted on data from the general study population. It then was applied to a sample of patients diagnosed with heart failure. The results revealed that the algorithm detects disease when data vectors profile each disease episode. (4) Conclusions: The prediction levels showed that this technique could be useful in screening processes on a specific population to detect the disease.

Reversible causes of cardiac arrest: Nursing competency acquisition and clinical simulation satisfaction in undergraduate nursing students.

BACKGROUND: It is essential to determine and treat the reversible causes of cardiac arrest, so emergency nurses must acquire the competencies needed for its adequate management. METHOD: 106 undergraduate nursing students participated in a cross-sectional study, using a mixed-method. Simulated scenarios recreated critically ill patients with diagnoses of potentially reversible causes of cardiac arrest in an emergency room. An internally validated questionnaire was used to analyse students' satisfaction and perceptions about clinical simulation sessions. Nursing competencies were assessed using a verification list. Data were analysed using the IBM SPSS Statistics version 24.0 (quantitative data) and ATLAS-ti version 8.0 (qualitative data) software. RESULTS: Nursing students expressed a high level of satisfaction (most of the scores obtained were higher than 90%) and positive perceptions about clinical simulation sessions. Most of the students (85.6%) acquired the necessary nursing competencies for adequate management of the reversible causes of cardiac arrest. CONCLUSION: Clinical simulation methodology is a useful tool for the learning process and acquisition of nursing competencies related to emergency situations management. This methodology prepares nursing students for their clinical placements and future careers in emergency care. Therefore, it is recommended to extend clinical simulation training to emergency qualified nursing staff and advanced practitioners.

Quality of cardiopulmonary resuscitation: Degree of agreement between instructor and a feedback device during a simulation exercise.

BACKGROUND: High-quality cardiopulmonary resuscitation (CPR) saves lives after a cardiorespiratory arrest. Currently used feedback devices (FD) provide accurate information on CPR quality during training. However, there is no consensus in previous studies that have compared FD to the feedback provided by an instructor and most show methodological limitations. This study aimed to analyse the degree of agreement between an FD and an instructor in the assessment of high-quality CPR. METHOD: 60 undergraduate nursing students participated in a descriptive observational study. Variables related to the quality of chest compressions (CC) and ventilation were recorded. Students were evaluated during 2-minute compression/ventilation cycles by an expert instructor and using the CPR training torso, Little Anne™ QCPR (Laerdal Medical) with its associated QCPR Instructor App software for iOS. RESULTS: The degree of agreement between instructor and FD assessments was moderate-good: CC rate per minute (Intracass correlation coeficiente [ICC] = 0.791), complete chest recoil (ICC = 0.437); CC depth (k = 0.804); CC with correct depth (ICC = 0.557); correct ventilations (k = 0.510); ventilations per cycle (ICC = 0.635); CC per cycle (ICC = 0.215); overall quality of CPR (ICC = 0.602). However, the degree of agreement should be considered poor since the limits were broad. CONCLUSIONS: Although there were discrepancies between the FD and the instructor, it would be advisable to follow a combined approach in CPR training, whereby the quantitative feedback supplied by the FD is complemented by the qualitative assessment of an instructor.