Background: To characterize patients dying in a community hospital with or without attempting cardiopulmonary resuscitation (CPR) and to describe patient involvement in, documentation of, and compliance with decisions on resuscitation (Do-not-attempt-to-resuscitate orders; DNAR).

Methods: All patients who died in Kalmar County Hospital during January 1, 2016 until December 31, 2016 were included. All information from the patients’ electronic chart was analysed.

Results: Of 660 patients (mean age 77.7 ± 12.1 years; range 21–101; median 79; 321 (48.6%) female), 30 (4.5%) were pronounced dead in the emergency department after out-of-hospital CPR. Of the remaining 630 patients a DNAR order had been documented in 558 patients (88.6%). Seventy had no DNAR order and 2 an explicit order to do CPR. In 43 of these 70 patients CPR was unsuccessfully attempted while the remaining 27 patients died without attempting CPR. In 2 of 558 (0.36%) patients CPR was attempted despite a DNAR order in place. In 412 patients (73.8%) the DNAR order had not been discussed with neither patient nor family/friends. Moreover, in 75 cases (13.4%) neither patient nor family/friends were even informed about the decision on code status.

Conclusions: In general, a large percentage of patients in our study had a DNAR order in place (88.6%). However, 27 patients (4.3%) died without CPR attempt or DNAR order. DNAR orders had not been discussed with the patient/surrogate in almost three fourths of the patients. Further work has to be done to elucidate the barriers to discussions of CPR decisions with the patient.

Introduction: A high quality of chest compressions, e.g. sufficient depth (5-6 cm) and rate (100-120 per min), has been associated with survival. The patient's underlay affects chest compression depth. Depth and rate can be assessed by feedback systems to guide rescuers during cardiopulmonary resuscitation. Aim: The purpose of this study was to describe the quality of chest compressions by healthcare professionals using real-time audiovisual feedback during in-hospital cardiopulmonary resuscitation. Method: An observational descriptive study was performed including 63 cardiac arrest events with a resuscitation attempt. Data files were recorded by Zoll AED Pro, and reviewed by RescueNet Code Review software. The events were analysed according to depth, rate, quality of chest compressions and underlay. Results: Across events, 12.7% (median) of the compressions had a depth of 5-6 cm. Compression depth of >6 cm was measured in 70.1% (median). The underlay could be identified from the electronic patient records in 54 events. The median compression depth was 4.5 cm (floor) and 6.7 cm (mattress). Across events, 57.5% (median) of the compressions were performed with a median frequency of 100-120 compressions/min and the most common problem was a compression rate of <100 (median=22.3%). Conclusions: Chest compression quality was poor according to the feedback system. However, the distribution of compression depth with regard to underlay points towards overestimation of depth when treating patients on a mattress. Audiovisual feedback devices ought to be further developed. Healthcare professionals need to be aware of the strengths and weaknesses of their devices.

Aim: The aim was to investigate the clinical performance of two different types of automated external defibrillators (AEDs). Methods: Three investigators reviewed 2938 rhythm analyses performed by AEDs in 240 consecutive patients (median age 72, q1-q3 = 62-83) who had suffered cardiac arrest between January 2011 and March 2015. Two different AEDs were used (AED A n = 105, AED B n = 135) in-hospital (n = 91) and out-of-hospital (n = 149). Results: Among 194 shockable rhythms, 17 (8.8%) were not recognized by AED A, while AED B recognized 100% (n = 135) of shockable episodes (sensitivity 91.2 vs 100%, p < 0.01). In AED A, 8 (47.1%) of these episodes were judged to be algorithm errors while 9 (52.9%) were caused by external artifacts. Among 1039 non-shockable rhythms, AED A recommended shock in 11 (1.0%), while AED B recommended shock in 63 (4.1%) of 1523 episodes (specificity 98.9 vs 95.9, p < 0.001). In AED A, 2 (18.2%) of these episodes were judged to be algorithm errors (AED B, n = 40, 63.5%), while 9 (81.8%) were caused by external artifacts (AED B, n = 23, 36.5%). Conclusions: There were significant differences in sensitivity and specificity between the two different AEDs. A higher sensitivity of AED B was associated with a lower specificity while a higher specificity of AED A was associated with a lower sensitivity. AED manufacturers should work to improve the algorithms. In addition, AED use should always be reviewed with a routine for giving feedback, and medical personnel should be aware of the specific strengths and shortcomings of the device they are using. (C) 2017 Elsevier B.V. All rights reserved.