Kramer-Johansen J, Myklebust H, Wik L, et al. Quality of out-of-hospital cardiopulmonary resuscitation with real time automated feedback: a prospective interventional study

Institute for Experimental Medical Research, University of Oslo, N-0407 Oslo, Norway.
Resuscitation (Impact Factor: 4.17). 12/2006; 71(3):283-92. DOI: 10.1016/j.resuscitation.2006.05.011
Source: PubMed


To compare quality of CPR during out-of-hospital cardiac arrest with and without automated feedback.
Consecutive adult, out-of-hospital cardiac arrests of all causes were studied. One hundred and seventy-six episodes (March 2002-October 2003) without feedback were compared to 108 episodes (October 2003-September 2004) where automatic feedback on CPR was given. Automated verbal and visual feedback was based on measured quality with a prototype defibrillator. Quality of CPR was the main outcome measure and survival was reported as specified in the protocol.
Average compression depth increased from (mean +/- S.D.) 34 +/- 9 to 38 +/- 6 mm (mean difference (95% CI) 4 (2, 6), P < 0.001), and median percentage of compressions with adequate depth (38-51 mm) increased from 24% to 53% (P < 0.001, Mann-Whitney U-test) with feedback. Mean compression rate decreased from 121 +/- 18 to 109 +/- 12 min(-1) (difference -12 (-16, -9), P = 0.001). There were no changes in the mean number of ventilations per minute; 11 +/- 5 min(-1) versus 11 +/- 4 min(-1) (difference 0 (-1, 1), P = 0.8) or the fraction of time without chest compressions; 0.48 +/- 0.18 versus 0.45 +/- 0.17 (difference -0.03 (-0.08, 0.01), P = 0.08). With intention to treat analysis 7/241 control patients were discharged alive (2.9%) versus 5/117 with feedback (4.3%) (OR 1.5 (95% CI; 0.8, 3), P = 0.2). In a logistic regression analysis of all cases, witnessed arrest (OR 4.2 (95% CI; 1.6, 11), P = 0.004) and average compression depth (per mm increase) (OR 1.05 (95% CI; 1.01, 1.09), P = 0.02) were associated with rate of hospital admission.
Automatic feedback improved CPR quality in this prospective non-randomised study of out-of-hospital cardiac arrest. Increased compression depth was associated with increased short-term survival. (NCT00138996),

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    • "Chest compression rate and depth are usually estimated by double integration of the acceleration or by mapping the pressure according to a built-in sensor in the feedback device during CCs [6] [7] [8]. By using both a feedback device and the guidance of a metronome, providers can perform CC at a correct and consistent rate following CPR guidelines [6] [7]. However, they might not compress the chest to the correct depth according to the guidelines because some devices overestimate or underestimate the depth, depending on the stiffness and the angle of incline of the surface on which the patient is placed [9]. "
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    ABSTRACT: Feedback devices are used to improve chest compression (CC) quality related to survival rates in cardiac arrest. However, several studies have shown that feedback devices are not sufficiently reliable to ensure adequate CC depth on soft surfaces. Here, we determined the proper target depth of feedback (TDF) using an accelerometer during cardiopulmonary resuscitation in hospital beds. In prospective randomized crossover study, 19 emergency physicians performed CCs for 2 minutes continuously on a manikin in 2 different beds with 3 TDFs (5, 6, and 7 cm). We measured CC depth, the proportion of accurate compression depths, CC rate, the proportion of incomplete chest decompressions, the velocity of CC (CC velocity), the proportion of time spent in CC relative to compression plus decompression (duty cycle), and the time spent in CC (CC time). Mean (SD) CC depths at TDF 5, 6, and 7 were 45.42 (5.79), 52.68 (4.18), and 58.47 (2.48) on one bed and 46.26 (4.49), 53.58 (3.15), and 58.74 (2.10) mm on the other bed (all P < .001), respectively. The proportions of accurate compression depths and CC velocity at TDF 5, 6, and 7 differed significantly according to TDF on both beds (all P < .001).The CC rate, CC time, and proportion of incomplete chest decompression did not differ on both beds (all P > .05). The duty cycle differed significantly on only B2. The target depth of the real-time feedback device should be at least 6 cm but should not exceed 7 cm for optimal CC on patients on hospital beds. Copyright © 2015. Published by Elsevier Inc.
    Full-text · Article · Jul 2015 · The American journal of emergency medicine
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    • "Christenson et al. reported that the chest compression fraction appears to be an important determinant of survival from cardiac arrest [13]. It was also reported that shallower chest compressions correlated significantly with a decrease in successful defibrillation [14,15]. Now, the rescuer should give chest compressions to a depth of at least 5 cm and at a rate of at least 100 times per minute, allow full chest recoil after each compression, and minimise interruptions in chest compression [5]. "
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    ABSTRACT: Background The 2010 Consensus on Science and Treatment Recommendations Statement recommended that short video/computer self-instruction courses, with minimal or no instructor coaching, combined with hands-on practice can be considered an effective alternative to instructor-led basic life support courses. The purpose of this study was to examine the effectiveness of a simplified cardiopulmonary resuscitation (CPR) training program for non-medical staff working at a university hospital. Methods Before and immediately after a 45-min CPR training program consisting of instruction on chest compression and automated external defibrillator (AED) use with a personal training manikin, CPR skills were automatically recorded and evaluated. Participants’ attitudes towards CPR were evaluated by a questionnaire survey. Results From September 2011 through March 2013, 161 participants attended the program. We evaluated chest compression technique in 109 of these participants. The number of chest compressions delivered after the program versus that before was significantly greater (110.8 ± 13.0/min vs 94.2 ± 27.4/min, p < 0.0001), interruption of chest compressions was significantly shorter (0.05 ± 0.34 sec/30 sec vs 0.89 ± 3.52 sec/30 sec, p < 0.05), mean depth of chest compressions was significantly greater (57.6 ± 6.8 mm vs 52.2 ± 9.4 mm, p < 0.0001), and the proportion of incomplete chest compressions of <5 cm among all chest compressions was significantly decreased (8.9 ± 23.2% vs 38.6 ± 42.9%, p < 0.0001). Of the 159 participants who responded to the questionnaire survey after the program, the proportion of participants who answered ‘I can check for a response,’ ‘I can perform chest compressions,’ and ‘I can absolutely or I think I can use an AED’ increased versus that before the program (81.8% vs 19.5%, 77.4% vs 10.1%, 84.3% vs 23.3%, respectively). Conclusions A 45-min simplified CPR training program on chest compression and AED use improved CPR quality and the attitude towards CPR and AED use of non-medical staff of a university hospital.
    Full-text · Article · May 2014 · Scandinavian Journal of Trauma Resuscitation and Emergency Medicine
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    • "All signals were acquired with a 500 Hz sampling rate. The initial rhythm and all subsequent changes in rhythm were annotated by consensus of an experienced anesthesiologist and a biomedical engineer, both specialized in resuscitation [21] [22]. Rhythm annotations comprised five types (see [21] for further details): VF and fast ventricular tachycardia (VT) in the shockable category and ASY, pulseless electrical activity (PEA), and pulse-generating rhythm (PR) in the nonshockable category. "
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    ABSTRACT: Interruptions in cardiopulmonary resuscitation (CPR) compromise defibrillation success. However, CPR must be interrupted to analyze the rhythm because although current methods for rhythm analysis during CPR have high sensitivity for shockable rhythms, the specificity for nonshockable rhythms is still too low. This paper introduces a new approach to rhythm analysis during CPR that combines two strategies: a state-of-the-art CPR artifact suppression filter and a shock advice algorithm (SAA) designed to optimally classify the filtered signal. Emphasis is on designing an algorithm with high specificity. The SAA includes a detector for low electrical activity rhythms to increase the specificity, and a shock/no-shock decision algorithm based on a support vector machine classifier using slope and frequency features. For this study, 1185 shockable and 6482 nonshockable 9-s segments corrupted by CPR artifacts were obtained from 247 patients suffering out-of-hospital cardiac arrest. The segments were split into a training and a test set. For the test set, the sensitivity and specificity for rhythm analysis during CPR were 91.0% and 96.6%, respectively. This new approach shows an important increase in specificity without compromising the sensitivity when compared to previous studies.
    Full-text · Article · May 2014 · BioMed Research International
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