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Instructions to "push as hard as you can" improve average chest compression depth in dispatcher-assisted cardiopulmonary resuscitation.

ABSTRACT: BACKGROUND AND OBJECTIVE:Cardiopulmonary resuscitation (CPR) with adequate chest compression depth appears to improve first shock success in cardiac arrest. We evaluate the effect of simplification of chest compression instructions on compression depth in dispatcher-assisted CPR protocol. METHODS:Data from two randomized, double-blinded, controlled trials with identical methodology were combined to obtain 332 records for this analysis. Subjects were randomized to either modified Medical Priority Dispatch System (MPDS) v11.2 protocol or a new simplified protocol. The main difference between the protocols was the instruction to "push as hard as you can" in the simplified protocol, compared to "push down firmly 2in. (5cm)" in MPDS. Data were recorded via a Laerdal ResusciAnne SkillReporter manikin. Primary outcome measures included: chest compression depth, proportion of compressions without error, with adequate depth and with total release. RESULTS:Instructions to "push as hard as you can", compared to "push down firmly 2in. (5cm)", resulted in improved chest compression depth (36.4 mm vs. 29.7 mm, p<0.0001), and improved median proportion of chest compressions done to the correct depth (32% vs. <1%, p<0.0001). No significant difference in median proportion of compressions with total release (100% for both) and average compression rate (99.7 min(-1) vs. 97.5 min(-1), p<0.56) was found. CONCLUSIONS:Modifying dispatcher-assisted CPR instructions by changing "push down firmly 2in. (5cm)" to "push as hard as you can" achieved improvement in chest compression depth at no cost to total release or average chest compression rate.

SUBMITTER: Mirza M

PROVIDER: S-EPMC2614464 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature

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Instructions to "push as hard as you can" improve average chest compression depth in dispatcher-assisted cardiopulmonary resuscitation.

Mirza Muzna M Brown Todd B TB Saini Devashish D Pepper Tracy L TL Nandigam Hari Krishna HK Kaza Niroop N Cofield Stacey S SS

Resuscitation 20080717 1

<h4>Background and objective</h4>Cardiopulmonary resuscitation (CPR) with adequate chest compression depth appears to improve first shock success in cardiac arrest. We evaluate the effect of simplification of chest compression instructions on compression depth in dispatcher-assisted CPR protocol.<h4>Methods</h4>Data from two randomized, double-blinded, controlled trials with identical methodology were combined to obtain 332 records for this analysis. Subjects were randomized to either modified M ...[more]

PMID: 18635306

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Project description:ObjectivesNew chest compression detection technology allows for the recording and graphical depiction of clinical cardiopulmonary resuscitation (CPR) chest compressions. The authors sought to determine the inter-rater reliability of chest compression pattern classifications by human raters. Agreement with automated chest compression classification was also evaluated by computer analysis.MethodsThis was an analysis of chest compression patterns from cardiac arrest patients enrolled in the ongoing Resuscitation Outcomes Consortium (ROC) Continuous Chest Compressions Trial. Thirty CPR process files from patients in the trial were selected. Using written guidelines, research coordinators from each of eight participating ROC sites classified each chest compression pattern as 30:2 chest compressions, continuous chest compressions (CCC), or indeterminate. A computer algorithm for automated chest compression classification was also developed for each case. Inter-rater agreement between manual classifications was tested using Fleiss's kappa. The criterion standard was defined as the classification assigned by the majority of manual raters. Agreement between the automated classification and the criterion standard manual classifications was also tested.ResultsThe majority of the eight raters classified 12 chest compression patterns as 30:2, 12 as CCC, and six as indeterminate. Inter-rater agreement between manual classifications of chest compression patterns was κ = 0.62 (95% confidence interval [CI] = 0.49 to 0.74). The automated computer algorithm classified chest compression patterns as 30:2 (n = 15), CCC (n = 12), and indeterminate (n = 3). Agreement between automated and criterion standard manual classifications was κ = 0.84 (95% CI = 0.59 to 0.95).ConclusionsIn this study, good inter-rater agreement in the manual classification of CPR chest compression patterns was observed. Automated classification showed strong agreement with human ratings. These observations support the consistency of manual CPR pattern classification as well as the use of automated approaches to chest compression pattern analysis.

Project description:BackgroundQuality of cardiopulmonary resuscitation (CPR) is key to increase survival from cardiac arrest. Providing chest compressions with adequate rate and depth is difficult even for well-trained rescuers. The use of real-time feedback devices is intended to contribute to enhance chest compression quality. These devices are typically based on the double integration of the acceleration to obtain the chest displacement during compressions. The integration process is inherently unstable and leads to important errors unless boundary conditions are applied for each compression cycle. Commercial solutions use additional reference signals to establish these conditions, requiring additional sensors. Our aim was to study the accuracy of three methods based solely on the acceleration signal to provide feedback on the compression rate and depth.Materials and methodsWe simulated a CPR scenario with several volunteers grouped in couples providing chest compressions on a resuscitation manikin. Different target rates (80, 100, 120, and 140 compressions per minute) and a target depth of at least 50 mm were indicated. The manikin was equipped with a displacement sensor. The accelerometer was placed between the rescuer's hands and the manikin's chest. We designed three alternatives to direct integration based on different principles (linear filtering, analysis of velocity, and spectral analysis of acceleration). We evaluated their accuracy by comparing the estimated depth and rate with the values obtained from the reference displacement sensor.ResultsThe median (IQR) percent error was 5.9% (2.8-10.3), 6.3% (2.9-11.3), and 2.5% (1.2-4.4) for depth and 1.7% (0.0-2.3), 0.0% (0.0-2.0), and 0.9% (0.4-1.6) for rate, respectively. Depth accuracy depended on the target rate (p < 0.001) and on the rescuer couple (p < 0.001) within each method.ConclusionsAccurate feedback on chest compression depth and rate during CPR is possible using exclusively the chest acceleration signal. The algorithm based on spectral analysis showed the best performance. Despite these encouraging results, further research should be conducted to asses the performance of these algorithms with clinical data.

Dataset Information

Instructions to "push as hard as you can" improve average chest compression depth in dispatcher-assisted cardiopulmonary resuscitation.

Publications

Instructions to "push as hard as you can" improve average chest compression depth in dispatcher-assisted cardiopulmonary resuscitation.

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