Literature DB >> 18952361

Compression feedback devices over estimate chest compression depth when performed on a bed.

Gavin D Perkins1, Laura Kocierz, Samuel C L Smith, Robert A McCulloch, Robin P Davies.   

Abstract

INTRODUCTION: CPR feedback/prompt devices are being used increasingly to guide CPR performance in clinical practice. A potential limitation of these devices is that they may fail to measure the amount of mattress compression when CPR is performed on a bed. The aim of this study is to quantify the amount of mattress compression compared to chest compression using a commercially available compression sensor (Q-CPR, Laerdal, UK). A secondary aim was to evaluate if placing a backboard beneath the victim would alter the degree of mattress compression.
METHODS: CPR was performed on a manikin on the floor and on a bed with a foam or inflatable mattress with and without a backboard. Chest and mattress compression depths were measured by an accelerometer placed on the manikin's chest (total compression depth) and sternal-spinal (chest) compression by manikin sensors.
RESULTS: Feedback provided by the accelerometer device led to significant under compression of the chest when CPR was performed on a bed with a foam 26.2 (2.2)mm or inflatable mattress 32.2 (1.16)mm. The use of a narrow backboard increased chest compression depth by 1.9mm (95% CI 0.1-3.7mm; P=0.03) and wide backboard by 2.6mm (95% CI 0.9-4.5mm; P=0.013). Under compression occurred as the device failed to compensate for compression of the underlying mattress, which represented 35-40% of total compression depth.
CONCLUSION: The use of CPR feedback devices that do not correct for compression of an underlying mattress may lead to significant under compression of the chest during CPR.

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Year:  2008        PMID: 18952361     DOI: 10.1016/j.resuscitation.2008.08.011

Source DB:  PubMed          Journal:  Resuscitation        ISSN: 0300-9572            Impact factor:   5.262


  28 in total

1.  Backboards are important when chest compressions are provided on a soft mattress.

Authors:  Akira Nishisaki; Matthew R Maltese; Dana E Niles; Robert M Sutton; Javier Urbano; Robert A Berg; Vinay M Nadkarni
Journal:  Resuscitation       Date:  2012-02-04       Impact factor: 5.262

2.  A new chest compression depth feedback algorithm for high-quality CPR based on smartphone.

Authors:  Yeongtak Song; Jaehoon Oh; Youngjoon Chee
Journal:  Telemed J E Health       Date:  2014-11-17       Impact factor: 3.536

3.  Improvement of lay rescuer chest compressions with a novel audiovisual feedback device : A randomized trial.

Authors:  A Wutzler; S von Ulmenstein; M Bannehr; K Völk; J Förster; C Storm; W Haverkamp
Journal:  Med Klin Intensivmed Notfmed       Date:  2017-04-04       Impact factor: 0.840

4.  The impact of a step stool on cardiopulmonary resuscitation: a cross-over mannequin study.

Authors:  Dana P Edelson; Shawn L Call; Trevor C Yuen; Terry L Vanden Hoek
Journal:  Resuscitation       Date:  2012-03-14       Impact factor: 5.262

5.  The prevalence of chest compression leaning during in-hospital cardiopulmonary resuscitation.

Authors:  David A Fried; Marion Leary; Douglas A Smith; Robert M Sutton; Dana Niles; Daniel L Herzberg; Lance B Becker; Benjamin S Abella
Journal:  Resuscitation       Date:  2011-04-08       Impact factor: 5.262

Review 6.  [Inhospital resuscitation : Decisive measures for the outcome].

Authors:  M P Müller; T Jantzen; S Brenner; J Gräsner; K Preiß; J Wnent
Journal:  Anaesthesist       Date:  2015-04       Impact factor: 1.041

7.  The Author's Response: Response to the Comment: Chest Compression Rate, Rescuer's Fatigue and Patient's Survival.

Authors:  Sung Oh Hwang
Journal:  J Korean Med Sci       Date:  2016-10       Impact factor: 2.153

8.  Part 12: Education, implementation, and teams: 2010 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science with Treatment Recommendations.

Authors:  Jasmeet Soar; Mary E Mancini; Farhan Bhanji; John E Billi; Jennifer Dennett; Judith Finn; Matthew Huei-Ming Ma; Gavin D Perkins; David L Rodgers; Mary Fran Hazinski; Ian Jacobs; Peter T Morley
Journal:  Resuscitation       Date:  2010-10       Impact factor: 5.262

9.  Association between chest compression rates and clinical outcomes following in-hospital cardiac arrest at an academic tertiary hospital.

Authors:  J Hope Kilgannon; Michael Kirchhoff; Lisa Pierce; Nicholas Aunchman; Stephen Trzeciak; Brian W Roberts
Journal:  Resuscitation       Date:  2016-09-22       Impact factor: 5.262

10.  Use of a simulation-based advanced resuscitation training curriculum: Impact on cardiopulmonary resuscitation quality and patient outcomes.

Authors:  Amanda K Young; Michael J Maniaci; Leslie V Simon; Philip E Lowman; Ryan T McKenna; Colleen S Thomas; Jordan J Cochuyt; Tyler F Vadeboncoeur
Journal:  J Intensive Care Soc       Date:  2019-05-07
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