Dataset Information

Optimal Landmark for Chest Compressions during Cardiopulmonary Resuscitation Derived from a Chest Computed Tomography in Arms-Down Position.

ABSTRACT: Compressions at the left ventricle increase rate of return of spontaneous circulation. This study aimed to identify the landmark of the point of maximal left ventricular diameter on the sternum (LVmax) by using chest computed tomography (CCT) in the arms-down position, which was similar to an actual cardiac arrest patient. A retrospective study was conducted between September 2014 and November 2020. We included adult patients who underwent CCT in an arms-down position and measured the rescuer’s hand. We measured the distance from the sternal notch to LVmax (DLVmax), to the lower half of sternum (DLH), and to the point of maximal force of hand, which placed the lowest palmar margin of the rescuer’s reference hand at the xiphisternal junction. Thirty-nine patients were included. The LVmax was located below the lower half of the sternum; DLVmax and DLH were 12.6 and 10.0 cm, respectively (p < 0.001). Distance from the sternal notch to the point of maximal force of the left hand, with the ulnar border located at the xiphisternal junction, was close to DLVmax; 11.3 and 12.6 cm, respectively (p = 0.076). In conclusion, LVmax was located below the lower half of the sternum, which is recommended by current guidelines.

SUBMITTER: Usawasuraiin P

PROVIDER: S-EPMC9033090 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Optimal Landmark for Chest Compressions during Cardiopulmonary Resuscitation Derived from a Chest Computed Tomography in Arms-Down Position.

Usawasuraiin Pimpan P Wittayachamnankul Borwon B Chenthanakij Boriboon B Euathrongchit Juntima J Phinyo Phichayut P Tangsuwanaruk Theerapon T

Journal of cardiovascular development and disease 20220327 4

Compressions at the left ventricle increase rate of return of spontaneous circulation. This study aimed to identify the landmark of the point of maximal left ventricular diameter on the sternum (LVmax) by using chest computed tomography (CCT) in the arms-down position, which was similar to an actual cardiac arrest patient. A retrospective study was conducted between September 2014 and November 2020. We included adult patients who underwent CCT in an arms-down position and measured the rescuer’s ...[more]

PMID: 35448077

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Project description:AimPropose new metrics of impulsiveness of manual chest compressions (CCs) that account for shape and duration, separate the characteristics of the compressive part of the CC cycle from those of the recoil part, and are uncorrelated to CC depth and rate.MethodsWe conducted a retrospective analysis of adult out-of-hospital cardiac arrest monitor-defibrillator recordings having CPR data. Specifically, episodes of adult patients with ≥ 1000 compressions free of leaning were examined. CCs were obtained from the depth signal of the valid episodes, and we calculated the novel metrics: compression area index (CAI), recoil area index (RAI), compression impulsiveness index (CII) and recoil impulsiveness index (RII). Generalized linear mixed-effects models and Jonckheere-Terpstra trend analyses were employed to measure differences between populations and trends, and the absolute value of Pearson's correlation coefficient |r| was used to report dependence between variables. Statistics are reported as median and interquartile range.ResultsWe analyzed 982,340 CCs corresponding to 453 episodes, for which we calculated their CAI, RAI and duty cycle (DC). We analyzed the metrics for various populations: age, sex, any ROSC achieved and disposition, and found that CAI was significantly different according to patient disposition and RAI relative to age and sex (p<0.05). None of the metrics was correlated strongly to depth or rate (|r| values of 0.22 or smaller), and all of them varied for CC series corresponding to the same rescuer over the course of resuscitation (ptrend<0.05). However, we observed that the metrics are not balanced, in that for any value of DC, CAI and RAI span almost their entire ranges.ConclusionThe proposed metrics correctly and completely describe manual CC waveforms, improve upon the DC, since they depend on the signal waveform, and provide additional information to current indicators of quality CPR, depth and rate. Furthermore, they allow to differentiate the compressive and recoil parts of the CC cycle, reflecting influence of the rescuer (via CAI or CII) and of the biomechanics of the patient's chest (via RAI or RII). Thus, they have the potential to contribute to better understanding CPR dynamics and, eventually, to enhanced quality of CPR practice as additional indicators of proper manual CC technique.

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.

Project description:AimThis study aimed to compare the quality of compressions in supine cardiopulmonary resuscitation (CPR) and prone CPR by performing chest compressions on a manikin. Evaluating the effect of prone CPR using different hand and body position on the quality of manual chest compressions and fatigue of participants.MethodsAfter completing 2 min of chest compression in the supine position (Supine Group), 25 participants randomly performed three sets of 2-minutes chest compressions on a prone position manikin. Stand + hands overlapped Group: participants stood beside the patient bed with their hands overlapped and placed on the posterior segment of the thoracic spine between the scapulae, Straddle + hands separated Group: participants straddled the patient bed with their hands placed above the scapulae on both sides at the mid-chest level, and Straddle + hands overlapped Group: participants straddled the patient bed with their hands overlapping on the posterior segment of the thoracic spine between the scapulae. Subsequently, the quality of chest compressions and participants fatigue were assessed.ResultsChest compression depth ratio and mean chest compression depth (MCCD) were worse in the three prone CPR groups (Stand + hands overlapped Group: 0.0(0.0,15.6) %, 39.8 ± 1.3 mm; Straddle + hands separated Group: 1.4(0.0,11.7) %, 42.4 ± 1.2 mm; Straddle + hands overlapped Group: 0.0(0.0,9.2) %, 40.9 ± 1.2 mm) than in the Supine group (87.1(68.1,94.0) %; p < 0.001, 52.4 ± 0.4 mm; p < 0.001). In the three prone CPR groups, Straddle + hands separated Group had the greatest MCCD, lowest changes in heart rate (p = 0.018) and lowest changes in RPE scores (p < 0.001). There were no significant differences between the four groups in terms of mean chest compression rate, accurate chest compression rate ratio, or correct recoil ratio.ConclusionThis simulation-based study showed that the quality of chest compressions was worse in the prone position than in the supine position. When prone chest compressions were performed using different hand and body position, prone CPR performed by a participant straddling a hospital bed with hands placed above the scapula on either side at the mid-chest level provided higher-quality chest compressions and lower rescuer fatigue.

Dataset Information

Optimal Landmark for Chest Compressions during Cardiopulmonary Resuscitation Derived from a Chest Computed Tomography in Arms-Down Position.

Publications

Optimal Landmark for Chest Compressions during Cardiopulmonary Resuscitation Derived from a Chest Computed Tomography in Arms-Down Position.

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