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Assessment of a new volumetric capnography-derived parameter to reflect compression quality and to predict return of spontaneous circulation during cardiopulmonary resuscitation in a porcine model

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Abstract

We aimed to evaluate a volumetric capnography (Vcap)-derived parameter, the volume of CO2 eliminated per minute and per kg body weight (VCO2/kg), as an indicator of the quality of chest compression (CC) and to predict the return to spontaneous circulation (ROSC) under stable ventilation status. Twelve male domestic pigs were utilized for the randomized crossover study. After 4 min of untreated ventricular fibrillation (VF), mechanical cardiopulmonary resuscitation and ventilation were administered. Following 5-min washout periods, each animal underwent two sessions of experiments: three types of CC quality for 5 min stages in the first session, followed by advanced life support, consecutively in two sessions. Different CC quality had a significant effect on the partial pressure of end-tidal carbon dioxide (PetCO2), VCO2/kg, aortic pressure (mean), aortic systolic pressure, aortic diastolic pressure, right atrial pressure (mean), and carotid blood flow (P < 0.05). With the improvement in CC quality, the values of PetCO2 and VCO2/kg also increased, and the difference between the groups was statistically significant (P < 0.05). The Spearman rank test revealed a significant correlation between the Vcap-derived parameters and hemodynamics. PetCO2 and VCO2/kg have similar capabilities for discriminating survivors from non-survivors, and the area under the curve for both was 0.97. VCO2/kg had similar performance as PetCO2 in reflecting the quality of CC and prediction of achieving ROSC under stable ventilation status in a porcine model of VF-related cardiac arrest. However, VCO2/kg requires a longer time to achieve a stable state after adjusting for quality of CC than PetCO2.

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Supplementary data associated with this article can be found online at https://doi.org/10.17632/7p27nk75k3.4.

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Acknowledgements

This work was supported by the Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (2017-I2M-1-009). The funding was used to purchase landrace cross pigs, experimental drugs, and disposable medical consumables. The sponsor was not involved in designing the study, in the collection and analysis of data, in the writing of the manuscript, or in the decision to submit the manuscript for publication.

Funding

This work was supported by the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2017-I2M-1-009). The funding was used to purchase landrace cross pigs, experimental drugs, and disposable medical consumables. The sponsor was not involved in designing the study, in the collection and analysis of data, in the writing of the manuscript, or in the decision to submit the manuscript for publication.

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Authors

Contributions

Conceptualization: JX, XY, and LZ. Supervision: JX and XY. Project administration: JX, XY, and HZ. Validation: JX and XY. Funding acquisition: XY. Methodology: LZ, KJ, and FS. Writing—original draft: LZ, KJ, and FS. Writing—review & editing: JX. Investigation: LZ, KJ, and FS. Resources: YF. Visualization: YF. Formal analysis: DL and SY. Data curation: DL and SY.

Corresponding authors

Correspondence to Jun Xu or Xuezhong Yu.

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All authors declare that they have no conflict of interest.

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All experiments were performed in accordance with the National Institutes of Health Guidelines, and under protocols approved by the Institutional Animal Care and Use Committee of the Peking union medical college.

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Research involving animal rights

This experimental animal study was approved by the Welfare and Ethical Inspection committee in Animal Experimentation of the Peking Union Medical College Hospital (Protocol Number: XHDW-2019-23).

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Zhang, L., Jin, K., Sun, F. et al. Assessment of a new volumetric capnography-derived parameter to reflect compression quality and to predict return of spontaneous circulation during cardiopulmonary resuscitation in a porcine model. J Clin Monit Comput 36, 199–207 (2022). https://doi.org/10.1007/s10877-020-00637-1

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