Predicting Return of Spontaneous Circulation with Ultrasound-Guided Carotid Artery Compression During Chest Compressions

28 Pages Posted: 4 Dec 2024

See all articles by Seung Jin Maeng

Seung Jin Maeng

Sungkyunkwan University - Samsung Medical Center

Hee Yoon

Sungkyunkwan University - Samsung Medical Center

Ik Joon Jo

Sungkyunkwan University - Department of Emergency Medicine

Sejin Heo

Sungkyunkwan University - Samsung Medical Center

Hansol Chang

Sungkyunkwan University - Samsung Medical Center

Guntak Lee

Sungkyunkwan University - Department of Emergency Medicine

Jong Eun Park

Sungkyunkwan University - Department of Emergency Medicine

Taerim Kim

Sungkyunkwan University - Samsung Advanced Institute of Health Sciences and Technology (SAIHST)

Se Uk Lee

Sungkyunkwan University - Department of Emergency Medicine

Sung Yeon Hwang

Sungkyunkwan University - Department of Emergency Medicine

Jihyeon Kim

Sungkyunkwan University - Samsung Medical Center

Min-Ji Kim

Sungkyunkwan University - Biomedical Statistics Center

Abstract

Objective: This study aimed to evaluate the diagnostic performance of intra-CPR Point-of-Care Ultrasound Carotid Artery Compression (POCUS-CAC) in predicting return of spontaneous circulation (ROSC) during chest compressions.Methods: A retrospective analysis was conducted on prospectively collected data from patients presenting to the emergency department with cardiac arrest between June 2022 and October 2023. POCUS-CAC was performed every 30 seconds during continuous chest compressions to assess carotid artery compressibility. A prediction of ROSC was recorded if the carotid artery remained non-compressible during both the systolic and diastolic phases. ROSC was confirmed using manual pulse palpation and electrocardiogram rhythm analysis every 2 minutes. The diagnostic performance of intra-CPR POCUS-CAC, including accuracy, sensitivity, and specificity, was assessed. Receiver operating characteristic analysis was performed. Multivariable analysis was used to determine factors associated with ROSC.Results: The study cohort included 37 patients, with a mean age of 71 years (standard deviation 18), and 57% were male. POCUS-CAC demonstrated 90.6% sensitivity, 87.2% accuracy, and an area under the curve (AUC) of 94.83% in predicting ROSC during rhythm checks conducted after two minutes of chest compressions. For final ROSC outcomes, POCUS-CAC had a sensitivity of 59.3% and specificity of 60.5%. Multivariable analysis identified POCUS-CAC as the strongest predictor of ROSC (odds ratio 39.25, 95% confidence intervals: 14.10–109.24, p < 0.0001).Conclusions: Intra-CPR POCUS-CAC demonstrated 87.2% accuracy and an AUC of 94.83% in predicting ROSC during chest compressions. This valuable, non-invasive tool may help facilitate faster ROSC determination, support real-time resuscitation adjustments, and enhance CPR quality monitoring.

Note:
Funding Declaration: This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT (MSIT) (NRF-2022R1C1C1011864).

Conflicts of Interest: None

Ethical Approval: This study was approved by the Institutional Review Board of the Samsung Medical Center (IRB file number 2024-10-109). The initial data collection was conducted under a consent- exempt protocol approved by the same board (IRB file number 2022-04-016). Informed consent was waived for both the initial data collection and the retrospective analysis, as both protocols were approved by the Institutional Review Board.

Keywords: Cardiopulmonary resuscitation, ultrasonography, Carotid artery, Return of Spontaneous Circulation

Suggested Citation

Maeng, Seung Jin and Yoon, Hee and Jo, Ik Joon and Heo, Sejin and Chang, Hansol and Lee, Guntak and Park, Jong Eun and Kim, Taerim and Lee, Se Uk and Hwang, Sung Yeon and Kim, Jihyeon and Kim, Min-Ji, Predicting Return of Spontaneous Circulation with Ultrasound-Guided Carotid Artery Compression During Chest Compressions. Available at SSRN: https://ssrn.com/abstract=5018529 or http://dx.doi.org/10.2139/ssrn.5018529

Seung Jin Maeng

Sungkyunkwan University - Samsung Medical Center ( email )

81, Irwon- Ro
Gangnam-gu
Seoul, 135-710
Korea, Republic of (South Korea)

Hee Yoon (Contact Author)

Sungkyunkwan University - Samsung Medical Center ( email )

81, Irwon- Ro
Gangnam-gu
Seoul, 135-710
Korea, Republic of (South Korea)

Ik Joon Jo

Sungkyunkwan University - Department of Emergency Medicine ( email )

Sejin Heo

Sungkyunkwan University - Samsung Medical Center ( email )

81, Irwon- Ro
Gangnam-gu
Seoul, 135-710
Korea, Republic of (South Korea)

Hansol Chang

Sungkyunkwan University - Samsung Medical Center ( email )

81, Irwon- Ro
Gangnam-gu
Seoul, 135-710
Korea, Republic of (South Korea)

Guntak Lee

Sungkyunkwan University - Department of Emergency Medicine ( email )

Jong Eun Park

Sungkyunkwan University - Department of Emergency Medicine ( email )

Taerim Kim

Sungkyunkwan University - Samsung Advanced Institute of Health Sciences and Technology (SAIHST) ( email )

Se Uk Lee

Sungkyunkwan University - Department of Emergency Medicine ( email )

Sung Yeon Hwang

Sungkyunkwan University - Department of Emergency Medicine ( email )

Jihyeon Kim

Sungkyunkwan University - Samsung Medical Center ( email )

81, Irwon- Ro
Gangnam-gu
Seoul, 135-710
Korea, Republic of (South Korea)

Min-Ji Kim

Sungkyunkwan University - Biomedical Statistics Center ( email )

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