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Resuscitation

Brain computed tomography angiography in postcardiac arrest patients and neurologic outcome

Clinical and Experimental Emergency Medicine 2019;6(4):297-302.
Published online: December 31, 2019

1Department of Emergency Medicine, Ajou University Medical Center, Ajou University School of Medicine, Suwon, Korea

2Division of Neuroradiology, Department of Radiology, Ajou University Medical Center, Ajou University School of Medicine, Suwon, Korea

Correspondence to: Minjung Kathy Chae Department of Emergency Medicine, Ajou University Medical Center, Ajou University School of Medicine, 164 World cup-ro, Yeongtong-gu, Suwon 16499, Korea E-mail: mjmj.chae@aumc.ac.kr
• Received: July 23, 2018   • Revised: September 11, 2018   • Accepted: September 17, 2018

Copyright © 2019 The Korean Society of Emergency Medicine

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/).

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Citations

Citations to this article as recorded by  Crossref logo
  • Prognostic value of machine learning for brain computed tomography as a predictor of neurologic outcomes after cardiac arrest: a systematic review and meta-analysis
    Kyung Hun Yoo, Juncheol Lee, Wonhee Kim, Bitnarae Kim, Elleah Jueun Chin, Jae-Guk Kim, Hyun-Young Choi, Jaehoon Oh
    Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine.2026;[Epub]     CrossRef
  • Taking a New SLANT on Postcardiac Arrest Prognostication?*
    Neha S. Dangayach, Brian J. Wright
    Critical Care Medicine.2022; 50(3): 519.     CrossRef

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Brain computed tomography angiography in postcardiac arrest patients and neurologic outcome
Clin Exp Emerg Med. 2019;6(4):297-302.   Published online December 31, 2019
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Brain computed tomography angiography in postcardiac arrest patients and neurologic outcome
Clin Exp Emerg Med. 2019;6(4):297-302.   Published online December 31, 2019
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Brain computed tomography angiography in postcardiac arrest patients and neurologic outcome
Image Image
Fig. 1. Ten vessels used for diagnosing brain death and predicting poor neurologic outcomes of postcardiac arrest patients. (A, B) Anterior cerebral artery A3 segment. (C) Middle cerebral artery M4 segment. (D) Posterior cerebral artery P2 segment. (E, F) Basilar artery. (G) Internal cerebral vein (ICV). (H) Vein of Galen. A point was given when the vessel was not opaque.
Fig. 2. Study flow. OHCA, out-of-hospital cardiac arrest; TTM, targeted temperature management; CTA, computed tomography angiography; ROSC, return of spontaneous circulation.
Brain computed tomography angiography in postcardiac arrest patients and neurologic outcome
Variable Good outcome (n = 17) Poor outcome (n = 56) P-value
Age (yr) 51.1 (13.4) 52 (16.1) 0.82
Male 12 (70.6) 23 (41.1) 0.03
Witnessed arrest 15 (88.2) 27 (48.2) 0.01
Bystander CPR 10 (58.8) 26 (46.4) 0.60
Arrest location 0.07
 Home 6 (35.3) 30 (53.6)
 Public 8 (47.1) 8 (14.3)
 Nursing home, healthcare facility 2 (11.8) 14 (25.0)
 Other 1 (5.9) 3 (5.4)
 Unknown 0 (0) 1 (1.8)
Cause of arrest 0.03
 Cardiogenic 13 (76.5) 19 (33.9)
 Other medical 2 (11.8) 4 (7.1)
 Poisoning 0 (0) 1 (1.8)
 Anaphylactic 0 (0) 1 (1.8)
 Asphyxia 2 (11.1) 29 (51.8)
 Unknown 0 (0) 2 (3.6)
AED shockable rhythm 13 (81.3) 10 (17.9) < 0.01
CPR duration (min) 16.2 (12.1) 25.0 (15.7) 0.04
Good (n = 17) Poor (n = 56) P-value Sensitivity (95% CI) Specificity (95% CI) PPV (95% CI) NPV (95% CI) AUROC (95% CI)
MCA-M1 0 (0) 1 (1.79) 0.58 1.79 (0.05–9.55) 100 (80.5–100) 100 (2.5–100) 23.6 (14.4–35.1) 0.51 (0.39–0.63)
MCA-M4 0 (0) 3 (5.4) 0.58 5.36 (1.12–14.9) 100 (80.5–100) 100 (29.2–100) 24.3 (14.8–36) 0.53 (0.40–0.64)
ACA-A3 0 (0) 1 (1.79) 0.33 1.79 (0.05–9.55) 100 (80.5–100) 100 (2.5–100) 23.6 (14.4–35.1) 0.51 (0.39–0.63)
PCA-P2 0 (0) 1 (1.79) 0.58 1.79 (0.05–9.55) 100 (80.5–100) 100 (2.5–100) 23.6 (14.4–35.1) 0.51 (0.39–0.63)
BA 0 (0) 1 (1.79) 0.58 1.79 (0.05–9.55) 100 (80.5–100) 100 (2.5–100) 23.6 (14.4–35.1) 0.51 (0.39–0.63)
VG 0 (0) 12 (21.4) 0.04 21.4 (11.6–34.4) 100 (80.5–100) 100 (73.5–100) 27.9 (17.1–40.8) 0.61 (0.48–0.72)
ICV 0 (0) 10 (17.9) 0.06 17.9 (8.91–30.4) 100 (80.5–100) 100 (69.2–100) 27.0 (16.6–39.7) 0.59 (0.47–0.70)
4-Point 0 (0) 10 (17.9) 0.06 17.9 (8.91–30.4) 100 (80.5–100) 100 (69.2–100) 27.0 (16.6–39.7) 0.59 (0.47–0.70)
7-Point 0 (0) 12 (21.4) 0.04 21.4 (11.6–34.4) 100 (80.5–100) 100 (73.5–100) 27.9 (17.1–40.8) 0.61 (0.48–0.72)
10-Point 0 (0) 12 (21.4) 0.04 21.4 (11.6–34.4) 100 (80.5–100) 100 (73.5–100) 27.9 (17.1–40.8) 0.61 (0.48–0.72)
Table 1. Baseline characteristics of the study population

Values are presented as number (%).

CPR, cardiopulmonary resuscitation; AED, automatic external defibrillator.

Table 2. Brain computed tomography angiography, neurologic outcomes, and diagnostic value of lacking opacification in each vessel and in at least one vessel for each scoring system

Values are presented as number (%) unless otherwise indicated.

CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; AUROC, area under the receiver operating characteristic curve; MCA-M1, middle cerebral artery M1 segment; MCA-M4, middle cerebral artery M4 segment; ACA-A3, anterior cerebral artery A3 segment; PCA-P2, posterior cerebral artery P2 segment; BA, basilar artery; VG, vein of Galen; ICV, internal cerebral vein.