• Ryosuke Takegawa, Tadahiko Shiozaki, Yoshihito Ogawa, Tomoya Hirose, Nobuto Mori, Mitsuo Ohnishi, Takuma Ishihara, Ayumi Shintani, and Takeshi Shimazu.
• Department of Traumatology and Acute Critical Medicine, Osaka University Graduate School of Medicine, 2-15 Yamada-oka, Suita, Osaka 565-0871, Japan. Electronic address: r-takegawa@hp-emerg.med.osaka-u.ac.jp.
• Resuscitation. 2019 Jun 1; 139: 201-207.

BackgroundCerebral oximetry (rSO2) may be useful in assessing the probability of return of spontaneous circulation (ROSC). However, the potential of assessing the trend in the rSO2 value has not been discussed when determining the probability of ROSC.MethodsThis was a retrospective study of out-of-hospital cardiac arrest (OHCA) patients with continuous rSO2 values recorded during cardiopulmonary arrest. We used logistic regression analysis at each time point to investigate the best subsets of rSO2-related variables for ROSC, which included rSO2 (baseline), the baseline value of rSO2; amount of maximum rise, the maximum difference of rSO2 from rSO2 (baseline) over t minutes; ΔrSO2 (t):(amount of maximum rise)/rSO2 (baseline) over t minutes after hospital arrival.ResultsAmong the 90 included patients, 35 achieved ROSC. Area under the curve (AUC) analysis revealed that ΔrSO2 over a 16-min measurement period was significantly higher than ΔrSO2 measured over 4-, 8-, 12-, and 20-min periods. During this 16-min period, the subset showing the best AUC value was interaction of the amount of maximum rise and rSO2 (baseline) rather than the amount of maximum rise or ΔrSO2 alone (AUC = 0.91).ConclusionsThe combination of rSO2 (baseline) with the amount of maximum rise in rSO2 value over time might be a new index for the prediction of ROSC that could be useful in guiding cardiopulmonary resuscitation. Further studies are needed to validate these findings.Copyright © 2019 The Author(s). Published by Elsevier B.V. All rights reserved.

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