To Clarify Features of Photoplethysmography in Monitoring Balanced Anesthesia, Compared with Cerebral State Index

Overview

Journal Med Sci Monit

Specialties General Medicine
Pathology

Date 2014 Mar 26

PMID 24662222

Citations 5

Authors

Lieliang Zhang

Lei Xu

Juan Zhu

Yujie Gao

Zhonghua Luo

Hongyu Wang

Zhongliang Zhu

Yi Yu

Hongwei Shi

Hongguang Bao

Affiliations

Soon will be listed here.

Abstract

Background: Although photoplethysmography and cerebral state index (CSI) have been used as indices in monitoring vital signs perioperatively, there are only a few reports comparing the performance of photoplethysmography with CSI in monitoring anaesthesia depth. The aim of the present study was to clarify features of photoplethysmography in monitoring balanced general anesthesia compared with CSI.

Material And Methods: Forty-five patients undergoing elective operation under general anaesthesia were enrolled in this study. Anaesthesia was induced with target-controlled infusion propofol. The photoplethysmogram, CSI, Modified Observer's Assessment of Alertness/Sedation Scale (MOAAS), and mean arterial pressure (MAP) were continuously monitored and recorded. Finger photoplethysmogram amplitude (PPGA) and pulse beat interval (PBI) were calculated off-line.

Results: For the period of time from pre-induction to pre-intubation, the coefficient of correlation between MOAAS and CSI was higher than those between MOAAS and PPGA, PBI, and MAP. CSI showed higher prediction probabilities (Pk) to differentiate the levels of MOAAS than did PPGA, PBI, and MAP. PPGA, PBI, and MAP values showed significant differences between before and after intubation, as well as pre- and post-incision (P<0.05), but no significant changes in cerebral state index (P>0.05).

Conclusions: The present study shows that photoplethysmography-derived parameters appear to be more suitable in monitoring the nociceptive component of balanced general anesthesia, while CSI performs well in detecting the sedation or hypnotic component of balanced general anesthesia.

Citing Articles

Photoplethysmography parameters in monitoring nociception during general anesthesia.

Li H, Tang Y, Chen X, Zhang M, Jiang F, Zhu F BMC Anesthesiol. 2025; 25(1):78.

PMID: 39962378 PMC: 11831782. DOI: 10.1186/s12871-025-02932-3.

Photoplethysmography temporal marker-based machine learning classifier for anesthesia drug detection.

Khalid S, Ali S, Liu H, Qurashi A, Ali U Med Biol Eng Comput. 2022; 60(11):3057-3068.

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Effect of Laryngeal Mask Airway Insertion on Parameters Derived From Catacrotic Phase of Photoplethysmography Under Different Concentrations of Remifentanil.

Chen W, Feng Y, Chen X, Jiang F, Miao J, Chen S IEEE J Transl Eng Health Med. 2020; 8:2700609.

PMID: 33178499 PMC: 7647452. DOI: 10.1109/JTEHM.2020.3017368.

Comparison of speckleplethysmographic (SPG) and photoplethysmographic (PPG) imaging by Monte Carlo simulations and measurements.

Dunn C, Lertsakdadet B, Crouzet C, Bahani A, Choi B Biomed Opt Express. 2019; 9(9):4306-4316.

PMID: 30615714 PMC: 6157764. DOI: 10.1364/BOE.9.004306.

The Effect of Tracheal Intubation-Induced Autonomic Response on Photoplethysmography.

Talke P Anesthesiol Res Pract. 2017; 2017:7646541.

PMID: 28469670 PMC: 5392400. DOI: 10.1155/2017/7646541.

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