Background: Validated monitoring methods for evaluating the balance of nociception and anti-nociception (BNAN) are needed in general anesthesia. This study assessed six photoplethysmography (PPG) parameters, computed from finger photoplethysmographic waveforms in patients undergoing gynecological surgery under general anesthesia.

Methods: A total of 20 participants were included, each undergoing general anesthesia with propofol and remifentanil. The same concentration of remifentanil was maintained throughout the experiment, four different intensities of electrical stimulation were administered, and the patient's fingertip PPG was meticulously recorded. PPG data were preprocessed to extract six PPG morphological parameters, and photoplethysmographic amplitude (PPGA), pulse beat interval (PBI), and surgical pleth index (SPI). Receiver operating characteristic (ROC) curves and the Area Under the Curve (AUC) were constructed and calculated to accurately measure its ability to reflect the nociceptive stimulus state. The consistency of different phase parameters at different stimulus intensities was evaluated by calculating the prediction probabilities. All results were compared with those obtained using SPI, PPGA, and PBI.

Results: After stimulation, all parameters and SPI showed significant changes compared with those before stimulation (p = 0.000). The catacrotic phase parameters (AC and MHC) showed higher discrimination in adequate analgesia and congruence with electrical stimulation intensity than the overall phase parameters, PPGA, and anacrotic phase parameters (AC: AUC = 0.851, Pk = 0.800; MHC: AUC = 0.837, Pk = 0.792).

Conclusions: In this study, six PPG morphological parameters were proposed and observed for the first time to effectively distinguish the occurrence of nociception. Compared with the overall phase parameters, PPGA, and anacrotic phase parameters, catacrotic phase parameters were more capable of characterizing noxious stimuli and more consistent with changes in electrical stimulation intensity.

Trial Registration: ChiCTR2200062228; Registered at http://clinicaltrials.gov on July 30, 2022.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11831782PMC
http://dx.doi.org/10.1186/s12871-025-02932-3DOI Listing

Publication Analysis

Top Keywords

phase parameters
28
general anesthesia
12
electrical stimulation
12
parameters
11
ppg morphological
8
morphological parameters
8
catacrotic phase
8
parameters ppga
8
ppga anacrotic
8
anacrotic phase
8

Similar Publications

In Situ Raman Spectra and Machine Learning Assistant Thermal Annealing Optimization for Effective Phototransistors.

ACS Appl Mater Interfaces

March 2025

State Key Laboratory of Luminescent Materials and Devices, Institute of Polymer Optoelectronic Materials and Devices, Guangdong Provincial Key Laboratory of Luminescence from Molecular Aggregates, South China University of Technology, Guangzhou 510640, P. R. China.

The relationship between the structure and function of condensed matter is complex and changeable, which is especially suitable for combination with machine learning to quickly obtain optimized experimental conditions. However, little research has been done on the effect of temperature on condensed matter and how it affects device performance because the difference between the in situ physical property parameters (which are lowered by the surface tension and mixing entropy) and the basic parameters of the bulk makes accurate AI predictions difficult. In this work, P3HT/ITIC was chosen as the donor/acceptor material for the active layer of organic phototransistors (OPTs).

View Article and Find Full Text PDF

Deep-Learning-Assisted Understanding of the Self-Assembly of Miktoarm Star Block Copolymers.

ACS Nano

March 2025

School of Chemical Science and Engineering, Tongji University, 1239 Siping Road, Shanghai 200092, China.

The self-assemblies of topological complex block copolymers, especially the AB type miktoarm star ones, are fascinating topics in the soft matter field, which represent typical self-assembly behaviors analogous to those of biological membranes. However, their diverse topological asymmetries and versatile spontaneous curvatures result in rather complex phase separations that deviate significantly from the common mechanisms. Thus, numerous trial-and-error experiments with tremendous parameter space and intricate relationships are needed to study their assemblies.

View Article and Find Full Text PDF

Electron beams evolved as important tools for modern technologies that construct and analyze nanoscale architectures. While electron-matter interactions at atomic and macro scales are well-studied, a knowledge gap persists at the molecular to nano level─the scale most relevant to the latest technologies. Here, we employ liquid-phase transmission electron microscopy supported by density functional theory calculations and a mathematical random search algorithm to rationalize and quantify electron beam-induced processes at the molecular level.

View Article and Find Full Text PDF

In the present study, magnetic-calcined bamboo composite adsorbents (MCBC200, MCBC400, MCBC600, MCBC800, and MCBC1000) were prepared, and their physicochemical characteristics (scanning electron microscope images, differential thermogravimetric analysis, Fourier transform-IR, specific surface area, surface functional groups, and point of zero charge [pH]) were evaluated. Furthermore, the adsorption capacity of methylene blue (MB, cationic dye) using the prepared adsorbents was assessed. The value of pH and the specific surface area of MCBC400 were 7.

View Article and Find Full Text PDF

PolyCrit: An Online Collaborative Platform for Polymer Characterization.

J Chromatogr A

March 2025

Department of Chemistry, University of Memphis, Memphis, TN, 38152, USA. Electronic address:

Polymer liquid chromatography at critical conditions (LCCC) is a chromatographic separation condition achieved by carefully balancing the interaction of a polymer with stationary and mobile phases to make the elution time of a polymer in chromatography independent of its molecular weight. By removing the dependence of elution time on polymer molecular weight, the LCCC then allows separation of polymer samples on the basis of secondary differences, such as topology, branching, and end-group functionality, that are otherwise difficult to resolve. Despite its potential, LCCC remains under-employed due to the complexity of its optimization and the scattered nature of existing data.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!