Initial Validation of the NOL Nociception Level Index® Monitoring System in Black and Multiracial People

The NOL-Nociception Level Index<sup>®</sup> is a multiparameter index, based on artificial intelligence for the monitoring of nociception (physiological pain response) during anesthesia that has recently been authorized by the FDA. The monitor utilizes continuous streams of information from a finger probe comprising four sensors, including photoplethysmography, to provide a personalized nociception score on a scale of 0-100. Recent studies have suggested racial bias in pulse oximeter measurements due to the effect of melanin levels on photoplethysmography measurements. Therefore, there is a need to clinically validate new monitoring technologies in patients of all skin tones. The performance of the NOL scale in 8 patients that self-identified as Black or multiracial was compared to a database of 447 consented patients, assessing the response to surgical events at different levels of intensity. The descriptive, pilot data suggest that NOL performance in Black and multiracial patients is not different from the performance shown for the large database. Larger studies utilizing recognized skin tone scales to ensure accurate assessment of skin pigmentation are planned for the future.

Authors

Institutions

Publication Details

Journal
Medical Devices Evidence and Research
Published
2024-11-01
DOI
https://doi.org/10.2147/mder.s492561
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Initial Validation of the NOL Nociception Level Index® Monitoring System in Black and Multiracial People

Rachel Weissbrod, Charlene Blake
Medical Devices Evidence and Research
Heart Rate Variability and Autonomic Control
article

Initial Validation of the NOL Nociception Level Index® Monitoring System in Black and Multiracial People

Rachel Weissbrod, Charlene Blake
article en

Abstract

The NOL-Nociception Level Index<sup>®</sup> is a multiparameter index, based on artificial intelligence for the monitoring of nociception (physiological pain response) during anesthesia that has recently been authorized by the FDA. The monitor utilizes continuous streams of information from a finger probe comprising four sensors, including photoplethysmography, to provide a personalized nociception score on a scale of 0-100. Recent studies have suggested racial bias in pulse oximeter measurements due to the effect of melanin levels on photoplethysmography measurements. Therefore, there is a need to clinically validate new monitoring technologies in patients of all skin tones. The performance of the NOL scale in 8 patients that self-identified as Black or multiracial was compared to a database of 447 consented patients, assessing the response to surgical events at different levels of intensity. The descriptive, pilot data suggest that NOL performance in Black and multiracial patients is not different from the performance shown for the large database. Larger studies utilizing recognized skin tone scales to ensure accurate assessment of skin pigmentation are planned for the future.

Medical Devices Evidence and ResearchVol. Volume 17
University of California, San Francisco (US), University of San Francisco (US)
Gender equality
Openalex Percentile: Top 63%
Heart Rate Variability and Autonomic Control
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Initial Validation of the NOL Nociception Level Index® Monitoring System in Black and Multiracial People — Rachel Weissbrod, Charlene Blake · Medical Devices Evidence and Research (2024) | TGRS Research Map | TGRS