Validation of the Nociception Level Index for the Detection of Nociception and Pain in Critically Ill Adults: Protocol for an Observational Study
Bibliographic record
Abstract
BACKGROUND: In the intensive care unit (ICU), many patients are unable to communicate their pain through self-reporting or behaviors due to their critical care condition, mechanical ventilation, and medication (eg, heavily sedated or chemically paralyzed). Therefore, alternative pain assessment methods are urgently needed for this vulnerable patient population. The Nociception Level (NOL) index is a multiparameter technology initially developed for the monitoring of nociception and related pain in anesthetized patients, and its use in the ICU is new. OBJECTIVE: This study aims to validate the NOL for the assessment of nociception and related pain in critically ill adults in the ICU. Specific objectives are to examine the ability of the NOL to: (1) detect pain using standard criteria (ie, self-report and behavioral measures), (2) discriminate between nociceptive and nonnociceptive procedures, and (3) generate consistent values when patients are at rest. METHODS: The NOL will be monitored in three ICU patient groups: (1) Group A, participants able to self-report their pain (the reference standard criterion using the 0-10 Faces Pain Thermometer) and express behaviors; (2) Group B, participants unable to self-report but able to express behaviors (the alternative standard criterion using the Critical-Care Pain Observation Tool); and (3) Group C, participants unable to self-report and express behaviors. The NOL will be tested before, during, and after two types of standard care procedures: (1) nonnociceptive (eg, cuff inflation to measure blood pressure, soft touch) and (2) nociceptive (eg, tube or drain removal, endotracheal or tracheal suctioning). Receiver operating characteristic curve analysis of the NOL will be performed for Groups A and B using pain standard measures as reference criteria. Mixed linear models for repeated measures will be used to compare time points, procedures, and their interaction in each group (A, B, and C). Based on power analyses and considering an attrition rate of 25%, a total sample size of 146 patients (68 in Group A, 62 in Group B, and 16 in Group C) is targeted. RESULTS: This study was funded in April 2020 but could not be launched until 2022 due to the COVID-19 pandemic. Recruitment and data collection began at the primary site in July 2022 and has been implemented at the secondary sites in 2023 and 2024 and is planned to continue until 2026. CONCLUSIONS: The primary strength of this study protocol is that it is based on rigorous validation strategies with the use of pain standard criteria (ie, self-report and behavioral measures). If found to be valid, the NOL could be used as an alternative physiologic measure of pain in critically ill adults for whom no other pain assessment methods are available. TRIAL REGISTRATION: ClinicalTrials.gov NCT05339737; https://clinicaltrials.gov/study/NCT05339737. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/60672.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.051 | 0.039 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".