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Erschienen in: Journal of Clinical Monitoring and Computing 1/2023

04.08.2022 | Original Research

Prediction of acute postoperative pain based on intraoperative nociception level (NOL) index values: the impact of machine learning-based analysis

verfasst von: Louis Morisson, Mathieu Nadeau-Vallée, Fabien Espitalier, Pascal Laferrière-Langlois, Moulay Idrissi, Nadia Lahrichi, Céline Gélinas, Olivier Verdonck, Philippe Richebé

Erschienen in: Journal of Clinical Monitoring and Computing | Ausgabe 1/2023

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Abstract

The relationship between intraoperative nociception and acute postoperative pain is still not well established. The nociception level (NOL) Index (Medasense, Ramat Gan, Israel) uses a multiparametric approach to provide a 0–100 nociception score. The objective of the ancillary analysis of the NOLGYN study was to evaluate the ability of a machine-learning aglorithm to predict moderate to severe acute postoperative pain based on intraoperative NOL values. Our study uses the data from the NOLGYN study, a randomized controlled trial that evaluated the impact of NOL-guided intraoperative administration of fentanyl on overall fentanyl consumption compared to standard of care. Seventy patients (ASA class I–III, aged 18–75 years) scheduled for gynecological laparoscopic surgery were enrolled. Variables included baseline demographics, NOL reaction to incision or intubation, median NOL during surgery, NOL time-weighted average (TWA) above or under manufacturers’ recommended thresholds (10–25), and percentage of surgical time spent with NOL > 25 or < 10. We evaluated different machine learning algorithms to predict postoperative pain. Performance was assessed using cross-validated area under the ROC curve (CV-AUC). Of the 66 patients analyzed, 42 (63.6%) experienced moderate to severe pain. NOL post-intubation (42.8 (31.8–50.6) vs. 34.8 (25.6–41.3), p = 0.05), median NOL during surgery (13 (11–15) vs. 11 (8–13), p = 0.027), percentage of surgical time spent with NOL > 25 (23% (18–18) vs. 20% (15–24), p = 0.036), NOL TWA < 10 (2.54 (2.1–3.0) vs. 2.86 (2.48–3.62), p = 0.044) and percentage of surgical time spent with NOL < 10 (41% (36–47) vs. 47% (40–55), p = 0.022) were associated with moderate to severe PACU pain. Corresponding ROC AUC for the prediction of moderate to severe PACU pain were 0.65 [0.51–0.79], 0.66 [0.52–0.81], 0.66 [0.52–0.79], 0.65 [0.51–0.79] and 0.67 [0.53–0.81]. Penalized logistic regression achieved the best performance with a 0.753 (0.718–0.788) CV-AUC. Our results, even if limited by the small number of patients, suggest that acute postoperative pain is better predicted by a multivariate machine-learning algorithm rather than individual intraoperative nociception variables. Further larger multicentric trials are highly recommended to better understand the relationship between intraoperative nociception and acute postoperative pain.
Trial registration Registered on ClinicalTrials.gov in October 2018 (NCT03776838).
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Literatur
6.
Zurück zum Zitat Espitalier F, Idrissi M, Fortier A, Belanger ME, Carrara L, Dakhlallah S, et al. Impact of nociception level (NOL) index intraoperative guidance of fentanyl administration on opioid consumption, postoperative pain scores and recovery in patients undergoing gynecological laparoscopic surgery. A randomized controlled trial. J Clin Anesth. 2021;75:110497. https://doi.org/10.1016/j.jclinane.2021.110497.CrossRef Espitalier F, Idrissi M, Fortier A, Belanger ME, Carrara L, Dakhlallah S, et al. Impact of nociception level (NOL) index intraoperative guidance of fentanyl administration on opioid consumption, postoperative pain scores and recovery in patients undergoing gynecological laparoscopic surgery. A randomized controlled trial. J Clin Anesth. 2021;75:110497. https://​doi.​org/​10.​1016/​j.​jclinane.​2021.​110497.CrossRef
17.
Zurück zum Zitat Lundberg SM, Lee S-I (2017) A unified approach to interpreting model predictions. Proceedings of the 31st International Conference on Neural Information Processing Systems. Curran Associates Inc, Long Beach Lundberg SM, Lee S-I (2017) A unified approach to interpreting model predictions. Proceedings of the 31st International Conference on Neural Information Processing Systems. Curran Associates Inc, Long Beach
Metadaten
Titel
Prediction of acute postoperative pain based on intraoperative nociception level (NOL) index values: the impact of machine learning-based analysis
verfasst von
Louis Morisson
Mathieu Nadeau-Vallée
Fabien Espitalier
Pascal Laferrière-Langlois
Moulay Idrissi
Nadia Lahrichi
Céline Gélinas
Olivier Verdonck
Philippe Richebé
Publikationsdatum
04.08.2022
Verlag
Springer Netherlands
Erschienen in
Journal of Clinical Monitoring and Computing / Ausgabe 1/2023
Print ISSN: 1387-1307
Elektronische ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-022-00897-z

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