Salekin Md Sirajus, Mouton Peter R, Zamzmi Ghada, Patel Raj, Goldgof Dmitry, Kneusel Marcia, Elkins Sammie L, Murray Eileen, Coughlin Mary E, Maguire Denise, Ho Thao, Sun Yu
Computer Science and Engineering Department University of South Florida Tampa FL USA.
SRC Biosciences Tampa FL USA.
Paediatr Neonatal Pain. 2021 Aug 5;3(3):134-145. doi: 10.1002/pne2.12060. eCollection 2021 Sep.
The advent of increasingly sophisticated medical technology, surgical interventions, and supportive healthcare measures is raising survival probabilities for babies born premature and/or with life-threatening health conditions. In the United States, this trend is associated with greater numbers of neonatal surgeries and higher admission rates into neonatal intensive care units (NICU) for newborns at all birth weights. Following surgery, current pain management in NICU relies primarily on narcotics (opioids) such as morphine and fentanyl (about 100 times more potent than morphine) that lead to a number of complications, including prolonged stays in NICU for opioid withdrawal. In this paper, we review current practices and challenges for pain assessment and treatment in NICU and outline ongoing efforts using Artificial Intelligence (AI) to support pain- and opioid-sparing approaches for newborns in the future. A major focus for these next-generation approaches to NICU-based pain management is proactive pain mitigation (avoidance) aimed at preventing harm to neonates from . AI-based frameworks can use single or multiple combinations of continuous objective variables, that is, facial and body movements, crying frequencies, and physiological data (vital signs), to make high-confidence predictions about time-to-pain onset following postsurgical sedation. Such predictions would create a therapeutic window prior to pain onset for mitigation with non-narcotic pharmaceutical and nonpharmaceutical interventions. These emerging AI-based strategies have the potential to minimize or avoid damage to the neonate's body and psyche from postsurgical pain and opioid withdrawal.
日益复杂的医疗技术、外科手术干预措施以及支持性医疗保健措施的出现，正在提高早产和/或患有危及生命健康状况的婴儿的生存概率。在美国，这一趋势与更多的新生儿手术以及所有出生体重的新生儿进入新生儿重症监护病房（NICU）的更高入院率相关。手术后，目前NICU的疼痛管理主要依赖于吗啡和芬太尼（效力约为吗啡的100倍）等麻醉剂（阿片类药物），这些药物会导致一系列并发症，包括因阿片类药物戒断而在NICU停留时间延长。在本文中，我们回顾了NICU疼痛评估和治疗的当前实践与挑战，并概述了目前利用人工智能（AI）在未来支持新生儿疼痛和阿片类药物节省方法的努力。这些基于NICU的下一代疼痛管理方法的一个主要重点是主动减轻疼痛（避免疼痛），旨在防止新生儿受到伤害。基于AI的框架可以使用连续客观变量的单一或多种组合，即面部和身体动作、哭闹频率以及生理数据（生命体征），对术后镇静后疼痛发作时间做出高置信度预测。这样的预测将在疼痛发作前创造一个治疗窗口，以便通过非麻醉性药物和非药物干预措施减轻疼痛。这些新兴的基于AI的策略有可能将术后疼痛和阿片类药物戒断对新生儿身体和心理的损害降至最低或避免。
