Chiera Marco, Cerritelli Francesco, Casini Alessandro, Barsotti Nicola, Boschiero Dario, Cavigioli Francesco, Corti Carla G, Manzotti Andrea
Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy.
Research Commission on Manual Therapies and Mind-Body Disciplines, Societ Italiana di Psico Neuro Endocrino Immunologia, Rome, Italy.
Front Neurosci. 2020 Sep 25;14:561186. doi: 10.3389/fnins.2020.561186. eCollection 2020.
Neonatal intensive care units (NICUs) greatly expand the use of technology. There is a need to accurately diagnose discomfort, pain, and complications, such as sepsis, mainly before they occur. While specific treatments are possible, they are often time-consuming, invasive, or painful, with detrimental effects for the development of the infant. In the last 40 years, heart rate variability (HRV) has emerged as a non-invasive measurement to monitor newborns and infants, but it still is underused. Hence, the present paper aims to review the utility of HRV in neonatology and the instruments available to assess it, showing how HRV could be an innovative tool in the years to come. When continuously monitored, HRV could help assess the baby's overall wellbeing and neurological development to detect stress-/pain-related behaviors or pathological conditions, such as respiratory distress syndrome and hyperbilirubinemia, to address when to perform procedures to reduce the baby's stress/pain and interventions, such as therapeutic hypothermia, and to avoid severe complications, such as sepsis and necrotizing enterocolitis, thus reducing mortality. Based on literature and previous experiences, the first step to efficiently introduce HRV in the NICUs could consist in a monitoring system that uses photoplethysmography, which is low-cost and non-invasive, and displays one or a few metrics with good clinical utility. However, to fully harness HRV clinical potential and to greatly improve neonatal care, the monitoring systems will have to rely on modern bioinformatics (machine learning and artificial intelligence algorithms), which could easily integrate infant's HRV metrics, vital signs, and especially past history, thus elaborating models capable to efficiently monitor and predict the infant's clinical conditions. For this reason, hospitals and institutions will have to establish tight collaborations between the obstetric, neonatal, and pediatric departments: this way, healthcare would truly improve in every stage of the perinatal period (from conception to the first years of life), since information about patients' health would flow freely among different professionals, and high-quality research could be performed integrating the data recorded in those departments.
新生儿重症监护病房(NICUs)极大地扩展了技术的应用。主要在不适、疼痛和并发症(如败血症)发生之前准确诊断它们很有必要。虽然有特定的治疗方法,但这些方法往往耗时、具有侵入性或会带来疼痛,对婴儿的发育有不利影响。在过去40年里,心率变异性(HRV)已成为一种监测新生儿和婴儿的非侵入性测量方法,但仍未得到充分利用。因此,本文旨在综述HRV在新生儿学中的效用以及可用于评估它的仪器,展示HRV在未来几年如何成为一种创新工具。持续监测时,HRV有助于评估婴儿的整体健康状况和神经发育,以检测与压力/疼痛相关的行为或病理状况,如呼吸窘迫综合征和高胆红素血症,确定何时进行操作以减轻婴儿的压力/疼痛以及采取诸如治疗性低温等干预措施,并避免严重并发症,如败血症和坏死性小肠结肠炎,从而降低死亡率。基于文献和以往经验,在新生儿重症监护病房有效引入HRV 的第一步可以是一个使用光电容积脉搏波描记法的监测系统,该方法成本低且非侵入性,并显示一个或几个具有良好临床效用的指标。然而,为了充分发挥HRV的临床潜力并大幅改善新生儿护理,监测系统将不得不依赖现代生物信息学(机器学习和人工智能算法),这可以轻松整合婴儿的HRV指标、生命体征,尤其是过往病史,从而构建能够有效监测和预测婴儿临床状况的模型。因此,医院和机构将不得不建立产科、新生儿科和儿科之间的紧密合作:这样一来,围产期(从受孕到生命的头几年)的每个阶段的医疗保健都将真正得到改善,因为患者健康信息将在不同专业人员之间自由流动,并且可以整合这些科室记录的数据进行高质量的研究。