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Smart respiratory monitoring: clinical development and validation of the IPI™ (Integrated Pulmonary Index) algorithm

机译:智能呼吸监测:IPI™(综合肺指数)算法的临床开发和验证

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摘要

Continuous electronic monitoring of patient respiratory status frequently includes PetCO2 (end tidal CO2), RR (respiration rate), SpO2 (arterial oxygen saturation), and PR (pulse rate). Interpreting and integrating these vital signs as numbers or waveforms is routinely done by anesthesiologists and intensivists but is challenging for clinicians in low acuity areas such as medical wards, where continuous electronic respiratory monitoring is becoming more common place. We describe a heuristic algorithm that simplifies the interpretation of these four parameters in assessing a patient’s respiratory status, the Integrated Pulmonary Index (IPI). The IPI algorithm is a mathematical model combining SpO2, RR, PR, and PetCO2 into a single value between 1 and 10 that summarizes the adequacy of ventilation and oxygenation at that point in time. The algorithm was designed using a fuzzy logic inference model to incorporate expert clinical opinions. The algorithm was verified by comparison to experts’ scoring of clinical scenarios. The validity of the index was tested in a retrospective analysis of continuous SpO2, RR, PR, and PetCO2 readings obtained from 523 patients in a variety of clinical settings. IPI correlated well with expert interpretation of the continuous respiratory data (R = 0.83, p <<< 0.001), with agreement of −0.5 ± 1.4. Receiver operating curves analysis resulted in high levels of sensitivity (ranging from 0.83 to 1.00), and corresponding specificity (ranging from 0.96 to 0.74), based on IPI thresholds 3−6. The IPI reliably interpreted the respiratory status of patients in multiple areas of care using off-line continuous respiratory data. Further prospective studies are required to evaluate IPI in real time in clinical settings.
机译:对患者呼吸状态的连续电子监控通常包括PetCO2(呼气末CO2),RR(呼吸率),SpO2(动脉血氧饱和度)和PR(脉率)。这些生命体征以数字或波形的形式进行解释和整合通常是由麻醉师和强化医师完成的,但是对于低敏锐度地区(例如病房)的临床医生来说却是一个挑战,在这些地区,连续电子呼吸监测正变得越来越普遍。我们描述了一种启发式算法,该算法可简化评估患者呼吸状态的这四个参数的解释,即综合肺指数(IPI)。 IPI算法是将SpO2,RR,PR和PetCO2合并为一个介于1到10之间的单个值的数学模型,该值总结了该时间点的通风和充氧情况。该算法是使用模糊逻辑推理模型设计的,以纳入专家的临床意见。通过与专家对临床情况的评分比较,验证了该算法。该指标的有效性通过对从523例患者在各种临床环境中获得的连续SpO2,RR,PR和PetCO2读数进行回顾性分析进行了测试。 IPI与持续呼吸数据的专家解释(R = 0.83,p < 0.001)很好地相关,一致为-0.5±1.4。接收器工作曲线分析基于IPI阈值3-6,导致高水平的灵敏度(从0.83到1.00)和相应的特异性(从0.96到0.74)。 IPI使用离线连续呼吸数据可靠地解释了多个护理领域中患者的呼吸状况。需要进一步的前瞻性研究以在临床环境中实时评估IPI。

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