Reichl J J, Leifke M, Wehrli S, Kunz D, Geissmann L, Broisch S, Illien M, Wellauer D, von Dach N, Diener S, Manser V, Herren V, Angerer A, Hirsch S, Hölz B, Eckstein J
Department of Internal Medicine, University Hospital of Basel, Petersgraben 4, CH-4031, Basel, Switzerland.
Innovationmanagement, University of Basel, Basel, Switzerland.
Arch Public Health. 2024 Oct 8;82(1):179. doi: 10.1186/s13690-024-01409-y.
Acute deteriorations of health status are common in hospitalized patients and are often preceded by changes in their vital signs. Events such as heart attacks, death or admission to the intensive care unit can be averted by early detection, therefore so-called Early Warning Scores (EWS) such as the National Early Warning Score 2 (NEWS2), including basic vital parameters such as heart rate, blood pressure, respiratory rate, temperature and level of consciousness, have been developed for a systematic approach. Although studies have shown that EWS have a positive impact on patient outcomes, they are often limited by issues such as calculation errors, time constraints, and a shortage of human resources. Therefore, development of tools for automatic calculation of EWS could help improve quality of EWS calculation and may improve patient outcomes. The aim of this study is to analyze the feasibility of wearable devices for the automatic calculation of NEWS2 compared to conventional calculation using vital signs measured by health care professionals.
We conducted a prospective trial at a large tertiary hospital in Switzerland. Patients were given a wristband with a photoplethysmogram (PPG) sensor that continuously recorded their heart rate and respiratory rate for 3 consecutive days. Combined with data from the electronic health record (EHR), NEWS2-score was calculated and compared to NEWS2 score calculated from vital parameters in the EHR measured by medical staff. The main objective of our study was to assess the agreement between NEWS2 scores calculated using both methods. This analysis was conducted using Cohen's Kappa and Bland-Altman analysis. Secondary endpoints were compliance concerning the medical device, patient acceptance, data quality analysis and data availability and signal quality for all time stamps needed for accurate calculation.
Of 210 patients enrolled in our study, NEWS2 was calculated in 904 cases, with 191 cases being directly compared to conventional measurements. Thirty-three of these measurements resulted in a NEWS2 ≥ 5, 158 in a NEWS2 < 5. Comparing all 191 measurements, accordance was substantial (K = 0.76) between conventional and automated NEWS2. No adverse effects due to the device were recorded. Patient acceptance was high.
In conclusion, the study found strong agreement between automated and conventional NEWS2 calculations using wearable devices, with high patient acceptance despite some data quality challenges. To maximize the potential of continuous monitoring, further research into fully automated EWS calculations without relying on spot measurements is suggested, as this could provide a reliable alternative to traditional methods.
January 26, 2023, NCT05699967.
健康状况的急性恶化在住院患者中很常见,且往往先于生命体征的变化。通过早期检测可以避免心脏病发作、死亡或入住重症监护病房等情况,因此,诸如国家早期预警评分2(NEWS2)等所谓的早期预警评分(EWS)已经被开发出来,用于系统评估,其中包括心率、血压、呼吸频率、体温和意识水平等基本生命参数。尽管研究表明EWS对患者预后有积极影响,但它们常常受到计算错误、时间限制和人力资源短缺等问题的限制。因此,开发用于自动计算EWS的工具可能有助于提高EWS计算的质量,并可能改善患者预后。本研究的目的是分析与使用医护人员测量的生命体征进行传统计算相比,可穿戴设备自动计算NEWS2的可行性。
我们在瑞士一家大型三级医院进行了一项前瞻性试验。为患者佩戴一个带有光电容积脉搏波描记法(PPG)传感器的腕带,该传感器连续3天记录他们的心率和呼吸频率。结合电子健康记录(EHR)中的数据,计算NEWS2评分,并与根据医护人员在EHR中测量的生命参数计算出的NEWS2评分进行比较。我们研究的主要目的是评估两种方法计算出的NEWS2评分之间的一致性。使用科恩kappa系数和布兰德-奥特曼分析进行此分析。次要终点包括医疗设备的依从性、患者接受度、数据质量分析、数据可用性以及准确计算所需的所有时间戳的信号质量。
在我们研究纳入的210名患者中,共计算了904例NEWS2评分,其中191例与传统测量值直接比较。这些测量中有33例的NEWS2≥5,158例的NEWS2<5。比较所有191次测量,传统计算和自动计算的NEWS2之间一致性较高(K = 0.76)。未记录到该设备引起的不良反应。患者接受度较高。
总之,该研究发现使用可穿戴设备进行自动计算和传统计算的NEWS2之间有很强的一致性,尽管存在一些数据质量挑战,但患者接受度较高。为了最大限度地发挥连续监测的潜力,建议进一步研究不依赖于即时测量的全自动EWS计算方法,因为这可能为传统方法提供可靠的替代方案。
2023年1月26日,NCT05699967。