Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA.
Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
Am J Addict. 2022 Nov;31(6):535-545. doi: 10.1111/ajad.13341. Epub 2022 Sep 5.
Substance use disorders (SUDs) are chronic relapsing diseases characterized by significant morbidity and mortality. Phenomenologically, patients with SUDs present with a repeating cycle of intoxication, withdrawal, and craving, significantly impacting their diagnosis and treatment. There is a need for better identification and monitoring of these disease states. Remote monitoring chronic illness with wearable devices offers a passive, unobtrusive, constant physiological data assessment. We evaluate the current evidence base for remote monitoring of nonalcohol, nonnicotine SUDs.
We performed a systematic, comprehensive literature review and screened 1942 papers.
We found 15 studies that focused mainly on the intoxication stage of SUD. These studies used wearable sensors measuring several physiological parameters (ECG, HR, O , Accelerometer, EDA, temperature) and implemented study-specific algorithms to evaluate the data.
Studies were extracted, organized, and analyzed based on the three SUD disease states. The sample sizes were relatively small, focused primarily on the intoxication stage, had low monitoring compliance, and required significant computational power preventing "real-time" results. Cardiovascular data was the most consistently valuable data in the predictive algorithms. This review demonstrates that there is currently insufficient evidence to support remote monitoring of SUDs through wearable devices.
This is the first systematic review to show the available data on wearable remote monitoring of SUD symptoms in each stage of the disease cycle. This clinically relevant approach demonstrates what we know and do not know about the remote monitoring of SUDs within disease states.
物质使用障碍（SUD）是一种慢性复发性疾病，其特征是发病率和死亡率高。从现象学上看，SUD 患者表现出反复的中毒、戒断和渴望循环，这对他们的诊断和治疗有重大影响。需要更好地识别和监测这些疾病状态。使用可穿戴设备对慢性病进行远程监测提供了一种被动、不引人注目的、持续的生理数据评估方法。我们评估了远程监测非酒精、非尼古丁 SUD 的现有证据基础。
我们进行了系统、全面的文献综述，并筛选了 1942 篇论文。
我们发现了 15 项主要关注 SUD 中毒阶段的研究。这些研究使用可穿戴传感器测量了几个生理参数（ECG、HR、O 、加速度计、EDA、温度），并实施了特定于研究的算法来评估数据。
根据 SUD 的三种疾病状态提取、组织和分析了研究。样本量相对较小，主要集中在中毒阶段，监测依从性低，需要大量的计算能力来防止“实时”结果。心血管数据是预测算法中最有价值的数据。这项综述表明，目前没有足够的证据支持通过可穿戴设备远程监测 SUD。
这是第一项系统综述，展示了可穿戴设备远程监测疾病周期各阶段 SUD 症状的现有数据。这种临床相关的方法展示了我们对 SUD 远程监测在疾病状态下的了解和未知。
