Santamaria Mar, Christakis Yiorgos, Demanuele Charmaine, Zhang Yao, Tuttle Pirinka Georgiev, Mamashli Fahimeh, Bai Jiawei, Landman Rogier, Chappie Kara, Kell Stefan, Samuelsson John G, Talbert Kisha, Seoane Leonardo, Mark Roberts W, Kabagambe Edmond Kato, Capelouto Joseph, Wacnik Paul, Selig Jessica, Adamowicz Lukas, Khan Sheraz, Mather Robert J
Pfizer Inc., Cambridge, MA, USA.
Ochsner Health, New Orleans, LA, USA.
NPJ Digit Med. 2025 Apr 11;8(1):202. doi: 10.1038/s41746-025-01584-4.
The Acute Respiratory Illness Surveillance (AcRIS) Study was a low-interventional trial that examined voice changes with respiratory illnesses. This longitudinal trial was the first of its kind, conducted in a fully decentralized manner via a Bring Your Own Device mobile application. The app enabled social-media-based recruitment, remote consent, at-home sample collection, and daily remote voice and symptom capture in real-world settings. From April 2021 to April 2022, the trial enrolled 9151 participants, followed for up to eight weeks. Despite mild symptoms experienced by reverse transcription polymerase chain reaction (RT-PCR) positive participants, two machine learning algorithms developed to screen respiratory illnesses reached the pre-specified success criteria. Algorithm testing on independent cohorts demonstrated that the algorithm's sensitivity increased as symptoms increased, while specificity remained consistent. Study findings suggest voice features can identify individuals with viral respiratory illnesses and provide valuable insights into fully decentralized clinical trials design, operation, and adoption (study registered at ClinicalTrials.gov (NCT04748445) on 5 February 2021).
急性呼吸道疾病监测（AcRIS）研究是一项低干预试验，旨在研究呼吸道疾病引起的声音变化。这项纵向试验尚属首次，通过自带设备移动应用程序以完全分散的方式进行。该应用程序支持基于社交媒体的招募、远程同意、在家中采集样本，以及在现实环境中每天远程采集声音和症状信息。从2021年4月到2022年4月，该试验招募了9151名参与者，随访时间长达八周。尽管逆转录聚合酶链反应（RT-PCR）呈阳性的参与者症状较轻，但为筛查呼吸道疾病而开发的两种机器学习算法达到了预先设定的成功标准。在独立队列上进行的算法测试表明，随着症状加重，该算法的敏感性增加，而特异性保持一致。研究结果表明，声音特征可以识别患有病毒性呼吸道疾病的个体，并为完全分散的临床试验设计、操作和应用提供有价值的见解（该研究于2021年2月5日在ClinicalTrials.gov（NCT04748445）注册）。
