Validation of the Diabetes Deep Neural Network Score for Diabetes Mellitus Screening
试验速览
- 阶段
- 不适用
- 状态
- 撤回
- 入组人数
- 6,006
- 试验地点
- 2
- 主要终点
- The area under the receiver operating characteristic (AUROC) of the DNN Score as compared with one HBA1c measurement, based an average of two PPG measurements.
研究概览
简要总结
The Validation of the Diabetes Deep Neural Network Score (DNN score) for Screening for Type 2 Diabetes Mellitus (diabetes) is a single center, unblinded, observational study to clinically validating a previously developed remote digital biomarker, identified as the DNN score, to screen for diabetes. The previously developed DNN score provides a promising avenue to detect diabetes in these high-risk communities by leveraging photoplethysmography (PPG) technology on the commercial smartphone camera that is highly accessible. Our primary aim is to prospectively clinically validate the PPG DNN algorithm against the reference standards of glycated hemoglobin (HbA1c) for the presence of prevalent diabetes. Our vision is that this clinical trial may ultimately support an application to the Food and Drug Administration so that it can be incorporated into guideline-based screening.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Parallel
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Age > 18 years old
- •Participants without a prior diagnosis of DM
- •Participants with a recently measured HBA1c one month before enrollment or scheduled to undergo a HBA1c measurement within one month after enrollment
- •Participants not scheduled for HBA1c and are willing to undergo a lab measured HBA1c
- •Participants without risk factors for DM
- •Participants with > 1 of the following risk factors for DM:
- •Age > 40 years old
- •Obesity (BMI > 30)
- •Family history: Any first degree relative with a hx of DM
- •Lifestyle risk factors (exercise, smoking, and sleep duration)
- •Ownership of a smart phone
- •Able to provide informed consent
- •Willingness to provide PPG waveforms
排除标准
- •Participants with a history of DM
- •Participants with a prior HBA1c > 6.5%
- •Inability to collect PPG signals (digit amputation, excessive tremors, etc)
- •Lack of ownership of a smartphone
- •Inability or unwillingness to consent and/or follow requirements of the study
结局指标
主要结局
The area under the receiver operating characteristic (AUROC) of the DNN Score as compared with one HBA1c measurement, based an average of two PPG measurements.
时间窗: PPG measurements and DNN score to be obtained within one month oh HBA1c measurement
Participants will provide seven total PPG measurements by their own smartphone camera. After PPG measurements are obtained, the DNN algorithm will be deployed and be reported a as a DNN score. The investigators will assess the DNN performance by the the area under the receiver operating characteristic (AUROC) of the DNN Score as compared with the HBA1c based on the DNN score from an average of 2 PPG measurements.
The Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value of the DNN Score as compared with one HBA1c measurement based an average of two PPG measurements.
时间窗: PPG measurements and DNN score to be obtained within one month oh HBA1c measurement
Participants will provide seven total PPG measurements by their own smartphone camera. After PPG measurements are obtained, the DNN algorithm will be deployed and be reported as a DNN score. The investigators will assess the DNN performance by the Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value of the DNN Score as compared with the HBA1c based on the DNN score from an average of 2 PPG measurements.
Assess the performance of the DNN score in different ethnicity and skin tones
时间窗: PPG measurements and DNN score to be obtained within one month oh HBA1c measurement
The investigators will aim to recruit individuals of different races/ethnicities and skin tones to assess the performance of the DNN score in different races/ethnicities.
次要结局
- The area under the receiver operating characteristic (AUROC) of the DNN Score as compared with one HBA1c measurement based on > 2 PPG measurements.(PPG measurements and DNN score to be obtained within one month oh HBA1c measurement)
- The Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value of the DNN Score as compared with one HBA1c measurement based on >2 PPG measurements.(PPG measurements and DNN score to be obtained within one month oh HBA1c measurement)
- Retrain the DNN algorithm(Retraining to occur after complete collection of PPG measurements and HBA1c data. The investigators estimate this will occur one year after enrollment.)