Using Artificial Intelligence (AI)-Assisted Pulse Diagnosis Analysis on Precision Critical Medicine.
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 45
- 试验地点
- 1
- 主要终点
- 28-days mortality
研究概览
简要总结
Precision/personalized medicine becomes an important part of modern medical system in the recent years. In the past, the treatments for patients have been decided by doctors according patients' symptoms and/or regular biochemical profiles. However, it is not uncommon that patients' condition varies tremendously even they have same diagnosis, and under such condition, treatment efficacy may be limited due to the heterogeneity among patients. Therefore, lack of therapeutic efficacy may be not really ineffective, and the main reason may be inadequate patient classification. For this reason, the "omics"-based personal/precision medicine emerges recently and becomes more and more important. However, in contrast to feasible and common "personalized" medicine, the approach of precision medicine to the molecular medicine level is still difficult, especially among patients in intensive critical units (ICUs). In contrast to cancer, which has remarkable advances in the past decades, the precision/personal medicine is more difficult in critical and emergent medicine. One reason is the amount of omics data is quite huge and thus dealing with omics data is time consuming. Therefore, it is not effective in daily clinical practice in ICUs care. For this condition, the investigators propose that the combination of clinical data, including pulse diagnosis by traditional Chinese medicine (TCM) doctor or ANSwatch wrist sphygmomanometer, fluid responsiveness by "Masimo" Radical-7 Pulse CO-Oximeter, and the specific database from monitors in ICUs may be a feasible way to predict outcome among ICU patients. There are two main goals for this study: (1) After establishing clinical traditional Chinese medicine (TCM) pulse diagnosis and ICU clinical parameters databases, acquiring and features of pulse diagnosis by applying AI and (2) analyzing the correlations between the features of pulse diagnosis and important clinical parameters.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Prospective
入排标准
- 年龄范围
- 20 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •1.The patient in ICU is willing to participate in the research project or patient's family member is willing patient to participate in the research project.
- •2.Acute circulatory failure
排除标准
- •The patient do not want to participate in the research project or patient's family member do not want the patient to participate in the research project.
- •Pregnant woman.
- •Goals of treatment is palliative care.
- •Patient is heritable immunodeficiency or acquired immunodeficiency.
- •Known existing cardiac arrhythmia, valvular heart disease, right ventricular dysfunction, intra-cardiac shunt, air leaking from chest drains, abdominal compartment syndrome.
结局指标
主要结局
28-days mortality
时间窗: 28 days
The investigators track the enrolled ICU patients for 28 days and record the date and cause of participants' death.
Pulse diagnosis
时间窗: Day1, Day4, Day8, Day11, Day15, Day18, Day22, Day25
Pulse diagnosis in radial artery is recorded by traditional Chinese medicine physician and ANSwatch wrist sphygmomanometer at the same time. With the help of artificial intelligence, the investigators will find the correlation/comparison of pulse diagnosis by physician or machine and hope to define which pulse waveform characteristics could predict the prognosis/outcome in ICU patients.
次要结局
- Heart rate variability(Day1, Day4, Day8, Day11, Day15, Day18, Day22, Day25,)
- Fluid-responsiveness(Day1, Day4, Day8, Day11, Day15, Day18, Day22, Day25)
- Hemodynamic status(Day1, Day4, Day8, Day11, Day15, Day18, Day22, Day25)