To assess whether the patient's self-reported pain level is associated with a multivariate physiological biomarker bias achieved in the actual clinical setting. This study will use a clinical-grade wearable sensor to continuously monitor the patient's physiological condition (pain-related biomarkers) and use the mobile app to allow participants to actively report their pain scores, symptoms and quality of life.After analysis of the biomarkers we may predict the coming pain attacks by way of the meaningful biomarkers.
Subjective scores have traditionally been used to measure human pain, such as the visual analog scale (VAS) to determine the presence or absence of pain and its severity. People can only express the pain experienced by dictation, scale, and image depicting the degree of pain. Although this is important information, the self-evaluation method has problems for diagnosis and research purposes. The results of a person's self-assessment depend on past pain experiences and many other cognitive and behavioral factors and therefore change over time. In addition, it is difficult to obtain a reliable comparison between the rewards of different people. When the patient complains of a certain degree of pain, it is impossible to know whether it is equivalent to the same pain described by other patients. Moreover, it is difficult to obtain self-evaluation results among ethnic groups of different natures, such as young people, patients who block the transmission of ideas due to different disease types, and those who are unconscious. A variety of survey-based pain scales and functions have been developed recently, and the utility has improved. However, because it is still based on self-assessment, it will leave some of the same problems with self-assessment. Developmental measurements of biomarkers or surrogate markers with acute and/or chronic pain have made significant progress over the past few years. Thanks to the development of new and improved technologies, such as in the field of angiography and wearable biosensors, there has been considerable development. Studies have shown that pupils respond to a variety of different stimuli and may predict the presence of pain. There are many different physiological parameters, such as changes in heart rate, pulsating components of the heart cycle, and skin activity, which have been shown to be associated with the presence or absence of pain. From the development of research in this field, it is feasible to develop clinical tools for measuring the presence or absence of acute and/or chronic pain, including cancer pain, using biomarkers or surrogate markers. This objective tool can make more significant advances in clinical pain research and treatment.
Study Type
OBSERVATIONAL
Enrollment
20
Taichung Veterans General Hospital
Taichung, Taiwan
RECRUITINGPain Reporting by pain intensity and body map
Patient will report pain intensity in Numerical Rating Scale (NRS) from 0-10 through smartphone and when they suffer from pain. If possible they will type in the medications they take when they suffer from moderate (NRS\>=4) to severe pain (NRS\>=7). Besides, they may choosing the location of pain using a validated body map and logging the time the pain event took place to the nearest 15 minutes.
Time frame: 30days
Symptom Reporting and record of EQ-5D-3L (Quality of Life Questionnaire)
There are 5 dimensions in the record of EQ-5D-3L (3-level version of the EuroQol-5 Dimension of health questionnaire) including mobility, self-care, usual activities, pain/ discomfort, and anxiety/ depression. There are 3 severity levels (no such problem, some problems/ moderately affected, unable to perform activities or extremely affected) in each dimensions of evaluation. The labels 1-3 describe different severity levels in a dimension and are used to form part of a numerical description of a health state. The second part is the EQ VAS (EuroQol visual analogue scale) records the respondent's self-rated health on a vertical VAS scled from 0 to 100 where the endpoints 0 and 100 are labelled 'The worst health you can imagine' and 'The best health you can imagine'. This information can be used as a quantitative measure of health outcome as judged by the individual respondents
Time frame: 30 days
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