Pain Detection Through Automated Video Analysis (FXPAL)
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|ClinicalTrials.gov Identifier: NCT04011189|
Recruitment Status : Active, not recruiting
First Posted : July 8, 2019
Last Update Posted : August 4, 2020
|Condition or disease||Intervention/treatment||Phase|
|Pain, Postoperative||Procedure: Videotaping Other: Questionnaires||Not Applicable|
Post-surgical pain, if inadequately controlled, has deleterious short and long term consequences for the patient. Although most patients are able to report their pain scores, a minority are unable to do so and assessing their pain can prove to be a challenge for healthcare professionals. In recent years, facial recognition tools have been developed based on the premise that subtle facial variations signifies pain. However, changes in body, and head posture can also represent pain. As such, these tools are with their limitations and are only validated on certain groups of patients, thus may not be sensitive enough to detect pain in post-surgical patients.
This pilot study will be conducted on 20 patients presenting for major gynaecological surgery, with the obtained data used to fine tune the algorithm. The patients will be video-taped pre-surgically in the pre-evaluation anaesthetic clinic and post-surgically in the ward. They will be asked to rate their pain scores on the numerical rating scale and fill in questionnaires on their psychological and quality of health status. The pain scores will be correlated with the results obtained from the pain assessment algorithm. The refined algorithm can be subsequently evaluated with a larger group of patients undergoing different pain conditions, and could potentially be used in clinical practice as a tool to assess pain if found to be sensitive.
|Study Type :||Interventional (Clinical Trial)|
|Actual Enrollment :||28 participants|
|Intervention Model:||Single Group Assignment|
|Masking:||None (Open Label)|
|Primary Purpose:||Supportive Care|
|Official Title:||Pain Detection Through Automated Video Analysis|
|Actual Study Start Date :||August 1, 2019|
|Actual Primary Completion Date :||June 30, 2020|
|Estimated Study Completion Date :||December 31, 2020|
Upon successful recruitment of the study, patients will be asked to complete 2 questionnaires and rate their pre-surgical pain on the numerical rating scale in the pre-anaesthetic evaluation clinic. Their face and body pose from a frontal view will be videotaped.
The general anaesthesia technique and type of analgesia administered intra-operatively will be according to standard practice and is at the discretion of the attending anaesthesiologist. After surgery, patients will be reviewed at 12-36 hrs, 36 hrs till before discharge post-operatively in the ward. They will be asked to rate their pain scores and videotaping will be done from a frontal view.
Before the videotaping, patients will be asked on their baseline pain scores. Their face and body pose from a frontal view will be videotaped via a mobile phone with no internet access. The collected videos will be further processed to extract keypoints (70 points to capture key facial landmark locations and 25 points to capture joint locations), which will be the primary input for modeling algorithms and will further ensure anonymity of the patients in the video sequences.
Other Name: Videotaping via mobile phone
Patients will be asked to fill in two questionnaires before surgery (Hospital Anxiety and Depression Scale (HADS), EQ-5D-3L). After surgery, patients will be again asked to fill in HADS questionnaire daily post-operatively.
Other Name: Questionnaires (HADS, EQ-5D-3L)
- Change in Pain score [ Time Frame: Before surgery (1 day) and after surgery (1-2 days) ]Difference of Pain score before and after surgery. Pain scores (Numeric Rating Scale 0-10) will be asked, with zero being no pain, and 10 being the worst pain possible.
- Extracted key points from video [ Time Frame: Before surgery (1 day) and after surgery (1-2 days) ]The collected videos will be further processed to extract keypoints (70 points to capture key facial landmark locations and 25 points to capture joint locations), which will be the primary input for modeling algorithms and will further ensure anonymity of the patients in the video sequences. This will then be used for pain score prediction by correlated to outcome 1 (patients' reported pain score).
- Change in Hospital Anxiety and Depression Scale (HADS) score [ Time Frame: Before surgery (1 day) and after surgery (1-2 days) ]HADS Anxiety and Depression score before and after surgery. HADS is commonly used by doctors to determine the levels of anxiety and depression that a patient is experiencing. Each item on the questionnaire is scored from 0-3 and this means that a person can score between 0 and 21 for either anxiety or depression. The HADS uses a scale and therefore the data returned from the HADS is ordinal. For each subscore (anxiety/depression), 0-7 = Normal; 8-10 = Borderline abnormal (borderline case); and 11-21 = Abnormal (case).
- EQ-5D-3L score [ Time Frame: Before surgery (1 day) ]EQ-5D-3L score before surgery. EQ-5D-3L is a standardized instrument for measuring generic health status. It is made up for two components; health state description and evaluation. The health status is measured in terms of five dimensions (5D); mobility, self-care, usual activities, pain/discomfort, and anxiety/depression; each dimension ranging from 1-3. From these five dimensions, EQ-5D index is calculated, having a value between 0-1. The evaluation part involves an analogue scale, asking to mark health status on the day of the interview on a 20 cm vertical scale with end points of 0 and 100. Zero corresponds to " the worst health you can imagine", and hundred corresponds to "the best health you can imagine".
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04011189
|KK Women's and Children's Hospital|
|Singapore, Singapore, 229899|
|Principal Investigator:||John Lee, M Med||KK Women's and Children's Hospital|