Coronary Heart DiseaseNCT04636996
Effects of AI Assisted Follow-up Strategy on Secondary Prevention in CABG Patients
A study testing artificial intelligence assisted follow-up in people with Coronary Heart Disease and Artificial Intelligence, run by Chinese Academy of Medical Sciences, Fuwai Hospital at 1 site in China.
Trial summary
The present study is trying to find out whether artificial intelligence assisted follow-up strategy will improve secondary prevention in CABG patients. In addition, we will test whether rural patients may have more benefits under the new follow-up strategy based on the artificial intelligence device compared with… Read more about this study
- Who is it for?
- Ages 18 to 70 years
- Conditions the study is for
- Coronary Heart Disease, Artificial Intelligence, Sleep Apnea
- What is being tested?
- artificial intelligence assisted follow-up
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 200 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2021to 31 Dec 2022
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 70 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Age between 18-70, male or female
- Received isolated CABG procedure due to coronary artery disease
- Having a smartphone and are willing to cooperate
- Signing written informed consent
Who cannot join
- Patients undergoing CABG + valve replacement surgery
- Postoperative hospital stays more than 10 days (Due to limited postoperative follow-up time and unstable condition such as incision infection, angina, etc.)
- Patients with lung, liver, and kidney failure (Due to organ dysfunction which needs more professional health care and not suitable for this trial)
- Patients with Urinary system diseases (Getting up during sleep, which will interfere with sleep monitoring)
- Patients mentally or legally disabled
- Breastfeeding or pregnant women
- End-stage disease, estimated survival time is less than 3 months
- Participate in other perioperative intervention studies at the same time
Trial locations and contacts
1 site in 1 country.
China1 site
Cardiovascular Institute and Fuwai Hospital, CAMS&PUMC
Beijing, Beijing Municipality, 100037
About this study
Official title: Effects of Artificial Intelligence Assisted Follow-up Strategy Based on a New Remote Contactless Sleep Monitoring System on Secondary Prevention in Patients Received Coronary Artery Bypass Grafting Surgery
The present study is trying to find out whether artificial intelligence assisted follow-up strategy will improve secondary prevention in CABG patients. In addition, we will test whether rural patients may have more benefits under the new follow-up strategy based on the artificial intelligence device compared with urban patients.
Read the detailed description
There are a large population of coronary heart disease patients in China, which needs more attention to optimize the secondary prevention and improve the prognosis. Secondary prevention has been showing the effects of improving symptoms, preventing disease progression, improving prognosis, and reducing mortality in patients received coronary artery bypass grafting (CABG) surgery. In this study, we are trying to evaluate the effectiveness of artificial intelligence (AI) assisted follow-up strategy on secondary prevention for patients received CABG surgery. And we are trying to find out whether there is difference in secondary prevention of coronary heart disease between urban and rural patients.
- Conditions
- Coronary Heart Disease, Artificial Intelligence, Sleep Apnea
- Being tested
- artificial intelligence assisted follow-up
- Keywords
- artificial intelligence
- Medical subject headings
- Coronary Disease, Sleep Apnea Syndromes
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
artificial intelligence assisted follow-upOther
We will use a new portable artificial intelligence assisted device to monitor the patients' postoperative heart rate and sleep quality, guiding the following follow-up process
| Study group | Role | What they receive |
|---|---|---|
| artificial intelligence assisted follow-up group | Experimental | artificial intelligence assisted follow-up group Receives: Other: artificial intelligence assisted follow-up |
| Control group | Placebo comparator | Control group Receives: Other: artificial intelligence assisted follow-up |
What is being measured
The primary outcome is the main question the study is designed to answer.
Heart rate
The average heart rate during the first 35 days postoperatively
Measured: 35 days
Secondary outcomes (8)
Duration of different sleep stages
It includes duration of falling asleep, light sleep, and deep sleep period
Measured: 35 days
Average Pulse oxygen saturation
The average pulse oxygen saturation during the sleep will be evaluated by the sleep monitor device automatically.
Measured: 35 days
Minimum pulse oxygen saturation
The pulse oxygen saturation during the sleep will be recorded by the sleep monitor device and the minimum pulse oxygen saturation will be analyzed.
Measured: 35 days
Pain score
It will be evaluated with the visual analogue scale from 0 to 10. Zero is the lowest level of pain and 10 is the highest level of pain.
Measured: 35 days
Medication compliance
It will be evaluated with Morisky Medication Adherence Scale (MMAS-4). The patients will receive four questions, which are answered by Yes or No ((Yes=0 and No=1) through the scoring system. Zero is the lowest level of medication adherence and 4 is the highest level of medication adherence.
Measured: 35 days
Re-admission rate
It is defined as re-admission between discharge to 35 days after surgery.
Measured: 35 days
All-cause mortality
refers to the incidence of death from the day of surgery to the end of the trial, regardless of the cause.
Measured: 35 days
Total cost of medical expenses
It refers to the total medical expenses for CABG surgery and the following follow-up process.
Measured: 35 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Nov 2020
- Study start1 Jan 2021 (estimated)
- Primary completion30 Sep 2022 (estimated)
- Study completion31 Dec 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (16)Papers the sponsor has linked to this study.
- Other trials for Coronary Heart DiseaseStudies of the same condition, open and under way.
- More trials run by Chinese Academy of Medical Sciences, Fuwai HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Quadruple blind
- Who is masked
- Participant, Care provider, Investigator, Outcomes assessor
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, SHI Jia, Chinese Academy of Medical Sciences, Fuwai Hospital
- Investigators
- Jia Shi, MD, Study chair, National Center for Cardiovascular Disease, China
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04636996
- Sponsor's protocol ID
- CIFuwaiHospital2019-1220
- Status last verified
- Nov 2020
- First submitted
- 26 Oct 2020
- Last updated
- 19 Nov 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Shen C, Ge J. Epidemic of Cardiovascular Disease in China: Current Perspective and Prospects for the Future. Circulation. 2018 Jul 24;138(4):342-344. doi: 10.1161/CIRCULATIONAHA.118.033484. No abstract available.
PubMed 30571361Mega JL, Stitziel NO, Smith JG, Chasman DI, Caulfield M, Devlin JJ, Nordio F, Hyde C, Cannon CP, Sacks F, Poulter N, Sever P, Ridker PM, Braunwald E, Melander O, Kathiresan S, Sabatine MS. Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials. Lancet. 2015 Jun 6;385(9984):2264-2271. doi: 10.1016/S0140-6736(14)61730-X. Epub 2015 Mar 4.
PubMed 25748612Hogh AL. The use of secondary medical prevention after primary vascular reconstruction: studies on usage and effectiveness. Dan Med J. 2012 Sep;59(9):B4514.
PubMed 22951205Kulik A. Secondary prevention after coronary artery bypass graft surgery: a primer. Curr Opin Cardiol. 2016 Nov;31(6):635-643. doi: 10.1097/HCO.0000000000000331.
PubMed 27583372Smith SC Jr, Benjamin EJ, Bonow RO, Braun LT, Creager MA, Franklin BA, Gibbons RJ, Grundy SM, Hiratzka LF, Jones DW, Lloyd-Jones DM, Minissian M, Mosca L, Peterson ED, Sacco RL, Spertus J, Stein JH, Taubert KA; World Heart Federation and the Preventive Cardiovascular Nurses Association. AHA/ACCF Secondary Prevention and Risk Reduction Therapy for Patients with Coronary and other Atherosclerotic Vascular Disease: 2011 update: a guideline from the American Heart Association and American College of Cardiology Foundation. Circulation. 2011 Nov 29;124(22):2458-73. doi: 10.1161/CIR.0b013e318235eb4d. Epub 2011 Nov 3. No abstract available.
PubMed 22052934Dorje T, Zhao G, Scheer A, Tsokey L, Wang J, Chen Y, Tso K, Tan BK, Ge J, Maiorana A. SMARTphone and social media-based Cardiac Rehabilitation and Secondary Prevention (SMART-CR/SP) for patients with coronary heart disease in China: a randomised controlled trial protocol. BMJ Open. 2018 Jun 30;8(6):e021908. doi: 10.1136/bmjopen-2018-021908.
PubMed 29961032Pradeepa R, Rajalakshmi R, Mohan V. Use of Telemedicine Technologies in Diabetes Prevention and Control in Resource-Constrained Settings: Lessons Learned from Emerging Economies. Diabetes Technol Ther. 2019 Jun;21(S2):S29-S216. doi: 10.1089/dia.2019.0038.
PubMed 31169429Hawker GA, Mian S, Kendzerska T, French M. Measures of adult pain: Visual Analog Scale for Pain (VAS Pain), Numeric Rating Scale for Pain (NRS Pain), McGill Pain Questionnaire (MPQ), Short-Form McGill Pain Questionnaire (SF-MPQ), Chronic Pain Grade Scale (CPGS), Short Form-36 Bodily Pain Scale (SF-36 BPS), and Measure of Intermittent and Constant Osteoarthritis Pain (ICOAP). Arthritis Care Res (Hoboken). 2011 Nov;63 Suppl 11:S240-52. doi: 10.1002/acr.20543. No abstract available.
PubMed 22588748Kolloch R, Legler UF, Champion A, Cooper-Dehoff RM, Handberg E, Zhou Q, Pepine CJ. Impact of resting heart rate on outcomes in hypertensive patients with coronary artery disease: findings from the INternational VErapamil-SR/trandolapril STudy (INVEST). Eur Heart J. 2008 May;29(10):1327-34. doi: 10.1093/eurheartj/ehn123. Epub 2008 Mar 29.
PubMed 18375982Wu ZK, Vikman S, Laurikka J, Pehkonen E, Iivainen T, Huikuri HV, Tarkka MR. Nonlinear heart rate variability in CABG patients and the preconditioning effect. Eur J Cardiothorac Surg. 2005 Jul;28(1):109-13. doi: 10.1016/j.ejcts.2005.03.011. Epub 2005 Apr 8.
PubMed 15982594Lakusic N, Mahovic D, Sonicki Z, Slivnjak V, Baborski F. Outcome of patients with normal and decreased heart rate variability after coronary artery bypass grafting surgery. Int J Cardiol. 2013 Jun 20;166(2):516-8. doi: 10.1016/j.ijcard.2012.04.040. Epub 2012 May 5.
PubMed 22560918Cox JL, Bata IR, Gregor RD, Johnstone DE, Wolf HK. Trends in event rate and case fatality of patients hospitalized with myocardial infarction between 1984 and 2001. Can J Physiol Pharmacol. 2006 Jan;84(1):121-7. doi: 10.1139/Y05-141.
PubMed 16845896Lindahl B, Baron T, Erlinge D, Hadziosmanovic N, Nordenskjold A, Gard A, Jernberg T. Medical Therapy for Secondary Prevention and Long-Term Outcome in Patients With Myocardial Infarction With Nonobstructive Coronary Artery Disease. Circulation. 2017 Apr 18;135(16):1481-1489. doi: 10.1161/CIRCULATIONAHA.116.026336. Epub 2017 Feb 8.
PubMed 28179398Roberts DM, Zimmer WE, Watterson DM. The use of synthetic oligodeoxyribonucleotides in the examination of calmodulin gene and protein structure and function. Methods Enzymol. 1987;139:290-303. doi: 10.1016/0076-6879(87)39093-7. No abstract available.
PubMed 3035326McEvoy RD, Antic NA, Heeley E, Luo Y, Ou Q, Zhang X, Mediano O, Chen R, Drager LF, Liu Z, Chen G, Du B, McArdle N, Mukherjee S, Tripathi M, Billot L, Li Q, Lorenzi-Filho G, Barbe F, Redline S, Wang J, Arima H, Neal B, White DP, Grunstein RR, Zhong N, Anderson CS; SAVE Investigators and Coordinators. CPAP for Prevention of Cardiovascular Events in Obstructive Sleep Apnea. N Engl J Med. 2016 Sep 8;375(10):919-31. doi: 10.1056/NEJMoa1606599. Epub 2016 Aug 28.
PubMed 27571048
Study at a glance
From the registry record, last updated by the sponsor on 19 Nov 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effects of Artificial Intelligence Assisted Follow-up Strategy Based on a New Remote Contactless Sleep Monitoring System on Secondary Prevention in Patients Received Coronary Artery Bypass Grafting Surgery
- ClinicalTrials.gov ID
- NCT04636996
- Acronym / sponsor ID
- CIFuwaiHospital2019-1220
- Conditions
- Coronary Heart Disease, Artificial Intelligence, Sleep Apnea
- Keywords
- artificial intelligence
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Chinese Academy of Medical Sciences, Fuwai HospitalUniversity, hospital or other
- Study start
- 1 Jan 2021 (estimated)
- Primary completion
- 30 Sep 2022 (estimated)
- Study completion
- 31 Dec 2022 (estimated)
- First posted
- 19 Nov 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The present study is trying to find out whether artificial intelligence assisted follow-up strategy will improve secondary prevention in CABG patients. In addition, we will test whether rural patients may have more benefits under the new follow-up strategy based on the artificial intelligence device compared with urban patients.
Detailed description
There are a large population of coronary heart disease patients in China, which needs more attention to optimize the secondary prevention and improve the prognosis. Secondary prevention has been showing the effects of improving symptoms, preventing disease progression, improving prognosis, and reducing mortality in patients received coronary artery bypass grafting (CABG) surgery. In this study, we are trying to evaluate the effectiveness of artificial intelligence (AI) assisted follow-up strategy on secondary prevention for patients received CABG surgery. And we are trying to find out whether there is difference in secondary prevention of coronary heart disease between urban and rural patients.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Quadruple blind (participant, care provider, investigator, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| artificial intelligence assisted follow-up group | Experimental | Other: artificial intelligence assisted follow-upartificial intelligence assisted follow-up group |
| Control group | Placebo comparator | Other: artificial intelligence assisted follow-upControl group |
Who may qualify
- Ages
- 18 to 70 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Age between 18-70, male or female
- Received isolated CABG procedure due to coronary artery disease
- Having a smartphone and are willing to cooperate
- Signing written informed consent
Key exclusion criteria (8 listed)
- Patients undergoing CABG + valve replacement surgery
- Postoperative hospital stays more than 10 days (Due to limited postoperative follow-up time and unstable condition such as incision infection, angina, etc.)
- Patients with lung, liver, and kidney failure (Due to organ dysfunction which needs more professional health care and not suitable for this trial)
- Patients with Urinary system diseases (Getting up during sleep, which will interfere with sleep monitoring)
- Patients mentally or legally disabled
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| artificial intelligence assisted follow-upWe will use a new portable artificial intelligence assisted device to monitor the patients' postoperative heart rate and sleep quality, guiding the following follow-up process | Other | Control group, artificial intelligence assisted follow-up group |
Primary outcome
Heart rate
Time frame: 35 days
The average heart rate during the first 35 days postoperatively
8 secondary outcomes
Duration of different sleep stages
Time frame: 35 days
Average Pulse oxygen saturation
Time frame: 35 days
Minimum pulse oxygen saturation
Time frame: 35 days
Pain score
Time frame: 35 days
Medication compliance
Time frame: 35 days
Re-admission rate
Time frame: 35 days
All-cause mortality
Time frame: 35 days
Total cost of medical expenses
Time frame: 35 days
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Nov 2020.
- Results publication: PubMed 30571361Shen C, Ge J. Epidemic of Cardiovascular Disease in China: Current Perspective and Prospects for the Future. Circulation. 2018 Jul 24;138(4):342-344. doi: 10.1161/CIRCULATIONAHA.118.033484. No abstract available.
- Results publication: PubMed 25748612Mega JL, Stitziel NO, Smith JG, Chasman DI, Caulfield M, Devlin JJ, Nordio F, Hyde C, Cannon CP, Sacks F, Poulter N, Sever P, Ridker PM, Braunwald E, Melander O, Kathiresan S, Sabatine MS. Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials. Lancet. 2015 Jun 6;385(9984):2264-2271. doi: 10.1016/S0140-6736(14)61730-X. Epub 2015 Mar 4.
- Results publication: PubMed 22951205Hogh AL. The use of secondary medical prevention after primary vascular reconstruction: studies on usage and effectiveness. Dan Med J. 2012 Sep;59(9):B4514.
- Results publication: PubMed 27583372Kulik A. Secondary prevention after coronary artery bypass graft surgery: a primer. Curr Opin Cardiol. 2016 Nov;31(6):635-643. doi: 10.1097/HCO.0000000000000331.
- Results publication: PubMed 22052934Smith SC Jr, Benjamin EJ, Bonow RO, Braun LT, Creager MA, Franklin BA, Gibbons RJ, Grundy SM, Hiratzka LF, Jones DW, Lloyd-Jones DM, Minissian M, Mosca L, Peterson ED, Sacco RL, Spertus J, Stein JH, Taubert KA; World Heart Federation and the Preventive Cardiovascular Nurses Association. AHA/ACCF Secondary Prevention and Risk Reduction Therapy for Patients with Coronary and other Atherosclerotic Vascular Disease: 2011 update: a guideline from the American Heart Association and American College of Cardiology Foundation. Circulation. 2011 Nov 29;124(22):2458-73. doi: 10.1161/CIR.0b013e318235eb4d. Epub 2011 Nov 3. No abstract available.
- Results publication: PubMed 29961032Dorje T, Zhao G, Scheer A, Tsokey L, Wang J, Chen Y, Tso K, Tan BK, Ge J, Maiorana A. SMARTphone and social media-based Cardiac Rehabilitation and Secondary Prevention (SMART-CR/SP) for patients with coronary heart disease in China: a randomised controlled trial protocol. BMJ Open. 2018 Jun 30;8(6):e021908. doi: 10.1136/bmjopen-2018-021908.
- Results publication: PubMed 31169429Pradeepa R, Rajalakshmi R, Mohan V. Use of Telemedicine Technologies in Diabetes Prevention and Control in Resource-Constrained Settings: Lessons Learned from Emerging Economies. Diabetes Technol Ther. 2019 Jun;21(S2):S29-S216. doi: 10.1089/dia.2019.0038.
- Results publication: PubMed 22588748Hawker GA, Mian S, Kendzerska T, French M. Measures of adult pain: Visual Analog Scale for Pain (VAS Pain), Numeric Rating Scale for Pain (NRS Pain), McGill Pain Questionnaire (MPQ), Short-Form McGill Pain Questionnaire (SF-MPQ), Chronic Pain Grade Scale (CPGS), Short Form-36 Bodily Pain Scale (SF-36 BPS), and Measure of Intermittent and Constant Osteoarthritis Pain (ICOAP). Arthritis Care Res (Hoboken). 2011 Nov;63 Suppl 11:S240-52. doi: 10.1002/acr.20543. No abstract available.
- Results publication: PubMed 18375982Kolloch R, Legler UF, Champion A, Cooper-Dehoff RM, Handberg E, Zhou Q, Pepine CJ. Impact of resting heart rate on outcomes in hypertensive patients with coronary artery disease: findings from the INternational VErapamil-SR/trandolapril STudy (INVEST). Eur Heart J. 2008 May;29(10):1327-34. doi: 10.1093/eurheartj/ehn123. Epub 2008 Mar 29.
- Results publication: PubMed 15982594Wu ZK, Vikman S, Laurikka J, Pehkonen E, Iivainen T, Huikuri HV, Tarkka MR. Nonlinear heart rate variability in CABG patients and the preconditioning effect. Eur J Cardiothorac Surg. 2005 Jul;28(1):109-13. doi: 10.1016/j.ejcts.2005.03.011. Epub 2005 Apr 8.
- Results publication: PubMed 22560918Lakusic N, Mahovic D, Sonicki Z, Slivnjak V, Baborski F. Outcome of patients with normal and decreased heart rate variability after coronary artery bypass grafting surgery. Int J Cardiol. 2013 Jun 20;166(2):516-8. doi: 10.1016/j.ijcard.2012.04.040. Epub 2012 May 5.
- Results publication: PubMed 16845896Cox JL, Bata IR, Gregor RD, Johnstone DE, Wolf HK. Trends in event rate and case fatality of patients hospitalized with myocardial infarction between 1984 and 2001. Can J Physiol Pharmacol. 2006 Jan;84(1):121-7. doi: 10.1139/Y05-141.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Jia Shi, MD study chair
National Center for Cardiovascular Disease, China
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing artificial intelligence assisted follow-up in people with Coronary Heart Disease and Artificial Intelligence, run by Chinese Academy of Medical Sciences, Fuwai Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 19 Nov 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. Some participants in this study may receive a placebo. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Jia Shi, MD (86-10-88322467, shiandypumc@sina.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Heart rate (time frame: 35 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04636996, which also lists 16 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Nov 2020.