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Friday, 23 Sep, 2022
Duke-NUS grants TIIM Healthcare exclusive licence to commercialise technology for intelligently triaging sepsis patients using novel in hospital mortality risk measurements
- Novel technology invented by clinician-scientists at Duke-NUS Medical School combines traditional and new measurements to predict in-hospital mortality among patients presenting with sepsis at emergency departments.
- TIIM Healthcare will exclusively commercialise the technology with the goal of augmenting clinicians’ accuracy and analytical powers when triaging septic patients, enabling prioritisation of limited hospital resources and delivering timely interventions for the prevention and treatment of complications.
SINGAPORE, 23 September 2022 – Duke-NUS Medical School and TIIM Healthcare have signed an exclusive IP licensing agreement that will enable the latter to commercialise an innovative new technology designed to help hospital emergency care providers quickly and efficiently identify sepsis patients at higher risk of dying.
The new technology—developed by Professor Marcus Ong, Director of the Health Services & Systems Research (HSSR) Programme at Duke-NUS Medical School; Associate Professor Liu Nan, also from the HSSR Programme; and their colleagues from Duke-NUS Medical School—uses selected heart rate variability measurements, specifically HRV and HRnV1, to assess the severity of sepsis in patients presenting with the condition in hospital emergency departments.
The team has piloted a novel scoring system incorporating HRV, HRnV, vital signs and quick sequential organ failure assessment (qSOFA) to predict in-hospital mortality (IHM) among sepsis patients over a 30-day stay on the emergency ward. The technology does not require laboratory-analysed blood tests and the risk assessment results can be generated within 10 minutes, which means it can be used for continuous monitoring of IHM risk among warded sepsis patients.
Sepsis, a potentially life-threatening condition caused by the body’s dysregulated response to infection affects more than 50 million people annually, resulting in more than five million deaths worldwide in both adult and paediatric populations.
Early goal-directed therapy initiated within the first six hours of sepsis diagnosis has been shown to significantly decrease IHM rates, which are estimated to be 14 per cent in emergency wards and 30 to 50 per cent, overall. Identifying patients who have a higher mortality risk from sepsis enables limited hospital resources to be prioritised for this group and timely interventions for the prevention and treatment of complications.
“Early risk stratification in septic patients using a quick and efficient triage tool would have great value in the emergency department.”
Prof Marcus Ong, Director, HSSR Programme, Duke-NUS Medical School, and Senior Consultant, Department of Emergency Medicine, Singapore General Hospital (senior author of the study)
“HRnV is a novel representation of beat-to-beat variation that can provide multiple sets of parameters from the same electrocardiogram (ECG) record. HRnV significantly increases the amount of extracted information to be used as the predictors to enhance machine learning model performance.”
Assoc Prof Liu Nan, HSSR Programme, Duke-NUS Medical School (first author of the study)
“Our mission at TIIM Healthcare is to make health care more efficient with intelligent risk stratification for triage. When integrated with our platform, this new technology has the potential to augment clinicians’ accuracy and analytical powers to triage septic patients more effectively. This is something we are very excited about.”
Mr Cheng Keng Liang, co-founder and CEO, TIIM Healthcare
“With our constant focus on technological innovation to transform health care with intelligent risk stratification, this new technology is a perfect fit to be integrated with our platform, marking a new technological milestone for us.”
Dr Guo Dagang, co-founder and CTO, TIIM Healthcare
“We are very delighted to complete the licence agreement with TIIM. CTeD works closely with our scientists and industry partners to facilitate bench-to-bedside translation. HRnV technology is yet another invention successfully transferred from Duke-NUS to industry partners for commercialisation, bringing artificial intelligence-enabled disease prediction and risk stratification solutions to triage patients and to more efficiently manage visits to the hospital.”
Dr David Wang, Director, Centre for Technology and Development (CTeD), Duke-NUS Medical School
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1 novel heart rate n-variability parameters invented by the team to provide enhanced prognostic information to complement traditional HRV parameters