Pain represents a major clinical, social and economic problem1 so it is no surprise that treating pain is at the epicentre of medicine and structures the aim of healthcare professionals. Pain affects hundreds of millions of people and, in Europe, national healthcare and socioeconomic costs of conditions associated with chronic pain run into billions annually and represents 3–10% of gross domestic product2. Currently there are no validated objective markers of nociception or pain that can be recommended for clinical use3 so treatment relies on patients’ subjective assessment and clinician interpretation, a particular issue when the patient cannot communicate (e.g. those who are anaesthetised). Postsurgical complications related to inadequate pain management negatively affect the patient’s welfare and the hospital performance because of extended lengths of stay and readmissions, both of which increase the cost of care4. Medasense’s vision is to optimise pain management through accurate and objective assessment of pain at hospitals, clinics and at home.
Medasense have developed a novel, multi-parametric, patented technology to objectively assess nociception (pain), quantify it and measure the analgesic effect. Due to the multifaceted nature of pain, Medasense’s solution focuses on the body’s physiological integrated response to pain, rather than individual pain pathways. The device consists of a non-invasive finger probe which continuously records multiple pain related physiological signals – using four sensors namely a photoplethysmograph, galvanic skin response, temperature and accelerometer. From the signals- dozen of pain related physiological parameters and derivatives are extracted and computed (heart rate, heart rate variability, skin conductance level, photoplethysmography pulse wave amplitude, a number of skin conduction fluctuations, skin temperature and more). The PMD200 bedside monitor uses composite artificial intelligence algorithms to analyze dozens of pain-related measurable changes in the physiological parameters and determine the individual’s nociception level index (NOL™). This NOL™ is visualized on the PMD200™ monitor using a scale of 0 to 100, where 0 represents no pain and 100, extreme pain. The device is calibrated to the individual’s baseline and provides continuous, real time monitoring.
NOL™ helps healthcare professionals monitor pain intensity and titrate analgesic medication accordingly during anaesthesia5,6 with the aim to reduce suffering and minimise adverse events which can be caused by over or under usage of analgesic medications.
Over an 8 year research period, 8 studies were conducted in Canada, Europe, Israel and the USA involving more than 500 patients. These patients were a combination of conscious, anaesthetised and those suffering from acute and chronic pain5-8 and included trials performed on patients undergoing surgery. Key results published and cited in peer reviewed medical journals (Pain, Anesthesiology, The Journal of Clinical Monitoring and Computing) have demonstrated the NOL™ index outperforms currently used parameters and methods.
Results show the technology is able to discriminate between noxious and non-noxious stimuli with high intensity and specificity, and grade the different levels5,6.
Following the CE approval of the PMD200™ the first stage of rollout will be aimed at institutions which treat anesthetised surgical patients, namely ORs, with further expansion anticipated once other regulatory approvals are received. Expansion of the market by collaborating with leading patient monitoring companies and possibly anaesthesia and infusion equipment suppliers, pharmaceutical companies, research institutes and wearable providers is a possibility. With nearly 234.2 million major surgical procedures worldwide each year9, the market potential for this device is enormous.
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- Phillips C. (2009) The Cost and Burden of Chronic Pain. Rev Pain, 3:2–5.
- Breivik H et al., (2013) The individual and societal burden of chronic pain in Europe: the case for strategic prioritisation and action to improve knowledge and availability of appropriate care. BMC Public Health, 13:1229
- Cowen R et al., (2015) Assessing pain objectively: the use of physiological markers. Anaesthesia, 70:828-847
- Wells N et al., (2008) Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Rockville (MD): Agency for Healthcare Research and Quality (US)
- Edry R et al., (2016) Preliminary Intraoperative Validation of the Nociception Level Index: A Noninvasive Nociception Monitor. Anesthesiology, 125:193-203
- Martini et al., (2015) Ability of the Nociception Level (NOL), a multiparameter composite of autonomic signals, to detect noxious stimuli during propofol-remifentanil anesthesia. Anesthesiology. 123:524-534
- Ben-Israel N et al., (2013) Monitoring the Nociception Level – A Multi-Parameter Approach. Journal of Clinical Monitoring and Computing, 27:659
- Roi T et al., (2012) Differentiating between heat pain intensities: the combined effect of multiple autonomic parameters. Pain. 153:1807-1814
- Weiser T et al., (2008) An estimation of the global volume of surgery: a modelling strategy based on available data. The Lancet, 372, 9633:139–144