Preventive and predictive healthcare Integration of Technologies

In India, the primary goal of PPH will be, to develop tools for early diagnosis of the risks and initiate appropriate preventive strategies, says Gundu H R Rao

201509ehm19

In India, the primary goal of PPH will be, to develop tools for early diagnosis of the risks and initiate appropriate preventive strategies, says Gundu H R Rao

201509ehm20
Gundu H R Rao

South Asians (Indians, Bangladeshis, Pakistanis and Sri Lankans) have a very high incidence of cardiometabolic diseases, such as hypertension, metabolic syndrome, abdominal obesity, Type-II diabetes, ischemic heart disease and stroke.

Preventive and Predictive Healthcare (PPH) uses state-of-the-art diagnostic tools, to identify the patients who may be at high risk for hospitalisation or developing acute events, leading to morbidity and mortality. Once identified, the system will proactively contact the patients, to initiate positive behavioural changes, to improve better management of their health. By integrating predictive modelling with early diagnosis of the risks, behavioural changes, life style management, medical management, pharma management and personalised empowerment services, PPH provides a unique healthcare service platform. Ayurveda scholars have been debating and using this logic for centuries. Tri-dosha classification of Prakriti has been used by the Vaidyas, to determine the state of health and predisposition of individuals to various metabolic diseases. According to this theory, each individual has a certain ratio of Vata, Pitta and Kapha (the three doshas) that is unique to him or her. Sharma and Chandola (2010) conclude in their article, that the complex set of disorders identified as Prameha in Ayurveda, correlates in many ways with obesity, metabolic syndrome, and diabetes. Neither the Emory University (USA) Predictive Health Initiatives nor the Ayurvedic studies on Prakriti, have developed significant clinical evidence, to support their concept and as such, cannot be effectively used for risk profiling, risk prediction, management of observed risks and disease prevention. Having said that, can we give this ancient science a critical validation at least? Of course we can design appropriate population-based studies, to test this system of classification of metabolic risks and diseases.

A large randomised study can be initiated to test the dosha system of classification of the health status. Various cardio metabolic diseases such as pre-hypertension, hypertension, visceral obesity, metabolic syndrome, pre-diabetes, type-II diabetes, ischemic heart diseases and stroke are, after all manifestation of alteration in the metabolic functions. For the sake of simplicity, we can administer Internet-based Deepak Chopra’s Dosha quiz (www.doshaquiz.chopra.com) to 10,000 individuals of ages between 30 to 60 and further evaluate this selected cohort, with another of Deepak Chopra’s survey or some other standardised test (www.doshaquiz.chopra.com/dosha_part2.asp) or an independent test developed by the experts in this field and further classify this population into the basic 3-doshas (Vata, Pitta, Kapha) or into six or nine subtle variants of the doshas. Then we can investigate these selected cohorts, with a second set of interviews, and identify the type of diseases which are prevalent or the observed risk factors they have for various metabolic diseases, and generate clusters of “at risk” individuals or diseases. We can further evaluate this population for altered activity of metabolic enzymes.

In a country like India, with an epidemic of cardio-metabolic disorders, the primary goal of PPH will be, to develop tools for early diagnosis of the risks and initiate appropriate preventive strategies. Currently, India has 65 million type-II diabetics and an equal number of pre-diabetics. In addition, there is co-occurrence or co-morbidity of other cardio metabolic risks such as hypertension, visceral obesity, metabolic syndrome, ischemic heart disease and stroke. All of these risks are, in some way or the other interrelated and plays a critical role in the development of acute vascular events. If we just look at type-II diabetes as an example, then from the management perspective, we will have to start with early diagnosis of the risks for hyperglycemia, as well as alterations in blood vessel-wall pathology. One of the gold standards to monitor hyperglycemia would be to monitor post-prandial glucose (PPG) levels, two hours (2HPPG) after a meal. This risk assessment will get a great boost, if we develop a non-invasive glucose monitoring (NIGM) system, as there will be little resistance for risk assessment using this novel technology. Similarly, early detection of altered vessel-wall pathology will provide us great opportunity to initiate behavioural changes and integrate holistic preventive management strategies.

Vascular physiology and pathology are modulated to a great extent by the endogenously produced vasoactive molecules. Endothelial cells lining the vessels produce a variety of vasodilators and circulating blood components produce vasoconstrictors. Alterations in the production of these vasoactive molecules will result in changes in the vascular compliance and initiate a condition called, endothelial dysfunction (ED). This is the earliest vascular pathology that we can detect currently, for risk assessment. There are many tools available for assessment of this condition. Examples include, Periscope (Genesis Medical System, Hyderabad), CV Profilor (HDI Diagnostica, Minneapolis, MN) and TM-Oxi system (LD Technologies, Miami, Florida). The software generates impressive diagnostic reports with some recommendations. Risk factors chart includes; marker for Autonomic Nervous System (ANS) activity, ANS balance, fat mass, markers of lipidemia, markers of endocrine disorder, insulin resistance, insulin production, microcirculation; C-fiber density, sympathetic failure score, parasympathetic failure score, blood pressure control score, cardiac performance score, and endothelial function score. The developers of the original non-invasive diagnostic system (LD-Technologies) claim, that the system detects 14 cardio-metabolic risk markers. Some major questions that arise in the mind when you hear, such claims is, how can a simple device, with three well-tested components such as pulse-oximeter, blood pressure monitor and galvanic skin response monitor, provide information on 14 vital cardiometabolic health indicators. As we have already discussed in this article, power of prediction mainly comes from analytic validity, clinical validity and finally clinical utility.

The point of concern when considering the power of prediction will be, the selection of parameters that provide the most accurate and reliable risk prediction. We also have to consider, whether we are discussing prediction of a risk for disease, for an interventional procedure, for hospitalisation or for acute events. Therefore, risk prediction tools have to be developed keeping these various stages of the risk and disease management strategy in mind, and come up with appropriate assessment tools. In view of the fact, that there is a tremendous activity in the development of risk and disease management applications, it should seriously consider the best use of the smart phone, tablets, big data and cloud computing, for enhancing our diagnostic and predictive capabilities. We should also consider what are the best diagnostic parameters needed for use in a risk assessment tool to get optimal results. With the rapid advance in the development of medical devices, data collection, computing, big data storage and analytics, genetic risk assessment, and the availability of a variety of non-invasive diagnostic technologies, now it is possible, to use multiple technologies, utilise the collective strengths and build a comprehensive risk assessment and risk prediction platform.

To create awareness, develop educational and preventive programmes, I started a professional society, SASAT (www.sasat.org) at Minnesota, USA, in 1993. We have organised over 15 international conferences on this subject in India, under the aegis of SASAT and published several books related to this topic. During the SASAT-2006 conference in Bangalore, we organised a round-table conference to discuss how we can develop a seamless platform for developing affordable healthcare for all. Experts who met at this conference suggested that we should bring in practitioners of traditional Indian medicine also on to this platform.

The purpose of this essay was to articulate the possibilities, create awareness about the priorities, describe current status, stress on challenges, and opportunities, initiate robust discussions related to the immediate need for the creation of a “National Platform” for addressing the prevention and management of cardiometabolic diseases. When it comes to preventive healthcare, the modern medicine has failed to develop robust preventive strategies for the prevention of cardiometabolic diseases. Whereas, the ancient art of healing, Ayurveda has been promoting holistic approach for a healthy disease-free life. Modern medicine on the other hand, has been advocating early detection of symptoms or risks for various disorders and better management of the risks for prevention of acute events from occurring.

We are of the opinion, that integrative approach to healthcare, taking the best of the ancient medicine and the best of the modern medicine would be ideal for a country like India. We should also take advantage of the rapid progress in emerging technologies, like biotechnology, bioengineering, biomedical sciences and information technology, to develop a seamless integration of these technologies, for developing an easily accessible, widely acceptable and relatively affordable healthcare.

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