Diagnosis Archives - InnoHEALTH magazine

Good’s Syndrome, a lesser known Immunodeficiency disorder

Khushi Khandelwal — Tue, 27 May 2025 10:30:00 +0000

Dr. Eshika Dubey

This whole-body FDG-PET scan of a patient reveals diffuse, moderately increased FDG uptake in a well-defined, heterogeneously hypo-enhancing mass with lobulated borders located in the right prevascular region. The mass measures approximately 3 x 5.5 x 7 cm, with slight bulging along the right mediastinal border, suggesting a possible thymic neoplasm. Additionally, there is evidence of high-grade FDG uptake in enlarged, mildly enhancing lymph nodes in the left lower paratracheal (largest node measuring 18 x 14 mm), right tracheobronchial, subcarinal, and left hilar regions, raising the suspicion of a granulomatous etiology in the context of known CVID. The presence of increased metabolic activity in the para-sinus areas also indicates ongoing inflammatory processes.

Differential Diagnosis:

Thymoma
Thymoma-associated hypogammaglobulinemia (Good’s Syndrome)
Neurogenic tumors
Benign cysts
Lymphadenopathy (LAD)
Lymphomas
Thyroid masses

Why might this be Good’s Syndrome, and how is it diagnosed?

Good’s syndrome is a rare adult-onset immunodeficiency disorder characterized by the triad of thymoma, hypogammaglobulinemia, and increased susceptibility to recurrent infections. It typically presents in individuals during their 4th or 5th decade of life, with the average age of diagnosis around 62–65 years. Patients often present with an asymptomatic anterior mediastinal mass, although symptoms such as cough, chest pain, dysphagia, dyspnea, and hoarseness may develop due to thymoma. Additionally, Good’s syndrome can be associated with superior vena cava syndrome, Horner’s syndrome, and neck masses.

Diagnosis is frequently made during investigations for conditions like Myasthenia Gravis, with which Good’s syndrome has a significant association. Immunological findings in Good’s syndrome include hypogammaglobulinemia, a decreased or absent B cell count, abnormal CD4+:CD8+ T cell ratios, CD4+ T cell lymphopenia, and impaired T cell responses, along with reductions in serum IgG, IgA, and IgM levels. The disease shares features with X-linked agammaglobulinemia (XLA) and common variable immunodeficiency (CVID).

Patients with Good’s syndrome may experience recurrent bacterial infections (e.g., urinary tract, skin infections), as well as opportunistic infections, such as cytomegalovirus (CMV) colitis, retinitis, and mucocutaneous candidiasis. It is important to suspect Good’s syndrome in individuals over 40 years of age who have a suspected or confirmed antibody deficiency, especially when they present with such infections and reduced mature B cell counts. This suspicion is further heightened in patients with presumed CVID attending immunology clinics. One of the first diagnostic steps in such cases is to measure serum immunoglobulins. A reduction in immunoglobulins, along with a history of sinopulmonary or opportunistic infections, is crucial in diagnosing Good’s syndrome.

Treatment

The primary treatment for thymoma is surgical removal or debulking of the tumor. For patients with stage 3 or 4 thymomas, radiotherapy and/or combination chemotherapy may be necessary. Immunoglobulin replacement therapy is required to address the antibody deficiency. If the patient has a CMV-negative or unknown CMV serology, CMV-negative blood products should be administered to avoid the risk of iatrogenic CMV infection.

Author’s Biography

Dr. Eshika Dubey, an MBBS doctor currently working in Paediatrics at HBT Cooper Municipal Hospital. She has experience in Nuclear Medicine from HN Reliance Hospital and aspires to specialize in Radiology or Dermatology in the UK. She is a graduate of MGM Medical College and is interested in unique cases, research and writing.

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The application of machine learning for the clinical identification of neurodegenerative disorders: Decoding degeneration

InnoHEALTH magazine digital team — Mon, 05 Feb 2024 05:11:00 +0000

Neural networks and deep learning have been employed in a range of translational research fields, such as image analysis, structural analysis, and sequence binding.

Affecting 15% of the global population, neurological illnesses are the most common cause of impairment, both mental and physical. Over the next 20 years, it is anticipated that the burden of chronic neurological ailments will only double due to the world’s ageing population. In light of this, maintaining universal access to neurological therapy will be very challenging. Alzheimer’s disease and Parkinson’s disease are the two neurodegenerative diseases that most frequently impact the elderly population.

One of the industries using wearable sensors, augmented and virtual reality, medical imaging, artificial intelligence, and other technologies most actively is the healthcare sector. Artificial intelligence is a fast-expanding field of research that tries to automate human intellect and recreate cognitive capacities using various approaches. It is becoming more and more relevant given the massive amount of huge data that is currently available.

A branch of artificial intelligence known as machine learning uses algorithms to identify patterns and extract significant features from massive datasets. Machine learning (ML) algorithms can be used to identify and forecast future outcomes once these patterns have been found and learned. In the medical field, machine learning can be used to data from several sources to help with tracking, diagnosis, and diagnostic-related tasks. ML systems, for example, can collect symptoms, register a patient’s response to treatment, and diagnose the severity of a disease in real-time remotely.

Like other medical specialties, neurology has benefited greatly from the integration of machine learning, particularly in the area of computer-aided detection, tracking, and treatment of symptoms related to neurodegenerative movement disorders.

Wearable technology and machine learning algorithms have been utilised to solve some of the difficulties related to neurological illness. ML has been used, for example, to follow and manage the progression of Parkinson Disease and to distinguish it from other conditions that appear similarly. The enhanced accuracy, dependability, accessibility, and efficiency of ML-integrated systems in clinical decision-making make them extremely promising for use in clinical practice. Moreover, ML has been applied to Alzheimer’s disease to monitor the illness’s course and serve as a source for differential diagnosis.

Instead of requiring manual interpretation by medical professionals, machine learning algorithms use computer-aided diagnosis to automatically identify and forecast the course of disease. This helps in clinical decision-making. A variety of methods are used to train machine learning models, such as ensemble model building, fresh model development, and transfer learning with pre-trained weights.

Machine Learning Contributions to The Computer-Aided Diagnosis of Neurodegenerative Diseases

Parkinson’s and Alzheimer’s disease (AD) account for most cases of neurodegeneration. There are actual diseases like Parkinson’s disease (PD), motor neurone disease, Huntington’s disease, and many more; however, this article will focus on the two most prevalent ones, AD and PD. Deep learning is a new soft computing approach in machine learning that makes use of layered mathematical structures called neural networks. A hybrid model is a DL architecture that is combined with a more traditional ML architecture, such as a support vector machine (SVM) for classification. Neural networks and deep learning have been employed in a range of translational research fields, such as image analysis, structural analysis, and sequence binding. Because the higher-level characteristics of Deep Learning algorithms are more noise-resistant, they produce better outcomes.

Information is sent unidirectionally via hidden layers in an artificial neural network (ANN) from the input layer to the output layer. An extension of an artificial neural network (ANN) with several hidden layers is a deep neural network (DNN). Increasing the number of layers facilitates the learning and representation of intricate data patterns. Convolutional Neural Networks (CNNs) are specifically engineered for the processing of images and videos. Convolutional layers are used to automatically identify and extract feature spatial hierarchies from pictures. These look for local patterns, edges, and textures in the input image.

Convolutional neural networks (CNNs) and deep learning are tools that are used to find illness biomarkers and detect tiny brain changes, which allows for the early identification of disease.

Dysfunctions in working memory, planning, rule-finding, and set-shifting are collectively referred to as cognitive inertia. These deficits lead to indifferent conduct. Neurodegenerative illnesses of the Lewy body and Alzheimer’s disease are the main causes of cognitive loss.

A battery of computerised tests that measure cognitive stability indices focusing on the memory, attention, and response time domains has been developed in order to aid in the early detection of cognitive decline. Furthermore, by analysing the kinematic patterns of the head and hand during real-life tasks, the combination of virtual reality (VR) and artificial intelligence (AI) facilitated the continuous assessment of instrumental activities of daily life and led to the identification of behavioural measures capable of predicting nonverbal dysphoria (NDD).

Deep neural network speech analysis was successful in classifying AD patients into binary categories. Natural language processing (NLP) was used to extract rhythmic, acoustic, lexical, morpho-syntactic, and syntactic features from spontaneous speech transcriptions. This allowed for the early, multi-domain MCI to be distinguished from healthy controls, demonstrating both the method’s sensitivity to the progression of the disease and its ability to classify subtypes.

A comprehensive deep learning model was created, utilising a vision-based transformer, bidirectional encoder representation transformer, co-attention, multimodal shifting gate, and self-attention mechanism to understand the interplay between textual and spoken information.

Machine Learning Model (MLM)

Machine learning relies on the assumption that computer systems can learn from data. This method is intended to give software the capacity to learn from the collected data. For the “Therapeutic Robot and Artificial Intelligence in experimental Therapy” project, machine learning proved to be the most appropriate technique for making predictions on patients suffering from motor cognitive impairment. The purpose is to ascertain the degree of cognitive impairment in the patient and, in light of their individual objectives, provide the best rehabilitation strategy. A machine learning-based predictive statistical model was utilised to determine whether the patient’s cognitive impairment was present or absent.

This neurodegenerative disorder is gaining more attention, maybe because there are no effective pharmaceutical therapies to halt the disease’s progression. Numerous research has backed the use of MLM based on neuroimaging biomarkers to better understand the aetiology of neurodegenerative illnesses and to aid in the differential diagnosis of AD. AI-driven algorithms are used to examine brain imaging data in medical image processing. Convolutional neural networks (CNNs) and deep learning are tools that are used to find illness biomarkers and detect tiny brain changes, which allows for the early identification of disease.

Furthermore, disease progression analysis and clinical outcome forecasting are conducted using AI’s predictive analytics capabilities. Through patient data analysis, AI models may detect patterns of sickness, calculate the rate of functional decline, and help physicians make informed decisions regarding therapy and care planning.

Algorithms can look at a range of data sources, such as genetic information, neuroimaging scans, and clinical assessments, to identify early signs and patterns suggestive of neurodegenerative disorders. Through early identification and an understanding of the minute changes that take place in the initial stages of the disease, numerical simulations aid in the development of computer models that depict the trajectory of the disease.

It will take some time before we can fully reap the benefits of artificial intelligence in the healthcare sector, as the technology is still in its infancy. Ahead of us lies a substantial amount of work, chief among which is the validation and optimisation of the existing models to produce more robust and long-lasting models.

“Composed by: ANUSHKA SAXENA a highly accomplished healthcare professional with background in physiotherapy, & now pursuing my Master’s degree in Hospital & healthcare management from Sharda University. Experienced in most widely used computer software, databases, healthcare terminologies, documents processing. Overall, a positive individual with a genuine interest in the well-being of patients & team mates with expertise in hygiene education.”

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Telemedicine Force Multiplier for Healthcare Delivery

InnoHEALTH Magazine — Mon, 13 Jan 2020 06:13:54 +0000

In any developing country, there is huge inequality in healthcare distribution due to various reasons such as poor infrastructure, poor communication, inadequate transport facilities, etc. Doctors find it difficult to stay in rural centers due to the above reasons.
It is also well known that 65% to 75% of the population resides in villages that are scattered and not well connected by roads. Hence, the rural population has to travel nearly 8-10 kilometers to access basic healthcare in nearby towns. They spend most of their out of pocket health expenses and at many times borrow money for these expenses.
Keeping this in the background, governments have been working on Sustainable Development Goals launched by the United Nations. Aim of these goals is to ensure healthy lives and promote well-being at all ages. Sustainable health is a huge challenge and it can only be achieved by adopting technology and innovations to improve healthcare delivery.
India now has a robust information technology manpower and the established communication technology is freely available at the village level, mobile phone applications in healthcare and wellness are being used in the rural bridge. Telemedicine is the combination of its communication network and healthcare promises to reach the rural-urban divide and it is also the cheapest and fastest way to reach the unreached population.

Government Initiatives in Telemedicine
Numerous telemedicine projects are now running in the country under the aegis of the National Health Mission. Rajasthan government has initiated a PPP model telemedicine project on BOOT (build own operate & transfer) concept. The Global Health System Kolkata is the vendor who has been operating the Telemedicine project for the past 3 years. Mahatma Gandhi Medical College and Hospital Sitapura Jaipur have signed MOU with the vendor for rendering telemedicine consultations to the periphery (100/ 150 nodes).
Mahatma Gandhi University of Medical Sciences & Technology (MGUMST) Experience
The experiences gained by providing healthcare through telemedicine is very interesting, it may be noted that the telemedicine consultations have grown with each passing year. It was interesting to note that the teledermatology was increasing on analysis, it was realized that dermatology revolves around photography and visible rules to make a diagnosis.
The numerous efforts made over the years can be analyzed based on the number of consultations: while dermatologists data showed 4011 consultations in 2017, it grew to 31436 in 2019. On the other hand, general medicine was ranging from 4759 consultations in 2017 and dropped down to 2889 consultations in 2019. Cardiologists/CVS/cardiac surgeon consultations were 324 in 2017 and dropped down to 238 in 2019. Obstetrician/gynecologist showed an increase from 854 consultations in 2017 to 1135 in 2019. Oncologist consultations were 33 in 2017 and dropped to 29 in 2019 while orthopedic was at 525 in 2017 and increased to 747
in 2019. Pediatrician/neonatologist was at 6260 in 2017 and drastically reduced to 585 in 2019. Overall consultations during the years 2017-2019 were 105,269.
Conclusion
Telemedicine is the future healthcare system as it reaches the unreached and it allows the remote health workers to avail consultation with territory care specialists in urban areas. The growing number seeking teleconsultations from the peripheral medical setup is proof that telemedicine delivery of healthcare is now being adopted by the rural population.

About the author

Major General Ashok Kumar Singh (retd) from the Indian Army has served all over India – Lucknow, Assam, Mizoram, Nagaland, Agartala, Delhi, Pune, Srinagar, Udhampur and many other places and been on official duties and attended conferences in Austria, Bhutan, Canada, and Sweden. His area of interest is rural health through telemedicine. He is currently serving as an Advisor in Health Informatics at Mahatma Gandhi University of Medical Sciences and Technology at Sitapura, Jaipur. He is also running a BSc course in Hospital and Health Information Administration.

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Innovative Biomarkers for Early Diagnosis and Treatment of Life

InnoHEALTH Magazine — Thu, 17 Oct 2019 09:37:15 +0000

From the inception of medical science, there is heavy reliance on research to find ways to detect and combat dreadful medical conditions. While the many of the diseases known are curable thanks to the advances in technology and innovations in research, there are still some that call for more attention and a more precise treatment plan.
One such medical condition is Sepsis – a life-threatening disease affecting more than 30 million people globally every year. Sepsis is a medical condition when the body’s response to a present infection damages its own tissues and organs resulting in death or serious illness. If not treated at the initial stages sepsis can trigger low blood pressure resulting in organ malfunction or even worse, a condition called septic shock.
Antibiotic treatment of sepsis patients often relies on clinical observation and educated guesswork as clinicians wait for a culture to determine whether the infection is bacterial, viral, or possibly fungal. But with the U.S. Food and Drug Administration’s (FDA) recent approval of automated platforms for procalcitonin assays and mounting evidence of PCT’s value as a biomarker, hospital laboratories are turning to PCT to diagnose sepsis and guide antimicrobial stewardship.
The world has acknowledged sepsis as a life-threatening condition and a challenge for the medical industry to combat. The Global Sepsis Alliance is an organisation working at the forefront to increase awareness about the disease and globally.
Over the past six years, Thermo Fisher has worked with the Global Sepsis Alliance and other advocates to raise awareness of the signs and symptoms of sepsis.
Thermo Fisher Scientific- a world leader in serving science is committed to providing exceptional laboratory tools to assess the risk of bacterial infection relating to sepsis with the B·R·A·H·M·S PCT (Procalcitonin) biomarker assay. The B∙R∙A∙H∙M∙S PCT assay provides information on the presence and severity of bacterial infection, helping physicians in emergency departments, intensive care units and other critical care units decide whether to initiate antibiotic therapy in patients and when to safely discontinue antibiotics in patients with lower respiratory tract infections (LRTI) and sepsis, without compromising patient safety.
B·R·A·H·M·S PCT (Procalcitonin) supports responsible use of antibiotics
The overuse of antibiotics is a global problem but the B·R·A·H·M·S Procalcitonin assay can help guide the judicious use of antibiotics. Credible evidence from several reproducible, randomized clinical trials with more than 10,000 patients support B·R·A·H·M·S PCT as an effective tool to safely reduce antibiotic exposure in patients. It has a proven utility across diverse clinical settings. In addition to other clinical criteria, these assays enable quick decision making by the clinicians, be it for starting antibiotic therapy or its safe discontinuation. B·R·A·H·M·S PCT greatly helps to reduce prescriptions, tailor the therapy duration to individual patient needs and finally supports to save costs.
There is a sheer need to develop and manufacture novel diagnostic testing tools that not only improve early diagnosis and treatment of life- threatening diseases like Sepsis, but also to provide high-quality immunodiagnostic assays to immensely support medical professionals and patients to get closer to a future without such dreadful infections.

About the author

Mr. Amit Chopra, Managing Director India and, Middle-East, Thermo Fisher Scientific
Amit joined Thermo Fisher Scientific India in May 2007 as Managing Director for their Laboratory Products Group in India, and was named Managing Director & VP/GM for Thermo Fisher’s India operations in March 2011. Amit has taken on additional responsibility for the Middle East region w.e.f. 2017.

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New Age Solutions for Diabetic Care

InnoHEALTH Magazine — Wed, 13 Feb 2019 10:47:37 +0000

Diabetes may not have a medically approved cure yet, but it sure can be turned a few knobs down with a well-balanced diet, regular exercise, and medication. Of course, one should follow a doctor’s advice for a lifestyle change. In the real world though, you look longingly at those French fries and convince yourself a few wouldn’t harm. Or you hit the snooze button and tell yourself, I will go for that long run tomorrow. And on and on you go, till your next visit to the Principal’s office, aka your doctor, where you hope miraculously for an improved report card. You are not alone my friend. Sticking to a regime requires discipline or an occasional reminder from your wellwishers (if you were me). A sight towards your goal and how far you have come in conquering it help matters further. Thankfully, plenty of new-age start-ups are here to make diabetes management and lifestyle changes easier.

Take for instance Life In Control and Wellthy Therapeutics. These digital platforms connect patients with doctors and coaches and provide personalized care in terms of diet and exercise plan. Users can create long-term health goals, follow-up daily tasks and keep tabs on their health profile including HbA1C and glucose levels, track medicines intake and understand how their daily routine affect these measures. These start-ups also give doctors the flexibility of reaching out to patients outside their clinical hours as well as to create and coach them on their personalized care plans. In the language of numbers, Life In Control has over 100 doctors on the platform and appears to have helped over a lakh patient with their app. Wellthy Therapeutics took the approach of a pilot program with diabetic patients and claims to have helped reduce both HbA1C levels by a little over 1% and an average weight reduction of 3.4 kgs over 16 weeks. It also got an endorsement by Asia’s largest diabetes association, Research Society for the Study of Diabetes in India. Both the apps are available for download on Android and iOS platforms.

Adding to the growing list of startups are those that detect blood glucose and connect directly to your smartphone. BioSense SYNC, for instance, is a compact Glucometer with Bluetooth connectivity to a user’s phone. It provides a detailed analysis of blood sugar data collected over a number of days. Similar to other diabetes management apps, a user can map their glucose data with their eating and exercising habits. Taking these interventions a step further, the start-up BeatO not only provides a smartphone Glucometer but also a range of diabetic friendly food products to munch upon. Patients can order medicines, sync their fitness devices and count calories on food items consumed. As of today, BeatO has served more than 25000 customers with a daily user add-on of 75-100. Most of these diabetes management apps can instantly connect a patient to a diabetic coach in case the sugar levels are off, and alert the patient’s family as well on concerning trends.

Complimenting these health management gurus, patients are also likely to benefit if there were devices providing at home diagnosis for diabetic complications, such as neuropathy, kidney malfunction or diabetic retinopathy. Scintiglo by Cutting Edge Medical Devices, Anupath by PathShodh and Sparsha by Yostra Labs have created Point of Care (PoC) tests to detect the first two complications. Scintiglo is a small handheld device that detects urinary proteins (should be trace levels in a healthy individual) at a low cost with remarkable accuracy and connects to a smartphone through a custom app. Anupath uses unique test strips for detection of specific biomarkers of diabetes, while also eliminating the need of usual sample preparation that one sees in clinics. Patients can get a comprehensive reading of their plasma and urine protein levels, HbA1c levels blood glucose and hemoglobin. While Sparsha, as the name suggests, focuses on touch-based tests that can diagnose diabetic peripheral neuropathy and send reports via users’ smartphone. Funded by the Department of Biotechnology grant (BIRAC), these start-ups focus on low-cost solutions, so an average user can save money on constant check-ups. Low costs also allow these start-ups to cater to rural segments of India, where a healthcare worker can refer patients to tertiary hospitals based on initial reports by these devices.

The complication of retinopathy, as mentioned above, relates to the slowly progressive disease of the eye and is one of the leading causes of blindness in diabetic patients. This segment is addressed by start-ups like ChironX and Artelus that use artificial intelligence to detect or monitor diabetic retinopathy risks from retinal image scans. Both the start-ups have achieved high accuracy of detection (over 95%) while the technology of AI confers an easy benefit of scanning retinas at a much faster speed to doctors and hospitals. Artelus also boasts to have saved over 3900 eyes so far from diabetic complications.

Given the burden of diabetes in every aspect of life (behavioral, physiological and financial), being handheld into recovery could be motivating for many patients. For maximum impact, we need to reach the furthest demographic corners of India, as diabetes has a growing prevalence in all sectors of the country. Infact, why wait for diabetes to knock at your door? One can also mitigate pre-diabetic conditions or reduce the chances of developing diabetes later in life. These start-ups aim to provide that ecosystem, where a patient can be led into an improved, healthy lifestyle at minimal costs. And just as it is heartening to see the growing awareness of Indians towards their health, it is equally imperative that these solutions are also as democratic as possible. Importantly in a booming start-up scenario, maintaining data integrity, complete transparency between doctors, patients and companies as well as strict adherence to ethical standards would go a long way in ensuring patient trust in this system.

About the author

Urvashi (Raheja) Bhattacharyya is a Biomedical Science graduate from Delhi University and a Ph.D. from National Centre for Biological Sciences. When not running behind her toddler, she spends time reading stuff about the brain, AI, ML, and latest innovations. Writing keeps her calm.

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InnoHEALTH Magazine | Volume 4 Issue 1 | Innovation in Diabetes – Unmet Needs
Highlights

Exclusive interview of H.E Klas Molin, Ambassador of Sweden to India on “Sweden-India collaboration in the health sector”
Digital healthcare
DISHA: Need of the hour. How crucial is DISHA (Act) for the healthcare industry?

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World’s First AI powered Ayurveda Protocol

InnoHEALTH Magazine — Wed, 26 Dec 2018 08:24:41 +0000

World’s First AI-powered Ayurveda Protocol launched in India; prospects of its linkage of AYUSH grid brighten up

Boarding a wobbly roadways bus, a dhoti-kurta clad young man, with protuberant vermillion dash on forehead, used to head for mythological twin city of Mathura and Vrindavan in Uttar Pradesh, clutching tightly his voluminous bag, stuffed with Ayurvedic medicines in tiny folded paper pouches for distribution to patients at ISKON center every weekend in early nineties.

But, recently, sporting a brick colored shirt and creamy Nehru jacket and matching black tight trousers, Ayurveda medicines practitioner Dr. Partap Chauhan unveiled world’s first Artificial Intelligence (AI) powered protocols modeled on the basis of a mind-boggling database of patients and their successful cure.

Moved by the protocols’ apparent efficacy, India’s AYUSH Secretary, Dr. Vaidya Rajesh Kotecha, has minced no words for exploration of a possibility to have a link of the protocols with the Ministry’s recently floated grid for the popularization of India’s traditional medicines at international fora.

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The world over, he said, moves are underway to reduce the cost of quality treatment. Recently, Amazon, Berkshire Hathaway, and JP Morgan have announced a company with an Indian American Dr. Atul Gawande as its CEO to work out healthcare of US employees. It might be typical of disrupting the healthcare industry whale cost, a conundrum is raging madly. The new company will be headquartered in Boston and will operate as an independent entity that is free from profit-making incentives and constraints.

Dr. Gawande is a globally-renowned surgeon, writer, and public health innovator. He practices general and endocrine surgery at Brigham and Women’s Hospital and is a Professor at the Harvard T.H. Chan School of Public Health and Harvard Medical School.

“I’m thrilled to be named CEO of this healthcare initiative,” said Dr. Gawande, “I have devoted my public health career to building scalable solutions for better healthcare delivery that are saving lives, reducing suffering, and eliminating wasteful spending both in the US and across the world”. This work will take time but must be done. The system is broken, and better is possible.”

He is the Founding Executive Director of the health systems innovation center, Ariadne Labs. He also is a staff writer for the New Yorker magazine, has written four New York Times bestsellers: Complications, Better, The Checklist Manifesto, and Being Mortal, and has received numerous awards for his contributions to science and healthcare.

“Medicine has triumphed in modern times, transforming the dangers of childbirth, injury, and disease from harrowing to manageable. But when it comes to the inescapable realities of aging and death, what medicine can do often runs counter to what it should”. Says Dr. Gawande in his book “Being Mortal”.

Dr. Kotecha envisions Indian traditional medicines’ colossal potential in ensuring cheap and best treatment and country’s values, coupled with such medicines, have answers of all these emerging challenges. He spoke briefly about the “Being Mortal” book and the newly formed company.

The AYUSH Secretary was of the view that Indian traditional medicines should be included in ICD -11 as Chinese medicines have entered the classification already. The International Classification of Diseases (ICD) is the international “standard diagnostic tool for epidemiology, health management, and clinical purposes.” Its full official name is International Statistical Classification of Diseases and Related Health Problems and is maintained by WHO.

Amid these developments, the protocols have been framed. Dr. Partap Chauhan, Director Jiva Ayurveda, narrated his arduous journey and said India’s traditional medicines efficacy was being recognized the world over, and his protocol would help according to it a scientific explanation on various parameters.

He had started his journey from a small dispensary in a garage in Haryana in 1992, and now a globetrotter is interacting with world-famous universities for deeper scientific researches on country’s 5000 years old traditional medicines.

The personalized treatment syndrome is catching up and researchers are underway on how to promote personalized treatment for more accuracy. He said the World’s first Diagnostic Protocols for Ayurveda would turn this ancient healing tradition into a data-and evidence-driven system of medicine and JIVA Health App.

These protocols, meant to standardize the practice of Ayurveda, have taken four years to develop after analyzing the consultation records of more than two lakh patients; the protocols have been successfully run on 20,000 patients till now, with dramatic results. This system will create a wealth of data and evidence that will go on to validate Ayurveda as a legitimate science of treatment, boosting its acceptability worldwide. The JIVA health app will provide authentic and actionable health and wellness information with content exclusively curated by Dr. Partap Chauhan.

JIVA group President Rishi Pal Chauhan has said the JIVA’s unique protocols are like an operating system for Ayurveda practice that structures the practice of Ayurveda and creates the wealth of data. It is well known that unlike Allopathy, which is focused on symptoms and standardized drug choices, Ayurveda is fundamentally a personalized system of medicine.

Even though thousands of years old, this traditional system of healing, conceptually, is a far more evolved science. For instance, personalized medicine (based on genomics) and the “systems view” of human health is only now beginning to come into fashion in allopathy, when Ayurveda has been built around these very concepts.

The reason is that the scientific community asks for data and evidence – on what basis are the medicines given and how is their effect proven? This data and evidence Ayurveda does not have. The big question is: “How do you standardize a system of medicine that is fundamentally personalized, with patients being given different treatment based on the root cause, even if the symptoms are the same?”

This is the challenge of mapping intuitive Eastern systems of medicine over objective Western frameworks. Data Analysis of Consultation Records of two lakh patients four years ago, Jiva Ayurveda began a huge data analytics project, reviewing the consultation records of two lakh patients that its doctors had treated over the decades.

After analysis, running into thousands of hours using artificial intelligence, machine learning, and computer modeling, the Jiva analysts concluded that while the Ayurveda treatment cannot be standardized for every patient, Ayurveda practice can surely be standardized. In other words, the way Ayurveda practitioners diagnose patients can be standardized by laying down definite protocols. This methodology currently exists only in the mind of the Ayurveda practitioner and each arrives at the diagnosis in his own way. The result of this is that no consistent data can be generated, and the methodology cannot be validated. And so began at JIVA the painstaking process of writing diagnostic protocols around the practice of Ayurveda by scanning the consultation records of lakhs of patients.

India’s first-ever Protocols for Ayurveda: the protocols that have been created over the last four years by Jiva. These protocols, and the decision support system built over them, help Ayurveda practitioners anywhere in the world arrive at the correct diagnosis in a data-driven way. The system also categorizes the diseases in terms of severity, which has a direct bearing on prognosis. As the consultation protocol flows, based on patient answers, the system starts assigning weights to different diagnostic possibilities and makes calculations to arrive at an authoritative diagnosis. It helps avoid judgmental errors and the cost of the wrong diagnosis. It also suggests diagnostic clues that the doctor may have missed which may lead to a possible different line of treatment.

Narrating all these, Dr. Chauhan says these protocols to standardize the practice of Ayurveda, the first-ever to be attempted in India, signal a revolutionary shift. They are akin to Ayurveda’s operating system that is accessible to everybody. This system will create a wealth of data and evidence that will eventually go on to validate Ayurveda as a legitimate science of treatment, boosting its acceptability worldwide. The protocols have been run successfully on 20,000 patients so far, with dramatic results. Three international universities are collaborating with JIVA to validate this data.

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National Strategic Plan for Elimination of Malaria

InnoHEALTH Magazine — Fri, 30 Nov 2018 06:17:45 +0000

National Strategic plan for the elimination of Malaria being implemented vigorously in India

Amid ongoing plans to eliminate malaria, experts have found the incidence of malaria in India is 0.66 cases per one thousand population last year.

Official sources say in the year 2017, reported malaria cases have declined by 23% as compared to 2016 in India.

As per the World Malaria Report 2017 of the World Health Organization (WHO), the estimated malaria cases from India are 87% in South East Asia region.

Malaria is mainly concentrated in the states of Chhattisgarh, Jharkhand, Meghalaya, Mizoram, Orissa, and Tripura because of the inaccessible terrain – many areas get cut off post-monsoon, the presence of efficient vectors – mosquito that transmits malaria and difficult terrain because of which malaria continues to be high in many pockets.

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Global Technical Strategy (2016-30) announced by WHO and adopted by World Health Assembly in May 2015 calls for malaria elimination by 2030.

According to the Minister of State (Health and Family Welfare) Ashwini Kumar, the Government has unveiled a plan to eliminate Malaria by 2030. The National Framework for Malaria Elimination (NFME) 2016-2030 document launched on 11th February 2016, lays out the vision, mission, broad principles and practices to achieve the target of malaria elimination by 2030 synchronizing with the Global Technical Strategy (GTS).

The Government has drafted National Strategic Plan for malaria elimination (2017-2020) wherein the country has been stratified based on the malaria burden into four categories – category 0 to category 3 and based on this the intervention of malaria control and prevention are being strengthened.

Interventions that are being strengthened are Early diagnosis and complete treatment; Case-based surveillance and rapid response; Integrated vector management; Indoor residual spray (IRS); Long-lasting insecticidal nets (LLINs)/ Insecticide-treated nets (ITNs); Larval source management (LSM); Epidemic preparedness and early response; Monitoring & Evaluation; Advocacy, coordination and partnerships; Behavior change communication (BCC) and Community mobilization and programme planning & management.

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Innovation Pitches from Global & Indian Companies

InnoHEALTH Magazine — Fri, 16 Nov 2018 08:56:58 +0000

The main concept behind the Innovation Pitches session was to enable innovative companies with the right to advise and linkages. Some of the top experts from Indian health sector listened to the company presentations and shared with them their feedback on how the companies should work on their goto market plan. The companies represented were a mix of Indian and European companies.

The companies who pitched and the expert panel were:
Companies Pitching:
● DocOnline Health India Pvt. Ltd.
● EMPE Diagnostics
● HealthCubed India Private Limited
Expert Panel:
● Adarsh Sharma, Financial Expert
● Sohini Mandal, Lawyer
● Nidhi Gani, Regulatory Expert
● Dr Vidur Mahajan, Industry leader
● Vishal Gandhi, Investment banker
● Dr Ravi Gaur, Industry leader
● Kshitij Chaudhary, Investment facilitator

Ajit Nair, DocOnline Health India Pvt. Ltd presented A Doctor Consultation Platform. Their core product offerings include – Last mile Clinical Delivery Platform/E Clinic Solution. They also enable a Clinical marketplace for their customers. DocOnline Health provides Doctor Consultation via video/audio and chat. Our Product is a secure platform ensuring data privacy. Provide Electronic Health Records for our customers. Doctor Consultations are provided in multiple regional languages. Flexible platform to derive clinical insights and Artificial Intelligence.

Pawan Asalapuram – EMPE Diagnostics presented his EMPE’s indigenous, customized test kits that can provide YES/NO answer in 60 min by developing visual signals and provides reliable clinical information already during the first contact point between the doctor and the patient. Our affordable tests are designed to operate even in resource-limited clinical laboratories, including medical camps.

Sridhar Ramanathan, HealthCubed India Private Limited has enabled better diagnosis for a patient by creating an ecosystem comprising of a multi-parameter point of care device operated with an easy to use the software on a mobile platform. It can screen for Vitals, Non Communicable diseases, and infectious diseases. It can expand the number of tests from 24 today to 65 based on user needs. Data is instantly backed-up in the cloud for further analysis.

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Young Indian Innovators Compete with Best Brains

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Regulatory alignment play catch up

InnoHEALTH Magazine — Fri, 13 Apr 2018 10:58:02 +0000

Telemedicine is no longer a form of medicine to be practiced in the future; it is very much prevalent now and has seen a very rapid increase in its take up in this millennium.

TELEMEDICINE IS ONE WAY OF practicing medicine, which may provide opportunities and increase possibilities to effectively use available human and material resources. The possibilities offered by telemedicine must be open to all doctors over geographical borders. I, however, prefer to advance to Telehealth, which involves the distribution of health-related services and information via electronic information and telecommunication technologies.

The Health Resources and Services Administration (HRSA – an agency of the U.S. Department of Health and Human Services) distinguishes telehealth from telemedicine in its scope.

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According to HRSA, telemedicine only describes remote clinical services; such as diagnosis and monitoring, while telehealth includes preventative, promotive and curative care delivery. This includes the nonclinical applications like administration and provider education which makes telehealth the preferred modern terminology. There has been an exponential increase in practice of telehealth which has meant that the legal and regulatory environment has not progressed as swiftly, for example the Data Protection Act, 1998 (DPA) in the UK has been in effect since March 2000 but has lacked the teeth to actually address the need of the hour. This is set to change with a new regulation. From May 25, 2018, the new regulation will come into force, which is being called, General Data Protection Regulation (GDPR). This is a regulation of the European Union Parliament and has a direct effect.

It is also believed that the inculcation of GDPR will go ahead despite Brexit i.e. Britain (UK) leaving the European Union.

GDPR will have certain principles which are strong and stringent, though further clarity on each of these will be over time and by judicial decisions, it is certainly set to have more power.

Consent has always been considered of great importance, however, it has been more implicit under the DPA but under the new GDPR there will be a need for a clear explicit consent from individuals to collect data. The other changes with massive repercussions for businesses doing business within or with the UK and EU will be in regards to automated decision making tools; right to access and portability; penalties; accountability and privacy notices.

This includes the non-clinical applications like administration and provider education which makes telehealth the preferred modern terminology. There has been an exponential increase in practice of telehealth which has meant that the legal and regulatory environment has not progressed as swiftly, for example the Data Protection Act, 1998 (DPA) in the UK has been in effect since March 2000 but has lacked the teeth to actually address the need of the hour. This is set to change with a new regulation. From May 25, 2018, the new regulation will come into force, which is being called, General Data Protection Regulation (GDPR).

GDPR PRINCIPLES:
• Information to be processed fairly and lawfully
• The personal data must be collected for specified, explicit and legitimate purposes
• It should be adequate, relevant and not excessive for those purposes
• It should be accurate and up to date
• It should be kept no longer than is necessary for the purposes it is being processed for
• Maintain integrity and confidentiality
• There will be accountability

(The writer is a lawyer with a Diploma in Hospital Administration from India; Masters of Law in Intellectual Property Rights from the U.S.A, Masters of Science in Telemedicine & ehealth from the UK and years of experience in Telehealth law research.)

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Read all the issues of InnoHEALTH magazine:
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InnoHEALTH Volume 1 Issue 2 (October to December 2016) – https://goo.gl/4GGMJz
InnoHEALTH Volume 2 Issue 1 (January to March 2017) – https://goo.gl/DEyKnw
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InnoHEALTH Volume 2 Issue 3 (July to September 2017) – https://goo.gl/MCVjd6
InnoHEALTH Volume 2 Issue 4 (October to December 2017) – http://amzn.to/2B2UMLw
InnoHEALTH Volume 3 Issue 1 (January to March 2018) – https://goo.gl/fksdQx
InnoHEALTH Volume 3 Issue 2 (April to June 2018) – https://goo.gl/grbtRo

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FIRST DIGITAL BREAST TOMOSYNTHESIS

InnoHEALTH Magazine — Tue, 09 Jan 2018 10:43:43 +0000

Breast Cancer has been ranked as the number one cancer among Indian women with age adjusted rate as high as 25.8 per 100,000 women, as per the latest statistics published in the Asia Pacific Journal of Clinical Oncology. Bengaluru has ranked third with age adjusted incidence rate of carcinoma of the breast found as high as 34.4 per 100,000 women. Projections for India suggest the number of breast cancer cases will likely go as high as 1,797,900 by 2020. Though there has been an increase in health check-ups among women recently and we can still see that screening is low on priority even in major cities.

Cytecare hospital is the first hospital in the city to introduce Digital Breast Tomosynthesis (popularly known as 3D-Mammography) for women.

Mammography continues to be the only screening test proven to decrease mortality from breast cancer. However, 2D mammography is less accurate in women with dense breasts for whom cancer may be masked by overlapping breast tissue. When a 2D mammogram detects an area of concern, radiologists further investigate with a diagnostic mammogram, ultrasound or biopsy. Looking at the same breast tissue in 3D, the radiologist may now be able to see that the abnormality on 2D mammogram in fact represents normal breast tissue. This avoids further investigation in large number of patients undergoing routine screening.

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3D mammography or Tomosynthesis is a special kind of mammogram that uses several low dose x-rays obtained at different angles to create multiple images or “sequential slices” that step through the breast tissue and allows radiologists to see more clearly. The breast is positioned and compressed in the same way as for a 2D mammogram but the x-ray tube moves in a circular arc around the breast. It takes less than 10 seconds for the scan. The information from the x-rays is sent to a computer, which produces a focused 3 D digital image of the breast.

There is no organised national or regional breast cancer screening program in India. Naturally, majority of those involved in women’s health are not aware of the available technology and expertise in the field of breast cancer diagnosis. Needless to say, women undergoing screening have little understanding of the tests or the results thereof.

In contrast to the western world, breast cancer incidence is much higher in premenopausal age group (<50 years) in India. As compared to both screen film and Computed Mammograms (older but most widely used technologies), 2D and 3D Digital Mammography has significantly higher accuracy in cancer detection in younger women and in women with dense glandular breasts. This will have large impact on decreasing the number of women undergoing unnecessary recalls or biopsies. It is most important to avoid anxiety in women opting for screening tests. 3D mammography serves as an excellent problem solving tool and reduces misdiagnoses. Contrary to common practice, ultrasound alone has significant limitations as a screening tool and must always be combined with a 2D or 3D Digital Mammogram. The x-ray dose of 3D mammography is comparable to that of a 2D mammogram. Therefore the cumulative dose of the combined screening is still below the FDA regulated limit and found to be safe and effective for patient use.

Incorporating this aspect Cytecare hospital’s breast imaging services are complete with Digital Breast Tomosynthesis (DBT or 3D Mammogram), Full Field Digital Mammogram (FFDM), Stereotactic and Vacuum Assisted Breast Biopsy (VABB).

3D mammography has shown to reduce percentage of missed cancers by 15%. More recent studies show about 30% increased 3D mammography sensitivity and specificity compared to 2D Mammography with a recalls reduction in screening by approximately 40%.

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