Myalgic encephalomyelitis, better known as Chronic Fatigue Syndrome (CFS), is a complicated disorder characterised by extreme fatigue that lasts for at least six months and cannot be fully explained by an underlying medical condition. As the world marks CFS Day on May 12, Omnia Health takes a look at various facets of the condition and its management.

According to Mariana Bodiu, a specialist at Plumm — a platform that delivers personalised care for workplace mental well-being — fatigue worsens with physical or mental activity but does not improve with rest.

“The most frequent indicators of CFS include sleep that is not refreshing, difficulties with memory, difficulties maintaining focus and concentration, and dizziness which worsens with minimal body movement,” she said.

The cause of CFS is unknown, although there are several theories ranging from viral infections to psychological stress. “In my professional opinion, CFS is frequently triggered by a combination of factors. As per my experience in private practice, the population residing in major cosmopolitan cities is at greater risk of suffering from CFS. The dynamic rhythm of life, ultra-demanding jobs, and extreme costs of living are all stressors that gradually build up,” she added.

Perception and diagnosis

There is no single test to confirm a diagnosis of CFS and a variety of medical tests may need to be performed to rule out other health problems that have similar symptoms. Treatment for CFS, however, focuses on improving symptoms as the condition is prone to relapse, said Bodiu, who is a Jungian Psychotherapist specialising in the intergenerational transmission of trauma and extensive individual psychoanalysis.

Symptoms of CFS can vary from person to person, and the severity of symptoms can fluctuate from day to day. As previously mentioned, signs and symptoms may include, but are not exclusive to, fatigue, problems with memory or concentration, headaches, unexplained muscle or joint pain, and extreme exhaustion after physical or mental exercise, she added.

Current treatment strategies

Making some lifestyle adjustments may help reduce symptoms. Limiting or eliminating caffeine intake can help improve sleep and ease insomnia.

“The avoidance of nicotine and alcohol is highly recommended. I would also avoid napping during the day if it’s hurting an individual's ability to sleep at night. Creating a sleep routine can be significantly life changing,” Bodiu added.

Commenting on medication involved in CFS treatment, she said that neurostimulants increasing dopamine and norepinephrine activity, such as bupropion, dextroamphetamine, and recently immediate-release methylphenidate have been advocated to improve neurocognitive deficits.

“The use of immediate-release methylphenidate in CFS has been identified in one small study. Using the positive results of this study and the well-known beneficial effects of the drug on a range of similar cognitive symptoms in attention-deficit/hyperactivity disorder, this perspective addresses CFS and other related disorders and provides a discussion on the potential promising role of methylphenidate in the therapeutic armamentarium of CFS.”

Therapists’ role in managing the condition

Despite increased research efforts, CFS remains a complex condition with no exact known cause or cure. “The recovery rate is only 5 per cent, so managing CFS can therefore be challenging. Patients will likely need to make lifestyle changes to adapt to their chronic fatigue. As a result, they may experience depression, anxiety, or social isolation,” she said.

This is where a consistent approach to mental well-being must become a priority. According to Bodiu, the practice of psychotherapy can make a great difference in managing CFS by keeping account of the symptoms and long-term effects, physical and psychological. 

“CFS progresses differently for everyone, so it is important to work with a dedicated doctor to create a treatment plan that meets individual needs as well as proactively revising a list of personal priorities. The allocation of your time, energy, and overall vitality is very important. I find that my patients have been rather receptive to reconsidering priorities as a strategy to overcome the heavy burden of CFS,” she concluded.

Florence Nightingale was the pioneer of modern nursing and early proponent of evidence-based nursing practices in the 19^th century, yet I don’t think she would recognise all the technology in modern hospitals. The world has changed a lot in the last two centuries. However, I believe she would understand the vital importance of data, the pressures on nurses in providing patient care today, and how – together – data and nurses can transform healthcare systems.

She may even question the current state of nursing informatics and areas of investment that are growing increasingly important, something that others in the healthcare community have also done since the start of the pandemic. So, I view International Nurses Day – the day celebrated in Florence Nightingale’s memory – as an opportunity for reflection.

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The theme for International Nurses Day 2022 is “Nurses: A Voice to Lead” and serves as a call to action to “invest in nursing and respect rights to secure global health.” Supporting nurses is critical for the health of patients and the well-being of nurses, which is why we must accept that technology is a vital part of today’s healthcare systems and must be better prioritised in terms of investment.

Nurses play valuable roles on every healthcare team and are often the ones delivering front-line patient care in the emergency room or in a patient’s room. The amount of time a nurse spends with a patient and the time it takes a nurse to respond to a patient call button directly affects patient outcomes. Without technology driving the right nurse to the right place to take the right action at the right time, there is a risk of delays or impacted decisions.

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Plus, there’s a growing shortage of nurses, which means patient capacity could decline if healthcare systems aren’t using technology to compensate – to augment the workforce. In 2020, The World Health Organization’s (WHO) first State of the World's Nursing report revealed the global nursing workforce was 27.9 million and estimated a global shortfall of 5.9 million nurses.

If we want to stop the bleed and prevent some of healthcare’s acute issues from becoming chronic, we must give nurses a voice in business decisions. They need the opportunity to influence technology investments. Who better to say which technology tools are effectively augmenting nursing teams and automating workflows than nurses? Only they will be able to confirm which technologies make it easier to give each patient the attention they deserve. 

A new set of priorities

Healthcare has traditionally been focused on controlling costs, providing care for the population, and the ‘consumer’ – meaning patient – experience. Now, healthcare system leaders are looking ahead and focusing on building sustainable operating models with new priorities, including improving the provider-employee experience and increasing health equity by providing care for more people and improving healthcare access. Of course, this must all be supported by technology to be successful.

The pandemic was a major accelerant for technology adoption across acute care environments. In a recent Healthcare Vision Study commissioned by Zebra Technologies, 85 per cent of decision-makers reported that their hospitals sped up their technology projects and continue to increase investments in mobility, locationing and automation solutions. Ninety-five percent (95 per cent) of IT decision-makers expect to increase spending in healthcare IT and clinical mobility by the end of 2022.

More specifically, hospital executives say they will invest heavily in care team communication and patient engagement tools, as well as mobile alerting systems. Near-term deployments will include both radio frequency identification (RFID) and Bluetooth® Low Energy (BLE) solutions that provide pinpoint location accuracy and expedite asset retrieval.

Nurses rely heavily on medical equipment to deliver patient care, including ventilators, infusion pumps and basic aids such as wheelchairs. Any delay in patient treatment due to troubles locating equipment or other team members for assistance adds to the stress both nurses and patients experience. Yet, one analysis estimates that nurses spend up to 40 hours a month searching for equipment, and 65 per cent of clinicians who participated in the Zebra study currently feel staff spend too much time searching for medical equipment and supplies. Every minute counts in a hospital environment, which is why every investment in track and trace technology counts.

The good news is that any investments made in location solutions have the potential to deliver multiple benefits. RFID and BLE systems can also help healthcare providers improve asset utilization, contact tracing and infection control. 

Healthcare studies also show that technologies like real-time location systems (RTLS) can result in up to a 50 per cent reduction in bed turnover times and as much as a three-hour reduction in patient length of stay. In a 275-bed hospital, cutting just four hours off the average hospital stay is the same as adding 10 new beds.

Taking a data-driven approach to addressing new nursing priorities?

Real-time data is largely viewed as essential to delivering advanced patient care, which is why more hospital decision-makers are planning to invest in locationing technology such as RFID for real-time visibility of equipment, supplies and the specimen chain across healthcare systems. However, healthcare IT teams have to update systems at the hardest time possible. That’s why we must turn to data to help guide technology decisions and understand which solutions are most apt to make the nursing shortage a nonissue.

In other words, we should not just be talking about the lessons learned from the pandemic for the sake of hindsight and “what we should have done better.” That was 2021 thinking. We must now look ahead to the next 12 months and lay the groundwork for the next few years based on what we know we can – and must – do better. Healthcare system leaders are feeling very ‘heads down’ to survive right now and it's time to change that. More than two-thirds (67 per cent) of hospital executives who participated in Zebra’s study don’t feel their organisations are investing enough to maximise staff efficiency and believe more must be done, so let’s do more (together).

Healthcare administrators will need to work quickly with nurses to find and deploy technology tools that facilitate widespread collaboration, improve planning and execution, and balance schedules according to actual – rather than assumed – bandwidth.

They must also spend much of 2022 collectively examining ways to automate workflows, information transfers, and physical hand overs of patients, equipment, rooms, supplies, medicines and more. As RFID technology is increasingly integrated into hospital technology architecture to expedite patient, staff and equipment locationing as well as the overall patient journey, healthcare leaders and IT administrators will need to ensure front-line staff can maximise the data generated by those RFID systems to get through tasks faster. That’s the only way everyone’s days will become easier, and nurses will become more likely to stay in the profession.

A call to action

This International Nurses Day gives us the opportunity to recognise the extraordinary value of our nursing community with tangible action. We must remain committed to empowering healthcare workers by making the equipment that supports their vital work visible, connected and fully optimised. We must follow through on the growing list of priorities so the list of “issues” hindering healthcare shrinks. Florence Nightingale recognised the unique perspective of nurses in improving healthcare and we salute this remarkable vision today by turning to nurses to guide the way forward; they truly know the power and potential of technology.

Rikki Jennings is Chief Nursing Informatics Officer at Zebra Technologies and a Registered Nurse

Clinical nutrition in medicine has a pivotal role, helping physicians diagnose and treat disorders that affect dietary constituent intake, absorption, and metabolism. As clinical nutrition is a part of a multidisciplinary approach in treatment, it also promotes good health via the prevention of diet- related diseases such as obesity, with its co-morbidities of hypertension, diabetes, dyslipidaemias, increased risks of cardiovascular disease, some cancers and pulmonary failure. In addition, intestinal disorders related to inadequate nutrient absorption; eating disorders; and malnutrition associated with chronic illness and surgical trauma are among the most common causes of mortality.

Scientific breakthroughs on the association between dietary components and illness cellular mechanisms emerge on a regular basis. A high frequency of nutritional diseases in clinical medicine and mounting scientific data supporting the importance of dietary modification in disease prevention is growing, along with the standardisation of curricula for nutrition education of medical students and trainees, is becoming increasingly important for the cost-effective integration of nutritional concepts into medical practice.

Related: Does Ketogenic diet work as a treatment for Type 2 diabetes and obesity?

Use of digital technology in clinical nutrition is also gaining prevalence, with AI being used namely in diet optimisation, food image recognition, risk prediction and diet pattern analysis. In an interview with Lina Shibib, Clinical Nutritionist, Medcare Hospitals and Medical Centres, we dive into how innovation and tech advancements are being integrated in clinical nutrition to support treatment plans become personalised in combatting chronic illnesses. Excerpts:

How does clinical nutrition serve as an integral component of chronic disease management in multidisciplinary approaches?

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Chronic disease represents one of the most important challenges facing healthcare systems. According to the WHO, tobacco use, physical inactivity, and unhealthy diet are the three most common modifiable risk factors of chronic disease. Most approaches to “fix the damage” would have to go back to these three factors – all which can be dealt with by a clinical nutritionist. As per the CDC, adults who eat a healthy diet live longer and have a lower risk of obesity, heart disease, type 2 diabetes, and certain cancers – the top causes of mortality. So basically, good nutrition can help reduce the risk and even treat some diseases, including heart disease, diabetes, stroke, some cancers, and osteoporosis.

Comment on the relationship between clinical nutritionists and physicians (for example, when diagnosing patients with irritable bowel syndrome) and working hand-in-hand to create personalised treatments.

As chronic disease numbers are rising, so is the demand for a multidisciplinary approach to target the villain – which many times is diet and lifestyle. A doctor will identify the cause, whereas the nutritionist will educate the patient further on a more personal level. Nutritionist literally “befriend” the patient to find out as much as possible about the patient’s diet, lifestyle, sleep, exercise, as well as psychology. Once all these families are discovered, the nutritionist will then report back (if necessary) to the doctor to account for all those aspects in the treatment plan, and together come up with a personalised approach for the patient. In the case of irritable bowel syndrome (IBS), for example, a doctor will diagnose the condition, but the nutritionist will work with the patient closer to discover which foods and habits are causing the symptoms and teach them healthy eating methods to avoid future discomfort.

As healthcare pivots towards digitalisation, how has this affected the clinical nutrition discipline?

Artificial Intelligence (AI) is human intelligence displayed by machines, and it is a technology that allows computers to conduct cognition, learning, inference, and actions in the same way that people can. To accomplish this, a machine must learn an algorithm based on a vast amount of big, scientific data acquired using a deep learning technique. Nevertheless, the real scientists will always be the nutritionists. An app can easily help a patient calculate calories, identify “hidden ingredients”, calculate blood pressure, blood sugar, and even exercise but it cannot go out of its “way”, in this case algorithm, to personalise a diet plan.

Just as technology is evolving, so is the F&B world. New foods require proper clinical-based research before being introduced into apps – most of which these apps lack. For a proper clinical nutrition plan, a one-size-fits-all diet through apps is not going to target the medical issue on a personal level. In some cases, a simple wrong data entry might even result in the wrong “advice”, which, especially in case of a medical condition, can have a serious impact on health.

Does AI play a part in automating the requirements of certain patients based on data? How can this prevent the prevalence of chronic illnesses and help manage it?

AI is generally regarded as positive by practitioners but also brings with it many challenges in medical ethics and patient-clinician relationships. AI systems can analyse unstructured clinical notes on patients, prepare reports (for example, on radiology examinations), transcribe patient interactions and conduct conversational AI, but the final translation of the data needs to always be approved by an actual doctor.

Healthcare is also being tackled by many tech companies and start-ups. For example, Google is working with health delivery networks to develop big data prediction algorithms that will alert clinicians to high-risk illnesses like sepsis and heart failure. AI-based image interpretation algorithms are being developed by Google, Enlitic, and several other firms. Jvion provides a 'clinical success machine’ that identifies patients who are most at risk and most likely to react to treatment programmes. Each of these could help professionals determine the optimal diagnosis and therapy for their patients by providing decision support, but not actually “do” the doctors job of prescribing and operating.

Researchers at the Mayo Clinic have made the first step toward applying artificial intelligence (AI) to predict early outcomes with antidepressants in children and adolescents with major depressive disorder. They discovered variations in six depression symptoms: trouble having fun, social withdrawal, excess fatigue, irritability, low self-esteem, and depressed sentiments. The study is published in The Journal of Child Psychology and Psychiatry.

Over 50 per cent of all mental health disorders are diagnosed when individuals are young (under the age of 18). As a result, it is critical to establish predictive approaches for treatment outcomes in depressed youth, according to Arjun P. Athreya, PH. D, M.S, a Mayo Clinic researcher and lead author of the study. This research addresses a global public health problem as paediatric depression is common and often undertreated.

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The ‘Children's Depression Rating Scale, Revised’ was used by the researchers to assess these symptoms and predict the results of 10 to 12 weeks of an antidepressant pharmacotherapy programme.

In fluoxetine testing datasets, the six symptoms predicted 10 to 12-week results with an average accuracy of 73 per cent at four to six weeks, whereas in duloxetine testing datasets, the same six symptoms predicted 10 to 12-week results with an average accuracy of 76 per cent at four to six weeks.

Related: Treating depression and anxiety in an age of technological advancement

Predicting response and remission accuracy in placebo-treated patients was much lower than in antidepressant-treated individuals, at 67 per cent.

“This preliminary work suggests that AI has promise for assisting clinical decisions by informing physicians on the selection, use, and dosing of antidepressants for children and adolescents with major depressive disorder," says senior author and Mayo Clinic Child Psychiatrist Paul Croarkin, D.O. "We saw improved predictions of treatment outcomes in samples of children and adolescents across two classes of antidepressants."

The current findings demonstrate that an AI platform using machine learning can predict antidepressant treatment outcomes in children and adolescents early during therapy. This is highly beneficial in the future as it has the potential to assist busy clinicians in treatment planning for adolescents while avoiding exposure to treatments that may not be effective for a patient. Furthermore, the findings show the potential of AI and patient data to ensure that children and adolescents receive treatment that has the highest likelihood of delivering therapeutic benefits while minimising side effects, according to Dr Athreya.

"We designed the algorithm to mimic a clinician's logic of treatment management at an interim time point based on their estimated guess of whether a patient will likely or not benefit from pharmacotherapy at the current dose," says Dr Athreya. "Hence, it was essential for me as a computer engineer to embed and observe the practice closely to not only understand the needs of the patient, but also how AI can be consumed and useful to the clinician to benefit the patient."

This integration makes use of clinical symptom changes that occur early during treatment. Patients undergo standard interviews, but using this platform, they may be given accurate predictions of treatment outcomes.

The findings of the study serve as a foundation for future research incorporating physiological information, brain-based measures, and pharmacogenomic data for precision medicine approaches in treating depressed youth. This will improve the care of young children suffering from depression and assist physicians in initiating and dosing antidepressants in patients who will benefit the most.

"Technological advances are understudied tools that could enhance treatment approaches," says Liewei Wang, M.D., PhD, the Bernard and Edith Waterman Director of the Pharmacogenomics Program and Director of the Centre for Individualised Medicine at the Mayo Clinic. "Predicting outcomes in children and adolescents treated for depression is critical in managing what could become a lifelong disease burden." 

The study was a collaborative effort between the Mayo Clinic departments of Molecular Pharmacology and Experimental Therapeutics, as well as Psychiatry and Psychology, with assistance from the Mayo Clinic Centre for Individualised Medicine.

This present research is promising, although it is still in its early stages. Dr Athreya adds that future research will integrate biological data or "biomarkers" to enhance or increase diagnostic accuracy and treatment planning.