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Popular semaglutide-based drugs used for weight loss may reduce chronic and acute pain, which could make them a promising alternative to opioids
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Tag: Pain
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Weight-loss medications may also ease chronic pain
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More people are living with pain today than before covid emerged
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Chronic pain has increased among adults in the US since 2019, which could be due to a rise in sedentary lifestyles or reduced access to healthcare amid covid-19 restrictions
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Meditation seems to improve our empathy for strangers
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Meditation can help you connect with others
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An eight-week meditation programme led women to experience more empathy for strangers, suggesting that meditation can improve our ability to understand and experience other people’s feelings.
“When you practise mindfulness meditation, these feelings of connectivity and empathy and compassion arise naturally. It is like a side effect almost,” says Fadel Zeidan at the University of California, San Diego. This type of meditation is the practice of focusing attention on the present moment by observing sensations like the breath and is believed to reduce people’s sense of self and help them…
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Pain relief from the placebo effect may not actually involve dopamine
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Dopamine (red) approaching one of its receptors (blue)
JUAN GAERTNER/SCIENCE PHOTO LIBRARY/ALAMY
The hormone and neurotransmitter dopamine is generally believed to be a driving force behind experiencing pain relief with the placebo effect, but it may actually play little or no part in the phenomenon.
The placebo effect occurs when someone’s medical symptoms are lessened through the power of suggestion and expectation, such as by taking a sugar pill. Dopamine, along with opioids and cannabinoids that are produced naturally in our bodies, was thought to be involved in this for pain relief specifically.
To get a clearer picture, Ulrike Bingel at University Hospital Essen in Germany and her colleagues teamed up with the Treatment Expectation research centre, also in Germany. The scientists asked 168 people, aged 18 to 40 and with no known medical conditions, to apply two creams to different parts of their arms, before being touched with a heated rod, which caused mild discomfort.
The creams were identical, but participants were told that one contained an active pain-relieving ingredient and the other was acting as a placebo.
Shortly before, the researchers asked the participants to take medications that suppressed dopamine, encouraged its release or didn’t alter its level.
The participants’ dopamine levels changed as expected, but this didn’t seem to affect how much pain they experienced or how much they anticipated that they would feel, which were both rated on a scale of 0 to 10.
This suggests that dopamine isn’t directly linked to the placebo effect for pain relief, says Bingel. Opioids and cannabinoids probably play a stronger role, she says. Hormones such as oxytocin and noradrenaline (norepinephrine) may also have an effect, which future studies could investigate, says Bingel.
However, it is also possible that dopamine comes into play when people are more motivated to feel pain relief, such as when the discomfort is more intense than it was in this study, she says.
Understanding the placebo effect could lead to therapies that harness its action for better pain management, says Bingel.
Lauren Atlas at the National Institutes of Health in Bethesda, Maryland, says that the placebo effect probably involves “verbal instructions and social factors that depend on the context surrounding treatment, and these factors are unlikely to be mediated by dopamine”.
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Most effective migraine drugs revealed by review of trial data
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Researchers assessed the efficacy of 17 drugs for treating migraines
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An underused category of drug appears more effective for managing migraine-related symptoms than newer, costlier medications, according to a sweeping review of clinical trials.
Despite being designed specifically to treat migraine episodes, triptan drugs are used in less than 22 per cent of migraine cases. Providing that patients have no medical conditions that preclude their use, such as cardiovascular disease, the results suggest people should consider low-cost triptans as a first-line treatment for migraine relief, says Andrea Cipriani at the University of Oxford.
“It’s not a bad idea to pull all the data together and re-emphasise – particularly to primary care physicians – that if someone comes in with migraine and they’ve got no contraindication, and they’ve tried [non-steroidal anti-inflammatory drugs], the evidence base for using the triptans is really quite good,” says Peter Goadsby at King’s College London, who wasn’t involved in the review.
Triptans, such as sumatriptan and eletriptan, have been progressively authorised globally since 1991 and are now available as off-brand or generic tablets. However, case reports have suggested that the drugs may trigger heart attacks or strokes – especially in people with pre-existing cardiovascular issues.
To offer alternative treatments, pharmaceutical companies developed newer drugs called ditans and gepants – which have a similar mechanism of action to triptans but avoid the cardiovascular risks. Licensed only in the past few years, these drugs – lasmiditan, rimegepant and ubrogepant – come at a high cost. For example, Eli Lilly’s trademarked formulation of lasmitidan, Reyvow, retails for $92.50 per 24-hour tablet, compared with about $17 for generic eletriptan.
People also have the option of taking non-steroidal anti-inflammatories (NSAIDs), such as ibuprofen, and analgesics, such as paracetamol, to control their migraine symptoms.
While researchers have carried out hundreds of studies investigating the efficacy, safety and side effects of each of the many drugs and drug classes used to treat migraines, there had been a lack of work comparing them with each other, says Cipriani. To take advantage of the vast amount of existing knowledge, he and his colleagues analysed 137 double-blind, randomised controlled trials carried out worldwide since 1991.
With a total of 89,445 adult participants, the trials assessed the efficacy of 17 oral medications in comparison with either a placebo or one of the other drugs. The team judged the drugs’ performance using recommended criteria from the International Headache Society, including how well the medications managed pain over a 2-hour period or throughout 24 hours following regular dosing.
Their results revealed that the most effective drug for pain relief at the two-hour mark was the triptan eletriptan, followed by three other triptans: rizatriptan, sumatriptan, and zolmitriptan.
Eletriptan and ibuprofen were the most effective drugs for sustained pain relief up to 24 hours.
Lasmiditan, rimegepant and ubrogepant, however, were no more effective in relieving the clinical signs of migraine than paracetamol and most of the NSAIDs – and they carried a higher risk of side effects, such as nausea. As such, these drugs should be considered “third-line options”, says Cipriani.
The findings suggest that some people would benefit from treating their migraines with certain triptans. But that doesn’t mean they are the right solution for everyone, adds co-author Elena Ruiz de la Torre at the European Migraine and Headache Alliance, in Brussels. “Migraine is a very personal disease,” she says.
“You really have to do the best thing for the person sitting in front of you,” says Goadsby. Meta-analyses like this one can’t offer much insight at a personal level, he says. “They tell you about a population, but they’re very blunt instruments for trying to understand what’s going on at an individual level.”
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Cats have brain activity recorded with the help of crocheted hats
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Custom-made wool caps have enabled scientists to record electroencephalograms in awake cats for the first time, which could help assess their pain levels
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Walking helps keep people free of lower back pain for longer
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Being active has a range of health benefits
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People who have recurring bouts of lower back pain seem to avoid the discomfort for longer if they go for regular walks.
More than 600 million people worldwide experience pain in this part of the back, which often recurs after initially resolving. Despite this high prevalence, there is very little research into its prevention, says Tash Pocovi at Macquarie University in Sydney, Australia.
Wanting to find an affordable and relatively accessible way for people to avoid the pain returning, Pocovi and her colleagues designed “WalkBack”, the first controlled trial of its kind.
The researchers selected 701 people, aged between 20 and 82 years old, who lived throughout Australia and had experienced an episode of lower back pain without a specific diagnosis, such as a fracture or infection, within the previous six months that then resolved.
On average, they had each had 33 episodes of lower back pain, which interfered with their daily activities and lasted at least 24 hours. None of the participants regularly chose to go for recreational walks or engaged in any kind of exercise programme for pain management.
The scientists asked 351 of them to develop an individualised walking programme with the help of a private physical therapist, aiming for a gradual build-up to 30 minutes of walking, five days a week, within six months. The programme varied according to each individual to help them stick to it, says Pocovi. By 12 weeks, the participants were walking an average of 130 minutes per week.
They were also told about the latest scientific knowledge regarding lower back pain, which was meant to reassure them that it is safe to move under the supervision of their physical therapist, says Pocovi. “A lot of people become avoidant and fearful of movement when they have a history of back pain,” she says.
The remaining 350 volunteers received no such education or walking programme recommendation. Pocovi and her team followed all the participants for up to three years. Regardless of which group they were in, they were free to seek any additional treatment for their pain.
On average, those in the treatment group had their first recurrence of activity-limiting lower back pain 208 days after the study began, compared with 112 days in the control group.
Furthermore, half the people in the control group sought other interventions, such as massages and chiropractic treatment, compared with only 36 per cent of those following the walking and education programme. However, the latter group was more likely to experience mild complications of exercise, such as sprains.
“I think this is probably a handy tool that clinicians and even patients can go to their clinicians with,” says Pocovi.
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Prenatal opioid exposure not associated with risk of neuropsychiatric disorders in children
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Opioid use during pregnancy is not associated with a substantial increase in the risk of neuropsychiatric disorders such as ADHD in children, finds a large study from South Korea published by The BMJ today.
A slightly increased risk of neuropsychiatric disorders was found, but the researchers say this should not be considered clinically meaningful because it was limited to mothers exposed to more than one opioid prescription, high doses, and over longer time periods during pregnancy.
According to 2019 data from the Centers for Disease Control and Prevention, around 7% of women in the United States were prescribed opioids during pregnancy.
Previous studies have shown mixed findings on the association between opioid use in pregnancy and various health outcomes in offspring due to small sample sizes and short follow-up periods.
To address this knowledge gap, an international team of researchers set out to investigate the potential association between opioid exposure during pregnancy and risk of neuropsychiatric disorders in offspring.
Their findings are based on data from the National Health Insurance Service (NHIS) of South Korea for 3,128,571 infants born between 2010 and 2017 and 2,299,664 mothers (average age 32).
Mothers were grouped according to dose, duration, and frequency of opioid prescriptions during pregnancy and infants were followed up for an average of six years.
Factors including mother’s age at delivery, household income and pre-existing health conditions, and infant sex, birth weight and breastfeeding history were taken into account. A sibling comparison analysis was also carried out to account for genetics, lifestyle, and environmental influences.
Overall, 216,012 (7%) of the 3,128,571 infants were exposed to opioids during pregnancy (prenatal exposure).
A small increased risk of neuropsychiatric disorders was found among children exposed to prescription opioids during pregnancy compared with those not exposed, but the researchers interpret this as clinically insignificant.
And no significant association was noted in the sibling comparison group.
However, exposure to prescription opioids during the first trimester of pregnancy, at higher doses, and for 60 days or more were associated with a slightly increased risk of mood disorders, ADHD, and intellectual disability.
This is an observational study so no firm conclusions can be drawn about cause and effect, and although the researchers adjusted for a range of factors, they can’t rule out the possibility that others may have influenced their results, or that some misclassification of opioid use may have occurred.
Nevertheless, this was a large study based on high quality data and several statistical analyses were carried out to test the strength of the results, providing greater confidence in the conclusions.
As such, they conclude: “These results support cautious opioid prescribing for relief of pain during pregnancy, highlighting the importance of further research for more definitive guidelines.”
In a linked editorial, researchers agree that while short term use of lower dose prescription opioids after the first trimester appears relatively safe, caution is warranted when prescribing opioids for longer durations or at higher dosages.
This study “provides additional evidence to inform clinical decision making for women requiring pain management during pregnancy,” they write.
“Given the unique clinical value of opioids for managing severe pain, additional research is needed to fully characterize the degree of risk and thoroughly disentangle the association among pain, pain management, and various pregnancy outcomes,” they conclude.
Source:
Journal reference:
Kang, J., et al. (2024). Prenatal opioid exposure and subsequent risk of neuropsychiatric disorders in children: nationwide birth cohort study in South Korea. BMJ. doi.org/10.1136/bmj-2023-077664.
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Researchers aim to use AI for early screening and prognosis of Dry Eye Disease
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Dry Eye Disease (DED) is one of the more common eye diseases, affecting up to 30% of the world’s population. This disease can affect many different types of people and can wind up being a great hindrance to their overall quality of life. Early screening and prognosis is vital to the patient’s progression with the disease. However, this can be difficult. In this study, researchers aim to use artificial intelligence (AI) to aid in early screening and prognosis of DED. Not only can the use of AI make screening more accessible for individuals, but it can also aid patients in personalized therapeutic intervention.
Researchers published their results in Big Data Mining and Analytics on April 22.
DED can affect a wide array of people, including those who wear contact lenses, makeup, stay up late, look at screens for a long time and are over 30 years old. Symptoms of this disease are dry eyes, irritation and burning, tears, eye fatigue and pain. One can easily see how this disease has the potential to drastically impact a large portion of the modern world’s population. Here is where the combined efforts of ophthalmic disease detection and the world of computer scientists and engineers can help.
By addressing challenges, imparting insights, and delineating future research pathways, it contributes substantially to the advancement of ophthalmic disease detection through sophisticated technological modalities.”
Mini Han Wang, author and researcher
There are seven facets to this AI-based disease detection. Timely intervention via the AI screening process and correct prognosis is the first part. The use of exhaustive surveys for DED through AI is another, and this is a supporting principle to ensure a level of thoroughness and trustworthiness throughout the process. A systematic approach follows, as well as the marriage of computer science and engineering with ophthalmology. Then, the standards for DED detection must be devised and upheld for future researchers and practitioners, which will naturally lead to the advancement of the field. Finally, all the research, methodologies and tools must be compiled so researchers, scholars and practitioners can have all of the information currently out there available to them.
While the ophthalmologists set the guidelines regarding the framework of the disease and flags for diagnosis, the AI does a lot of the heavy lifting. Ideally, this AI would use images and videos taken from a user’s cell phone to help reach users across the world. The AI can then utilize these images, as well as risk factors in the patient’s life, to make a smart and well-informed prognosis. Further, AI continuously learns and can help propel research forward by contributing to predictive models for DED.
The use of AI detection for DED holds a lot of promise, especially considering the risk factors are often normal activities in many people’s everyday lives. To make the detection methods accessible enough and accurate enough, further research needs to be done.
“However, there are still challenges for engineers to select the diagnostic standards and combinations of different types of datasets. By using trustworthy algorithms, images and videos captured from phones for accessibility purposes, a holistic approach to healthcare for early screening is possible,” said Wang.
With continued testing and collaboration between engineers and ophthalmologists, there is great potential for this method of testing to be useful in contributing to early screening of DED and subsequent therapeutic actions taken for the patient to reduce a worsening condition or to recover some quality of life.
Mini Han Wang and Xiangrong Yu of the Zhuhai People’s Hospital with Mini Han Wang also of the Department of Ophthalmology and Visual Sciences at the Chinese University of Hong Kong, The Faculty of Data Sciences at City University of Macau and the Department of big data at the Zhuhai Institute of Advanced Technology at the Chinese Academy of Sciences, Lumin Xing of the First Affiliated Hospital of Shandong First Medical University, Yi Pan of the Shenzhen Institute of Advanced Technology Chinese Academy of Sciences, Feng Gu of the College of Staten Island at the City University of New York, Junbin Fang at the Department of Optoelectronic Engineering at Jinan University, Chi Pui Pang, Kelvin KL Chong, Carol Yim-Lui Cheung and Xulin Liao of the Department of Ophthalmology and Visual Sciences at The Chinese University of Hong Kong, Xiaoxiao Fang with the Zhuhai Aier Eye Hospital, Jie Yang of the College of Artificial Intelligence at Chongqing Industry and Trade Polytechnic, Ruoyu Zhou and Wenjian Liu with the Faculty of Data Science at City University of Macao, Xiaoshu Zhou with the Centre for Science and Technology Exchange and Cooperation between China and Portuguese-Speaking Countries, and Fengling Wang with the School of Artificial Intelligence at Hezhou Univeristy contributed to this research.
The National Natural Science Foundation of China Natural, the Shenzhen Key Laboratory of Intelligent Bioinformatics, the Shenzhen Science and Technology Program, the Guangdong Basic and Applied Basic Research Foundation, the Zhuhai Technology and Research Foundation, the Project of Humanities and Social Science of MOE, the Science and Technology Research Program of Chongqing Municipal Education Commission and the Natural Science Foundation of Chongqing China made this research possible.
Source:
Journal reference:
Wang, M. H., et al. (2024) AI-Based Advanced Approaches and Dry Eye Disease Detection Based on Multi-Source Evidence: Cases, Applications, Issues, and Future Directions. Big Data Mining and Analytics. doi.org/10.26599/BDMA.2023.9020024.
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Variability shown across patient characteristics
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In a recent study published in the BMC Medicine, a group of researchers identified the factors influencing the variability in depression prevalence among chronic pain sufferers and developed clinical prediction models for estimating depression likelihood in this group.
Study: Variability in the prevalence of depression among adults with chronic pain: UK Biobank analysis through clinical prediction models. Image Credit: fizkes/Shutterstock.comBackground
Chronic pain is a major global disability cause, affecting over 30% of the population and often coexisting with depression, which disables roughly 5% of adults worldwide. The relationship between chronic pain and depression is well-established; each condition has the potential to worsen the other.
Despite this, the prevalence of depression among those with chronic pain is variable, with estimates ranging from 15% to 85%, influenced by differences in depression definitions, pain severity, and demographic factors such as gender, additional health conditions, and socioeconomic status.
Further research is needed to refine the understanding of the complex relationship between chronic pain and depression and to enhance the accuracy and applicability of clinical prediction models across diverse populations.
About the study
The present study utilized data from the United Kingdom (UK) Biobank. It focused on participants who completed the “online mental health self-assessment” between 2016 and 2017 and the “experience of pain” questionnaire from 2019 to 2020.
The UK Biobank’s large dataset, combined with detailed surveys on pain and mental health, provided a unique platform for exploring chronic pain and its association with depression.
The “experience of pain” questionnaire was selected over the baseline data due to its more extensive array of pain types and additional variables related to pain characteristics.
Chronic pain was defined using criteria from the International Classification of Diseases 11th Revision, categorizing it as either widespread or regional based on participant responses. This distinction was important because the nature and location of pain are significant factors in the prevalence of depression among those affected.
Additionally, the study considered multisite pain and its impact on mood disorders, integrating questions about the most bothersome pain areas and the nature of the pain (neuropathic or not).
Depression was defined using a dual approach: a professional diagnosis linked from healthcare records and self-reported symptoms through a validated short form of the Composite International Diagnostic Interview.
This method aimed to capture a comprehensive view of participants’ lifetime mental health history, which is crucial for understanding fluctuating conditions like depression.
The study also used the Patient Health Questionnaire to assess current depression among participants, adding another layer to the analysis. Statistical analyses included logistic regression models developed to estimate depression probability among chronic pain sufferers.
The models integrated a range of predictors, including demographic details, pain characteristics, and lifestyle factors, highlighting the complexity of chronic pain’s impact on mental health.
Study results
The present comprehensive analysis involved 24,405 UK Biobank participants with chronic pain. Among these individuals, 3.7% reported present depression, 32.6% had a lifetime history of depression, 21.8% exhibited subthreshold depressive symptoms throughout their lives, and 45.6% had no lifetime history of depression.
The cohort predominantly comprised white individuals (97.1%) with an average age of 64.1 years, highlighting the need to consider a variety of demographic factors in understanding depression among those with chronic pain.
For those experiencing chronic widespread pain, 45.7% reported a lifetime history of depression, with prevalence rates varying significantly from 25.0% to 66.7% based on individual characteristics.
A prediction model incorporating variables such as age, body mass index (BMI), smoking status, physical activity, and medical history showed moderate discrimination and good calibration, suggesting its utility in clinical settings. Notably, age, gender, and BMI emerged as significant predictors of a lifetime history of depression.
Similarly, among those with chronic regional pain, 30.2% had a lifetime history of depression. The model for this group included predictors like the nature of pain and regular opioid use, and it demonstrated similar levels of discrimination and calibration.
Key predictors again included age, gender, and the specific characteristics of pain, which significantly influenced depression outcomes.
The study also assessed present depression, finding that 10.5% of individuals with chronic widespread pain and 2.5% of those with chronic regional pain were currently depressed.
Different predictors were relevant for these outcomes, with smoking status, physical activity, and comorbid conditions like chronic kidney disease playing significant roles. Models developed for current depression demonstrated moderate to high levels of discrimination and good calibration, indicating their potential reliability.
Additional analyses confirmed that the prediction models were generally robust across different types of regional pain, although some categories, like stomach and chest pain, showed slightly lower predictive accuracy.
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