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April 24, 2024
Are attention-deficit/hyperactivity disorder (ADHD) medications associated with risk of cardiovascular disease (CVD)?
An international study team has just explored this question with a meta-analysis of nineteen studies with a total of almost four million participants of all ages. It included 3,931,532 participants from six countries or regions: United States, South Korea, Canada, Denmark, Spain, and Hong Kong.
Overall, using the entire data set, it found no significant association between any ADHD medication use and any cardiovascular event.
The same held true when breaking this down by children and adolescents (twelve studies with over 1.7 million participants), young and middle-aged adults (seven studies with over 850,000 participants), and older adults (six studies with over a quarter million participants).
The team then compared the data for stimulant medications with data for non-stimulant medications. A meta-analysis of 17 studies with over 3.8 million participants found no significant association between stimulant medications and cardiovascular risk. Similarly, a meta-analysis of three studies with over 670,000 participants found no significant association between non-stimulant medications and cardiovascular risk.
Distinguishing between types of cardiovascular risk made no difference. For instance, a meta-analysis of nine studies with over 900,000 participants found no effect of stimulant medications on risk of myocardial infarction (heart attack), and a meta-analysis of six studies, also with over 900,000 participants, found no effect of stimulant medications on risk of cerebrovascular disease, including stroke, brain aneurysm, brain bleed, and carotid artery disease. A meta-analysis of eight studies with over 1.1 million participants did find an increase in the occurrence of cardiac arrest and tachyarrhythmias (racing heart rate accompanied by arrhythmias), but it was not statistically significant.
A meta-analysis of eleven studies with over 3.1 million persons with no prior history of cardiovascular disease found absolutely no effect of ADHD medications on subsequent risk for any cardiovascular event. Another meta-analysis, of eight studies encompassing over 1.8 million individuals with a prior history of cardiovascular disease, reported a higher rate of subsequent occurrence, but it was not considered statistically significant.
The team concluded, “Overall, our meta-analysis provides reassuring data on the putative cardiovascular risk with ADHD medications.” An international team of researchers recently investigated whether medications for attention-deficit/hyperactivity disorder (ADHD) are linked to an increased risk of cardiovascular disease (CVD). They conducted a comprehensive review, known as a meta-analysis, which included 19 studies with nearly four million participants from six countries or regions: the United States, South Korea, Canada, Denmark, Spain, and Hong Kong.
The findings from the entire data set showed no significant link between the use of any ADHD medications and the occurrence of cardiovascular events. This lack of association was consistent across all age groups: children and adolescents (12 studies with over 1.7 million participants), young and middle-aged adults (7 studies with over 850,000 participants), and older adults (6 studies with over 250,000 participants).
The researchers also compared the effects of stimulant medications against non-stimulant medications on cardiovascular risk. Both categories showed no significant risks in a meta-analysis of 17 studies with more than 3.8 million participants for stimulants, and three studies with over 670,000 participants for non-stimulants.
Further analysis differentiated between types of cardiovascular risks, such as myocardial infarction (heart attack) and cerebrovascular diseases (like stroke, brain aneurysm, and carotid artery disease). Again, stimulant medications showed no significant impact on these conditions in studies involving over 900,000 participants each. However, a review of eight studies with over 1.1 million participants suggested a slight increase in incidents of cardiac arrest and tachyarrhythmias (a racing heart rate with irregular rhythms), but these findings were not statistically significant.
Additionally, an analysis of 11 studies involving more than 3.1 million people without a prior history of cardiovascular disease found no effect of ADHD medications on the risk of developing cardiovascular events. Likewise, an analysis of eight studies with over 1.8 million individuals who had a history of cardiovascular disease showed a higher occurrence rate of events, but this increase was also not statistically significant.
The conclusion of the research team was clear: the data is reassuring and does not suggest a substantial cardiovascular risk associated with ADHD medications. Keep in mind that this reflects current standards of care. Most guidelines call for monitoring of pulse and blood pressure during treatment so that adverse cardiovascular outcomes can be avoided.
Le Zhang, Honghui Yao, Lin Li, Ebba Du Rietz, Pontus Andell, Miguel Garcia-Argibay, Brian M. D’Onofrio, Samuele Cortese, Henrik Larsson, Zheng Chang, “Risk of Cardiovascular Diseases Associated With Medications Used in Attention-Deficit/Hyperactivity Disorder: A Systematic Review and Meta-analysis,” JAMA Network Open (2022) 5(11), e2243597, https://doi.org/10.1001/jamanetworkopen.2022.43597.
Methylphenidate, a psychostimulant, is among the drugs most frequently prescribed to children with ADHD.
Using magnetic resonance imaging(MRI), studies have shown that as children mature, those with ADHD differ from controls in developing regionally thinner cortices (the folded outer layer of the cerebrum that is essential to rational thought) and smaller lower basal ganglia(structures linked to the thalamus in the base of the brain and involved in the coordination of movement). The cortical differences were found in the right medial frontal motor region, the left middle/inferior frontal gyrus, and the right posterior parieto-occipital region in children with ADHD who were not taking psychostimulants.
A Dutch/Norwegian team of researchers conducted a randomized, double-blind, placebo-controlled trial with 96 males recruited from Dutch clinical programs. 48 were boys aged 10-12 years, and 47 were men between the ages of 23 and 40. None had previously been on methylphenidate. There were no significant differences in baseline age, ADHD symptom severity, estimated intelligence quotient, the proportion of right-handedness, or region of interest brain characteristics between the placebo and medication groups.
The trial was carried out during the standard 17-week waiting list time for evaluation and treatment to begin so that those receiving a placebo during the trial would not ultimately be at a disadvantage. The same MRI scanner was used for all measurements, both before and after treatment.
Among the boys, the methylphenidate group showed increased thickness in the right medial cortex, while the placebo group showed cortical thinning. In adults, both groups showed cortical thinning. When converted into an estimated mean rate of change in cortical thickness for the right medial cortex, boys taking methylphenidate could expect to lose about 0.01 mm per year, versus about 0.14 mm for boys not on methylphenidate.
In the right posterior cortex, scans also showed reduced thinning in the methylphenidate treatment group, though to a lesser extent. But there was no reduced thinning in the left frontal cortex.
The authors noted several limitations. The sample size was small. Second, "because we did not detect significant relationships between changes in cortical [regions of interest] and changes in symptom severity, the functional significance remains uncertain." Third, the follow-up period was relatively short, not allowing any assessment of the longer-term effects of the medication. Fourth, the differences in effects on the three brain regions examined were uneven, contrary to what had been expected from previous studies. They recommended replication with larger groups and longer follow-ups.
A Chinese research team performed two types of meta-analyses to compare the risk of suicide for ADHD patients taking ADHD medication as opposed to those not taking medication.
The first type of meta-analysis combined six large population studies with a total of over 4.7 million participants. These were located on three continents - Europe, Asia, and North America - and more specifically Sweden, England, Taiwan, and the United States.
The risk of suicide among those taking medication was found to be about a quarter less than for unmediated individuals, though the results were barely significant at the 95 percent confidence level (p = 0.49, just a sliver below the p = 0.5 cutoff point). There were no significant differences between males and females, except that looking only at males or females reduced sample size and made results non-significant.
Differentiating between patients receiving stimulant and non-stimulant medications produced divergent outcomes. A meta-analysis of four population studies covering almost 900,000 individuals found stimulant medications to be associated with a 28 percent reduced risk of suicide. On the other hand, a meta-analysis of three studies with over 62,000 individuals found no significant difference in suicide risk for non-stimulant medications. The benefit, therefore, seems limited to stimulant medication.
The second type of meta-analysis combined three within-individual studies with over 3.9 million persons in the United States, China, and Sweden. The risk of suicide among those taking medication was found to be almost a third less than for unmediated individuals, though the results were again barely significant at the 95 percent confidence level (p =0.49, just a sliver below the p = 0.5 cutoff point). Once again, there were no significant differences between males and females, except that looking only at males or females reduced the sample size and made results non-significant.
Differentiating between patients receiving stimulant and non-stimulant medications once again produced divergent outcomes. Meta-analysis of the same three studies found a 25 percent reduced risk of suicide among those taking stimulant medications. But as in the population studies, a meta-analysis of two studies with over 3.9 million persons found no reduction in risk among those taking non-stimulant medications.
A further meta-analysis of two studies with 3.9 million persons found no reduction in suicide risk among persons taking ADHD medications for 90 days or less, "revealing the importance of duration and adherence to medication in all individuals prescribed stimulants for ADHD."
The authors concluded, "exposure to non-stimulants is not associated with a higher risk of suicide attempts. However, a lower risk of suicide attempts was observed for stimulant drugs. However, the results must be interpreted with caution due to the evidence of heterogeneity ..."
For centuries, we’ve called the eyes the "windows to the soul," but for modern neurologists, they are quite literally a window into the brain. The retina and the central nervous system share the same embryonic origins, developing from the same neural tissue in the womb. Because of this deep biological connection, the back of your eye acts as a non-invasive map of your brain's health, displaying a complex web of nerves and blood vessels that can (theoretically!) mirror certain neurodevelopmental conditions.
Recently, a buzz rippled through the mental health community when a study published in partnership with Seoul National University Bundang Hospital claimed a massive breakthrough. Researchers developed an Artificial Intelligence (AI) model that could screen children for Attention-Deficit/Hyperactivity Disorder (ADHD) using nothing more than a simple retinal photograph. The study, which prospectively recruited children from Severance Hospital and Eunpyeong St. Mary’s Hospital, produced results that were staggering: the AI reportedly achieved an accuracy rate of 96.9%!
In the world of medical testing, scientists use a metric called AUROC (Area Under the Receiver Operating Characteristic) to measure how well a test works.
An AUROC of 96.9% is a near-perfect score, suggesting a tool is ready for immediate, real-world deployment. While headlines promised a revolution in mental health screening, a deeper look into this research and the study’s design has exposed that this 96.9% AUROC was more likely evidence of a flawed methodology rather than a biological reality.
To build their screening tool, researchers analyzed over 1,100 retinal images using a digital pipeline called AutoMorph and a machine-learning model known as XGBoost. The AI was trained to hunt for physical signals of the "Dopamine Connection." Dopamine is the primary neurotransmitter involved in ADHD, but it is also essential to the eye. It regulates synaptic formation, retinal blood flow, and vascular endothelial regulation. Because dopamine dysregulation influences how blood vessels grow and remodel, the study hypothesized that an ADHD brain would leave a unique "fingerprint" on the retinal vasculature, resulting in denser, thicker vessel structures.
On paper, the logic was sound: use AI to spot the subtle vascular remodeling caused by dopaminergic shifts. But a closer look at the investigation revealed that the AI wasn't just spotting ADHD; it was over-indexing on technical noise.
The most significant "smoking gun" flagged by critics is a massive temporal mismatch. In other words, there was a severe disparity in the timeframes and conditions under which the retinal images for the two comparison groups were collected. For an AI to learn a biological condition, it must compare groups under identical technical conditions. Instead, this study created a time-traveling dataset:
A scientific study is only as reliable as its control group. The control in any experiment acts as a baseline against which the study group is compared. In this case, the control group should be composed of children without any neurodevelopmental disorders, or of “typically developing” children.
In this study, the control group wasn't composed of healthy children from the community. Instead, they were patients visiting a tertiary ophthalmology clinic. Children visiting a specialist eye hospital are rarely "typical." They are there because they have symptomatic eye issues. This introduced a massive selection bias involving three major confounders:
When training AI, you must never allow the "test questions" to leak into the "study material." The researchers, however, committed a fundamental violation of machine learning hygiene known as Eye-to-Eye Data Leakage. The study split the data by the eye rather than by the participant.
Human eyes are highly correlated; the left eye is a near-mirror of the right. If a child's left eye was used for training and their right eye was used for testing, the AI was effectively "cheating." Instead of learning the general traits of ADHD, the model was potentially memorizing individuals. This error artificially balloons accuracy metrics.
The true test of medical AI is diagnostic specificity, or differential diagnosis. This refers to the ability to tell one condition apart from another. While the model claimed 96.9% accuracy against a flawed control group, its performance collapsed when faced with real-world complexity.
When the researchers asked the AI to differentiate between ADHD and Autism Spectrum Disorder (ASD), the accuracy plummeted to a poor 63% AUROC. In real-world clinical settings, an accuracy of 63% is dangerously close to a 50% coin flip. Since ADHD frequently co-occurs with ASD, anxiety, or intellectual disabilities, an AI that cannot handle these "clinical differentials" is functionally useless in a doctor's office. The failure at this stage proves the model was likely detecting technical quirks of the dataset rather than a unique biological marker for ADHD.
To move from the lab to the clinic, we must establish a foundation built on rigor rather than high-speed data scraping. Moving forward, we must demand these 3 Pillars of Trusted Medical AI :
The dream of a quick eye scan to diagnose ADHD is not dead, but it must be rescued from "fast science" shortcuts and buzzy headlines.
Background:
One of the more persistent concerns among parents of children with ADHD is whether stimulant medications will stunt their child's growth. A large Israeli cohort study now offers some of the most rigorous reassurance to date, and its methodology sets it apart from earlier research.
The question has long been complicated by a more fundamental uncertainty: do growth differences in children with ADHD stem from the condition itself, from stimulant treatment, or from factors present before any medication is ever prescribed? Without a clear answer, clinicians and families have faced a genuine dilemma when weighing the benefits of stimulant therapy against potential long-term physical costs.
Most previous studies compounded this difficulty by comparing group-average heights, which ignores the crucial variable of genetic potential. A child who is short relative to the general population may simply have short parents. Failing to account for this introduces systematic bias and can make medications appear more harmful than they are.
The Study:
The Israeli research team addressed this directly. Using health records from a nationwide provider, they assembled a retrospective cohort of children born between 1995 and 2003, following them through 2023. This amount of time was long enough for all participants to have reached adult stature (defined as 17 or older for females, 19 or older for males). Their sample included 5,671 children with untreated ADHD, 11,846 who received stimulant treatment, and 47,258 non-ADHD controls. Children who took stimulants for only one to two months, or who had chronic medical conditions requiring long-term medication, were excluded to avoid confounding the results.
Crucially, adult height was evaluated not against population norms but against each individual's expected height, calculated from parental heights using the Tanner-Goldstein-Whitehouse method, a standard approach for estimating genetic height potential via mid-parental height.
When the researchers compared adult heights across the three groups using analysis of variance (ANOVA), they did find statistically significant differences. But statistical significance, particularly in studies with tens of thousands of participants, does not automatically translate into clinical significance. The effect sizes were consistently very small, and the absolute differences were under one centimeter, which is a margin considered clinically negligible.
Their conclusion is measured but clear: after accounting for genetic growth potential, neither an ADHD diagnosis nor stimulant treatment was associated with meaningful reductions in adult height. The findings, they argue, support prioritizing behavioral and functional outcomes when making treatment decisions, since the risk of clinically significant height loss appears to be minimal.
The Take-Away:
For families navigating ADHD treatment, the practical implication is significant: concerns about permanent growth suppression, while understandable, should not be the primary driver of whether or how long a child receives stimulant therapy.
A recent meta-analysis examined how well cognitive behavioral therapy (CBT) improves not just symptoms, but everyday functioning and quality of life in adults with ADHD.
The Background:
ADHD in adults affects far more than attention or impulsivity. It often disrupts key areas of life:
These broad impacts highlight a key issue: reducing symptoms does not automatically translate into better day-to-day functioning.
CBT is a structured, skills-based therapy that helps people:
While both medication (especially stimulants) and CBT improve core ADHD symptoms, CBT is particularly aimed at improving real-world functioning.
The Study:
The researchers analyzed studies involving adults diagnosed with ADHD (or showing clinically significant symptoms). They included:
They focused specifically on outcomes beyond symptoms:
The Results:
1. Strongest Effects: Occupational functioning
CBT showed consistently strong improvements in work-related functioning compared to control groups, both immediately after treatment and at follow-up. This was the most robust finding across domains.
2. Moderate Improvement: Global Functional Impairment
CBT led to moderate improvements in overall daily functioning, with some evidence that gains persist over time. In studies tracking individuals over time, improvements were even stronger at follow-up.
3. Modest Gains: Social Relationships
CBT produced small to moderate improvements in social functioning. Benefits were present both after treatment and at follow-up, but were less pronounced than in work-related outcomes.
4. Limited Effects: Academic Functioning
There were moderate short-term gains when CBT was compared to control groups, but these did not persist at follow-up. Within-subject studies showed only small improvements overall.
5. Modest and Inconsistent Effects: Quality of Life
Improvements in quality of life were small when compared to control groups and often did not last. However, studies tracking individuals over time showed moderate improvements, suggesting some benefit that may not always show up clearly in between-group comparisons.
Overall, the findings suggest:
One notable nuance: CBT did not always outperform other active treatments (like medication or other therapies). This suggests that while CBT is effective, its benefits may partly overlap with broader therapeutic or support effects rather than relying on a single, unique mechanism.
The Take-Away:
CBT is a valuable, evidence-based treatment for adults with ADHD, especially for improving work functioning and overall daily life management. However, its impact on relationships, academic outcomes, and quality of life is more limited and less consistent, pointing to the need for more targeted or combined approaches in those areas.
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