April 3, 2021

ADHD Treatment Decision Tree

If you've ever wondered how experts make treatment recommendations for patients with ADHD, take a look at this ADHD treatment decision tree that my colleagues and I constructed for our "Primer" about ADHD,http://rdcu.be/gYyV.  

Although a picture is worth a thousand words, keep in mind that this infographic only gives the bare bones of a complex process. That said, it is telling that one of the first questions an expert asks is if the patient has a comorbid condition that is more severe than ADHD. The general rule is to treat the more severe disorder first and after that condition has been stabilized plan a treatment approach for the other condition. Stimulants are typically the first-line treatment due to their greater efficacy compared with non-stimulants.

When considering any medication treatment for ADHD safety is the first concern, which is why medical contraindications to stimulants, such as cardiovascular issues or concerns about substance abuse, must be considered. For very young children (preschoolers) family behavior therapy is typically used before medication. Clinicians also must deal with personal preferences.  Some parents and some adolescents and adults with ADHD simply don't want to take stimulant medications for the disorder. When that happens, clinicians should do their best to educate them about the costs and benefits of stimulant treatment.

If, as is the case for most patients, the doctor takes the stimulant arm of the decision tree, he or she must next decide if methylphenidate or amphetamine is more appropriate. Here there is very little guidance for doctors. Amphetamine compounds are a bit more effective, but can lead to greater side effects.  Genetic studies suggest that a person's genetic background provides some information about who will respond well to methylphenidate, but we are not yet able to make very accurate predictions. After choosing the type of stimulant, the doctor must next consider what duration of action is appropriate for each patient.

There is no simple rule here; the choice will depend upon the specific needs of each patient. Many children benefit from longer-acting medications to get them through school, homework, and late afternoon/evening social activities. Likewise for adults. But many patients prefer shorter-acting medications, especially as these can be used to target specific times of day and can also lower the burden of side effects.  

For patients taking down the non-stimulant arm of the decision tree, duration is not an issue but the patient and doctor must choose from among two classes of medications norepinephrine reuptake inhibitors or alpha-2-agonists. There are not a lot of good data to guide this decision but, again, genetics can be useful in some cases. Regardless of whether the first treatment is a stimulant or a non-stimulant, the patient's response must be closely monitored as there is no guarantee that the first choice of medication will work out well. In some cases, efficacy is low, or adverse events are high. Sometimes this can be fixed by changing the dose, and sometimes a trial of a new medication is indicated.

If you are a parent of a child with ADHD or an adult with ADHD, this trial-and-error approach can be frustrating. But don't lose hope. In the end, most ADHD patients find a dose and a medication that works for them. Last but not least, when medication leads to a partial response, even after adjusting doses and trying different medication types, doctors should consider referring the patient for a non-pharmacologic ADHD treatment.

You can read details about these in my other blogs, but here the main point is to find an evidence-based treatment. For children, the biggest evidence base is for behavioral family therapy. For adults, cognitive behavior therapy (CBT) is the best choice.  Except for preschoolers, the experts I worked with on this infographic did not recommend these therapies before medication treatment. The reason is that the medications are much more effective, and many non-pharmacologic treatments (such as CBT) have no data indicating they work well in the absence of medication.

Faraone, S.V. et al. (2015) Attention-deficit/hyperactivity disorder Nat. Rev. Dis.Primers doi:10.1038/nrdp.2015.20. http://rdcu.be/gYyV

Related posts

No items found.

Using Video Analysis and Machine Learning in ADHD Diagnosis

NEWS TUESDAY: Machine Learning and The Possible Future of Diagnosing ADHD

Typically, clinicians rely on both subjective and objective observations, patient interviews and questionnaires, as well as reports from family and (in the case of children) parents and teachers, in order to diagnose ADHD. 

A group of researchers are aiming to find a diagnostic test that is purely objective and utilizes recent technological advancements. The method they developed involves analyzing videos of children in outpatient settings, focusing on their movements. The study included 96 children, half of whom had ADHD and half who did not.

How It Works

  1. Video Recording: Children were recorded during their outpatient visits.
  2. Skeleton Detection: Using a tool called OpenPose, the researchers detected and tracked the children's skeletons (essentially a map of their body's movements) in the videos.
  3. Movement Analysis: The researchers analyzed these movements, looking at 11 different movement features. They specifically focused on the angles of different body parts and how much they moved.
  4. Machine Learning: Six different machine learning models were used to see which movement features could best distinguish between children with ADHD and those without.

Key Findings

  • Movement Differences: Children with ADHD showed significantly more movement in all the features analyzed compared to children without ADHD.
  • Thigh Angle: The angle of the thigh was the most telling feature. On average, children with ADHD had a thigh angle of about 157.89 degrees, while those without ADHD had an angle of 15.37 degrees.
  • High Accuracy: Using thigh angle alone, the model could diagnose ADHD with 91.03% accuracy. It was very sensitive (90.25%) and specific (91.86%), meaning it correctly identified most children with ADHD and correctly recognized most children without it.

This new method could potentially provide a more objective way to diagnose ADHD, reducing the reliance on subjective observations and reports. It can help doctors make more accurate diagnoses, ensuring that those who need help get it and that those who don't aren't misdiagnosed.

May 28, 2024

Understanding Attention to Social Images in Children with ADHD and Autism

NEWS TUESDAY: Understanding Attention to Social Images in Children with ADHD and Autism

In the field of mental health, professionals often use a variety of tools to diagnose and understand neurodevelopmental disorders such as Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). One such tool is the Autism Diagnostic Observation Schedule (ADOS), which is specifically designed to help diagnose autism. However, the ADOS wasn't originally intended for children who have both autism and ADHD, though this comorbidity is not uncommon.

A recent study aimed to explore how children with ADHD, autism, or both, pay attention to social images, such as faces. The study focused on using eye-tracking technology to measure where children direct their gaze when viewing pictures, and how long they look at certain parts of the image. This is important because differences in visual attention can provide insights into the nature of these disorders.

The researchers included 84 children in their study, categorized into four groups: those with ASD, those with ADHD, those with both ASD and ADHD, and neurotypical (NT) children without these conditions. During the study, children were shown social scenes from the ADOS, and their eye movements were recorded. The ADOS assessment was administered afterward. To ensure that the results were not influenced by medications, children who were on stimulant medications for ADHD were asked to pause their medication temporarily.

The results of the study showed that children with ASD, whether they also had ADHD or not, tended to spend less time looking at faces compared to children with just ADHD or NT children. The severity of autism symptoms, measured by the Social Communication Questionnaire (SCQ), was associated with reduced attention to faces. Interestingly, ADHD symptom severity, measured by Conners' Rating Scales (CRS-3), did not correlate with how children looked at faces.

These findings suggest that measuring visual attention might be a valuable addition to the assessment process for ASD, especially in cases where ADHD is also present. The study indicates that if a child with ADHD shows reduced attention to faces, it might point to additional challenges related to autism. The researchers noted that more studies with larger groups of children are needed to confirm these findings, but the results are promising. They hope that such measures could eventually enhance diagnostic processes and help in managing the complexities of cases involving comorbidity of ADHD and ASD.

This research opens up the possibility of using eye-tracking as a supplementary diagnostic tool in the assessment of autism, providing a more nuanced understanding of how attentional differences in social settings are linked to ASD and ADHD.

May 14, 2024

NEW STUDY: RASopathies Influences on Neuroanatomical Variation in Children

NEW STUDY: RASopathies Influences on Neuroanatomical Variation in Children

This study investigates how certain genetic disorders, called RASopathies, affect the structure of the brain in children. RASopathies are conditions caused by mutations in a specific signaling pathway in the body. Two common RASopathies are Noonan syndrome (NS) and neurofibromatosis type 1 (NF1), both of which are linked to a higher risk of autism spectrum disorder (ASD) and attention deficit and hyperactivity disorder (ADHD).

The researchers analyzed brain scans of children with RASopathies (91 participants) and compared them to typically developing children (74 participants). They focused on three aspects of brain structure: surface area (SA), cortical thickness (CT), and subcortical volumes.

The results showed that children with RASopathies had both similarities and differences in their brain structure compared to typically developing children. They had increased SA in certain areas of the brain, like the precentral gyrus, but decreased SA in other regions, such as the occipital regions. Additionally, they had thinner CT in the precentral gyrus. However, the effects on subcortical volumes varied between the two RASopathies: children with NS had decreased volumes in certain structures like the striatum and thalamus, while children with NF1 had increased volumes in areas like the hippocampus, amygdala, and thalamus.

Overall, this study highlights how RASopathies can impact the development of the brain in children. The shared effects on SA and CT suggest a common influence of RASopathies on brain development, which could be important for developing targeted treatments in the future.

In summary, understanding how these genetic disorders affect the brain's structure can help researchers and healthcare professionals develop better treatments for affected children.

April 30, 2024