From the Editor

He’s tried several medications, but still struggles with his depression. The story is too familiar. Transcranial direct current stimulation (tDCS) is an option, and increasingly the focus of research. With relatively few side effects and the possibility of doing the treatment at home, the advantages of tDCS are clear.

But how do patients taking antidepressants respond? In the first selection, from the pages of The Lancet, Dr. Gerrit Burkhardt (of the University of Munich) and his co-authors report the findings of an impressive study, with a comparison against sham treatment, across eight sites, and involving triple blinding. “Active tDCS was not superior to sham stimulation during a 6-week period. Our trial does not support the efficacy of tDCS as an additional treatment to SSRIs in adults with MDD.” We consider the paper, an accompanying Comment, and the implications.

In the second selection, Joseph J. Palamar (of New York University) and his colleagues analyze data on US ketamine seizures in a Research Letter for JAMA Psychiatry. They view seizures as a measure of recreational and nonmedical use, and conclude: “These data suggest increasing availability of illicit ketamine.”

And in this week’s third selection, Dr. Daniela J. Lamas (of Harvard University), an internist, writes about AI for The New York Times. In thinking about medical practice, she sees artificial intelligence doing more and more, and ultimately helping with diagnosis. She also sees trade-offs. Still, she concludes: “Beyond saving us time, the intelligence in A.I. – if used well – could make us better at our jobs.”

Note that there will be no Reading next week.

DG

Selection 1: “Transcranial direct current stimulation as an additional treatment to selective serotonin reuptake inhibitors in adults with major depressive disorder in Germany (DepressionDC): a triple-blind, randomised, sham-controlled, multicentre trial” 

Gerrit Burkhardt, Ulrike Kumpf, Alexander Crispin, et al

The Lancet, 3 July 2023  Online First

Major depressive disorder (MDD) affects approximately 5% of adults worldwide. Pharmacological treatment is commonly initiated with a selective serotonin reuptake inhibitor (SSRI), but about 50% of patients do not respond to the first SSRI and about 30% do not respond to second-line medication or psychotherapy. Therefore, effective and tolerable new treatments with high scalability are urgently needed to improve patient outcomes. 

Non-invasive brain stimulation techniques, including repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS), aim to alleviate the symptoms of MDD by neurophysiologically modulating prefrontal cortex connectivity. Multicentre randomised controlled trials (RCTs) have led to the introduction of rTMS for the clinical treatment of MDD in adults. More recently, tDCS has been proposed as another non-invasive brain stimulation intervention in MDD because it is less costly than rTMS and is potentially scalable for multiple settings, including treatment at home. Common tDCS protocols for daily treatment have been developed, as have more complex concurrent tDCS and cognitive training paradigms and tDCS and cognitive behavioural therapy paradigms. Meta-analyses indicate that tDCS elicits low-to-moderate antidepressant effects, but these analyses are mainly based on single-centre studies and include combinations with cognitive training or psychotherapy, patients with or without concomitant medication, and patients with bipolar depression… To our knowledge, no multicentre RCTs have investigated tDCS in patients with MDD and stable SSRI medication.

So begins a paper by Burkhardt et al.

Here’s what they did:

  • They conducted a trial that was “triple-blind, randomised, and sham-controlled and conducted at eight hospitals in Germany.”
  • Inclusion criteria: “aged 18–65 years if they had a diagnosis of MDD, a score of at least 15 on the Hamilton Depression Rating Scale, no response to at least one antidepressant trial in their current depressive episode, and treatment with an SSRI at a stable dose for at least 4 weeks before inclusion.”
  • Participants were “allocated (1:1) by fixed-blocked randomisation to receive either 30 min of 2 mA bifrontal tDCS every weekday for 4 weeks, then two tDCS sessions per week for 2 weeks [for a total of 24 treatments], or sham stimulation at the same intervals.”
  • Primary outcome: “change on the MADRS at week 6, analysed in the intention-to-treat population.”
  • Statistical analyses were done.

Here’s what they found:

  • 160 were enrolled and randomly assigned to treatment, with 150 proceeding after six withdrew and 4 were deemed ineligible.
  • Demographics. 59% of participants were female with a median age of 40.1 years. 98% identified as White, 1% as Asian, 1% as Hispanic.
  • Depression. “The mean change in MADRS score from baseline to week 6 was –8.2… in the active tDCS group and –8.0… in the sham tDCS group (difference 0.3…), indicating no significant difference between groups.” 
  • Secondary outcomes. “No significant differences in secondary outcomes were found between groups.”
  • Adverse events. “Significantly more participants had one or more mild adverse events in the active tDCS group (60%) than in the sham tDCS group (43%).”

A few thoughts:

1. This is an impressive paper. The study is well designed, blinded, and involving multiple sites. And, yes, it’s published in a very big journal.

2. The main finding in a sentence: “In this study, we found no significant difference in the change in MADRS scores in patients with MDD at week 6 after either active tDCS or sham tDCS.”

3. The paper runs with a Comment by Drs. Daphne Voineskos and Daniel M. Blumberger (both of the University of Toronto). In “Transcranial direct current stimulation as a treatment for major depressive disorder,” they praise the trial as “carefully designed, including many best-practice approaches for neurostimulation trials.”

Daphne Voineskos

The authors note several “remaining unknowns” including about the placebo effect. “There should be a better understanding of the relatively large placebo response to sham tDCS seen in this and other neurostimulation trials given the overlapping neurobiology of placebo effects and depression. Although masking integrity was assessed, other factors that could help explain the placebo response (eg, measures of expectancy) were not assessed, as the authors highlight.”

They also note the potential of tDCS – though in a different population and one that hasn’t proven unresponsive to multiple medication trials.

“One advantage of tDCS is its portability, which could revolutionise its therapeutic potential. The safety, reliability, and efficacy of at-home tDCS for people with MDD has been extensively tested. However, Burkhardt and colleagues did not employ an at-home design, instead providing treatment in standard settings at each hospital. tDCS is a brain stimulation modality that can be delivered outside of health-care settings and in combination with other therapeutic interventions, including cognitive training or psychotherapy… The at-home delivery potential of tDCS emphasises the need to study its efficacy in antidepressant-naive populations as a first-line treatment.”

The Comment can be found here:

https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(23)00822-X/fulltext

4. That last point is particularly thoughtful. Is there a role for tDCS with some patients – especially given its convenience?

The full Lancet paper can be found here:

https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(23)00640-2/fulltext

Selection 2: “Trends in Illicit Ketamine Seizures in the US From 2017 to 2022”

Joseph J. Palamar, Samuel T. Wilkinson, Thomas H. Carr, et al

JAMA Psychiatry, 24 May 2023

Ketamine is a dissociative anesthetic that has been used in medicine for a half century, with recent trials demonstrating efficacy of esketamine (an enantiomer of ketamine) for treatment-resistant depression… It is unclear whether extensive media coverage about the therapeutic benefits of ketamine and esketamine has influenced nonmedical or recreational use. In this cross-sectional study, we investigated seizures of illicit ketamine in the US from 2017 through 2022 as a measure of availability of ketamine for nonmedical use.

So begins a Research Letter by Palamar et al.

Here’s what they did:

  • Data was examined from ketamine seizures in the US from January 2017 to December 2022. 
  • They drew from the data of the High Intensity Drug Trafficking Areas (HIDTA) program which assists federal, state, local, and tribal law enforcement agencies within areas in the US determined to be critical drug trafficking regions. 
  • Total number of seizures and total weight of seizures were calculated for each year both nationally and at the state level.

Here’s what they found:

  • “There were 873 ketamine seizures between 2017 and 2022, weighing a total of 1852.4 kg…”
  • “The highest numbers of seizures were reported in Tennessee (14.9%), Florida (12.9%), and California (8.4%); the greatest weight seized was also in Tennessee (844.1 kg), followed by Pennsylvania (154.3 kg) and New York (132.6 kg).” 
  • “The number of ketamine seizures in the US increased from 55 in 2017 to 247 to 2022… a 349.1% increase. The total weight of ketamine seized increased from 57.8 kg in 2017 to 703.3 kg in 2022… a 1116.4% increase.”

A few thoughts:

1. This is interesting data.

2. The authors see a connection with misuse. “Increases in the number and size of ketamine seizures suggest that availability of illicit ketamine increased from 2017 through 2022 and that nonmedical or recreational use may have increased.”

3. The authors note that ketamine is often distributed in powder form “which may increase the likelihood of adulteration or contamination with other drugs such as fentanyl.”

The full JAMA Psych Research Letter can be found here:

https://jamanetwork.com/journals/jamapsychiatry/article-abstract/2804864

Selection 3: “There’s One Hard Question My Fellow Doctors and I Will Need to Answer Soon”

Daniela J. Lamas

The New York Times, 6 July 2023

When faced with a particularly tough question on rounds during my intern year, I would run straight to the bathroom. There, I would flip through the medical reference book I carried in my pocket, find the answer and return to the group, ready to respond.

At the time, I believed that my job was to memorize, to know the most arcane of medical eponyms by heart. Surely an excellent clinician would not need to consult a book or a computer to diagnose a patient. Or so I thought then.

Not even two decades later, we find ourselves at the dawn of what many believe to be a new era in medicine, one in which artificial intelligence promises to write our notes, to communicate with patients, to offer diagnoses.”

So begins an essay by Dr. Lamas.

“The potential is dazzling.” But she notes complicated questions ahead: “Where does specialized expertise live? If the thought process to arrive at a diagnosis can be done by a computer ‘co-pilot,’ how does that change the practice of medicine, for doctors and for patients?”

She considers X-rays and ECGs. “One of the easiest ways to imagine using A.I. is when it comes to work that requires pattern recognition, such as reading X-rays. Even the best doctor may be less adept than a machine when it comes to recognizing complex patterns without bias.” She writes about the work of a Harvard internist and his team who use AI for ECGs. “[W]hen asked to predict age based on an ECG, the A.I. program would from time to time give an entirely incorrect response. At first, the researchers thought the machine simply wasn’t great at age prediction based on the ECG – until they realized that the machine was offering the ‘biological’ rather than chronological age, explained Dr. Lopez-Jimenez. Based on the patterns of the ECG alone, the A.I. program knew more about a patient’s aging than a clinician ever could.”

She notes other possible applications. “Some studies are using A.I. to try to diagnose a patient’s condition based on voice alone. Researchers promote the possibility of A.I. to speed drug discovery.”

Could AI help with diagnosis? “Dr. Adam Rodman, an internist at Beth Israel Deaconess Hospital in Boston and a historian, found that the majority of his medical students are using Chat GPT already, to help them on rounds or even to help predict test questions. Curious about how A.I. would perform on tough medical cases, Dr. Rodman gave the notoriously challenging New England Journal of Medicine weekly case – and found that the program offered the correct diagnosis in a list of possible diagnoses just over 60 percent of the time.”

She sees some advantages. AI could help with monotonous tasks, like note writing. But she does caution that things may be lost. “After all, notes are not simply drudgery; they also represent a time to take stock, to review the data and reflect on what comes next for our patients. If we offload that work, we surely gain time, but maybe there are trade-offs, too.”

And, in terms of diagnosis, she favours a hybrid approach. “Maybe the diagnoses offered by A.I. will become an adjunct to our own thought processes, not replacing us but allowing us all the tools to become better. Particularly for those working in settings with limited specialists for consultation, A.I. could bring everyone up to the same standard. At the same time, patients will be using these technologies, asking questions and coming to us with potential answers. This democratizing of information is already happening and will only increase.”

She concludes that “A.I. can be part of that process, just one more tool that we use, but it will never replace a hand at the bedside, eye contact, understanding – what it is to be a doctor.”

A few thoughts:

1. This is a good essay. Her conclusion – that AI will assist human clinicians – seems reasonable. (No need to re-train just yet.)

2. It’s striking that ChatGPT can get a correct diagnosis 60% of the time on cases of the week. Imagine what AI will be able to do in 5 or 10 years.

3. The author is an intensivist and focuses on physical medicine. Of course, her arguments would apply to mental health. AI could help with complex presentations for mental health disorders. With access to care being so challenging, could AI also help with triage and identification of problems? Last week, Nicole Ireland of Canadian Press reported on the use of AI by Kids Help Phone. “The planned AI will be able to recognize key words and speech patterns from young people who reach out to Kids Help Phone to help busy counsellors zero in on what they need and tailor their support accordingly.” That article can be found here:

https://www.theglobeandmail.com/canada/article-kids-help-phone-seeking-help-from-ai-tech-to-meet-demand-for-mental/

The full NYT essay can be found here:

https://www.nytimes.com/2023/07/06/opinion/artificial-intelligence-medicine-healthcare.html

Reading of the Week. Every week I pick articles and papers from the world of Psychiatry.