Medical Bulletin 1/January/2024

Here are the top medical news of the day:

Brain health after COVID-19, pneumonia, heart attack, or critical illness

Impaired brain health after SARS-CoV-2 infection remains common 3 years after the outbreak of COVID-19, echoing impairments seen in previous virus pandemics. The long-term effects of COVID-19 are associated with more than 200 symptoms, affecting 65 million individuals worldwide.

A new study in JAMA Network including 345 participants, patients hospitalized for COVID-19 performed worse than healthy controls on cognitive, psychiatric, and neurological tests. However, compared with hospitalized controls matched for age, sex, and severity of disease, the impairment of brain health was similar.

Researchers conducted a prospective cohort study with matched controls was conducted at 2 academic hospitals in Copenhagen, Denmark. The case cohort comprised patients with COVID-19 hospitalized between March 1, 2020, and March 31, 2021. Control cohorts consisted of patients hospitalized for pneumonia, myocardial infarction, or non–COVID-19 intensive care–requiring illness between March 1, 2020, and June 30, 2021, and healthy age- and sex-matched individuals.

Out of 345 participants, including 120 patients with COVID-19 ( 70 men [58.3%]), 125 hospitalized controls ( 73 men [58.4%]), and 100 healthy controls (46 men [46.0%]). Patients with COVID-19 also performed worse than healthy controls during all other psychiatric and neurological assessments. However, except for executive dysfunction (Trail Making Test Part B; relative mean difference, 1.15), the brain health of patients with COVID-19 was not more impaired than among hospitalized control patients. These results remained consistent across various sensitivity analyses.

Researchers concluded that this prospective cohort study suggests that post–COVID-19 brain health was impaired but, overall, no more than the brain health of patients from 3 non–COVID-19 cohorts of comparable disease severity. Long-term associations with brain health might not be specific to COVID-19 but associated with overall illness severity and hospitalization. This information is important for putting understandable concerns about brain health after COVID-19 into perspective.

Reference: Peinkhofer C, Zarifkar P, Christensen RHB, et al. Brain Health After COVID-19, Pneumonia, Myocardial Infarction, or Critical Illness. JAMA Netw Open. 2023;6(12):e2349659. doi:10.1001/jamanetworkopen.2023.49659

New perspectives on treating gallbladder inflammation

Ischaemic cholecystitis is a form of gallbladder inflammation that occurs without gallstones or another form of external compression. It is caused by poor perfusion to the gallbladder tissue.

This new research is important because it helps to better understand the cause of ischaemic cholecystitis and to develop more effective treatments for this condition.

A team of researchers from the University of California, San Francisco, conducted a study investigating the cause of ischaemic cholecystitis. They found that the gallbladder is particularly susceptible to ischaemia because it receives its blood supply from a terminal artery, meaning that there is no other artery to supply blood to the gallbladder if this artery is blocked.

The researchers also found that ischaemic cholecystitis is more common in patients who are critically ill. This is because critically ill patients are often hypovolemic, meaning that they have low blood volume. This can lead to poor gallbladder perfusion, which can lead to inflammation.

These findings have important implications for the diagnosis and treatment of ischaemic cholecystitis. Because it is often difficult to diagnose, ischaemic cholecystitis can be misdiagnosed as another condition, such as sepsis or pancreatitis. This can lead to delays in treatment and poorer outcomes for patients.

The researchers also found that ischaemic cholecystitis is more likely to recur than obstructive cholecystitis. This means that patients with ischaemic cholecystitis are more likely to require surgery to remove their gallbladder.

Reference: New perspectives on treating gallbladder inflammation; eGastroenterology, DOI: 10.1136/egastro-2023-100004

Artificial intelligence as therapeutic support

The face is a mirror for a person’s emotional state. The interpretation of facial expressions as part of psychotherapy or psychotherapeutic research, for example, is a very effective way of characterizing how a person is feeling in that particular moment. Back in the 1970s, psychologist Paul Ekmann developed a standardized coding system to assign basic emotions such as happiness, disgust or sadness to a facial expression in an image or video sequence.

“Ekman’s system is very widespread, and represents a standard in psychological emotion research,” says Dr. Martin Steppan, psychologist at the Faculty of Psychology at the University of Basel.

But the process of analyzing and interpreting recorded facial expressions as part of research projects or psychotherapy is extremely time-consuming, which is why psychiatry specialists often use less reliable, indirect methods such as skin conductance measurements, which can also be a measure of emotional arousal.

“We wanted to find out whether AI systems can reliably determine the emotional states of patients in video recordings,” says Martin Steppan, who developed the study together with emeritus Professor Klaus Schmeck, Dr. Ronan Zimmermann and Dr. Lukas Fürer from the UPK. The researchers published their findings in the journal Psychopathology.

The researchers used freely available artificial neural networks that were trained in the detection of six basic emotions (happiness, surprise, anger, disgust, sadness and fear) using over 30,000 facial photos. This AI system then analyzed video data from therapy sessions with a total of 23 patients with borderline personality pathology at the Center for Scientific Computing at the University of Basel. The high-performance computer had to process over 950 hours of video recordings for this study.

The results were astonishing: statistical comparisons between the analysis of three trained therapists and the AI system showed a remarkable level of agreement. The AI system assessed the facial expressions as reliably as a human but was also able to detect even the most fleeting of emotions within the millisecond range, such as a brief smile or expression of disgust.

The results were astonishing: statistical comparisons between the analysis of three trained therapists and the AI system showed a remarkable level of agreement. The AI system assessed the facial expressions as reliably as a human but was also able to detect even the most fleeting of emotions within the millisecond range, such as a brief smile or expression of disgust.

Reference: Artificial intelligence as therapeutic support; Psychopathology, DOI: 10.1159/000534811