[The efficacy of magnetic transcranial stimulation in treating treatment-resistant or prolonged depression in a clinical sample].

INTRODUCTION: Depression is a common, serious and often chronic disorder and one of the leading causes of disability worldwide. The annual prevalence of depression is 5-10%, twice as high among women as men and the lifetime prevalence is at least 20%. Up to a third of depressed individuals meet criteria for treatment-resistant depression, where two antidepressants have been tried for at least 6 weeks each at therapeutic doses. As of January 2022 transcranial magnetic stimulation for adults with treatment-resistant depression that has not responded to other forms of treatment has been available by a service that is part of Primary Health Care of the Capital Area in Iceland. METHODS: This is a retrospective cohort study where participants completed a course of magnetic transcranial treatment for depression in the years 2022 and 2023. Two validated self-rating measures were used to assess depression. Information on previous treatment approaches for depression was collected from electronic health records. RESULTS: 104 individuals completed the treatment in these first two years, 60,6% women. Most had unipolar depression (86,5%), but a small subgroup had bipolar depression (13,5%). The proportion of responders varied according to the measures used, 36,1% and 45,7%, respectively, and the same was true for remission where the proportions were 12,4% and 31,5%, respectively, higher for the longer inventory. The drop-out rate was only 12,5% and no serious adverse events were reported during the treatment. CONCLUSION: The results support that magnetic transcranial stimulation, as provided by this service is effective in treating treatment-resistant or longstanding depression in a real life clinical setting and the low drop-out rate supports that the treatment is generally very well tolerated.

Diagnostic accuracy of statistical pattern recognition of electroencephalogram registration in evaluation of cognitive impairment and dementia.

BACKGROUND: There is still a need for simple, noninvasive, and inexpensive methods to diagnose the causes of cognitive impairment and dementia. In this study, contemporary statistical methods were used to classify the clinical cases of cognitive impairment based on electroencephalograms (EEG). METHODS: An EEG database was established from seven different groups of subjects with cognitive impairment and dementia as well as healthy controls. A classifier was created for each possible pair of groups using statistical pattern recognition (SPR). RESULTS: A good-to-excellent separation was found when differentiating cases of degenerative disorders from controls, vascular disorders, and depression but this was less so when the likelihood of comorbidity was high. CONCLUSIONS: Using EEG with SPR seems to be a reliable method for diagnosing the causes of cognitive impairment and dementia, but comorbidity must be taken into account.