The American journal of medicine
-
Alongside the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic, the number of patients with persistent symptoms following acute infection with SARS-CoV-2 is of concern. It is estimated that at least 65 million people worldwide meet criteria for what the World Health Organization (WHO) defines as "post-COVID-19 condition" - a multisystem disease comprising a wide range of symptoms. Effective treatments are lacking. In the present review, we aim to summarize the current evidence for the effectiveness of non-invasive or minimally invasive brain stimulation techniques in reducing symptoms of post-COVID-19. ⋯ Existing studies report first promising results, illustrating improvement in clinical outcome parameters. Yet, the mechanistic understanding of post-COVID-19 and how brain stimulation techniques may be benefitial are limited. Directions for future research in the field are discussed.
-
Internal tremors and vibrations are symptoms previously described as part of neurologic disorders but not fully described as a part of long COVID. This study compared pre-pandemic comorbidities, new-onset conditions, and long COVID symptoms between people with internal tremors and vibrations as part of their long COVID symptoms and people with long COVID but without these symptoms. ⋯ Among people with long COVID, those with internal tremors and vibrations had different conditions and symptoms and worse health status compared with others who had long COVID without these symptoms.
-
The purpose of this study was to examine the multimorbidity burden of clinical trial participants and assess its association with treatment response. ⋯ These trials were mainly composed of patient populations with CCI scores ≤4. Despite this, biologically plausible treatment interactions were commonly suggested. These results are hypothesis generating; confirmation of results would require larger studies or studies targeted specifically toward patients with higher levels of multimorbidity.
-
Adults presenting with a neutrophil-predominant leukocytosis (white cell count >50,000/μL) often necessitate urgent medical management. These patients are diagnosed with either acute presentations of chronic myeloid malignancies or leukemoid reactions, yet accurate models to distinguish between these entities do not exist. We used demographic and lab data to build a machine learning model capable of discriminating between these diagnoses. ⋯ These findings need to be validated but fill an unmet need for timely and accurate diagnosis in the setting of profound, neutrophil-predominant leukocytosis and support the use of predictive models as a means to improve patient outcomes.