Case Report: Use of Bedside Handheld Ultrasound to Diagnose Finger Dislocation

Here we present the case of a 37-year-old male with a finger injury in which finger dislocation was suspected clinically. A bedside pocket ultrasound was performed using a water submersion technique, which identified a posterior dislocated right 2nd digit at the PIP joint. This finding was confirmed with an x-ray. This case report demonstrates that ultrasonography can be utilized to correctly identify finger dislocation. Although larger studies need to be performed to validate the accuracy of this imaging technique, the implications may improve care of the patient. It would also be particularly beneficial for this technique to be applied to the pediatric population as it may reduce unnecessary radiation. In conclusion, ultrasonography can be successfully utilized to correctly diagnose finger dislocations

New Onset Lichen Planus and Back Pain Leading to Discovery of a Peri Aortic Abscess

Back pain is a common chief complaint in the emergency department. With the differential ranging from musculoskeletal pain to cauda equina, there are a plethora of diagnoses. Differentiating between benign back pain and back pain that warrants further evaluation and even possible emergent surgical intervention is often a challenge in the acute setting. In this case report, a strange combination of all new symptoms including lichen planus, fevers, chills and atraumatic back pain lead to the eerie and very unexpected diagnosis of a peri-aortic abscess

Hallucinations Under Psychedelics and in the Schizophrenia Spectrum: An Interdisciplinary and Multiscale Comparison

The recent renaissance of psychedelic science has reignited interest in the similarity of drug-induced experiences to those more commonly observed in psychiatric contexts such as the schizophrenia-spectrum. This report from a multidisciplinary working group of the International Consortium on Hallucinations Research (ICHR) addresses this issue, putting special emphasis on hallucinatory experiences. We review evidence collected at different scales of understanding, from pharmacology to brain-imaging, phenomenology and anthropology, highlighting similarities and differences between hallucinations under psychedelics and in the schizophrenia-spectrum disorders. Finally, we attempt to integrate these findings using computational approaches and conclude with recommendations for future research

A Case Report on VT from TV: DVT and PE from Prolonged Television Watching

Pulmonary embolus (PE) and deep vein thrombosis are diagnoses that are commonly made in the emergency department. Well known risk factors for thromboembolic events include immobility, malignancy, pregnancy, surgery, and acquired or inherited thrombophilias, obesity, cigarette smoking, and hypertension. We present a case of a 59-year-old female who watched TV and developed leg swelling and was found to have PE and DVT

Natural speech algorithm applied to baseline interview data can predict which patients will respond to psilocybin for treatment-resistant depression

Background: Natural speech analytics has seen some improvements over recent years, and this has opened a window for objective and quantitative diagnosis in psychiatry. Here, we used a machine learning algorithm applied to natural speech to ask whether language properties measured before psilocybin for treatment-resistant can predict for which patients it will be effective and for which it will not. Methods: A baseline autobiographical memory interview was conducted and transcribed. Patients with treatment-resistant depression received 2 doses of psilocybin, 10 mg and 25 mg, 7 days apart. Psychological support was provided before, during and after all dosing sessions. Quantitative speech measures were applied to the interview data from 17 patients and 18 untreated age-matched healthy control subjects. A machine learning algorithm was used to classify between controls and patients and predict treatment response. Results: Speech analytics and machine learning successfully differentiated depressed patients from healthy controls and identified treatment responders from non-responders with a significant level of 85% of accuracy (75% precision). Conclusions: Automatic natural language analysis was used to predict effective response to treatment with psilocybin, suggesting that these tools offer a highly cost-effective facility for screening individuals for treatment suitability and sensitivity. Limitations: The sample size was small and replication is required to strengthen inferences on these results.Fil: Carrillo, Facundo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación. Laboratorio de Inteligencia Artificial Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Sigman, Mariano. Universidad Torcuato Di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fernandez Slezak, Diego. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación. Laboratorio de Inteligencia Artificial Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Ashton, Philip. Imperial College London; Reino UnidoFil: Fitzgerald, Lily. Imperial College London; Reino UnidoFil: Stroud, Jack. Imperial College London; Reino UnidoFil: Nutt, David J.. Imperial College London; Reino UnidoFil: Carhart Harris, Robin L.. Imperial College London; Reino Unid