Esclerosis lateral amiotrófica y miastenia gravis (síndrome overlap): presentación de 3 nuevos casos

Sr. Editor: La asociación de miastenia gravis (MG) y esclerosis lateralamiotrófica (ELA) (síndrome overlap) no es frecuente en lapráctica clínica. La evidencia disponible sugiere un efectoprotector de la terapia inmunomoduladora en fases inicialesde enfermedad de la motoneurona (ENM)1, 2. Presentamos 3 casos de síndrome overlap cuyas características se resumenen la tabla 1.Caso 1Varón de 52 a ~nos con cuadro clínico inicial de ptosis bila-teral, diplopía y disfagia que asocia, 6-8 meses después, paresia braquial izquierda con atrofia tenar, hiperreflexiaglobal e incremento del reflejo mentoniano. En la estimu-lación repetitiva a 3 Hz se obtuvo un decremento > 10% delquinto potencial en separador del quinto dedo. La titula-ción de los anticuerpos anti-receptor de acetilcolina (ACanti-RACA) fue de 0, 74 (positividad > 0, 7) que se mantuvoen determinaciones posteriores..

Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators

Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survivalof out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrilla-tors (AED). AED algorithms for VF-detection are customarily assessed using Holter record-ings from public electrocardiogram (ECG) databases, which may be different from the ECGseen during OHCA events. This study evaluates VF-detection using data from both OHCApatients and public Holter recordings. ECG-segments of 4-s and 8-s duration were ana-lyzed. For each segment 30 features were computed and fed to state of the art machinelearning (ML) algorithms. ML-algorithms with built-in feature selection capabilities wereused to determine the optimal feature subsets for both databases. Patient-wise bootstraptechniques were used to evaluate algorithm performance in terms of sensitivity (Se), speci-ficity (Sp) and balanced error rate (BER). Performance was significantly better for publicdata with a mean Se of 96.6%, Sp of 98.8% and BER 2.2% compared to a mean Se of94.7%, Sp of 96.5% and BER 4.4% for OHCA data. OHCA data required two times morefeatures than the data from public databases for an accurate detection (6 vs 3). No signifi-cant differences in performance were found for different segment lengths, the BER differ-ences were below 0.5-points in all cases. Our results show that VF-detection is morechallenging for OHCA data than for data from public databases, and that accurate VF-detection is possible with segments as short as 4-s

Auditory event-related potentials

Auditory event related potentials are electric potentials (AERP, AEP) and magnetic fields (AEF) generated by the synchronous activity of large neural populations in the brain, which are time-locked to some actual or expected sound event

Vulvar cancer: a review for dermatologists.

Vulvar malignancies are important tumors of the female reproductive system. They represent a serious health issue with an incidence between 2 and 7 per 100,000 and year. We provide a review about most important cancer entities, i.e., melanoma, squamous cell carcinoma, basal cell carcinoma, neuroendocrine cancer, and skin adnexal malignancies.Squamous cell carcinoma is the most common vulvar malignancy that can develop from vulvar intraepithelial neoplasia or de novo. Basal cell carcinoma represents only 2 % of all vulvar cancers. Melanoma of the vulva exists in two major types-superficial spreading and acral lentiginous. A special feature is the occurrence of multiple vulvar melanomas. Of the adnexal cancer types Paget's disease and carcinoma are seen more frequently than other adnexal malignancies. The dermatologist should be aware of this problem, since he might be the first to be consulted by patients for vulvar disease. Treatment should be interdisciplinary in close association to gynecologists, oncologists, and radiologists