Discinesia tardía: Efecto adverso de la terapia con neurolépticos.

De los numerosos efectos secundarios que ocasionan los neurolépticos (1), la discinesia tardía es uno de los que más limitan su empleo, dada la alta y creciente prevalencia de la misma y su difícil tratamiento (2, 3). Estas razones han hecho que los estudios sobre discinesia tardía se hayan incrementado de forma sustancial durante la última década (2,4), siendo numerosas las revisiones recientes sobre el tema (3, 5-8). Sin embargo, la atención dedicada a ese movimiento anómalo, en nuestra literatura, es escasa (9), y no hemos encontrado ninguna referencia a su incidencia en nuestro medio. Esta situación y la indudable trascendencia del tema nos ha motivado a realizar una revisión actualizada del mism

Discinesia tardía: Efecto adverso de la terapia con neurolépticos.

De los numerosos efectos secundarios que ocasionan los neurolépticos (1), la discinesia tardía es uno de los que más limitan su empleo, dada la alta y creciente prevalencia de la misma y su difícil tratamiento (2, 3). Estas razones han hecho que los estudios sobre discinesia tardía se hayan incrementado de forma sustancial durante la última década (2,4), siendo numerosas las revisiones recientes sobre el tema (3, 5-8). Sin embargo, la atención dedicada a ese movimiento anómalo, en nuestra literatura, es escasa (9), y no hemos encontrado ninguna referencia a su incidencia en nuestro medio. Esta situación y la indudable trascendencia del tema nos ha motivado a realizar una revisión actualizada del mism

Crítica de Libros.

Eugenio Trías: Lo bello y lo siniestro; Joyce McDougall: Alegato por cierta anormalidad; S. B. Filskov y T. J. Boll: Handbook of clinical neuropsychology; Mercedes Várela: Psicología de la mujer embarazada

Loss of serum IGF-I input to the brain as an early biomarker of disease onset in Alzheimer mice

Circulating insulin-like growth factor I (IGF-I) enters the brain and promotes clearance of amyloid peptides known to accumulate in Alzheimer's disease (AD) brains. Both patients and mouse models of AD show decreased level of circulating IGF-I enter the brain as evidenced by a lower ratio of cerebrospinal fluid/plasma IGF-I. Importantly, in presymptomatic AD mice this reduction is already manifested as a decreased brain input of serum IGF-I in response to environmental enrichment. To explore a potential diagnostic use of this early loss of IGF-I input, we monitored electrocorticogram (ECG) responses to systemic IGF-I in mice. Whereas control mice showed enhanced ECG activity after IGF-I, presymptomatic AD mice showed blunted ECG responses. Because nonhuman primates showed identically enhanced electroencephalogram (EEG) activity in response to systemic IGF-I, loss of the EEG signature of serum IGF-I may be exploited as a disease biomarker in AD patients

Using XAI in the Clock Drawing Test to reveal the cognitive impairment pattern.

he prevalence of dementia is currently increasing worldwide. This syndrome produces a deteriorationin cognitive function that cannot be reverted. However, an early diagnosis can be crucial for slowing itsprogress. The Clock Drawing Test (CDT) is a widely used paper-and-pencil test for cognitive assessmentin which an individual has to manually draw a clock on a paper. There are a lot of scoring systems forthis test and most of them depend on the subjective assessment of the expert. This study proposes acomputer-aided diagnosis (CAD) system based on artificial intelligence (AI) methods to analyze the CDTand obtain an automatic diagnosis of cognitive impairment (CI). This system employs a preprocessingpipeline in which the clock is detected, centered and binarized to decrease the computational burden.Then, the resulting image is fed into a Convolutional Neural Network (CNN) to identify the informativepatterns within the CDT drawings that are relevant for the assessment of the patient’s cognitive status.Performance is evaluated in a real context where patients with CI and controls have been classified byclinical experts in a balanced sample size of 3282 drawings. The proposed method provides an accuracyof 75.65% in the binary case-control classification task, with an AUC of 0.83. These results are indeedrelevant considering the use of the classic version of the CDT. The large size of the sample suggests thatthe method proposed has a high reliability to be used in clinical contexts and demonstrates the suitabilityof CAD systems in the CDT assessment process. Explainable artificial intelligence (XAI) methods areapplied to identify the most relevant regions during classification. Finding these patterns is extremelyhelpful to understand the brain damage caused by CI. A validation method using resubstitution withupper bound correction in a machine learning approach is also discusseThis work was supported by the MCIN/ AEI/10.13039/501100011033/ and FEDER “Una manera de hacer Europa” under the RTI2018- 098913-B100 project, by the Consejeria de Economia, Innovacion, Ciencia y Empleo (Junta de An765 dalucia) and FEDER under CV20-45250, A-TIC080-UGR18, B-TIC-586-UGR20 and P20-00525 projects, and by the Ministerio de Universidades under the FPU18/04902 grant given to C. JimenezMesa and the Margarita-Salas grant to J.E. Arco