Euploid embryos selected by an automated time-lapse system have superior SET outcomes than selected solely by conventional morphology assessment.

PURPOSE: We investigated if automated TLI selection may be a valuable strategy to identify those euploid embryos with the best chances of success. METHODS: This is a unicentric and retrospective study involving 244 patients undergoing preimplantational genetic screening (PGS) cycles with autologous oocytes or oocyte donation (OD) with single euploid embryo transferred. We examined euploid embryos selected for transfer based on morphology evaluation alone (PGS-only; control group) or by assessment using an automated TLI system (Eeva™; PGS-TLI group). RESULTS: In both, autologous oocytes and OD patients, significantly better implantation and clinical and ongoing pregnancy rates were obtained in the PGS-TLI group when euploid embryos with high implantation potential as predicted by the automated TLI System (Eeva™) were transferred compared with the PGS-only group. This improvement was also observed when only transfers of good morphological quality embryos were compared. TLI categories showed significant differences on blastocyst formation and euploidy rate. CONCLUSIONS: Automated TLI combined with PGS is a useful prognostic tool to identify euploid embryos with the highest potential for implantation and pregnancy. Further, these results provide evidence that a healthy pregnancy does not only depend upon normal chromosomal status.

Analysis of ZP1 gene reveals differences in zona pellucida composition in carnivores.

The zona pellucida (ZP) is an extracellular envelope that surrounds mammalian oocytes. This coat participates in the interaction between gametes, induction of the acrosome reaction, block of polyspermy and protection of the oviductal embryo. Previous studies suggested that carnivore ZP was formed by three glycoproteins (ZP2, ZP3 and ZP4), with ZP1 being a pseudogene. However, a recent study in the cat found that all four proteins were expressed. In the present study, in silico and molecular analyses were performed in several carnivores to clarify the ZP composition in this order of mammals. The in silico analysis demonstrated the presence of the ZP1 gene in five carnivores: cheetah, panda, polar bear, tiger and walrus, whereas in the Antarctic fur seal and the Weddell seal there was evidence of pseudogenisation. Molecular analysis showed the presence of four ZP transcripts in ferret ovaries (ZP1, ZP2, ZP3 and ZP4) and three in fox ovaries (ZP2, ZP3 and ZP4). Analysis of the fox ZP1 gene showed the presence of a stop codon. The results strongly suggest that all four ZP genes are expressed in most carnivores, whereas ZP1 pseudogenisation seems to have independently affected three families (Canidae, Otariidae and Phocidae) of the carnivore tree.

Conciliación de la medicación al ingreso: resultados e identificación de pacientes diana / Medication reconciliation at hospital admission: results and identification of target patients

Objetivo. Identificar y cuantificar las discrepancias entre el tratamiento prescrito al ingreso hospitalario y el tratamiento crónico del paciente. Identificar variables que puedan utilizarse en la selección de los pacientes más susceptibles de beneficiarse de un programa de conciliación de la medicación. Material y métodos. Se diseñó un estudio prospectivo de conciliación de la medicación al ingreso hospitalario en el servicio de cirugía vascular y angiología de marzo a diciembre de 2014. Al ingreso el personal de enfermería informaba al paciente del estudio y le solicitaban que recopilara información sobre su tratamiento crónico. Posteriormente, el personal farmacéutico revisaba el historial clínico, las prescripciones crónicas y entrevistaba al paciente para obtener la mejor historia farmacoterapéutica posible. Ésta se comparaba con la prescripción realizada al ingreso y las discrepancias se registraban en el evolutivo clínico. Finalmente, el personal médico clasificaba las discrepancias y modificaba la prescripción en caso necesario. Se compararon las características de los pacientes con y sin discrepancias no justificadas (DNJ) y se construyeron las curvas de característica operativa del receptor de aquellas con diferencias estadísticamente significativas, para determinar su sensibilidad y especificidad para seleccionar pacientes con DNJ. Resultados. Se incluyeron 380 pacientes, registrándose 845 DNJ, 600 justificadas no documentadas y 439 justificadas documentadas. Doscientos noventa y tres pacientes tuvieron al menos una DNJ (77%), 65 solo justificadas (17%) y 22 ninguna (6%). Las DNJ fueron: diferente dosis, vía o frecuencia (51%), omisión (39%), medicamento equivocado (8%) y comisión (2%). Las variables relacionadas con las discrepancias fueron número de medicamentos habituales y quién facilitaba la información. Conclusiones. En la mayoría de estudios la DNJ mayoritaria es la omisión, a diferencia de lo que ocurre en nuestro caso. La variable que permite seleccionar pacientes con mayor riesgo de presentar discrepancias es el número de medicamentos habituales. También aumenta el riesgo de sufrir DNJ cuando no es el propio paciente el que conoce y gestiona su tratamiento crónico (AU)

Objective. To quantify and to classify the discrepancies between the admission treatment and the usual patient treatment. To determine the variables that predict those patients that will have more benefit from medication reconciliation. Material and methods. A prospective medication reconciliation study was conducted in the Vascular Surgery Unit from March 2014 to December 2014. When the patients were admitted to the Vascular Surgery Unit, they were informed about the study and asked to prepare information about their chronic treatment. The pharmacist then checked their clinical records, outpatient prescriptions, and also interviewed the patient, obtaining the best pharmacotherapeutic history available. The discrepancies with the admission treatment were written into the patient electronic clinical records. Finally, the physician classified the discrepancies, and changed the treatment, if needed. The statistical analysis included a comparison between patients with and without a non-justified discrepancy (NJD). The statistically different characteristics were used to plot Receiver Operating Characteristic curves, in order to determine the sensitivity and the specificity of these variables to select patients with discrepancies. Results. A total of 380 patients were included. There were 845 non-justified, 600 justified non-documented, and 439 justified documented discrepancies. At least one NJD was identified in 293 patients (77%), with 65 patients (17%) having only justified discrepancies, and 22 patients (6%) having no discrepancies. NJD were: different dose, route or schedule (51%), omission (39%), wrong drug (8%) and commission (2%). The variables associated with discrepancies were number of chronic medications drugs and provider of information. Conclusions. In most studies, omission is the most frequent error. In contrast, in our study the most frequent error is different dose, route, or schedule. The variable that allows selecting patients at higher risk of discrepancies is the number of chronic drugs. This risk is also increased if the patients are not the manager of their own medication (AU)

[Medication reconciliation at hospital admission: Results and identification of target patients]. / Conciliación de la medicación al ingreso: resultados e identificación de pacientes diana.

OBJECTIVE: To quantify and to classify the discrepancies between the admission treatment and the usual patient treatment. To determine the variables that predict those patients that will have more benefit from medication reconciliation. MATERIAL AND METHODS: A prospective medication reconciliation study was conducted in the Vascular Surgery Unit from March 2014 to December 2014. When the patients were admitted to the Vascular Surgery Unit, they were informed about the study and asked to prepare information about their chronic treatment. The pharmacist then checked their clinical records, outpatient prescriptions, and also interviewed the patient, obtaining the best pharmacotherapeutic history available. The discrepancies with the admission treatment were written into the patient electronic clinical records. Finally, the physician classified the discrepancies, and changed the treatment, if needed. The statistical analysis included a comparison between patients with and without a non-justified discrepancy (NJD). The statistically different characteristics were used to plot Receiver Operating Characteristic curves, in order to determine the sensitivity and the specificity of these variables to select patients with discrepancies. RESULTS: A total of 380 patients were included. There were 845 non-justified, 600 justified non-documented, and 439 justified documented discrepancies. At least one NJD was identified in 293 patients (77%), with 65 patients (17%) having only justified discrepancies, and 22 patients (6%) having no discrepancies. NJD were: different dose, route or schedule (51%), omission (39%), wrong drug (8%) and commission (2%). The variables associated with discrepancies were number of chronic medications drugs and provider of information. CONCLUSIONS: In most studies, omission is the most frequent error. In contrast, in our study the most frequent error is different dose, route, or schedule. The variable that allows selecting patients at higher risk of discrepancies is the number of chronic drugs. This risk is also increased if the patients are not the manager of their own medication.