3 resultados para dying in hospital

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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Background: Few studies have analyzed predictors of length of stay (LOS) in patients admitted due to acute bipolar manic episodes. The purpose of the present study was to estimate LOS and to determine the potential sociodemographic and clinical risk factors associated with a longer hospitalization. Such information could be useful to identify those patients at high risk for long LOS and to allocate them to special treatments, with the aim of optimizing their hospital management. Methods: This was a cross-sectional study recruiting adult patients with a diagnosis of bipolar disorder (Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revision (DSM-IV-TR) criteria) who had been hospitalized due to an acute manic episode with a Young Mania Rating Scale total score greater than 20. Bivariate correlational and multiple linear regression analyses were performed to identify independent predictors of LOS. Results: A total of 235 patients from 44 centers were included in the study. The only factors that were significantly associated to LOS in the regression model were the number of previous episodes and the Montgomery-Åsberg Depression Rating Scale (MADRS) total score at admission (P < 0.05). Conclusions: Patients with a high number of previous episodes and those with depressive symptoms during mania are more likely to stay longer in hospital. Patients with severe depressive symptoms may have a more severe or treatment-resistant course of the acute bipolar manic episode.

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Se realiza una revisión de los estudios españoles publicados sobre la atención a las paradas cardiorrespiratorias (PCR) intrahospitalarias (IH) y extrahospitalarias (EH) con el fin de realizar una comparativa acerca de las diferentes características clínicas que presentaron dichas paradas, además de estimar la supervivencia inicial, al alta y al año de los diferentes episodios. Este estudio revisó inicialmente todos los trabajos de origen español que versaron acerca de la asistencia a las PCR IH y EH publicados en el periodo de tiempo entre 1990 y 2014 de acuerdo a una metodología sistemática. Se extrajeron datos numéricos en referencia al número de pacientes asistidos, la edad media y sexo de los mismos, el lugar y la etiología principal de las PCR, los ritmos electrocardiográficos (ECG) iniciales, la asistencia inicial, los tiempos de llegada del soporte vital avanzado (SVA), la supervivencia inicial, al alta y al año, y la capacidad cerebral funcional de los pacientes tras el suceso. Se seleccionaron 10 estudios descriptivos y observacionales, 5 IH y 5 EH, de los cuales se dedujeron diferentes datos. El número total de pacientes intervenidos y susceptibles de reanimación asciende a 6011. Entre el 57-71% eran hombres. La edad media de los pacientes oscila entre 59-73 años para los hombres y 62-78 años para las mujeres. El lugar principal donde tuvo lugar la parada fue el domicilio en los estudios EH, mientras que a nivel IH no hubo un claro consenso variando la localización principal entre las salas médicas, la planta de hospitalización convencional o la unidad de cuidados intensivos (UCI). La etiología principal de las paradas corresponde a una causa cardiogénica. El ritmo ECG inicial predominante fue la asistolia con un 35-74%, observándose únicamente ritmos desfibrilables en el 18-39%. El testigo principal de las PCR EH fue el propio viandante, mientras que en las PCR IH fue el personal sanitario. En la mayoría de los estudios se realizó reanimación cardiopulmonar (RCP) previa a la llegada del SVA. El tiempo medio de llegada de este último fue de 1-4 minutos a nivel IH y de 10-15 minutos a nivel EH. La supervivencia inicial de los pacientes tras las maniobras de RCP oscila entre un 15-64%. La supervivencia al alta fue del 10-35%, presentando en su gran mayoría una buena funcionalidad cerebral (CPC 1-2). Al año se recogieron tasas de supervivencia del 16-31%.

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[EN]Hyperventilation, which is common both in-hospital and out-of-hospital cardiac arrest, decreases coronary and cerebral perfusion contributing to poorer survival rates in both animals and humans. Current resucitation guidelines recommend continuous monitoring of exhaled carbon dioxide (CO2) during cardiopulmonary resucitation (CPR) and emphasize good quality of CPR, including ventilations at 8-10 min1. Most of commercial monitors/de- brilators incorporate methods to compute the respiratory rate based on capnography since it shows uctuations caused by ventilations. Chest compressions may induce artifacts in this signal making the calculation of the respiratory rate di cult. Nevertheless, the accuracy of these methods during CPR has not been documented yet. The aim of this project is to analyze whether the capnogram is reliable to compute ventilation rate during CPR. A total of 91 episodes, 63 out-of-hospital cardiac arrest episodes ( rst database) and 28 in-hospital cardiac arrest episodes (second database) were used to develop an algorithm to detect ventilations in the capnogram, and the nal aim is to provide an accurate ventilation rate for feedback purposes during CPR. Two graphic user interfaces were developed to make the analysis easier and another two were adapted to carry out this project. The use of this interfaces facilitates the managment of the databases and the calculation of the algorithm accuracy. In the rst database, as gold standard every ventilation was marked by visual inspection of both the impedance, which shows uctuations with every ventilation, and the capnography signal. In the second database, volume of the respiratory ow signal was used as gold standard to mark ventilation instants since it is not a ected by chest compressions. The capnogram was preprocessed to remove high frequency noise, and the rst di erence was computed to de ne the onset of inspiration and expiration. Then, morphological features were extracted and a decission algorithm built based on the extracted features to detect ventilation instants. Finally, ventilation rate was calculated using the detected instants of ventilation. According to the results obtained in this project, the capnogram can be reliably used to give feedback ventilation rate, and therefore, on hyperventilation in a resucitation scenario.