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The respiratory control system is one of the most complex physiological systems, whose controller has been extensively modeled based on the criterion of minimizing work of breathing (WOB). However, cost functions and their related parameters are still an open topic. The aim of this paper is to evaluate different estimates of WOB for given ventilatory demands. Two known computations of mechanical work are compared with regard to an estimate proposed in this paper. Appropriate values for these parameters were found based on the best fitting of the breathing pattern obtained from experimental data during increased hypercapnia. The comparison among them was carried out from their breathing pattern predictability and the physiological viewpoint. For this purpose, two nested optimization processes were performed: minimization of prediction error, with regard to the experimental response, in order to obtain the best estimating parameters; identification of a breathing pattern that minimizes the mechanical WOB. The former was performed using Co-variance Matrix Adaptation Evolution Strategy and the latter using sequential quadratic programming. Results show that the estimate proposed in this paper is less sensitive to their parameters and reaches a significantly lower prediction error of breathing pattern during increased ventilatory effort and a better interpretation from a physiological viewpoint.

Frailty and multi-morbidity have been associated with increased pressure on Emergency Departments (ED), higher hospital admissions and more risks for patients arising from the ED stay. The advantages of developing specific attention to frailty in ED have been highlighted. The benefits of these approaches are related to patients but also to organizations. The aim is to present how a Program of Care for Frailty (PCF) in an ED impacts on patient flows. Setting: A tertiary, teaching, 550-bed urban hospital, with 80,000 adult patients/year ED attendances (43% ≥ 65 years). The three main axes of the program are (1) an ED geriatrization, implementing multidisciplinary comprehensive geriatric assessment performed by ED professionals (physician, nurses, social worker, pharmacist); (2) an elder-friendly area (EFA) inside the ED was built; (3) The ED integration in a collaborative network with others healthcare providers in the territory for a shared urgent care. Between 2011 and 2017, we observe a progressive increase in ED activity (+ 8.1%), in patient’s age (40.9% vs 42.8% ≥ 65 years), and an increase in ambulance arrivals (+ 25.1%). The admission rate was rising until 2014 (10.8–12%). In 2014, the ED geriatrization began and networking was reinforced, and a decrease in the rate of admission (11.3%) is observed. Despite a progressive increase in ED activity and older people, we have observed a decrease in hospital admissions in parallel with the Program of Care for Frailty development. Systematic application of similar programs in distinct EDs would have an impact on the overall health system.

We read with interest the report by Witjes et al regarding the influence of end-of-life care on organ donor potential (1). The report promotes innovation in management of potential organ donors outside the ICU, particularly in patients admitted to the emergency department (ED) with acute devastating brain injury (DBI) and imminent brain death. This article is protected by copyright. All rights reserved.

Classification algorithms with unbalanced datasets tend to produce high predictive accuracy over the majority class, but poor predictive accuracy over the minority class. This problem is very common in biomedical data mining. This paper introduces a Support Vector Machine (SVM)-based optimized feature selection method, to select the most relevant features and maintain an accurate and well-balanced sensitivity-specificity result between unbalanced groups. A new metric called the balance index (B) is defined to implement this optimization. The balance index measures the difference between the misclassified data within each class. The proposed optimized feature selection is applied to the classification of patients' weaning trials from mechanical ventilation: patients with successful trials who were able to maintain spontaneous breathing after 48h and patients who failed to maintain spontaneous breathing and were reconnected to mechanical ventilation after 30min. Patients are characterized through cardiac and respiratory signals, applying joint symbolic dynamic (JSD) analysis to cardiac interbeat and breath durations. First, the most suitable parameters (C"+,C"-,@s) are selected to define the appropriate SVM. Then, the feature selection process is carried out with this SVM, to maintain B lower than 40%. The best result is obtained using 6 features with an accuracy of 80%, a B of 18.64%, a sensitivity of 74.36% and a specificity of 82.42%.

Graphical abstractDisplay Omitted HighlightsTwo respiratory control models based on minimizing work of breathing are analyzed.Optimization algorithms and hypercapnic data are used to adjust model parameters.Algorithms are assessed in terms of convergence rate, solution accuracy and precision.Models are evaluated in terms of prediction error and physiological meaning. One of the most complex physiological systems whose modeling is still an open study is the respiratory control system where different models have been proposed based on the criterion of minimizing the work of breathing (WOB). The aim of this study is twofold: to compare two known models of the respiratory control system which set the breathing pattern based on quantifying the respiratory work; and to assess the influence of using direct-search or evolutionary optimization algorithms on adjustment of model parameters. This study was carried out using experimental data from a group of healthy volunteers under CO2 incremental inhalation, which were used to adjust the model parameters and to evaluate how much the equations of WOB follow a real breathing pattern. This breathing pattern was characterized by the following variables: tidal volume, inspiratory and expiratory time duration and total minute ventilation. Different optimization algorithms were considered to determine the most appropriate model from physiological viewpoint. Algorithms were used for a double optimization: firstly, to minimize the WOB and secondly to adjust model parameters. The performance of optimization algorithms was also evaluated in terms of convergence rate, solution accuracy and precision. Results showed strong differences in the performance of optimization algorithms according to constraints and topological features of the function to be optimized. In breathing pattern optimization, the sequential quadratic programming technique (SQP) showed the best performance and convergence speed when respiratory work was low. In addition, SQP allowed to implement multiple non-linear constraints through mathematical expressions in the easiest way. Regarding parameter adjustment of the model to experimental data, the evolutionary strategy with covariance matrix and adaptation (CMA-ES) provided the best quality solutions with fast convergence and the best accuracy and precision in both models. CMAES reached the best adjustment because of its good performance on noise and multi-peaked fitness functions. Although one of the studied models has been much more commonly used to simulate respiratory response to CO2 inhalation, results showed that an alternative model has a more appropriate cost function to minimize WOB from a physiological viewpoint according to experimental data.

Weaning from mechanical ventilation is still one of the most challenging problems in intensive care. Unnecessary delays in discontinuation and weaning trials that are undertaken too early are both undesirable. This study investigated the contribution of spectral signals of heart rate variability (HRV) and respiratory flow, and their coherence to classifying patients on weaning process from mechanical ventilation. A total of 121 candidates for weaning, undergoing spontaneous breathing tests, were analyzed: 73 were successfully weaned (GSucc), 33 failed to maintain spontaneous breathing so were reconnected (GFail), and 15 were extubated after the test but reintubated within 48 h (GRein). The power spectral density and magnitude squared coherence (MSC) of HRV and respiratory flow signals were estimated. Dimensionality reduction was performed using principal component analysis (PCA) and sequential floating feature selection. The patients were classified using a fuzzy K-nearest neighbour method. PCA of the MSC gave the best classification with the highest accuracy of 92% classifying GSucc versus GFail patients, and 86% classifying GSucc versus GRein patients. PCA of the respiratory flow signal gave the best classification between GFail and GRein patients (79% accuracy). These classifiers showed a good balance between sensitivity and specificity. Besides, the spectral coherence between HRV and the respiratory flow signal, in patients on weaning trial process, can contribute to the extubation decision.

Objective: Patients with heart failure (HF) seen at the emergency department (ED) are increasingly older and more likely to present delirium. Little is known, however, about the impact of this syndrome on outcome in these patients. We aimed to investigate the prognostic value and risk factors of delirium at admission (prevalent delirium) in ED patients with decompensated HF. Methods and Results: We performed a prospective, observational study, analyzing the presence of prevalent delirium in decompensated HF patients attended at the ED in 2 hospitals in Spain in the context of the Epidemiology Acute Heart Failure Emergency project. We used the brief Confusion Assessment Method to assess the presence of delirium. Patients were followed for 1 month after discharge. Of 239 enrolled patients (81.7 +/- 9.4 years, women 61.1%, long-term care [LTC] 11%), 35 (14.6%) had prevalent delirium (20% LTC vs 9.4% in-home, P = .078). The factors associated with delirium in the multivariate analysis were functional dependence (P = .001) and dementia (P = .005). Prevalent delirium was an independent risk factor of death within 30 days (OR 3.532; 95% CI 1.422-8.769, P = .007) whereas autonomy in basic activities of daily living was a protective factor (OR 0.971; 95% CI 0.956-0.986, P = .001). The area under the ROC curve for our 30-day mortality model was 0.802 (95% CI 0.721-0.883, P = .001). Conclusion: Prevalent delirium in patients with decompensated HF was a predictor of short-term mortality. Routine identification of delirium in patients at risk, particularly those with greater functional dependence, can help emergency physicians in decision-making and enhance care in patients with decompensated HF. (C) 2015 AMDA - The Society for Post-Acute and Long-Term Care Medicine.

Background/Aims The currently recommended treatment for acute variceal bleeding is the association of vasoactive drugs and endoscopic therapy. However, which emergency endoscopic treatment combines better with drugs has not been clarified. This study compares the efficacy and safety of variceal ligation and sclerotherapy as emergency endoscopic treatment added to somatostatin. Methods Patients admitted with acute gastrointestinal bleeding and with suspected cirrhosis received somatostatin infusion (for 5 days). Endoscopy was performed within 6h and those with esophageal variceal bleeding were randomized to receive either sclerotherapy ( N =89) or ligation ( N =90). Results Therapeutic failure occurred in 21 patients treated with sclerotherapy (24%) and in nine treated with ligation (10%) (RR=2.4, 95% CI=1.1–4.9). Failure to control bleeding occurred in 15% vs 4%, respectively ( P =0.02). Treatment group, shock and HVPG >16mmHg were independent predictors of failure. Side-effects occurred in 28% of patients receiving sclerotherapy vs 14% with ligation (RR=1.9, 95% CI=1.1–3.5), being serious in 13% vs 4% ( P =0.04). Six-week survival probability without therapeutic failure was better with ligation ( P =0.01). Conclusions The use of variceal ligation instead of sclerotherapy as emergency endoscopic therapy added to somatostatin for the treatment of acute variceal bleeding significantly improves the efficacy and safety.

Objective To evaluate short- and long-term outcomes of elderly patients (≥ 65 years) treated at an intermediate care unit (IMCU) and to identify outcome predictors.

Traditional time domain techniques of data analysis are often not sufficient to characterize the complex dynamics of respiration. In this paper, the respiratory pattern variability is analyzed using symbolic dynamics. A group of 20 patients on weaning trials from mechanical ventilation are studied at two different pressure support ventilation levels, in order to obtain respiratory volume signals with different variability. Time series of inspiratory time, expiratory time, breathing duration, fractional inspiratory time, tidal volume and mean inspiratory flow are analyzed. Two different symbol alphabets, with three and four symbols, are considered to characterize the respiratory pattern variability. Assessment of the method is made using the 40 respiratory volume signals classified using clinical criteria into two classes: low variability (LV) or high variability (HV). A discriminant analysis using single indexes from symbolic dynamics has been able to classify the respiratory volume signals with an out-of-sample accuracy of 100%.

Objective: The society which hospitals serve is currently undergoing demographic, technological and cultural changes. The Internal Medicine Service (IMS) of the Hospital de la Santa Creu i Sant Pau considers these changes to provide an opportunity for improvement. We present the proposals and methodology applied for the re-engineering of the IMS. Method: The nominal group technique was used to identify and prioritize objectives and to select problems and interventions for implementation. Hospital staff of all levels, residents’ associations in the hospital’s vicinity, health authorities external to the hospital, patients and their families participated in these groups. The redesign was initiated in 1998 and continues to date. Results: The strong points of the IMS were considered to be its multidisciplinary training and adaptability to different situations and needs. The seven objectives selected identified the external and internal clients. Among the five main problems prioritized, three centered on improving process management and two on non-clinical skills training. Finally, 23 end points influencing daily clinical activity were selected. These end-points aim to improve the participation of all the team members in the objectives of the service/hospital and to help in resolving citizen’s problems. Conclusions: Our proposal for remodelling raises two important issues. The first reveals the importance of working with specific and participative methodology. The second identifies objectives, detects problems, proposes courses of action for improvement, and selects a number of end points, which should be incorporated in the redesign of our IMS. The proposed redesign continues to be open and to incorporate improvements.

This work proposed and studied a method of automatically classifying respiratory volume signals as high or low variability by means of non-linear analysis of the respiratory volume. The analysis used volume signals generated by the respiratory system to construct a model of its dynamics and to estimate the quality of the predictions made with the model. Different methods of prediction evaluation, prediction horizons and embedding dimensions were also analysed. Assessment of the method was made using a database that contained 40 respiratory volume signals classified using clinical criteria into two classes: low or high variability. The results obtained using the method of surrogate data provided evidence of non-linear determinism in the respiratory volume signals. A discriminant analysis carried out using non-linear prediction variables classified the respiratory volume signals with an accuracy of 95%.

La enfermedad cardiovascular representa la principal causa de mortalidad entre los adultos de mas de 30 anos de las sociedades industrializadas, y la enfermedad coronaria es la principal causa de esta mortalidad, seguida de los episodios cerebrovasculares. La enfermedad arteriosclerotica ‐habitualmente asintomatica durante decadas‐ subyace en la anatomia y patologia de estas entidades. Siendo una enfermedad cronica relativamente benigna, se transforma en una grave enfermedad aguda que se manifiesta clinicamente como un sindrome coronario agudo (SCA) en forma de angina inestable, infarto agudo de miocardio (IAM) o muerte subita 1 . La fisiopatologia de los SCA es compleja y multifactorial; en ella desempenan un papel importante la inflamacion e infeccion de la pared arterial, la disfuncion endotelial, la desproporcion entre el aporte y la demanda de oxigeno, el metabolismo lipidico, la estenosis coronaria y, finalmente, la erosion o rotura de una placa aterosclerotica vulnerable, que determina la formacion de un trombo intracoronario 3 . El

La utilizacion de sistemas para establecer el pronostico de los pacientes es habitual en las unidades de cuidados intensivos. Su capacidad predictiva es variable y depende de la poblacion a la que se aplica. Entre las poblaciones en las que han demostrado una menor exactitud se encuentra la de los enfermos ventilados mecanicamente Estudio de cohortes de 1.103 pacientes ventilados mecanicamente. Con un analisis de particiones recursivas se determinaron las variables asociadas a la mortalidad, y con un analisis de regresion logistica se construyeron dos modelos predictivos: el primero con el SAPS II y las variables previas al inicio de la ventilacion mecanica, y el segundo con el SAPS II y las variables previas y aparecidas durante la ventilacion mecanica. Para evaluar la prediccion de la mortalidad se realizo una medida de calibracion con el metodo de Lemeshow y Hosmer y una medida de discriminacion calculando el area bajo la curva ROC La mortalidad observada fue de un 42% (IC del 95%, 39-45) frente a una predicha por el SAPS II de un 36%. En el analisis de particiones recursivas, las variables asociadas a la mortalidad fueron: fracaso renal agudo, shock, PaO2/FiO2 En una cohorte de enfermos ventilados mecanicamente, el SAPS II fue un mal predictor de la mortalidad hospitalaria. La inclusion de factores previos al inicio y aparecidos durante la ventilacion mecanica mejora discretamente la exactitud predictiva

Fundamento La ventilacion mecanica es una tecnica fundamental en las unidades de cuidados intensivos (UCI). El objetivo es conocer su utilizacion y las diferencias en su aplicacion en 72 UCI espanolas Metodos Estudio de cohortes de los pacientes ventilados durante mas de 12 h. Se registraron datos demograficos, indicacion de la ventilacion mecanica, parametros ventilatorios, modos de ventilacion y desconexion, y dias de soporte ventilatorio, dias de estancia y situacion al alta Resultados Se incluyo a 1.103 pacientes (29%) de los ingresados, un 66% de varones, con una mediana de edad de 65 anos y del SAPS II de 43. No se observaron diferencias geograficas en la aplicacion de la ventilacion mecanica ni en los desenlaces principales. En el 64% la indicacion de ventilacion fue insuficiencia respiratoria. Al inicio, la modalidad asistida-controlada fue la mas utilizada (90%), con un volumen tidal medio (desviacion estandar [DE]) 8,9 (2,0) ml/kg y PEEP 5,5 (2,2) cmH2O. El 4% recibio ventilacion no invasora, el 68% de los enfermos no preciso intubacion. La duracion de la ventilacion fue 7 (8) dias. El metodo de desconexion mas utilizado fue una prueba unica diaria de respiracion espontanea (58%). La duracion fue de 3 (5) dias. La incidencia de traqueostomia fue 15% y se realizo a los 14 (8) dias. La mortalidad en la UCI fue del 32,8% y en el hospital del 42,8% Conclusiones La comparacion de la utilizacion de la ventilacion mecanica en 72 UCI espanolas evidencia una practica similar, con minimas diferencias en el uso de los modos de ventilacion y desconexion y una similar mortalidad y dias de estancia

Resumen Introduccion El tratamiento de las neumonias adquiridas en la comunidad (NAC) con antibioticos en monoterapia y monodosis (MM) ha demostrado la misma efectividad clinica que las pautas clasicas de antibioterapia fraccionada, a la vez que disminuye la estancia hospitalaria. Esto hace que la MM constituya una opcion de mejora. Objetivo: Comprobar si las caracteristicas del tratamiento de las NAC con MM eran exportables a un hospital diferente de aquellos en los que se habian descrito inicialmente. Material y metodo Estudio de intervencion para la mejora de la calidad, en el periodo de enero a mayo de 1999. Tipo de muestreo: consecutivo. Datos recogidos: edad, sexo, puntuacion APACHE II e indice de Charlson para comorbilidades, tiempo de estancia, mortalidad a 30 dias, reingresos en los 10 dias siguientes del alta hospitalaria, tiempos de enfermeria en preparar y suministrar el tratamiento. En la etapa I se compararon las pautas de MM con levofloxacino o ceftriaxona frente a la pauta clasica de cefotaxima cada 6 h acompanada de un macrolido cada 12 h. En la etapa II se compararon entre si las pautas de MM: levofloxacino frente a ceftriaxona. Durante todo el estudio se aplicaron guias de practica clinica comunes a todos los pacientes con NAC. En la etapa III, segun los resultados obtenidos y a las evidencias bibliograficas, el grupo de expertos selecciono la pauta definitiva. Resultados En la etapa I el tiempo medio ± desviacion estandar (DE) de estancia de las NAC tratadas con MM fue de 151 ± 80,6 h frente a 204 ± 110,4 horas en el tratamiento clasico, siendo la diferencia estadisticamente significativa y clinicamente relevante. No se detectaron diferencias en la mortalidad y reingresos; el tiempo de enfermeria fue de 4 min/paciente/dia en la MM frente a 16 minutos en el tratamiento clasico. En la segunda etapa no se detectaron diferencias entre los dos tipos de MM empleadas, si bien no se alcanzo el tamano adecuado de la muestra. El grupo de expertos selecciono la MM con levofloxacino por permitir un tratamiento secuencial sin cambio de farmaco y porque su biodisponibilidad oral proxima al cien por cien permite iniciar el tratamiento oral rapidamente. Comentario Nuestros resultados ponen de manifiesto que la MM supone una opcion de mejora en nuestro hospital, dado que al disminuir los tiempos de estancia por paciente junto con un ahorro en el tiempo de enfermeria mejora la utilizacion de las camas sin incrementar los riesgos para el paciente.

The purpose of this work is to evaluate characteristics of a respiratory model, RS1 , in the presence of the following stimuli: exercise, hypercapnia and hypoxia. RS1 has a controller where the driving signal optimizes alveolar ventilation and respiratory frequency to minimize the respiratory work output. A comparative study of the steady-state and transient responses with other three models is performed by simulation. Alternative equations to calculate the optimum frequency are evaluated during exercise and a linear average of two of them is proposed and tested for a healthy subject and with restrictive/obstructive pathology. Additionally, the circulatory time delay in gas transport that produces periodic breathing is calculated.

We have read with interest the report by Ramanathan et al regarding a case of ornithine transcarbamylase (OTC) deficiency unmasked post–liver transplantation (1). This serves as a big learning opportunity in clinical organ donor evaluation. A consequence of this disorder is hyperammonemia. Acute high levels in serum ammonia can cause severe neurological findings such as cerebral edema and brain death (2-4). This article is protected by copyright. All rights reserved.

Due to the increasing elderly population and the extensive number of comorbidities that affect them, studies are required to determine future increments in admission to emergency departments. Some of these studies could focus on the relation between chronic diseases and breathing pattern in elderly patients. Variations in the fractal properties of respiratory signals can be associated with several diseases. To determine the relationship between these variations and breathing patterns, and to quantify the fractal properties of respiratory flow signals, we estimated the Hurst exponent (H). Detrended fluctuation analysis (DFA) and discrete wavelet transform-based estimation (DWTE) methods were applied. The estimation methods were analyzed using simulated data series generated by fractional Gaussian noise. 43 elderly patients (19 patients with a non-periodic breathing pattern - nPB, and 24 patients with a periodic breathing pattern - PB) were studied. The results were evaluated according to the length of data and the number of averaged data series used to obtain a good estimation. The DWTE method estimated the respiratory flow signals better than the DFA method, and obtained Hurst values clustered by group. We found significant differences in the H exponent (p = 0.002) between PB and nPB patients, which showed different behavior in the fractal properties.

Blood pressure carries a great deal of information about people’s physical attributes. We analyzed the blood pressure signal in healthy subjects considering two positions, supine and sitting. 44 healthy subjects were studied. Parameters extracted from the blood pressure signal, related to time and frequency domain were used to compare the effect of postural position between supine and sitting. In time domain analysis, the time systolic interval and the time of blood pressure interval were higher in supine than in sitting position (p = 0.001 in both case). Parameters related to frequency peak, interquartile range, in frequency domain presented statistically significant difference (p < 0.0005 in both case). The blood pressure variability parameters presented smaller values in supine than in sitting position (p < 0.0005). In general, the position change of supine to sitting produces an increment in the pressure gradient inside heart, reflected in the blood pressure variability.

La presente investigación tuvo como objetivo general, determinar qué efectos tiene el programa de procedimientos de consolidación de estados financieros en la mejora de la Información contable financiera de las entidades que conforman la Corporación Municipal Metropolitana de Lima. 2014. La población de 60 personas trabajadores de la Municipalidad Metropolitana de Lima, la muestra censal consideró toda la población, en los cuales se han empleado las variables: Programa de procedimientos de consolidación de estados financieros y Información Contable Financiera. El método empleado en la investigación fue el hipotético-deductivo. Esta investigación utilizó para su propósito el diseño experimental de clase cuasi-experimental, con dos grupos experimental y control; en donde se recogió la información en un período específico, que se desarrolló al aplicar el Pre-test y Pos-Test, los cuales están constituidos por un cuestionario de 30 preguntas en la escala continua de 0-30, que brindo información acerca de la Información Contable Financiera, cuyos resultados se presentan gráfica y textualmente. La investigación concluye que existe evidencia significativa para afirmar que: El programa de Procedimientos de consolidación de estados financieros tiene efectos significativos en la mejora de la Información financiera de las entidades que conforman la Corporación Municipal Metropolitana de Lima. 2014 Lima Norte Escuela de Posgrado Dirección

Resumen Objetivo Describir la metodologia de trabajo y los resultados funcionales obtenidos al redisenar un servicio de urgencias de un hospital terciario. Metodologia Se ha trabajado con la metologia de las tecnicas de mejora de la calidad, detectando los grupos de trabajo las siguientes areas de mejora: 1. reordenacion de los recursos aportados por cada servicio participante 2. reestructuracion fisica del servicio 3. mejora de su competencia tecnica mediante la renovacion de equipos tecnol ogicos, y 4. informatizacion del servicio. Resultados Se han creado 3 circuitos diferenciados para atender a los pacientes segun su nivel de riesgo vital: 1. pacientes criticos que requieren soporte cardiovascular avanzado (nivel I de riesgo). Su circuito asistencial se apoya en cubiculos de reanimacion avanzada, quirofanos y UCI. 2. emergencias o pacientes con riesgo vital potencial (nivel II de riesgo) cuyo circuito se apoya en cubiculos monitorizados zona de observacion, quirofanos y salas de alta rapida y salas de semicriticos, y 3. urgencias o pacientes sin riesgo vital (nivel III de riesgo), con un circuito que se apoya en cubiculos no monitorizados y area de terapeuticas cortas. Para dar soporte a todos estos circuitos se modifico la estructura del servicio de urgencias que paso de 420 m2 a 1.750m2; para agilizar estos circuitos se ha integrado con una doctrina asistencial comun a todas las areas implicadas en la asistencia de estos pacientes. La informatizacion del complejo, los equipos de imagen de ultima generacion, junto las guias de practica clinica consensuada complementaron la competencia tecnica de medicos/enfermeros. Conclusion La reforma del servicio de urgencias se ha basado en el trabajo de los grupos de mejora y sus propuestas de intervenciones, la integracion de areas tales como las Salas de Alta Rapida, y la Unidad de Semicriticos junto con las areas propiamente de urgencias y su coordinacion a traves de circuitos definidos por el nivel de riesgo del paciente constituye una de las aportaciones relevantes de la reforma del servicio de urgencias, que ha pasado a denominarse Complejo de Urgencias, Emergencias y Criticos para reflejar el cambio de filosofia que suponen las medidas aplicadas, con respecto a la etapa anterior.

One of the most challenging problems in intensive care is still the process of discontinuing mechanical ventilation, called weaning process. Both an unnecessary delay in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we analyzed respiratory pattern variability using the respiratory volume signal of patients submitted to two different levels of pressure support ventilation (PSV), prior to withdrawal of the mechanical ventilation. In order to characterize the respiratory pattern, we analyzed the following time series: inspiratory time, expiratory time, breath duration, tidal volume, fractional inspiratory time, mean inspiratory flow and rapid shallow breathing. Several autoregressive modeling techniques were considered: autoregressive models (AR), autoregressive moving average models (ARMA), and autoregressive models with exogenous input (ARX). The following classification methods were used: logistic regression (LR), linear discriminant analysis (LDA) and support vector machines (SVM). 20 patients on weaning trials from mechanical ventilation were analyzed. The patients, submitted to two different levels of PSV, were classified as low PSV and high PSV. The variability of the respiratory patterns of these patients were analyzed. The most relevant parameters were extracted using the classifiers methods. The best results were obtained with the interquartile range and the final prediction errors of AR, ARMA and ARX models. An accuracy of 95% (93% sensitivity and 90% specificity) was obtained when the interquartile range of the expiratory time and the breath duration time series were used a LDA model. All classifiers showed a good compromise between sensitivity and specificity., Uno de los problemas más difíciles en cuidados intensivos sigue siendo el proceso de interrupción de la ventilación mecánica, denominado proceso de destete. Tanto un retraso innecesario en el proceso de interrupción como un ensayo de destete demasiado precoz son indeseables. En este estudio, analizamos la variabilidad del patrón respiratorio utilizando la señal de volumen respiratorio de pacientes sometidos a dos niveles diferentes de ventilación con presión de soporte (PSV), antes de la retirada de la ventilación mecánica. Para caracterizar el patrón respiratorio, se analizaron las siguientes series temporales: tiempo inspiratorio, tiempo espiratorio, duración de la respiración, volumen corriente, tiempo inspiratorio fraccional, flujo inspiratorio medio y respiración rápida superficial. Se consideraron varias técnicas de modelización autorregresiva: modelos autorregresivos (AR), modelos autorregresivos de medias móviles (ARMA) y modelos autorregresivos con entrada exógena (ARX). Se utilizaron los siguientes métodos de clasificación: regresión logística (LR), análisis discriminante lineal (LDA) y máquinas de vectores soporte (SVM). Se analizaron 20 pacientes en ensayos de destete de la ventilación mecánica. Los pacientes, sometidos a dos niveles diferentes de PSV, se clasificaron como PSV baja y PSV alta. Se analizó la variabilidad de los patrones respiratorios de estos pacientes. Se extrajeron los parámetros más relevantes utilizando los métodos clasificadores. Los mejores resultados se obtuvieron con el rango intercuartílico y los errores finales de predicción de los modelos AR, ARMA y ARX. Se obtuvo una precisión del 95% (93% de sensibilidad y 90% de especificidad) cuando el rango intercuartílico del tiempo espiratorio y las series temporales de duración de la respiración se utilizaron un modelo LDA. Todos los clasificadores mostraron un buen compromiso entre sensibilidad y especificidad.

One objective of mechanical ventilation is the recovery of spontaneous breathing as soon as possible. Remove the mechanical ventilation is sometimes more difficult that maintain it. This paper proposes the study of respiratory flow signal of patients on weaning trials process by autoregressive moving average model (ARMA), through the location of poles and zeros of the model. A total of 151 patients under extubation process (T-tube test) were analyzed: 91 patients with successful weaning (GS), 39 patients that failed to maintain spontaneous breathing and were reconnected (GF), and 21 patients extubated after the test but before 48 hours were reintubated (GR). The optimal model was obtained with order 8, and statistical significant differences were obtained considering the values of angles of the first four poles and the first zero. The best classification was obtained between GF and GR, with an accuracy of 75.3% on the mean value of the angle of the first pole.

Background Weaning patients from mechanical ventilation is an important problem in intensive care units. Weaning is usually conducted in an empirical manner, and a standardized approach has not been developed. Methods We carried out a prospective, randomized, multicenter study involving 546 patients who had received mechanical ventilation for a mean (±SD) of 7.5±6.1 days and who were considered by their physicians to be ready for weaning. One hundred thirty patients had respiratory distress during a two-hour trial of spontaneous breathing. These patients were randomly assigned to undergo one of four weaning techniques: intermittent mandatory ventilation, in which the ventilator rate was initially set at a mean (±SD) of 10.0±2.2 breaths per minute and then decreased, if possible, at least twice a day, usually by 2 to 4 breaths per minute (29 patients); pressure-support ventilation, in which pressure support was initially set at 18.0±6.1 cm of water and then reduced, if possible, by 2 to 4 cm of water at le...

Weaning trials process of patients in intensive care units is a complex clinical procedure. 153 patients under extubation process (T-tube test) were studied: 94 patients with successful trials (group S), 38 patients who failed to maintain spontaneous breathing and were reconnected (group F), and 21 patients with successful test but that had to be reintubated before 48 hours (group R). The respiratory pattern of each patient was characterized through the following time series: inspiratory time (T(I)), expiratory time (T(E)), breathing cycle duration (T(Tot)), tidal volume (V(T)), inspiratory fraction (T(I)/T(Tot)), half inspired flow (V(T)/T(I)), and rapid shallow index (f/V(T)), where ƒ is respiratory rate. Using techniques as autoregressive models (AR), autoregressive moving average models (ARMA) and autoregressive models with exogenous input (ARX), the most relevant parameters of the respiratory pattern were obtained. We proposed the evaluation of these parameters using classifiers as logistic regression (LR), linear discriminant analysis (LDA), support vector machines (SVM) and classification and regression tree (CART) to discriminate between patients from groups S, F and R. An accuracy of 93% (98% sensitivity and 82% specificity) has been obtained using CART classification.

Autonomic nervous system regulates the behavior of cardiac and respiratory systems. Its assessment during the ventilator weaning can provide information about physio-pathological imbalances. This work proposes a non linear analysis of the complexity of the heart rate variability (HRV) and breathing duration (T Tot ) applying recurrence plot (RP) and their interaction joint recurrence plot (JRP). A total of 131 patients on weaning trials from mechanical ventilation were analyzed: 92 patients with successful weaning (group S) and 39 patients that failed to maintain spontaneous breathing (group F). The results show that parameters as determinism (DET), average diagonal line length (L), and entropy (ENTR), are statistically significant with RP for T Tot series, but not with HRV. When comparing the groups with JRP, all parameters have been relevant. In all cases, mean values of recurrence quantification analysis are higher in the group S than in the group F. The main differences between groups were found on the diagonal and vertical structures of the joint recurrence plot.

Several modalities of ventilatory support have been proposed to gradually withdraw patients from mechanical ventilation, but their respective effects on the outcome of weaning from mechanical ventilation are not known. We conducted a randomized trial in three intensive care units in mechanically ventilated patients who met standard weaning criteria. Those who could not sustain 2 h of spontaneous breathing were randomly assigned to be weaned with T-piece trials, with synchronized intermittent mandatory ventilation (SIMV), or with pressure support ventilation (PSV). Specific criteria for performing tracheal extubation were defined for each modality. The number of patients who could not be separated from the ventilator at 21 d (i.e., who failed to wean) was compared between the groups. Patients in whom tracheal intubation was required in a 48-h period following extubation were also classified as failures. Among 456 mechanically ventilated patients who met weaning criteria, 109 entered into the study (35 with T piece, 43 with SIMV, and 31 with PSV). The three groups were comparable in terms of etiology of disease or characteristics at entry in the study. When all causes for weaning failure were considered, a lower number of failures was found with PSV than with the other two modes, with the difference just reaching the level of significance (23% for PSV, 43% for T piece, 42% for SIMV; p = 0.05). After excluding patients whose weaning was terminated for complications unrelated to the weaning process, the difference became highly significant (8% for PSV versus 33% and 39%, p < 0.025).(ABSTRACT TRUNCATED AT 250 WORDS)

Little information exists regarding the proportion of patients treated with mechanical ventilation in intensive care units (ICUs), their underlying disease states, the modes of ventilation used, duration of ventilator support, methods and time required for weaning, and mortality in these patients. We carried out a cross-sectional multicenter study in 47 medical-surgical ICUs in Spain to investigate these issues in 290 patients who required mechanical ventilation for at least 24 hs. Relative frequency of different modes was as follows: assist-control ventilation (AC), 55%; synchronized intermittent mandatory ventilation (SIMV), 26%; pressure support ventilation (PSV), 8%; SIMV plus PSV, 8%; pressure-controlled ventilation (PCV), 1%; and continuous positive airway pressure (CPAP), 2%. Overall duration of mechanical ventilation was 27.1±1.1 (SE). A variety of techniques were used for weaning: T-tube trials, 24%; SIMV, 18%; PSV, 15%; SIMV plus PSV, 9%; and some combination of two or more methods in succession in 33% of the patients. Time required for weaning using a combination of SIMV and PSV was longer (17.8 days) than with other techniques (about 5 days, p

One of the most challenging problems in intensive care is the process of discontinuing mechanical ventilation, called weaning process. An unnecessary delay in the discontinuation process and an early weaning trial are undesirable. This paper proposes to analysis the respiratory pattern variability of these patients using autoregressive modeling techniques: autoregressive models (AR), autoregressive moving average models (ARMA), and autoregressive models with exogenous input (ARX). A total of 153 patients on weaning trials from mechanical ventilation were analyzed: 94 patients with successful weaning (group S); 38 patients that failed to maintain spontaneous breathing (group F), and 21 patients who had successful weaning trials, but required reintubation in less than 48 h (group R). The respiratory pattern was characterized by their time series. The results show that significant differences were obtained with parameters as model order and first coefficient of AR model, and final prediction error by ARMA model. An accuracy of 86% (84% sensitivity and 86% specificity) has been obtained when using order model and first coefficient of AR model, and mean of breathing duration.

The process of discontinuing mechanical ventilation is called weaning and is one of the most challenging problems in intensive care. An unnecessary delay in the discontinuation process and an early weaning trial are undesirable. This study aims to characterize the respiratory pattern through features that permit the identification of patients' conditions in weaning trials. Three groups of patients have been considered: 94 patients with successful weaning trials, who could maintain spontaneous breathing after 48 h (GSucc); 39 patients who failed the weaning trial (GFail) and 21 patients who had successful weaning trials, but required reintubation in less than 48 h (GRein). Patients are characterized by their cardiorespiratory interactions, which are described by joint symbolic dynamics (JSD) applied to the cardiac interbeat and breath durations. The most discriminating features in the classification of the different groups of patients (GSucc, GFail and GRein) are identified by support vector machines (SVMs). The SVM-based feature selection algorithm has an accuracy of 81% in classifying GSucc versus the rest of the patients, 83% in classifying GRein versus GSucc patients and 81% in classifying GRein versus the rest of the patients. Moreover, a good balance between sensitivity and specificity is achieved in all classifications.