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Introducción: Comparar los scores de gravedad anatómicos y fisiológicos en los pacientes traumáticos ingresados en unidad de cuidados intensivos (UCI) y crear modelos combinados que mejoren su precisión. Método: Estudio prospectivo de cohorte observacional. UCI polivalente de un hospital universitario de 2.o nivel. Se incluyeron los pacientes traumáticos mayores de 16 años ingresados en UCI (n=780). Se comparan los modelos anatómicos (ISS, NISS) con los modelos fisiológicos (T-RTS, APACHE II [APII]), MPM II). La probabilidad de muerte se calculó según metodología TRISS. La discriminación se valoró mediante curvas ROC (ABC [IC 95%]) y la calibración con el estadístico H de Hosmer-Lemeshow. Los modelos combinados se realizaron con metodología de árboles de clasificación tipo Chi Square Automatic Interaction Detection. Resultados: Mortalidad global del 14%. Los modelos fisiológicos son los que presentan mejores valores de discriminación (APII con 0,87 [0,84-0,90]). Todos los modelos tienen una mala calibración (p<0,01). El mejor modelo combinado es el que utiliza APII junto a ISS (0,88 [0,83-0,90]) y encuentra un grupo de pacientes (valores de APII entre 10-17) que necesita la puntuación ISS (punto de corte de 22) para diferenciar entre mortalidad del 7,5% asociada a pacientes mayores con antecedentes patológicos y del 25,0% en pacientes con mayor presencia de TCE. Conclusiones: Los modelos fisiológicos presentan ventajas sobre los anatómicos en los pacientes traumáticos ingresados en UCI. Los pacientes con puntuaciones bajas en los modelos fisiológicos requieren del análisis anatómico de las lesiones para determinar su gravedad

Introduction: The goals of this project were to compare both the anatomic and physiologic severity scores in trauma patients admitted to intensive care unit (ICU), and to elaborate mixed statistical models to improve the precision of the scores. Methods: A prospective study of cohorts. The combined medical/surgical ICU in a secondary university hospital. Seven hundred and eighty trauma patients admitted to ICU older than 16 years of age. Anatomic models (ISS and NISS) were compared and combined with physiological models (T-RTS, APACHE II [APII], and MPM II). The probability of death was calculated following the TRISS method. The discrimination was assessed using ROC curves (ABC [CI 95%]), and the calibration using the Hosmer-Lemeshoẃs H test. The mixed models were elaborated with the tree classification method type Chi Square Automatic Interaction Detection. Results: A 14% global mortality was recorded. The physiological models presented the best discrimination values (APII of 0.87 [0.84-0.90]). All models were affected by bad calibration (P<.01). The best mixed model resulted from the combination of APII and ISS (0.88 [0.83-0.90]). This model was able to differentiate between a 7.5% mortality for elderly patients with pathological antecedents and a 25% mortality in patients presenting traumatic brain injury, from a pool of patients with APII values ranging from 10 to 17 and an ISS threshold of 22. Conclusions: The physiological models perform better than the anatomical models in traumatic patients admitted to the ICU. Patients with low scores in the physiological models require an anatomic analysis of the injuries to determine their severity

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INTRODUCTION: The goals of this project were to compare both the anatomic and physiologic severity scores in trauma patients admitted to intensive care unit (ICU), and to elaborate mixed statistical models to improve the precision of the scores. METHODS: A prospective study of cohorts. The combined medical/surgical ICU in a secondary university hospital. Seven hundred and eighty trauma patients admitted to ICU older than 16 years of age. Anatomic models (ISS and NISS) were compared and combined with physiological models (T-RTS, APACHE II [APII], and MPM II). The probability of death was calculated following the TRISS method. The discrimination was assessed using ROC curves (ABC [CI 95%]), and the calibration using the Hosmer-Lemeshows H test. The mixed models were elaborated with the tree classification method type Chi Square Automatic Interaction Detection. RESULTS: A 14% global mortality was recorded. The physiological models presented the best discrimination values (APII of 0.87 [0.84-0.90]). All models were affected by bad calibration (P<.01). The best mixed model resulted from the combination of APII and ISS (0.88 [0.83-0.90]). This model was able to differentiate between a 7.5% mortality for elderly patients with pathological antecedents and a 25% mortality in patients presenting traumatic brain injury, from a pool of patients with APII values ranging from 10 to 17 and an ISS threshold of 22. CONCLUSIONS: The physiological models perform better than the anatomical models in traumatic patients admitted to the ICU. Patients with low scores in the physiological models require an anatomic analysis of the injuries to determine their severity.

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OBJETIVO: El objetivo de este estudio fue conocer las características clínicas de los pacientes con sepsis urológica obstructiva por litiasis ureteral que ingresaron en la Unidad de Cuidados Intensivos e identificar los factores predictores de mortalidad en las primeras 24 horas del ingreso. DISEÑO: Estudio observacional retrospectivo durante un periodo de 16 años (1996-2011). ÁMBITO: Unidad de Cuidados Intensivos polivalente de 20 camas de un hospital universitario de 2.° nivel. PACIENTES: Todos los pacientes que ingresaron en Unidad de Cuidados Intensivos por sepsis urológica obstructiva. INTERVENCIONES: Ninguna. VARIABLES DE INTERÉS PRINCIPALES: Variables clínicas y analíticas generales y relacionadas con el proceso urológico. Método diagnóstico, técnica desobstructiva, germen aislado y tratamiento. Análisis de factores de riesgo mediante regresión logística múltiple. RESULTADOS: Ciento siete pacientes ingresados con una mortalidad del 19,6%. El diagnóstico fue mayoritariamente por ecografía y la técnica descompresiva más utilizada fue la colocación de catéter ureteral doble J. Se aisló germen en el 48,6% de los pacientes. El 20,6% presentaron bacteriemia. En el análisis multivariante, la edad, el fallo renal agudo y el uso de drogas vasoactivas en las primeras 24 horas del ingreso se relacionaron de forma independiente con la mortalidad. CONCLUSIONES: La edad avanzada, el fallo renal agudo y la necesidad de fármacos vasoactivos se relacionaron con un aumento de riesgo de mortalidad en los pacientes con urosepsis secundaria a litiasis ureteral

PURPOSE: The aims of this study were to determine the clinical characteristics of patients with urinary sepsis associated to ureteral calculi admitted to the Intensive Care Unit (ICU), and to identify predictors of mortality in the first 24 hours of admission. DESIGN: A retrospective observational study covering a 16-year period (2006-2011) was carried out. SETTING: The combined clinical/surgical ICU of a secondary-level University hospital. PATIENTS: All patients admitted to the ICU due to obstructive urinary sepsis. INTERVENTIONS: None. MAIN VARIABLES: We analyzed general clinical and laboratory test and urological data. The diagnostic technique, affected side, decompression technique, isolated microorganism and antibiotic therapy used were also considered. The assessment of risk factors was performed by multiple logistic regression analysis. RESULTS: A total of 107 patients admitted to the ICU were included in the study, with a mortality rate of 19.6%. The diagnosis was mainly established by ultrasound, and the most commonly used decompression technique was retrograde JJ stenting. Microorganisms were isolated in 48.6% of the patients. In total, 20.6% of the patients had bacteremia. Multivariate analysis found age, acute renal failure and the use of vasoactive drugs administered continuously for the first 24hours of admission to be independently associated to mortality. CONCLUSIONS: Advanced age, acute renal failure and the need for vasoactive drugs were associated to an increased risk of mortality in patients with urinary sepsis associated to upper urinary tract calculi

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Objetivo Conocer las características de los procedimientos de intubación orotraqueal (IOT) en una Unidad de Medicina Intensiva, describir las complicaciones graves relacionadas con el procedimiento y los factores de riesgo asociados a su aparición. Diseño Estudio prospectivo de cohorte, observacional, durante un periodo de 2 años. Ámbito Unidad de Cuidados Intensivos polivalente de un hospital universitario de segundo nivel. Pacientes Se incluyeron todas las IOT (309 procedimientos) realizadas por el intensivista. Intervenciones Ninguna. Variables de interés principal Datos clínicos previos a la IOT, durante y posintubación, motivo de IOT y sus complicaciones. Análisis de factores de riesgo mediante regresión logística múltiple. Resultados El 76% de las IOT se realizaron de forma inmediata. Se llevaron a cabo mayoritariamente por el médico interno residente de la Unidad de Cuidados Intensivos (60%). El 34% de los procedimientos presentaron complicaciones graves con alteración respiratoria (16%), hemodinámica (5%) o ambas (10%). Fallecieron 3 pacientes (1%) y presentaron parada cardiaca el 2% de los casos. El análisis de regresión logística mostró que la edad (OR 1,1; IC 95%: 1,1-1,2), la tensión arterial sistólica≤90mmHg (OR 3,0; IC 95%: 1,4-6,4) y la SapO2≤90% (OR 4,4; IC 95%: 2,3-8,1) previos a la intubación, la presencia de secreciones (OR 2,2; IC 95%: 1,1-4,6) y la necesidad de más de un intento (OR 3,5; IC 95%: 1,4-8,7) fueron factores independientes para la aparición de complicaciones. Conclusiones La IOT del paciente crítico se asocia a complicaciones respiratorias y hemodinámicas. Los factores de riesgo independientes relacionados con la aparición de complicaciones fueron la edad avanzada, la hipotensión, la hipoxemia previa, las secreciones y la necesidad de más de un intento (AU)

Objective A study is made to determine the characteristics of endotracheal intubation (ETI) procedures performed in an Intensive Care Unit, and to describe the associated severe complications and related risk factors. Design A prospective cohort study involving a 2-year period was carried out. Setting The combined clinical/surgical Intensive Care Unit in a secondary university hospital. Patients All ETIs carried out by intensivists were included. Interventions None. Main variables We analyzed the data associated with the patient, the procedure and the postoperative complications after intubation. The study of risk factors was performed using multiple logistic regression analysis. Results Seventy-six percent of the ETIs were performed immediately. Most of them were carried out by Intensive Care Units residents (60%). A total of 34% of the procedures had severe complications, including respiratory (16%) or hemodynamic (5%) disorders, or both (10%). Three patients died (1%), and 2% of the subjects experienced cardiac arrest. Logistic regression analysis identified the following independent risk factors for complications: age (OR 1.1; 95% CI: 1.1-1.2), systolic blood pressure≤90mmHg (OR 3.0; 95% CI: 1.4-6.4) and SpO2≤90% (OR 4.4; 95% CI: 2.3-8.1) prior to intubation, the presence of secretions (OR 2.2; 95% CI: 1.1-4.6), and the need for more than one ETI attempt (OR 3.5; 95% CI: 1.4-8.7).Conclusions ETI in Intensive Care Unit patients is associated with respiratory and hemodynamic complications. The independent risk factors associated with the development of complications were advanced age, hypotension and previous hypoxemia, the presence of secretions, and the need for more than one ETI attempt (AU)

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PURPOSE: The aims of this study were to determine the clinical characteristics of patients with urinary sepsis associated to ureteral calculi admitted to the Intensive Care Unit (ICU), and to identify predictors of mortality in the first 24 hours of admission. DESIGN: A retrospective observational study covering a 16-year period (2006-2011) was carried out. SETTING: The combined clinical/surgical ICU of a secondary-level University hospital. PATIENTS: All patients admitted to the ICU due to obstructive urinary sepsis. INTERVENTIONS: None. MAIN VARIABLES: We analyzed general clinical and laboratory test and urological data. The diagnostic technique, affected side, decompression technique, isolated microorganism and antibiotic therapy used were also considered. The assessment of risk factors was performed by multiple logistic regression analysis. RESULTS: A total of 107 patients admitted to the ICU were included in the study, with a mortality rate of 19.6%. The diagnosis was mainly established by ultrasound, and the most commonly used decompression technique was retrograde JJ stenting. Microorganisms were isolated in 48.6% of the patients. In total, 20.6% of the patients had bacteremia. Multivariate analysis found age, acute renal failure and the use of vasoactive drugs administered continuously for the first 24 hours of admission to be independently associated to mortality. CONCLUSIONS: Advanced age, acute renal failure and the need for vasoactive drugs were associated to an increased risk of mortality in patients with urinary sepsis associated to upper urinary tract calculi.

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OBJECTIVE: A study is made to determine the characteristics of endotracheal intubation (ETI) procedures performed in an Intensive Care Unit, and to describe the associated severe complications and related risk factors. DESIGN: A prospective cohort study involving a 2-year period was carried out. SETTING: The combined clinical/surgical Intensive Care Unit in a secondary university hospital. PATIENTS: All ETIs carried out by intensivists were included. INTERVENTIONS: None. MAIN VARIABLES: We analyzed the data associated with the patient, the procedure and the postoperative complications after intubation. The study of risk factors was performed using multiple logistic regression analysis. RESULTS: Seventy-six percent of the ETIs were performed immediately. Most of them were carried out by Intensive Care Units residents (60%). A total of 34% of the procedures had severe complications, including respiratory (16%) or hemodynamic (5%) disorders, or both (10%). Three patients died (1%), and 2% of the subjects experienced cardiac arrest. Logistic regression analysis identified the following independent risk factors for complications: age (OR 1.1; 95% CI: 1.1-1.2), systolic blood pressure≤90mmHg (OR 3.0; 95% CI: 1.4-6.4) and SpO2≤90% (OR 4.4; 95% CI: 2.3-8.1) prior to intubation, the presence of secretions (OR 2.2; 95% CI: 1.1-4.6), and the need for more than one ETI attempt (OR 3.5; 95% CI: 1.4-8.7). CONCLUSIONS: ETI in Intensive Care Unit patients is associated with respiratory and hemodynamic complications. The independent risk factors associated with the development of complications were advanced age, hypotension and previous hypoxemia, the presence of secretions, and the need for more than one ETI attempt.

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OBJECTIVES: An analysis is made of the characteristics of patients younger than 14 years treated in an adult ICU (AICU), to determine the procedures and techniques required by such patients, and to evaluate the use of the Pediatric Index of Mortality (PIM) in stratifying severity. DESIGN: A retrospective observational study was carried out. SETTING: An AICU of a second level hospital. PATIENTS: We studied 130 patients aged from 1 month to 14 years (average age 6.1±4 years) treated in the AICU from January 1997 to December 2010. VARIABLES OF INTEREST: Clinical-demographic parameters, diagnosis, clinical procedures, PIM score, length of stay, transfer to pediatric ICU (PICU), and mortality. Classification by destination (AICU, PICU) and outcome (alive, dead). PIM and assessment of the diagnostic performance curve (ROC) for mortality. RESULTS: The average age of the patients was 6.1±4 years. Most common diagnoses: trauma (26.9%) and sepsis (22.3%). Main procedures: mechanical ventilation (58.5%), central venous line (74.6%) and vasoactive drugs (20%). A total of 64.6% were transferred to PICU, and the overall mortality was 13%. Patients who stayed in the AICU were older (8.2±4 vs 5.5±4 years, p<0.001), had low morbidity, and their stay was short (44.5±38 hours). The PIM score was significantly higher in the patients who died (60±20 AICU, 38±30 PICU) than in those who survived (4±1 AICU, 9±1 PICU) (p<0.001). ROC curve with AUC=0.91 (95%CI: 0.85 to 0.98). CONCLUSIONS: The PIM score can stratify severity and identify patients at an increased risk of death. Critical child care in the AICU requires the presence of adequate materials and the continuous learning of procedures adapted to pediatric patients in order to ensure adequate care.

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Objetivos. Primero, validar la escala Risk Assessment and Prediction Tool (RAPT) para valorar el tratamiento rehabilitador tras prótesis total de rodilla (PTR) en nuestra población. Y, segundo, utilizando la escala validada, identificar los factores que influyen en la calidad de vida previa y a los 3 meses de la PTR. Método. Estudio prospectivo de todos los pacientes con indicación de PTR ingresados desde enero a julio de 2005 (cohorte 1) y desde enero a julio de 2006 (cohorte 2). Procedimiento de traducción-retrotraducción y validación de la escala RAPT en cohorte 1 (49 pacientes). Se evaluó la calidad de vida mediante EQ-5D y WOMAC. Se realizó un análisis de regresión lineal y logística múltiple en cohorte 2 (106 pacientes) de los factores relacionados con peor calidad de vida. Resultados. La validación de la escala RAPT obtuvo una buena correlación con EQ-5D y WOMAC. En la cohorte 2, los pacientes se clasificaron en 4 grupos según RAPT (medio-alto y bajo) y lugar de residencia (rural y urbano). Un nivel de RAPT medio-alto y vivir en zona rural se relacionó con peor calidad de vida previa y a los 3 meses. En cambio, tener una PTR previa y pareja fueron factores relacionados con mejor calidad de vida previa. Los factores relacionados con peor calidad de vida a los 3 meses fueron ser mujer y la edad avanzada. Conclusiones. La escala RAPT es un instrumento válido, fiable y de fácil aplicación. La escala RAPT y zona de residencia permiten estratificar los pacientes según la calidad de vida y la necesidad de rehabilitación (AU)

Objective. The first objective is to validate the Risk Assessment and Prediction Tool (RAPT) scale to assess rehabilitation therapy after total knee arthroplasty (TKA) in our population. The second objective is to identify the factors that affect quality of life before and at 3 months post-TKA using the validated scale. Method. A prospective study of all patients with TKA admitted to hospital from January to July 2005 (cohort 1) and from January to July 2006 (cohort 2) was performed. The «translation-back-translation» procedure and validation of the RAPT scale in cohort 1 (49 patients) were carried out. Quality of life was assessed with the WOMAC and EQ-5D scales. A lineal regression and multiple logistic analysis was carried out in cohort 2 (106 patients) regarding the factors related to worse quality of life. Results. Validation of the RAPT scale obtained good correlation with the EQ-5D and WOMAC. The cohort 2 patients were classified into 4 groups according RAPT (medium-high and low) and place of residence (rural and urban). Medium-high RAPT level together with rural residence was associated with worse quality of life before and at 3 months post-TKA. Having a previous TKA and living with a partner were factors associated with a better previous quality of life. Older age and female gender were factors associated with worse quality of life at 3 months. Conclusions. The RAPT scale is a valid, reliable, and easy-to-use application. The RAPT scale and area of residence makes it possible to stratify patients according to quality of life and need for rehabilitation (AU)

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Objetivo: Conocer la incidencia y características del trastorno mental (TM) en la UCI y definir una clasificación adaptada al entorno de UCI. Diseño: Estudio descriptivo y retrospectivo. Ámbito: Unidad de Cuidados Intensivos polivalente del Hospital Universitario Arnau de Vilanova de Lérida. Pacientes: Se incluyó 146 pacientes que ingresaron con TM durante un periodo de 5 anos (1 de enero de 2004 a 31 de diciembre de 2008).Variables de interés: Variables generales: clínico-demográficas, diagnóstico, procedimientos, gravedad, estancia y mortalidad. Variables específicas: antecedentes psiquiátricos, screening de tóxicos, valoración psiquiátrica, seguimiento y traslado a centro psiquiátrico. Clasificacióndel TM: 1) intoxicación aguda por sustancias (IS), 2) intento autolítico (IA) y 3) trastorno mental asociado al diagnóstico principal (TA).Resultados: Un total de 146 pacientes con TM (7,8%). Predominio de varones (74%) y más jóvenes(43,9 vs 55,3 anos, p < 0,001). La estancia en la UCI fue más corta (4 días vs 7 días, p < 0,001) y ˜hubo menor mortalidad hospitalaria (17,1 vs 25%, p < 0,05). Sin diferencias en nivel de gravedad pero más incidencia de neumonía (19,9 vs 13,8%, p < 0,05). El grupo IS (24,7%), más jóvenes, el grupo IA (36,3%) con predominio de mujeres y TA (39%) con estancia y mortalidad más altas. La consulta a Psiquiatría se realizó prioritariamente en IA (62,3%).Conclusiones: El TM es un problema relativamente frecuente en UCI. La colaboración con Psiquiatría es minoritaria y debe ser potenciada para conseguir un manejo integral del paciente crítico con TM (AU)

Purpose: To determine the incidence and characteristics of mental disorders (MD) in the Intensive Care Unit (ICU), and to define a classification system adapted to the ICU environment. Design: A retrospective, descriptive analysis. Setting: Intensive Care Unit, Arnau de Vilanova Hospital in Lérida (Spain).Patients: All patients with MD admitted during 5-year period (January, 1 2004 to December 31,2008).Main variables: General variables included clinical-demographic data, diagnostic variables, procedures, severity score, length of stay and mortality. Specific variables included psychiatric history, screening for substance abuse, psychiatric assessment, monitoring and transfer to a psychiatric center. Classification of the MD was as follows: 1) acute substance intoxication(SI); 2) suicide attempts (SA); and 3) MD associated with the main diagnosis (AMD).Results: A total of 146 patients had MD (7.8%); they were predominantly male (74%) and were younger than the general ICU population (43.9 vs. 55.3 years, p < 0.001). The ICU stays of the patients with MDs were shorter (4 days vs. 7 days, p < 0.001), and there was less hospital mortality (17.1 vs. 25%, p < 0.05). They also showed a higher incidence of pneumonia (19.9 vs. 13.8%,p < 0.05), but no differences in the level of severity were observed. The SI group (24.7%) contained the highest number of young people; the SA group (36.3%) showed a predominance of women; and the AMD (39%) group had the longest stays and the highest mortality. Psychiatric consultation was carried out mainly in the SA group (62.3%).Conclusions: MD is a relatively common problem in the ICU. Collaboration with the Psychiatry Department seldom occurs, but must be encouraged to develop fully integrated management of critical patients with MD (AU)

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PURPOSE: To determine the incidence and characteristics of mental disorders (MD) in the Intensive Care Unit (ICU), and to define a classification system adapted to the ICU environment. DESIGN: A retrospective, descriptive analysis. SETTING: Intensive Care Unit, Arnau de Vilanova Hospital in Lérida (Spain). PATIENTS: All patients with MD admitted during 5-year period (January, 1 2004 to December 31, 2008). MAIN VARIABLES: General variables included clinical-demographic data, diagnostic variables, procedures, severity score, length of stay and mortality. Specific variables included psychiatric history, screening for substance abuse, psychiatric assessment, monitoring and transfer to a psychiatric center. Classification of the MD was as follows: 1) acute substance intoxication (SI); 2) suicide attempts (SA); and 3) MD associated with the main diagnosis (AMD). RESULTS: A total of 146 patients had MD (7.8%); they were predominantly male (74%) and were younger than the general ICU population (43.9 vs. 55.3 years, p<0.001). The ICU stays of the patients with MDs were shorter (4 days vs. 7 days, p<0.001), and there was less hospital mortality (17.1 vs. 25%, p<0.05). They also showed a higher incidence of pneumonia (19.9 vs. 13.8%, p<0.05), but no differences in the level of severity were observed. The SI group (24.7%) contained the highest number of young people; the SA group (36.3%) showed a predominance of women; and the AMD (39%) group had the longest stays and the highest mortality. Psychiatric consultation was carried out mainly in the SA group (62.3%). CONCLUSIONS: MD is a relatively common problem in the ICU. Collaboration with the Psychiatry Department seldom occurs, but must be encouraged to develop fully integrated management of critical patients with MD.

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Objetivo: a) establecer qué variables funcionales, de tratamiento y analíticas tienen capacidad pronóstica independiente en pacientes con cáncer en situación de enfermedad terminal; y b) desarrollar una ecuación logística que defina un modelo predictivo útil para un paciente con cáncer terminal. Material y método: estudio prospectivo realizado en pacientes con cáncer avanzado sin tratamiento curativo. Variable dependiente: supervivencia igual o inferior a 30 días; variables independientes: situación funcional, tratamiento, parámetros bioquímicos y hematológicos procedentes de una muestra de sangre periférica y accesibles al médico de cabecera. Análisis estadístico: descriptivo; univariable mediante t de Student y Chi cuadrado y multivariable mediante regresión logística. Paquete SPSS Windows 2000. Resultados: se incluyeron 130 evaluaciones procedentes de 73 pacientes. La edad media fue de 68.89 (DT 11,54). El 60% fueron hombres. Las neoplasias más frecuentes fueron: tubo digestivo 39,2% y pulmón 21,5%. Las variables seleccionadas por el análisis univariable fueron: urea, proteínas totales, albúmina, prealbúmina, beta-globulina, hierro, LDH, ferritina, hematocrito, hemoglobina, leucocitos, neutrófilos, linfocitos, sodio, calcio, KPS y tratamiento con corticoides. Las variables seleccionadas por el análisis multivariable fueron: urea, albúmina, hierro, LDH, leucocitos, neutrófilos, CD8, Corticoides y KPS. La sensibilidad del modelo desarrollado alcanza el 76% y una especificidad del 92%. Valor predictivo positivo de 0,82 y valor predictivo negativo de 0,87%. Conclusión: el análisis conjunto de las variables seleccionadas por el análisis de regresión logística permite generar una ecuación logística que define un modelo predictivo útil para el cálculo de la probabilidad de supervivencia menor o igual a 30 días en pacientes con cáncer en situación de enfermedad terminal (AU)

Aim: a) to know which variables from functional assessment, treatment, or blood samples have prognostic value in advanced cancer patients; and b) to develop a logistic equation able to establish prognosis in advanced cancer patients. Patients and method: a prospective study in advanced cancer patients. Dependent variable: life lasting 30 or fewer days. Independent variables: performance status, treatment, biochemical and hematological parameters from a blood sample available for general practitioners. Statistics: A descriptive analysis – a univariate analysis using Student’s t-test and chisquared test; a multivariate analysis by logistic regression. SPSS Windows 2000. Results: 130 evaluations were included from 73 patients. Main age was 68.89 (DT 11.54). 60% were males. Most frequent tumors included: digestive tract, 39.2%; and lung cancer 21.5%. Variables selected by the univariate analysis were: urea, total protein, albumin, prealbumin, betaglobulin, iron, calcium, LDH, ferritin, hematocrit, hemoglobin, total white blood cell count, neutrophils, lymphocytes, sodium corticoids, and KPS. Variables selected by the multivariate analysis were: urea, albumin, iron, LDH, total white blood cell count, neutrophils, CD8, corticoids, and KPS. The model’s sensitivity was 76%, specificity was 92%. Positive predictive value was 0.82, and negative predictive value was 0.87%. Conclusions: selected variables in the multivariate analysis allow to develop a predictive model that is useful to establish the survival probability at 30 or fewer days for every advanced cancer patient (AU)

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Post-anesthesic parotiditis is a little known entity related with anesthesic procedures but described in any situation that motivates manipulation of the oropharyngeal cavity. Its physiopathological mechanism is not well-defined, although it could have a multifactorial origin. A case of a male who was admitted for post-operative control of brain tumor exeresis and who had preauricular and submaxillary inflammation after a routinely performed tracheostomy is presented. Coincidence with the performing of a tracheostomy required us to propose the differential diagnosis with the complications associated to said surgical act. Post-anesthesic parotiditis, even though it is a rare complication and has no clinical significance, should be kept in mind when there is facial edema after any manipulation of the oropharyngeal cavity.

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La parotiditis postanestésica es una entidad poco conocida, relacionada con procedimientos anestésicos pero descrita ante cualquier situación que motiva una manipulación de la cavidad orofaríngea. Su mecanismo fisiopatológico no está bien definido aunque podría ser de origen multifactorial. Se presenta el caso de un varón que ingresó para control postoperatorio de exéresis de tumor cerebral y que tras una traqueotomía realizada de forma rutinaria presenta una inflamación a nivel preauricular y submaxilar. La coincidencia con la realización de traqueotomía nos obligó a plantearnos el diagnóstico diferencial con las complicaciones asociadas a dicho acto quirúrgico. La parotiditis postanestésica, aun tratándose de una complicación poco frecuente y sin trascendencia clínica, debe tenerse en cuenta ante la aparición de edema facial tras cualquier manipulación de la cavidad orofaríngea

Post-anesthesic parotiditis is a little known entity related with anesthesic procedures but described in any situation that motivates manipulation of the oropharyngeal cavity. Its physiopathological mechanism is not well-defined, although it could have a multifactorial origin. A case of a male who was admitted for post-operative control of brain tumor exeresis and who had preauricular and submaxillary inflammation after a routinely performed tracheostomy is presented. Coincidence with the performing of a tracheostomy required us to propose the differential diagnosis with the complications associated to said surgical act. Post-anesthesic parotiditis, even though it is a rare complication and has no clinical significance, should be kept in mind when there is facial edema after any manipulation of the oropharyngeal cavity

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OBJECTIVE: To compare the ability of an artificial neural network (ANN) to predict hospital mortality with that of the Acute Physiology and Chronic Health Evaluation II (APACHE II) system and multiple logistic regression (LR). A secondary objective was to compare the allocation of individual probability among the models. METHOD: The variables required for calculating the APACHE II were prospectively collected. A total of 1146 patients were divided (randomly 70% and 30%) into the Development (800) and the Validation (346) sets. With the same variables an LR model and an ANN were carried out (a 3-layer perceptron trained by algorithm backpropagation with bootstrap resampling and with 9 nodes in the hidden layer) in the Development set. The models developed were contrasted with the Validation set and their discrimination properties were evaluated using the area under the ROC curve (AUC [95% CI]) and calibration with the Hosmer-Lemeshow C (HLC) test. Differences between the probabilities were evaluated using the Bland-Altman test. RESULTS: The Validation set showed an APACHE II with an AUC = 0.79 (0.75-0.84) and HLC = 11 (p = 0.329); LR model AUC = 0.81 (0.76-0.85) and HLC = 29 (p = 0.0001) and an ANN AUC = 0.82 (0.77-0.86) and HLC = 10 (p = 0.404). The patients with the most important differences in the allocation of probability between LR and ANN (8% of the total) were neurological. The worst results were found in trauma patients with an AUC of not greater than 0.75 in all the models. In respiratory patients, the ANN achieved the best AUC = 0.87 (0.78-0.91). CONCLUSIONS: The ANN was able to stratify hospital mortality risk by using the APACHE II system variables. The ANN tended to achieve better results than LR, since, in order to work, it does not require lineal restrictions or independent variables. Allocation of individual probability differed in each model.

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OBJECTIVE: The objective of this study is to identify the dermatological disorders (DDs) responsible for the most common skin lesions in the ICU, their incidence and their impact on mortality, degree of severity and length of stay in the ICU. DESIGN AND SETTING: We performed a 2-year prospective study in a general medical and surgical ICU including, exceptionally, paediatric cases. PATIENTS: We included all patients who presented skin lesions upon admission or developed them during their ICU stay. RESULTS: Forty-six patients (10% of all admissions) were enrolled, with 51 DDs. SAPS II score (43) and mean length of stay (19 days) were significantly higher than in the general group of ICU admissions. Differences in mortality rates (26% versus 29%) were not statistically significant. CONCLUSIONS: DDs are entities that should be borne in mind in the critically ill patient; their incidence is by no means negligible and makes careful examination of the skin mandatory both on admission and during a patient's ICU stay.

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