ABSTRACT
Introducción. La pandemia de la obesidad junto con la pandemia de gripe puede dar lugar a una importante carga de enfermedad. El índice de masa corporal (IMC) no correlaciona adecuadamente con el porcentaje de grasa corporal. El CUN-BAE es un estimador de grasa corporal para caucásicos que incluye el IMC, el sexo y la edad. El objeto de este trabajo es valorar la fracción atribuible poblacional de ingreso hospitalario por gripe debido a la grasa corporal medida con el IMC y el CUN-BAE. Metodología. Estudio multicéntrico de casos y controles. Los casos fueron ingresos hospitalarios con confirmación de gripe por PCR-RT entre 2009-2011. Empleando IMC o CUN-BAE, para cada categoría de adiposidad se calculó el riesgo de hospitalización por gripe mediante regresión logística condicional, y se estimó la fracción atribuible poblacional en el total de la muestra, en no vacunados y en menores de 65 años. Resultados. Se incluyeron 472 casos hospitalizados y 493 controles. La ORa de hospitalización por gripe, en comparación con el normopeso, se incrementó con cada nivel de IMC (ORa=1,26; 2,06 y 11,64) y de CUN-BAE (ORa=2,78; 4,29; 5,43 y 15,18). La fracción atribuible poblacional de hospitalización por gripe del CUN-BAE fue 3 veces superior que la estimada con el IMC (0,72 vs. 0,27), siendo similares las diferencias encontradas en no vacunados y en menores de 65 años. Conclusión. El IMC podría estar infraestimando la carga de enfermedad atribuible a la obesidad en la hospitalización por gripe. Se debería valorar adecuadamente el impacto de la obesidad y los criterios de recomendación vacunal
Introduction. The obesity pandemic together with the influenza pandemic could lead to a significant burden of disease. The body mass index (BMI) does not discriminate obesity appropriately. The CUN-BAE has recently been used as an estimate of body fatness for Caucasians, including BMI, gender, and age. The aim of this study is to assess the population attributable fraction of hospital admissions due to influenza, due to the body fatness measured with the BMI, and the CUN-BAE. Methods. A multicentre study was conducted using matched case-controls. Cases were hospital admissions with the influenza confirmed by the RT-PCR method between 2009 and 2011. The risk of hospital admission and the population attribuible fraction were calculated using the BMI or the CUN-BAE for each adiposity category in a conditional logical regression analysis adjusted for confounding variables. The analyzes were estimated in the total sample, in unvaccinated people, and those less than 65 years-old. Results. A total of 472 hospitalised cases and 493 controls were included in the study. Compared to normal weight, the aOR of influenza hospital admissions increases with each level of BMI (aOR=1.26; 2.06 and 11.64) and CUN-BAE (aOR=2.78; 4.29; 5.43 and 15.18). The population attributable fraction of influenza admissions using CUN-BAE is 3 times higher than that estimated with BMI (0,72 vs. 0,27), with the differences found being similar the non-vaccinated and under 65 year-olds. Conclusion. The BMI could be underestimating the burden of disease attributable to obesity in individuals hospitalised with influenza. There needs to be an appropriate assessment of the impact of obesity and vaccine recommendation criteria
Subject(s)
Humans , Male , Female , Middle Aged , Obesity/complications , Influenza, Human/diagnosis , Body Mass Index , Case-Control Studies , Adiposity/physiology , Logistic ModelsABSTRACT
INTRODUCTION: The obesity pandemic together with the influenza pandemic could lead to a significant burden of disease. The body mass index (BMI) does not discriminate obesity appropriately. The CUN-BAE has recently been used as an estimate of body fatness for Caucasians, including BMI, gender, and age. The aim of this study is to assess the population attributable fraction of hospital admissions due to influenza, due to the body fatness measured with the BMI, and the CUN-BAE. METHODS: A multicentre study was conducted using matched case-controls. Cases were hospital admissions with the influenza confirmed by the RT-PCR method between 2009 and 2011. The risk of hospital admission and the population attribuible fraction were calculated using the BMI or the CUN-BAE for each adiposity category in a conditional logical regression analysis adjusted for confounding variables. The analyzes were estimated in the total sample, in unvaccinated people, and those less than 65 years-old. RESULTS: A total of 472 hospitalised cases and 493 controls were included in the study. Compared to normal weight, the aOR of influenza hospital admissions increases with each level of BMI (aOR=1.26; 2.06 and 11.64) and CUN-BAE (aOR=2.78; 4.29; 5.43 and 15.18). The population attributable fraction of influenza admissions using CUN-BAE is 3 times higher than that estimated with BMI (0,72 vs. 0,27), with the differences found being similar the non-vaccinated and under 65 year-olds. CONCLUSION: The BMI could be underestimating the burden of disease attributable to obesity in individuals hospitalised with influenza. There needs to be an appropriate assessment of the impact of obesity and vaccine recommendation criteria.
Subject(s)
Body Mass Index , Hospitalization/statistics & numerical data , Influenza, Human/epidemiology , Obesity/epidemiology , Age Factors , Aged , Case-Control Studies , Cost of Illness , Female , Humans , Influenza Vaccines/administration & dosage , Influenza, Human/diagnosis , Male , Middle Aged , Regression Analysis , Reverse Transcriptase Polymerase Chain ReactionABSTRACT
OBJECTIVE: To assess reproducibility in data collection and its influence on the calculation of the severity scoring and mortality risk in APACHE II, APACHE III adapted for Spain and SAPS II. DESIGN: Multicenter, prospective, observational cohort study. SETTING: Nine Spanish Intensive Care Units (ICUs). PATIENTS: 1,211 consecutive patients admitted during the study period were included. Those patients under 16 years of age, those with a stay in the ICU of less than 24 hours, those admitted for scheduled pacemaker implant and those readmitted to the ICU within the same hospital admission were excluded. INTERVENTION: None. ENDPOINTS OF INTEREST: The data needed to calculate the severity and mortality risk scores were collected. A total of 10% of the patients were chosen by simple random sampling and the same data were collected by an independent group of intensive care physicians. Finally, the data obtained by the two groups of intensivists were compared. RESULTS: Significant differences were detected in the acute physiology score (APS) and severity score used for the calculation of APACHE III and SAPS II, and the predicted risk of death calculated for SAPS II. The percentage of agreement on admission diagnosis to the ICU was 50% for both APACHE II and III models. Nonetheless, in most of the patients (76.58% for APACHE II and 79.82% for APACHE III), the difference in the predicted risk of death due to the different assignation of diagnoses on admission to the ICU was less than 10%. CONCLUSIONS: In this study, APS was the most influential factor on the reproducibility of severity scores and risk of death prediction. Admission diagnosis assignment had no significant impact on the reproducibility of the predicted mortality risk.
Subject(s)
APACHE , Intensive Care Units , Humans , Middle Aged , Prospective Studies , Reproducibility of Results , SpainABSTRACT
Objetivo. Evaluar la reproducibilidad en la recogida de datos y su influencia en el cálculo de la gravedad y del riesgo predicho de muerte para los modelos APACHE II, APACHE III adaptado para España y SAPS II. Diseño. Estudio multicéntrico, prospectivo y observacional de cohortes. Ámbito. Nueve Unidades de Cuidados Intensivos (UCI) en España. Pacientes. Inclusión consecutiva de los pacientes ingresados en el período de estudio. Se excluyeron los pacientes menores de 16 años, con estancia en UCI menor de 24 horas, los ingresados para implante programado de marcapasos y los reingresados en UCI dentro del mismo ingreso hospitalario. Intervención. Ninguna. Variables de interés principales. Se recogieron los datos necesarios para el cálculo de las puntuaciones de gravedad y del riesgo predicho de muerte. Se seleccionaron el 10% de los pacientes por muestreo aleatorio simple y se recogieron los mismos datos por un grupo independiente de intensivistas. Finalmente se compararon los datos recogidos por los dos grupos de intensivistas. Resultados. Se encontraron diferencias significativas en el APS (acute physiology score) y puntuación de gravedad calculados para el APACHE III y SAPS II, y en el riesgo de muerte predicho por SAPS II. El porcentaje de acuerdos en el diagnóstico de ingreso en UCI fue del 50% para los modelos APACHE II y III. En la mayoría de los pacientes (76,58% en el APACHE II y 79,82% en el APACHE III) la diferencia en el riesgo predicho de muerte debido a la diferente asignación del diagnóstico de ingreso en UCI fue menor del 10%. Conclusiones. En este estudio el APS se mostró como el factor más influyente en la reproducibilidad de los índices de gravedad y del cálculo del riesgo predicho de muerte. El diagnóstico de ingreso en UCI no mostró un impacto importante en la reproducibilidad del riesgo predicho de muerte
Objective. To assess reproducibility in data collection and its influence on the calculation of the severity scoring and mortality risk in APACHE II, APACHE III adapted for Spain and SAPS II. Design. Multicenter, prospective, observational cohort study. Setting. Nine Spanish Intensive Care Units (ICUs). Patients. 1,211 consecutive patients admitted during the study period were included. Those patients under 16 years of age, those with a stay in the ICU of less than 24 hours, those admitted for scheduled pacemaker implant and those readmitted to the ICU within the same hospital admission were excluded. Intervention. None. Endpoints of interest. The data needed to calculate the severity and mortality risk scores were collected. A total of 10% of the patients were chosen by simple random sampling and the same data were collected by an independent group of intensive care physicians. Finally, the data obtained by the two groups of intensivists were compared. Results. Significant differences were detected in the acute physiology score (APS) and severity score used for the calculation of APACHE III and SAPS II, and the predicted risk of death calculated for SAPS II. The percentage of agreement on admission diagnosis to the ICU was 50% for both APACHE II and III models. Nonetheless, in most of the patients (76.58% for APACHE II and 79.82% for APACHE III), the difference in the predicted risk of death due to the different assignation of diagnoses on admission to the ICU was less than 10%. Conclusions. In this study, APS was the most influential factor on the reproducibility of severity scores and risk of death prediction. Admission diagnosis assignment had no significant impact on the reproducibility of the predicted mortality risk
Subject(s)
Humans , Quality Assurance, Health Care/methods , APACHE , Hospital Mortality/trends , Quality Indicators, Health Care/statistics & numerical data , Reproducibility of Results , Intensive Care Units/organization & administration , Prospective Studies , Diagnosis-Related Groups/statistics & numerical dataABSTRACT
A 2-h T-tube trial of spontaneous breathing was used in selecting patients ready for extubation and discontinuation of mechanical ventilation. However, some doubt remains as to whether it is the most appropriate method of performing a spontaneous breathing trial. We carried out a prospective, randomized, multicenter study involving patients who had received mechanical ventilation for more than 48 h and who were considered by their physicians to be ready for weaning according to clinical criteria and standard weaning parameters. Patients were randomly assigned to undergo a 2-h trial of spontaneous breathing in one of two ways: with a T-tube system or with pressure support ventilation of 7 cm H2O. If a patient had signs of poor tolerance at any time during the trial, mechanical ventilation was reinstituted. Patients without these features at the end of the trial were extubated. Of the 246 patients assigned to the T-tube group, 192 successfully completed the trial and were extubated; 36 of them required reintubation. Of the 238 patients in the group receiving pressure support ventilation, 205 were extubated and 38 of them required reintubation. The percentage of patients who remained extubated after 48 h was not different between the two groups (63% T-tube, 70% pressure support ventilation, p = 0.14). The percentage of patients falling the trial was significantly higher when the T-tube was used (22 versus 14%, p = 0.03). Clinical evolution during the trial was not different in patients reintubated and successfully extubated. ICU mortality among reintubated patients was significantly higher than in successfully extubated patients (27 versus 2.6%, p < 0.001). Spontaneous breathing trials with pressure support or T-tube are suitable methods for successful discontinuation of ventilator support in patients without problems to resume spontaneous breathing.
