Prognostic value of metabolic parameters measured by first responders attending patients with severe trauma: associations with the New Injury Severity Score and mortality. / Valor pronóstico de los parámetros metabólicos medidos en la asistencia inicial a pacientes con trauma grave: asociación con la puntuación de la escala NISS y la mortalidad.

OBJECTIVES: Patients with severe or potentially severe trauma must be identified early, a challenge in prehospital settings. This study aimed to analyze the possible diagnostic and prognostic usefulness of analytical markers recorded in the early moments of care. MATERIAL AND METHODS: Observational study of information extracted from the prospective multicenter Code Trauma database for 2016-2019, excluding data for isolated head injuries. Using the New Injury Severity Score (NISS), we classified cases into 4 levels of severity. NISS and mortality were considered the dependent variables in inferential analyses. We calculated the areas under receiver operating characteristic curves, identified optimal cutoff points (Youden index), and calculated positive (PPV) and negative predictive values.. RESULTS: Of the 1039 trauma patients in the registry, 709 were included in the study. Their mean (SD) age was 40.4 (17.3) years, and 77.3% were men. Motorcycle accidents were the most common causes of trauma (in 21%), and mortality was 12.1%. Lactate concentration, pH, PCO2, hemoglobin concentration, hematocrit, and blood sugar were significantly associated with severity and mortality. The PPVs corresponding to pH for the 4 NISS score groups (34-41, 42-49, 50-59, and $ 60) and mortality, respectively, were 61.2, 64.1, 70.7, 62.2, and 66.6. The PPVs of traditionally used clinical variables were lower. CONCLUSION: Patients with more severe trauma had lower pH values and higher PCO2, lactate, and base excess values. PCO2, pH, and blood sugar findings were the best predictors of severity. Metabolic variables are better predictors than traditionally recorded hemodynamic variables.

OBJETIVO: En entornos de emergencia prehospitalarios, la detección temprana de un paciente con trauma grave o potencialmente crítico es un desafío. El objetivo es analizar las posibilidades diagnósticas y pronóstico de los parámetros analíticos obtenidos en los primeros momentos de la asistencia inicial. METODO: Estudio observacional multicéntrico de la base de datos prospectiva "Código Trauma" de 2016-2019 excluyendo el trauma craneoencefálico aislado. La evaluación de las lesiones se realizó utilizando el New Injury Severity Score (NISS). Los pacientes fueron clasificados en 4 grupos según nivel de gravedad. Para el análisis inferencial, las puntuaciones NISS y el resultado de mortalidad se consideraron variables dependientes. Se realizó el análisis de la curva ROC, puntos de corte óptimos mediante el índice de Youden y se calcularon los valores predictivos positivo (VPP) y negativo. RESULTADOS: De los 1.039 pacientes traumatizados del registro, 709 fueron incluidos en el estudio, con una edad media de 40,4 años (DE 17,3), 77,3% eran varones, el mecanismo lesional principal accidentes de moto (21%) y la mortalidad del 12,1%. El pH, lactato, pCO2, hemoglobina, hematocrito y glucemia influyeron significativamente en gravedad y mortalidad. El VPP de mortalidad para pH fue 61,2, 64,1, 70,7, 62,2 y 66,6 para los grupos de NISS 34- 41, 42-49, 50-59 y $ 60 puntos la mortalidad, respectivamente. Las variables clínicas clásicas obtuvieron valores más bajos. CONCLUSIONES: Los pacientes con mayor gravedad presentaron menor pH y concentraciones más altas de pCO2, lactato y exceso de bases. El pH, la pCO2 y la glucemia tuvieron la mayor capacidad predictiva de gravedad. La capacidad predictiva de los valores metabólicos es superior a la de los valores hemodinámicos clásicos.

Valor pronóstico de los parámetros metabólicos medidos en la asistencia inicial a pacientes con trauma grave: asociación con la puntuación de la escala NISS y la mortalidad / Prognostic value of metabolic parameters measured by first responders attending patients with severe trauma: associations with the New Injury Severity Score and mortality

Objetivos. En entornos de emergencia prehospitalarios, la detección temprana de un paciente con trauma grave o potencialmente crítico es un desafío. El objetivo es analizar las posibilidades diagnósticas y pronóstico de los parámetros analíticos obtenidos en los primeros momentos de la asistencia inicial. Métodos. Estudio observacional multicéntrico de la base de datos prospectiva “Código Trauma” de 2016-2019 excluyendo el trauma craneoencefálico aislado. La evaluación de las lesiones se realizó utilizando el New Injury Severity Score (NISS). Los pacientes fueron clasificados en 4 grupos según nivel de gravedad. Para el análisis inferencial, las puntuaciones NISS y el resultado de mortalidad se consideraron variables dependientes. Se realizó el análisis de la curva ROC, puntos de corte óptimos mediante el índice de Youden y se calcularon los valores predictivos positivo (VPP) y negativo. Resultados. De los 1.039 pacientes traumatizados del registro, 709 fueron incluidos en el estudio, con una edad media de 40,4 años (DE 17,3), 77,3% eran varones, el mecanismo lesional principal accidentes de moto (21%) y la mortalidad del 12,1%. El pH, lactato, pCO2, hemoglobina, hematocrito y glucemia influyeron significativamente en gravedad y mortalidad. El VPP de mortalidad para pH fue 61,2, 64,1, 70,7, 62,2 y 66,6 para los grupos de NISS 34-41, 42-49, 50-59 y $ 60 puntos la mortalidad, respectivamente. Las variables clínicas clásicas obtuvieron valores más bajos. Conclusiones. Los pacientes con mayor gravedad presentaron menor pH y concentraciones más altas de pCO2, lactato y exceso de bases. El pH, la pCO2 y la glucemia tuvieron la mayor capacidad predictiva de gravedad. La capacidad predictiva de los valores metabólicos es superior a la de los valores hemodinámicos clásicos. (AU)

Background and objective: Patients with severe or potentially severe trauma must be identified early, a challenge in prehospital settings. This study aimed to analyze the possible diagnostic and prognostic usefulness of analytical markers recorded in the early moments of care. Methods: Observational study of information extracted from the prospective multicenter Code Trauma database for 2016-2019, excluding data for isolated head injuries. Using the New Injury Severity Score (NISS), we classified cases into 4 levels of severity. NISS and mortality were considered the dependent variables in inferential analyses. We calculated the areas under receiver operating characteristic curves, identified optimal cutoff points (Youden index), and calculated positive (PPV) and negative predictive values. Results: Of the 1039 trauma patients in the registry, 709 were included in the study. Their mean (SD) age was 40.4 (17.3) years, and 77.3% were men. Motorcycle accidents were the most common causes of trauma (in 21%), and mortality was 12.1%. Lactate concentration, pH, PCO2, hemoglobin concentration, hematocrit, and blood sugar were significantly associated with severity and mortality. The PPVs corresponding to pH for the 4 NISS score groups (34-41, 42-49, 50-59, and $ 60) and mortality, respectively, were 61.2, 64.1, 70.7, 62.2, and 66.6. The PPVs of traditionally used clinical variables were lower. Conclusions: Patients with more severe trauma had lower pH values and higher PCO2, lactate, and base excess values. PCO2, pH, and blood sugar findings were the best predictors of severity. Metabolic variables are better predictors than traditionally recorded hemodynamic variables. (AU)

Traumatic Brain Injury and Acute Kidney Injury-Outcomes and Associated Risk Factors.

Our objective was to analyze the contribution of acute kidney injury (AKI) to the mortality of isolated TBI patients and its associated risk factors. Observational, prospective and multicenter registry (RETRAUCI) methods were used, from March 2015 to December 2019. Isolated TBI was defined as abbreviated injury scale (AIS) ≥ 3 head with no additional score ≥ 3. A comparison of groups was conducted using the Wilcoxon test, chi-square test or Fisher's exact test, as appropriate. A multiple logistic regression analysis was conducted to analyze associated risk factors in the development of AKI. For the result, overall, 2964 (30.2%) had AIS head ≥ 3 with no other area with AIS ≥ 3. The mean age was 54.7 (SD 19.5) years, 76% were men, and the ground-level falls was 49.1%. The mean ISS was 18.4 (SD 8). The in-hospital mortality was 22.2%. Up to 310 patients (10.6%) developed AKI, which was associated with increased mortality (39% vs. 17%, adjusted OR 2.2). Associated risk factors (odds ratio (OR) (95% confidence interval)) were age (OR 1.02 (1.01-1.02)), hemodynamic instability (OR 2.87 to OR 5.83 (1.79-13.1)), rhabdomyolysis (OR 2.94 (1.69-5.11)), trauma-associated coagulopathy (OR 1.67 (1.05-2.66)) and transfusion of packed red-blood-cell concentrates (OR 1.76 (1.12-2.76)). In conclusion, AKI occurred in 10.6% of isolated TBI patients and was associated with increased mortality.

Risk Factors Associated with Mortality in Severe Chest Trauma Patients Admitted to the ICU.

Our objective was to determine outcomes of severe chest trauma admitted to the ICU and the risk factors associated with mortality. An observational, prospective, and multicenter registry of trauma patients admitted to the participating ICUs (March 2015-December 2019) was utilized to collect the patient data that were analyzed. Severe chest trauma was defined as an Abbreviated Injury Scale (AIS) value of ≥3 in the thoracic area. Logistic regression analysis was used to evaluate the contribution of severe chest trauma to crude and adjusted ORs for mortality and to analyze the risk factors associated with mortality. Overall, 3821 patients (39%) presented severe chest trauma. The sample's characteristics were as follows: a mean age of 49.88 (19.21) years, male (77.6%), blunt trauma (93.9%), a mean ISS of 19.9 (11.6). Crude and adjusted (for age and ISS) ORs for mortality in severe chest trauma were 0.78 (0.68-0.89) and 0.43 (0.37-0.50) (p < 0.001), respectively. In-hospital mortality in the severe chest trauma patients without significant traumatic brain injury (TBI) was 5.63% and was 25.71% with associated significant TBI (p < 0.001). Age, the severity of injury (NISS and AIS-head), hemodynamic instability, prehospital intubation, acute kidney injury, and multiorgan failure were risk factors associated with mortality. The contribution of severe chest injury to the mortality of trauma patients admitted to the ICU was very low. Risk factors associated with mortality were identified.

Craniectomías descompresivas en el traumatismo craneoencefálico: la visión del intensivista / Decompressive craniectomy in traumatic brain injury: the intensivist's point of view

Objetivo Realizar una escala con parámetros clínicos y radiológicos precoces tras un TCE que identifique a los enfermos que en su evolución posterior van a someterse a una CD. Método Estudio observacional de una cohorte retrospectiva de pacientes que tras un TCE ingresan en la Sección de Neurocríticos del Servicio de Medicina Intensiva de nuestro hospital durante un periodo de 5 años (2014-2018). Detección de variables clínicas y radiológicas y creación de todos los modelos posibles con las variables significativas, clínicamente relevantes y de fácil detección precoz. Selección del que presentaba valores más bajos de criterios de información bayesiano y de Akaike para la creación de la escala. Calibración y validación interna mediante la prueba de bondad de ajuste de Hosmer-Lemeshow y análisis bootstrapping con 1.000 re-muestreos. Resultados Se realizaron 37 CD en 153 enfermos que ingresaron tras un TCE. El modelo final resultante incluía desviación de línea media, GCS y colapso ventricular con un área bajo la curva ROC de 0,84 (IC95% 0,78-0,91) y Hosmer-Lemeshow p=0,71. La escala desarrollada detectaba bien a los enfermos que iban a precisar una CD precoz (en las primeras 24horas) tras un TCE (2,5±0,5) pero no a aquellos que la necesitarían en una fase más tardía de su enfermedad (1,7±0,8). Sin embargo, parece prevenirnos sobre los enfermos que si bien no precisan inicialmente una CD sí tienen probabilidades de necesitarla posteriormente en su evolución (CD tardía vs. no precisan CD, 1,7±0,8 vs. 1±0,7; p=0,002). Conclusión Hemos desarrollado una escala pronóstica que permite detectar en nuestro medio, con una buena sensibilidad y especificidad y usando criterios clínico-radiológicos precoces, aquellos pacientes que tras un TCE van a precisar una CD (AU)

Objetive To perform a score with early clinical and radiological findings after a TBI that identifies the patients who in their subsequent evolution are going to undergo DC. Method Observational study of a retrospective cohort of patients who, after a TBI, enter the Neurocritical Section of the Intensive Care Unit of our hospital for a period of 5 years (2014-2018). Detection of clinical and radiological criteria and generation of all possible models with significant, clinically relevant and easy to detect early variables. Selection of the one with the lowest Bayesian Information Criterion and Akaike Information Criterion values for the creation of the score. Calibration and internal validation of the score using the Hosmer-Lemeshow and a bootstrapping analysis with 1,000 re-samples respectively. Results 37 DC were performed in 153 patients who were admitted after a TBI. The resulting final model included Cerebral Midline Deviation, GCS and Ventricular Collapse with an Area under ROC Curve: 0.84 (95% IC 0.78-0.91) and Hosmer-Lemeshow p=0.71. The developed score detected well those patients who were going to need an early DC (first 24hours) after a TBI (2.5±0.5) but not those who would need it in a later stage of their disease (1.7±0.8). However, it seems to advice us about the patients who, although not requiring an early DC are likely to need it later in their evolution (DC after 24hours vs do not require DC, 1.7±0.8 vs 1±0.7; p=0.002). Conclusion We have developed a prognostic score using early clinical-radiological criteria that, in our environment, detects with good sensitivity and specificity those patients who, after a TBI, will require a DC (AU)

Decompressive craniectomy in traumatic brain injury: The intensivist's point of view.

OBJETIVE: To perform a score with early clinical and radiological findings after a TBI that identifies the patients who in their subsequent evolution are going to undergo DC. METHOD: Observational study of a retrospective cohort of patients who, after a TBI, enter the Neurocritical Section of the Intensive Care Unit of our hospital for a period of 5 years (2014-2018). Detection of clinical and radiological criteria and generation of all possible models with significant, clinically relevant and easy to detect early variables. Selection of the one with the lowest Bayesian Information Criterion and Akaike Information Criterion values for the creation of the score. Calibration and internal validation of the score using the Hosmer-Lemeshow and a bootstrapping analysis with 1000 re-samples respectively. RESULTS: 37 DC were performed in 153 patients who were admitted after a TBI. The resulting final model included Cerebral Midline Deviation, GCS and Ventricular Collapse with an Area under ROC Curve: 0.84 (95% IC 0.78-0.91) and Hosmer-Lemeshow p=0.71. The developed score detected well those patients who were going to need an early DC (first 24h) after a TBI (2.5±0.5) but not those who would need it in a later stage of their disease (1.7±0.8). However, it seems to advice us about the patients who, although not requiring an early DC are likely to need it later in their evolution (DC after 24h vs. do not require DC, 1.7±0.8 vs. 1±0.7; p=0.002). CONCLUSION: We have developed a prognostic score using early clinical-radiological criteria that, in our environment, detects with good sensitivity and specificity those patients who, after a TBI, will require a DC.

Decompressive craniectomy in traumatic brain injury: the intensivist's point of view. / Craniectomías descompresivas en el traumatismo craneoencefálico: la visión del intensivista.

OBJETIVE: To perform a score with early clinical and radiological findings after a TBI that identifies the patients who in their subsequent evolution are going to undergo DC. METHOD: Observational study of a retrospective cohort of patients who, after a TBI, enter the Neurocritical Section of the Intensive Care Unit of our hospital for a period of 5 years (2014-2018). Detection of clinical and radiological criteria and generation of all possible models with significant, clinically relevant and easy to detect early variables. Selection of the one with the lowest Bayesian Information Criterion and Akaike Information Criterion values for the creation of the score. Calibration and internal validation of the score using the Hosmer-Lemeshow and a bootstrapping analysis with 1,000 re-samples respectively. RESULTS: 37 DC were performed in 153 patients who were admitted after a TBI. The resulting final model included Cerebral Midline Deviation, GCS and Ventricular Collapse with an Area under ROC Curve: 0.84 (95% IC 0.78-0.91) and Hosmer-Lemeshow p=0.71. The developed score detected well those patients who were going to need an early DC (first 24hours) after a TBI (2.5±0.5) but not those who would need it in a later stage of their disease (1.7±0.8). However, it seems to advice us about the patients who, although not requiring an early DC are likely to need it later in their evolution (DC after 24hours vs do not require DC, 1.7±0.8 vs 1±0.7; p=0.002). CONCLUSION: We have developed a prognostic score using early clinical-radiological criteria that, in our environment, detects with good sensitivity and specificity those patients who, after a TBI, will require a DC.

Early prognostic value of an Algorithm based on spectral Variables of Ventricular fibrillAtion from the EKG of patients with suddEn cardiac death: A multicentre observational study (AWAKE).

OBJECTIVE: Ventricular fibrillation (VF)-related sudden cardiac death (SCD) is a leading cause of mortality and morbidity. Current biological and imaging parameters show significant limitations on predicting cerebral performance at hospital admission. The AWAKE study (NCT03248557) is a multicentre observational study to validate a model based on spectral ECG analysis to early predict cerebral performance and survival in resuscitated comatose survivors. METHODS: Data from VF ECG tracings of patients resuscitated from SCD will be collected using an electronic Case Report Form. Patients can be either comatose (Glasgow Coma Scale - GCS - ≤8) survivors undergoing temperature control after return of spontaneous circulation (RoSC), or those who regain consciousness (GCS=15) after RoSC; all admitted to Intensive Cardiac Care Units in 4 major university hospitals. VF tracings prior to the first direct current shock will be digitized and analyzed to derive spectral data and feed a predictive model to estimate favorable neurological performance (FNP). The results of the model will be compared to the actual prognosis. RESULTS: The primary clinical outcome is FNP during hospitalization. Patients will be categorized into 4 subsets of neurological prognosis according to the risk score obtained from the predictive model. The secondary clinical outcomes are survival to hospital discharge, and FNP and survival after 6 months of follow-up. The model-derived categorisation will be also compared with clinical variables to assess model sensitivity, specificity, and accuracy. CONCLUSIONS: A model based on spectral analysis of VF tracings is a promising tool to obtain early prognostic data after SCD.

Early prognostic value of an Algorithm based on spectral Variables of Ventricular fibrillAtion from the EKG of patients with suddEn cardiac death: A multicentre observational study (AWAKE) / Valor pronóstico precoz de un algoritmo basado en variables espectrales de la fibrilación ventricular del ECG de pacientes con muerte súbita cardiaca: estudio observacional multicéntrico (AWAKE)

Abstract Objective: Ventricular fibrillation (VF)-related sudden cardiac death (SCD) is a leading cause of mortality and morbidity. Current biological and imaging parameters show significant limitations on predicting cerebral performance at hospital admission. The AWAKE study (NCT03248557) is a multicentre observational study to validate a model based on spectral ECG analysis to early predict cerebral performance and survival in resuscitated comatose survivors. Methods: Data from VF ECG tracings of patients resuscitated from SCD will be collected using an electronic Case Report Form. Patients can be either comatose (Glasgow Coma Scale GCS --- ≤8) survivors undergoing temperature control after return of spontaneous circulation (RoSC), or those who regain consciousness (GCS = 15) after RoSC; all admitted to Intensive Cardiac Care Units in 4 major university hospitals. VF tracings prior to the first direct current shock will be digitized and analyzed to derive spectral data and feed a predictive model to estimate favorable neurological performance (FNP). The results of the model will be compared to the actual prognosis. Results: The primary clinical outcome is FNP during hospitalization. Patients will be categorized into 4 subsets of neurological prognosis according to the risk score obtained from the predictive model. The secondary clinical outcomes are survival to hospital discharge, and FNP and survival after 6 months of follow-up. The model-derived categorisation will be also compared with clinical variables to assess model sensitivity, specificity, and accuracy. Conclusions: A model based on spectral analysis of VF tracings is a promising tool to obtain early prognostic data after SCD.

Resumen Objetivo: La muerte súbita (MS) por fibrilación ventricular (FV) es una importante causa de morbilidad y mortalidad. Los métodos biológicos y de imagen actuales muestran limitaciones para predecir el pronóstico cerebral al ingreso hospitalario. AWAKE es un estudio observacional, multicéntrico, con el objetivo de validar un modelo basado en el análisis espectral del elec- trocardiograma (ECG), que predice precozmente el pronóstico cerebral y la supervivencia en pacientes resucitados y en estado de coma. Métodos: Se recogerán datos de los ECG con FV de pacientes reanimados de MS. Los pacientes pueden ser tanto supervivientes en estado de coma (Glasgow Coma Scale GCS ≤ 8) sometidos a control de temperatura tras la recuperación de circulación espontánea (RCE), como aquellos que recuperan la consciencia (GCS = 15) tras RCE; todos ellos ingresados en unidades de terapia intensiva cardiológica de 4 hospitales de referencia. Los registros de FV previos al primer choque se digitalizarán y analizarán para obtener datos espectrales que se incluirán en un modelo predictivo que estime el pronóstico neurológico favorable (PNF). El resultado del modelo se comparará con el pronóstico real. Resultados: El objetivo principal es el PNF durante la hospitalización. Los pacientes se categorizarán en 4 subgrupos de pronóstico neurológico según la estimación de riesgo obtenida en el modelo predictivo. Los objetivos secundarios son supervivencia al alta hospitalaria, y PNF y supervivencia a los 6 meses. El resultado de este modelo también se comparará con el pronóstico según variables clínicas. Conclusiones: Un modelo basado en el análisis espectral de registros de FV es una herramienta prometedora para obtener datos pronósticos precoces tras MS por FV.

Falta de asociación entre las concentraciones de radón en el domicilio y el cáncer de pulmón en Cantabria / No evidence of a link between household radon concentrations and lung cancer in Cantabria, Spain

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Bacteriemia, neumonía y meningitis por Streptococcus constellatum / Bacteremia, pneumonia and meningitis due to Streptococcus constellatum

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