Perfil de tromboelastometría rotacional (ROTEM) en una cohorte de asistolia no controlada / Rotational thromboelastometry (ROTEM) profile in a cohort of asystole donors

Introducción: La hipoperfusión juega un papel central en el shock, y es un desencadenante de la coagulopatía. El estudio del perfil ROTEM durante la parada cardíaca prolongada podría ofrecer nuevos conocimientos sobre la fisiopatología de la coagulopatía por shock. Objetivo: Describir el perfil de tromboelastometría rotacional en una cohorte de donantes en asistolia y determinar la incidencia de hiperfibrinólisis. Diseño: Cohortes prospectivo. Incluimos 18 pacientes ingresados tras parada cardíaca extrahospitalaria no recuperada. Se recopiló el primer ritmo cardíaco registrado, los tiempos de parada y los de asistencia. Al ingreso se realizaron test de coagulación convencional y ROTEM (EXTEM, APTEM, FIBTEM) en los 30min tras la obtención de la muestra. Ámbito: El estudio se llevó a cabo en un hospital de tercer nivel incluido en un programa de donación en asistolia. Participantes: Pacientes en parada cardíaca extrahospitalaria no recuperada. Resultados: La mediana de edad fue de 50años y 14 de los participantes eran hombres (77,8%). La mediana de tiempo (rango intercuartílico) desde la parada hasta la obtención de muestras fue de 91min (75-104). Los resultados de la coagulación fueron: INR 1,25 (1,19-1,34), TTPA 55s (45-73) y fibrinógeno 161mg/dl (95-295). Los resultados del ROTEM (APTEM): CT 126s (104-191), CFT 247s (203-694). En 15 (83,3%) se cumplió el criterio de hiperfibrinólisis. También se observó mejoría del MCF en APTEM frente a EXTEM. Tiempos más prolongados se asociaron con niveles inferiores de fibrinógeno y un MCF FIBTEM inferior (p<0,05). Conclusiones: El análisis ROTEM mostró una profunda alteración en la formación del coágulo junto con alta incidencia de hiperfibrinólisis

Background: Hypoperfusion plays a central role in shock states, and has been proposed as a coagulopathy trigger. The study of the rotational thromboelastometry (ROTEM) profile during cardiac arrest could offer new insights to the role of hypoperfusion in coagulation during shock states. Outcome: To describe the ROTEM profile in a cohort of asystole donors and elucidate the incidence of hyperfibrinolysis. Design: A prospective observational study was carried out in 18 patients consecutively admitted to the ICU after out-of-hospital non-recovered cardiac arrest (CA). Initial rhythm and time between CA and admission were recorded. Conventional coagulation and ROTEM (EXTEM, APTEM, FIBTEM) tests were performed within 30minutes after blood sample collection. Scope: An asystole donor reference hospital. Participants: Patients admitted to the ICU after out-of-hospital non-recovered CA. Results: The median age was 50years, and 14 of the patients were men (77.8%). The time from CA to hospital admission expressed as the median (interquartile range) was 91minutes (75-104). The results of the routine tests were: INR 1.25 (1.19-1.34), aPTT 55s (45-73) and fibrinogen 161mg/dl (95-295). For the ROTEM APTEM assay the results were: CT 126s (104-191), CFT 247s (203-694). Hyperfibrinolysis criteria were recorded in 15 patients (83.3%). In addition, MCF improved in APTEM versus EXTEM. Prolonged CA times were associated to lower fibrinogen levels and lower values for MCF FIBTEM (P<.05). Conclusions: The ROTEM assays revealed severe alterations of the clot formation parameters and a high incidence of hyperfibrinolysis

Predicción de hemorragia masiva a nivel extrahospitalario: validación de seis escalas / Prediction of massive bleeding in a prehospital setting: validation of six scoring systems

Objetivo: Validar a nivel extrahospitalario la capacidad diagnóstica de seis escalas de predicción para hemorragia masiva. Diseño: Cohorte retrospectiva. Ámbito: Atención extrahospitalaria del paciente con enfermedad traumática grave. Participantes: Pacientes mayores de 15 años, que han sufrido un trauma grave (definido por los criterios de código 15), atendidos en el medio extrahospitalario por un servicio de atención sanitaria de emergencias desde enero de 2010 hasta diciembre de 2015 y trasladados a un centro hospitalario de alta complejidad en Madrid. Variables de interés principales: Se validaron las siguientes escalas: 1. Trauma Associated Severe Haemorrhage score. 2. Assessment of Blood Consumption Score. 3. Emergency Transfusion Score. 4. Índice de Shock. 5. Prince of Wales Hospital/Rainer Score. 6. Larson Score. Resultados: Se estudiaron 548 pacientes, el 76,8% (420) fueron hombres, una edad mediana de 38 (rango intercuartil [RIC]: 27-50). Injury Severity Score de 18 (RIC: 9-29). El trauma cerrado fue el 82,5% (452). La frecuencia global de HM fue de 9,2% (48), días de estancia en UCI de 2,1 (RIC: 0,8 - 6,2) y una mortalidad hospitalaria del 11,2% (59). La escala con mayor precisión fue la Emergency Transfusion Score (AUC 0,85), en segundo lugar se encuentran Trauma Associated Severe Haemorrhage y Prince of Wales Hospital/Rainer (AUC 0,82); la escala con menor precisión Assessment of Blood Consumption (AUC 0,68). Conclusiones: A nivel extrahospitalario la aplicación de cualquiera de las seis escalas predice la presencia de hemorragia masiva y permite la activación de los protocolos de transfusión masiva mientras el paciente es trasladado a un centro hospitalario

Objective: To validate the diagnostic ability of six different scores to predict massive bleeding in a prehospital setting. Design: Retrospective cohort. Setting: Prehospital attention of patients with severe trauma. Subjects: Subjects with more than 15 years, a history of severe trauma (defined by code 15 criteria), that were initially assisted in a prehospital setting by the emergency services between January 2010 and December 2015 and were then transferred to a level one trauma center in Madrid. Variables: To validate: 1. Trauma Associated Severe Haemorrhage Score. 2. Assessment of Blood Consumption Score. 3. Emergency Transfusión Score. 4. Índice de Shock. 5. Prince of Wales Hospital/Rainer Score. 6. Larson Score. Results: 548 subjects were studied, 76,8% (420) were male, median age was 38 (interquartile range [IQR]: 27-50). Injury Severity Score was 18 (IQR: 9-29). Blunt trauma represented 82,5% (452) of the cases. Overall, frequency of MB was 9,2% (48), median intensive care unit admission days was 2,1 (IQR: 0,8 - 6,2) and hospital mortality rate was 11,2% (59). Emergency Transfusión Score had the highest precisions (AUC 0,85), followed by Trauma Associated Severe Haemorrhage score and Prince of Wales Hospital/Rainer Score (AUC 0,82); Assessment of Blood Consumption Score was the less precise (AUC 0,68). Conclusion: In the prehospital setting the application of any the six scoring systems predicts the presence of massive hemorrhage and allows the activation of massive transfusion protocols while the patient is transferred to a hospital

Prediction of massive bleeding in a prehospital setting: validation of six scoring systems. / Predicción de hemorragia masiva a nivel extrahospitalario: validación de seis escalas.

OBJECTIVE: To validate the diagnostic ability of six different scores to predict massive bleeding in a prehospital setting. DESIGN: Retrospective cohort. SETTING: Prehospital attention of patients with severe trauma. SUBJECTS: Subjects with more than 15 years, a history of severe trauma (defined by code 15 criteria), that were initially assisted in a prehospital setting by the emergency services between January 2010 and December 2015 and were then transferred to a level one trauma center in Madrid. VARIABLES: To validate: 1. Trauma Associated Severe Haemorrhage Score. 2. Assessment of Blood Consumption Score. 3. Emergency Transfusión Score. 4. Índice de Shock. 5. Prince of Wales Hospital/Rainer Score. 6. Larson Score. RESULTS: 548 subjects were studied, 76,8% (420) were male, median age was 38 (interquartile range [IQR]: 27-50). Injury Severity Score was 18 (IQR: 9-29). Blunt trauma represented 82,5% (452) of the cases. Overall, frequency of MB was 9,2% (48), median intensive care unit admission days was 2,1 (IQR: 0,8 - 6,2) and hospital mortality rate was 11,2% (59). Emergency Transfusión Score had the highest precisions (AUC 0,85), followed by Trauma Associated Severe Haemorrhage score and Prince of Wales Hospital/Rainer Score (AUC 0,82); Assessment of Blood Consumption Score was the less precise (AUC 0,68). CONCLUSION: In the prehospital setting the application of any the six scoring systems predicts the presence of massive hemorrhage and allows the activation of massive transfusion protocols while the patient is transferred to a hospital.

Rotational thromboelastometry (ROTEM) profile in a cohort of asystole donors. / Perfil de tromboelastometría rotacional (ROTEM) en una cohorte de asistolia no controlada.

BACKGROUND: Hypoperfusion plays a central role in shock states, and has been proposed as a coagulopathy trigger. The study of the rotational thromboelastometry (ROTEM) profile during cardiac arrest could offer new insights to the role of hypoperfusion in coagulation during shock states. OUTCOME: To describe the ROTEM profile in a cohort of asystole donors and elucidate the incidence of hyperfibrinolysis. DESIGN: A prospective observational study was carried out in 18 patients consecutively admitted to the ICU after out-of-hospital non-recovered cardiac arrest (CA). Initial rhythm and time between CA and admission were recorded. Conventional coagulation and ROTEM (EXTEM, APTEM, FIBTEM) tests were performed within 30minutes after blood sample collection. SCOPE: An asystole donor reference hospital. PARTICIPANTS: Patients admitted to the ICU after out-of-hospital non-recovered CA. RESULTS: The median age was 50years, and 14 of the patients were men (77.8%). The time from CA to hospital admission expressed as the median (interquartile range) was 91minutes (75-104). The results of the routine tests were: INR 1.25 (1.19-1.34), aPTT 55s (45-73) and fibrinogen 161mg/dl (95-295). For the ROTEM APTEM assay the results were: CT 126s (104-191), CFT 247s (203-694). Hyperfibrinolysis criteria were recorded in 15 patients (83.3%). In addition, MCF improved in APTEM versus EXTEM. Prolonged CA times were associated to lower fibrinogen levels and lower values for MCF FIBTEM (P<.05). CONCLUSIONS: The ROTEM assays revealed severe alterations of the clot formation parameters and a high incidence of hyperfibrinolysis.

Predicción de hemorragia masiva. Índice de shock e índice de shock modificado / Prediction of massive bleeding. Shock index and modified shock index

Objetivo: Determinar la capacidad de predicción del índice de shock y del índice de shock modificado para hemorragia masiva tras sufrir un trauma grave. Diseño: Cohorte retrospectiva. Ámbito: Atención inicial hospitalaria al paciente con enfermedad traumática grave en una unidad de cuidados intensivos de trauma de un hospital terciario. Sujetos: Pacientes mayores de 14 años con trauma grave (injury severity score [ISS] >15), admitidos de forma consecutiva desde enero de 2014 hasta diciembre de 2015. Variables: Se estudiaron sensibilidad (Se), especificidad (Sp), valores predictivos positivo y negativo (VP+ y VP-), razones de verosimilitud positiva y negativa (RV+ y RV-), curvas ROC (receiver operating characteristics) y el área bajo las mismas (AUROC) para predicción de hemorragia masiva. Resultados: Se incluyeron 287 pacientes, el 76,31% (219) fueron varones, con una edad media de 43,36 (±17,71) e ISS de 26 (rango intercuartil [RIC]: 21-34). La frecuencia global de hemorragia masiva fue de 8,71% (25). Para el índice de shock se obtuvo: AUROC de 0,89 (intervalo de confianza [IC] 95%: 0,84-0,94), con un punto de corte óptimo en 1,11, Se del 91,3% (IC 95%: 73,2-97,58) y Sp del 79,69% (IC 95%: 74,34-84,16). Para el índice de shock modificado se obtuvo: AUROC de 0,90 (IC 95%: 0,86-0,95), con un punto de corte óptimo en 1,46, Se del 95,65% (IC 95%: 79,01-99,23) y Sp del 75,78% (IC 95%: 70,18-80,62). Conclusiones: El índice de shock y el índice de shock modificado son buenos predictores de hemorragia masiva y de fácil aplicación durante la atención inicial del trauma grave (AU)

Objective: To determine the predictive value of the Shock Index and Modified Shock Index in patients with massive bleeding due to severe trauma. Design: Retrospective cohort. Setting: Severe trauma patient's initial attention at the intensive care unit of a tertiary hospital. Subjects: Patients older than 14 years that were admitted to the hospital with severe trauma (Injury Severity Score >15) form January 2014 to December 2015. Variables: We studied the sensitivity (Se), specificity (Sp), positive and negative predictive value (PV+ and PV-), positive and negative likelihood ratio (LR+ and LR-), ROC curves (Receiver Operating Characteristics) and the area under the same (AUROC) for prediction of massive hemorrhage. Results: 287 patients were included, 76.31% (219) were male, mean age was 43,36 (±17.71) years and ISS was 26 (interquartile range [IQR]: 21-34). The overall frequency of massive bleeding was 8.71% (25). For Shock Index: AUROC was 0.89 (95% confidence intervals [CI] 0.84 to 0.94), with an optimal cutoff at 1.11, Se was 91.3% (95% CI: 73.2 to 97.58) and Sp was 79.69% (95% CI: 74.34 to 84.16). For the Modified Shock Index: AUROC was 0.90 (95% CI: 0.86 to 0.95), with an optimal cutoff at 1.46, Se was 95.65% (95% CI: 79.01 to 99.23) and Sp was 75.78% (95% CI: 70.18 to 80.62). Conclusion: Shock Index and Modified Shock Index are good predictors of massive bleeding and could be easily incorporated to the initial workup of patients with severe trauma (AU)

Prediction of massive bleeding. Shock index and modified shock index. / Predicción de hemorragia masiva. Índice de shock e índice de shock modificado.

OBJECTIVE: To determine the predictive value of the Shock Index and Modified Shock Index in patients with massive bleeding due to severe trauma. DESIGN: Retrospective cohort. SETTING: Severe trauma patient's initial attention at the intensive care unit of a tertiary hospital. SUBJECTS: Patients older than 14 years that were admitted to the hospital with severe trauma (Injury Severity Score >15) form January 2014 to December 2015. VARIABLES: We studied the sensitivity (Se), specificity (Sp), positive and negative predictive value (PV+ and PV-), positive and negative likelihood ratio (LR+ and LR-), ROC curves (Receiver Operating Characteristics) and the area under the same (AUROC) for prediction of massive hemorrhage. RESULTS: 287 patients were included, 76.31% (219) were male, mean age was 43,36 (±17.71) years and ISS was 26 (interquartile range [IQR]: 21-34). The overall frequency of massive bleeding was 8.71% (25). For Shock Index: AUROC was 0.89 (95% confidence intervals [CI] 0.84 to 0.94), with an optimal cutoff at 1.11, Se was 91.3% (95% CI: 73.2 to 97.58) and Sp was 79.69% (95% CI: 74.34 to 84.16). For the Modified Shock Index: AUROC was 0.90 (95% CI: 0.86 to 0.95), with an optimal cutoff at 1.46, Se was 95.65% (95% CI: 79.01 to 99.23) and Sp was 75.78% (95% CI: 70.18 to 80.62). CONCLUSION: Shock Index and Modified Shock Index are good predictors of massive bleeding and could be easily incorporated to the initial workup of patients with severe trauma.

Atención inicial al trauma grave. Utilidad de la videograbación en la valoración de la calidad asistencial / Trauma initial management. Usefulness of the video recording in the evaluation of the quality of care

Objetivo: Determinar la utilidad de la videograbación en la monitorización de la calidad asistencial. Pacientes y método: Estudio descriptivo prospectivo observacional durante un periodo de seis meses. Se incluyeron todos los pacientes adultos con lesión traumática admitidos en la UCI procedentes del medio extrahospitalario. Se realizó grabación continua en vídeo de la resucitación inicial, con posterior revisión por un grupo multidisciplinar. Se analizaron las características epidemiológicas, adhesión al protocolo establecido, tiempos de actuación y la incidencia de errores y/o fallos del sistema. Resultados: 117 pacientes, edad media 43 años, varones 71%, índice de gravedad (ISS) 19.8 ± 15.6. El promedio de cumplimentación del protocolo en el reconocimiento primario y secundario fue del 79.9% y el 70% respectivamente. En la valoración del trabajo en equipo se mantuvieron: liderazgo 87%, organización del equipo 88%, organización de la asistencia 75% y seguimiento de roles 76%. La asistencia se realizó en 43 minutos. Conclusiones: La utilización de la videograbación durante la atención inicial al paciente traumatizado permite analizar la presencia de errores o retrasos que influyen en la calidad de la asistencia prestada (AU)

Objective: To study usefulness of the video recording in the evaluation of the quality of care in hospital initial care of patients with severe trauma. Patients and methods: Prospective observational study over a period of 6 months. We included all adult patients with traumatic injury admitted to the ICU from the pre-hospital means. Continuous recording took place in video of the initial resuscitation, with subsequent review by a multidisciplinary group. Epidemiological characteristics, adherence to the established protocol, time management and the incidence of errors or system failures were analyzed. Results: 117 patients admitted were included. Of these, 71% were male, with an average age of 43 years and Injury Severity Score (ISS) 19.8 ± 15.6. Overall protocol compliance in the primary and secondary survey was 79.9% and 70% respectively. The evaluation of trauma team performance were: leadership 87%, team organization 88%, care organization 75% and roles follow-up 76%. Resuscitation took 43 minutes. Conclusion: The video-recording of trauma resuscitation allows to analyze the presence of errors and/or delays affecting the quality of the assistance provided (AU)

Contralateral extraaxial hematomas after urgent neurosurgery of a mass lesion in patients with traumatic brain injury.

PURPOSE: The development of a contralateral extraaxial hematoma has repeatedly been described in small series and descriptive studies. However, the evidence available to date is limited. OBJECTIVES: To evaluate the incidence and risk factors leading to the development of a contralateral extraaxial hematoma and to describe the characteristics of cases. METHODS: A retrospective cohort study with prospective data collection was undertaken. All patients admitted to an intensive care unit (ICU) from 2006 to 2010 were studied. The inclusion criteria were as follows: severe trauma [Injury Severity Score (ISS ≥ 16)], neurosurgery (NeuroSx) in the first 24 h. The following were excluded: subacute/chronic subdural hematomas, first bilateral NeuroSx. Cases were those who required immediate contralateral NeuroSx after the first NeuroSx due to the occurrence of a new extraaxial injury or significant growth of a previous one. Controls were those patients those who did not require second NeuroSx or who required reoperation due to ipsilateral lesions. The variables considered were: demographics, neurological assessment, traumatic injuries and severity, image and surgical findings, clinical course, and outcome. Statistics analysis comprised descriptive, inferential, and multivariate analysis by logistic regression. RESULTS: A total of 120 patients were included, among which there were 11 cases (incidence 9.2 %). The cases showed a significantly higher frequency of coma or severe traumatic brain injury (TBI) at admission, contralateral injury and contralateral skull fracture in the preoperative computed tomography (CT) scan, as well as decompressive craniectomy. There were no significant differences in the severity scores, clinical course, or outcomes. The presence of contralateral fracture was identified as an independent risk factor [relative risk (RR) 47.9, 95 % confidence interval (CI) 5.2-443]. CONCLUSIONS: Contralateral extraaxial hematoma is a rare entity, although it has a high mortality rate. Therefore, it requires a high index of suspicion, especially in patients with severe TBI, with minimal contralateral injury and mainly with contralateral skull fracture on the initial CT scan.

Desarrollo de una herramienta de comunicación para la seguridad del paciente (Briefing). Experiencia en una unidad de cuidados intensivos de trauma y emergencias / Development of communication tool for patient safety (

Objetivo: Validar una herramienta de seguridad utilizada en sectores de alto riesgo (briefing de seguridad) en la medicina intensiva. Diseño: Estudio prospectivo, observacional y analítico. Ámbito: UCI de Trauma y Emergencias de un hospital terciario. Pacientes: Pacientes con trauma grave (Injury Severity Score-ISS>16). Intervención: Recogida de incidentes, relacionados con la seguridad del paciente (SP). Variables: Características de la población, estado de la unidad, incidentes de SP, aspectos de la herramienta e impacto sobre la cultura de seguridad. Resultados: Se incluyeron 441 pacientes (edad media 39,9±17,5 años), 75,15% hombres, 89% con trauma cerrado y un 10,5% de mortalidad. La herramienta se aplicó en 586 turnos de 798 posibles (73,4%) y se recogieron 942 incidentes (2,20 incidentes por paciente). Los incidentes más frecuentes se relacionaron con la medicación (20,7%), los dispositivos (colocación 4,03% y mantenimiento 17,8%) y la vía aérea y la ventilación mecánica (VM) (17,09%). Se estableció una correlación entre la presencia de incidentes y las características del enfermo (mayor Injury Severity Score, presencia de VM y terapias de reemplazo renal continuo) y con el estado de la unidad (más de 6 pacientes por turno sobre 8 posibles y el periodo vacacional). La herramienta influyó en diferentes aspectos de la cultura de seguridad de la unidad de manera significativa (frecuencia de comunicación, número de eventos, pérdida de carácter punitivo y trabajo de manera activa en SP). Conclusiones: El briefing es una herramienta para la recogida de los incidentes, simple, fácil de usar, útil para implantar mejoras e influir en la cultura de seguridad (AU)

Objective: To validate a safety tool used in high-risk sectors (safety briefing) in intensive care medicine. Design: A prospective, observational and analytical study was carried out. Setting: Trauma and emergency intensive care unit in a tertiary hospital. Patients: Patients with severe trauma (Injury Severity Score ISS>16). Intervention: Documentation of incidents related to patient safety (PS). Variables: Patients characteristics, state of the Unit, patient safety incidents, aspects of the tool (SP) and safety culture impact. Results: We included 441 patients (75.15% males, mean age 39.9±17.5 years), with blunt trauma in 89% and a 10.5% mortality rate. The tool was applied in 586 out of 798 possible shifts (73.4%), and documented 942 events (2.20 incidents per patient). The incidents were more frequently associated with medication (20.7%), devices (placement 4.03%, and maintenance 17.8%) and airway and mechanical ventilation (MV) (17.09%). A correlation was established between the occurrence of incidents and the characteristics of the patient (higher Injury Severity Score, presence of MV, and continuous renal replacement therapies) and the status of the Unit (more than 6 patients per shift out of 8 possible, and holiday period). The tool significantly influenced different aspects of the safety culture of the unit (communication frequency, number of events, punitive loss and active work in PS). Conclusions: Safety briefing is a tool for the documentation of incidents that is simple and easy to use, and is useful for implementing improvements and in influencing safety culture (AU)

[Development of communication tool for patient safety ("Briefing"). Experience in a trauma and emergency intensive care unit]. / Desarrollo de una herramienta de comunicación para la seguridad del paciente (Briefing). Experiencia en una unidad de cuidados intensivos de trauma y emergencias.

OBJECTIVE: To validate a safety tool used in high-risk sectors (safety briefing) in intensive care medicine. DESIGN: A prospective, observational and analytical study was carried out. SETTING: Trauma and emergency intensive care unit in a tertiary hospital. PATIENTS: Patients with severe trauma (Injury Severity Score ISS≥16). INTERVENTION: Documentation of incidents related to patient safety (PS). VARIABLES: Patients characteristics, state of the Unit, patient safety incidents, aspects of the tool (SP) and safety culture impact. RESULTS: We included 441 patients (75.15% males, mean age 39.9±17.5 years), with blunt trauma in 89% and a 10.5% mortality rate. The tool was applied in 586 out of 798 possible shifts (73.4%), and documented 942 events (2.20 incidents per patient). The incidents were more frequently associated with medication (20.7%), devices (placement 4.03%, and maintenance 17.8%) and airway and mechanical ventilation (MV) (17.09%). A correlation was established between the occurrence of incidents and the characteristics of the patient (higher Injury Severity Score, presence of MV, and continuous renal replacement therapies) and the status of the Unit (more than 6 patients per shift out of 8 possible, and holiday period). The tool significantly influenced different aspects of the safety culture of the unit (communication frequency, number of events, punitive loss and active work in PS). CONCLUSIONS: Safety briefing is a tool for the documentation of incidents that is simple and easy to use, and is useful for implementing improvements and in influencing safety culture.

Escalas predictivas de transfusión masiva en trauma. Experiencia de un registro de transfusiones / Massive transfusion predictive scores in trauma. Experience of a transfusion registry

Objetivo: Valorar la utilidad de diferentes escalas previamente descritas, en la predicción de transfusión masiva (TM) con un registro de transfusiones en trauma grave. Diseño: Estudio retrospectivo de cohortes. Ámbito: Unidad de Cuidados Intensivos de Trauma de un hospital terciario. Pacientes: Se incluyeron pacientes adultos con trauma grave (Injury Severity Score >15), admitidos desde octubre de 2006 hasta julio de 2009.Intervención: Ninguna. Variables: Se evaluaron las siguientes escalas y puntos de corte (PC): Trauma Associated Severe Haemorrhage (TASH) PC: ≥ 16 y ≥ 18; Assessment Blood Consumption (ABC) PC: ≥ 2 y Emergency Transfusion Score (ETS) PC: ≥ 3, ≥ 4 y ≥ 6. TM fue definida como la transfusión de 10 o más unidades de concentrados de hematíes (CH) en las primeras 24 horas del ingreso. Estudiamosla sensibilidad (S), especificidad (E), valor predictivo positivo y negativo (VPP y VPN), razones de verosimilitud positiva y negativa (RVP y RVN) y las curvas receiver-operating characteristics (ROC) y el área bajo las mismas (AUROC).Resultados: Se estudiaron 568 pacientes, el 77,6% hombres, con una edad media de 41,16 ± 18 años e ISS de 30 ± 13. El 93,8% con trauma cerrado. La frecuencia global de TM fue del 18,8%. La mejor S se obtuvo para el ETS ≥ 3 y la mejor especificidad con el TASH ≥ 18. El AUROC para los diferentes escalas fue: ABC: 0,779, ETS: 0,784 y el TASH: 0,889.Conclusiones: Estas escalas pueden ser útiles para caracterizar la población con TM, la exclusión de población de bajo riesgo, intentar ser objetivos en la resucitación con control de daños y apoyar las decisiones clínicas, con pocos datos y fáciles de obtener. (AU)

Objectives: Our purpose is to validate previously described massive transfusion (MT) scoring in our Transfusion Trauma Registry. Design: A retrospective cohort of adult trauma patients. Setting: Trauma and Emergency Intensive Care Unit of a tertiary hospital. Patients: Patients with severe trauma (injury severity score > 15) admitted from October 2006to July 2009.Interventions: None. Variables: The following MT scoring and cutoff points (CP) were evaluated: Trauma-Associated Severe Hemorrhage (TASH) CP: ≥ 16 and ≥ 18; Assessment Blood Consumption (ABC) CP: ≥ 2and Emergency Transfusion Score (ETS) CP: ≥ 3, ≥ 4, ≥ 6. MT was defined as the transfusion of10 units or more of packed red blood cells in the first 24 hours. We studied the sensivity (S),specifity (SP), and positive and negative predictive values (PPV, NPV), the positive and negative likehood ratios (LHR +, LHR-) and area under the receiver operating characteristic curve (ROC).Results: A total of 568 patients were available for analysis; 77.6% were men, with a mean age of 41.16 ± 18 years and an ISS of 30 ± 13. 93.8% with blunt trauma. The overall MT rate was18.8%. The best S was obtained with ETS ≥3 and best SP was obtained with TASH ≥18. ROC for different scores was: ABC: 0.779, ETS: 0. 784, TASH: 0.889.Conclusion: These scales can be useful for characterizing the TM population, for excluding low risk populations, and for attempting to be objective in hematological damage control and in supporting clinical decisions, based on fe1w and easily obtainable data (AU)

[Massive transfusion predictive scores in trauma. Experience of a transfusion registry]. / Escalas predictivas de transfusión masiva en trauma. Experiencia de un registro de transfusiones.

OBJECTIVES: Our purpose is to validate previously described massive transfusion (MT) scoring in our Transfusion Trauma Registry. DESIGN: A retrospective cohort of adult trauma patients. SETTING: Trauma and Emergency Intensive Care Unit of a tertiary hospital. PATIENTS: Patients with severe trauma (injury severity score>15) admitted from October 2006 to July 2009. INTERVENTIONS: None. VARIABLES: The following MT scoring and cutoff points (CP) were evaluated: Trauma-Associated Severe Hemorrhage (TASH) CP: ≥16 and ≥18; Assessment Blood Consumption (ABC) CP: ≥2 and Emergency Transfusion Score (ETS) CP: ≥3, ≥4, ≥6. MT was defined as the transfusion of 10 units or more of packed red blood cells in the first 24 hours. We studied the sensivity (S), specifity (SP), and positive and negative predictive values (PPV, NPV), the positive and negative likehood ratios (LHR +, LHR-) and area under the receiver operating characteristic curve (ROC). RESULTS: A total of 568 patients were available for analysis; 77.6% were men, with a mean age of 41.16 ± 18 years and an ISS of 30 ± 13. 93.8% with blunt trauma. The overall MT rate was 18.8%. The best S was obtained with ETS ≥3 and best SP was obtained with TASH ≥18. ROC for different scores was: ABC: 0.779, ETS: 0. 784, TASH: 0.889. CONCLUSION: These scales can be useful for characterizing the TM population, for excluding low-risk populations, and for attempting to be objective in hematological damage control and in supporting clinical decisions, based on fe1w and easily obtainable data.