In France, the pre-hospital field triage of trauma patients is currently based on the Vittel criteria algorithm. This algorithm was originally created in 2002 before the stratification of trauma ...centers and, at the national level, has not been revised since. This could be responsible for the overtriage of trauma patients in Level I Trauma Centers. The principal aim of this study was to evaluate the correlation between each Vittel field triage criterion and trauma patients' Injury Severity Score.
Our Level I Trauma Center receives an average of 300 trauma patients per year. Demographic and physiological data, along with the entire trauma patient management process and Vittel field triage criteria, are recorded in a local trauma registry. The Abbreviated Injury Scale (AIS) and Injury Severity Score (ISS) are calculated after a complete assessment of the trauma victim during their in-hospital management. Results were concerned with the presence of an ISS of greater than 15, which defined a major trauma patient; mortality within 30 days; and admission to the intensive care unit. This study is a registry analysis from January 2013 to September 2017.
Of the 1373 patients in the registry, 1151 were included in the analysis with a mean age of 43 years (± 19) and a median ISS of 13 (IQR = 5-22), where 887 (77%) were male. Nine of the 24 Vittel criteria were associated with an ISS > 15. In a multivariate analysis, no criterion related to kinetic elements was significantly correlated with an ISS > 15, mortality within 30 days, or admission to intensive care. Three algorithm categories were predictive of a major trauma patient (ISS > 15): physiological variables, pre-hospital resuscitation, and physical injuries, while kinetic elements were not.
Criteria related to physiological variables, pre-hospital resuscitation, and physical injuries are the most relevant to predicting the severity of a trauma patient's condition. A revision of the VCA could potentially have beneficial effects on the over and undertriage phenomena, which constitute ongoing medical and financial concerns.
Background and Objectives
Our study sought to evaluate and compare different prediction scores for massive transfusion in‐hospital packed red blood cell (PRBC) transfusions.
Materials and Methods
...Between January 2013 and December 2018, 1843 trauma patients were enrolled in the registry of a level‐1 trauma centre. All prehospital and in‐hospital variables needed to calculate the Shock Index and RED FLAG, Assessment of Blood Consumption (ABC) and Trauma Associated Severe Hemorrhage (TASH) scores were prospectively collected in the registry. The primary endpoint was the initiation of transfusion within the first hour of the patient's arrival at the hospital.
Results
A total of 1767 patients were included for analysis with a mean age of 43 years (±19) and a mean Injury Severity Score of 15 (±14). The in‐hospital TASH score had the highest predictive performance overall (area under the curve AUC = 0.925, 95% confidence interval CI 0.904–0.946), while the RED FLAG score (AUC = 0.881, 95% CI 0.854–0.908) had the greatest prehospital predictive performance compared to the ABC score (AUC = 0.798, 95% CI 0.759–0.837) and Shock Index (AUC = 0.795, 95% CI 0.752–0.837). Using their standard thresholds, the RED FLAG score was the most efficient in predicting early transfusion (sensitivity: 87%, specificity: 76%, positive predictive value: 25%, negative predictive value: 99%, Youden index: 0.63).
Conclusion
The RED FLAG score appears to outperform both the ABC score and the Shock Index in predicting early in‐hospital transfusion in trauma patients managed by pre‐hospital teams. If adopted, this score could be used to give advance warning to trauma centres or even to initiate early transfusion during pre‐hospital care.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Background and objectives
Haemorrhagic shock is a leading cause of avoidable mortality in prehospital care. For several years, our centre has followed a procedure of transfusing two units of packed ...red blood cells outside the hospital. Our study’s aim was twofold: describe the patient characteristics of those receiving prehospital blood transfusions and analyse risk factors for the 7‐day mortality rate.
Materials and methods
We performed a monocentric retrospective observational study. Demographic and physiological data were recovered from medical records. The primary outcome was mortality at seven days for all causes. All patients receiving prehospital blood transfusions between 2013 and 2018 were included.
Results
Out of 116 eligible patients, 56 patients received transfusions. Trauma patients (n = 18) were younger than medical patients (n = 38) (P = 0·012), had lower systolic blood pressure (P = 0·001) and had higher haemoglobin levels (P = 0·016). Mortality was higher in the trauma group than the medical group (P = 0·015). In‐hospital trauma patients received more fresh‐frozen plasma and platelet concentrate than medical patients (P < 0·05). Predictive factors of 7‐day mortality included transfusion for trauma‐related reasons, low Glasgow Coma Scale, low peripheral oxygen saturation, prehospital intensive resuscitation, existing coagulation disorders, acidosis and hyperlactataemia (P < 0·05).
Conclusion
Current guidelines recommend early transfusion in patients with haemorrhagic shock. Prehospital blood transfusions are safe. Coagulation disorders and acidosis remain a cause of premature death in patients with prehospital transfusions.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Introduction: Several prehospital major trauma patient triage scores have been developed, the triage revised trauma score (T-RTS), Vittel criteria, Mechanism/Glasgow Coma Scale/Age/Systolic blood ...pressure score (MGAP), and the new trauma score (NTS). These scoring schemes allow a rapid and accurate prognostic assessment of the severity of potential lesions. The aim of our study was to compare these scores with in-hospital mortality predictions in a cohort of consecutive trauma patients admitted in a Level 1 trauma center. Materials: Between 2013 and 2016, 1,112 patients were admitted to the "major trauma" spinneret of a Level 1 trauma center in the south of France. All prehospital data needed to calculate the T-RTS, Vittel criteria, the MGAP score, and the NTS were collected. The main evaluation criterion was in-hospital mortality at 30 days for all causes. The predictive performances of these scores were evaluated and compared with each other using the analysis of the receiver operating curves. Results: A total of 1,001 patients were included in the analysis, 238 (24%) females, aged 43 ± 19 years with ISS 15 ± 13. The area under the curve was for each score: T-RTS, AUC = 0.84, 0.82-0.87; Vittel criteria, AUC = 0.87 0.85-0.89; MGAP score, AUC = 0.91 0.89-0.92 and NTS, AUC = 0.90 0.88-0.92. By comparing the ROC curves of these scores, the MGAP and NTS scores were statistically higher than the T-RTS. With the current thresholds, the sensitivity, specificity, positive and negative predictive values of these scores were 91%, 35%, 10%, 98% for T-RTS, 100%, 2%, 8%, 100% for Vittel criteria, 91%, 71%, 24%, 99% for MGAP score, 82%, 86%, 33%, 98% for NTS. Only Vittel's criteria allowed undertriage below 5% as recommended by the American College of Surgeons Committee on Trauma (ACSCOT). Conclusion: The comparison of these different triage scores concluded with a superiority of the MGAP and NTS scores compared with the T-RTS. Including the calculation of MGAP or NTS scores with the Vittel criteria would reduce the risk of overtriage in the Level 1 trauma centers by further directing patients at low risk of death to a lower-level trauma facility.
Gestational trophoblastic disease occurs rarely in postmenopausal women. We report the case of a 51 year-old postmenopausal woman with an invasive complete mole. Invasive mole should be distinguished ...from choriocarcinoma, by a thorough sampling showing infiltrative molar villi associated with a prominent trophoblastic proliferation. Gestational trophoblastic diseases in postmenopausal women can represent malignant changes of trophoblastic remnants of a prior pregnancy after a period of latency or correspond to a possible current pregnancy as demonstrated by an ovarian corpus luteum of pregnancy in our patient. The unusual finding in our case is that the gestational trophoblastic disease follows a pregnancy occurring after a biologically confirmed menopause.
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