Predictors of Prehospital Transfusion in Paediatric Trauma: A Retrospective Analysis of 11,849 Cases from the TraumaRegister DGUⓇ

Predictors of Prehospital Transfusion in Paediatric Trauma: A Retrospective Analysis of 11,849 Cases from the TraumaRegister DGUⓇ | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Predictors of Prehospital Transfusion in Paediatric Trauma: A Retrospective Analysis of 11,849 Cases from the TraumaRegister DGU Ⓡ Niko R. E. Schneider, Ralf Kraus, Rolf Lefering, Fabian Hemm, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7108398/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Nov, 2025 Read the published version in Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine → Version 1 posted 11 You are reading this latest preprint version Abstract Background The prehospital transfusion of red blood cell (RBC) concentrates represents an emerging approach in paediatric trauma management. Nevertheless, distinctive parameters for predicting the need for transfusion in children are still lacking. This study aimed to identify predictors for early in-hospital RBC transfusions that are readily available to emergency medical services (EMS) at the scene to aid in deciding whether to transfuse. Methods This study comprised a retrospective analysis of the German TraumaRegister DGU ® . It included children and adolescents aged 1 to 16 years from Germany, Austria, and Switzerland over a 15-year period. Contingency tables were used to identify risk factors, which were then assessed through multivariate regression analysis. The model’s predictive capacity was evaluated using the receiver operating characteristic (ROC) curve. Results A total of 11,849 patients were included, with RBC transfusion performed in 5.9% of cases. Polytraumatised patients (adjusted odds ratio (adj. OR) 4.18 [95% confidence interval 3.26–5.34]) and those with penetrating injuries (adj. OR 4.32 [2.96–6.30]) and abdominal injuries (adj. OR 4.18 [3.34–5.24]) exhibited the highest risk of requiring an RBC transfusion. The need for cardiopulmonary resuscitation (adj. OR 2.46 [1.84–3.28]), endotracheal intubation (adj. OR 2.51 [1.93–3.28]), and Glasgow Coma Scale (GCS) ≤ 8 (adj. OR 2.49 [1.85–3.36]) were also significant, but weaker, predictors. A model based on the mentioned parameters achieved an area under the ROC curve of 0.87 [0.85–0.88]. Conclusion The likelihood of requiring an RBC transfusion is increased in cases of polytrauma, abdominal and penetrating trauma, patients with a GCS ≤ 8, and those requiring tracheal intubation or cardiopulmonary resuscitation. All the included parameters are straightforward to assess, making them practical for use by EMS. Therefore, the proposed risk factors can help identify patients at risk of severe haemorrhage and subsequent transfusion requirement. Clinical Trial Number: not applicable children red blood cell concentrate haemorrhage paediatric trauma emergency medicine Figures Figure 1 Figure 2 Figure 3 Background Trauma remains the leading cause of death in children in Europe and the United States (US) [ 1 , 2 ]. The main factors contributing to this high mortality rate are traumatic brain injuries, hypoxia, and haemorrhage, which rapidly worsen the patient’s condition and often result in death at the scene [ 1 , 2 ]. An analysis of the National Trauma Data Bank of the US found that 51% of paediatric patients were already deceased upon arrival, highlighting the need for urgent treatment at the scene [ 3 ]. Considering causes of death, as delineated by the cABCDE algorithm, emergency medical services (EMS) should address the most urgent issues in paediatric trauma, that is, immediate critical bleeding control, securing the airway and providing adequate ventilation, volume resuscitation, and minimising on-scene time, to enable timely surgical treatment and transfusion [ 4 ]. The transfusion of red blood cell (RBC) concentrates, combined with the replacement of coagulation factors and platelets, remains an essential component of trauma resuscitation in the emergency room [ 5 ]. Derived from military experience, the prehospital transfusion (PT) of RBCs has been introduced into civilian EMS [ 6 ]. Increasing evidence supports PT in adult populations based on reduced trauma-associated morbidity and mortality; thus, it has been implemented in European EMS [ 7 ]. A survey by the European Society of Anaesthesiology revealed that 48% of respondents, primarily from helicopter EMS, had the logistical capacity to perform PT [ 8 ]. PT’s technical feasibility has also been proven previously [ 9 ]. Recently, the combined use of RBC and plasma was shown to improve survival in adult trauma patients [ 10 , 11 ]. Only limited data on PT in children are available. However, in 2023, a landmark study by Morgan et al. investigated 559 children from the Pennsylvania Trauma Systems Foundation database, 13% of whom received PT. The study showed that early transfusion at the scene resulted in reduced 24-hour and in-hospital mortality compared to early in-hospital transfusion [ 12 ]. Therefore, the PT of RBCs should be considered in critically injured children. In addition to establishing the logistics for PT, determining the correct indication remains a major challenge for emergency response teams. On one hand, unnecessary transfusions must be avoided; on the other hand, restrictive approaches might lead to further deterioration of the circulation. EMS face a time-critical situation and only have information on the patient’s current status to decide if a transfusion should be performed. Data derived from adult populations suggest indicators for coagulopathy, such as base excess and lactate levels, as predictors for massive transfusion. Often, these are not available on site [ 13 , 14 ]. In general, data on predictors for trauma-associated transfusions in children are limited [ 15 ]. Therefore, the present analysis aimed to identify predictors available to EMS at the scene for early in-hospital transfusion in a large paediatric trauma cohort. Methods Study design A retrospective analysis of the German TraumaRegister DGU ® of the German Trauma Society (Deutsche Gesellschaft für Unfallchirurgie (DGU)) was performed. As it involved analyses of routine, anonymous data, no ethical approval was necessary (Justus Liebig University Giessen, Giessen, Germany; correspondence from February 25, 2025). The study followed the current publication guidelines of the TraumaRegister DGU® and was registered under the TR-DGU Project ID 2024–040. The study was conducted according to the principles of the Declaration of Helsinki [ 16 ]. The methods and results are presented according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [ 17 ]. TraumaRegister DGU® The TraumaRegister DGU® of the German Trauma Society was founded in 1993. This multicentre database aims for the pseudonymised and standardised documentation of severely injured patients. Data are collected prospectively in four consecutive time phases from the site of the accident until discharge from the hospital: A) prehospital phase, B) emergency room and initial surgery, C) intensive care unit (ICU), and D) discharge. The documentation includes detailed information on demographics, injury pattern, comorbidities, pre- and in-hospital management, course in the intensive care unit, relevant laboratory findings (including data on transfusion), and the outcome of each individual. The inclusion criterion is hospital admission via the emergency room with subsequent ICU care or arrival at the hospital with vital signs and death before ICU admission. The infrastructure for documentation, data management, and data analysis is provided by the Academy for Trauma Surgery (Akademie der Unfallchirurgie GmbH), a company affiliated with the German Trauma Society. The scientific leadership is provided by the Committee on Emergency Medicine, Intensive Care and Trauma Management (Sektion NIS) of the German Trauma Society. The participating hospitals submit their pseudonymised data to a central database via a web-based application. Scientific data analysis is approved according to a peer review procedure in the publication guidelines of TraumaRegister DGU®. The participating hospitals are primarily located in Germany (90%), but a rising number of hospitals from other countries also contribute data (currently, Austria, Belgium, China, Finland, Luxembourg, Slovenia, Switzerland, the Netherlands, and the United Arab Emirates). Currently, about 38,000 cases from almost 700 hospitals are entered into the database per year. Participation in TraumaRegister DGU® is voluntary. For hospitals associated with TraumaNetzwerk DGU®, however, the entry of at least a basic dataset is obligatory for quality assurance purposes. Inclusion criteria The study included patients from Germany, Austria, and Switzerland over a 15-year period (January 1, 2008, to December 31, 2023). Only children and adolescents aged 1 to 16 years were included. Transfers between hospitals to higher-level care centres were excluded. Only data from the core collective were analysed. To exclude patients with minor injuries, only those with a Maximal Abbreviated Injury Scale (MAIS) score ≥ 3 or those with a MAIS score ≥ 2 who required ICU treatment or died were included. Statistical analysis Descriptive analysis of the study cohort was performed, with data presented as absolute numbers and percentages. Metric data are presented as mean with standard deviation (SD). Parameters included baseline characteristics, as well as details regarding the severity and location of injuries. An Abbreviated Injury Scale (AIS) score ≥ 3 was classified as a serious injury, while an Injury Severity Score (ISS) ≥ 16 was considered indicative of severe multiple trauma. Polytrauma was defined according to the Berlin definition as injuries affecting at least two body regions with an AIS score ≥ 3, accompanied by at least one physiological deterioration parameter (systolic blood pressure ≤ 90 mmHg, Glasgow Coma Scale ≤ 8, base excess ≤ − 6.0 mmol/L, coagulopathy (INR ≥ 1.4 or PTT ≥ 40 s), or body temperature ≤ 34°C) [ 18 ]. High-energy trauma was defined as injuries resulting from motor vehicle collisions, motor bike accidents, or falls from a height of ≥ 3 metres. The chi-square test was used for categorical data, comparing patients with and without transfusions; metric data were compared with the Mann–Whitney U-test. A p -value < 0.05 was considered statistically significant. Finally, a multivariate logistic regression analysis with transfusion as the dependent variable was performed, including potential predictors from the univariate analysis. Only parameters available at the scene were taken into account. Since several parameters differed significantly between patients with and without transfusion, trauma experts assessed if they were clinically present for EMS before validation in the multivariate regression analysis. The results are presented as adjusted odds ratios (ORs) with 95% confidence intervals. Variables with an OR > 2.0 were used to build a simple point score: 1 point if the OR was 2.0–4.0 and 2 points if the OR was > 4.0. Receiver operating characteristic (ROC) curve analysis was then performed to assess the predictive accuracy of the score. The area under the ROC curve was presented with 95% confidence intervals. Statistical analyses were conducted using SPSS (version 29, IBM Inc., Armonk, NY, US). Results Study cohort Overall, 11,849 patients of 569 hospitals were included in the study, with blood transfusions performed in 5.9% of cases. If patients were transfused, they received 4.1 (SD 8.8) RBC units on average. The transfusion rate remained relatively stable across different age categories, ranging from 4.2% in 12-year-olds to 8.0% in 1-year-olds (Figure 1). The mean age of the included patients was 9.6 years (SD 4.5). However, the absolute number of transfusions increased significantly in older children and adolescents, who accounted for 51% of all transfusions (age ≥ 11–16 years, n = 358, p < 0.001). The majority of patients were treated in level 1 or 2 hospitals, while only a small minority (< 1%) received transfusions in level 3 hospitals. The mean transportation time from scene to hospital was 59.9 minutes (SD 26.2, n = 9,185). Baseline characteristics and the underlying trauma mechanisms are shown in Table 1. Table 1. Basic characteristics and overview of underlying trauma mechanisms. Parameters All patients (n = 11,849) No transfusion (n = 11,147) Transfusion (n = 702) p-value Age (years) Toddler [1-5 years], n (%) School child [6-10 years], n (%) Adolescents [11-15 years], n (%) 2,634 (22.2) 3,256 (27.5) 5,959 (50.3) 2,458 (22.1) 3,088 (27.7) 5,601 (50.2) 176 (25.1) 168 (23.9) 358 (51.0) <.001 Sex (n = 11,838) Male, n (%) 7,444 (62.9) 7,031 (63.1) 413 (58.9) .026 Died in hospital 571 (4.8) 313 (2.8) 258 (36.8) <.001 Trauma mechanism Motor vehicle accident, n (%) Motorcycle accident, n (%) Bicycle accident, n (%) Pedestrian accident, n (%) Fall from a height of ≥3 m, n (%) Fall from a height of <3 m, n (%) Others, n (%) 1,320 (11.3) 736 (6.3) 1,833 (15.7) 2,331 (20.0) 2,043 (17.5) 1,632 (14.0) 1,748 (15.0) 1,188 (10.8) 685 (6.3) 1,750 (16.0) 2,198 (20.1) 1,899 (17.3) 1,602 (14.6) 1,630 (14.9) 132 (19.1) 51 (7.4) 83 (12.0) 133 (19.2) 144 (20.8) 30 (4.3) 118 (17.1) <.001 Severe trauma types High energy trauma Traffic-associated accidents Penetrating trauma Violence-associated trauma 4,099 (34.6) 6,576 (55.5) 334 (2.8) 156 (1.3) 3,772 (32.7) 6,143 (55.1) 276 (2.5) 129 (1.2) 327 (40.4) 433 (61.7) 58 (8.3) 27 (3.8) <.001 <.001 <.001 <.001 Level of hospital care Basic hospital care (Level 3) Specialized hospital care (Level 2) Comprehensive hospital care (Level 1) 784 (6.6) 3,008 (25.4) 8,057 (68.0) 765 (6.9) 2,903 (26.0) 7.479 (67.1) 19 (2.7) 105 (15.0) 578 (82.3) <.001 <.001 <.001 Helicopter emergency medical service transportation 3,335 (29.2) 3,040 (28.3) 295 (43.6) <.001 Trauma severity ISS ≥16, n (%) Polytrauma, n (%) Single trauma, n (%) 5,048 (42.6) 995 (8.4) 6,591 (55.6) 4,405 (39.5) 630 (5.7) 6,333 (58.8) 643 (91.6) 365 (52.0) 258 (36.8) <.001 <.001 <.001 Abbreviated injury scale AIS head ≥3, n (%) AIS thorax ≥3, n (%) AIS abdomen ≥3, n (%) AIS extremities ≥3, n (%) 4,321 (35.5) 2,366 (20.0) 1,330 (11.2) 2,678 (22.6) 3,901 (35) 2,006 (18) 1,075 (9.6) 2,390 (21.4) 420 (59.8) 360 (51.3) 255 (36.3) 288 (41.0) <.001 <.001 <.001 <.001 Data are presented as absolute numbers and percentages. Data points were available in 11,643 cases for trauma mechanisms and in 11,423 for helicopter emergency medical service transportation, respectively. All other parameters were available in all included patients. Statistical significance refers to the difference between transfused and non-transfused patients per each parameter. P-values were calculated using the chi-square test. Abbreviations: AIS = abbreviated injury scale; ISS = injury severity scale. Injury severity In total, 42.6% of patients suffered from severe trauma, defined as an ISS ≥ 16 (mean ISS 15.7, SD 11.2; n = 11,849), while only 8.4% met the Berlin definition of polytrauma. The risk of death based on the Revised Injury Severity Scale II (RISC II) was 34.7% (n = 702) and 3.4% (n = 11,147) in transfused and non-transfused patients, respectively [19]. The mean ISS of non-transfused patients was 14.7 (SD 9.7), whereas transfused patients had a significantly higher mean ISS of 34.1 (SD 16.2; p < 0.01). While children with polytrauma (Berlin definition) reached the highest specificity for transfusion (94.3 %), the sensitivity remained low (52%). The ISS offered a low specificity (60.5%) but a high sensitivity (91.6%). Overall, with the exception of an ISS ≥ 16 (positive predictive value (PPV) 63.2 %), the PPV of single parameters remained low (Table 2). The highest transfusion rates were observed in children with head and thoracic injuries, followed by extremity and abdominal injuries (Table 1). An AIS ≥ 3 did sufficiently discriminate between transfused and non-transfused patients, which was particularly evident for abdominal injuries. Most patients (63.7%) with abdominal lesions were categorised as AIS < 3. Nevertheless, robust statistical differences were observed, with significantly more transfused than non-transfused children across all AIS categories, ISS ≥ 16, polytrauma, and single trauma. Table 2 . Prevalence, specificity, sensitivity, and positive predictive value (PPV) for various clinical predictors of transfusion. Parameters Prevalence (n, %) Specificity (%) S ensitivity (%) P PV (%) Trauma severity ISS ≥16 P olytrauma Isolated injury Penetrating trauma Violence-associated trauma High energy trauma Traffic-associated accidents 5,048 (42.6) 995 (8.4) 6,591 (55.6) 334 (2.8) 156 (1.3) 4099 (34.6) 6576 (55.5) 60.5 94.3 43.2 97.5 98.8 66.2 44.9 91.6 52.0 36.8 8.3 3.8 46.6 61.7 63.2 45.6 44.8 17.4 17.3 8.0 6.6 Injury pattern (AIS ≥ 3) Serious head injury Serious thorax trauma Serious abdominal trauma Serious extremity injury 4321 (36.5) 2366 (20.0) 1330 (11.2) 2678 (22.6) 65.0 82.0 90.4 78.6 59.8 51.3 36.3 41.0 9.7 15.2 19.2 10.8 Pre-clinical assessment and interventions Systolic blood pressure ≤90 mmHg Glasgow Coma Scale 3 – 8 Volume therapy Catecholamine therapy # Cardiopulmonary resuscitation Tracheal Intubation Emergency thoracocentesis # 1266 (13.6) 1942 (18.0) 8439 (74.8) 434 (6.4) 433 (3.8) 2668 (23.6) 108 (1.6) 88.1 84.6 25.6 95.9 97.5 79.2 99.1 42.7 59.4 81.1 33.5 23.7 67.8 9.4 17.6 19.8 6.6 40.3 37.6 17.5 45.4 # not available in the reduced basic dataset. Abbreviations: AIS = abbreviated injury scale; ISS = injury severity scale. Table 3. Contingency tables on indices of the clinical appearance and performed emergency procedures. Parameters No transfusion (n = 11,147) Transfusion (n = 702) p-value Clinical appearance Systolic blood pressure ≤90 mmHg 1,043 (11.9) 223 (42.7) < 0.001 Glasgow Coma Scale 13-15, n (%) 9-12, n (%) 3-8, n (%) 6,956 (68.6) 1,624 (16.0) 1,558 (15.4) 176 (27.2) 86 (13.3) 384 (59.4) < 0.001 Pupillary light responsiveness normal, n (%) delayed, n (%) none, n (%) 7,095 (88.3) 605 (7.5) 333 (4.1) 273 (49.1) 95 (17.1) 188 (33.8) < 0.001 Pupillary size regular size, n (%) anisocor, n (%) bilaterally dilated, n (%) 10,052 (92.8) 343 (3.2) 438 (4.0) 434 (63.8) 62 (9.1) 184 (27.1) < 0.001 Emergency procedures Volume therapy, n (%) 7,882 (74.4) 557 (81.1) < 0.001 Catecholamine therapy, n (%) 259 (4.1) 175 (33.5) < 0.001 Cardiopulmonary resuscitation, n (%) 270 (2.5) 163 (23.7) < 0.001 Tracheal Intubation, n (%) 2,202 (20.8) 466 (67.8) < 0.001 Emergency thoracocentesis, n (%) 59 (0.9) 49 (9.4) < 0.001 Data are presented as absolute numbers and percentages. Volume therapy was defined as the administration of at least one unit of fluid (500 mL of crystalloids or colloids). Data was available for Glasgow coma scale in 10,784 cases, for pupillary light responsiveness in 8,589 cases, for pupillary size in 10,486 cases, volume therapy 6,775 cases, catecholamine therapy in 6,775 cases, cardiopulmonary resuscitation in 11,286 cases, tracheal intubation in 11,286 cases and thoracocentesis in 6,775 cases. All other parameters were available in all included patients. Statistical significance refers to the difference between transfused and non-transfused patients per each parameter. P-values were calculated using the chi-square test based on contingency tables. Clinical status of patients and emergency procedures In total, 33.9% of patients were not alert at the scene, of whom 15.9% had a Glasgow Coma Scale (GCS) of 9–12, and 18% had a GCS ≤ 8. Overall, in 23.7% of cases, the airway was secured via intubation. The transfusion rate was significantly higher in unresponsive patients (GCS 3–8), those with pathological pupil reactions, and those requiring intubation (Table 3). Patients with a GCS of 9–12 did not have an increased need for transfusion. Regardless of age, a systolic blood pressure ≤ 90 mmHg was associated with a higher need for transfusion. At the scene, the mean systolic blood pressure was 115 mmHg (SD 26, n = 9,278), and the mean heart rate was 102 bpm (SD 27, n = 6,448). These vital signs did not differ at hospital admission (systolic blood pressure: 117 mmHg (SD 24); heart rate: 101 bpm (SD 25). No information on capillary refill time was available. In total, patients received an average of 464 mL of fluids at the scene (SD 453, n = 11,286) and 768 mL in the resuscitation room (SD 1027, n = 5,772). Patients requiring transfusion received significantly more fluids (scene: 753 mL (SD 779) vs. 446 mL (SD 417); hospital: 2184 mL (SD 2160) vs. 640 mL (SD 731); p < 0.001). Risk prediction The final multivariate logistic regression model included 10,594 patients. The included parameters of the regression model are shown in Table 4. The transfusion rate increased significantly from 7.4% (2 points) to 21.6% when 3 points were achieved (Figure 2). If 5 or more points were reached, the transfusion rate exceeded 50%. ROC analysis showed a predictive value of 0.87 [0.85–0.88] for transfusion prediction (Figure 3). Table 4. Results of the multivariate logistic regression analysis. Parameters Adj. Odds ratio 95%-confidence interval Weighting Injury severity Polytrauma Thoracic AIS ≥3 Abdominal AIS ≥3 4.18 1.19 4.18 3.26 – 5.34 0.95 – 1.49 3.34 – 5.24 2 2 Glasgow Coma Scale 9-12 3-8 1.38 2.49 1.03 – 1.86 1.85 – 3.36 1 Type of injury Penetrating High energy trauma 4.32 1.55 2.96 – 6.30 1.28 – 1.87 2 Emergency procedures Endotracheal Intubation Cardiopulmonary resuscitation 2.51 2.46 1.93 – 3.28 1.84 – 3.28 1 1 Abbreviation: AIS = Abbreviated injury scale. Discussion This study reviewed several predictors of early in-hospital transfusions in a large paediatric trauma cohort of 11,849 patients. It demonstrated that prehospital assessment of clinically apparent parameters can sufficiently predict the need for PT. The highest risk for transfusion was observed in patients with penetrating trauma, abdominal injuries, and polytrauma, followed by those who were unconscious, required tracheal intubation, or underwent cardiopulmonary resuscitation. A notable strength of this study lies in the high number of patients included, a crucial consideration given the limited number of paediatric trauma cases where transfusion was needed and the paucity of prospective studies in this domain. The observed transfusion rate is consistent with data from the US National Trauma Databank, which reported a transfusion rate of 4% within the first 24 hours after hospital admission [20]. Like the data presented, a higher absolute number of transfusions was observed in older children and adolescents, severely injured patients (ISS ≥ 25), and unresponsive patients, making the results comparable to those in the US population. Several studies have investigated diagnostic algorithms for predicting transfusions in adults, resulting in the development of more than 20 scoring tools [21,22]. In contrast, transfusion prediction in paediatric trauma care has been studied less. To date, only one other large registry study, an analysis of the Trauma Quality Improvement Project (TQIP), has aimed to identify intra- and prehospital predictors for transfusion after paediatric trauma [15]. This study used a Bayesian Belief Network to predict the probability of in-hospital transfusions in severely injured children. The transfusion rate in the TQIP study was lower than in the present analysis, with 2.8% of patients receiving a transfusion within the first 4 hours after hospital admission. The model included 14 parameters and demonstrated a high predictive power for transfusion. The most influential predictors were GCS and impaired systolic blood pressure at admission and at the scene. This finding is particularly relevant because systolic blood pressure was not adjusted for age, indicating that a blood pressure ≤ 90 mmHg is predictive of transfusion regardless of age, aligning with our study. However, this finding should be interpreted with caution as 50% of the patients in our study were older than 10 years, and 27% were aged between 5 and 10 years. This suggests that while hypotension may be predictive of the need for transfusion in school-aged children and adolescents, it may not necessarily apply to younger children. This may also account for the significantly higher transfusion rate in this study, despite these factors not being independent predictors of transfusion, possibly since blood pressure and other vital signs were likely optimised by EMS personnel before hospital admission. Additionally, this might explain why heart rate failed to predict transfusion in our study and had only a minor impact in the TQIP study, especially when only prehospital vital signs were considered. Undisputably, age-adjusted vital parameters are ideal for the assessment of children’s hemodynamic status; however, these measurements are not practically achievable at the scene in emergencies [23,24]. Therefore, heart rate and blood pressure do not necessarily comprise important indicators of the need for transfusion, most likely because vital parameters were not analysed in an age-adjusted manner. Unfortunately, the capillary refill time, which could have been an easily assessable option, was not available in the TraumaRegister DGU â . To address these limitations, we focused on identifying predictors available at the scene and excluded all in-hospital parameters. Consistent with our findings, the TQIP registry showed that only the inclusion of impaired GCS improved the model’s predictive accuracy (AUC ROC 0.84 vs. 0.87 in our study), highlighting the importance of GCS assessment. On the other hand, abdominal injuries, the need for resuscitation, and the presence of multiple injuries did not improve the Bayesian model, whereas these factors were among the strongest predictors in our logistic model. Interestingly, the accident mechanism improved the predictive accuracy of the TQIP model, whereas the resulting injuries did not. This may be explained by the fact that the accident mechanism serves as an early proxy for injury severity, while the actual injuries often require time-consuming diagnostics. Since transfusion decisions must frequently be made before a complete assessment is available, the accident mechanism might have had a greater impact on the predictive model. Additionally, prehospital interventions could have mitigated the effects of some injuries, further reducing their predictive value. Finally, it is important to note that the TQIP analysis has not yet been externally validated. Low GCS, tracheal intubation, and cardiopulmonary resuscitation showed a lower adjusted OR than the presence of polytrauma and abdominal and penetrating trauma. In our opinion, this reflects the underlying trauma pathophysiology. An impaired GCS is often caused by severe traumatic brain injury and the subsequent tracheal intubation and/or resuscitation [25]. On the other hand, multiple, penetrating, and abdominal traumas display common causes of severe bleeding [20,22]. In summary, it is important to understand that with the exception of an ISS ≥ 16, the positive predictive value of individual parameters remains low, but their combination allows for a reliable prediction of transfusion needs. While some parameters were highly specific but had low sensitivity, the opposite was true for others. Moreover, the high prevalence of certain parameters (e.g., volume therapy) further reduced the positive predictive value. Therefore, each patient should be assessed based on multiple transfusion indicators rather than a single definitive criterion. This study has several limitations. First and most importantly, it lacks a validation cohort. This is due to the low incidence of paediatric trauma requiring transfusion, which posed a challenge for the study design. To generate a derivation cohort with sufficient transfused patients, a large dataset was required, which was feasible in this study. However, this approach limited the possibility of creating a separate validation cohort. Additionally, data quality before 2008 was insufficient, and transfusion strategies may have changed over the past 25 years, making a historical validation cohort unfeasible. The use of data from other countries was also not a viable option, as only 5% of the TraumaRegister DGU â data originates from outside Germany, Austria, and Switzerland. For these reasons, this study focused on identifying predictors for transfusion rather than dividing the study population. To develop a reliable scoring tool, the identified risk factors must first be validated. Second, children under 1 year of age were excluded due to limited data availability. However, most children were of school age or adolescents; therefore, the bias probably has little impact on the study results. Nevertheless, future studies should focus on neonates and infants, despite the rarity of these cases, to better understand their specific clinical outcomes. Third, only limited datasets were available for lactate and base excess, which have been identified as potential predictors of transfusion and could be assessed at the scene using point-of-care devices [13]. Fourth, this study did not report the amount of blood transfused relative to the patient’s body weight. Fifth, Due to changes in documentation practices in 2020, with separate recording of transfusions in the trauma bay and operating room introduced only thereafter, a consistent phase-specific analysis across the full study period (2009–2023) was not methodologically feasible. Finally, due to the retrospective design, the investigators had to rely on the quality of the documentation within the database. Conclusion In summary, based on a large cohort of 11,849 severely injured children and adolescents, this study demonstrated that the risk for intrahospital transfusion can be assessed using parameters available in the prehospital setting. This information aids in evaluating the need for PT in these patients. An impaired GCS proved to be more predictive than other impaired vital parameters, such as hypotension or tachycardia, likely due to prior correction by EMS. Particularly in the case of multiple, abdominal, and penetrating trauma, the probability of blood loss increases to such an extent that the PT of RBC can be considered. All the included parameters are straightforward to assess, making them practical for use by emergency medical teams. Therefore, the proposed risk factors can help identify patients at risk of severe haemorrhage and the subsequent transfusion requirement. Abbreviations Adj. OR Adjusted odds ratio AIS Abbreviated Injury Scale AUC Area under the curve DGU Deutsche Gesellschaft für Unfallchirurgie EMS Emergency medical services GCS Glasgow Coma Scale ICU Intensive care unit INR International Normalised Ratio ISS Injury Severity Scale MAIS Maximal Abbreviated Injury Scale PPV Positive predictive value PT Prehospital transfusion PTT Partial Thromboplastin Time RISC II Revised Injury Severity Scale II RBC Red blood cell concentrate ROC Receiver operating characteristic SD Standard deviation STROBE Strengthening the Reporting of Observational Studies in Epidemiology TQIP Trauma Quality Improvement Project US United States Declarations Human Ethics and Consent to Participate declarations: not applicable Consent for publication Not applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests None Funding None Authors' contributions NS, ES conceived the study and designed the research. ES, NS and MS developed the methodology. Data collection and investigation were performed by ES and RL. RL conducted the formal analysis and NS, ES, RK, AH and DU performed data interpretation. The original draft of the manuscript was written by ES, NS, FH, and all authors contributed to reviewing and editing the final manuscript. Supervision and project administration were provided by CH, MS. All authors read and approved the final manuscript. Acknowledgements None References Drake SA, Holcomb JB, Yang Y, Thetford C, Myers L, Brock M et al. Establishing a regional pediatric trauma preventable/potentially preventable death rate. Pediatr Surg Int. 2020;36. Theodorou CM, Galganski LA, Jurkovich GJ, Farmer DL, Hirose S, Stephenson JT et al. Causes of early mortality in pediatric trauma patients. J Trauma Acute Care Surg. 2021;90. McLaughlin C, Zagory JA, Fenlon M, Park C, Lane CJ, Meeker D et al. Timing of mortality in pediatric trauma patients: A National Trauma Data Bank analysis. J Pediatr Surg. 2018;53. Freire GC, Beno S, Yanchar N, Weiss M, Stang A, Stelfox T et al. Clinical Practice Guideline Recommendations For Pediatric Multisystem Trauma Care: A Systematic Review. Ann Surg. 2023. Rossaint R, Afshari A, Bouillon B, Cerny V, Cimpoesu D, Curry N et al. The European guideline on management of major bleeding and coagulopathy following trauma: sixth edition. Crit Care [Internet]. 2023;27:1–45. Available from: https://doi.org/10.1186/s13054-023-04327-7 Shackelford SA, del Junco DJ, Powell-Dunford N, Mazuchowski EL, Howard JT, Kotwal RS et al. Association of Prehospital Blood Product Transfusion During Medical Evacuation of Combat Casualties in Afghanistan With Acute and 30-Day Survival. JAMA [Internet]. 2017;318:1581. Available from: http://jama.jamanetwork.com/article.aspx?doi=10.1001/jama.2017.15097 Shand S, Curtis K, Dinh M, Burns B. What is the impact of prehospital blood product administration for patients with catastrophic haemorrhage: an integrative review. Injury. 2019. Thies KC, Truhlář A, Keene D, Hinkelbein J, Rützler K, Brazzi L et al. Pre-hospital blood transfusion- A n ESA survey of European practice. Scand J Trauma Resusc Emerg Med. 2020;28. Selleng K, Baschin M, Henkel B, Jenichen G, Thies KC, Rudolph M et al. Blood Product Supply for a Helicopter Emergency Medical Service. Transfus Med Hemotherapy. 2021;48. Pusateri AE, Moore EE, Moore HB, Le TD, Guyette FX, Chapman MP et al. Association of Prehospital Plasma Transfusion with Survival in Trauma Patients with Hemorrhagic Shock When Transport Times Are Longer Than 20 Minutes: A Post Hoc Analysis of the PAMPer and COMBAT Clinical Trials. JAMA Surg. 2020;155. Tucker H, Brohi K, Tan J, Aylwin C, Bloomer R, Cardigan R et al. Association of red blood cells and plasma transfusion versus red blood cell transfusion only with survival for treatment of major traumatic hemorrhage in prehospital setting in England: a multicenter study. Crit Care. 2023;27. Morgan KM, Abou-Khalil E, Strotmeyer S, Richardson WM, Gaines BA, Leeper CM. Association of Prehospital Transfusion With Mortality in Pediatric Trauma. JAMA Pediatr [Internet]. 2023;177:693. Available from: https://jamanetwork.com/journals/jamapediatrics/fullarticle/2805185 Gaessler H, Helm M, Kulla M, Hossfeld B, Riedel J, Kerschowski J et al. Prehospital predictors of the need for transfusion in patients with major trauma. Eur J Trauma Emerg Surg. 2023;49. Gaessler H, Helm M, Kulla M, Hossfeld B, Riedel J, Kerschowski J, et al. Prehospital predictors of the need for transfusion in patients with major trauma. Eur J Trauma Emerg Surg. 2023;49:803–12. Sullivan TM, Milestone ZP, Tempel PE, Gao S, Burd RS. Development and validation of a Bayesian belief network predicting the probability of blood transfusion after pediatric injury. J Trauma Acute Care Surg. 2023;94:304–11. World Medical Association Declaration of Helsinki. JAMA. 2013;310:2191. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61:344–9. Pape HC, Lefering R, Butcher N, Peitzman A, Leenen L, Marzi I et al. The definition of polytrauma revisited: An international consensus process and proposal of the new ‘Berlin definition’. J Trauma Acute Care Surg. 2014;77. Lefering R, Huber-Wagner S, Nienaber U, Maegele M, Bouillon B. Update of the trauma risk adjustment model of the TraumaRegister DGUTM: The Revised Injury Severity Classification, version II. Crit Care. 2014;18. Shroyer MC, Griffin RL, Mortellaro VE, Russell RT. Massive transfusion in pediatric trauma: analysis of the National Trauma Databank. J Surg Res. 2017;208:166–72. Yin G, Radulovic N, O’Neill M, Lightfoot D, Nolan B. Predictors of Transfusion in Trauma and Their Utility in the Prehospital Environment: A Scoping Review. Prehospital Emerg Care. 2023;27:575–85. Pommerening MJ, Goodman MD, Holcomb JB, Wade CE, Fox EE, del Junco DJ, et al. Clinical gestalt and the prediction of massive transfusion after trauma. Injury. 2015;46:807–13. Stevens J, Reppucci ML, Meier M, Phillips R, Shahi N, Shirek G et al. Pre-hospital and emergency department shock index pediatric age-adjusted (SIPA) cut points to identify pediatric trauma patients at risk for massive transfusion and/or mortality. J Pediatr Surg. 2022;57. Reppucci ML, Acker SN, Cooper E, Meier M, Stevens J, Phillips R, et al. Improved identification of severely injured pediatric trauma patients using reverse shock index multiplied by Glasgow Coma Scale. Journal of Trauma and Acute Care Surgery; 2022. de Carlotti CP, do Amaral AP, de Carvalho Canela Balzi VH, Johnston AP, Regalio C, Cardoso FA. Management of severe traumatic brain injury in pediatric patients: an evidence-based approach. Neurol Sci. 2025;46:969–91. Additional Declarations No competing interests reported. Supplementary Files GraphicalAbstractTR.pdf Cite Share Download PDF Status: Published Journal Publication published 26 Nov, 2025 Read the published version in Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine → Version 1 posted Editorial decision: Revision requested 23 Sep, 2025 Reviews received at journal 21 Sep, 2025 Reviewers agreed at journal 18 Sep, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviewers agreed at journal 30 Jul, 2025 Reviews received at journal 28 Jul, 2025 Reviewers agreed at journal 28 Jul, 2025 Reviewers invited by journal 27 Jul, 2025 Editor assigned by journal 21 Jul, 2025 Submission checks completed at journal 15 Jul, 2025 First submitted to journal 12 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7108398","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":492236667,"identity":"74af1aaf-7a2a-47fc-9a38-a203ebb890e4","order_by":0,"name":"Niko R. E. Schneider","email":"","orcid":"","institution":"Justus-Liebig University, University Hospital Giessen","correspondingAuthor":false,"prefix":"","firstName":"Niko","middleName":"R. E.","lastName":"Schneider","suffix":""},{"id":492236668,"identity":"d4c7a954-7821-4d28-9525-4dd0ff2956ca","order_by":1,"name":"Ralf Kraus","email":"","orcid":"","institution":"Justus-Liebig University, University Hospital Giessen","correspondingAuthor":false,"prefix":"","firstName":"Ralf","middleName":"","lastName":"Kraus","suffix":""},{"id":492236669,"identity":"9bd2387d-cff5-4421-87da-722f07da69a5","order_by":2,"name":"Rolf Lefering","email":"","orcid":"","institution":"University Witten/Herdecke","correspondingAuthor":false,"prefix":"","firstName":"Rolf","middleName":"","lastName":"Lefering","suffix":""},{"id":492236670,"identity":"902a8e4b-805d-4ffc-b165-31669f3864b9","order_by":3,"name":"Fabian Hemm","email":"","orcid":"","institution":"Justus-Liebig University, University Hospital Giessen","correspondingAuthor":false,"prefix":"","firstName":"Fabian","middleName":"","lastName":"Hemm","suffix":""},{"id":492236671,"identity":"2988d313-179a-48fa-931a-ae7b6e6715e1","order_by":4,"name":"Davut Deniz Uzun","email":"","orcid":"","institution":"Heidelberg University","correspondingAuthor":false,"prefix":"","firstName":"Davut","middleName":"Deniz","lastName":"Uzun","suffix":""},{"id":492236672,"identity":"da9138cc-e50f-4fca-b8a0-6c3e0e6a3b18","order_by":5,"name":"Christan Heiss","email":"","orcid":"","institution":"Justus-Liebig University, University Hospital Giessen","correspondingAuthor":false,"prefix":"","firstName":"Christan","middleName":"","lastName":"Heiss","suffix":""},{"id":492236673,"identity":"fb986dd4-61ce-4454-b352-1d118d87b5ec","order_by":6,"name":"Andreas Hecker","email":"","orcid":"","institution":"Justus-Liebig University, University Hospital Giessen","correspondingAuthor":false,"prefix":"","firstName":"Andreas","middleName":"","lastName":"Hecker","suffix":""},{"id":492236674,"identity":"ec4344fb-5921-46c8-bed1-bee2b673837b","order_by":7,"name":"Michael Sander","email":"","orcid":"","institution":"Justus-Liebig University, University Hospital Giessen","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Sander","suffix":""},{"id":492236675,"identity":"2fa0625c-9210-4af0-8d4c-2acbf274f4d7","order_by":8,"name":"TraumaRegister DGU","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"TraumaRegister","middleName":"","lastName":"DGU","suffix":""},{"id":492236677,"identity":"586a75df-6c02-42e9-b0f8-86f4f4da55d9","order_by":9,"name":"Emmanuel Schneck","email":"data:image/png;base64,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","orcid":"","institution":"Justus-Liebig University, University Hospital Giessen","correspondingAuthor":true,"prefix":"","firstName":"Emmanuel","middleName":"","lastName":"Schneck","suffix":""}],"badges":[],"createdAt":"2025-07-12 13:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7108398/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7108398/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13049-025-01516-x","type":"published","date":"2025-11-26T15:58:41+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87885426,"identity":"adba2373-9446-4cf6-8b38-b9c39672f037","added_by":"auto","created_at":"2025-07-30 05:07:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":276796,"visible":true,"origin":"","legend":"\u003cp\u003eGraph showing the number of patients and the transfusion rate for each age.\u003c/p\u003e","description":"","filename":"TRtransfusionfigure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7108398/v1/10b69a835c41811081e9d805.jpg"},{"id":87884433,"identity":"f05a4123-9c57-4a23-9685-ac5d09ebbc81","added_by":"auto","created_at":"2025-07-30 04:59:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":299848,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative transfusion rate based on the scoring point derived from the logistic regression analysis. \u003cem\u003eAbbreviation: AIS = Abbreviated injury scale; CPR = Cardiopulmonary resuscitation.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7108398/v1/0a064bba57f387de199771a7.jpg"},{"id":87885425,"identity":"e0f1a96c-3d54-4ad9-bee9-43fc7e84d96a","added_by":"auto","created_at":"2025-07-30 05:07:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":17762,"visible":true,"origin":"","legend":"\u003cp\u003eResults to the ROC analysis for the prediction of an intrahospital transfusion.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7108398/v1/717ac6e0cb747cc93e4e4dc7.png"},{"id":97178628,"identity":"06a098ce-706f-47eb-ad83-c34bb56ce6fd","added_by":"auto","created_at":"2025-12-01 16:11:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1584643,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7108398/v1/78bb0b17-2ee3-4f51-983d-5edf6dd8a003.pdf"},{"id":87884426,"identity":"ebbbb073-f866-4dac-a6b6-a8635cac83cf","added_by":"auto","created_at":"2025-07-30 04:59:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":388952,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstractTR.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7108398/v1/845ef7e29a35b4e828b095d6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePredictors of Prehospital Transfusion in Paediatric Trauma: A Retrospective Analysis of 11,849 Cases from the TraumaRegister DGU\u003csup\u003eⓇ\u003c/sup\u003e\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eTrauma remains the leading cause of death in children in Europe and the United States (US) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The main factors contributing to this high mortality rate are traumatic brain injuries, hypoxia, and haemorrhage, which rapidly worsen the patient\u0026rsquo;s condition and often result in death at the scene [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. An analysis of the National Trauma Data Bank of the US found that 51% of paediatric patients were already deceased upon arrival, highlighting the need for urgent treatment at the scene [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConsidering causes of death, as delineated by the cABCDE algorithm, emergency medical services (EMS) should address the most urgent issues in paediatric trauma, that is, immediate critical bleeding control, securing the airway and providing adequate ventilation, volume resuscitation, and minimising on-scene time, to enable timely surgical treatment and transfusion [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The transfusion of red blood cell (RBC) concentrates, combined with the replacement of coagulation factors and platelets, remains an essential component of trauma resuscitation in the emergency room [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDerived from military experience, the prehospital transfusion (PT) of RBCs has been introduced into civilian EMS [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Increasing evidence supports PT in adult populations based on reduced trauma-associated morbidity and mortality; thus, it has been implemented in European EMS [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. A survey by the European Society of Anaesthesiology revealed that 48% of respondents, primarily from helicopter EMS, had the logistical capacity to perform PT [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. PT\u0026rsquo;s technical feasibility has also been proven previously [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Recently, the combined use of RBC and plasma was shown to improve survival in adult trauma patients [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Only limited data on PT in children are available. However, in 2023, a landmark study by Morgan et al. investigated 559 children from the Pennsylvania Trauma Systems Foundation database, 13% of whom received PT. The study showed that early transfusion at the scene resulted in reduced 24-hour and in-hospital mortality compared to early in-hospital transfusion [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Therefore, the PT of RBCs should be considered in critically injured children.\u003c/p\u003e\u003cp\u003eIn addition to establishing the logistics for PT, determining the correct indication remains a major challenge for emergency response teams. On one hand, unnecessary transfusions must be avoided; on the other hand, restrictive approaches might lead to further deterioration of the circulation. EMS face a time-critical situation and only have information on the patient\u0026rsquo;s current status to decide if a transfusion should be performed. Data derived from adult populations suggest indicators for coagulopathy, such as base excess and lactate levels, as predictors for massive transfusion. Often, these are not available on site [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In general, data on predictors for trauma-associated transfusions in children are limited [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, the present analysis aimed to identify predictors available to EMS at the scene for early in-hospital transfusion in a large paediatric trauma cohort.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cb\u003eStudy design\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003cp\u003eA retrospective analysis of the German TraumaRegister DGU\u003csup\u003e\u0026reg;\u003c/sup\u003e of the German Trauma Society (Deutsche Gesellschaft f\u0026uuml;r Unfallchirurgie (DGU)) was performed. As it involved analyses of routine, anonymous data, no ethical approval was necessary (Justus Liebig University Giessen, Giessen, Germany; correspondence from February 25, 2025). The study followed the current publication guidelines of the TraumaRegister DGU\u0026reg; and was registered under the TR-DGU Project ID 2024\u0026ndash;040. The study was conducted according to the principles of the Declaration of Helsinki [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The methods and results are presented according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eTraumaRegister DGU\u0026reg;\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe TraumaRegister DGU\u0026reg; of the German Trauma Society was founded in 1993. This multicentre database aims for the pseudonymised and standardised documentation of severely injured patients. Data are collected prospectively in four consecutive time phases from the site of the accident until discharge from the hospital: A) prehospital phase, B) emergency room and initial surgery, C) intensive care unit (ICU), and D) discharge. The documentation includes detailed information on demographics, injury pattern, comorbidities, pre- and in-hospital management, course in the intensive care unit, relevant laboratory findings (including data on transfusion), and the outcome of each individual. The inclusion criterion is hospital admission via the emergency room with subsequent ICU care or arrival at the hospital with vital signs and death before ICU admission.\u003c/p\u003e\u003cp\u003eThe infrastructure for documentation, data management, and data analysis is provided by the Academy for Trauma Surgery (Akademie der Unfallchirurgie GmbH), a company affiliated with the German Trauma Society. The scientific leadership is provided by the Committee on Emergency Medicine, Intensive Care and Trauma Management (Sektion NIS) of the German Trauma Society. The participating hospitals submit their pseudonymised data to a central database via a web-based application. Scientific data analysis is approved according to a peer review procedure in the publication guidelines of TraumaRegister DGU\u0026reg;. The participating hospitals are primarily located in Germany (90%), but a rising number of hospitals from other countries also contribute data (currently, Austria, Belgium, China, Finland, Luxembourg, Slovenia, Switzerland, the Netherlands, and the United Arab Emirates). Currently, about 38,000 cases from almost 700 hospitals are entered into the database per year. Participation in TraumaRegister DGU\u0026reg; is voluntary. For hospitals associated with TraumaNetzwerk DGU\u0026reg;, however, the entry of at least a basic dataset is obligatory for quality assurance purposes.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cb\u003eInclusion criteria\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study included patients from Germany, Austria, and Switzerland over a 15-year period (January 1, 2008, to December 31, 2023). Only children and adolescents aged 1 to 16 years were included. Transfers between hospitals to higher-level care centres were excluded. Only data from the core collective were analysed. To exclude patients with minor injuries, only those with a Maximal Abbreviated Injury Scale (MAIS) score\u0026thinsp;\u0026ge;\u0026thinsp;3 or those with a MAIS score\u0026thinsp;\u0026ge;\u0026thinsp;2 who required ICU treatment or died were included.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive analysis of the study cohort was performed, with data presented as absolute numbers and percentages. Metric data are presented as mean with standard deviation (SD). Parameters included baseline characteristics, as well as details regarding the severity and location of injuries. An Abbreviated Injury Scale (AIS) score\u0026thinsp;\u0026ge;\u0026thinsp;3 was classified as a serious injury, while an Injury Severity Score (ISS)\u0026thinsp;\u0026ge;\u0026thinsp;16 was considered indicative of severe multiple trauma. Polytrauma was defined according to the Berlin definition as injuries affecting at least two body regions with an AIS score\u0026thinsp;\u0026ge;\u0026thinsp;3, accompanied by at least one physiological deterioration parameter (systolic blood pressure\u0026thinsp;\u0026le;\u0026thinsp;90 mmHg, Glasgow Coma Scale\u0026thinsp;\u0026le;\u0026thinsp;8, base excess\u0026thinsp;\u0026le;\u0026thinsp;\u0026minus;\u0026thinsp;6.0 mmol/L, coagulopathy (INR\u0026thinsp;\u0026ge;\u0026thinsp;1.4 or PTT\u0026thinsp;\u0026ge;\u0026thinsp;40 s), or body temperature\u0026thinsp;\u0026le;\u0026thinsp;34\u0026deg;C) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. High-energy trauma was defined as injuries resulting from motor vehicle collisions, motor bike accidents, or falls from a height of \u0026ge;\u0026thinsp;3 metres.\u003c/p\u003e\u003cp\u003eThe chi-square test was used for categorical data, comparing patients with and without transfusions; metric data were compared with the Mann\u0026ndash;Whitney U-test. A \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003cp\u003eFinally, a multivariate logistic regression analysis with transfusion as the dependent variable was performed, including potential predictors from the univariate analysis. Only parameters available at the scene were taken into account. Since several parameters differed significantly between patients with and without transfusion, trauma experts assessed if they were clinically present for EMS before validation in the multivariate regression analysis. The results are presented as adjusted odds ratios (ORs) with 95% confidence intervals. Variables with an OR\u0026thinsp;\u0026gt;\u0026thinsp;2.0 were used to build a simple point score: 1 point if the OR was 2.0\u0026ndash;4.0 and 2 points if the OR was \u0026gt;\u0026thinsp;4.0. Receiver operating characteristic (ROC) curve analysis was then performed to assess the predictive accuracy of the score. The area under the ROC curve was presented with 95% confidence intervals.\u003c/p\u003e\u003cp\u003eStatistical analyses were conducted using SPSS (version 29, IBM Inc., Armonk, NY, US).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eStudy cohort\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, 11,849 patients of 569 hospitals were included in the study, with blood transfusions performed in 5.9% of cases. If patients were transfused, they received 4.1 (SD 8.8) RBC units on average. The transfusion rate remained relatively stable across different age categories, ranging from 4.2% in 12-year-olds to 8.0% in 1-year-olds (Figure 1). The mean age of the included patients was 9.6 years (SD 4.5). However, the absolute number of transfusions increased significantly in older children and adolescents, who accounted for 51% of all transfusions (age \u0026ge; 11\u0026ndash;16 years, n = 358, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe majority of patients were treated in level 1 or 2 hospitals, while only a small minority (\u0026lt; 1%) received transfusions in level 3 hospitals. The mean transportation time from scene to hospital was 59.9 minutes (SD 26.2, n = 9,185). Baseline characteristics and the underlying trauma mechanisms are shown in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eBasic characteristics and overview of underlying trauma mechanisms.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.7959%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eParameters\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAll patients\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e(n = 11,849)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNo transfusion\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e(n = 11,147)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3061%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTransfusion\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e(n = 702)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2041%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.7959%;\"\u003e\n \u003cp\u003e\u003cem\u003eAge (years)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Toddler [1-5 years], n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;School child [6-10 years], n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Adolescents [11-15 years], n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2,634 (22.2)\u003c/p\u003e\n \u003cp\u003e3,256 (27.5)\u003c/p\u003e\n \u003cp\u003e5,959 (50.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2,458 (22.1)\u003c/p\u003e\n \u003cp\u003e3,088 (27.7)\u003c/p\u003e\n \u003cp\u003e5,601 (50.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3061%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e176 (25.1)\u003c/p\u003e\n \u003cp\u003e168 (23.9)\u003c/p\u003e\n \u003cp\u003e358 (51.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2041%;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.7959%;\"\u003e\n \u003cp\u003e\u003cem\u003eSex (n = 11,838)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Male, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7,444\u0026nbsp;(62.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7,031 (63.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3061%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e413 (58.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2041%;\"\u003e\n \u003cp\u003e.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.7959%;\"\u003e\n \u003cp\u003e\u003cem\u003eDied in hospital\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e571 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e313 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.3061%;\"\u003e\n \u003cp\u003e258 (36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2041%;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.7959%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrauma mechanism\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Motor vehicle accident, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Motorcycle accident, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Bicycle accident, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003cem\u003ePedestrian accident, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Fall from a height of \u0026ge;3 m, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Fall from a height of \u0026lt;3 m, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Others, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1,320 (11.3)\u003c/p\u003e\n \u003cp\u003e736 (6.3)\u003c/p\u003e\n \u003cp\u003e1,833 (15.7)\u003c/p\u003e\n \u003cp\u003e2,331 (20.0)\u003c/p\u003e\n \u003cp\u003e2,043 (17.5)\u003c/p\u003e\n \u003cp\u003e1,632 (14.0)\u003c/p\u003e\n \u003cp\u003e1,748 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1,188 (10.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;685 (6.3)\u003c/p\u003e\n \u003cp\u003e1,750 (16.0)\u003c/p\u003e\n \u003cp\u003e2,198 (20.1)\u003c/p\u003e\n \u003cp\u003e1,899 (17.3)\u003c/p\u003e\n \u003cp\u003e1,602 (14.6)\u003c/p\u003e\n \u003cp\u003e1,630 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3061%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e132 (19.1)\u003c/p\u003e\n \u003cp\u003e51 (7.4)\u003c/p\u003e\n \u003cp\u003e83 (12.0)\u003c/p\u003e\n \u003cp\u003e133 (19.2)\u003c/p\u003e\n \u003cp\u003e144 (20.8)\u003c/p\u003e\n \u003cp\u003e30 (4.3)\u003c/p\u003e\n \u003cp\u003e118 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2041%;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.7959%;\"\u003e\n \u003cp\u003e\u003cem\u003eSevere trauma types\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;High energy trauma\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Traffic-associated accidents\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Penetrating trauma\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Violence-associated trauma\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4,099 (34.6)\u003c/p\u003e\n \u003cp\u003e6,576 (55.5)\u003c/p\u003e\n \u003cp\u003e334 (2.8)\u003c/p\u003e\n \u003cp\u003e156 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3,772 (32.7)\u003c/p\u003e\n \u003cp\u003e6,143 (55.1)\u003c/p\u003e\n \u003cp\u003e276 (2.5)\u003c/p\u003e\n \u003cp\u003e129 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3061%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e327 (40.4)\u003c/p\u003e\n \u003cp\u003e433 (61.7)\u003c/p\u003e\n \u003cp\u003e58 (8.3)\u003c/p\u003e\n \u003cp\u003e27 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2041%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.7959%;\"\u003e\n \u003cp\u003e\u003cem\u003eLevel of hospital care\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Basic hospital care (Level 3)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Specialized hospital care (Level 2)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Comprehensive hospital care (Level 1)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e784 (6.6)\u003c/p\u003e\n \u003cp\u003e3,008 (25.4)\u003c/p\u003e\n \u003cp\u003e8,057 (68.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e765 (6.9)\u003c/p\u003e\n \u003cp\u003e2,903 (26.0)\u003c/p\u003e\n \u003cp\u003e7.479 (67.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3061%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19 (2.7)\u003c/p\u003e\n \u003cp\u003e105 (15.0)\u003c/p\u003e\n \u003cp\u003e578 (82.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2041%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.7959%;\"\u003e\n \u003cp\u003e\u003cem\u003eHelicopter emergency medical service transportation\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e3,335 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e3,040 (28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3061%;\"\u003e\n \u003cp\u003e295 (43.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2041%;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.7959%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrauma severity\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eISS \u0026ge;16, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Polytrauma, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Single trauma, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5,048 (42.6)\u003c/p\u003e\n \u003cp\u003e995 (8.4)\u003c/p\u003e\n \u003cp\u003e6,591 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4,405 (39.5)\u003c/p\u003e\n \u003cp\u003e630 (5.7)\u003c/p\u003e\n \u003cp\u003e6,333 (58.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3061%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e643\u0026nbsp;(91.6)\u003c/p\u003e\n \u003cp\u003e365 (52.0)\u003c/p\u003e\n \u003cp\u003e258 (36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2041%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.7959%;\"\u003e\n \u003cp\u003e\u003cem\u003eAbbreviated injury scale\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;AIS head \u0026ge;3, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;AIS thorax \u0026ge;3, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;AIS abdomen \u0026ge;3, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;AIS extremities \u0026ge;3, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4,321 (35.5)\u003c/p\u003e\n \u003cp\u003e2,366 (20.0)\u003c/p\u003e\n \u003cp\u003e1,330 (11.2)\u003c/p\u003e\n \u003cp\u003e2,678 (22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3469%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3,901 (35)\u003c/p\u003e\n \u003cp\u003e2,006 (18)\u003c/p\u003e\n \u003cp\u003e1,075 (9.6)\u003c/p\u003e\n \u003cp\u003e2,390 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3061%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e420 (59.8)\u003c/p\u003e\n \u003cp\u003e360 (51.3)\u003c/p\u003e\n \u003cp\u003e255 (36.3)\u003c/p\u003e\n \u003cp\u003e288 (41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2041%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as absolute numbers and percentages. Data points were available in 11,643 cases for trauma mechanisms and in 11,423 for helicopter emergency medical service transportation, respectively. All other parameters were available in all included patients. Statistical significance refers to the difference between transfused and non-transfused patients per each parameter. P-values were calculated using the chi-square test. \u003cem\u003eAbbreviations: AIS = abbreviated injury scale; ISS = injury severity scale.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInjury severity\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn total, 42.6% of patients suffered from severe trauma, defined as an ISS \u0026ge; 16 (mean ISS 15.7, SD 11.2; n = 11,849), while only 8.4% met the Berlin definition of polytrauma. The risk of death based on the Revised Injury Severity Scale II (RISC II) was 34.7% (n = 702) and 3.4% (n = 11,147) in transfused and non-transfused patients, respectively [19]. The mean ISS of non-transfused patients was 14.7 (SD 9.7), whereas transfused patients had a significantly higher mean ISS of 34.1 (SD 16.2; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01). While children with polytrauma (Berlin definition) reached the highest specificity for transfusion (94.3 %), the sensitivity remained low (52%). The ISS offered a low specificity (60.5%) but a high sensitivity (91.6%). Overall, with the exception of an ISS \u0026ge; 16 (positive predictive value (PPV) 63.2 %), the PPV of single parameters remained low (Table 2). The highest transfusion rates were observed in children with head and thoracic injuries, followed by extremity and abdominal injuries (Table 1).\u003c/p\u003e\n\u003cp\u003eAn AIS \u0026ge; 3 did sufficiently discriminate between transfused and non-transfused patients, which was particularly evident for abdominal injuries. Most patients (63.7%) with abdominal lesions were categorised as AIS \u0026lt; 3. Nevertheless, robust statistical differences were observed, with significantly more transfused than non-transfused children across all AIS categories, ISS \u0026ge; 16, polytrauma, and single trauma.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e. Prevalence, specificity, sensitivity, and positive predictive value (PPV) for various clinical predictors of transfusion.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eParameters\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ePrevalence\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e(n, %)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSpecificity\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e(%)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eS\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eensitivity (%)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003ePV\u003cbr\u003e\u0026nbsp;(%)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTrauma severity\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cem\u003eISS \u0026ge;16\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003cem\u003eolytrauma\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eIsolated injury\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePenetrating trauma\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eViolence-associated trauma\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHigh energy trauma\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eTraffic-associated accidents\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e5,048 (42.6)\u003c/p\u003e\n \u003cp\u003e995 (8.4)\u003c/p\u003e\n \u003cp\u003e6,591 (55.6)\u003c/p\u003e\n \u003cp\u003e334 (2.8)\u003c/p\u003e\n \u003cp\u003e156 (1.3)\u003c/p\u003e\n \u003cp\u003e4099 (34.6)\u003c/p\u003e\n \u003cp\u003e6576 (55.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e60.5\u003c/p\u003e\n \u003cp\u003e94.3\u003c/p\u003e\n \u003cp\u003e43.2\u003c/p\u003e\n \u003cp\u003e97.5\u003c/p\u003e\n \u003cp\u003e98.8\u003c/p\u003e\n \u003cp\u003e66.2\u003c/p\u003e\n \u003cp\u003e44.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e91.6\u003c/p\u003e\n \u003cp\u003e52.0\u003c/p\u003e\n \u003cp\u003e36.8\u003c/p\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003cp\u003e46.6\u003c/p\u003e\n \u003cp\u003e61.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e63.2\u003c/p\u003e\n \u003cp\u003e45.6\u003c/p\u003e\n \u003cp\u003e44.8\u003c/p\u003e\n \u003cp\u003e17.4\u003c/p\u003e\n \u003cp\u003e17.3\u003c/p\u003e\n \u003cp\u003e8.0\u003c/p\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eInjury pattern (AIS\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026ge; 3)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cem\u003eSerious head injury\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSerious thorax trauma\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSerious abdominal trauma\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSerious extremity injury\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e4321 (36.5)\u003c/p\u003e\n \u003cp\u003e2366 (20.0)\u003c/p\u003e\n \u003cp\u003e1330 (11.2)\u003c/p\u003e\n \u003cp\u003e2678 (22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e65.0\u003c/p\u003e\n \u003cp\u003e82.0\u003c/p\u003e\n \u003cp\u003e90.4\u003c/p\u003e\n \u003cp\u003e78.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e59.8\u003c/p\u003e\n \u003cp\u003e51.3\u003c/p\u003e\n \u003cp\u003e36.3\u003c/p\u003e\n \u003cp\u003e41.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003cp\u003e19.2\u003c/p\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ePre-clinical assessment and interventions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cem\u003eSystolic blood pressure \u0026le;90 mmHg\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eGlasgow Coma Scale 3 \u0026ndash; 8\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eVolume therapy\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCatecholamine therapy #\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCardiopulmonary resuscitation\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eTracheal Intubation\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eEmergency thoracocentesis #\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e1266 (13.6)\u003c/p\u003e\n \u003cp\u003e1942 (18.0)\u003c/p\u003e\n \u003cp\u003e8439 (74.8)\u003c/p\u003e\n \u003cp\u003e434 (6.4)\u003c/p\u003e\n \u003cp\u003e433 (3.8)\u003c/p\u003e\n \u003cp\u003e2668 (23.6)\u003c/p\u003e\n \u003cp\u003e108 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e88.1\u003c/p\u003e\n \u003cp\u003e84.6\u003c/p\u003e\n \u003cp\u003e25.6\u003c/p\u003e\n \u003cp\u003e95.9\u003c/p\u003e\n \u003cp\u003e97.5\u003c/p\u003e\n \u003cp\u003e79.2\u003c/p\u003e\n \u003cp\u003e99.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e42.7\u003c/p\u003e\n \u003cp\u003e59.4\u003c/p\u003e\n \u003cp\u003e81.1\u003c/p\u003e\n \u003cp\u003e33.5\u003c/p\u003e\n \u003cp\u003e23.7\u003c/p\u003e\n \u003cp\u003e67.8\u003c/p\u003e\n \u003cp\u003e9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003cp\u003e19.8\u003c/p\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003cp\u003e40.3\u003c/p\u003e\n \u003cp\u003e37.6\u003c/p\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003cp\u003e45.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e# not available in the reduced basic dataset. \u003cem\u003eAbbreviations: AIS = abbreviated injury scale; ISS = injury severity scale.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Contingency tables on indices of the clinical appearance and performed emergency procedures.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eParameters\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNo transfusion\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e(n = 11,147)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTransfusion\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e(n = 702)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eClinical appearance\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003eSystolic blood pressure \u0026le;90 mmHg\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e1,043 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e223 (42.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003eGlasgow Coma Scale\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; 13-15, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; 9-12, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; 3-8, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6,956 (68.6)\u003c/p\u003e\n \u003cp\u003e1,624 (16.0)\u003c/p\u003e\n \u003cp\u003e1,558 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e176 (27.2)\u003c/p\u003e\n \u003cp\u003e86 (13.3)\u003c/p\u003e\n \u003cp\u003e384 (59.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003ePupillary light responsiveness\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; normal, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; delayed, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; none, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7,095 (88.3)\u003c/p\u003e\n \u003cp\u003e605 (7.5)\u003c/p\u003e\n \u003cp\u003e333 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e273 (49.1)\u003c/p\u003e\n \u003cp\u003e95 (17.1)\u003c/p\u003e\n \u003cp\u003e188 (33.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003ePupillary size\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; regular size, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;anisocor, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;bilaterally dilated, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10,052 (92.8)\u003c/p\u003e\n \u003cp\u003e343 (3.2)\u003c/p\u003e\n \u003cp\u003e438 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e434 (63.8)\u003c/p\u003e\n \u003cp\u003e62 (9.1)\u003c/p\u003e\n \u003cp\u003e184 (27.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eEmergency procedures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003eVolume therapy, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e7,882 (74.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e557 (81.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003eCatecholamine therapy, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e259 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e175 (33.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003eCardiopulmonary resuscitation, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e270 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e163 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003eTracheal Intubation, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e2,202 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e466 (67.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003eEmergency thoracocentesis, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e59 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e49 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as absolute numbers and percentages. Volume therapy was defined as the administration of at least one unit of fluid (500 mL of crystalloids or colloids). Data was available for Glasgow coma scale in 10,784 cases, for pupillary light responsiveness in 8,589 cases, for pupillary size in 10,486 cases, volume therapy 6,775 cases, catecholamine therapy in 6,775 cases, cardiopulmonary resuscitation in 11,286 cases, tracheal intubation in 11,286 cases and thoracocentesis in 6,775 cases. All other parameters were available in all included patients. Statistical significance refers to the difference between transfused and non-transfused patients per each parameter. P-values were calculated using the chi-square test based on contingency tables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical status of patients and emergency procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn total, 33.9% of patients were not alert at the scene, of whom 15.9% had a Glasgow Coma Scale (GCS) of 9\u0026ndash;12, and 18% had a GCS \u0026le; 8. Overall, in 23.7% of cases, the airway was secured via intubation. The transfusion rate was significantly higher in unresponsive patients (GCS 3\u0026ndash;8), those with pathological pupil reactions, and those requiring intubation (Table 3). Patients with a GCS of 9\u0026ndash;12 did not have an increased need for transfusion.\u003c/p\u003e\n\u003cp\u003eRegardless of age, a systolic blood pressure \u0026le; 90 mmHg was associated with a higher need for transfusion. At the scene, the mean systolic blood pressure was 115 mmHg (SD 26, n = 9,278), and the mean heart rate was 102 bpm (SD 27, n = 6,448). These vital signs did not differ at hospital admission (systolic blood pressure: 117 mmHg (SD 24); heart rate: 101 bpm (SD 25). No information on capillary refill time was available.\u003c/p\u003e\n\u003cp\u003eIn total, patients received an average of 464 mL of fluids at the scene (SD 453, n = 11,286) and 768 mL in the resuscitation room (SD 1027, n = 5,772). Patients requiring transfusion received significantly more fluids (scene: 753 mL (SD 779) vs. 446 mL (SD 417); hospital: 2184 mL (SD 2160) vs. 640 mL (SD 731); \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk prediction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe final multivariate logistic regression model included 10,594 patients. The included parameters of the regression model are shown in Table 4.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe transfusion rate increased significantly from 7.4% (2 points) to 21.6% when 3 points were achieved (Figure 2). If 5 or more points were reached, the transfusion rate exceeded 50%. ROC analysis showed a predictive value of 0.87 [0.85\u0026ndash;0.88] for transfusion prediction (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Results of the multivariate logistic regression analysis.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eParameters\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAdj. Odds ratio\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e95%-confidence interval\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eWeighting\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cem\u003eInjury severity\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Polytrauma\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Thoracic AIS \u0026ge;3\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Abdominal AIS \u0026ge;3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.18\u003c/p\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003cp\u003e4.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.26 \u0026ndash; 5.34\u003c/p\u003e\n \u003cp\u003e0.95 \u0026ndash; 1.49\u003c/p\u003e\n \u003cp\u003e3.34 \u0026ndash; 5.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cem\u003eGlasgow Coma Scale\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; 9-12\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;3-8\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003cp\u003e2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.03 \u0026ndash; 1.86\u003c/p\u003e\n \u003cp\u003e1.85 \u0026ndash; 3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cem\u003eType of injury\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Penetrating\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; High energy trauma\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.96 \u0026ndash; 6.30\u003c/p\u003e\n \u003cp\u003e1.28 \u0026ndash; 1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cem\u003eEmergency procedures\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;Endotracheal Intubation\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Cardiopulmonary resuscitation\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003cp\u003e2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.93 \u0026ndash; 3.28\u003c/p\u003e\n \u003cp\u003e1.84 \u0026ndash; 3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAbbreviation: AIS = Abbreviated injury scale.\u003c/em\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study reviewed several predictors of early in-hospital transfusions in a large paediatric trauma cohort of\u0026nbsp;11,849 patients. It demonstrated that prehospital assessment of clinically apparent parameters can sufficiently predict the need for PT. The highest risk for transfusion was observed in patients with penetrating trauma, abdominal injuries, and polytrauma, followed by those who were unconscious, required tracheal intubation, or underwent cardiopulmonary resuscitation.\u003c/p\u003e\n\u003cp\u003eA notable strength of this study lies in the high number of patients included, a crucial consideration given the limited number of paediatric trauma cases where transfusion was needed and the paucity of prospective studies in this domain. The observed transfusion rate is consistent with data from the US National Trauma Databank, which reported a transfusion rate of 4% within the first 24 hours after hospital admission [20]. Like the data presented, a higher absolute number of transfusions was observed in older children and adolescents, severely injured patients (ISS ≥ 25), and unresponsive patients, making the results comparable to those in the US population.\u003c/p\u003e\n\u003cp\u003eSeveral studies have investigated diagnostic algorithms for predicting transfusions in adults, resulting in the development of more than 20 scoring tools [21,22]. In contrast, transfusion prediction in paediatric trauma care has been studied less. To date, only one other large registry study, an analysis of the Trauma Quality Improvement Project (TQIP), has aimed to identify intra- and prehospital predictors for transfusion after paediatric trauma [15]. This study used a Bayesian Belief Network to predict the probability of in-hospital transfusions in severely injured children. The transfusion rate in the TQIP study was lower than in the present analysis, with 2.8% of patients receiving a transfusion within the first 4 hours after hospital admission. The model included 14 parameters and demonstrated a high predictive power for transfusion. The most influential predictors were GCS and impaired systolic blood pressure at admission and at the scene. This finding is particularly relevant because systolic blood pressure was not adjusted for age, indicating that a blood pressure ≤ 90 mmHg is predictive of transfusion regardless of age, aligning with our study. However, this finding should be interpreted with caution as 50% of the patients in our study were older than 10 years, and 27% were aged between 5 and 10 years. This suggests that while hypotension may be predictive of the need for transfusion in school-aged children and adolescents, it may not necessarily apply to younger children. This may also account for the significantly higher transfusion rate in this study, despite these factors not being independent predictors of transfusion, possibly since blood pressure and other vital signs were likely optimised by EMS personnel before hospital admission. Additionally, this might explain why heart rate failed to predict transfusion in our study and had only a minor impact in the TQIP study, especially when only prehospital vital signs were considered. Undisputably, age-adjusted vital parameters are ideal for the assessment of children’s hemodynamic status; however, these measurements are not practically achievable at the scene in emergencies [23,24]. Therefore, heart rate and blood pressure do not necessarily comprise important indicators of the need for transfusion, most likely because vital parameters were not analysed in an age-adjusted manner. Unfortunately, the capillary refill time, which could have been an easily assessable option, was not available in the TraumaRegister DGU\u003csup\u003eâ\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo address these limitations, we focused on identifying predictors available at the scene and excluded all in-hospital parameters. Consistent with our findings, the TQIP registry showed that only the inclusion of impaired GCS improved the model’s predictive accuracy (AUC ROC 0.84 vs. 0.87 in our study), highlighting the importance of GCS assessment. On the other hand, abdominal injuries, the need for resuscitation, and the presence of multiple injuries did not improve the Bayesian model, whereas these factors were among the strongest predictors in our logistic model. Interestingly, the accident mechanism improved the predictive accuracy of the TQIP model, whereas the resulting injuries did not. This may be explained by the fact that the accident mechanism serves as an early proxy for injury severity, while the actual injuries often require time-consuming diagnostics. Since transfusion decisions must frequently be made before a complete assessment is available, the accident mechanism might have had a greater impact on the predictive model. Additionally, prehospital interventions could have mitigated the effects of some injuries, further reducing their predictive value. Finally, it is important to note that the TQIP analysis has not yet been externally validated.\u003c/p\u003e\n\u003cp\u003eLow GCS, tracheal intubation, and cardiopulmonary resuscitation showed a lower adjusted OR than the presence of polytrauma and abdominal and penetrating trauma. In our opinion, this reflects the underlying trauma pathophysiology. An impaired GCS is often caused by severe traumatic brain injury and the subsequent tracheal intubation and/or resuscitation [25]. On the other hand, multiple, penetrating, and abdominal traumas display common causes of severe bleeding [20,22]. In summary, it is important to understand that with the exception of an ISS ≥ 16, the positive predictive value of individual parameters remains low, but their combination allows for a reliable prediction of transfusion needs. While some parameters were highly specific but had low sensitivity, the opposite was true for others. Moreover, the high prevalence of certain parameters (e.g., volume therapy) further reduced the positive predictive value. Therefore, each patient should be assessed based on multiple transfusion indicators rather than a single definitive criterion.\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. First and most importantly, it lacks a validation cohort. This is due to the low incidence of paediatric trauma requiring transfusion, which posed a challenge for the study design. To generate a derivation cohort with sufficient transfused patients, a large dataset was required, which was feasible in this study. However, this approach limited the possibility of creating a separate validation cohort. Additionally, data quality before 2008 was insufficient, and transfusion strategies may have changed over the past 25 years, making a historical validation cohort unfeasible. The use of data from other countries was also not a viable option, as only 5% of the TraumaRegister DGU\u003csup\u003eâ\u003c/sup\u003e data originates from outside Germany, Austria, and Switzerland. For these reasons, this study focused on identifying predictors for transfusion rather than dividing the study population. To develop a reliable scoring tool, the identified risk factors must first be validated. Second, children under 1 year of age were excluded due to limited data availability. However, most children were of school age or adolescents; therefore, the bias probably has little impact on the study results. Nevertheless, future studies should focus on neonates and infants, despite the rarity of these cases, to better understand their specific clinical outcomes. Third, only limited datasets were available for lactate and base excess, which have been identified as potential predictors of transfusion and could be assessed at the scene using point-of-care devices [13]. Fourth, this study did not report the amount of blood transfused relative to the patient’s body weight. Fifth, Due to changes in documentation practices in 2020, with separate recording of transfusions in the trauma bay and operating room introduced only thereafter, a consistent phase-specific analysis across the full study period (2009–2023) was not methodologically feasible. Finally, due to the retrospective design, the investigators had to rely on the quality of the documentation within the database.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, based on a large cohort of 11,849 severely injured children and adolescents, this study demonstrated that the risk for intrahospital transfusion can be assessed using parameters available in the prehospital setting. This information aids in evaluating the need for PT in these patients. An impaired GCS proved to be more predictive than other impaired vital parameters, such as hypotension or tachycardia, likely due to prior correction by EMS. Particularly in the case of multiple, abdominal, and penetrating trauma, the probability of blood loss increases to such an extent that the PT of RBC can be considered. All the included parameters are straightforward to assess, making them practical for use by emergency medical teams. Therefore, the proposed risk factors can help identify patients at risk of severe haemorrhage and the subsequent transfusion requirement.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAdj. OR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Adjusted odds ratio\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAIS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Abbreviated Injury Scale\u003c/p\u003e\n\u003cp\u003eAUC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Area under the curve\u003c/p\u003e\n\u003cp\u003eDGU\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Deutsche Gesellschaft für Unfallchirurgie\u003c/p\u003e\n\u003cp\u003eEMS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Emergency medical services\u003c/p\u003e\n\u003cp\u003eGCS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Glasgow Coma Scale\u003c/p\u003e\n\u003cp\u003eICU\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Intensive care unit\u003c/p\u003e\n\u003cp\u003eINR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;International Normalised Ratio\u003c/p\u003e\n\u003cp\u003eISS Injury Severity Scale\u003c/p\u003e\n\u003cp\u003eMAIS Maximal Abbreviated Injury Scale\u003c/p\u003e\n\u003cp\u003ePPV\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Positive predictive value\u003c/p\u003e\n\u003cp\u003ePT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Prehospital transfusion\u003c/p\u003e\n\u003cp\u003ePTT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Partial Thromboplastin Time\u003c/p\u003e\n\u003cp\u003eRISC II Revised Injury Severity Scale II\u003c/p\u003e\n\u003cp\u003eRBC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Red blood cell concentrate\u003c/p\u003e\n\u003cp\u003eROC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Receiver operating characteristic\u003c/p\u003e\n\u003cp\u003eSD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Standard deviation\u003c/p\u003e\n\u003cp\u003eSTROBE Strengthening the Reporting of Observational Studies in Epidemiology\u003c/p\u003e\n\u003cp\u003eTQIP Trauma Quality Improvement Project\u003c/p\u003e\n\u003cp\u003eUS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; United States\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations:\u0026nbsp;\u003c/strong\u003enot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNS, ES conceived the study and designed the research. ES, NS and MS developed the methodology. Data collection and investigation were performed by ES and RL. RL conducted the formal analysis and NS, ES, RK, AH and DU performed data interpretation. The original draft of the manuscript was written by ES, NS, FH, and all authors contributed to reviewing and editing the final manuscript. Supervision and project administration were provided by CH, MS. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDrake SA, Holcomb JB, Yang Y, Thetford C, Myers L, Brock M et al. Establishing a regional pediatric trauma preventable/potentially preventable death rate. Pediatr Surg Int. 2020;36.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTheodorou CM, Galganski LA, Jurkovich GJ, Farmer DL, Hirose S, Stephenson JT et al. Causes of early mortality in pediatric trauma patients. J Trauma Acute Care Surg. 2021;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcLaughlin C, Zagory JA, Fenlon M, Park C, Lane CJ, Meeker D et al. Timing of mortality in pediatric trauma patients: A National Trauma Data Bank analysis. J Pediatr Surg. 2018;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFreire GC, Beno S, Yanchar N, Weiss M, Stang A, Stelfox T et al. Clinical Practice Guideline Recommendations For Pediatric Multisystem Trauma Care: A Systematic Review. Ann Surg. 2023.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRossaint R, Afshari A, Bouillon B, Cerny V, Cimpoesu D, Curry N et al. The European guideline on management of major bleeding and coagulopathy following trauma: sixth edition. Crit Care [Internet]. 2023;27:1\u0026ndash;45. 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Association of Prehospital Transfusion With Mortality in Pediatric Trauma. JAMA Pediatr [Internet]. 2023;177:693. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://jamanetwork.com/journals/jamapediatrics/fullarticle/2805185\u003c/span\u003e\u003cspan address=\"https://jamanetwork.com/journals/jamapediatrics/fullarticle/2805185\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGaessler H, Helm M, Kulla M, Hossfeld B, Riedel J, Kerschowski J et al. Prehospital predictors of the need for transfusion in patients with major trauma. Eur J Trauma Emerg Surg. 2023;49.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGaessler H, Helm M, Kulla M, Hossfeld B, Riedel J, Kerschowski J, et al. Prehospital predictors of the need for transfusion in patients with major trauma. 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Prehospital Emerg Care. 2023;27:575\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePommerening MJ, Goodman MD, Holcomb JB, Wade CE, Fox EE, del Junco DJ, et al. Clinical gestalt and the prediction of massive transfusion after trauma. Injury. 2015;46:807\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStevens J, Reppucci ML, Meier M, Phillips R, Shahi N, Shirek G et al. Pre-hospital and emergency department shock index pediatric age-adjusted (SIPA) cut points to identify pediatric trauma patients at risk for massive transfusion and/or mortality. J Pediatr Surg. 2022;57.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReppucci ML, Acker SN, Cooper E, Meier M, Stevens J, Phillips R, et al. Improved identification of severely injured pediatric trauma patients using reverse shock index multiplied by Glasgow Coma Scale. Journal of Trauma and Acute Care Surgery; 2022.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Carlotti CP, do Amaral AP, de Carvalho Canela Balzi VH, Johnston AP, Regalio C, Cardoso FA. Management of severe traumatic brain injury in pediatric patients: an evidence-based approach. Neurol Sci. 2025;46:969\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scandinavian-journal-of-trauma-resuscitation-and-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"stre","sideBox":"Learn more about [Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine](http://sjtrem.biomedcentral.com)","snPcode":"13049","submissionUrl":"https://submission.nature.com/new-submission/13049/3","title":"Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine","twitterHandle":"@SJTREM","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"children, red blood cell concentrate, haemorrhage, paediatric trauma, emergency medicine","lastPublishedDoi":"10.21203/rs.3.rs-7108398/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7108398/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe prehospital transfusion of red blood cell (RBC) concentrates represents an emerging approach in paediatric trauma management. Nevertheless, distinctive parameters for predicting the need for transfusion in children are still lacking. This study aimed to identify predictors for early in-hospital RBC transfusions that are readily available to emergency medical services (EMS) at the scene to aid in deciding whether to transfuse.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study comprised a retrospective analysis of the German TraumaRegister DGU\u003csup\u003e\u0026reg;\u003c/sup\u003e. It included children and adolescents aged 1 to 16 years from Germany, Austria, and Switzerland over a 15-year period. Contingency tables were used to identify risk factors, which were then assessed through multivariate regression analysis. The model\u0026rsquo;s predictive capacity was evaluated using the receiver operating characteristic (ROC) curve.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 11,849 patients were included, with RBC transfusion performed in 5.9% of cases. Polytraumatised patients (adjusted odds ratio (adj. OR) 4.18 [95% confidence interval 3.26\u0026ndash;5.34]) and those with penetrating injuries (adj. OR 4.32 [2.96\u0026ndash;6.30]) and abdominal injuries (adj. OR 4.18 [3.34\u0026ndash;5.24]) exhibited the highest risk of requiring an RBC transfusion. The need for cardiopulmonary resuscitation (adj. OR 2.46 [1.84\u0026ndash;3.28]), endotracheal intubation (adj. OR 2.51 [1.93\u0026ndash;3.28]), and Glasgow Coma Scale (GCS)\u0026thinsp;\u0026le;\u0026thinsp;8 (adj. OR 2.49 [1.85\u0026ndash;3.36]) were also significant, but weaker, predictors. A model based on the mentioned parameters achieved an area under the ROC curve of 0.87 [0.85\u0026ndash;0.88].\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe likelihood of requiring an RBC transfusion is increased in cases of polytrauma, abdominal and penetrating trauma, patients with a GCS\u0026thinsp;\u0026le;\u0026thinsp;8, and those requiring tracheal intubation or cardiopulmonary resuscitation. All the included parameters are straightforward to assess, making them practical for use by EMS. Therefore, the proposed risk factors can help identify patients at risk of severe haemorrhage and subsequent transfusion requirement.\u003c/p\u003e\u003ch2\u003eClinical Trial Number:\u003c/h2\u003e\u003cp\u003enot applicable\u003c/p\u003e","manuscriptTitle":"Predictors of Prehospital Transfusion in Paediatric Trauma: A Retrospective Analysis of 11,849 Cases from the TraumaRegister DGUⓇ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-30 04:59:52","doi":"10.21203/rs.3.rs-7108398/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-23T07:32:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-21T14:07:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"121691463931387866159397693409419177610","date":"2025-09-18T08:37:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248722444240297408167495371524306052656","date":"2025-09-15T14:44:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"338516030018707124843846313653191632484","date":"2025-07-30T07:30:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-29T01:12:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1824099774607522897280132413275527079","date":"2025-07-28T22:53:06+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-27T22:54:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-21T08:59:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-15T08:57:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine","date":"2025-07-12T13:20:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scandinavian-journal-of-trauma-resuscitation-and-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"stre","sideBox":"Learn more about [Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine](http://sjtrem.biomedcentral.com)","snPcode":"13049","submissionUrl":"https://submission.nature.com/new-submission/13049/3","title":"Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine","twitterHandle":"@SJTREM","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7f5bed16-96bf-471d-8a07-bfd7402138f0","owner":[],"postedDate":"July 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:04:58+00:00","versionOfRecord":{"articleIdentity":"rs-7108398","link":"https://doi.org/10.1186/s13049-025-01516-x","journal":{"identity":"scandinavian-journal-of-trauma-resuscitation-and-emergency-medicine","isVorOnly":false,"title":"Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine"},"publishedOn":"2025-11-26 15:58:41","publishedOnDateReadable":"November 26th, 2025"},"versionCreatedAt":"2025-07-30 04:59:52","video":"","vorDoi":"10.1186/s13049-025-01516-x","vorDoiUrl":"https://doi.org/10.1186/s13049-025-01516-x","workflowStages":[]},"version":"v1","identity":"rs-7108398","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7108398","identity":"rs-7108398","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}