Transfusion Ratios of Fresh Frozen Plasma and Platelet Concentrate to Packed Red Blood Cells in Patients with Severe Blunt Trauma Receiving Massive Transfusion: A Nationwide Retrospective Cohort Study

Transfusion Ratios of Fresh Frozen Plasma and Platelet Concentrate to Packed Red Blood Cells in Patients with Severe Blunt Trauma Receiving Massive Transfusion: A Nationwide Retrospective Cohort Study | 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 Article Transfusion Ratios of Fresh Frozen Plasma and Platelet Concentrate to Packed Red Blood Cells in Patients with Severe Blunt Trauma Receiving Massive Transfusion: A Nationwide Retrospective Cohort Study Toru Takiguchi, Tomohisa Seki, Takashi Tagami, Yu Akagi, Ryuta Nakae, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6316025/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Background The efficacy and optimal transfusion ratios of fresh frozen plasma (FFP), platelet concentrate (PC), and packed red blood cells (pRBC) exceeding 1:1:1 in patients with severe blunt trauma receiving massive transfusion, as well as the optimal ratios for specific trauma phenotypes, remain unknown. Methods We conducted a nationwide retrospective cohort study using data from the Japan Trauma Data Bank (January 2019 and December 2022). The final study population consisted of patients who received massive transfusions following blunt trauma, defined as the administration of ≥ 10 units of pRBC within 24 hours. The FFP-to-pRBC and PC-to-pRBC ratios were categorised as 0–0.5, 0.5–1, 1–1.5, 1.5–2, and > 2. Multivariate logistic regression analysis was performed to analyse the association between these ratios and in-hospital survival rates. Unsupervised agglomerative clustering was used to identify distinct clinical phenotypes. Results Among 2,849 eligible patients, an FFP-to-pRBC ratio of 1–1.5 was associated with significantly higher in-hospital survival compared to a ratio of 0.5–1 (adjusted odds ratio [OR] = 1.46; 95% confidence interval [CI], 1.12–1.92; P = 0.006). Similarly, a PC-to-pRBC ratio of 1.5–2 was associated with higher survival compared to a ratio of 0.5–1 (adjusted OR = 1.62; 95% CI, 1.00–2.69; P = 0.053). Patients were categorized into three phenotypes: truncal trauma with shock (70.3%), moderate head and extremity trauma (11.8%), and severe head trauma with consciousness disturbances (17.9%). In the truncal trauma with shock phenotype, FFP-to-pRBC ratios of 1–1.5 (adjusted OR = 1.56; 95% CI, 1.12–2.20; P = 0.010) and > 2 (adjusted OR = 2.32; 95% CI, 1.14–5.10; P = 0.027) were associated with improved survival. Conclusions Higher FFP-to-pRBC (1–1.5) and PC-to-pRBC (1.5–2) ratios were associated with improved survival. Higher FFP-to-pRBC ratios were particularly beneficial for truncal trauma with shock phenotype. Health sciences/Medical research/Outcomes research Health sciences/Diseases/Trauma Health sciences/Health care/Therapeutics/Surgery transfusion ratio blunt trauma massive transfusion clustering truncal trauma shock Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Severe trauma poses a significant challenge to global public health. According to the Global Burden of Diseases, Injuries, and Risk Factors Study, trauma is responsible for approximately 8% of all deaths each year [ 1 ]. Post-traumatic bleeding and the resulting traumatic coagulopathy continue to be major contributors to potentially preventable multiorgan failure and mortality [ 2 ]. Recent clinical guidelines recommend that massive transfusion protocols for the initial management of major haemorrhage emphasise the maintenance of a high fresh frozen plasma (FFP)-to-packed red blood cells (pRBC) ratio and high platelet concentrate (PC)-to-pRBC ratio to achieve haemostasis and effectively manage trauma-induced coagulopathy [ 3 – 5 ]. The optimal transfusion ratio for massive transfusion protocols in patients with trauma remains unknown. The PROPPR trial, a landmark randomised controlled study on massive transfusion ratios, demonstrated that using a 1:1:1 ratio of FFP, PC, and pRBC resulted in quicker haemostasis and reduced 24-hour mortality due to exsanguination compared with using a 1:1:2 ratio, although it did not decrease 30-day mortality [ 6 ]. Literature reviews on massive transfusion suggest that protocols should use ratios of 1:1:1 or 1:1:2 for FFP, PC, and pRBC [ 7 – 25 ]. Current guidelines in Europe, the United States, and Japan recommend a massive transfusion protocol with high FFP-to-pRBC and PC-to-pRBC ratios ranging from 1:2 to 1:1 [ 3 – 5 ]. However, clinical studies forming the basis of current guidelines have not examined transfusion ratios > 1 for both FFP-to-pRBC and PC-to-pRBC. Furthermore, the optimal range for high transfusion ratios (> 1) has not been determined. Although severe blunt trauma encompasses a spectrum of coagulopathic phenotypes [ 26 – 30 ], the optimal transfusion ratio for different trauma phenotypes remains unclear. Coagulopathy associated with traumatic injury is caused by multiple factors and complex interactions. Trauma-induced coagulopathy is associated with the severity of injury, shock, hypothermia, and haemodilution [ 26 – 30 ]. Furthermore, a retrospective observational study using large-scale registry data demonstrated that specific combinations of multiple injuries significantly affected patient outcomes [ 31 ]. In addition, blunt trauma typically results in more extensive tissue injury and hypoperfusion compared to penetrating trauma, leading to more pronounced coagulopathy [ 26 , 30 , 32 ]. Consequently, the optimal transfusion ratio for managing specific phenotypes of blunt trauma may vary. Unsupervised agglomerative clustering, a technique that identifies patient groups based on multiple variables without prior assumptions, shows promise for refining phenotype classification in blunt trauma [ 33 – 38 ]. Applying machine learning to sub-phenotypic blunt trauma may ultimately enable the development of more targeted transfusion strategies, potentially improving the outcomes for specific trauma phenotypes. The aim of the present study was to evaluate the optimal transfusion ratio > 1 for massive transfusion in severe blunt trauma in both an entire cohort and specific phenotypes, using a nationwide trauma registry in Japan. Methods Ethical Approval This study was approved by the Institutional Review Board of Nippon Medical School Hospital (B-2024-896). Due to the retrospective nature of the study, informed consent was waived by the Institutional Review Board of Nippon Medical School Hospital. All methods were performed in accordance with the relevant guidelines and regulations. Data source This retrospective observational study used data from the Japan Trauma Data Bank (JTDB), a prospective multicentre nationwide trauma registry [39]. Established in 2003 by the Trauma Registry Committee of the Japanese Association for the Surgery of Trauma and the Committee for Clinical Care Evaluation of the Japanese Association for Acute Care Medicine, the JTDB is managed by Japan Trauma Care and Research to improve and ensure the quality of trauma care in Japan. The JTDB requires the registration of all severe trauma cases with an Abbreviated Injury Scale (AIS) score ≥ 3 [40]; however, registration of all patients is also permitted. This database contains information on 303 facilities across Japan, compiled annually [39]. The JTDB includes patient characteristics, injury type, mechanism, vital signs, AIS score, injury severity score (ISS) [41], revised trauma score (RTS) [42], trauma and injury severity score and probability of survival (TRISS-PS) [43], in-hospital treatment and procedures, and outcomes. The data collection items in this registry were revised in 2019, with the amount of blood transfused within 24 h added as a new entry. In this study, we used JTDB 2019 registry cases following the implementation of new data collection items. Study Population This study included trauma patients registered in the JTDB dataset between January 2019 and December 2022. The exclusion criteria were as follows: 1) penetrating injuries; 2) burns; 3) mixed injuries; 4) other non-blunt trauma injuries; 5) Unknown; 6) non-direct transportation; 7) cardiac arrest on hospital arrival; 8) patients who did not receive a transfusion within 24 h; and 9) patients who received < 10 units of pRBCs within 24 h. The final study population consisted of patients who received massive transfusions following blunt trauma, defined as the administration of ≥ 10 units of pRBCs within 24 h. Data Collection and Outcome The following patient data were collected from the JTDB database: age, sex, Charlson Comorbidity Index (CCI) [44], vital signs on hospital arrival (systolic blood pressure, heart rate, respiratory rate, body temperature, and Glasgow Coma Scale), maximum AIS region score (head and neck, face, chest, abdomen, extremities, and external), ISS, RTS, TRISS-PS, amount of blood products within 24 hours (pRBC, FFP, and PC), treatments (the use of tranexamic acid and vasopressors) and procedures (resuscitative endovascular balloon occlusion of the aorta and transcatheter arterial embolization) in the emergency department, in-hospital surgery, and outcomes (in-hospital survival). Massive transfusion was defined as the administration of ≥10 units of pRBC within 24 hours. (In Japan, 1 unit of pRBC is approximately 120 m.) The primary outcome was in-hospital survival owing to any cause. Statistical Analyses Clustering method Clustering variables were selected based on a previous study using the JTDB which analysed trauma clinical phenotypes and biological profiles related to inflammation and coagulation disorders as follows: age, sex, CCI, vital signs on hospital arrival (systolic blood pressure, heart rate, respiratory rate, body temperature, and Glasgow Coma Scale score), and maximum AIS region scores (head and neck, face, chest, abdomen, extremities, and external) [45]. To handle the missing data for clustering, the specific imputation methods were chosen based on the type of variable. Predictive mean matching was used for continuous variables such as age, CCI, systolic blood pressure, heart rate, respiratory rate, body temperature, Glasgow Coma Scale score, and maximum AIS region scores. A logistic regression model was used for binary variables such as sex. A distance matrix was calculated using Euclidean distance, followed by an elbow plot to determine the optimal number of clusters based on the within-cluster sum of squares. Finally, agglomerative hierarchical clustering was performed using Ward's minimum variance method. A heatmap of the accompanying data was generated to visualise the clustering results. Missing data were imputed prior to calculating the distance matrix and performing hierarchical clustering; however, the imputed data were not used for cluster comparisons or subsequent statistical analyses. Statistical testing Continuous variables were presented as mean values with standard deviations. Categorical variables were presented as frequencies and percentages. We compared baseline characteristics across phenotypes using analysis of variance or Kruskal-Wallis tests, as appropriate, for continuous variables and the chi-square tests for categorical variables. The survival rates for each FFP-to-pRBC and PC-to-pRBC ratios were presented for the total cohort and by phenotype, along with the number of survivors out of the total number of patients in each FFP-to-pRBC ratio category. Based on literature review and clinical guidelines of massive transfusion, which suggest that massive transfusion should employ FFP, PC, and pRBC ratios between 1:1:1 and 1:1:2, we classified the FFP-to-pRBC and PC-to-pRBC ratios into the following categories: 0–0.5 (including 0.5), 0.5–1 (including 1), 1–1.5 (including 1.5), 1.5–2 (including 2), and > 2 [3-5, 7-10]. Multivariable logistic regression analyses were conducted to assess the association between FFP-to-pRBC and PC-to-pRBC ratios and in-hospital survival. The covariates used in clustering were adjusted for age, sex, CCI, vital signs on hospital arrival (systolic blood pressure, heart rate, respiratory rate, body temperature, and Glasgow Coma Scale), and maximum AIS region score (head and neck, face, chest, abdomen, extremities, and external). The reference category for the multivariable logistic regression analyses of FFP-to-pRBC and PC-to-pRBC ratios was greater than 0.5–1 (including 1), based on the recommended transfusion ratios from literature reviews and clinical guidelines on massive transfusion [3-5, 7-10]. Data were reported as odds ratios (ORs) with 95% confidence intervals (CIs). All statistical analyses were performed using R software package version 4.3.1 (R Foundation for Statistical Computing, Vienna, Austria). Two-sided values of p < 0.05 were considered statistically significant. Results Overall, 133,384 patients with trauma were registered with the JTDB during the study period. We identified 2,849 patients with blunt trauma who underwent massive transfusions (Fig. 1). The optimal number of clusters was determined using the elbow method, which demonstrated that three clusters was ideal (Fig. 2). Subsequently, patients were categorised into three phenotypes using unsupervised agglomerative clustering (Additional file 1: Fig. S1). Table 1 compares the baseline characteristics of the entire cohort with those of the three phenotypes. Phenotype 1 (n=2,004 [70.3%]), which comprised the majority of patients, included those with truncal trauma involving the chest, abdomen, and extremities, along with shock characterised by low systolic blood pressure and high heart rate (in-hospital survival: 72.2%). Phenotype 2 (n=336 [11.8%]) included patients with moderate head and extremity trauma, moderate consciousness disturbance characterised by a low Glasgow Coma Scale score, and shock with low systolic blood pressure and high heart rate (in-hospital survival: 72.6%). Phenotype 3 (n=509 [17.9%]) included patients with severe head trauma and severe consciousness disturbances, as indicated by a low Glasgow Coma Scale score (in-hospital survival: 48.5%). Table 2 shows the survival rate and number of survivors out of the total number of patients for each FFP-to-pRBC ratio. The highest survival rate in each FFP-to-pRBC ratio category was observed at a ratio of 1–1.5 in the total cohort, > 2 in phenotype 1, and 0–0.5 in phenotypes 2 and 3 (Fig. 3). The largest number of patients in each FFP-to-pRBC ratio category was in the 0.5–1 ratio for the total cohort and across all three phenotypes. Table 3 shows the survival rate and number of survivors out of the total number of patients for each PC-to-pRBC ratio. The highest survival rate in each PC-to-pRBC ratio category was observed at a ratio of 1.5–2 in the total cohort and across all three phenotypes (Fig. 4). The largest number of patients was in the 0.5–1 ratio for the total cohort and across all three phenotypes. Table 4 shows the multivariate logistic regression analyses of in-hospital survival based on the FFP-to-pRBC ratio for the entire cohort and across the three phenotypes. In the total cohort, a ratio of 1–1.5 was associated with a significantly higher in-hospital survival rate compared to a ratio of 0.5–1 (adjusted OR = 1.46; 95% CI, 1.12–1.92; P = 0.006). For phenotype 1, ratios of 1–1.5 (adjusted OR = 1.56; 95% CI, 1.12–2.20; P = 0.010) and > 2 (adjusted OR = 2.32; 95% CI, 1.14–5.10; P = 0.027) were associated with a significantly higher in-hospital survival rate compared to a ratio of 0.5–1. Table 5 shows the multivariate logistic regression analyses of in-hospital survival based on the PC-to-pRBC ratio for the entire cohort and across the three phenotypes. In the total cohort, although not statistically significant, a ratio of 1.5–2 was associated with a higher in-hospital survival rate compared to a ratio of 0.5–1 (adjusted OR = 1.62; 95% CI, 1.00–2.69; P = 0.053). Across the three phenotypes, multivariate logistic regression analyses revealed no significant differences for in-hospital survival. Discussion This nationwide cohort study demonstrated that FFP-to-pRBC and PC-to-pRBC transfusion ratios > 1 were associated with improved survival rates in patients with severe blunt trauma undergoing massive transfusion. Ratios of 1 to 1.5 for FFP-to-pRBC and 1.5 to 2 for PC-to-pRBC were particularly effective for enhancing in-hospital survival. Notably, in patients classified as having phenotype 1 (truncal trauma with shock), the association with improved survival was even more pronounced with higher FFP-to-pRBC transfusion ratios, suggesting that specific trauma phenotypes may benefit from tailored transfusion strategies. While prior research, including the PROPPR trial, primarily focused on transfusion ratios up to 1:1, our study examined transfusion ratios > 1 for both FFP-to-pRBC and PC-to-pRBC [6]. Several studies comparing high ratios (≥ 1) with low ratios (< 1) for FFP-to-pRBC and PC-to-pRBC in massive transfusion have shown that high ratios improved survival [46-48]. However, in these studies, the 1:1 ratio, already recommended by the PROPPR trial and clinical guidelines, was included in the high-ratio group [6-10]. Although a recent retrospective study showed that an FFP-to-RBC ratio > 1 was associated with favourable survival [49], the optimal transfusion ratio remains unclear. Our study addressed this knowledge gap, suggesting that FFP-to-pRBC ratios > 1 and ≤ 1.5, and PC-to-pRBC ratios > 1.5 and ≤ 2, were particularly effective in enhancing in-hospital survival. A high FFP-to-pRBC ratio was significantly associated with improved in-hospital survival rates, especially in patients with truncal trauma with shock (phenotype 1). Truncal trauma leads to extensive tissue damage, hypoperfusion, and shock, quickly depleting coagulation factors and causing systemic coagulopathy, which a high FFP ratio can effectively counter [28-30]. In contrast, in head trauma, where trauma-induced coagulopathy is often more severe, a high FFP-to-pRBC ratio alone may not be sufficient to fully restore coagulation factors [27, 50-52]. Additionally, the increased volume due to a high FFP ratio can increase intracranial pressure, potentially worsening intracranial haemorrhage. Our study had several limitations. First, this was a retrospective observational study, which may have introduced bias due to unmeasured confounding factors. Second, there are concerns regarding external validity as the data were derived exclusively from Japanese patients. Consequently, the findings may not be generalisable to other populations because of variations in trauma care practices, patient demographics, and healthcare systems across different countries and regions. Third, the database did not specify the cause of death, preventing analyses of cause-specific mortality. Conclusions This nationwide retrospective cohort study suggested that FFP-to-pRBC and PC-to-pRBC ratios > 1 improved survival in patients with severe blunt trauma, with optimal ranges of 1–1.5 for FFP-to-pRBC and 1.5–2 for PC-to-pRBC. High FFP-to-pRBC ratios were particularly beneficial for phenotype 1 patients with truncal trauma with shock. Nevertheless, further prospective studies are necessary to validate these findings and refine the optimal ratio thresholds for different trauma phenotypes. Abbreviations FFP, high fresh frozen plasma; pRBC, packed red blood cells; PC, platelet concentrate; JTDB, Japan Trauma Data Bank; AIS, Abbreviated Injury Scale; ISS, injury severity score; RTS, revised trauma score; TRISS-PS, trauma and injury severity score and probability of survival; CCI, Charlson Comorbidity Index; OR, odds ratio; CI, confidence interval; SD, standard deviation Declarations Ethics approval and consent to participate This study was approved by the Institutional Review Board of Nippon Medical School Hospital (B-2024-896). The requirement for informed consent was waived due to data anonymity. Consent for publication Not applicable. Availability of data and materials A summary of the JTDB is available at http://www.jtcr-jatec.org/traumabank/index.htm. The specific data within the JTDB, which support the findings of this study, are accessible through Japan Trauma Care and Research. However, these data are subject to access restrictions, as they were utilised under licence for this study and are, therefore, not available to the public. Please refer to Toru Takiguchi ( [email protected] ) for data access enquiries. Competing interests Kawazoe Y belong to the Artificial Intelligence and Digital Twin in Healthcare, Graduate School of Medicine, University of Tokyo, which is an endowment department, and was supported by an unrestricted grant from EM Systems, EPNextS, MRP CO., LTD., SHIP HEALTHCARE HOLDINGS, INC., SoftBank Corp., and NEC Corporation; these organizations had no control over the interpretation, writing, or publication of this work. The other authors declare no financial or no competing interests. Funding No funding was obtained for the present work. Authors' contributions Study conception and design: Takiguchi T, Seki T, Tagami T, Akagi Y, Ito H, and Ohe K. Data collection: Takiguchi T, Nakae R, Okada I, Kim S, and Inoue M. Data Analysis: Takiguchi T and Seki T. Data interpretation: Takiguchi T, Seki T, Akagi Y, Ito H, Kawazoe Y, and Ohe K. Writing the initial draft: Takiguchi T and Seki T. Writing and editing: Tagami T, Nakae R, Kawazoe Y, and Yokobori S. Supervision: Ohe K and Yokobori S. All authors read and approved the final manuscript. Acknowledgements We sincerely appreciate the involvement of the emergency medical service personnel, nurses, and emergency physicians in the JTDB, and we extend our gratitude to the patients for their valuable contributions to this study. References Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017. 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Moore EE, Moore HB, Kornblith LZ, Neal MD, Hoffman M, Mutch NJ, Schöchl H, Hunt BJ, Sauaia A: Trauma-induced coagulopathy. Nat Rev Dis Primers 2021, 7(1):30. https://doi.org/10.1111/jth.14450 Tachino J, Katayama Y, Kitamura T, Kiyohara K, Nakao S, Umemura Y, Ishida K, Hirose T, Nakagawa Y, Shimazu T: Assessment of the interaction effect between injury regions in multiple injuries: A nationwide cohort study in Japan. J Trauma Acute Care Surg 2021, 90(1):185-190. https://doi.org/10.1097/TA.0000000000002969 Hoshino K, Naito M, Nakamura Y, Irie Y, Nishida T, Kitamura T, Ishikura H: Differences in coagulopathy and massive transfusion strategy based on trauma type. Am J Emerg Med 2020, 38(5):860-863. https://doi.org/10.1016/j.ajem.2019.06.048 A. K. Jain MNM, P. J. Flynn: Data clustering: a review. ACM Computing Surveys 1999, 31(3):264-323. https://doi.org/10.1145/331499.331504 Lachmann M, Rippen E, Schuster T, Xhepa E, von Scheidt M, Pellegrini C, Trenkwalder T, Rheude T, Stundl A, Thalmann R et al: Subphenotyping of Patients With Aortic Stenosis by Unsupervised Agglomerative Clustering of Echocardiographic and Hemodynamic Data. JACC Cardiovasc Interv 2021, 14(19):2127-2140. https://doi.org/10.1016/j.jcin.2021.08.034 Goerigk S, Elsaesser M, Reinhard MA, Kriston L, Härter M, Hautzinger M, Klein JP, McCullough JP, Jr., Schramm E, Padberg F: Childhood Trauma Questionnaire-based child maltreatment profiles to predict efficacy of the Cognitive Behavioral Analysis System of Psychotherapy versus non-specific psychotherapy in adults with early-onset chronic depression: cluster analysis of data from a randomised controlled trial. Lancet Psychiatry 2024, 11(9):709-719. https://doi.org/10.1016/S2215-0366(24)00209-8 Alim-Marvasti A, Kuleindiren N, Tiersen F, Johal M, Lin A, Selim H, Rifkin-Zybutz R, Mahmud M: Hierarchical clustering of prolonged post-concussive symptoms after 12 months: symptom-centric analysis and association with functional impairments. Brain Inj 2023, 37(4):317-328. https://doi.org/10.1080/02699052.2022.2158229 Russell HF, January AM, Kelly EH, Mulcahey MJ, Betz RR, Vogel LC: Patterns of coping strategy use and relationships with psychosocial health in adolescents with spinal cord injury. J Pediatr Psychol 2015, 40(5):535-543. https://doi.org/10.1093/jpepsy/jsu159 Dudli S, Ferguson SJ, Haschtmann D: Severity and pattern of post-traumatic intervertebral disc degeneration depend on the type of injury. Spine J 2014, 14(7):1256-1264. https://doi.org/10.1016/j.spinee.2013.07.488 Kobayashi K: Challenges for improving trauma care in Japan. J Trauma 2005, 58(6):1134-1139. https://doi.org/10.1097/01.ta.0000169953.29347.81 Palmer CS, Gabbe BJ, Cameron PA: Defining major trauma using the 2008 Abbreviated Injury Scale. Injury 2016, 47(1):109-115. Baker SP, O'Neill B, Haddon W, Jr., Long WB: The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma 1974, 14(3):187-196. https://doi.org/10.1016/j.injury.2015.07.003 Champion HR, Sacco WJ, Copes WS, Gann DS, Gennarelli TA, Flanagan ME: A revision of the Trauma Score. J Trauma 1989, 29(5):623-629. https://doi.org/10.1097/00005373-198905000-00017 Boyd CR, Tolson MA, Copes WS: Evaluating trauma care: the TRISS method. Trauma Score and the Injury Severity Score. J Trauma 1987, 27(4):370-378. https://doi.org/10.1097/00005373-198704000-00005 Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, Januel JM, Sundararajan V: Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 2011, 173(6):676-682. https://doi.org/10.1093/aje/kwq433 Tachino J, Matsumoto H, Sugihara F, Seno S, Okuzaki D, Kitamura T, Komukai S, Kido Y, Kojima T, Togami Y et al: Development of clinical phenotypes and biological profiles via proteomic analysis of trauma patients. Crit Care 2022, 26(1):241. https://doi.org/10.1186/s13054-022-04103-z Zink KA, Sambasivan CN, Holcomb JB, Chisholm G, Schreiber MA: A high ratio of plasma and platelets to packed red blood cells in the first 6 hours of massive transfusion improves outcomes in a large multicenter study. Am J Surg 2009, 197(5):565-570; discussion 570. https://doi.org/10.1016/j.amjsurg.2008.12.014 Balvers K, van Dieren S, Baksaas-Aasen K, Gaarder C, Brohi K, Eaglestone S, Stanworth S, Johansson PI, Ostrowski SR, Stensballe J et al: Combined effect of therapeutic strategies for bleeding injury on early survival, transfusion needs and correction of coagulopathy. Br J Surg 2017, 104(3):222-229. https://doi.org/10.1002/bjs.10330 Holcomb JB, del Junco DJ, Fox EE, Wade CE, Cohen MJ, Schreiber MA, Alarcon LH, Bai Y, Brasel KJ, Bulger EM et al: The prospective, observational, multicenter, major trauma transfusion (PROMMTT) study: comparative effectiveness of a time-varying treatment with competing risks. JAMA Surg 2013, 148(2):127-136. https://doi.org/10.1001/2013.jamasurg.387 Fujiwara G, Okada Y, Ishii W, Echigo T, Shiomi N, Ohtsuru S: High Fresh Frozen Plasma to Red Blood Cell Ratio and Survival Outcomes in Blunt Trauma. JAMA Surg 2024, 159(11):1272-1280. https://doi.org/10.1001/jamasurg.2024.3097 Cap AP, Spinella PC: Severity of head injury is associated with increased risk of coagulopathy in combat casualties. J Trauma 2011, 71(1 Suppl):S78-81. https://doi.org/10.1097/TA.0b013e3182218cd8 Maegele M, Schöchl H, Menovsky T, Maréchal H, Marklund N, Buki A, Stanworth S: Coagulopathy and haemorrhagic progression in traumatic brain injury: advances in mechanisms, diagnosis, and management. Lancet Neurol 2017, 16(8):630-647. https://doi.org/10.1016/S1474-4422(17)30197-7 Maegele M: Coagulopathy and Progression of Intracranial Hemorrhage in Traumatic Brain Injury: Mechanisms, Impact, and Therapeutic Considerations. Neurosurgery 2021, 89(6):954-966. https://doi.org/10.1093/neuros/nyab358 Tables Tables 1 to 5 are available in the Supplementary Files section. Additional Declarations Competing interest reported. Kawazoe Y belong to the Artificial Intelligence and Digital Twin in Healthcare, Graduate School of Medicine, University of Tokyo, which is an endowment department, and was supported by an unrestricted grant from EM Systems, EPNextS, MRP CO., LTD., SHIP HEALTHCARE HOLDINGS, INC., SoftBank Corp., and NEC Corporation; these organizations had no control over the interpretation, writing, or publication of this work. The other authors declare no financial or no competing interests. Supplementary Files Additionalfile1FigS1.tiff Additional file 1: Fig. S1 File format: TIFF Title of data: Elbow method for determining the optimal number of clusters. Description of data: This figure illustrates the elbow method used to determine the optimal number of clusters for unsupervised agglomerative clustering. A distance matrix was constructed using Euclidean distance, and the within-cluster sum of squares was evaluated to identify the point at which the marginal gain decreased, indicating three as the optimal number of clusters. table1.docx table2.docx table3.docx table4.docx table5.docx Cite Share Download PDF Status: Published Journal Publication published 15 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 11 Jun, 2025 Reviews received at journal 09 Jun, 2025 Reviewers agreed at journal 21 May, 2025 Reviews received at journal 21 May, 2025 Reviewers agreed at journal 21 May, 2025 Reviewers invited by journal 01 Apr, 2025 Editor assigned by journal 01 Apr, 2025 Editor invited by journal 31 Mar, 2025 Submission checks completed at journal 31 Mar, 2025 First submitted to journal 26 Mar, 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. 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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-6316025","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":444277256,"identity":"05778d24-3457-49cf-9c4f-91d0eacda907","order_by":0,"name":"Toru 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1","display":"","copyAsset":false,"role":"figure","size":4333316,"visible":true,"origin":"","legend":"\u003cp\u003ePatient selection\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/a03b59552c313d6b55c6a6c5.png"},{"id":82073020,"identity":"b800f6dc-cc61-4369-834c-62f55add9f08","added_by":"auto","created_at":"2025-05-06 13:26:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2769919,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap and dendrogram for visualization of clustering results.\u003c/p\u003e\n\u003cp\u003eSDs, standard deviations; CCI, Charlson Comorbidity Index; AIS, Abbreviated Injury Scale.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/20756d217ec401317eae78e2.png"},{"id":82073011,"identity":"04e869dc-0c3b-4af3-9d94-1bf32a5c91cd","added_by":"auto","created_at":"2025-05-06 13:26:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":906867,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival rate by FFP to pRBC ratio for each group.\u003c/p\u003e\n\u003cp\u003eFFP, fresh frozen plasma; pRBC, packed red blood cells.\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/25a0088283a228bdf358d7c4.png"},{"id":82075480,"identity":"fb734494-90b5-4309-91c9-8a891337f999","added_by":"auto","created_at":"2025-05-06 13:42:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":930138,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival rate by PC to pRBC ratio for each group.\u003c/p\u003e\n\u003cp\u003ePC, platelet concentrate; pRBC, packed red blood cells.\u003c/p\u003e","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/8568fa8f18f52ff18c0994ce.png"},{"id":87219791,"identity":"147c2146-532f-4888-9462-fa205eefafe9","added_by":"auto","created_at":"2025-07-21 16:05:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8129419,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/ad336f87-0fcf-45e3-b7f3-6ec744c981ea.pdf"},{"id":82073034,"identity":"0ba42fc6-c6b3-46b1-bd92-0ee74991129d","added_by":"auto","created_at":"2025-05-06 13:26:51","extension":"tiff","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16616774,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 1: Fig. S1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFile format: TIFF\u003c/p\u003e\n\u003cp\u003eTitle of data: Elbow method for determining the optimal number of clusters.\u003c/p\u003e\n\u003cp\u003eDescription of data: This figure illustrates the elbow method used to determine the optimal number of clusters for unsupervised agglomerative clustering. A distance matrix was constructed using Euclidean distance, and the within-cluster sum of squares was evaluated to identify the point at which the marginal gain decreased, indicating three as the optimal number of clusters.\u003c/p\u003e","description":"","filename":"Additionalfile1FigS1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/e70bf659601a7e43efdde6cc.tiff"},{"id":82073010,"identity":"2911ada7-4101-4cee-ae68-7fb92c8312e2","added_by":"auto","created_at":"2025-05-06 13:26:50","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":28712,"visible":true,"origin":"","legend":"","description":"","filename":"table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/dfd90757e2f507c2b949d1d5.docx"},{"id":82073019,"identity":"ceefd46b-dac6-4bbb-b51a-38e97d4d735e","added_by":"auto","created_at":"2025-05-06 13:26:50","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":20419,"visible":true,"origin":"","legend":"","description":"","filename":"table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/ff017d37349c4232aac97bf9.docx"},{"id":82073835,"identity":"1d4d8072-20e5-4939-a01c-b9cea0c8b5df","added_by":"auto","created_at":"2025-05-06 13:34:50","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":20324,"visible":true,"origin":"","legend":"","description":"","filename":"table3.docx","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/e77078f98821413a3879c862.docx"},{"id":82073014,"identity":"7efcc6b8-c539-4529-9923-f796093c5c3c","added_by":"auto","created_at":"2025-05-06 13:26:50","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":20903,"visible":true,"origin":"","legend":"","description":"","filename":"table4.docx","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/e51bbf5b9df13febe24662cd.docx"},{"id":82073016,"identity":"1834203f-1f5c-4a34-abd5-746e7d45b5eb","added_by":"auto","created_at":"2025-05-06 13:26:50","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":20624,"visible":true,"origin":"","legend":"","description":"","filename":"table5.docx","url":"https://assets-eu.researchsquare.com/files/rs-6316025/v1/81768e2c292df32d3af1f8ca.docx"}],"financialInterests":"Competing interest reported. Kawazoe Y belong to the Artificial Intelligence and Digital Twin in Healthcare, Graduate School of Medicine, University of Tokyo, which is an endowment department, and was supported by an unrestricted grant from EM Systems, EPNextS, MRP CO., LTD., SHIP HEALTHCARE HOLDINGS, INC., SoftBank Corp., and NEC Corporation; these organizations had no control over the interpretation, writing, or publication of this work. The other authors declare no financial or no competing interests.","formattedTitle":"Transfusion Ratios of Fresh Frozen Plasma and Platelet Concentrate to Packed Red Blood Cells in Patients with Severe Blunt Trauma Receiving Massive Transfusion: A Nationwide Retrospective Cohort Study","fulltext":[{"header":"Background","content":"\u003cp\u003eSevere trauma poses a significant challenge to global public health. According to the Global Burden of Diseases, Injuries, and Risk Factors Study, trauma is responsible for approximately 8% of all deaths each year [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Post-traumatic bleeding and the resulting traumatic coagulopathy continue to be major contributors to potentially preventable multiorgan failure and mortality [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Recent clinical guidelines recommend that massive transfusion protocols for the initial management of major haemorrhage emphasise the maintenance of a high fresh frozen plasma (FFP)-to-packed red blood cells (pRBC) ratio and high platelet concentrate (PC)-to-pRBC ratio to achieve haemostasis and effectively manage trauma-induced coagulopathy [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe optimal transfusion ratio for massive transfusion protocols in patients with trauma remains unknown. The PROPPR trial, a landmark randomised controlled study on massive transfusion ratios, demonstrated that using a 1:1:1 ratio of FFP, PC, and pRBC resulted in quicker haemostasis and reduced 24-hour mortality due to exsanguination compared with using a 1:1:2 ratio, although it did not decrease 30-day mortality [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Literature reviews on massive transfusion suggest that protocols should use ratios of 1:1:1 or 1:1:2 for FFP, PC, and pRBC [\u003cspan additionalcitationids=\"CR8 CR9 CR10 CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Current guidelines in Europe, the United States, and Japan recommend a massive transfusion protocol with high FFP-to-pRBC and PC-to-pRBC ratios ranging from 1:2 to 1:1 [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, clinical studies forming the basis of current guidelines have not examined transfusion ratios\u0026thinsp;\u0026gt;\u0026thinsp;1 for both FFP-to-pRBC and PC-to-pRBC. Furthermore, the optimal range for high transfusion ratios (\u0026gt;\u0026thinsp;1) has not been determined.\u003c/p\u003e \u003cp\u003eAlthough severe blunt trauma encompasses a spectrum of coagulopathic phenotypes [\u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], the optimal transfusion ratio for different trauma phenotypes remains unclear. Coagulopathy associated with traumatic injury is caused by multiple factors and complex interactions. Trauma-induced coagulopathy is associated with the severity of injury, shock, hypothermia, and haemodilution [\u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Furthermore, a retrospective observational study using large-scale registry data demonstrated that specific combinations of multiple injuries significantly affected patient outcomes [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In addition, blunt trauma typically results in more extensive tissue injury and hypoperfusion compared to penetrating trauma, leading to more pronounced coagulopathy [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Consequently, the optimal transfusion ratio for managing specific phenotypes of blunt trauma may vary. Unsupervised agglomerative clustering, a technique that identifies patient groups based on multiple variables without prior assumptions, shows promise for refining phenotype classification in blunt trauma [\u003cspan additionalcitationids=\"CR34 CR35 CR36 CR37\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Applying machine learning to sub-phenotypic blunt trauma may ultimately enable the development of more targeted transfusion strategies, potentially improving the outcomes for specific trauma phenotypes.\u003c/p\u003e \u003cp\u003eThe aim of the present study was to evaluate the optimal transfusion ratio\u0026thinsp;\u0026gt;\u0026thinsp;1 for massive transfusion in severe blunt trauma in both an entire cohort and specific phenotypes, using a nationwide trauma registry in Japan.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of Nippon Medical School Hospital (B-2024-896). Due to the retrospective nature of the study, informed consent was waived by the Institutional Review Board of Nippon Medical School Hospital. All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective observational study used data from the Japan Trauma Data Bank (JTDB), a prospective multicentre nationwide trauma registry [39]. Established in 2003 by the Trauma Registry Committee of the Japanese Association for the Surgery of Trauma and the Committee for Clinical Care Evaluation of the Japanese Association for Acute Care Medicine, the JTDB is managed by Japan Trauma Care and Research to improve and ensure the quality of trauma care in Japan. The JTDB requires the registration of all severe trauma cases with an Abbreviated Injury Scale (AIS) score\u0026nbsp;≥\u0026nbsp;3\u0026nbsp;[40];\u0026nbsp;however, registration of all patients is also permitted. This database contains information on 303 facilities across Japan, compiled annually\u0026nbsp;[39].\u0026nbsp;The JTDB includes patient characteristics, injury type, mechanism, vital signs, AIS score, injury severity score (ISS) [41], revised trauma score (RTS) [42], trauma and injury severity score and probability of survival (TRISS-PS) [43], in-hospital treatment and procedures, and outcomes.\u0026nbsp;The data collection items in this registry were revised in 2019, with the amount of blood transfused within 24 h added as a new entry. In this study, we used JTDB 2019 registry cases following the implementation of new data collection items.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included trauma patients registered in the JTDB dataset between January 2019 and December 2022. The exclusion criteria were as follows: 1) penetrating injuries; 2) burns; 3) mixed injuries; 4) other non-blunt trauma injuries; 5) Unknown; 6) non-direct transportation; 7) cardiac arrest on hospital arrival; 8) patients who did not receive a transfusion within 24 h; and 9) patients who received \u0026lt; 10 units of pRBCs within 24 h. The final study population consisted of patients who received massive transfusions following blunt trauma, defined as the administration of\u0026nbsp;≥\u0026nbsp;10 units of pRBCs within 24 h.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection and Outcome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following patient data were collected from the JTDB database: age, sex, Charlson Comorbidity Index (CCI) [44], vital signs on hospital arrival (systolic blood pressure, heart rate, respiratory rate, body temperature, and Glasgow Coma Scale), maximum AIS region score (head and neck, face, chest, abdomen, extremities, and external), ISS, RTS, TRISS-PS, amount of blood products within 24 hours (pRBC, FFP, and PC), treatments (the use of tranexamic acid and vasopressors) and procedures (resuscitative endovascular balloon occlusion of the aorta and transcatheter arterial embolization) in the emergency department, in-hospital surgery, and outcomes (in-hospital survival). Massive transfusion was defined as the administration of ≥10 units of pRBC within 24 hours. (In Japan, 1 unit of pRBC is approximately 120 m.) The primary outcome was in-hospital survival owing to any cause.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eClustering method\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eClustering variables were selected based on a previous study using the JTDB which analysed trauma clinical phenotypes and biological profiles related to inflammation and coagulation disorders as follows: age, sex, CCI, vital signs on hospital arrival (systolic blood pressure, heart rate, respiratory rate, body temperature, and Glasgow Coma Scale score), and maximum AIS region scores (head and neck, face, chest, abdomen, extremities, and external) [45]. To handle the missing data for clustering, the specific imputation methods were chosen based on the type of variable. Predictive mean matching was used for continuous variables such as age, CCI, systolic blood pressure, heart rate, respiratory rate, body temperature, Glasgow Coma Scale score, and maximum AIS region scores. A logistic regression model was used for binary variables such as sex. A distance matrix was calculated using Euclidean distance, followed by an elbow plot to determine the optimal number of clusters based on the within-cluster sum of squares. Finally, agglomerative hierarchical clustering was performed using Ward's minimum variance method. A heatmap of the accompanying data was generated to visualise the clustering results. Missing data were imputed prior to calculating the distance matrix and performing hierarchical clustering; however, the imputed data were not used for cluster comparisons or subsequent statistical analyses.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical testing\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eContinuous variables were presented as mean values with standard deviations. Categorical variables were presented as frequencies and percentages. We compared baseline characteristics across phenotypes using analysis of variance or Kruskal-Wallis tests, as appropriate, for continuous variables and the chi-square tests for categorical variables. The survival rates for each FFP-to-pRBC and PC-to-pRBC ratios were presented for the total cohort and by phenotype, along with the number of survivors out of the total number of patients in each FFP-to-pRBC ratio category. Based on literature review and clinical guidelines of massive transfusion, which suggest that massive transfusion should employ FFP, PC, and pRBC ratios between 1:1:1 and 1:1:2, we classified the FFP-to-pRBC and PC-to-pRBC ratios into the following categories: 0–0.5 (including 0.5), 0.5–1 (including 1), 1–1.5 (including 1.5), 1.5–2 (including 2), and \u0026gt; 2 [3-5, 7-10]. Multivariable logistic regression analyses were conducted to assess the association between FFP-to-pRBC and PC-to-pRBC ratios and in-hospital survival. The covariates used in clustering were adjusted for age, sex, CCI, vital signs on hospital arrival (systolic blood pressure, heart rate, respiratory rate, body temperature, and Glasgow Coma Scale), and maximum AIS region score (head and neck, face, chest, abdomen, extremities, and external). The reference category for the multivariable logistic regression analyses of FFP-to-pRBC and PC-to-pRBC ratios was greater than 0.5–1 (including 1), based on the recommended transfusion ratios from literature reviews and clinical guidelines on massive transfusion [3-5, 7-10]. Data were reported as odds ratios (ORs) with 95% confidence intervals (CIs). All statistical analyses were performed using R software package version 4.3.1 (R Foundation for Statistical Computing, Vienna, Austria). Two-sided values of p \u0026lt; 0.05 were considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOverall, 133,384 patients with trauma were registered with the JTDB during the study period. We identified 2,849 patients with blunt trauma who underwent massive transfusions (Fig. 1).\u003c/p\u003e\n\u003cp\u003eThe optimal number of clusters was determined using the elbow method, which demonstrated that three clusters was ideal (Fig. 2). Subsequently, patients were categorised into three phenotypes using unsupervised agglomerative clustering (Additional file 1: Fig. S1).\u003c/p\u003e\n\u003cp\u003eTable 1 compares the baseline characteristics of the entire cohort with those of the three phenotypes. Phenotype 1 (n=2,004 [70.3%]), which comprised the majority of patients, included those with truncal trauma involving the chest, abdomen, and extremities, along with shock characterised by low systolic blood pressure and high heart rate (in-hospital survival: 72.2%). Phenotype 2 (n=336 [11.8%]) included patients with moderate head and extremity trauma, moderate consciousness disturbance characterised by a low Glasgow Coma Scale score, and shock with low systolic blood pressure and high heart rate (in-hospital survival: 72.6%). Phenotype 3 (n=509 [17.9%]) included patients with severe head trauma and severe consciousness disturbances, as indicated by a low Glasgow Coma Scale score (in-hospital survival: 48.5%).\u003c/p\u003e\n\u003cp\u003eTable 2 shows the survival rate and number of survivors out of the total number of patients for each FFP-to-pRBC ratio. The highest survival rate in each FFP-to-pRBC ratio category was observed at a ratio of 1–1.5 in the total cohort, \u0026gt; 2 in phenotype 1, and 0–0.5 in phenotypes 2 and 3 (Fig. 3). The largest number of patients in each FFP-to-pRBC ratio category was in the 0.5–1 ratio for the total cohort and across all three phenotypes.\u003c/p\u003e\n\u003cp\u003eTable 3 shows the survival rate and number of survivors out of the total number of patients for each PC-to-pRBC ratio. The highest survival rate in each PC-to-pRBC ratio category was observed at a ratio of 1.5–2 in the total cohort and across all three phenotypes (Fig. 4). The largest number of patients was in the 0.5–1 ratio for the total cohort and across all three phenotypes.\u003c/p\u003e\n\u003cp\u003eTable 4 shows the multivariate logistic regression analyses of in-hospital survival based on the FFP-to-pRBC ratio for the entire cohort and across the three phenotypes. In the total cohort, a ratio of 1–1.5 was associated with a significantly higher in-hospital survival rate compared to a ratio of 0.5–1 (adjusted OR = 1.46; 95% CI, 1.12–1.92; P = 0.006). For phenotype 1, ratios of 1–1.5 (adjusted OR = 1.56; 95% CI, 1.12–2.20; P = 0.010) and \u0026gt; 2 (adjusted OR = 2.32; 95% CI, 1.14–5.10; P = 0.027) were associated with a significantly higher in-hospital survival rate compared to a ratio of 0.5–1.\u003c/p\u003e\n\u003cp\u003eTable 5 shows the multivariate logistic regression analyses of in-hospital survival based on the PC-to-pRBC ratio for the entire cohort and across the three phenotypes. In the total cohort, although not statistically significant, a ratio of 1.5–2 was associated with a higher in-hospital survival rate compared to a ratio of 0.5–1 (adjusted OR = 1.62; 95% CI, 1.00–2.69; P = 0.053). Across the three phenotypes, multivariate logistic regression analyses revealed no significant differences for in-hospital survival.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis nationwide cohort study demonstrated that FFP-to-pRBC and PC-to-pRBC transfusion ratios \u0026gt; 1 were associated with improved survival rates in patients with severe blunt trauma undergoing massive transfusion. Ratios of 1 to 1.5 for FFP-to-pRBC and 1.5 to 2 for PC-to-pRBC were particularly effective for enhancing in-hospital survival. Notably, in patients classified as having phenotype 1 (truncal trauma with shock), the association with improved survival was even more pronounced with higher FFP-to-pRBC transfusion ratios, suggesting that specific trauma phenotypes may benefit from tailored transfusion strategies.\u003c/p\u003e\n\u003cp\u003eWhile prior research, including the PROPPR trial, primarily focused on transfusion ratios up to 1:1, our study examined transfusion ratios \u0026gt; 1 for both FFP-to-pRBC and PC-to-pRBC [6]. Several studies comparing high ratios (\u0026ge;\u0026nbsp;1) with low ratios (\u0026lt; 1) for FFP-to-pRBC and PC-to-pRBC in massive transfusion have shown that high ratios improved survival\u0026nbsp;[46-48].\u0026nbsp;However, in these studies, the 1:1 ratio,\u0026nbsp;already recommended by the PROPPR trial and clinical guidelines, was included in the high-ratio group\u0026nbsp;[6-10].\u0026nbsp;Although a recent retrospective study showed that an FFP-to-RBC ratio \u0026gt; 1 was associated with favourable survival\u0026nbsp;[49], the optimal transfusion ratio remains unclear. Our study addressed this knowledge gap, suggesting that FFP-to-pRBC ratios\u0026nbsp;\u0026gt; 1 and \u0026le; 1.5, and PC-to-pRBC ratios\u0026nbsp;\u0026gt; 1.5 and \u0026le; 2, were particularly effective in enhancing in-hospital survival.\u003c/p\u003e\n\u003cp\u003eA high FFP-to-pRBC ratio was significantly associated with improved in-hospital survival rates, especially in patients with truncal trauma with shock (phenotype 1). Truncal trauma leads to extensive tissue damage, hypoperfusion, and shock, quickly depleting coagulation factors and causing systemic coagulopathy, which a high FFP ratio can effectively counter [28-30]. In contrast, in head trauma, where trauma-induced coagulopathy is often more severe, a high FFP-to-pRBC ratio alone may not be sufficient to fully restore coagulation factors [27, 50-52]. Additionally, the increased volume due to a high FFP ratio can increase intracranial pressure, potentially worsening intracranial haemorrhage.\u003c/p\u003e\n\u003cp\u003eOur study had several limitations. First, this was a retrospective observational study, which may have introduced bias due to unmeasured confounding factors. Second, there are concerns regarding external validity as the data were derived exclusively from Japanese patients. Consequently, the findings may not be generalisable to other populations because of variations in trauma care practices, patient demographics, and healthcare systems across different countries and regions. Third, the database did not specify the cause of death, preventing analyses of cause-specific mortality.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis nationwide retrospective cohort study suggested that FFP-to-pRBC and PC-to-pRBC ratios \u0026gt; 1 improved survival in patients with severe blunt trauma, with optimal ranges of 1\u0026ndash;1.5 for FFP-to-pRBC and 1.5\u0026ndash;2 for PC-to-pRBC. High FFP-to-pRBC ratios were particularly beneficial for phenotype 1 patients with truncal trauma with shock. Nevertheless, further prospective studies are necessary to validate these findings and refine the optimal ratio thresholds for different trauma phenotypes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eFFP, high fresh frozen plasma; pRBC, packed red blood cells; PC, platelet concentrate; JTDB, Japan Trauma Data Bank; AIS, Abbreviated Injury Scale; ISS, injury severity score; RTS, revised trauma score; TRISS-PS, trauma and injury severity score and probability of survival; CCI, Charlson Comorbidity Index; OR, odds ratio; CI, confidence interval; SD, standard deviation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of Nippon Medical School Hospital (B-2024-896). The requirement for informed consent was waived due to data anonymity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA summary of the JTDB is available at http://www.jtcr-jatec.org/traumabank/index.htm. The specific data within the JTDB, which support the findings of this study, are accessible through Japan Trauma Care and Research. However, these data are subject to access restrictions, as they were utilised under licence for this study and are, therefore, not available to the public. Please refer to Toru Takiguchi ([email protected]) for data access enquiries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKawazoe Y belong to the Artificial Intelligence and Digital Twin in Healthcare, Graduate School of Medicine, University of Tokyo, which is an endowment department, and was supported by an unrestricted grant from EM Systems, EPNextS, MRP CO., LTD., SHIP HEALTHCARE HOLDINGS, INC., SoftBank Corp., and NEC Corporation; these organizations had no control over the interpretation, writing, or publication of this work. The other authors declare no financial or no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was obtained for the present work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy conception and design: Takiguchi T, Seki T, Tagami T, Akagi Y, Ito H, and Ohe K. Data collection: Takiguchi T, Nakae R, Okada I, Kim S, and Inoue M. Data Analysis: Takiguchi T and Seki T. Data interpretation: Takiguchi T, Seki T, Akagi Y, Ito H, Kawazoe Y, and Ohe K. Writing the initial draft: Takiguchi T and Seki T. Writing and editing: Tagami T, Nakae R, Kawazoe Y, and Yokobori S. Supervision: Ohe K and Yokobori S.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely appreciate the involvement of the emergency medical service personnel, nurses, and emergency physicians in the JTDB, and we extend our gratitude to the patients for their valuable contributions to this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGlobal, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017. 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J Trauma 2008, 65(5):986-993. https://doi.org/10.1097/TA.0b013e3181878028\u003c/li\u003e\n\u003cli\u003eHolcomb JB, Wade CE, Michalek JE, Chisholm GB, Zarzabal LA, Schreiber MA, Gonzalez EA, Pomper GJ, Perkins JG, Spinella PC et al: Increased plasma and platelet to red blood cell ratios improves outcome in 466 massively transfused civilian trauma patients. Ann Surg 2008, 248(3):447-458. https://doi.org/10.1097/SLA.0b013e318185a9ad\u003c/li\u003e\n\u003cli\u003eMaegele M, Lefering R, Paffrath T, Tjardes T, Simanski C, Bouillon B: Red-blood-cell to plasma ratios transfused during massive transfusion are associated with mortality in severe multiple injury: a retrospective analysis from the Trauma Registry of the Deutsche Gesellschaft f\u0026uuml;r Unfallchirurgie. 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J Trauma 2011, 71(1 Suppl):S78-81. https://doi.org/10.1097/TA.0b013e3182218cd8\u003c/li\u003e\n\u003cli\u003eMaegele M, Sch\u0026ouml;chl H, Menovsky T, Mar\u0026eacute;chal H, Marklund N, Buki A, Stanworth S: Coagulopathy and haemorrhagic progression in traumatic brain injury: advances in mechanisms, diagnosis, and management. Lancet Neurol 2017, 16(8):630-647. https://doi.org/10.1016/S1474-4422(17)30197-7\u003c/li\u003e\n\u003cli\u003eMaegele M: Coagulopathy and Progression of Intracranial Hemorrhage in Traumatic Brain Injury: Mechanisms, Impact, and Therapeutic Considerations. Neurosurgery 2021, 89(6):954-966. https://doi.org/10.1093/neuros/nyab358\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 5 are available in the Supplementary Files section.\u003c/p\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"transfusion ratio, blunt trauma, massive transfusion, clustering, truncal trauma, shock","lastPublishedDoi":"10.21203/rs.3.rs-6316025/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6316025/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe efficacy and optimal transfusion ratios of fresh frozen plasma (FFP), platelet concentrate (PC), and packed red blood cells (pRBC) exceeding 1:1:1 in patients with severe blunt trauma receiving massive transfusion, as well as the optimal ratios for specific trauma phenotypes, remain unknown.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a nationwide retrospective cohort study using data from the Japan Trauma Data Bank (January 2019 and December 2022). The final study population consisted of patients who received massive transfusions following blunt trauma, defined as the administration of \u0026ge;\u0026thinsp;10 units of pRBC within 24 hours. The FFP-to-pRBC and PC-to-pRBC ratios were categorised as 0\u0026ndash;0.5, 0.5\u0026ndash;1, 1\u0026ndash;1.5, 1.5\u0026ndash;2, and \u0026gt;\u0026thinsp;2. Multivariate logistic regression analysis was performed to analyse the association between these ratios and in-hospital survival rates. Unsupervised agglomerative clustering was used to identify distinct clinical phenotypes.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 2,849 eligible patients, an FFP-to-pRBC ratio of 1\u0026ndash;1.5 was associated with significantly higher in-hospital survival compared to a ratio of 0.5\u0026ndash;1 (adjusted odds ratio [OR]\u0026thinsp;=\u0026thinsp;1.46; 95% confidence interval [CI], 1.12\u0026ndash;1.92; P\u0026thinsp;=\u0026thinsp;0.006). Similarly, a PC-to-pRBC ratio of 1.5\u0026ndash;2 was associated with higher survival compared to a ratio of 0.5\u0026ndash;1 (adjusted OR\u0026thinsp;=\u0026thinsp;1.62; 95% CI, 1.00\u0026ndash;2.69; P\u0026thinsp;=\u0026thinsp;0.053). Patients were categorized into three phenotypes: truncal trauma with shock (70.3%), moderate head and extremity trauma (11.8%), and severe head trauma with consciousness disturbances (17.9%). In the truncal trauma with shock phenotype, FFP-to-pRBC ratios of 1\u0026ndash;1.5 (adjusted OR\u0026thinsp;=\u0026thinsp;1.56; 95% CI, 1.12\u0026ndash;2.20; P\u0026thinsp;=\u0026thinsp;0.010) and \u0026gt;\u0026thinsp;2 (adjusted OR\u0026thinsp;=\u0026thinsp;2.32; 95% CI, 1.14\u0026ndash;5.10; P\u0026thinsp;=\u0026thinsp;0.027) were associated with improved survival.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHigher FFP-to-pRBC (1\u0026ndash;1.5) and PC-to-pRBC (1.5\u0026ndash;2) ratios were associated with improved survival. Higher FFP-to-pRBC ratios were particularly beneficial for truncal trauma with shock phenotype.\u003c/p\u003e","manuscriptTitle":"Transfusion Ratios of Fresh Frozen Plasma and Platelet Concentrate to Packed Red Blood Cells in Patients with Severe Blunt Trauma Receiving Massive Transfusion: A Nationwide Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-06 13:26:45","doi":"10.21203/rs.3.rs-6316025/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-11T09:02:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-10T00:36:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"270029086135378730904529247794104119038","date":"2025-05-22T00:29:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-21T14:48:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"335054761709103590948584954029367944967","date":"2025-05-21T14:34:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-01T20:04:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-01T19:56:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-31T13:42:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-31T07:06:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-27T01:45:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a8ba2efe-2aae-4c31-a855-b10a1cbe1cb3","owner":[],"postedDate":"May 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47299803,"name":"Health sciences/Medical research/Outcomes research"},{"id":47299804,"name":"Health sciences/Diseases/Trauma"},{"id":47299805,"name":"Health sciences/Health care/Therapeutics/Surgery"}],"tags":[],"updatedAt":"2025-07-21T16:04:30+00:00","versionOfRecord":{"articleIdentity":"rs-6316025","link":"https://doi.org/10.1038/s41598-025-11338-7","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-07-15 15:56:55","publishedOnDateReadable":"July 15th, 2025"},"versionCreatedAt":"2025-05-06 13:26:45","video":"","vorDoi":"10.1038/s41598-025-11338-7","vorDoiUrl":"https://doi.org/10.1038/s41598-025-11338-7","workflowStages":[]},"version":"v1","identity":"rs-6316025","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6316025","identity":"rs-6316025","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}