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Abstracts of 25th Annual NATA Symposiumon Patient Blood Management, Haemostasis and ThrombosisMunich, Germany24-26 April 2026Reviewers NATA Scientific Committee Sigismond Lasocki - France (Chair)Michael Auerbach - USA Elivra Bisbe - SpainJeffrey L. Carson - USADavid Faraoni - USAThomas Frietsch - GermanyBernd Froessler - AustraliaJosé A. Garcia-Erce - SpainOliver Grottke - GermanyToby Richards - UKEmmanuel Rineau - FranceMaria Beatrice Rondinelli - ItalyCharles Marc Samama - FranceIgnacio Sarmiento Goldberg - ChileJakob Stensballe - DenmarkAlexander Vlaar - The NetherlandsChristian von Heymann - GermanyJonathan W. Waters - USA

Number of units of component transfusion therapy administered N x SD RBC (number of RBC units administered), FFP (number of fresh frozen plasma unitsadministered) PLT (number of platelet concentrates administered), Cryo-P (number ofcryoprecipitate units administered), (x (mean ) , SD (standard deviation), Min (minimum value),Max ( maximum value) Min Max t test p PLT– P FFP – P Cryo – P RBC – P TestedControlTotal TestedControlTotalTestedControlTotalTested Control Total 212243 212243 21 22 43 21 22 43 1,811,411,60 0,431,180,81 8,05 2,55 5,23 7,95 1,82 4,81 1,4011,1411,275 0,6760,9070,880 9,516 4,284 7,749 10,151 3,948 8,154 000 000 0 0 0 0 0 0 545 233 30 10 30 30 10 30 1,030 3,076 2,464 2,635 0,309 0,004 0,018 0,012

Table. Parameters of the blood coagulation system in the blood plasma of patients with severe burn injury oracoustic trauma. Reference group – blood plasma of healthy volunteers. Parameters Fibrinogen, mg/mlProthrombin time, sProtein C, %D-dimer, ng/mlSoluble Fibrin, µg/ml Soluble Fibrin (early forms), µg/ml 2.6 ± 0.329 ± 2100 ± 1054 ± 302.2 ± 0.8 2.2 ± 0.6 4.7 ± 0.6 *26 ± 6 *91 ± 26750 ± 800 *25.0 ± 18.0 3.0 ± 6.0 3.0 ± 0.931 ± 393 ± 17170 ± 150 *4.3 ± 1.9 1.2 ± 0.9 Reference group,n = 10 Thermal trauma,n = 5 Acoustic trauma,n = 22 * - Results are significant according to the Mann-Whitney test when compared to the reference group.

CONSORT CHART

Systolic Blood pressure/ Heart rate≤1.0 Indicates shock Heart rate / Systolic Blood Pressure≥0.9 Indicates Shock Each Postive response carries a response of 1 Systolic blood pressure- Diastolic blood pressure≤25 mm Hg indicates shock Shock index: Pulse Pressure: Reverse Shock index: ABC score RABT score HR> 120/min SBP< 90 mmHg Penetrating mechanism Positive e-FAST Presence of pelvic fracture Shock Index >0.9 Penetrating mechanism Positive e-FAST

IQR 0.000 0.000 0.513 0.053 0.230 0.002 0.154 0.285 0.028 0.031 0.067 0.658 0.168 HS HS NS NS NS HS NS NS sig sig NS NS NS p value ASI ISS RSI MSI ABC GCS Heartrate SI RABT SystolicBP(mmHg)Diastolic BP (mmHg)PulsePressure MAP MTNon MTMTNon MTMTNon MTMTNon MT MT Non MT MT Non MT MT Non MT MT Non MT MT Non MT MT Non MT MT Non MT MT Non MT MT Non MT Mean 1.7 1.0 1.8 1.1 11.9 12.2 90.7 100.8 58.26 62.4532.39 38.41 69.06 75.26 111.82 106.33 1.38 1.15 0.89 1.01 1.82 1.53 50.25 46.06 32.95 30.37 StandardDeviation0.9 0.9 0.7 0.8 4.6 4.2 28.9 28.8 20.3218.05 17.90 15.52 21.98 20.99 33.26 27.05 0.70 0.52 0.45 0.40 0.96 0.64 29.96 24.86 8.96 7.23 Median 2.0 1.0 2.0 1.0 15.0 15.0 90.0 96.0 60.00 60.0029.00 40.00 67.00 71.33 122.00 101.00 1.11 1.05 0.90 0.95 1.50 1.38 43.14 40.85 33.50 30.50 Lower 1.0 0.0 1.0 1.0 9.0 10.0 70.0 80.0 45.00 50.0020.00 30.00 56.67 60.00 88.00 88.00 0.98 0.79 0.62 0.70 1.29 1.07 26.45 26.88 27.00 26.00 Upper 2.0 2.0 2.0 2.0 15.0 15.0 110.0 124.0 60.00 76.0040.00 48.00 79.67 90.00 132.00 125.00 1.63 1.43 1.02 1.26 2.14 1.88 70.91 61.00 34.00 34.00

2 Scale: ABC Cutpoint Sensitivity(%) 63.16% Specificity(%) 69.66% PPV(%) 15.09% NPV(%) 95.68% Youden'sindex 0.328AUC 0.698 MetricScore 1.332 Cutpoint Scale: RABT Sensitivity(%) 65.79% Specificity(%) 69.44% PPV(%) 15.53% NPV(%) 95.96% Youden'sindex 0.352AUC 0.708 MetricScore 1.35

Shock Index: Cut point 0.9 Sensitivity (%) 86.84 Reverse Shock Index: Cut point Sensitivity (%) 48.96 0.98 Specificity(%) 73.68 Specificity (%) 36.03 PPV (%) 95.5 PPV (%) 10.65 NPV (%) 11.24 NPV (%) 96.89 Youden’s Index0.226 Youden’sIndex0.229 AUC 0.606 AUC 0.607 Metricscore1.23 Metricscore1.23

Figure1. EtCO2 trend shows a decrease in CO2 delivery to the lung (approx. at 11.40) due to the reduction of the cardiac output at the time of hemorrhagic shock. It was sharply increased and stabilized after intravenous administration of 3 boluses of epinephrine 0.1 mg. Figure 2. BIS monitoring trend indicates a downward trend of electrical activities of the brain due to a decrease of the BP and brain perfusion (approx. at 11.40) and restoration of the level of BIS after normalization of the hemodynamic.

Type 2 is a milder form Type 3 is a variant form Type 1 most common type PLATELET COUNT PLATELET FUNCTION BLEEDING TIMEFIBRINOGENPROTHROMBIN TIME(PT)ACTIVATED PARTIAL THROMBOPLASTIN TIME (aPTT) NORMAL ABNORMAL PROLONGEDREDUCEDNORMALNORMAL αIIbβ3 integrin seems to be non-functioning. αIIbβ3 integrin is present in reduced amounts (5%–20%) αIIbβ3 integrin is absent or present in trace amounts (0%–5%). LABORATORY INVESTIGATIONS INTERPRETATION

CASE 2: CASE 1: MANAGEMENT OF GLANZMANN THROMBASTHENIA: Pre-MedicationInduction:Post-operative MILD BLEEDINGMODERATE BLEEDING SEVERE BLEEDING •Inj. Propofol 80 mg Intravenous•Inj. Cisatracurium 10 mg Intravenous •Inj. Propofol 100 mg Intravenous •Inj. Midazolam 1 mg Intravenous•Inj. Fentanyl 200 mcg Intravenous•Inj. Cisatracurium 10 mg Intravenous•Analgesics : Inj. Paracetamol 1 g Intravenous•Inj.Neostigmine 2 mg and Inj. Glycopyrolate 0.4 mg Intravenous LOCAL MEASURESANTI-FIBRINOLYTICS PLATELET TRANSFUSION+/- recombinant factor VIIa (rFVIIa) Premedication•Inj. Midazolam 1 mg Intravenous•Inj.Fentanyl 200 mcg Intravenous•Analgesics : Inj. Paracetamol 1 g Intravenous•Inj.Neostigmine 2 mg and Inj. Glycopyrolate 0.4 mg Intravenous Induction P ost-oper ative

POSTER 9 Title: Authors’ affiliations: Bucharest, RomaniaABSTRACT: Background: Acute aortic dissection is a surgical emergency with high mortality if untreated. This study aimed toassess hemorrhagic complications, transfusion requirements, and survival outcomes in patientsundergoing surgical intervention, focusing on the impact of preoperative antiplatelet or anticoagulanttherapy. Methods: We conducted a retrospective analysis of patients treated for acute aortic dissection in a cardiac surgical intensive care unit between January 2023 and December 2024. Patients were categorized based on preoperative antiplatelet/anticoagulant use. Data collected included demographic characteristics, hemorrhagic events, transfusion requirements, and survival rates. Institutional protocols incorporating classical and viscoelastic coagulation tests guided management. Descriptive statistics were calculated using Microsoft Excel. Results: The study included 36 patients (median age 58 years, range 41–77), with 16.7% (n=6) on preoperative antiplatelet or anticoagulant therapy (AC/AP) - five on aspirin and one on apixaban. Intraoperative blood transfusion requirements were similar between groups, with a mean of 1.5 ± 2.12 units of red blood cells (RBC) for the AC/AP group versus 1.53 ± 0.70 units for the non-AC/AP group. However, postoperative transfusion needs were higher in the antiplatelet/anticoagulant group, with a mean RBC transfusion of 2.83 ± 7.7 units compared to 2.06 ± 11.31 units in the non-antiplatelet group. Hemorrhagic complications in the non AC/AP group were important (23.3%, n=7), with 6 patients requiring surgical hemostasis. These patients had a mortality of 36% (11/30). In the global cohort, liver dysfunction was identified in 36% of patients (n=13), contributing to worsened bleeding outcomes. The median length of ICU stay was 6.7 days (range 2–30), and the observed survival rate was 63% in the non-antiplatelet group compared to 66% in the antiplatelet/anticoagulant group. Conclusions: Preoperative antiplatelet or anticoagulant therapy in patients with acute aortic dissection is associated with increased postoperative bleeding and transfusion requirements, although survival rates were comparable to patients without such therapy. These findings highlight the importance of tailored perioperative coagulation management to improve outcomes in this high-risk population. Hemorrhagic complications of acute aortic dissection in a surgical cardiac intensive care unit (ICU)– a two years retrospective study Author(s): Mihnea Lapadat, Ana Maria Morar, Cornelia Predoi, Mihai Stefan, Ioana Marinica, Daniela Filipescu

Table 2: Postoperative transfusion of blood products and coagulation factors Table 1: Intraoperative transfusion of blood products and coagulation factors 1.2.RBCFresh frozen plasmaPlateletsCryoprecipitateCell Saver RBCFresh frozen plasmaPlateletsCryoprecipitate Fibrinogen (grams/patient)Prothrombin complex (units/patient) Postoperative blood transfusion(mean/patient +/- SD) Intraoperative blood transfusion(mean/patient +/- SD) 0,33+/-0416,66+/- 707,10 Onantiplatelet/anticoagulation No =6 1,5+/- 2,12 0,66+/-2,82 0 +/- 0 1,33+/-0 241,66+/-593,96 Onantiplatelet/anticoagulation No =6 2,83+/- 7,7 0 0 0 Controlgroup No=30 1,53+/-0,70 1,86+/-2,82 1,4+/-2,82 2,86+/- 4,24 465,73+/- 353,55 1,03+/-0,70 106,66+/-707,10 TotalNo=36 ESC Guidelines for the management of peripheral arterial and aortic diseases, 2024EACTS/STS Guidelines for Diagnosing and Treating Acute and Chronic Syndromes of theAortic Organ, 2024 1,52+/-0,701,66 +/- 2,821,22 +/- 02,61+/-12,02428,33+/- 695,08 0,91+/- 1,41 158,33+/- 848,52 Control group No=302,06+/-11,310,9+/-1,410,6+/-6,360,43+/-2,82 Total No=36 2,19+/-11,310,75+/-1,410,5+/-6,360,36+/-2,82 References

POSTER 11 The structure of supportive transfusion therapy in the treatment of patients with severe traumaMarija Milenkovic1,2MD PhD, Lidija Mijovic MD,Mirjana Kovac1,3MD PhD 21Faculty of Medicine, University of Belgrade, Serbia; 2Emergency Centre, University Clinical Centre of Serbia, Belgrade; 3Blood Transfusion Institute of Serbia, Belgrade Serbia Introduction: Trauma is one of the leading causes of global mortality. The Injury Severity Score (ISS) is the most widely used scoring system in traumatized patients. Severe trauma is defined as ISS>15. Early trauma-induced coagulopathy (TIC) is recognized as an independent predictor of mortality. Traumatized patients with TIC and haemorrhage show increased transfusion requirements and higher mortality rate. Transfusion supportive therapy consists of the use of the red blood cells, fresh frozen plasma and platelets in a ratio of 1:1:1. Tranexamic acid, given early, including early and repeated monitoring o f hemostasis, using standard tests and/or point of care (POC) tests of, were recommended. Methods: This retrospective, cohort study included 200 severely traumatized patients, hospitalised and treateDdE inA tDheL EINmEer gFeOncRy SCeUnBteMr oISf tSheIO thNe 09 January, 2025 – 23:59 CET from June 2022 until September 2023. Results: The average age of the patients proved to be a predictor of mortality (p=0.003), including prolonged stay in the intensive care unit (p=0.028) and ISS score (p<0.001). Mortality rates were higher in patients with comorbidities (p=0.008). The initial levels of hemoglobin, hematocrit and platelets, showed statistical relation to the outcome of treatment (p=0,008, p=0.014 and p<0.001), as well as the total number of administered doses of red blood cells and fresh frozen plasma (p<0.001, p<0.001). The same was concluded in patients who received ≥10 doses of platelets or cryoprecipitate (p<0.001, p=0.002). Conclusion: Our results show the predictive effect of transfusion therapy on the patient outcome. We did not find any correlation between tranexamic acid treatment and patient survival. We showed that patient age, prolonged stay in the intensive care unit, presence of comorbidities, vasopressor therapy and mechanical ventilation were predictors of mortality.

Table- Initial values of hematological parameters Table- The influence of transfusion and hematological supportive therapy on the outcome of patient treatment PRPCs- Packed red blood cells FFP-Fresh frozen plasma ParametersHemoglobinHematocritPlatelets Transfusion therapy that was givento the patient PRPCs 10 FFP 10 Platelets10 Cryoprecipitate10 Yes No Yes No Yes No Yes No Yes No Tranexamic acid Average value ± SD116±19,20,34±0,05187±78,8 Treatment outcome Survived6(4,08%)141(95,92%)1(0,68%)146(99,32%)8(5,4%)139(94,6%)12(8,2%)135(91,8%)13(8,8%)134(91,2%) Died1(1,9%)52(98,1%)1(1,9%)52(98,1%)13(24,5%)40(75,5%)13(24,5%)40(75,5%)9(16,98%)44(83,02%) p 0,456 0,449 <0,001 0,002 0,089 P0,0080,014<0,001 26.50%73.50%Outcome of treatment●73,50% survived●26,50% died

Figure 1. Pre-transfusion Hemoglobin (top panel) and Transfusion Probability (bottom panel)illustrated in patients with cardiac disease, GI bleeding, and sickle cell disease.

Introduction Pre-introduction Post-introduction(1st half) Post-introduction (2nd half) 65 (8.5) 83 (16.6) 73 (15.4) 119 (17.7) 192 (25.0) 214 (31.8) 204 (40.8) 215 (45.4) 96 (14.3) 89 (17.8) 86 (18.2) 154 (20.1) 411 (53.6) 429 (63.7) 376 (75.2) 374 (79.1) 767 (100.0) 673 (100.0) 500 (100.0) 473 (100.0) Table 1. Hemoglobin concentration before and after red blood cell transfusions during the study period.Hemoglobin concentration, Me, IQR [g L-1] Study periodPre-introductionIntroductionPost-introduction (1st half)Post-introduction (2nd half) Pre-transfusion73 (66–78)69 (62–77)68 (62–73)67 (60–73) Post-transfusion91 (80–99)87 (76–96)86 (78–93)84 (75–93) IQR–interquartile range, Me–median value Table 2. Appropriateness of red blood cell transfusions during the study period. Study period Hb <60 [g L-1] Hb <70 [g L-1] Hb <80 [g L-1] Appropriate Transfusions all all Hb–hemoglobin concentration

POSTER 16 Clinicians´ self-assessed knowledge on plasma transfusion in Norway:Results of a national survey 1 3 4 6Kongsgaard U, 7Munkeby B.H., 8Joly S.I., 3Mohus M.R. Espinosa A., 2Aandahl A., Jacobsen B., Kristoffersen G., 5Sundic T., Arsenovic M., 7, 234 5 61Oslo University Hospital, Oslo, Norway Akershus University Hospital, Lørenskog, Norway, St. Olav´s University hospital, Trondheim, Norway, Stavanger University Hospital, Norway, Haugesund Hospital, Norway, University Hospital North Norway, Tromsø, Norway, 8 Dept. of Anesthesia, Baerum Hospital, Norway References: 1. Plasma Transfusion Practice in Adult Surgical Patients: Systematic Review of the Literature.Sep 18;47(5):347–359. 2. Plasma transfusion practices: A multicentre electronic audit. Elisabeth Hannah Adam et al. Transfused Med Hemother. 2020 Aditi Khandelwal et al. Vox Sang. 2022 Oct;117(10):1211-1219. Introduction: In Norway, 40.000 plasma units, mainly Octaplasma ® are transfusedannually, corresponding to 7,2 units per 1.000 inhabitants. The plasma usage has beenstable in Norway, compared to the decreasing usage of red cell concentrates. There arefew evidence-based indications for plasma transfusion (1) and no national transfusionguidelines in Norway. The Norwegian Patient Blood Management (PBM) Working Groupconducted an anonymous national survey among clinicians in 2024, to evaluate their self-assessed knowledge on plasma transfusion. Methods: The survey included questions regarding indications for plasma transfusion, dosage and ordering routines. Responders were able to supply with additional comments on the survey. We included information on medical speciality, senior/resident background and geographical region. Results: 256 completed forms were recei ved, 28% from residents and 72 % from senior doctors. Anaesthesiology, General Surger y and Internal Medicine were the specialties with highest number of responders (84% of all the received forms). The indications for plasmatransfusion with highest number of answers were in a massive transfusion protocol,coagulopathic bleeding diagnosed by viscoelastic testing, reversing oral anticoagulation ina bleeding patient and moderate bleeding in a haemodynamically stable patient. 20 % ofthe responders would give plasma as a volume substitute to an intensive care patient.59 % of the participants responded that they do not know the recommended plasma dose,while 6 % chose the right recommended plasma dose of 15 mL/kg weight. 36 % of theparticipants would give another dose, a dose of 1-2 plasma units, or a dose based on thepatient´s INR value. Only 3,5 % of the residents and 18 % of the senior doctors regardedtheir knowledge on plasma transfusion as satisfactory. Many responders pointed out theneed for national transfusion guidelines in Norway. Conclusion: This survey shows that the responders´ self-assessed knowledge on plasma transfusion is low. Several other surveys have demonstrated sub-optimal use of plasma (2), which may not be in accordance with the limited number of evidence-based indications. Efforts should be made to reduce inadequate use. Patient Blood Management programmes should include plasma management in their scope. The elaboration of national transfusion guidelines in Norway, including plasma transfusion, should be a priority.

0 20 40 60Number of answers80 100Number of answers120 140 160 180NoI don´t knowResidentsResidentsSenior doctorsSenior doctorsYesDo you consider your knowledge on plasma transfusion as adequate?Dose by INR15mL/kg patient´s body weight1-2 unitsOtherNo, I do not know the plasma dose020 40 60 80 100Number of answers120 140 160Are you familiar with the recommended plasma dose?Which are the main indications you use for ordering plasma? Massive transfusion protocolBleeding with coagulopathy by viscoelastic testsModerate bleeding in haemodynamically stable patientReversing oral anticoagulation prior to procedure with risk for bleedingVolume substitution in critical care patientsTogether with every erytrocyte concentrateProphylactic prior to diagnostic invasive procedure, regardless INROther indications050 100 150 200 250 300Reversing oral anticoagulation in bleeding patient

ResultsErythrocyte suspensions had the highest usage and disposal costs,significantly impacting overall expenditures. Fresh frozen plasma (FFP)contributed moderately to both usage and wastage, with notable disposalshighlighting the need for improved inventory practicesConclusionThis study highlights the financial impact of blood product disposals,with erythrocyte suspensions contributing the highest costs.Notably, apheresis platelets and cryoprecipitate had no disposals,primarily due to their preparation being limited to immediate andconfirmed clinical needs, unlike other products that are often preparedin advance for potential use.These findings underscore the importance of aligning inventorymanagement practices with clinical demand to minimize wastage andenhance cost efficiencyReferencesAntalya City Hospital Blood Bank Records, 2023-2024MethodologyThis retrospective study analyzed blood transfusion records from Antalya City Hospital over a one-year period. Data on the types and quantities oftransfused blood products, associated costs, and unused or discarded units were collected from hospital records. Cost analysis was conducted based;Erythrocyte SuspensionsFresh Frozen PlasmaPooled PlateletsApheresis PlateletsCryoprecipitateANNUAL COST ANALYSIS OF BLOODPRODUCTS TRANSFUSED ATANTALYA CITY HOSPITALBlood transfusions are essential for patient care but come with considerable costs.This study evaluates the annual usage and financial impact of blood products atAntalya City Hospital, highlighting potential areas for cost reduction and qualityimprovement.The findings were evaluated to identify patterns of usage and potential cost-saving opportunities.These findings emphasize the need for optimized managementstrategies across all blood products to minimize wastage and reducecosts.

Table 1: Studies comparing the Effect of Viscoelastic Testing-guided Bleeding Management versus Control (CON) on Mortality in Cirrhotic Patients undergoing invasiveProcedures or in Patients undergoing Liver Transplantation. Study (Author,Journal, Year) Wang, Transplant Proc, 2010 Alamo, Transplant Proc, 2013 Roullet, Liver Transpl, 2015 Leon-Justel, Clin Chim Acta, 2015 De Pietri, Hepatology, 2016 Smart, Ann Hepatol, 2017 Kandeel, Egyt J Anaesth, 2018 Zamper, BMC Anesthesiol, 2018 Schumacher, Exp Clin Transplant, 2019 Leon-Justel, Clin Chem Lab Med, 2019 Bonnet, Eur J Anaesthesiol, 2019 Kumar, Hepatology, 2020 Rout, J Clin Gastroenterol, 2020 Rocha, J Thromb Haemost, 2020 Vuyyuru, Dig Dis Sci, 2020 Nascimento, Eur J Gastroenterol Hepatol, 2020 RCT RCT Study Type RCT RCT Prospective Cohort Study RCT Case-Control Study Prospective Cohort Study Prospective Cohort Study RCT Prospective Cohort Study Retrospective Cohort Study Matched Cohort Retrospective Cohort Study Prospective Cohort Study RCT LTX, 3-month postop Mortality Clinical Setting, Age, Mortality(Definition) LTX, 3-years Mortality LTX, 5-years Mortality LTX, 28-days Mortality LTX, 1-year Mortality Cirrhosis, invasive Procedures, 90-days Mortality LTX, 60-days Mortality LD-LTX, 1-year Mortality LTX, In-hospital Mortality LTX, ≥14 years, Mortality before first postop ICU Discharge LTX, 1-year Mortality Cirrhosis, nonvariceal Bleeding, 42-daysMortalityCirrhosis, variceal Bleeding, 6-weeks Mortality Cirrhosis, Central Venous Catheterization, 28-days Mortality Cirrhosis, high-risk invasive Liver-related Procedures, 28-days Mortality LTX, 1-year Mortality TEG TEG ROTEM ROTEM ROTEM TEG ROTEM VET Device(ROTEM, TEG,Quantra, etc.)TEG ROTEM ROTEM ROTEM TEG ROTEM ROTEM ROTEM ROTEM OverallMortality (%[N/N]) 17.9%[5/28] 37.9% [89/235] 6.7% [4/60] 20.0% [40/200] 25.0% [15/60] 2.9% [2/68] 18.5% [40/216] 4.5% [6/134] 16.9% [70/413] 15.5% [52/336] 3.8% [3/79] 60.4% [58/96] 20.0% [12/60] 39.5% [15/38] 1.7% [1/58] 31.4% [48/153] 55.1% [27/49] 13.3% [4/30] 57.9% [11/19] 0% [0/29] 26.8% [22/82] VET Mortality(% [N/N]) 14.3% [2/14] 22.5% [20/89] 6.7% [2/30] 19.0% [19/100] 26.7% [8/30] 2.9% [1/34] 16.5% [20/121] 2.2% [1/45] 12.2% [10/82] 14.3% [24/168] 5.1% [2/39] 21.1% [4/19] 3.4% [1/29] 36.6% [26/71] 66.0% [31/47] 26.7% [8/30] CON Mortality (% [N/N]) 21.4% [3/14] 47.3% [69/146] 6.7% [2/30] 21.0% [21/100] 23.3% [7/30] 2.9% [1/34] 21.1% [20/95] 5.6% [5/89] 18.1% [60/331] 16.7% [28/168] 2.5% [1/40] RR [95% CI] 0.86 [0.52; 1.42] 0.84 [0.60; 1.16] 0.50 [0.17; 1.48] 2.75 [1.06; 7.12] 0.33 [0.01; 7.85] 0.73 [0.46; 1.17] 0.67 [0.13; 3.40] 0.48 [0.31; 0.73] 1.00 [0.15; 6.64] 0.90 [0.52; 1.58] 1.14 [0.47; 2.75] 1.00 [0.07; 15.34] 0.79 [0.45; 1.37] 0.40 {0.05; 3.29] 0.67 [0.36; 1.26] 2.05 [0.19; 21.72] NA NA NA NA NA NA NA FragilityIndex(for MA)NA NA NA NA NA NA NA NA NA

RCTs ROTEM Cohort Studies Scarlatescu,Transfus ApherSci, 2021Gaspari, J Clin Anesth, 2021 Maria, Liver Int, 2022 CirrhosisundergoinginvasiveProceduresLiverTransplantation TEG Sarmiento,Transfus MedHemother, 2024Biswas, J Vasc Interv Radiol, 2024 Kumar, J Clin ExpHepatol, 2025 TOTAL 10 RCTs RetrospectiveCohort Study RCT RCT 10 RCTS + 12 Cohort Studies 12 CohortStudies 8 RCTs, 0 Cohort Studies Propensity Score-Matched CohortStudyRetrospective Cohort Study RCT 2 RCTs + 12Cohort Studies 6 RCTs + 1 Cohort Study 4 RCTs + 11 Cohort Studies 12 LTX Studies 8 Cirrhosis Studies LTX, 30-days Mortality 2 LTX + 8 Cirrhosis Studies 2 LTX + 5 Cirrhosis Studies 12 LTX + 3 Cirrhosis Studies 14 Liver Transplantation Studies Cirrhosis, Thrombocytopenia, high-riskinvasive Procedures, Bleeding-relatedMortalityCirrhosis, invasive Procedure, 90-days Mortality 14 LTX + 8 Cirrhosis Studies (including 1 Pediatric Cirrhosis Study) LTX, 90-days Mortality Cirrhosis, invasive Procedures, children <18 years; Mortality data provided by the corresponding author Seema Alam, ILBS, New Delhi LTX, 28-days Mortality TEG ROTEM ROTEM TEG ROTRM 15 ROTEMStudies ROTEM 15 ROTEM + 7 TEG Studies 4 ROTEM +6 TEG Studies 11 ROTEM + 1 TEG Study 3 ROTEM + 5 TEG Studies 12 ROTEM +2 TEG Studies 7 TEG Studies 0% [0/58] 20% [8/40] 17.9% [498/2789] 20.3%[117/577] 17.2% [381/2212] 23.2% [109/470] 16.8%[389/2319] 19.5% [105/539] 17.5% [393/2250] 3.3% [1/30] 8.0% [15/188] 7.8% [14/179] 0% [0/60] 0% [0/29] 20.1%[58/289] 13.9% [132/951} 22.9% [54/236] 20% [4/20] 15.3% [190/1240] 13.5%[136/1004] 16.6% [45/271] 15.0% [145/969] 8.5% [8/94] 4.4% [4/90] 0% [0/30] 6.3% [1/16] 0% [0/14] 0% [0/29] 20% [4/20] 19.9% [308/1549] 20.5%[59/288] 19.7% [249/1261] 23.5% [55/234] 19.2%[253/1315] 22.4% [60/268] 19.4% [248/1281] 7.4% [7/94] 11.2% [10/89] 0% [0/30] 1.14 [0.43; 3.02] 0.40 [0.13; 1.21] Zero Event Study Zero Event Study 2.64 [0.12; 59.82] 1.00 [0.29; 3.45] 0.77 [0.66; 0.91]; P = 0.00162; I2 = 0%; AIS = 96% 0.97 [0.68; 1.37]; P = 0.84584; I2 = 12%; AIS = 19% 0.70 [0.58; 0.86]; P < 0.0005; I2 = 0%; AIS = 75% 1.00 [0.64; 1.55]; P = 0.98487; I2 = 32%; AIS = 15% 0.71 [0.58; 0.86]; P = 0.00055; I2 = 0%; AIS = 76% 0.79 [0.59; 1.04]; P = 0.08915; I2 = 0%; AIS = 22% 0.79 [0.64; 0.99]; P = 0.04173; I2 = 14%; AIS = 64% 1 10 11 NA NA NA NA NA NA 6 NA NA NA

Figure 1: graphical abstract

HOT TOPICS SESSION

Table 2. IMP dose and INR values before and after the first dose of IMP* in the FARES-II study (FASPopulation; N=420) Table 1. IMP dose and Clauss plasma fibrinogen levels before and after the first dose of IMP* in theFIBRES study (mITT Population; N=735) Fibrinogen concentrate Cryoprecipitate Mean (±SD) Mean (±SD) Median (IQR) Median (IQR) N N Total IMP dose† g U 4.8 (±2.1) 4.0 (4.0, 4.0) 12.8 (±8.5) 10.0 (10.0, 10.0) 372 363 Plasma fibrinogen level (g/L) 1.7 (±0.6) 2.5 (±0.6) 1.6 (1.3, 2.0) 2.4 (2.1, 2.8) 1.7 (±0.6) 2.3 (±0.6) 1.7 (1.3, 2.0) 2.2 (2.0, 2.5) Pre-IMP 223 182 Post-IMP 253 242 *Includes measurements taken before IMP initiation and after IMP completion. N values represent the number of patients out of the mITT population (N=735) for whom data were available. †As per the randomised treatment allocation schedule, 4 g FC or 10 U cryoprecipitate were administered each time fibrinogen supplementation was ordered for post-CPB hemorrhage with confirmed or suspected acquired hypofibrinogenemia during the first 24 hours after termination of CPB (thereafter, only cryoprecipitate was used for fibrinogen replacement). Analysis excludes two patients (PCC group) who switched treatment. IMP = investigational medicinal product; IQR = interquartile range; mITT = modified intention-to-treat; SD = standard deviation; U = units. INR Total IMP dose† N PCCMean (±SD) Median(IQR) N FP Mean (±SD) Median(IQR) 213 27.8(±10.5) IU/kg 25.0(21.8, 29.4) 207 4.5(±1.6) U 4.0(4.0, 4.0) 2.3(±0.8) 1.5 (±0.4) 2.2(1.8, 2.5) 1.4 (1.2, 1.6) 2.2(±0.6) 1.6 (±0.7) 2.0(1.7, 2.6) 1.5 (1.3, 1.7) Pre-IMP 203 195 Post-IMP 210 204 *Includes measurements taken before IMP initiation and after IMP completion. N values represent the number of patients out of the FAS population (N=420) for whom data were available. †As per the randomised treatment allocation schedule, PCC (1,500 IU for bw ≤60 kg, 2,000 IU for bw >60 kg) or FP (3 U for bw ≤60 kg, 4 U for bw >60 kg) were administered when coagulation factor replacement was ordered for management of bleeding or anticipated bleeding and known or suspected coagulation factor deficiency. A second dose could be administered within 24 hours after the first dose if the patient continued to have at least moderate bleeding and suspected coagulation deficiency. Analysis excludes one patient (FP group) who received a different treatment than randomized as the second dose of IMP. bw =body weight; FAS = full analysis set; FP = frozen plasma; IMP = investigational medicinal product; IQR = interquartile range; IU = international units; PCC = prothrombin complex concentrate; SD = standard deviation; U = units.

Fig. 1 Distribution of Diagnosis of patients Table 1 Pair wise comparison of TEG parameters at different time points Table 2 Pair wise comparison of standard coagulation parameters at different timepoints (N=60) PTMean ± SD ('p' value)* 16.0 ± 3.519.9 ± 3.8 (p=0.000) 19.9 ± 2.6 (p=0.000) 22.4 ± 1.9 (p=0.000) APTTMean ± SD ('p' value)* 28.3 ± 2.830.9 ± 4.2 (p=0.000) 30.7 ± 2.7 (p=0.000) 30.9 ± 4.2 (p=0.000) PlateletMean ± SD ('p' value)* 1.8 ± 0.52.4 ± 0.6 (p=0.000) 2.1 ± 0.7 (p=0.001) 1.3 ± 0.4 (p=0.000) FibrinogenMean ± SD ('p' value)* 197.4 ± 18.8256.1 ± 22.6 (p=0.000) 407.9 ± 46.9 (p=0.000) 330.8 ± 49.5 (p=0.000) Time Time R K ALPHA MA CI ly 30 Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD ('p' value)* 0.1 ± 0.20.6 ± 1.0 (p=0.000) 1.1 ± 1.6 (p=0.000) 0.7 ± 0.7 (p=0.000) 1.2 ± 0.5 (p=0.000) ('p' value)* 6.5 ± 1.95.1 ± 2.2 (p=0.201) 5.9 ± 2.1 (p=0.328) 6.7 ± 2.7 (p=0.005) 6.4 ± 1.9 (p=0.009) ('p' value)* 1.9 ± 0.61.6 ± 0.7 (p=0.033) 1.6 ± 0.5 (p=0.002) 1.8 ± 0.8 (p=0.903) 1.7 ± 0.6 (p=0.062) ('p' value)* 64.0 ± 7.866.9 ± 8.5 (p=0.042) 65.9 ± 7.3 (p=0.071) 64.7 ± 8.8 (p=0.592) 64.1 ± 7.0 (p=0.895) ('p' value)* 68.0 ± 7.169.0 ± 7.4 (p=0.300) 71.9 ± 5.2 (p=0.000) 72.7 ± 6.1 (p=0.000) 71.2 ± 5.2 (p=0.003) ('p' value)* -1.3 ± 2.11.7 ± 2.8 (p=0.321) 1.5 ± 2.1 (p=0.531) 0.9 ± 3.2 (p=0.310) 0.8 ± 3.2 (p=0.293) CRS Post-HIPEC Post-operative day 1 Post-operative day 2 * 'p' value is computed corresponds to pre-op CRS Post HIPEC Post-operative day 1 Post-operative day 2 Post-operative day 3 * 'p' value is computed corresponds to pre-op A pend ixGa stri cOva ryStomach1.1%3.4% 1.1% 1.1%8.0%3.4%ColonMesiothe68.2%Ps eudoColon/pse13.6%

Table 3 variables in patient undergoing HIPEC Variables Values PCI*PRBC*FFP*Crystalloid (In litre)*Colloid* (In litre)Duration of Surgery (In hours)*Blood loss in lit.*Ascites in lit.*Morphine in mg*Fentanyl in microgram/ml*Cam mol/l*Mg mg/dl*Discharge ICU* (In days)Discharge Hospital*# (In days)Temperature* °Centigrade 15.1(4.9)1.3(1.6)0.6(1.2)3.5(0.8)1.5(0.7)9.9(1.8)1.2(1.3)0.4(0.4)7.1(2.5)154.1(27.1)0.9(0.1)1.3(0.3)5.2(1.7)7.8(2.5)38.4(0.4)11.4% No Yes All cases in day 4 No Yes No 6 cycles Epidural (n, %) 88.6% Epidural removal (n, %) 100% 17.0% Extubation(n, %) 83.0% Pre-Operative Chemotherapy (n, %) 54.5% 40%

Overall cohort(n=44) Factor XIIIactivity <50 %(n=25) Factor XIIIactivity ≥50%(n=19) p-value Major bleeding event (n/%) In-Hospital Mortality (n/%) ICU Mortality (n/%) 28-day Mortality (n/%) ECMO weaning 48 hours survival (n/%) ICU length of stay (days) 33 (75) 21 (84) 12(63.2) 0.21 11 (25) 7 (28) 4 (21.1) 0.73 10 (22.7) 6 (24.0) 4 (21.1) 1.0 10 (22.7) 6 (24.0) 4 (21.1) 1.0 34 (77.3) 21 (84) 13 (68.4) 0.67 16 (12) 21 (9) 14 (16.5) 0.3 Table 1. Outcome parameters of overall patient cohort as well as patients with minimum Factor XIII activity <50% and ≥50%. Data are presented as median and IQR or absolute numbers and percentages. ECMO: extracorporeal membrane oxygenation; ICU: intensive care unit.

Spearman‘s rho=−0.32p-value = 0.03Minimum FXIII activity measuredAmount of pRBCs transfused

TRANSFUSION REQUIREMENTSFresh FrozenPlasmaPlatelets Red blood cellsUnits transfused

1 ROC curve for FXIII activity <50% to predict major bleeding eventsVariable Odds Ratio CI Lower (95%)CI Upper (95%)InterceptFXIII <50 %1,71433,060,67490,744,354412,65p-val ue=0. 12− SpecificitySensitivity

thresholdFXIII 55.5% 0.82 sensitivity specificity0.451 ROC curve for minimum FXIII activity to predict major bleeding events− specificitysensitivity

Fig.3 PROMs and PREMs for the Obstetric PBM Journey Fig 1. Pregnancy Path Fig 2. Postpartum Path

Fig. 4 Obstetric PBM Journey CROMs

Group Total GROUP A GROUP B 90 200 Rotems Fibtem 6 16 A5 < or = 8 Fibtem A5 < or= 10 10 24 Total RotemsFibtem A5 < or= 10Fibtem A5 < or = 8050 100 150GROUP B GROUP A200 250

Transfused units DECREASE of 13% Transfused units DECREASE of 13% SUT transfusion IMPROVEMENT of 39% (<7 and >8 no improvement) 4704604504404304204104003903803705004504003503002502001501005008649 55 61 42Physician 1467201954%11110398 9955Physician 22019 2020430404202475%283225Physician 32021 2022135202370%60%50%40%30%20%10%0%101 93 9149 63 52Physician 42024Physician 5132108 9962704803540Units Transfused267SUT20480%83RBC Transfusion & SUTRBC 2019 -2024

Overall 4% DECREASE of all products from 2019 to 2024. 7006005004003002001000114 10664 74 59 50Physician 1143Physician 220192541772020441629Physician 32021 20224403763282712023Physician 42024191 211220140 136 148Physician 5286218189 192145 173252234246All Products 2019 -2024

TABLE 1: Transfusion consume evolution 2010-2022

UNITEDKINGDOMSPAINITALYGERMANYPORTUGALRed Cell Concentrate (U)Platelets (DT) Total Plasma(U) Transfusión Hematíes(U) Transfusión Plaquetas(DT) Transfusión Plasma (L)Transfusión Hematíes (U)Transfusión Plaquetas (DT)Transfusión Plasma (L) RedCell Concentrate (U) RedCell Concentrate (U)-56601043245-75412-10794045322-71498-50310-13730-32382-197098-26,0%+17,5%-21,5%-6,8%+23,3%-35,6%-15,0%-20,7%-43,0%-7 , 3%-26,7%TABLE 2: Overall Transfusion consume evolution 2010-2022U: units; DT: Terapeutic DoseL L: litres

40 .0 035 .0 030 .0 025 .0 015 .0 010 .0 05.000.002011 2012 2013RED Cell SPAIN2014 2015 2016RED Cell UK2017 2018 2019 2020RED Cell PORTUGAL2021 202220 .0 0RED CELL CONCENTRATESFigure 2: Rate Red Cell Transfusion/1000 hab evolution 2011-2022

45.0040.0035.0030.0025.0020.0015.0010.005.000.00UKUKSPAINGERMANY*PORTUGALPORTUGALITALYSPAIN ITALY GERMANY*Red Cell Transfusion/1000 Hab (2021)

POSTER 138 Title: Preoperative autologous bl ood donation program for bone marrow donors: do we still need one? Author(s): MAZIĆ Sanja, Majcen Kristina, Lukić Marija, Bojanić Ines Authors’ affiliations: UHC Zagreb, Department of Clinical Transfusion Medicine and Transplantation Biology, Kišpatićeva 12, 10 000 Zagreb, CROATIA ABSTRACT: IntroductionAfter discontinuing the perioperative autologous blood donation (PAD) program inorthopedics in 2012. our hospital kept PAD active for healthy bone marrow donors.Donors are evaluated and referred to National blood institute for donation of 450mL autologous blood and production of RBC concentrate and SSP that are stored inhospital blood bank until procedure. After BM collection unit is transfused inoperating room to compensate for the blood loss.MethodsRetrospective single-centre analysis of collected, transfused and discardedautologous units, and donor outcomes in the period from 2017. to 2024. wasconducted. Data was gathered from hospital and transfusion information systems.ResultsIn the period of 2017. to 2024. 129 donors donated bone marrow. Donordemographics (63 female, 49%, 66 male 51%, median of age 33 y. (range 4-68),102 related, 27 nonrelated). 12 (9,3%) donors were not refered to PAD (N forreasons of young age (N 6), medical contraindication (N 2), poor venous acces (N1), organizational reasons (N 1) and unnecessary due to low volumes collected (N2) had available antigen matched homologous blood. Of 117 collected units 5expired due to procedure postponements and discard rate was 4,3%. Median ofcollected bone marrow was 15,8 mL/kg (1,7 to 37,1) and median Hb loss postcollection compared to pre-PAD was 39 g/L (10 to 73). 112 units were transfusedon median day 6 (3-24) without adverse events reported, one donor requiredadditional 2 homologous units and 7 donors received intravenous iron.ConclusionsConsidering the well established PAD programme in our institution it is stillbeneficial for healthy bone marrow donors minimizing the need for the allogenictransfusion.

Table 1 - perioperative vairables and red blood cell transfusion of female patients. NAge (years)Surgery time(mins) CPB time (mins) Hb1(g/dl) Hb2 (g/dl) Hb3 (g/dl) PRBC Transfusion (number of patients, percentage) PRBC units Periop Transfusion (median) PRBC units Periop Transfusion (mean) Mortality Hospital length of stay (days) ICU length of stay (days) 1 (0-2) 3 (2-4) 1 (SD 3) 2 (1.17%)13 (10-18) F Hb preop 13 171 64 (58-68) 240 (190-290) 84 (67-103) 13.6 (13.3-14.4) 9.6 (8.7-10.7) 9.4 (8.9-10.4) 98 (57.3%) 2 (0-3) 3 (2-4) 2 (SD 3) 5 (4.46%)14 (11-17) F Hb preop12- <13 11267 (58-72) 250(200-300) 96 (76-120) 12.5 (12.2-12.8) 9.5 (8.7-10.2) 9.4 (8.9-10.2) 78 (69.6%) 2 (1-3) 3 (2-5) 3 (SD 2) 3 (2.6%)14 (11-19) FHb <12 116 67 (61-72) 240 (200-300) 94 (72-116) 11.1 (10.5-11.6) 9 (8.4-9.8) 9.4 (8.6-10) 101 (87%) P=1 P value P=0.014P=0.534 P=0.301 P<0.001 P=0.002 P=0.796 P<0.001 P<0.001 P=0.004 P=0.530P=0.824

Title: Transfusion Practices in Cardiac Surgery: A Three-Year Analysis of Two US AcademicHealthcare Systems Overall Transfusion Rates by Surgical Characteristics Transfusion Rates in Cardiac Surgery Patients by Calendar Years (2022-2024) Transfused (Yes) n (%) DESCRIPTION All Surgery(n=2,546) 681 (26.7) Any Blood Product All surgeryCABG (+/-Valve)Valvular Surgery RBC All surgeryCABG (+/-Valve)Valvular Surgery FFP All surgeryCABG (+/-Valve)Valvular Surgery PLT All surgeryCABG (+/-Valve)Valvular Surgery Cryo All surgeryCABG (+/-Valve)Valvular Surgery 2022Total (n=275)CABG (+/-Valve) (n=138)Valve (n=137)n (%)115 (41.8)65 (47.1)50 (36.5) 89 (32.4)59 (42.8)30 (21.9) 35 (12.7)19 (13.8)16 (11.7) 56 (20.4)27 (19.6)29 (21.2) 33 (12.0)17 (12.3)16 (11.7) CABG (+/- Valve)(n=1033; 40.6%) 349 (33.8) Type of Surgery Transfused (Yes)n (%) 324 (32.9) 25 (53.2) Isolated CABG (n=986) CABG+ Valve (n=47) 2023Total (n=1048)CABG (+/-Valve) (n=377)Valve (n=671)n (%)237 (22.6)95 (25.2)142 (21.2) 195 (18.6)89 (23.6)106 (15.8) 59 (5.6)17 (4.5)42 (6.3) 91 (8.7)26 (6.9)65 (9.7) 72 (6.9)15 (4.0)57 (8.5) 2024Total (n=1223)CABG (+/-Valve) (n=518)Valve (n=705)n (%)329 (26.9)189 (36.5)140 (19.9) 258 (21.1)155 (29.9)103 (14.6) 75 (6.1)34 (6.6)41 (5.8) 130 (10.6)56 (10.8)74 (10.5) 110 (9.0)53 (10.2)57 (8.1) Valvular Surgery(n=1513; 59.4%) 332 (21.9) Transfused (Yes) n (%) Type of Surgery AVR (n=1217) MV Replace (n=219) MR Repair (n=75) AVR+MV Replace (n=2) 264 (21.7) 66 (30.1) 2 (2.7) 0 (0)

Transfused Units of Blood Products Transfusion Rates in Cardiac Surgery Patients by Health System (2022-2024) DESCRIPTION Any BloodProduct All surgeryCABG (+/-Valve)Valvular Surgery RBC All surgeryCABG (+/-Valve)Valvular Surgery DESCRIPTIONTotal Blood Product Units Mean (SD)Range RBC Units Mean (SD)Range FFP Units Mean (SD)Range PLT Units Mean (SD)Range CRYO Units Mean (SD)Range All Surgery(n=681)6.1 (7.6)1 - 75(n=542)2.5 (2.5)1 - 32(n=169)2.5 (2.2)1 – 22(n=277)1.9 (1.4)1 – 13(n=215)8.6 (4.8)5 - 30 INSTITUTION 1 (n =1782) 2023Total (n=629)CABG (+/-Valve) (n=156)Valve (n=473) n (%) 133 (21.1)39 (25.0)94 (19.9) 2024Total (n=1153)CABG (+/-Valve) (n=471)Valve (n=682) n (%) 298 (25.8)168 (35.7)130 (19.1) 109 (17.3) 35 (22.4) 74 (15.6) 232 (20.1) 136 (28.9) 96 (14.1) CABG (+/-Valve)(n=349)5.2 (7.4)1 - 75(n=303)2.4 (2.6)1 - 32(n=70)2.9 (2.9)1 – 22(n=109)1.8 (1.4)1 – 8(n=85)7.9 (4.0)5 - 25 INSTITUTION 2 (n=764) 2022Total (n=275)CABG (+/- Valve)(n=138)Valve (n=137) n (%) 115 (41.8)65 (47.1)50 (36.5) 2023Total (n=419)CABG (+/- Valve)(n=221)Valve (n=198) n (%) 104 (24.8)56 (25.3)48 (24.2) 89 (32.4) 59 (42.8) 30 (21.9) 86 (20.5) 54 (24.4) 32 (16.2) Valvular Surgery(n=332)7.0 (7.6)1 – 54(n=239)2.5 (2.4)1 – 21(n=99)2.3 (1.4)1 – 8(n=168)1.9 (1.4)1 – 13(n=130)9.0 (4.0)5 - 30 2024Total (n=70) CABG (+/- Valve) (n=47) Valve (n=23) n (%) 31 (44.3)21 (44.7)10 (43.5) 26 (37.1) 19 (40.4) 7 (30.4)

Safety of IntraOperative Cell Salvage in visceral ONcologic surgery (SIOCSON) 1 1 1Fig 1: Schematic representation of sample collection for the Study SureshKumar HK, Schenz J, Weigand MA, Fischer D1 1Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany Figure 1

1Addressing anaemia in major oncological surgery: national priority, local success?Implementing PQIP guidelines at a UK specialist cancer hospital Ganatra S, Seligman WH, Dormido C, Black E, Rao Baikady R Department of Anaesthesia, The Royal Marsden NHS Foundation Trust, London, United Kingdom FOUR FIGURES ATTACHED, ONE PER PAGE – PLEASE SEE BELOW Fig. 1 – The evolution of the Royal Marsden’s Perioperative Anaemia Management Service (PAMS)

2Fig. 2 – Baseline characteristics Fig. 3 – Proportion of patients with anaemia stratified by type (anaemia) Hb, haemoglobin; IDA, iron-deficiency Fig. 4 – Implementation of patient blood management: intravenous iron (IVFe) administration,tranexamic acid (TXA) usage, and red cell transfusion (EBL, estimated blood loss; IOCS,intraoperative cell salvage)

4

Fig. 3. A decrease in mortality, posttransfusion complications and infections after the application of Patient Blood Management (PBM) in a study indicates that the PBM strategies are having a positive impact on patient outcomes, reducing risks and enhancing the recovery process. Before PBMAfter PBM 913911272 846653 9.26%5.81% Fig. 4. A decrease in anemia incidence after applying PBM indicates that the protocols are successfully preventing and managing anemia, ultimately leading to fewer transfusions, improved recovery, and better overall patient health outcomes Period Total patients Patients with anemia Anemia Incidence (%)

CONSORT CHART

Systolic Blood pressure/ Heart rate ≤1.0 Indicates shock Heart rate / Systolic Blood Pressure ≥0.9 Indicates Shock Each Positive response carries a response of 1 Systolic blood pressure- Diastolic blood pressure ≤25 mm Hg indicates shock Shock index: Pulse Pressure: Reverse Shock index: ABC score RABT score HR> 120/min SBP< 90 mmHg Penetrating mechanism Positive e-FAST Presence of pelvic fracture Shock Index >0.9 Penetrating mechanism Positive e-FAST

Shock Index: Cut point 0.9 Sensitivity (%) 86.84 Reverse Shock Index: Cut point Sensitivity (%) 48.96 0.98 Specificity(%) 73.68 Specificity (%) 36.03 PPV (%) 95.5 PPV (%) 10.65 NPV (%) 11.24 NPV (%) 96.89 Youden’s Index0.226 Youden’sIndex0.229 AUC 0.606 AUC 0.607 Metricscore1.23 Metricscore1.23

This box plot compares how haemoglobin levels change between patients receivingchemotherapy (Y) and those who are not (N). Important findings: - Average change for chemotherapy patients: +15.11 - Average change for non-chemotherapy patients: +18.17 - Both groups show positive responses to iron infusions - Non-chemotherapy patients show slightly better average improvement Graphs: The analysis evaluates whether the number of days post-iron infusion correlates withcurrent hemoglobin levels (HB NOW) using a scatter plot, regression line, and correlation coefficient. The results and visualizations are shown below. The correlation coefficient (0.278) suggests a weak positive relationship, and the summaryshows how HB NOW varies across time periods.The weak positive correlation (0.278) suggests that hemoglobin levels (HB NOW) slightlyincrease as the number of days post-iron infusion increases, but the relationship is not strong.This indicates other factors, such as individual patient conditions or treatment protocols, mayplay a more significant role in determining hemoglobin levels. The summary table furtherhighlights that hemoglobin levels tend to rise over time but with variability. Haemoglobin Change by Chemotherapy Status

Interpretation: While both groups benefit from iron infusions, non-chemotherapy patients show slightly better average improvement. This could be due to the additional physiological stress chemotherapy places on patients, which may limit their response to treatment.

Figure 2: Doppler ultrasound of both lower limbs showing no abnormalities. Figure 1: Fetal ultrasound showing an ongoing pregnancy with an 8-week fetus.

Figure 3: Computed tomography pulmonary angiography (CTPA) showing massivebilateral pulmonary embolism with right heart chamber dilation.

Figure 1. ROTEM results after 1000mL blood loss

Title: The Rational For Patient Blood Management In Septic Revision Arthroplasties Or LowerLimb Amputations – A Retrospective Analysis Of Anaemia Severity, Blood Loss And Transfusion Risk Table 1: Patient characteristics Age (Median) (N = 184)< 49 50-59 60-69 70-79 > 89Female Mean (sd) 10 (5%) 24 (13%) 49 (27%)69 (38%)32 (17%)79 (43%) 28.4 (6.4) 42 (23%) 45 (25%) 20 (11%) 15 (8%) 17 (9%) 69 (38%) 7 (4%) 130 (71%) 27 (15%) 58 (32%) 32 (17%) 41 (14%) 50 (27%) 69 (38%) 0 44 (24%) 121 (66%) 17 (9%) 2 (1%) Sex BMI Comorbidities AOMI Arrythmia Asthma AVC COPD Cardiopathy Cirrhosis Hypertension Alcohol consumption Chronic renal insufficiency Thromboembolic diseases Regular alcohol consumption Tobacco Diabetes 1 2 3 4 5 ASA Score Footnote: For patients undergoing different interventions at different time points during study period, either the average of the different values was taken (ex BMI, age) or were added (comorbidities) or the highest documented was reported (ASA). Alcohol consumption was based on preanesthetic evaluation (>2 units/day).

Table 2: Complications (N=257) Acute renal insufficiencyPneumoniaeThromboembolic eventsAcute Myocardial InfarctionAVC 39 (15%)12 (5%)17 (7%) 5(2%) 4(2%) Complications are reported per hospital stay.

Sex (being a woman)BMIASASurgery duration (h)Higher Hb preop [unit: 10g/l]Group (Hip vs. Knee)Group (Amputation vs. Knee)TXA [g]Blood loss [unit: 100ml]Acute renal insufficiencyPneumoniaeMyocardial infarctionStrokeThrombosis 1.25 (0.67 to 2.33; p=0.49)1.01 (0.96 to 1.06; p=0.81)2.76 (1.54 to 4.96; p=0.001)2.23 (1.46 to 3.41; p<0.001)0.61 (0.51 to 0.74; p<0.001) 7.48 (2.45 to 22.85; p<0.001) 1.50 (0.75 to 2.99; p=0.25) 2.61 (1.31 to 5.17; p=0.006) 1.19 (1.10 to 1.29; p<0.001) 1.70 (0.75 to 3.88; p=0.21) 2.61 (0.55 to 12.31; p=0.23) 2.02 (0.22 to 18.44; p=0.53) 4.63 (0.25 to 87.43; p=0.31) 2.28 (0.63 to 8.34; p=0.21) 2.60 (1.04 to 6.48; p=0.04)2.26 (1.07 to 4.76; p=0.03)0.43 (0.32 to 0.58; p<0.001) 5.45 (1.11 to 26.84; p=0.04) 0.75 (0.22 to 2.59; p=0.65) 2.30 (0.80 to 6.62; p=0.12) 1.20 (1.07 to 1.35; p=0.002) Table 3: Uni- and Multivariable logistic regression for transfusion risk Variable Odds Ratio (95% CI; p-value) - Univariate Odds Ratio (95% CI; p-value) - Multivariable

Table: Errors in Transfusion Center Celje in period from 2015 to 2024 *component required,number of units required, urgency of transfusion, contact number of ordering clinician Type of error/number of errorsPersonal data mismatch on sample and request formIncorrect data of patients AB0 on request formWrong Blood In TubeIncomplete data on request form*Error in patient data entry (detected before issuing report)Error in patient data entry (detected after issuing report)Error in ordering clinician data entry (detected before issuing report)Error in ordering clinician data entry (detected after issuing report)Wrong result on report (detected before issuing exam)Wrong result on report (detected after issuing exam)Total errors per yearNumber of erythrocyte units issued201533342724066401077310201642104251619105101326892201732150192115463011573162018252433917125710114372992019182526118131807116374972020241824715161752014674982021152408433111510001927329202223200842191651301917394202320373712213112201817185202410 year total1957 251233205152041161065044515447402525817 844231748305

Figure 1: The Sysmex DI-60 Digital Cell Morphology Analyser (Sysmex 2024). Figure 2: Extracted cell features subjected to ANN algorithms in order to find comparablepatterns between cell features on patient film and in stored database of cells,, allowingsubsequent cell pre-classification (Sysmex 2020).

Figure 5: Hyper-segmented neutrophils seen in a case of megaloblastic anaemia on theDI-60. All neutrophils can be seen on the screen simultaneously, allowing easyidentification of this abnormality (Gilmore and O’Brien 2022).

Figure 1. Change in SPC and Glyc markers from baseline by intervention group. The data is displayed as the mean change from baseline to each studytimepoint with error bars indicating the standard deviation. Timepoints where there is a significant difference between intervention groups (p<0.05) areindicated “*”. p < 0.05 * * * * * * * * * * * * * *

Figure 1. Haematological intention to treat analysis. Data displayed include haemoglobin concentration (Hb) (g/L) as mean ± standard deviation. Ferritin (µg/L),transferrin saturation (TSAT) (%) and C-reactive protein (CRP) (mg/L) are displayed as median ± interquartile range. * p < 0.05

Figure 1: Patient Inclusion and Exclusion Flow Diagram Anaemia severity classified as no anaemia (Hgb >12 g/dL in females, >13 g/dL in males), mildanaemia (Hb >11 and either <12 g/dL in women or <13 g/dL in men), moderate anaemia (Hb >8and <11 g/dL), or severe anaemia (<8 g/dL).

Table 1: Patient characteristics according to gender and anaemia category Age (Years)Non-Hispanic whiteCharlson ScoreASA PS; n=224,644 1-23-4+ Surgery type OrthopedicsUrology/GynecologyGeneral surgeryENT/OMSNeurosurgeryCardiac surgeryOtherThoracicPlasticColorectalSurgical oncologyTraumaVascularSpineEndocrine/metabolic Mennonanaemic(N=79088) 63 (53, 71) 72910 (92.2%) 4 (2, 5) 35314 (45.2%) 42805 (54.8%) 20159 (25.5%) 10751 (13.6%) 9554 (12.1%) 3731 (4.7%) 8948 (11.3%) 10209 (12.9%) 1651 (2.1%) 3666 (4.6%) 470 (0.6%) 2593 (3.3%) 1453 (1.8%) 1785 (2.3%) 2337 (3.0%) 1490 (1.9%) 291 (0.4%) Menanaemic (N=36136) 67 (57, 75) 32759 (90.7%) 6 (4, 8) 7346 (20.7%) 28162 (79.3%) 8348 (23.1%) 3277 (9.1%) 6073 (16.8%) 1630 (4.5%) 2319 (6.4%) 3877 (10.7%) 1501 (4.2%) 2288 (6.3%) 367 (1.0%) 1591 (4.4%) 1129 (3.1%) 1517 (4.2%) 1773 (4.9%) 344 (1.0%) 102 (0.3%) Womennonanaemic(N=77970) 61 (49, 71) 71701 (92.0%) 4 (2, 5) 42340 (55.0%) 34648 (45.0%) 22538 (28.9%) 13704 (17.6%) 9622 (12.3%) 2882 (3.7%) 7037 (9.0%) 5161 (6.6%) 1771 (2.3%) 3828 (4.9%) 1427 (1.8%) 2697 (3.5%) 2301 (3.0%) 1936 (2.5%) 1221 (1.6%) 1164 (1.5%) 681 (0.9%) Womenanaemic (N=34615) 62 (46, 73) 30428 (87.9%) 4 (2, 7) 11877 (34.9%) 22152 (65.1%) 8206 (23.7%) 6590 (19.0%) 5881 (17.0%) 1020 (2.9%) 1742 (5.0%) 2153 (6.2%) 1374 (4.0%) 1429 (4.1%) 594 (1.7%) 1517 (4.4%) 1294 (3.7%) 1401 (4.0%) 964 (2.8%) 280 (0.8%) 170 (0.5%) ASA PS, American Society of Anesthesiologists Physical Status. ENT/OMS, otolaryngology/oraland maxillofacial surgery.

Table 2: Clinical outcomes according to gender and anaemia category Ischemic eventPostop SSIAcute kidney injuryPeriop RBC transfusionPostoperative Length of StayReadmission (90-day)Mortality (12-month) Mennonanaemic(N=79088) 9160 (11.6%) 1869 (2.4%) 12135 (15.3%) 4796 (6.1%) 2 (1, 5) 9137 (11.6%) 2373 (3.0%) Menanaemic (N=36136) 6972 (19.3%) 2644 (7.3%) 9513 (26.3%) 11029 (30.5%) 4 (2, 8) 9197 (25.5%) 5245 (14.5%) Periop, perioperative; RBC, red blood cell; SSI, surgical site infection. Women nonanaemic (N=77970) 5152 (6.6%) 1548 (2.0%) 3609 (4.6%) 5744 (7.4%) 2 (1, 4) 8145 (10.4%) 2040 (2.6%) Womenanaemic (N=34615) 4646 (13.4%) 2384 (6.9%) 4907 (14.2%) 10507 (30.4%) 3 (2, 7) 7392 (21.4%) 3820 (11.0%) Total(N=227809) 25930 (11.4%) 8445 (3.7%) 30164 (13.2%) 32076 (14.1%) 3 (1, 5) 33871 (14.9%) 13478 (5.9%)

Table 3: Adjusted odds of clinical outcomes according to gender and severity of preoperative anaemia OutcomeAcute kidney injury Ischemic event Postop SSI Periop RBC transfusion Postoperative Length of Stay Readmission (90-day) Mortality (12-month) GenderWomenMenWomenMenWomenMenWomenMenWomenMenWomenMenWomenMen Mild 1.96 (1.84,2.09) 1.39 (1.33,1.44) 1.39 (1.30,1.48) 1.22 (1.17,1.28) 2.34 (2.13,2.56) 2.36 (2.19,2.55) 2.79 (2.65,2.94) 3.77 (3.59,3.96) 1.29 (1.28,1.30) 1.44 (1.43,1.45) 1.53 (1.46,1.61) 1.69 (1.62,1.76) 1.94 (1.79,2.10) 2.25 (2.11,2.39) Anaemia severity Moderate 3.26(3.08, 3.44) 1.97(1.88, 2.06) 1.97(1.87, 2.08) 1.64(1.56, 1.73) 4.15(3.85, 4.48) 3.84(3.55, 4.15) 7.42(7.09, 7.76) 13.5(12.8, 14.2) 1.77(1.76, 1.78) 2.01(2.00, 2.03) 2.12(2.03, 2.21) 2.36(2.25, 2.46) 3.68(3.45, 3.93) 4.09(3.84, 4.36) Severe 5.12(4.49, 5.83) 2.69(2.39, 3.01) 3.26(2.85, 3.73) 2.13(1.87, 2.42) 5.72(4.81, 6.80) 3.15(2.60, 3.83) 38.7(34.0, 44.1) 73.2(63.6, 84.5) 2.42(2.38, 2.46) 2.56(2.53, 2.60) 2.68(2.38, 3.02) 3.04(2.72, 3.40) 6.07(5.27, 7.00) 7.24(6.35, 8.25) Adjusted for age, race, Charlson score, ASA physical class, and surgery type.NR, not reported.

Figure 2: Adjusted odds of clinical outcomes according to gender and severity of preoperative anaemia Odds ratio reported with bars representing 95% confidence intervals.RBC, red blood cell; SSI, surgical site infection

TABLES Table 1. Baseline characteristics (n=86) 73 years (63-82) 71 (82.5%) 19 (22.1%) 30 (24-33) 32 (37.2%) 7 (8.1%) 23 (26.7%) 5 (5.8%) 34 (39.5%) 6 (6.9%) 4 (4.7%) (n=70) 69 years (61-82) 54 (77.1%) 17 (24.3%) 28 (24-31) 23 (31.9%) 0 18 (25%) 11(15.2%) 29 (40.2%) 6 (8.3%) 0 20.290.40 0.79 0.31 0.57 0.88 0.04 0.81 0.71 Demographic characteristicsMedian age (IQR)Males (%)Lifestyle factors Smoking BMI Health conditions HypertensionHigh cholesterolCKDCOPD IHD Stroke Cancer Anaemia No anaemia P Value Data are presented as n (%), P values in bold are statically significant. X test for categorical data, Mann-Whitney U test for non-parametric data. CKD, chronic kidney disease; COPD, chronicobstructive pulmonary disease; IHD, ischaemic heart disease. Data are presented as n (%), P values in bold are statically significant. X2 test for categoricaldata, Mann-Whitney U test for non-parametric data. CKD, chronic kidney disease; COPD,chronic obstructive pulmonary disease; IHD, ischaemic heart disease.

Major amputation Minor amputation DFU related admission DFU related re-admission Ulcer healed in 12 months 12 month all cause mortality All cause hospital admission Revision of major amputation Revision of minor amputation 12 monthDFU-related mortality Table 2. Diabetic foot ulcer-related outcomes Anaemia(n=86)59 (68.6%) No anaemia(n=70)31 (44.3%) P value 0.002 0 2 (2.3%) 4 (4.7%) 1 (1.2%) 34 (39.5%) 13 (15.1%) 15 (17.4%) 11 (12.8%) 20 (23.2%) 0 4 (5.7%) 1 (1.4%) 2 (2.9%) 4 (5.7%) 14 (20%) 9 (12.9%) 9 (12.9%) 20 (28.6%) 0.21 0.49 0.29 0.39 0.54 0.14 0.10

Table 1. Intergroup differences between treatment and control groups. Variable Male sex [n,%] Age, Me (IQR) [years] Body mass index, Me (IQR) [kg m-2] Study period, Me (IQR) [days] ICU mortality [n,%] SAPS II, Me (IQR) [points] APACHE II, Me (IQR) [points] SOFA, Me (IQR) [points] Daily blood loss, Me (IQR) [mL] Ferritin, Me (IQR) [ng mL-1] Iron, Me (IQR) [µg dL-1] Transferrin, Me (IQR) [mg dL-1] Transferrin saturation, Me (IQR) [%] Interleukin-6, Me (IQR) [pg mL-1] Procalcitonin, Me (IQR) [ng mL-1] C-reactive protein, Me (IQR) [mg L-1] Hb (baseline), Me (IQR) [g L-1] RET-He (baseline), Me (IQR) [pg] Hb change in the 1st week [g L-1] Hb change during study period [g L-1] Treatment group (n=6) 2 (33.3) 46.5 (40.0–58.0) 30.2 (24.8–31.2) 9 (8–11) 1 (16.7) 39.0 (26.0–43.0) 12.0 (7.0–17.0) 6.5 (5.0–7.0) 7.6 (3.9–8.0) 260.5 (137.0–609.0) 14.0 (9.7–21.2) 154.5 (144.0–158.0) 6.0 (5.0–10.0) 70.4 (34.1–126.0) 0.8 (0.5–3.1) 261.5 (164.0–320.0) 95 (89–107) 28.6 (26.7–30.4) 14 (13–16) 15 (4–16) Placebo group (n=6) 2 (33.3) 67.5 (59.0–68.0) 24.3 (21.2–27.7) 6.5 (5.0–8.0) 1 (16.7) 37.7 (32.0–45.0) 15.5 (10.0–17.0) 6.5 (5.0–7.0) 3.6 (3.3–6.4) 672.4 (495.9–765.0) 17.2 (12.4–31.2) 120.5 (97.4–168.0) 10.0 (6.0–14.0) 225 (31.6–628.0) 1.1 (0.1–4.5) 190.5 (94.6–349.0) 108 (88–110) 32.9 (29.4–34.3) 0 (-8–8) -5 (-8–5) P-value 1.00 0.08 0.26 0.05 1.00 0.91 0.73 0.87 0.48 0.09 0.59 0.70 0.29 0.59 0.94 0.59 0.48 0.18 0.09 0.02 APACHE–Acute Physiology and Chronic Health Evaluation II, Hb–hemoglobin concentration, ICU–intensive care unit, IQR–interquartile range, Me–median value, RET-He–reticulocyte hemoglobin equivalent, SAPS–Simplified Acute Physiology Score II, SOFA–Sequential Organ Failure Assessment In bold statistically significant differences

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