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Hemorrhagic shock in intensive care: Variation in blood product administration during resuscitation

Reuland, Merijn C., Raasveld, Senta Jorinde, Dongelmans, Dave A., Elbers, Paul W. G., Müller, Marcella C. A., Vlaar, Alexander P. J.·2026·Vox Sanguinis

Abstract

Background and Objectives: Hemorrhagic shock requires timely resuscitation to maintain organ perfusion and hemostasis until source control is achieved. Most resuscitation strategies have been studied outside the intensive care unit (ICU), and optimal approaches in critically ill patients remain unclear. With this study, we aim to characterize variation in resuscitation practices for hemorrhagic shock with (near‐)massive transfusion across public ICU datasets. Materials and Methods: Red blood cell (RBC) transfusions were extracted from four public ICU datasets (AmsterdamUMCdb, HiRID, MIMIC‐IV, and SICdb). Transfusions were stratified by 24‐h intensity: near‐massive (6–10 RBC units) and massive (≥10 units). Clinical parameters from 48 h before and after transfusion were analyzed. Continuous variables were compared using Kruskal–Wallis tests, with Dunn's post hoc tests and Bonferroni correction. Results: In near‐massive transfusion, median nadir hemoglobin differed across datasets: AmsterdamUMCdb 6.6 g/dL (interquartile range [IQR], 5.6–7.7), HiRID 6.8 (6.1–7.3), MIMIC‐IV 7.2 (6.2–8.0), and SICdb 6.2 (5.5–6.7) ( p < 0.001). In massive transfusion, nadir hemoglobin was 6.4 (5.6–7.1), 6.9 (6.3–7.3), 7.1 (6.0–8.1), and 5.3 (4.3–6.3), respectively ( p < 0.001). Post‐resuscitation hemoglobin also differed: 9.5 (8.7–10.3), 9.1 (8.4–9.6), 10.4 (9.4–11.6), and 7.7 (6.9–8.5) ( p < 0.001). Crystalloid use varied widely (3350–12,865 mL, p < 0.001), as did the mean arterial pressure at transfusion (60–76 mmHg, p < 0.001). Conclusion: Resuscitation practices vary substantially across ICU datasets, including differences in hemoglobin levels, fluid administration, and hemodynamic status at transfusion. These findings highlight the heterogeneity of real‐world resuscitation strategies in hemorrhagic shock.

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Research works printed but not linked: 36

  1. Cannon JW, 2018, Hemorrhagic shock, N Engl J Med, 370, 370, 10.1056/NEJMra1705649 · DOI
  2. Vlaar APJ, 2021, Transfusion strategies in bleeding critically ill adults: a clinical practice guideline from the European Society of Intensive Care Medicine, Intensive Care Med, 47, 1368, 10.1007/s00134-021-06531-x · DOI
  3. Raasveld SJ, 2023, Red blood cell transfusion in the intensive care unit, JAMA, 329, 1852, 10.1001/jama.2023.20737 · DOI
  4. Shafi S, 2016, Bundles of care for resuscitation from hemorrhagic shock and severe brain injury in trauma patients—translating knowledge into practice, J Trauma Acute Care Surg, 81, 780, 10.1097/TA.0000000000001161 · DOI
  5. Tran A, 2018, Permissive hypotension versus conventional resuscitation strategies in adult trauma patients with hemorrhagic shock: a systematic review and meta‐analysis of randomized controlled trials, J Trauma Acute Care Surg, 85, 802, 10.1097/TA.0000000000001816 · DOI
  6. Holcomb JB, 2013, The prospective, observational, multicenter, major trauma transfusion (PROMMTT) study, JAMA Surg, 148, 127, 10.1001/2013.jamasurg.387 · DOI · Paper page
  7. Chen S, 2026, Nationwide expert survey on transfusion and coagulation management strategies for bleeding critically ill patients in China, J Crit Care, 92, 10.1016/j.jcrc.2025.155352 · DOI
  8. Maynard S, 2024, Machine learning in transfusion medicine: a scoping review, Transfusion, 64, 162, 10.1111/trf.17582 · DOI
  9. Haeren MMT, 2024, Plasma transfusion in the intensive care unit, Transfusion, 65, 73, 10.1111/trf.18071 · DOI
  10. Rockenschaub P, 2024, The impact of multi‐institution datasets on the generalizability of machine learning prediction models in the ICU, Crit Care Med, 52, 1710, 10.1097/CCM.0000000000006359 · DOI
  11. Reuland MC, 2025, Pitfalls and paradoxes: blood transfusion in 5 public ICU databases, Crit Care, 29, 503, 10.1186/s13054-025-05737-5 · DOI
  12. Bennett N, 2022, ricu: R's interface to intensive care data, Gigascience, 11, 10.1093/gigascience/giad041 · DOI
  13. R Core Team, 2023, R: a language and environment for statistical computing
  14. Elm E, 2007, The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies, Lancet, 370, 1453, 10.1016/S0140-6736(07)61602-X · DOI · Paper page
  15. Arnold DM, 2007, Bleeding during critical illness: a prospective cohort study using a new measurement tool, Clin Invest Med, 30, E93, 10.25011/cim.v30i2.985 · DOI
  16. Balitsky AK, 2021, Exploring the components of bleeding outcomes in transfusion trials for patients with hematologic malignancy, Transfusion, 61, 286, 10.1111/trf.16126 · DOI
  17. McQuilten ZK, 2015, Transfusion interventions in critical bleeding requiring massive transfusion: a systematic review, Transfus Med Rev, 29, 127, 10.1016/j.tmrv.2015.01.001 · DOI
  18. Lin YM, 2024, Calculation methods for intraoperative blood loss: a literature review, BMC Surg, 24, 394, 10.1186/s12893-024-02699-3 · DOI
  19. Agnihotri N, 2014, The need to label red blood cell units with their haemoglobin content: a single centre study on haemoglobin variations due to donor‐related factors, Blood Transfus, 12, 520
  20. Jain R, 2022, Assessment of hemoglobin content of packed red cells, Glob J Transfus Med, 7, 36, 10.4103/gjtm.gjtm_56_21 · DOI
  21. Wonderen SF, 2025, Platelet transfusion practices in the ICU: a prospective multicenter cohort study, Crit Care Med, 53, e2526, 10.1097/CCM.0000000000006880 · DOI
  22. Vincent JL, 2018, Worldwide audit of blood transfusion practice in critically ill patients, Crit Care, 22, 10.1186/s13054-018-2018-9 · DOI
  23. Downs JW, 1958, The problem of overtransfusion in massive hemorrhage, Ann Surg, 147, 73, 10.1097/00000658-195807000-00008 · DOI
  24. Barmparas G, 2022, Overtransfusion of packed red blood cells during massive transfusion activation: a potential quality metric for trauma resuscitation, Trauma Surg Acute Care Open, 7, 10.1136/tsaco-2022-000896 · DOI
  25. Villanueva C, 2013, Transfusion strategies for acute upper gastrointestinal bleeding, N Engl J Med, 368, 11, 10.1056/NEJMoa1211801 · DOI · Paper page
  26. Schaap CM, 2025, Ultrarestrictive transfusion thresholds in critically ill adults: are we ready for the next step?, Transfus Med Rev, 39, 10.1016/j.tmrv.2025.150893 · DOI
  27. Beni CE, 2021, Acute intensive care unit resuscitation of severely injured trauma patients: do we need a new strategy?, J Trauma Acute Care Surg, 91, 1010, 10.1097/TA.0000000000003373 · DOI
  28. The National Heart, Lung, and Blood Institute Prevention and Early Treatment of Acute Lung Injury Clinical Trials Network, 2023, Early restrictive or liberal fluid management for sepsis‐induced hypotension, N Engl J Med, 388, 499, 10.1056/NEJMoa2212663 · DOI · Paper page
  29. Miller TE, 2016, Fluid resuscitation practice patterns in intensive care units of the USA: a cross‐sectional survey of critical care physicians, Perioper Med, 5, 15, 10.1186/s13741-016-0035-2 · DOI
  30. Pusateri AE, 2020, Association of prehospital plasma transfusion with survival in trauma patients with hemorrhagic shock when transport times are longer than 20 minutes: a post hoc analysis of the PAMPer and COMBAT clinical trials, JAMA Surg, 155, 10.1001/jamasurg.2019.5085 · DOI
  31. Reed CR, 2025, Hemostatic abnormalities after trauma resuscitation: challenges and strategies in caring for the critically injured patient, Ann Intensive Care, 15, 163, 10.1186/s13613-025-01587-0 · DOI
  32. Holcomb JB, 2015, Transfusion of plasma, platelets, and red blood cells in a 1:1:1 vs a 1:1:2 ratio and mortality in patients with severe trauma: the PROPPR randomized clinical trial, JAMA, 313, 471, 10.1001/jama.2015.12 · DOI
  33. Halmin M, 2013, Effect of plasma‐to‐RBC ratios in trauma patients, Crit Care Med, 41, 1905, 10.1097/CCM.0b013e31828a3214 · DOI
  34. Mesar T, 2017, Association between ratio of fresh frozen plasma to red blood cells during massive transfusion and survival among patients without traumatic injury, JAMA Surg, 152, 574, 10.1001/jamasurg.2017.0098 · DOI
  35. Reuland MC, 2025, Restrictive RBC transfusion in the ICU: trends in clinical adherence, Transfus Clin Biol, 32, 309, 10.1016/j.tracli.2025.04.003 · DOI
  36. Hernán MA, 2022, Target trial emulation: a framework for causal inference from observational data, JAMA, 328, 2446, 10.1001/jama.2022.21383 · DOI

Metadata

Authors
Reuland, M. C., Raasveld, S. J., Dongelmans, D. A., Elbers, P. W. G., Müller, M. C. A., & Vlaar, A. P. J.
Venue
Vox Sanguinis
Publisher
Wiley
Published
2026-09-23
ISSN
  • 0042-9007
  • 1423-0410
Cited by
0
References
1
Language
en
Licence

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