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A predictive model for massive transfusion in combat casualty patients.
J Trauma. 2008 Feb; 64(2 Suppl):S57-63; discussion S63.JT

Abstract

BACKGROUND

Massive transfusion (MT) is associated with increased morbidity and mortality in severely injured patients. Early and aggressive use of blood products in these patients may correct coagulopathy, control bleeding, and improve outcomes. However, rapid identification of patients at risk for MT has been difficult. We postulated that evaluation of clinical variables routinely assessed upon admission would allow identification of these patients for earlier, more effective intervention.

METHODS

A retrospective cohort study was conducted at a single combat support hospital to identify risk factors for MT in patients with traumatic injuries. Demographic, diagnostic, and laboratory variables obtained upon admission were evaluated. Univariate and multivariate analyses were performed. An algorithm was formulated, validated with an independent dataset and a simple scoring system was devised.

RESULTS

Three thousand four hundred forty-two patient records were reviewed. At least one unit of blood was transfused to 680 patients at the combat support hospital. Exclusion criteria included age less than 18 years, transfer from another medical facility, designation as a security internee, or incomplete data fields. The final number of patients was 302, of whom 26.5% (80 of 302) received a MT. Patients with MT had higher mortality (29 vs. 7% [p < 0.001]), and an increased Injury Severity Score (25 +/- 11.1 vs. 18 +/- 16.2 [p < 0.001]). Four independent risk factors for MT were identified: heart rate >105 bpm, systolic blood pressure <110 mm Hg, pH <7.25, and hematocrit <32.0%. An algorithm was created to analyze the risk of MT (area under the curve [AUC] = 0.839). In an independent data set of 396 patients the ability to accurately identify those requiring MT was 66% (AUC = 0.747).

CONCLUSIONS

Independent predictors for MT were identified in a cohort of severely injured patients requiring transfusions. Patients requiring a MT can be identified with variables commonly obtained upon hospital admission.

Authors+Show Affiliations

United States Institute of Surgical Research, Fort Sam Houston, TX 78234, USA. daniel.mclaughlin@amedd.army.milNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article

Language

eng

PubMed ID

18376173

Citation

McLaughlin, Daniel F., et al. "A Predictive Model for Massive Transfusion in Combat Casualty Patients." The Journal of Trauma, vol. 64, no. 2 Suppl, 2008, pp. S57-63; discussion S63.
McLaughlin DF, Niles SE, Salinas J, et al. A predictive model for massive transfusion in combat casualty patients. J Trauma. 2008;64(2 Suppl):S57-63; discussion S63.
McLaughlin, D. F., Niles, S. E., Salinas, J., Perkins, J. G., Cox, E. D., Wade, C. E., & Holcomb, J. B. (2008). A predictive model for massive transfusion in combat casualty patients. The Journal of Trauma, 64(2 Suppl), S57-63; discussion S63. https://doi.org/10.1097/TA.0b013e318160a566
McLaughlin DF, et al. A Predictive Model for Massive Transfusion in Combat Casualty Patients. J Trauma. 2008;64(2 Suppl):S57-63; discussion S63. PubMed PMID: 18376173.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A predictive model for massive transfusion in combat casualty patients. AU - McLaughlin,Daniel F, AU - Niles,Sarah E, AU - Salinas,Jose, AU - Perkins,Jeremy G, AU - Cox,E Darrin, AU - Wade,Charles E, AU - Holcomb,John B, PY - 2008/4/11/pubmed PY - 2008/5/15/medline PY - 2008/4/11/entrez SP - S57-63; discussion S63 JF - The Journal of trauma JO - J Trauma VL - 64 IS - 2 Suppl N2 - BACKGROUND: Massive transfusion (MT) is associated with increased morbidity and mortality in severely injured patients. Early and aggressive use of blood products in these patients may correct coagulopathy, control bleeding, and improve outcomes. However, rapid identification of patients at risk for MT has been difficult. We postulated that evaluation of clinical variables routinely assessed upon admission would allow identification of these patients for earlier, more effective intervention. METHODS: A retrospective cohort study was conducted at a single combat support hospital to identify risk factors for MT in patients with traumatic injuries. Demographic, diagnostic, and laboratory variables obtained upon admission were evaluated. Univariate and multivariate analyses were performed. An algorithm was formulated, validated with an independent dataset and a simple scoring system was devised. RESULTS: Three thousand four hundred forty-two patient records were reviewed. At least one unit of blood was transfused to 680 patients at the combat support hospital. Exclusion criteria included age less than 18 years, transfer from another medical facility, designation as a security internee, or incomplete data fields. The final number of patients was 302, of whom 26.5% (80 of 302) received a MT. Patients with MT had higher mortality (29 vs. 7% [p < 0.001]), and an increased Injury Severity Score (25 +/- 11.1 vs. 18 +/- 16.2 [p < 0.001]). Four independent risk factors for MT were identified: heart rate >105 bpm, systolic blood pressure <110 mm Hg, pH <7.25, and hematocrit <32.0%. An algorithm was created to analyze the risk of MT (area under the curve [AUC] = 0.839). In an independent data set of 396 patients the ability to accurately identify those requiring MT was 66% (AUC = 0.747). CONCLUSIONS: Independent predictors for MT were identified in a cohort of severely injured patients requiring transfusions. Patients requiring a MT can be identified with variables commonly obtained upon hospital admission. SN - 1529-8809 UR - https://www.unboundmedicine.com/medline/citation/18376173/A_predictive_model_for_massive_transfusion_in_combat_casualty_patients_ L2 - https://doi.org/10.1097/TA.0b013e318160a566 DB - PRIME DP - Unbound Medicine ER -