Clinical gestalt and the prediction of massive transfusion after trauma

MPH on behalf of the PROMMTT Study Group

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

Introduction Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesised that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. Methods Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centres in patients who survived ≥30 min after admission and received ≥1 unit of RBC within 6 h of arrival. Subjects who received ≥10 units within 24 h of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question "Is the patient likely to be massively transfused?" 10 min after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. Results Of the 1245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all p <0.05). Gestalt sensitivity was 65.6% and specificity was 63.8%. PPV and NPV were 34.9% and 86.2% respectively. Conclusion Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier.

Original languageEnglish (US)
Pages (from-to)807-813
Number of pages7
JournalInjury
Volume46
Issue number5
DOIs
StatePublished - 2015

Fingerprint

Wounds and Injuries
Mortality
Blood Pressure
Injury Severity Score
Trauma Centers
Chi-Square Distribution
ROC Curve
Multicenter Studies
Heart Rate
Therapeutics

Keywords

  • Gestalt
  • Massive transfusion
  • Trauma

ASJC Scopus subject areas

  • Emergency Medicine
  • Orthopedics and Sports Medicine

Cite this

Clinical gestalt and the prediction of massive transfusion after trauma. / MPH on behalf of the PROMMTT Study Group.

In: Injury, Vol. 46, No. 5, 2015, p. 807-813.

Research output: Contribution to journalArticle

MPH on behalf of the PROMMTT Study Group 2015, 'Clinical gestalt and the prediction of massive transfusion after trauma', Injury, vol. 46, no. 5, pp. 807-813. https://doi.org/10.1016/j.injury.2014.12.026
MPH on behalf of the PROMMTT Study Group. / Clinical gestalt and the prediction of massive transfusion after trauma. In: Injury. 2015 ; Vol. 46, No. 5. pp. 807-813.
@article{0cbe449114d747adb98e712ad1012153,
title = "Clinical gestalt and the prediction of massive transfusion after trauma",
abstract = "Introduction Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesised that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. Methods Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centres in patients who survived ≥30 min after admission and received ≥1 unit of RBC within 6 h of arrival. Subjects who received ≥10 units within 24 h of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question {"}Is the patient likely to be massively transfused?{"} 10 min after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. Results Of the 1245 patients enrolled, 966 met inclusion criteria and 221 (23{\%}) patients received MT. 415 (43{\%}) were predicted to have a MT and 551(57{\%}) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all p <0.05). Gestalt sensitivity was 65.6{\%} and specificity was 63.8{\%}. PPV and NPV were 34.9{\%} and 86.2{\%} respectively. Conclusion Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier.",
keywords = "Gestalt, Massive transfusion, Trauma",
author = "{MPH on behalf of the PROMMTT Study Group} and Pommerening, {Matthew J.} and Goodman, {Michael D.} and Holcomb, {John B.} and Wade, {Charles E.} and Fox, {Erin E.} and {Del Junco}, {Deborah J.} and Brasel, {Karen J.} and Bulger, {Eileen M.} and Cohen, {Mitch J.} and Alarcon, {Louis H.} and Schreiber, {Martin A.} and Myers, {John G} and Phelan, {Herb A.} and Peter Muskat and Mohammad Rahbar and Cotton, {Bryan A.}",
year = "2015",
doi = "10.1016/j.injury.2014.12.026",
language = "English (US)",
volume = "46",
pages = "807--813",
journal = "Injury",
issn = "0020-1383",
publisher = "Elsevier Limited",
number = "5",

}

TY - JOUR

T1 - Clinical gestalt and the prediction of massive transfusion after trauma

AU - MPH on behalf of the PROMMTT Study Group

AU - Pommerening, Matthew J.

AU - Goodman, Michael D.

AU - Holcomb, John B.

AU - Wade, Charles E.

AU - Fox, Erin E.

AU - Del Junco, Deborah J.

AU - Brasel, Karen J.

AU - Bulger, Eileen M.

AU - Cohen, Mitch J.

AU - Alarcon, Louis H.

AU - Schreiber, Martin A.

AU - Myers, John G

AU - Phelan, Herb A.

AU - Muskat, Peter

AU - Rahbar, Mohammad

AU - Cotton, Bryan A.

PY - 2015

Y1 - 2015

N2 - Introduction Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesised that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. Methods Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centres in patients who survived ≥30 min after admission and received ≥1 unit of RBC within 6 h of arrival. Subjects who received ≥10 units within 24 h of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question "Is the patient likely to be massively transfused?" 10 min after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. Results Of the 1245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all p <0.05). Gestalt sensitivity was 65.6% and specificity was 63.8%. PPV and NPV were 34.9% and 86.2% respectively. Conclusion Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier.

AB - Introduction Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesised that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. Methods Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centres in patients who survived ≥30 min after admission and received ≥1 unit of RBC within 6 h of arrival. Subjects who received ≥10 units within 24 h of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question "Is the patient likely to be massively transfused?" 10 min after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. Results Of the 1245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all p <0.05). Gestalt sensitivity was 65.6% and specificity was 63.8%. PPV and NPV were 34.9% and 86.2% respectively. Conclusion Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier.

KW - Gestalt

KW - Massive transfusion

KW - Trauma

UR - http://www.scopus.com/inward/record.url?scp=84944061942&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84944061942&partnerID=8YFLogxK

U2 - 10.1016/j.injury.2014.12.026

DO - 10.1016/j.injury.2014.12.026

M3 - Article

VL - 46

SP - 807

EP - 813

JO - Injury

JF - Injury

SN - 0020-1383

IS - 5

ER -