Comparison of massive and emergency transfusion prediction scoring systems after trauma with a new Bleeding Risk Index score applied in-flight. Issue 2 (February 2021)

• Record Type: Journal Article
• Authors: Yang, Shiming; Mackenzie, Colin F.; Rock, Peter; Lin, Chienyu; Floccare, Doug; Scalea, Thomas; Stumpf, Florian; Winans, Christopher; Galvagno, Samuel; Miller, Catriona; Stein, Deborah; Hu, Peter F.
• Is Part Of: Journal of trauma and acute care surgery. Volume 90:Issue 2(2021)
• Publication Date: 2021-02
• Subjects: Autonomous prediction of transfusion -- vital signs signal analysis -- trauma patient triage -- machine learning -- in-flight prediction algorithms; Surgical intensive care -- Periodicals; Surgical emergencies -- Periodicals; Wounds and injuries -- Surgery -- Periodicals; 617.026
• DOI: 10.1097/TA.0000000000003031
• Languages: English
• ISSNs: 2163-0755

Abstract

Abstract : BACKGROUND: Assessment of blood consumption (ABC), shock index (SI), and Revised Trauma Score (RTS) are used to estimate the need for blood transfusion and triage. We compared Bleeding Risk Index (BRI) score calculated with trauma patient noninvasive vital signs and hypothesized that prehospital BRI has better performance compared with ABC, RTS, and SI for predicting the need for emergent and massive transfusion (MT). METHODS: We analyzed 2-year in-flight data from adult trauma patients transported directly to a Level I trauma center via helicopter. The BRI scores 0 to 1 were derived from continuous features of photoplethymographic and electrocardiographic waveforms, oximetry values, blood pressure trends. The ABC, RTS, and SI were calculated using admission data. The area under the receiver operating characteristic curve (AUROC) with 95% confidence interval (CI) was calculated for predictions of critical administration threshold (CAT, ≥3 units of blood in the first hour) or MT (≥10 units of blood in the first 24 hours). DeLong's method was used to compare AUROCs for different scoring systems. p < 0.05 was considered statistically significant. RESULTS: Among 1, 396 patients, age was 46.5 ± 20.1 years (SD), 67.1% were male. The MT rate was 3.2% and CAT was 7.6%, most (92.8%) were blunt injury. Mortality was 6.6%. Scene arrival to hospital time was 35.3 ± (10.5) minutes. The BRI prediction of MT with AUROC 0.92 (95% CI, 0.89–0.95) was significantly better than ABC, SI, or RTS (AUROCs = 0.80, 0.83, 0.78, respectively; 95% CIs 0.73–0.87, 0.76–0.90, 0.71–0.85, respectively). The BRI prediction of CAT had an AUROC of 0.91 (95% CI, 0.86–0.94), which was significantly better than ABC (AUROC, 077; 95% CI, 0.73–0.82) or RTS (AUROC, 0.79; 95% CI, 0.74–0.83) and better than SI (AUROC, 0.85; 95% CI, 0.80–0.89). The BRI score threshold for optimal prediction of CAT was 0.25 and for MT was 0.28. CONCLUSION: The autonomous continuous noninvasive patient vital signs–based BRI score performs better than ABC, RTS, and SI predictions of MT and CAT. Bleeding Risk Index does not require additional data entry or expert interpretation. LEVEL OF EVIDENCE: Prognostic test, level III. Abstract : Supplemental digital content is available in the text.