COMPARISON OF CONTINUOUS VITAL SIGNS DATA ANALYSIS VERSUS VENOUS LACTATE FOR THE PREDICTION OF LIFESAVING INTERVENTIONS IN PATIENTS WITH TRAUMATIC SHOCK.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος:	COMPARISON OF CONTINUOUS VITAL SIGNS DATA ANALYSIS VERSUS VENOUS LACTATE FOR THE PREDICTION OF LIFESAVING INTERVENTIONS IN PATIENTS WITH TRAUMATIC SHOCK.
Συγγραφείς:	Yang S, Hu P, Teeter W; Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland., Floccare DJ, Hu H; Department of Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland., Galvagno SM Jr; Department of Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland.
Πηγή:	Shock (Augusta, Ga.) [Shock] 2025 Jan 01; Vol. 63 (1), pp. 64-71. Date of Electronic Publication: 2024 Oct 21.
Τύπος έκδοσης:	Journal Article; Comparative Study
Γλώσσα:	English
Στοιχεία περιοδικού:	Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 9421564 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1540-0514 (Electronic) Linking ISSN: 10732322 NLM ISO Abbreviation: Shock Subsets: MEDLINE
Imprint Name(s):	Publication: 2002- : Philadelphia : Lippincott Williams & Wilkins Original Publication: Augusta, GA : BioMedical Press, [1994-
Ιατρικοί όροι (MeSH):	Lactic Acid/blood , Shock, Traumatic/blood , Shock, Traumatic/therapy , Vital Signs, Humans ; Male ; Female ; Adult ; Middle Aged ; Prospective Studies ; Emergency Medical Services ; Predictive Value of Tests
Περίληψη:	Abstract: Introduction: The prehospital environment is fraught with operational constraints, making it difficult to assess the need for resources such as lifesaving interventions (LSI) for adults with traumatic injuries. While invasive methods such as lactate have been found to be highly predictive for estimating injury severity and resource requirements, noninvasive methods, to include continuous vital signs ( VS ), have the potential to provide prognostic information that can be quickly acquired, interpreted, and incorporated into decision making. In this work, we hypothesized that an analysis of continuous VS would have predictive capacity comparable to lactate and other laboratory tests for the prediction of injury severity, need for LSIs and intensive care unit admission. Methods: In this preplanned secondary analysis of 300 prospectively enrolled patients, venous blood samples were collected in the prehospital environment aboard a helicopter and analyzed with a portable lab device. Patients were transported to the primary adult resource center for trauma in the state of Maryland. Continuous VS were simultaneously collected. Descriptive statistics were used to describe the cohort and predictive models were constructed using a regularized gradient boosting framework with 10-fold cross-validation with additional analyses using Shapley additive explanations (SHAP). Results: Complete VS and laboratory data from 166 patients were available for analysis. The continuous VS models had better performance for prediction of receiving LSIs and intensive care unit length of stay compared to single (initial) VS measurements. The continuous VS models had comparable performance to models using only laboratory tests in predicting discharge within 24 h (continuous VS model: area under the receiver operating curve [AUROC] 0.71; 95% CI, 0.68-0.75 vs. lactate model: AUROC, 0.65; 95% CI, 0.68; 95% CI, 0.66-0.71). The model using all laboratory data yielded the highest sensitivity and sensitivity (AUROC, 0.77; 95% CI, 0.74-0.81). Discussion: The results from this study suggest that continuous VS obtained from autonomous monitors in an aeromedical environment may be helpful for predicting LSIs and the critical care requirements for traumatically injured adults. The collection and use of noninvasively obtained physiological data during the early stages of prehospital care may be useful for in developing user-friendly early warning systems for identifying potentially unstable trauma patients. (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Shock Society.)
Competing Interests:	The authors report no conflicts of interest.
References:	Shackelford S, Yang S, Hu P, et al. Predicting blood transfusion using automated analysis of pulse oximetry signals and laboratory values. J Trauma Acute Care Surg . 2015;79(4 suppl 2):S175–S180. Hu P, Galvagno SM Jr., Sen A, et al. Identification of dynamic prehospital changes with continuous vital signs acquisition. Air Med J . 2014;33(1):27–33. Brown JB, Lerner EB, Sperry JL, et al. Prehospital lactate improves accuracy of prehospital criteria for designating trauma activation level. J Trauma Acute Care Surg . 2016;81(3):445–452. Guyette F, Suffoletto B, Castillo JL, et al. Prehospital serum lactate as a predictor of outcomes in trauma patients: a retrospective observational study. J Trauma . 2011;70(4):782–786. Galvagno SM Jr., Sikorski RA, Floccare DJ, et al. Prehospital point of care testing for the early detection of shock and prediction of lifesaving interventions. Shock . 2020;54(6):710–716. Guyette FX, Meier EN, Newgard C, et al. A comparison of prehospital lactate and systolic blood pressure for predicting the need for resuscitative care in trauma transported by ground. J Trauma Acute Care Surg . 2015;78(3):600–606. Zadorozny EV, Weigel T, Stone A, et al. Prehospital lactate is associated with the need for blood in trauma. Prehosp Emerg Care . 2022;26(4):590–599. Kahraman S, Dutton RP, Hu P, et al. Automated measurement of “pressure times time dose” of intracranial hypertension best predicts outcome after severe traumatic brain injury. J Trauma Acute Care Surg . 2010;69(1):110–118. Garcia D. Robust smoothing of gridded data in one and higher dimensions with missing values. Comput Stat Data Anal . 2010;54(4):1167–1178. Vila J, Palacios F, Presedo J, et al. Time-frequency analysis of heart-rate variability. IEEE Eng Med Biol Mag . 1997;16(5):119–126. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation . 1996;93(5):1043–1065. Ryan ML, Ogilvie MP, Pereira BMT, et al. Heart rate variability is an independent predictor of morbidity and mortality in hemodynamically stable trauma patients. J Trauma . 2011;70(6):1371–1380. Norris PR, Morris JA Jr., Ozdas A, et al. Heart rate variability predicts trauma patient outcome as early as 12 h: implications for military and civilian triage. J Surg Res . 2005;129(1):122–128. Liu NT, Holcomb JB, Wade CE, et al. Utility of vital signs, heart rate variability and complexity, and machine learning for identifying the need for lifesaving interventions in trauma patients. Shock . 2014;42(2):108–114. Baker SP, O'Neill B, Haddon W Jr., et al. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma . 1974;14(3):187–196. Chen T, Guestrin C. Xgboost: A scalable tree boosting system. In Proceedings of the 22nd ACM Sigkdd International Conference on Knowledge Discovery and Data Mining 2016 (pp. 785–794). Lundberg SM, Lee SI. A unified approach to interepreting model predictions 2017. Pedregosa F, Varoquaux G, Gramfort A, et al. Scikit-learn: machine learning in Python. LMLR . 2011;12(85):2825–2830. Available at: https://jmlr.csail.mit.edu/papers/v12/pedregosa11a.html . Accessed April 25, 2024 from. Galvagno SM Jr., Sikorski R, Hirshon JM, et al. Helicopter emergency medical services for adults with major trauma. Cochrane Database Syst Rev . 2015;2015(12):CD009228. Galvagno SM Jr., Haut ER, Zafar SN, et al. Association between helicopter vs ground emergency medical services and survival for adults with major trauma [published correction appears in JAMA . 2022 Jul 5;328(1):79]. JAMA . 2012;307(15):1602–1610. Owens BD, Kragh JF Jr., Wenke JC, et al. Combat wounds in operation Iraqi Freedom and Operation Enduring Freedom. J Trauma . 2008;64:295–299. Potter D, Kehoe A, Smith JE. The sensitivity of pre-hospital and in-hospital tools for the identification of major trauma patients presenting to a major trauma centre. J R Nav Med Serv . 2013;99(1):16–19. Eastridge BJ, Butler F, Wade CE, et al. Field triage score (FTS) in battlefield casualties: validation of a novel triage technique in a combat environment. Am J Surg . 2010;200(6):724–727, discussion 727. Bellamy RF. The causes of death in conventional land warfare: implications for combat casualty care research. Mil Med . 1984;149:55–62. Eastridge BJ, Mabry RL, Seguin P, et al. Death on the battlefield (2001-2011): implications for the future of combat casualty care. J Trauma Acute Care Surg . 2012;73(6 Suppl 5):S431–S437. Kelly JF, Ritenour AE, McLaughlin DF, et al. Injury severity and causes of death from Operation Iraqi Freedom and Operation Enduring Freedom: 2003-2004 versus 2006. J Trauma . 2008;64(2 Suppl):S21–S26, discussion S26–7. doi: 10.1097/TA.0b013e318160b9fb . 10. Raux M, et al. What do prehospital trauma scores predict besides mortality? J Trauma 2011;71(3):754–9. (PMID: 10.1097/TA.0b013e318160b9fb) Larson CR, White CE, Spinella PC, et al. Association of shock, coagulopathy, and initial vital signs with massive transfusion in combat casualties. J Trauma . 2010;69:S26–S32. Mitra B, Cameron PA, Mori A, et al. Early prediction of acute traumatic coagulopathy. Resuscitation . 2011;82(9):1208–1213. Mackenzie CF, Hu P, Sen A, et al. Automatic pre-hospital vital signs waveform and trend data capture fills quality management, triage and outcome prediction gaps. AMIA Annu Symp Proc . 2008;2008:318–322. Liu NT, Holcomb JB, Wade CE, et al. Data quality of a wearable vital signs monitor in the pre-hospital and emergency departments for enhancing prediction of needs for life-saving interventions in trauma patients. J Med Eng Technol . 2015;39(6):316–321. Yang S, Mackenzie CF, Rock P, et al. Comparison of massive and emergency transfusion prediction scoring systems after trauma with a new bleeding risk index score applied in-flight. J Trauma Acute Care Surg . 2021;90(2):268–273. Zeineddin A, Hu P, Yang S, et al. Prehospital continuous vital signs predict need for resuscitative endovascular balloon occlusion of the aorta and resuscitative thoracotomy prehospital continuous vital signs predict resuscitative endovascular balloon occlusion of the aorta. J Trauma Acute Care Surg . 2021;91(5):798–802.
Substance Nomenclature:	33X04XA5AT (Lactic Acid)
Entry Date(s):	Date Created: 20241024 Date Completed: 20241213 Latest Revision: 20241216
Update Code:	20260130
DOI:	10.1097/SHK.0000000000002474
PMID:	39447081
Βάση Δεδομένων:	MEDLINE

Περιγραφή
ISSN:	1540-0514
DOI:	10.1097/SHK.0000000000002474