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Trauma
Timing and Associated Factors for Sepsis-3 in Severe Trauma Patients: A 3-Year Single Trauma Center Experience
Seungwoo Chung, Donghwan Choi, Jayun Cho, Yo Huh, Jonghwan Moon, Junsik Kwon, Kyoungwon Jung, John-Cook Jong Lee, Byung Hee Kang
Acute Crit Care. 2018;33(3):130-134.   Published online August 31, 2018
DOI: https://doi.org/10.4266/acc.2018.00122
  • 8,421 View
  • 224 Download
  • 14 Web of Science
  • 14 Crossref
AbstractAbstract PDF
Background
We hypothesized that the recent change of sepsis definition by sepsis-3 would facilitate the measurement of timing of sepsis for trauma patients presenting with initial systemic inflammatory response syndrome. Moreover, we investigated factors associated with sepsis according to the sepsis-3 definition.
Methods
Trauma patients in a single level I trauma center were retrospectively reviewed from January 2014 to December 2016. Exclusion criteria were younger than 18 years, Injury Severity Score (ISS) <15, length of stay <8 days, transferred from other hospitals, uncertain trauma history, and incomplete medical records. A binary logistic regression test was used to identify the risk factors for sepsis-3.
Results
A total of 3,869 patients were considered and, after a process of exclusion, 422 patients were reviewed. Fifty patients (11.85%) were diagnosed with sepsis. The sepsis group presented with higher mortality (14 [28.0%] vs. 17 [4.6%], P<0.001) and longer intensive care unit stay (23 days [range, 11 to 35 days] vs. 3 days [range, 1 to 9 days], P<0.001). Multivariate analysis demonstrated that, in men, high lactate level and red blood cell transfusion within 24 hours were risk factors for sepsis. The median timing of sepsis-3 was at 8 hospital days and 4 postoperative days. The most common focus was the respiratory system.
Conclusions
Sepsis defined by sepsis-3 remains a critical issue in severe trauma patients. Male patients with higher ISS, lactate level, and red blood cell transfusion should be cared for with caution. Reassessment of sepsis should be considered at day 8 of hospital stay or day 4 postoperatively.

Citations

Citations to this article as recorded by  
  • A biomarker panel of C-reactive protein, procalcitonin and serum amyloid A is a predictor of sepsis in severe trauma patients
    Mei Li, Yan-jun Qin, Xin-liang Zhang, Chun-hua Zhang, Rui-juan Ci, Wei Chen, De-zheng Hu, Shi-min Dong
    Scientific Reports.2024;[Epub]     CrossRef
  • Identifying biomarkers deciphering sepsis from trauma-induced sterile inflammation and trauma-induced sepsis
    Praveen Papareddy, Michael Selle, Nicolas Partouche, Vincent Legros, Benjamin Rieu, Jon Olinder, Cecilia Ryden, Eva Bartakova, Michal Holub, Klaus Jung, Julien Pottecher, Heiko Herwald
    Frontiers in Immunology.2024;[Epub]     CrossRef
  • The Road to Sepsis in Geriatric Polytrauma Patients—Can We Forecast Sepsis in Trauma Patients?
    Cédric Niggli, Philipp Vetter, Jan Hambrecht, Hans-Christoph Pape, Ladislav Mica
    Journal of Clinical Medicine.2024; 13(6): 1570.     CrossRef
  • Defining Posttraumatic Sepsis for Population-Level Research
    Katherine Stern, Qian Qiu, Michael Weykamp, Grant O’Keefe, Scott C. Brakenridge
    JAMA Network Open.2023; 6(1): e2251445.     CrossRef
  • Strategies for the treatment of femoral fractures in severely injured patients: trends in over two decades from the TraumaRegister DGU®
    Felix M. Bläsius, Markus Laubach, Hagen Andruszkow, Philipp Lichte, Hans-Christoph Pape, Rolf Lefering, Klemens Horst, Frank Hildebrand
    European Journal of Trauma and Emergency Surgery.2022; 48(3): 1769.     CrossRef
  • Infectious Diseases-Related Emergency Department Visits Among Non-Elderly Adults with Intellectual and Developmental Disabilities in the United States: Results from the National Emergency Department Sample, 2016
    Hussaini Zandam, Monika Mitra, Ilhom Akobirshoev, Frank S. Li, Ari Ne'eman
    Population Health Management.2022; 25(3): 335.     CrossRef
  • Patient, provider, and system factors that contribute to health care–associated infection and sepsis development in patients after a traumatic injury: An integrative review
    Debbie Tan, Taneal Wiseman, Vasiliki Betihavas, Kaye Rolls
    Australian Critical Care.2021; 34(3): 269.     CrossRef
  • Accuracy of Procalcitonin Levels for Diagnosis of Culture-Positive Sepsis in Critically Ill Trauma Patients: A Retrospective Analysis
    Aisha Bakhtiar, Syed Jawad Haider Kazmi, Muhammad Sohaib Asghar, Muhammad Nadeem Khurshaidi, Salman Mazhar, Noman A Khan, Nisar Ahmed, Farah Yasmin, Rabail Yaseen, Maira Hassan
    Cureus.2021;[Epub]     CrossRef
  • An Evaluation of the Effect of Performance Improvement and Patient Safety Program Implemented in a New Regional Trauma Center of Korea
    Yo Huh, Junsik Kwon, Jonghwan Moon, Byung Hee Kang, Sora Kim, Jayoung Yoo, Seoyoung Song, Kyoungwon Jung
    Journal of Korean Medical Science.2021;[Epub]     CrossRef
  • The impact of infection complications after trauma differs according to trauma severity
    Akira Komori, Hiroki Iriyama, Takako Kainoh, Makoto Aoki, Toshio Naito, Toshikazu Abe
    Scientific Reports.2021;[Epub]     CrossRef
  • Gene Expression–Based Diagnosis of Infections in Critically Ill Patients—Prospective Validation of the SepsisMetaScore in a Longitudinal Severe Trauma Cohort
    Simone Thair, Caspar Mewes, José Hinz, Ingo Bergmann, Benedikt Büttner, Stephan Sehmisch, Konrad Meissner, Michael Quintel, Timothy E. Sweeney, Purvesh Khatri, Ashham Mansur
    Critical Care Medicine.2021; 49(8): e751.     CrossRef
  • Immunometabolic signatures predict risk of progression to sepsis in COVID-19
    Ana Sofía Herrera-Van Oostdam, Julio E. Castañeda-Delgado, Juan José Oropeza-Valdez, Juan Carlos Borrego, Joel Monárrez-Espino, Jiamin Zheng, Rupasri Mandal, Lun Zhang, Elizabeth Soto-Guzmán, Julio César Fernández-Ruiz, Fátima Ochoa-González, Flor M. Trej
    PLOS ONE.2021; 16(8): e0256784.     CrossRef
  • Sepsis in Trauma: A Deadly Complication
    Fernanda Mas-Celis, Jimena Olea-López, Javier Alberto Parroquin-Maldonado
    Archives of Medical Research.2021; 52(8): 808.     CrossRef
  • New automated analysis to monitor neutrophil function point-of-care in the intensive care unit after trauma
    Lillian Hesselink, Roy Spijkerman, Emma de Fraiture, Suzanne Bongers, Karlijn J. P. Van Wessem, Nienke Vrisekoop, Leo Koenderman, Luke P. H. Leenen, Falco Hietbrink
    Intensive Care Medicine Experimental.2020;[Epub]     CrossRef
Trauma
The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring Systems
Kyoungwon Jung, John Cook-Jong Lee, Rae Woong Park, Dukyong Yoon, Sungjae Jung, Younghwan Kim, Jonghwan Moon, Yo Huh, Junsik Kwon
Korean J Crit Care Med. 2016;31(3):221-228.   Published online August 30, 2016
DOI: https://doi.org/10.4266/kjccm.2016.00486
  • 9,612 View
  • 204 Download
  • 7 Crossref
AbstractAbstract PDF
Background
Injury severity scoring systems that quantify and predict trauma outcomes have not been established in Korea. This study was designed to determine the best system for use in the Korean trauma population.
Methods
We collected and analyzed the data from trauma patients admitted to our institution from January 2010 to December 2014. Injury Severity Score (ISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) were calculated based on the data from the enrolled patients. Area under the receiver operating characteristic (ROC) curve (AUC) for the prediction ability of each scoring system was obtained, and a pairwise comparison of ROC curves was performed. Additionally, the cut-off values were estimated to predict mortality, and the corresponding accuracy, positive predictive value, and negative predictive value were obtained.
Results
A total of 7,120 trauma patients (6,668 blunt and 452 penetrating injuries) were enrolled in this study. The AUCs of ISS, RTS, and TRISS were 0.866, 0.894, and 0.942, respectively, and the prediction ability of the TRISS was significantly better than the others (p < 0.001, respectively). The cut-off value of the TRISS was 0.9082, with a sensitivity of 81.9% and specificity of 92.0%; mortality was predicted with an accuracy of 91.2%; its positive predictive value was the highest at 46.8%.
Conclusions
The results of our study were based on the data from one institution and suggest that the TRISS is the best prediction model of trauma outcomes in the current Korean population. Further study is needed with more data from multiple centers in Korea.

Citations

Citations to this article as recorded by  
  • Outcomes in trauma patients undergoing veno-venous extracorporeal membrane oxygenation for acute respiratory distress syndrome
    Seon Hee Kim, Up Huh, Seunghwan Song, Min Su Kim, Il Jae Wang, Young Jin Tak
    Perfusion.2023; 38(5): 1037.     CrossRef
  • Prehospital Trauma Scoring Systems for Evaluation of Trauma Severity and Prediction of Outcomes
    Radojka Jokšić-Mazinjanin, Nikolina Marić, Aleksandar Đuričin, Zoran Gojković, Velibor Vasović, Goran Rakić, Milena Jokšić-Zelić, Siniša Saravolac
    Medicina.2023; 59(5): 952.     CrossRef
  • Correlation between trauma and injury severity score and prognosis in patients with trauma
    Chusnul Chatimah, Indah D. Pratiwi, Chairul H. Al Husna
    Journal of Taibah University Medical Sciences.2021; 16(6): 807.     CrossRef
  • Trauma Volume and Performance of a regional Trauma Center in Korea: Initial 5-year analysis
    Byungchul Yu, Giljae Lee, Min A Lee, Kangkook Choi, Sungyoul Hyun, Yangbin Jeon, Yong-Cheol Yoon, Jungnam Lee
    Journal of Trauma and Injury.2020; 33(1): 31.     CrossRef
  • Inclusion of lactate level measured upon emergency room arrival in trauma outcome prediction models improves mortality prediction: a retrospective, single-center study
    Jonghwan Moon, Kyungjin Hwang, Dukyong Yoon, Kyoungwon Jung
    Acute and Critical Care.2020; 35(2): 102.     CrossRef
  • Trauma and Injury Severity Score modification for predicting survival of trauma in one regional emergency medical center in Korea: Construction of Trauma and Injury Severity Score coefficient model
    In Hye Kang, Kang Hyun Lee, Hyun Youk, Jeong Il Lee, Hee Young Lee, Keum Seok Bae
    Hong Kong Journal of Emergency Medicine.2019; 26(4): 225.     CrossRef
  • The thorax trauma severity score and the trauma and injury severity score
    Seong Ho Moon, Jong Woo Kim, Joung Hun Byun, Sung Hwan Kim, Jun Young Choi, In Seok Jang, Chung Eun Lee, Jun Ho Yang, Dong Hun Kang, Ki Nyun Kim, Hyun Oh Park
    Medicine.2017; 96(42): e8317.     CrossRef
Case Report
Trauma/Surgery
Secondary Abdominal Compartment Syndrome Recognized in Operating Room in Severely Injured Patients
Seok Hwa Youn, John Cook-Jong Lee, Kyoungwon Jung, Jonghwan Moon, Yo Huh, Younghwan Kim
Korean J Crit Care Med. 2016;31(1):58-62.   Published online February 29, 2016
DOI: https://doi.org/10.4266/kjccm.2016.31.1.58
  • 33,179 View
  • 90 Download
AbstractAbstract PDF
For trauma patients with severe shock, massive fluid resuscitation is necessary. However, shock and a large amount of fluid can cause bowel and retroperitoneal edema, which sometimes leads to abdominal compartment syndrome in patients without abdomino-pelvic injury. If other emergent operations except intraabdomen are needed, a distended abdomen is likely to be recognized late, leading to multiple organ dysfunction. Herein, we report two cases of a 23-year-old woman who was in a car accident and a 53-year old man who was pressed on his leg by a pressing machine; severe brain swelling and popliteal vessel injury were diagnosed, respectively. They were both in severe shock and massive fluid resuscitation was required in the emergency department. Distended abdomen was recognized in both the female and male patients immediately after neurosurgical operation and immediately before orthopaedic operation in the operating room, respectively. Decompressive laparotomy revealed massive ascites with retroperitoneal edema.

ACC : Acute and Critical Care