New injury severity score (NISS) outperforms injury severity score (ISS) in the evaluation of severe blunt trauma patients

Li, Hui; Ma, Yuefeng

doi:10.1016/j.cjtee.2021.01.006

Cited by 44 publications

(42 citation statements)

References 22 publications

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“…Septic shock, APACHE II score on admission, SOFA score, and MODS were independent risk factors of death for patients with post-traumatic sepsis. ISS is the most commonly used tool for stratification of injured patients and have been widely used in trauma evaluation, which presents excellent performance in predicting mortality caused by blunt trauma when the patients' ISS are lower than 25 [ 27 ]. In 1999, SOFA was applied to evaluate organ dysfunction in trauma patients and associated with prediction of prolonged ICU stay or death [ 28 ].…”

Section: Discussionmentioning

confidence: 99%

Risk Factors and Outcome of Sepsis in Traumatic Patients and Pathogen Detection Using Metagenomic Next-Generation Sequencing

Tong

Zhang

et al. 2022

Canadian Journal of Infectious Diseases and Medical Microbiolog

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Objective. Sepsis, a life-threatening clinical syndrome, is a leading cause of mortality after experiencing multiple traumas. Once diagnosed with sepsis, patients should be given an appropriate empiric antimicrobial treatment followed by the specific antibiotic therapy based on blood culture due to its rapid progression to tissue damage and organ failure. In this study, we aimed to analyze the risk factors and outcome of sepsis in traumatic patients and to investigate the performance of metagenomic next-generation sequencing (mNGS) compared with standard microbiological diagnostics in post-traumatic sepsis. Methods. The study included 528 patients with multiple traumas among which there were 142 cases with post-traumatic sepsis. Patients’ demographic and clinical data were recorded. The outcome measures included mortality during the emergency intensive care unit (EICU), EICU length of stay (LOS), all-cause 28-day mortality, and total ventilator days in 28 days after admission. A total of 89 blood samples from 89 septic patients underwent standard microbiological blood cultures and 89 samples of peripheral blood (n = 21), wound secretion (n = 41), bronchoalveolar lavage fluid (BALF) (19), ascites (n = 5), and sputum (n = 3) underwent mNGS. Pathogen detection was compared between standard microbiological blood cultures and mNGS. Results. The sepsis group and non-sepsis group exhibited significant differences regarding shock on admission, blood transfusion, mechanical ventilation, body temperature, heart rate, WBC count, neutrophil count, hematocrit, urea nitrogen, creatinine, CRP, D-D dimer, PCT, scores of APACHE II, sequential organ failure assessment (SOFA), and Injury Severity Score (ISS) on admission to the EICU, and Multiple Organ Dysfunction Syndromes (MODS) ( P < 0.05 ). Multivariate logistic regression analysis showed that scores of APACHE II, SOFA, and ISS on admission, and MODS were independent risk factors for the occurrence of sepsis in patients with multiple traumas. The 28-day mortality was higher in the sepsis group than in the non-sepsis group (45.07% vs. 19.17%, P < 0.001 ). The mortality during the EICU was higher in the sepsis group than in the non-sepsis group ( P = 0.002 ). The LOS in the EICU in the sepsis group was increased compared with the non-sepsis group ( P = 0.004 ). The total ventilator days in 28 days after admission in the sepsis group was increased compared with the non-sepsis group ( P < 0.001 ). Multivariate logistic regression analysis showed that septic shock, APACHE II score on admission, SOFA score, and MODS were independent risk factors of death for patients with post-traumatic sepsis. The positive detection rate of mNGS was 91.01% (81/89), which was significantly higher than that of standard microbiological blood cultures (39.33% (35/89)). Standard microbiological blood cultures and mNGS methods demonstrated double positive results in 33 (37.08%) specimens and double-negative results in 8 (8.99%) specimens, while 46 (51.69%) samples and 2 (2.25%) samples had positive results only with mNGS or culture alone, respectively. Conclusion. Our study identifies risk factors for the incidence and death of sepsis in traumatic patients and shows that mNGS may serve as a better diagnostic tool for the identification of pathogens in post-traumatic sepsis than standard microbiological blood cultures.

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Section: Discussionmentioning

confidence: 99%

Risk Factors and Outcome of Sepsis in Traumatic Patients and Pathogen Detection Using Metagenomic Next-Generation Sequencing

Tong

Zhang

et al. 2022

Canadian Journal of Infectious Diseases and Medical Microbiolog

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“…The cohort's median TRISS survival percentage was 98.4% (IQR, 96.6-99.3%) with those who survived at 98.6% (IQR, 97-99.3%) and those who died at 88.9% (IQR, 64.7-97.7%). The cohort's median GCS was 15 (IQR, [13][14][15] with those who survived at 15 (IQR, 14-15) and those who died at 13 (IQR, [3][4][5][6][7][8][9][10][11][12][13][14][15]. The cohort's mean ± SD SI was 0.88 ± 0.4 with those who survived at 0.85 ± 0.12 and those who died at 1.17 ± 0.19.…”

Section: Resultsmentioning

confidence: 99%

“…[7][8][9] In addition, NISS was superior to ISS when predicting for mortality and complications of penetrating trauma patients. 10,11 The significance of these trauma scoring systems in influencing patient care makes constant reevaluations and improvements an imperative. This is especially true when taking a historical context.…”

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confidence: 99%

New Injury Severity Score and Trauma Injury Severity Score are superior in predicting trauma mortality

Chun

Zhang

Becnel

et al. 2021

J Trauma Acute Care Surg

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BACKGROUND:Trauma scores are used to give clinicians appropriate quantitative context in making decisions. Studies show that anatomical trauma scores predicted intensive care unit admission better, while physiological trauma scores predicted mortality better. We hypothesize that trauma scores have a hierarchy of efficacies at predicting mortality and operative decision making. METHODS:We performed a retrospective analysis of our trauma patient database at a level 1 trauma center from 2016 to 2020 and calculated the following trauma scores: Glasgow Coma Scale, Revised Trauma Score, Trauma Injury Severity Score, Injury Severity Score, Shock Index, and New Trauma Injury Severity Score (NISS). Receiver operating characteristic curves were used to evaluate the sensitivity and specificity of trauma scores for predicting mortality. RESULTS:A total of 738 patients were included (mean ± SD age, 35.7 ± 15.6 years). Area under the curve (AUC) results from the DeLong test showed that NISS predicted mortality the best compared with other trauma scores. New Trauma Injury Severity Score was superior in predicting mortality for penetrating trauma (AUC, 0.86 ± 0.02; p < 0.001) compared with blunt trauma (AUC, 0.73 ± 0.04; p < 0.001). Trauma Injury Severity Score was the best predictor of mortality for patients with gunshot wounds (AUC, 0.83; 95% confidence interval [CI], 0.73-0.92; p < 0.001), motor vehicle accidents (AUC, 0.80; 95% CI, 0.61-1.00; p = 0.01), and falls (AUC, 0.73; 95% CI, 0.61-0.85; p = 0.007). CONCLUSION:New Trauma Injury Severity Score was the best scoring index for predicting mortality in trauma patients, especially for penetrating trauma. Clinicians should consider incorporating other trauma scores, especially NISS and Trauma Injury Severity Score, in determining injury severity and the likelihood of mortality. These scores can help physicians determine the best course of action in patient management.

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“…Ranging from an increased incidence of secondary complications to discharge to specialised care facilities, critically ill patients with an extended ICU LOS experience poor short and long-term clinical outcomes [6,8]. In paediatric and adult trauma settings, several groups have investigated whether an assessment of injury severity at hospital presentation can aid in the identification of patients at risk of a prolonged ICU LOS [17][18][19]42].…”

Section: Discussionmentioning

confidence: 99%

“…These factors include male gender [9], increased age [6,9,10], pre-existing co-morbidities [6], higher injury severity [6,9,10], severe head injury [6,[10][11][12], surgical procedures [10] and nosocomial infection [9,10]. While an assessment of injury severity at hospital arrival, using either the injury severity score (ISS) or new ISS (NISS), can predict who requires admission to ICU [13][14][15][16], these anatomical scoring systems are unable to accurately distinguish between patients who subsequently experience a short or prolonged ICU LOS [17][18][19], with the area under the receiver operating characteristic (AUROC) curve values ranging from 0.448-0.804 [17][18][19]. Thus, new models capable of predicting ICU LOS with greater discriminatory power are needed to aid in the development of targeted treatments during the acute post-injury phase.…”

Section: Introductionmentioning

confidence: 99%

Integration of Metabolomic and Clinical Data Improves the Prediction of Intensive Care Unit Length of Stay Following Major Traumatic Injury

et al. 2021

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Background: Recent advances in emergency medicine and the co-ordinated delivery of trauma care mean more critically-injured patients now reach the hospital alive and survive life-saving operations. Indeed, between 2008 and 2017, the odds of surviving a major traumatic injury in the UK increased by nineteen percent. However, the improved survival rates of severely-injured patients have placed an increased burden on the healthcare system, with major trauma a common cause of intensive care unit (ICU) admissions that last ≥10 days. Improved understanding of the factors influencing patient outcomes is now urgently needed. Methods: We investigated the serum metabolomic profile of fifty-five major trauma patients across three post-injury phases: acute (days 0–4), intermediate (days 5–14) and late (days 15–112). Using ICU length of stay (LOS) as a clinical outcome, we aimed to determine whether the serum metabolome measured at days 0–4 post-injury for patients with an extended (≥10 days) ICU LOS differed from that of patients with a short (<10 days) ICU LOS. In addition, we investigated whether combining metabolomic profiles with clinical scoring systems would generate a variable that would identify patients with an extended ICU LOS with a greater degree of accuracy than models built on either variable alone. Results: The number of metabolites unique to and shared across each time segment varied across acute, intermediate and late segments. A one-way ANOVA revealed the most variation in metabolite levels across the different time-points was for the metabolites lactate, glucose, anserine and 3-hydroxybutyrate. A total of eleven features were selected to differentiate between <10 days ICU LOS vs. >10 days ICU LOS. New Injury Severity Score (NISS), testosterone, and the metabolites cadaverine, urea, isoleucine, acetoacetate, dimethyl sulfone, syringate, creatinine, xylitol, and acetone form the integrated biomarker set. Using metabolic enrichment analysis, we found valine, leucine and isoleucine biosynthesis, glutathione metabolism, and glycine, serine and threonine metabolism were the top three pathways differentiating ICU LOS with a p < 0.05. A combined model of NISS and testosterone and all nine selected metabolites achieved an AUROC of 0.824. Conclusions: Differences exist in the serum metabolome of major trauma patients who subsequently experience a short or prolonged ICU LOS in the acute post-injury setting. Combining metabolomic data with anatomical scoring systems allowed us to discriminate between these two groups with a greater degree of accuracy than that of either variable alone.

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New injury severity score (NISS) outperforms injury severity score (ISS) in the evaluation of severe blunt trauma patients

Cited by 44 publications

References 22 publications

Risk Factors and Outcome of Sepsis in Traumatic Patients and Pathogen Detection Using Metagenomic Next-Generation Sequencing

Risk Factors and Outcome of Sepsis in Traumatic Patients and Pathogen Detection Using Metagenomic Next-Generation Sequencing

New Injury Severity Score and Trauma Injury Severity Score are superior in predicting trauma mortality

Integration of Metabolomic and Clinical Data Improves the Prediction of Intensive Care Unit Length of Stay Following Major Traumatic Injury

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