Modified Revised Trauma-Marshall score as a proposed tool in predicting the outcome of moderate and severe traumatic brain injury

Predicting Vasospasm and Early Mortality in Severe Traumatic Brain Injury: A Model Using Serum Cytokines, Neuronal Proteins, and Clinical Data

BACKGROUND AND OBJECTIVES

Prediction of patient outcomes after severe traumatic brain injury (sTBI) is limited with current clinical tools. This study aimed to improve such prognostication by combining clinical data and serum inflammatory and neuronal proteins in patients with sTBI to develop predictive models for post-traumatic vasospasm (PTV) and mortality.

METHODS

Fifty-three adult civilian patients were prospectively enrolled in the sTBI arm of the Surgical Critical Care Initiative (SC2i). Clinical, serum inflammatory, and neuronal protein data were combined using the parsimonious machine learning methods of least absolute shrinkage and selection operator (LASSO) and classification and regression trees (CART) to construct parsimonious models for predicting development of PTV and mortality.

RESULTS

Thirty-six (67.9%) patients developed vasospasm and 10 (18.9%) died. The mean age was 39.2 years; 22.6% were women. CART identified lower IL9, lower presentation pulse rate, and higher eotaxin as predictors of vasospasm development (full data area under curve (AUC) = 0.89, mean cross-validated AUC = 0.47). LASSO identified higher Rotterdam computed tomography score and lower age as risk factors for vasospasm development (full data AUC 0.94, sensitivity 0.86, and specificity 0.94; cross-validation AUC 0.87, sensitivity 0.79, and specificity 0.93). CART identified high levels of eotaxin as most predictive of mortality (AUC 0.74, cross-validation AUC 0.57). LASSO identified higher serum IL6, lower IL12, and higher glucose as predictive of mortality (full data AUC 0.9, sensitivity 1.0, and specificity 0.72; cross-validation AUC 0.8, sensitivity 0.85, and specificity 0.79).

CONCLUSION

Inflammatory cytokine levels after sTBI may have predictive value that exceeds conventional clinical variables for certain outcomes. IL-9, pulse rate, and eotaxin as well as Rotterdam score and age predict development of PTV. Eotaxin, IL-6, IL-12, and glucose were predictive of mortality. These results warrant validation in a prospective cohort.

Development and validation of a clinical nomogram for predicting in-hospital mortality in patients with traumatic brain injury prehospital: A retrospective study

Objective

Traumatic brain injury (TBI) is among the leading causes of death and disability globally. Identifying and assessing the risk of in-hospital mortality in traumatic brain injury patients at an early stage is challenging. This study aimed to develop a model for predicting in-hospital mortality in TBI patients using prehospital data from China.

Methods

We retrospectively included traumatic brain injury patients who sustained injuries due to external forces and were treated by pre-hospital emergency medical services (EMS) at a tertiary hospital. Data from the pre-hospital emergency database were analyzed, including demographics, trauma mechanisms, comorbidities, vital signs, clinical symptoms, and trauma scores. Eligible patients were randomly divided into a training set (241 cases) and a validation set (104 cases) at a 7:3 ratio. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were employed to identify independent risk factors. Analyzed the discrimination, calibration, and net benefit of the nomogram across both groups.

Results

17.40 % (42/241) of TBI patients died in the hospital in the training set, while 18.30 % (19/104) in the validation set. After analysis, chest trauma (odds ratio [OR] = 4.556, 95 % confidence interval [CI] = 1.861-11.152, P = 0.001), vomiting (OR = 2.944, 95%CI = 1.194-7.258, P = 0.019), systolic blood pressure (OR = 0.939, 95%CI = 0.913-0.966, P < 0.001), SpO2 (OR = 0.778, 95%CI = 0.688-0.881, P < 0.001), and heart rate (OR = 1.046, 95%CI = 1.015-1.078, P = 0.003) were identified as independent risk factors for in-hospital mortality in TBI patients. The nomogram based on the five factors demonstrated well-predictive power, with an area under the curve (AUC) of 0.881 in the training set and 0.866 in the validation set. The calibration curve and decision curve analysis showed that the predictive model exhibited good consistency and covered a wide range of threshold probabilities in both sets.

Conclusion

The nomogram based on prehospital data demonstrated well-predictive performance for in-hospital mortality in TBI patients, helping prehospital emergency physicians identify and assess severe TBI patients earlier, thereby improving the efficiency of prehospital emergency care.

The GCS-Pupils (GCS-P) score to assess outcomes after traumatic brain injury: a retrospective study

INTRODUCTION

The Glasgow Coma Scale (GCS) and pupil response to light are commonly used to assess brain injury severity and predict outcomes. The aim of this study was to investigate whether the GCS combined with pupil response (GCS-P), compared to the GCS alone, could be a better predictor of hospital mortality for patients with traumatic brain injury (TBI).

METHODS

A retrospective cohort study was undertaken at an adult level one trauma centre including patients with isolated TBI of Abbreviated Injury Scale above three. The GCS and pupil response were combined to an arithmetic score (GCS score (range 3-15) minus the number of nonreacting pupils (0, 1, or 2)), or by treating each factor as separate categorical variables. The association of in-hospital mortality with GCS-P as a categorical variable was evaluated using Nagelkerke's R2 and compared using areas under the receiver operating characteristic (AUROC) curve.

RESULTS

There were 392 patients included over the study period of 1 July 2014 and 30 September 2017, with an overall mortality rate of 15.2%. Mortality was highest at GCS-P of 1 (79%), with lowest mortality at a GCS-P 15 (1.6%). Nagelkerke's R2 was 0.427 for GCS alone and 0.486 for GCS-P. The AUROC for GCS-P to predict mortality was 0.87 (95%CI: 0.82-0.72), higher than for GCS alone (0.85; 95%CI: 0.80-0.90; p < .001).

DISCUSSION

GCS-P provided a better predictor of mortality compared to the GCS. As both the GCS and pupillary response are routinely recorded on all patients, combination of these pieces of information into a single score can further simplify assessment of patients with TBI, with some improvement in performance.

Risk factors of prognosis in older patients with severe brain injury after surgical intervention

BACKGROUND

Older patients (aged ≥ 60 years) with severe brain injury have a high mortality and disability rate. The objective of this retrospective study was to assess the clinical risk factors of prognosis in older patients with severe brain injury after surgical intervention and to analyze the prognosis of the surviving group of patients 1 year after discharge.

METHODS

Clinical data of older patients with severe brain injury who were admitted to two neurosurgical centers between January 2010 and December 2020 were collected. Patient age, sex, Glasgow Coma Scale (GCS) score at admission, underlying disease, mechanisms of injury, abnormal pupillary reflex, head computed tomography imaging findings (such as hematoma type),intraoperative brain swelling and other factors were reviewed. All the patients were categorized into a good prognosis (survival) group and a poor prognosis (death) group by the Glasgow Outcome Score (GOS); also, the related factors affecting the prognosis were screened and the independent risk factors were identified by the Binary logistic regression analysis. GOS was used to evaluate the prognosis of the surviving group of patients 1 year after discharge.

RESULTS

Out of 269 patients, 171 (63.6%) survived, and 98 (36.4%) died during hospitalization. Univariate analysis showed that age, GCS score at admission, underlying diseases, abnormal pupillary reflex, the disappearance of ambient cistern, the midline structure shift, intraoperative brain swelling, oxygen saturation < 90%, and cerebral hernia were risk factors for the prognosis of older patients with severe brain injury after surgical intervention. Multivariate analysis showed that age, underlying diseases, disappearance of ambient cistern, Oxygen saturation < 90% and intraoperative brain swelling were independent risk factors of the prognosis in the population. The effect of surgical intervention differed among various age groups at 1-year follow-up after surgery.

CONCLUSIONS

The results of this retrospective study confirmed that age, underlying diseases, disappearance of ambient cistern, intraoperative brain swelling, and oxygen saturation < 90% are associated with poor prognosis in older postoperative patients with severe brain injury. Surgical intervention may improve prognosis and reduce mortality in older patients (age < 75 years). But for those patients (age ≥ 75 years), the prognosis was poor after surgical intervention.

The association between lactate to albumin ratio and outcomes at early phase in patients with traumatic brain injury

BACKGROUND

The majority of traumatic brain injury (TBI) cases result in death in the early phase; predicting short-term progno-sis of affected patients is necessary to prevent this. This study aimed to examine the association between the lactate-to-albumin ratio (LAR) on admission and outcomes in the early phase of TBI.

METHODS

This retrospective observational study included patients with TBI who visited our emergency department between January 2018 and December 2020. TBI was considered as an head abbreviated injury scale (AIS) score of 3 or higher and other AIS of 2 or lower. The primary and secondary outcomes were 24-h mortality and massive transfusion (MT), respectively.

RESULTS

In total, 460 patients were included. The 24-h mortality was 12.6% (n=28) and MT was performed in 31 (6.7%) patients. In the multivariable analysis, LAR was associated with 24-h mortality (odds ratio [OR], 2.021; 95% confidence interval [CI], 1.301-3.139) and MT (OR, 1.898; 95% CI, 1.288-2.797). The areas under the curve of LAR for 24-h mortality and MT were 0.805 (95% CI, 0.766-0.841) and 0.735 (95% CI, 0.693-0.775), respectively.

CONCLUSION

LAR was associated with early-phase outcomes in patients with TBI, including 24-h mortality and MT. LAR may help predict these outcomes within 24 h in patients with TBI.

Community Integration and Associated Factors 10 Years after Moderate-to-Severe Traumatic Brain Injury

This study evaluated the impact of baseline injury characteristics and one-year functional level on the 10-year community integration outcomes for working-age patients with moderate-to-severe traumatic brain injury (TBI). Patients aged 16-55 and diagnosed with moderate-to-severe TBI within 24 h of injury were eligible for the study. Multivariable hierarchical linear regression was utilized to assess the impact of baseline characteristics and one-year functional measures on the mean Community Integration Questionnaire (CIQ) scores 10 years after injury. Of 133 original study participants, 97 survived 10 years, and 75 were available for this study. The mean total CIQ score changed positively from one to 10 years post-injury, from 18.7 (±5.5) to 19.8 (±4.8) (p = 0.04). The results suggested that age (β = -0.260, p = 0.013), FIM-Cognitive subscale (β = 0.608, p = 0.002), and the bodily pain subscale (BP) (β = 0.277, p = 0.017) of the SF-36 were significantly associated with the mean CIQ scores. In conclusion, this study demonstrated improved community integration from one to 10 years in a sample of working-age patients with moderate-to-severe TBI. The findings also showed that age, cognitive function, and bodily pain were significant predictors of long-term community integration, suggesting post-acute rehabilitation should focus on factors related to long-term risk and protective factors to improve long-term outcomes.

Role of electrocardiogram findings in predicting 48-h mortality in patients with traumatic brain injury

OBJECTIVE

Electrocardiogram (ECG) patterns can change, especially in patients with central nervous system disorders such as spontaneous subarachnoid hemorrhage. However, the association between the prognosis of traumatic brain injury (TBI) and ECG findings is unknown. Therefore, this study aimed to compare and to analyze ECG findings to predict early mortality in patients with TBI.

METHODS

This retrospective observational study included patients with severe trauma and TBI who were admitted to the emergency department (ED) between January 2018 and December 2020. TBI was defined as an abbreviated injury scale score of the head of ≥3. We examined ECG findings, including PR prolongation (≥ 200 ms), QRS complex widening (≥ 120 ms), corrected QT interval prolongation (QTP, ≥ 480 ms), ST-segment elevation, and ST-segment depression (STD) at ED arrival. The primary outcome was 48-h mortality.

RESULTS

Of the total patients with TBI, 1024 patients were included in this study and 48-h mortality occurred in 89 patients (8.7%). In multivariate analysis, QTP (odds ratio [OR], 2.017; confidence interval [CI], 1.203-3.382) and STD (OR, 8.428; 95% CI, 5.019-14.152) were independently associated with 48-h mortality in patients with TBI. The areas under the curve (AUCs) of the revised trauma score (RTS), injury severity score (ISS), QTP, STD, and the combination of QTP and STD were 0.790 (95% CI, 0.764-0.815), 0.632 (95% CI, 0.602-0.662), 0.605 (95% CI, 0.574-0.635), 0.723 (95% CI, 0.695-0.750), and 0.786 (95% CI, 0.759-0.811), respectively. The AUC of the combination of QTP and STD significantly differed from that of ISS, QTP, and STD, but not RTS.

CONCLUSION

Based on the ECG findings, QTP and STD were associated with 48-h mortality in patients with TBI.

Prognostic properties of the association between the S‑100B protein levels and the mean cerebral blood flow velocity in patients diagnosed with severe traumatic brain injury

Craniocerebral injury (CBI) is tissue damage caused by a sudden mechanical force. CBI can result in neurological, neuropsychological and psychiatric dysfunctions. Currently, the severity of CBI is assessed using the Glasgow Coma Scale, brain perfusion pressure measurements, transcranial Doppler tests and biochemical markers. This study aimed to determine the applicability of the S-100B protein levels and the time-averaged mean maximum cerebral blood flow velocity (V_mean) as a means of predicting the treatment outcomes of CBI in the first 4 days of hospitalization. The results validated the standard reference ranges previously proposed for the concentration of S-100B (0.05-0.23 µg/l) and the mean of cerebral blood flow velocity (30.9 to 74.1 cm/sec). The following stratification scheme was used to predict the success of treatment: Patients with a Glasgow Outcome Scale (GOS) score ≥4 or GOS <4 were stratified into ‘favorable’ and ‘unfavorable’ groups, respectively. The favorable group showed relatively constant levels of the S-100B protein close to the normal range and exhibited an increase in V_mean, but this was still within the normal range. The unfavorable group exhibited a high level of S-100B protein and increased V_mean outside of the normal ranges. The changes in the levels of S-100B in the unfavorable and favorable groups were -0.03 and -0.006 mg/l/h, respectively. Furthermore, the rate of decrease in the V_mean value in the unfavorable and favorable groups were -0.26 and -0.18 cm/sec/h, respectively. This study showed that constant levels of S-100B protein, even slightly above the normal range, associated with an increase in V_mean was indicative of a positive therapeutic outcome. However, additional research is required to obtain the appropriate statistical strength required for clinical practice.

Healthcare-associated Infections in Pediatric Patients in Neurotrauma Intensive Care Unit: A Retrospective Analysis

Background

Healthcare-associated infections (HAIs) can impact the outcome following traumatic brain injury (TBI) in children. We undertook a retrospective observational study to see the incidence, risk factors, and microbiological profile for HAIs in pediatric TBI. We also studied the impact of baseline patient characteristics, HAIs on patient outcome, and antibiotic resistance of different types of bacteria.

Materials and methods

Data on pediatric TBI patients of age up to 12 years were collected via a computerized patient record system (CPRS) from January 2012 to December 2018. Descriptive Chi-square test and Wilcoxon signed rank test were used to characterize baseline parameters. General linear regression models were run to find an unadjusted and adjusted odds ratio (OR).

Results

HAIs were found in 144 (34%) out of 423 patients. The most commonly seen infections were of the respiratory tract in 73 (17.26%) subjects. The most predominant microorganism isolated was Acinetobacter baumannii in 188 (41%) samples. A. baumannii was sensitive to colistin in 91 (48.4%) patients. Male gender (OR 0.630; p-value 0.035), fall from height (OR 0.374; p-value 0.008), and higher injury severity scale (ISS) (OR 1.040; p-value 0.002) were independent risk factors for development of HAIs. Severe TBI, higher ISS and Marshall grade, and HAIs were significantly associated with poor patient outcome.

Conclusion

Severe TBI poses a significant risk of HAIs. The most common site was the respiratory tract, predominately infected with A. baumannii. HAIs in pediatric TBI patients resulted in poor patient outcome.

How to cite this article

Prasad C, Bindra A, Singh P, Singh GP, Singh PK, Mathur P. Healthcare-associated Infections in Pediatric Patients in Neurotrauma Intensive Care Unit: A Retrospective Analysis. Indian J Crit Care Med 2021;25(11):1308-1313.

Relationship of Time of Injury Marijuana Exposure and Traumatic Brain Injury: A Systematic Review

BACKGROUND

Traumatic brain injury (TBI) is a significant nursing concern, as it is a leading cause of mortality, morbidity, and disability in the United States. Notably, up to 51% of all TBI patients have substance use exposure at the time of injury. Marijuana remains the most widely used illicit drug in the United States. However, little is known about marijuana exposure and TBI incidence and severity, particularly at the time of injury.

METHODS

A systematic literature review was conducted following PRISMA guidelines in PubMed to determine the relationship between marijuana exposure and TBI severity.Heterogeneity of study designs, concepts, samples, and variables in included studies precluded a meta-analysis. Hence, a descriptive analysis of findings was conducted.

RESULTS

The search yielded 939 studies, of which eight met inclusion criteria. Only one study found a connection between positive marijuana toxicology screen and mortality outcomes in TBI patients. There was significant variation in how marijuana exposure was defined, conceptualized, and operationalized in the other studies.

CONCLUSIONS

This review identified the need for larger, better-designed studies to address the significant knowledge gap about the relationship between marijuana use and its influence on TBI. Data and knowledge derived from such studies can help inform policy and aid in the development of nursing interventions that target prevention and increase awareness of TBI risk when under the influence of marijuana.

Evaluation of Intracranial Hypertension in Traumatic Brain Injury Patient: A Noninvasive Approach Based on Cranial Computed Tomography Features

BACKGROUND

Our purpose was to establish a noninvasive quantitative method for assessing intracranial pressure (ICP) levels in patients with traumatic brain injury (TBI) through investigating the Hounsfield unit (HU) features of computed tomography (CT) images.

METHODS

In this retrospective study, 47 patients with a closed TBI were recruited. Hounsfield unit features from the last cranial CT and the initial ICP value were collected. Three models were established to predict intracranial hypertension with Hounsfield unit (HU model), midline shift (MLS model), and clinical expertise (CE model) features.

RESULTS

The HU model had the highest ability to predict intracranial hypertension. In 34 patients with unilateral injury, the HU model displayed the highest performance. In three classifications of intracranial hypertension (ICP ≤ 22, 23-29, and ≥30 mmHg), the HU model achieved the highest F1 score.

CONCLUSIONS

This radiological feature-based noninvasive quantitative approach showed better performance compared with conventional methods, such as the degree of midline shift and clinical expertise. The results show its potential in clinical practice and further research.

Performance of Modified Early Warning Score (MEWS) for Predicting In-Hospital Mortality in Traumatic Brain Injury Patients

The present study aimed to analyze and compare the prognostic performances of the Revised Trauma Score (RTS), Injury Severity Score (ISS), Shock Index (SI), and Modified Early Warning Score (MEWS) for in-hospital mortality in patients with traumatic brain injury (TBI). This retrospective observational study included severe trauma patients with TBI who visited the emergency department between January 2018 and December 2020. TBI was considered when the Abbreviated Injury Scale was 3 or higher. The primary outcome was in-hospital mortality. In total, 1108 patients were included, and the in-hospital mortality was 183 patients (16.3% of the cohort). Receiver operating characteristic curve analyses were performed for the ISS, RTS, SI, and MEWS with respect to the prediction of in-hospital mortality. The area under the curves (AUCs) of the ISS, RTS, SI, and MEWS were 0.638 (95% confidence interval (CI), 0.603–0.672), 0.742 (95% CI, 0.709–0.772), 0.524 (95% CI, 0.489–0.560), and 0.799 (95% CI, 0.769–0.827), respectively. The AUC of MEWS was significantly different from the AUCs of ISS, RTS, and SI. In multivariate analysis, age (odds ratio (OR), 1.012; 95% CI, 1.000–1.023), the ISS (OR, 1.040; 95% CI, 1.013–1.069), the Glasgow Coma Scale (GCS) score (OR, 0.793; 95% CI, 0.761–0.826), and body temperature (BT) (OR, 0.465; 95% CI, 0.329–0.655) were independently associated with in-hospital mortality after adjustment for confounders. In the present study, the MEWS showed fair performance for predicting in-hospital mortality in patients with TBI. The GCS score and BT seemed to have a significant role in the discrimination ability of the MEWS. The MEWS may be a useful tool for predicting in-hospital mortality in patients with TBI.

Incidence of Paroxysmal Sympathetic Hyperactivity after Traumatic Brain Injury in a Tertiary Care ICU: A Retrospective Cohort Study

Background Paroxysmal sympathetic hyperactivity (PSH) is an understudied complication of traumatic brain injury (TBI). PSH usually presents with transient rise in sympathetic outflow, leading to increased blood pressure, heart rate, temperature, respiratory rate, sweating, and posturing activity. We retrospectively analyzed the incidence of PSH in TBI using PSH-assessment measure (PSH-AM) scale.

Methods This single-center retrospective cohort study was conducted in traumatic head injury patients admitted in the intensive care unit from January 1, 2016 to December 31, 2019 in a tertiary care center. The data was collected from the hospital database after obtaining approval from the hospital ethics committee.

Results A total of 287 patients (18–65 years of age) were admitted to intensive care unit (ICU) with TBI out of which 227 patients were analyzed who had ICU stay for more than 14 days. PSH was diagnosed in 70 (30.8%) patients. Mean age of PSH positive patients was 40 ± 18 and 49 ± 11 years for PSH negative patients (p < 0.001). The age group between 40 and 50 years had a higher incidence of PSH. The age and Glasgow coma score (GCS) were significantly associated with the occurrence of PSH. The GCS score demonstrated good accuracy for predicting the occurrence of PSH with AUC 0.83, 95% CI of 0.775 to 0.886, and a p-value of 0.001.

Conclusion We observed that the incidence of PSH was 30.8% in the patients with TBI. Age and GCS were found to have a significant association for predicting the occurrence of PSH. The patients who developed PSH had a longer length of hospital stay in ICU.

Prognosis in Moderate and Severe Traumatic Brain Injury: A Systematic Review of Contemporary Models and Validation Studies

Outcome prognostication in traumatic brain injury (TBI) is important but challenging due to heterogeneity of the disease. The aim of this systematic review is to present the current state-of-the-art on prognostic models for outcome after moderate and severe TBI and evidence on their validity. We searched for studies reporting on the development, validation or extension of prognostic models for functional outcome after TBI with Glasgow Coma Scale (GCS) ≤12 published between 2006-2018. Studies with patients age ≥14 years and evaluating a multi-variable prognostic model based on admission characteristics were included. Model discrimination was expressed with the area under the receiver operating characteristic curve (AUC), and model calibration with calibration slope and intercept. We included 58 studies describing 67 different prognostic models, comprising the development of 42 models, 149 external validations of 31 models, and 12 model extensions. The most common predictors were GCS (motor) score (n = 55), age (n = 54), and pupillary reactivity (n = 48). Model discrimination varied substantially between studies. The International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) and Corticoid Randomisation After Significant Head injury (CRASH) models were developed on the largest cohorts (8509 and 10,008 patients, respectively) and were most often externally validated (n = 91), yielding AUCs ranging between 0.65-0.90 and 0.66-1.00, respectively. Model calibration was reported with a calibration intercept and slope for seven models in 53 validations, and was highly variable. In conclusion, the discriminatory validity of the IMPACT and CRASH prognostic models is supported across a range of settings. The variation in calibration, reflecting heterogeneity in reliability of predictions, motivates continuous validation and updating if clinical implementation is pursued.

Higher plasma C-type lectin-like receptor 2 concentrations for prediction of higher risk of 30-day mortality in isolated severe blunt traumatic brain injury

BACKGROUND

Platelet activation is implicated in secondary brain injury following traumatic brain injury (TBI). C-type lectin-like receptor 2 (CLEC-2) is extensively expressed on platelets and participates in platelet activation. We investigate dthe prognostic significance of plasma CLEC-2 in TBI patients.

METHODS

One hundred and six patients with isolated severe blunt TBI and 106 healthy controls were prospectively investigated. Plasma CLEC-2 concentrations were detected and Glasgow coma scale (GCS) scores were recorded. The relationship between plasma CLEC-2 concentrations and 30-day mortality in addition to overall survival was determined using multivariate models.

RESULTS

Patients exhibited a substantially higher concentration of plasma CLEC-2 than healthy controls. Among patients, plasma CLEC-2 concentrations were remarkably increased in the GCS scores- and Rotterdam computerized tomography classification- dependent manner. As compared with survivors within posttraumatic 30 days, plasma CLEC-2 concentrations were remarkably raised in non-survivors. Rising plasma CLEC-2 concentration was independently associated with an enhanced risk of 30-day mortality and short overall survival time. Plasma CLEC-2 concentrations had a significantly high area under receiver operating characteristic curve for predicting 30-day mortality.

CONCLUSIONS

Incremental plasma CLEC-2 concentrations are intimately related to increasing trauma severity, in close association with increased 30-day death, indicating the prognostic role of plasma CLEC-2 in TBI.

Serum soluble TWEAK levels in severe traumatic brain injury and its prognostic significance

BACKGROUND

Severe traumatic brain injury (sTBI) is characterized by a high mortality. Tumor necrosis factor-like weak inducer of apoptosis (TWEAK) participates in inflammation. We determined serum soluble TWEAK (sTWEAK) levels with respect to its prognostic ability.

METHODS

This was a single-center prospective, observational study that was performed from December 2014 to December 2017. A total of 114 sTBI patients who met the inclusion criteria and 114 randomly selected healthy controls were included in the study. Serum sTWEAK levels were gauged. Patients were followed-up until death or completion of 6 months. Poor outcome was referred to as Glasgow outcome scale score of 1-3.

RESULTS

In comparison with controls, patients displayed predominantly higher serum sTWEAK levels. Serum sTWEAK levels were strongly correlated with Glasgow coma scale scores and serum C-reactive protein levels. 32 patients (28.1%) died and 60 patients (52.6%) suffered from a poor outcome. Receiver operating characteristic curve analysis clearly showed that serum sTWEAK levels had substantially high predictive performance for 6-month mortality and poor outcome. Serum sTWEAK emerged as an independent predictor for 6-month mortality, overall survival and poor outcome.

CONCLUSIONS

Raised serum sTWEAK levels are closely related to increasing inflammatory response, elevated trauma severity and worse clinical outcome after sTBI.

A prospective study on serum secreted protein acidic and rich in cysteine-like 1 as a prognostic marker for severe traumatic brain injury

BACKGROUND

Secreted protein acidic and rich in cysteine-like 1 (SPARCL1) regulates synaptic stability with upregulation throughout axonal regeneration. Our study aims to determine the correlation of serum SPARCL1 concentrations with the severity and in-hospital mortality of severe traumatic brain injury (sTBI).

METHODS

A total of 102 consecutively recruited patients admitted for sTBI and 102 randomly selected healthy controls were included in this observational prospective study. Serum SPARCL1 concentrations were measured and correlated with Glasgow coma scale (GCS) scores and in-hospital mortality using multivariate analysis.

RESULTS

Compared with controls (median, 0.22 ng/ml; interquartile range, 0.19-0.41 ng/ml), patients had significantly higher SPARCL1 concentrations (median, 3.29 ng/ml; interquartile range, 1.88-4.37; P < 0.001). There was an independently correlation between SPARCL1 concentrations and GCS scores (t = -7.011, P < 0.001). We found a high area under receiver operating curve (AUC) of serum SPARCL1 concentrations to predict in-hospital mortality (AUC, 0.822; 95% confidence interval, 0.734-0.891). In the multiple logistic regression analysis, serum SPARCL1 concentrations >3.29 ng/ml was independently associated with in-hospital mortality (odds ratio = 10.052, 95% confidence interval = 1.918-52.686, P = 0.006).

CONCLUSIONS

The novel findings of our study are that sTBI patients had an increase of serum SPARCL1 concentrations, and that there is an association between high serum SPARCL1 concentrations and sTBI mortality or trauma severity.

The relationship between serum fibrinogen-like protein 2 concentrations and 30-day mortality of patients with traumatic brain injury

BACKGROUND

Fibrinogen-like protein 2 (FGL2) is an inflammatory procoagulant protein. We discerned the impact of serum FGL2 on trauma severity and 30-day mortality in patients with traumatic brain injury (TBI).

METHODS

A total of 114 severe TBI patients were subjected to assessment of trauma severity using the Glasgow coma scale (GCS). Measurement of the serum concentrations of FGL2 was done. 114 matched control subjects for their age and sex were included for comparison of serum concentration of FGL2.

RESULTS

The concentration of FGL2 was dramatically increased in the patients as compared with the control subjects. FGL2 concentration was inversely correlated with GCS score among the patients. The non-survivors within 30 days exhibited substantially higher FGL2 concentrations than the alive. FGL2 concentrations discriminated the patients at risk of 30-day death with significantly high area under receiver operating characteristic curve. Serum FGL2 emerged as an independent predictor for mortality and overall survival at 30 days after head trauma.

CONCLUSIONS

Serum FGL2 is a promising biomarker for assessing the severity and prognosis in severe TBI.