Pediatric traumatic brain injury outcome

Pediatric traumatic brain injury outcome


Neuropsychological and behavioral outcomes for injured children vary with the severity of the injury, child age at injury, premorbid child characteristics, family factors, and the family’s socioeconomic status. Each of these factors needs to be taken into account when designing rehabilitation strategies and assessing factors related to outcomes 1)


The Functional Status Score (FSS) can be implemented as part of routine practice in two different healthcare systems and the relationships observed between the FSS and patient characteristics can serve as a baseline for work going forward in the coming years. As a field, establishing which outcomes tests can be readily administered while also measuring relevant outcomes for various populations of children with TBI is an essential next step in developing therapies for this disorder that is highly prevalent and morbid 2).


The multi-center, prospectively collected CENTER-TBI core and registry databases were screened and patients were included when younger than 18 years at enrollment and admitted to the regular ward (admission stratum) or intensive care unit (ICU stratum) following TBI. Patient demographics, injury causes, clinical findings, brain CT imaging details, and outcome (GOSE at 6 months follow-up) were retrieved and analyzed. Injury characteristics were compared between patients admitted to the regular ward and ICU and a multivariate analysis of factors predicting an unfavorable outcome (GOSE 1-4) was performed. Results from the core study were compared to the registry dataset which includes larger patient numbers but no follow-up data. Results: Two hundred and twenty-seven patients in the core dataset and 687 patients in the registry dataset were included in this study. In the core dataset, road-traffic incidents were the most common cause of injury overall and in the ICU stratum, while incidental falls were most common in the admission stratum. Brain injury was considered serious to severe in the majority of patients and concurrent injuries in other body parts were very common. Intracranial abnormalities were detected in 60% of initial brain CTs. Intra- and extracranial surgical interventions were performed in one-fifth of patients. The overall mortality rate was 3% and the rate of unfavorable outcomes was 10%, with those numbers being considerably higher among ICU patients. GCS and the occurrence of secondary insults could be identified as independent predictors of an unfavorable outcome 3).


There are few specific prognostic models specifically developed for the pediatric traumatic brain injury (TBI) population.


Fang et al. aimed to combine multiple machine learning approaches to building hybrid models for predicting the prognosis and length of hospital stay for adults and children with TBI.

They collected relevant clinical information from patients treated at the Neurosurgery Center of the Second Affiliated Hospital of Anhui Medical University between May 2017 and May 2022, of which 80% was used for training the model and 20% for testing via screening and data splitting. They trained and tested the machine learning models using 5 cross-validations to avoid overfitting. In the machine learning models, 11 types of independent variables were used as input variables and the Glasgow Outcome Scale score, was used to evaluate patients’ prognosis, and patient length of stay was used as the output variable. Once the models were trained, we obtained and compared the errors of each machine-learning model from 5 rounds of cross-validation to select the best predictive model. The model was then externally tested using clinical data of patients treated at the First Affiliated Hospital of Anhui Medical University from June 2021 to February 2022.

Results: The final convolutional neural network-support vector machine (CNN-SVM) model predicted the Glasgow Outcome Scale score with an accuracy of 93% and 93.69% in the test and external validation sets, respectively, and an area under the curve of 94.68% and 94.32% in the test and external validation sets, respectively. The mean absolute percentage error of the final built convolutional neural network-support vector regression (CNN-SVR) model predicting inpatient time in the test set and external validation set was 10.72% and 10.44%, respectively. The coefficient of determination (R2) was 0.93 and 0.92 in the test set and external validation set, respectively. Compared with a back-propagation neural network, CNN, and SVM models built separately, our hybrid model was identified to be optimal and had high confidence.

This study demonstrates the clinical utility of 2 hybrid models built by combining multiple machine learning approaches to accurately predict the prognosis and length of stay in hospital for adults and children with TBI. Application of these models may reduce the burden on physicians when assessing TBI and assist clinicians in the medical decision-making process 4).


Mikkonen et al., tested the predictive performance of existing prognostic tools, originally developed for the adult TBI population, in pediatric TBI patients requiring stays in the ICU.

They used the Finnish Intensive Care Consortium database to identify pediatric patients (< 18 years of age) treated in 4 academic ICUs in Finland between 2003 and 2013. They tested the predictive performance of 4 classification systems-the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) TBI model, the Helsinki CT score, the Rotterdam CT score, and the Marshall CT classification-by assessing the area under the receiver operating characteristic curve (AUC) and the explanatory variation (pseudo-R2 statistic). The primary outcome was 6-month functional outcome (favorable outcome defined as a Glasgow Outcome Scale score of 3-5).

Overall, 341 patients (median age 14 years) were included; of these, 291 patients had primary head CT scans available. The IMPACT core-based model showed an AUC of 0.85 (95% CI 0.78-0.91) and a pseudo-R2 value of 0.40. Of the CT scoring systems, the Helsinki CT score displayed the highest performance (AUC 0.84, 95% CI 0.78-0.90; pseudo-R2 0.39) followed by the Rotterdam CT score (AUC 0.80, 95% CI 0.73-0.86; pseudo-R2 0.34).

Prognostic tools originally developed for the adult TBI population seemed to perform well in pediatric TBI. Of the tested CT scoring systems, the Helsinki CT score yielded the highest predictive value 5).


1)

Keenan HT, Bratton SL. Epidemiology and outcomes of pediatric traumatic brain injury. Dev Neurosci. 2006;28(4-5):256-63. doi: 10.1159/000094152. PMID: 16943649.
2)

Bell MJ. Outcomes for Children With Traumatic Brain Injury-How Can the Functional Status Scale Contribute? Pediatr Crit Care Med. 2016 Dec;17(12):1185-1186. doi: 10.1097/PCC.0000000000000950. PMID: 27918390; PMCID: PMC5142208.
3)

Riemann L, Zweckberger K, Unterberg A, El Damaty A, Younsi A; Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Investigators and Participants. Injury Causes and Severity in Pediatric Traumatic Brain Injury Patients Admitted to the Ward or Intensive Care Unit: A Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study. Front Neurol. 2020 Apr 30;11:345. doi: 10.3389/fneur.2020.00345. PMID: 32425879; PMCID: PMC7205018.
4)

Fang C, Pan Y, Zhao L, Niu Z, Guo Q, Zhao B. A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study. J Med Internet Res. 2022 Dec 9;24(12):e41819. doi: 10.2196/41819. PMID: 36485032.
5)

Mikkonen ED, Skrifvars MB, Reinikainen M, Bendel S, Laitio R, Hoppu S, Ala-Kokko T, Karppinen A, Raj R. Validation of prognostic models in intensive care unit-treated pediatric traumatic brain injury patients. J Neurosurg Pediatr. 2019 Jun 7:1-8. doi: 10.3171/2019.4.PEDS1983. [Epub ahead of print] PubMed PMID: 31174193.

Deep Brain Stimulation for Post-Traumatic Stress Disorder

Deep Brain Stimulation for Post-Traumatic Stress Disorder

In 2018 the application of DBS for PTSD was still strictly investigational and animal models suggest that stimulation of the amygdalaventral striatumhippocampus, and prefrontal cortex may be effective in fear extinction and anxiety-like behavior 1).


Neuroimaging, preclinical, and preliminary clinical data suggested that the use of DBS for the treatment of PTSD may be practical 2).


PTSD is the only potential clinical indication for DBS that shows extensive animal research prior to human applications. Nevertheless, DBS for PTSD remains highly investigational. Despite several years of government funding of DBS research in view of treating severe PTSD in combat veterans, ethical dilemmas, recruitment difficulties, and issues related to use of DBS in such a complex and heterogenous disorder remain prevalent 3).


Hamani et al. treated four posttraumatic stress disorder (PTSD) patients with DBS delivered to the subgenual cingulum and the uncinate fasciculus. In addition to validated clinical scales, patients underwent neuroimaging studies and psychophysiological assessments of fear conditioning, extinction, and recall. They show that the procedure is safe and potentially effective (55% reduction in Clinical Administered PTSD Scale scores). Posttreatment imaging data revealed metabolic activity changes in PTSD neurocircuits. During psychophysiological assessments, patients with PTSD had higher skin conductance responses when tested for recall compared to healthy controls. After DBS, this objectively measured variable was significantly reduced. Last, they found that a ratio between recall of extinguished and nonextinguished conditioned responses had a strong correlation with clinical outcomes. As this variable was recorded at baseline, it may comprise a potential biomarker of treatment response 4).


Amygdala Deep Brain Stimulation for Post-Traumatic Stress Disorder

Functional neuroimaging studies have suggested that amygdala hyperactivity is responsible for the symptoms of PTSD. Deep brain stimulation (DBS) can functionally reduce the activity of a cerebral target by delivering an electrical signal through an electrode. We tested whether DBS of the amygdala could be used to treat PTSD symptoms. Rats traumatized by inescapable shocks, in the presence of an unfamiliar object, develop the tendency to bury the object when re-exposed to it several days later. This behavior mimics the symptoms of PTSD. 10 Sprague-Dawley rats underwent the placement of an electrode in the right basolateral nucleus of the amygdala (BLn). The rats were then subjected to a session of inescapable shocks while being exposed to a conspicuous object (a ball). Five rats received DBS treatment while the other 5 rats did not. After 7 days of treatment, the rats were re-exposed to the ball and the time spent burying it under the bedding was recorded. Rats treated with BLn DBS spent on average 13 times less time burying the ball than the sham control rats. The treated rats also spent 18 times more time exploring the ball than the sham control rats. In conclusion, the behavior of treated rats in this PTSD model was nearly normalized. We argue that these results have direct implications for patients suffering from treatment-resistant PTSD by offering a new therapeutic strategy 5)


1)

Lavano A, Guzzi G, Della Torre A, Lavano SM, Tiriolo R, Volpentesta G. DBS in Treatment of Post-Traumatic Stress Disorder. Brain Sci. 2018 Jan 20;8(1):18. doi: 10.3390/brainsci8010018. PMID: 29361705; PMCID: PMC5789349.
2)

Reznikov R, Hamani C. Posttraumatic Stress Disorder: Perspectives for the Use of Deep Brain Stimulation. Neuromodulation. 2016 Dec 19. doi: 10.1111/ner.12551. [Epub ahead of print] Review. PubMed PMID: 27992092.
3)

Meeres J, Hariz M. Deep Brain Stimulation for Post-Traumatic Stress Disorder: A Review of the Experimental and Clinical Literature. Stereotact Funct Neurosurg. 2022 Jan 3:1-13. doi: 10.1159/000521130. Epub ahead of print. PMID: 34979516.
4)

Hamani C, Davidson B, Corchs F, Abrahao A, Nestor SM, Rabin JS, Nyman AJ, Phung L, Goubran M, Levitt A, Talakoub O, Giacobbe P, Lipsman N. Deep brain stimulation of the subgenual cingulum and uncinate fasciculus for the treatment of posttraumatic stress disorder. Sci Adv. 2022 Dec 2;8(48):eadc9970. doi: 10.1126/sciadv.adc9970. Epub 2022 Dec 2. PMID: 36459550.
5)

Langevin JP, De Salles AA, Kosoyan HP, Krahl SE. Deep brain stimulation of the amygdala alleviates post-traumatic stress disorder symptoms in a rat model. J Psychiatr Res. 2010 Dec;44(16):1241-5. doi: 10.1016/j.jpsychires.2010.04.022. Epub 2010 May 26. PMID: 20537659.

Serum Biomarkers for Traumatic Brain Injury

Serum Biomarkers for Traumatic Brain Injury

Traumatic brain injury (TBI) is frequently associated with abnormal blood-brain barrier function, resulting in the release of factors that can be used as molecular biomarkers of TBI, among them GFAPUCH-L1S100B, and NSE. Although many experimental studies have been conducted, clinical consolidation of these biomarkers is still needed to increase the predictive power and reduce the poor outcome of TBI. Interestingly, several of these TBI biomarkers are oxidatively modified to carbonyl groups, indicating that markers of oxidative stress could be of predictive value for the selection of therapeutic strategies 1).


Unlike other organ-based diseases where rapid diagnosis employing biomarkers from blood tests are clinically essential to guide diagnosis and treatment, there are no rapid, definitive diagnostic blood tests for TBI. Over the last decade there has been a myriad of studies exploring many promising biomarkers. Despite the large number of published studies there is still a lack of any FDA-approved biomarkers for clinical use in adults and children. There is now an important need to validate and introduce them into the clinical setting 2).


Richter et al. aimed to assess if day of injury serum protein biomarkers could identify critically ill TBI patients in whom the risks of transfer are compensated by the likelihood of detecting management-altering neuroimaging findings.

Data were obtained from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. Eligibility criteria included: TBI patients aged ≥ 16 years, Glasgow Coma Score (GCS) < 13 or patient intubated with unrecorded pre-intubation GCS, CT with Marshall score < 3, serum biomarkers (GFAP, NFL, NSE, S100B, Tau, UCH-L1) sampled ≤ 24 h of injury, MRI < 30 days of injury. The degree of axonal injury on MRI was graded using the Adams-Gentry classification. The association between serum concentrations of biomarkers and Adams-Gentry stage was assessed and the optimum threshold concentration identified, assuming different minimum sensitivities for the detection of brainstem injury (Adams-Gentry stage 3). A cost-benefit analysis for the USA and UK health care settings was also performed.

Among 65 included patients (30 moderate-severe, 35 unrecorded) axonal injury was detected in 54 (83%) and brainstem involvement in 33 (51%). In patients with moderate-severe TBI, brainstem injury was associated with higher concentrations of NSETauUCH-L1 and GFAP. If the clinician did not want to miss any brainstem injury, NSE could have avoided MRI transfers in up to 20% of patients. If a 94% sensitivity was accepted considering potential transfer-related complications, GFAP could have avoided 30% of transfers. There was no added net cost, with savings up to £99 (UK) or $612 (US). No associations between proteins and axonal injury were found in intubated patients without a recorded pre-intubation GCS.

Serum protein biomarkers show potential to safely reduce the number of transfers to MRI in critically ill patients with moderate-severe TBI at no added cost 3).

Mozaffari et al. created a comprehensive appraisal of the most prominent serum biomarkers used in the assessment and care of TBI.The PubMed, Scopus, Cochrane, and Web of Science databases were queried with the terms “biomarker” and “traumatic brain injury” as search terms with only full-text, English articles within the past 10 years selected. Non-human studies were excluded, and only adult patients fell within the purview of this analysis. A total of 528 articles were analyzed in the initial search with 289 selected for screening. A further 152 were excluded for primary screening. Of the remaining 137, 54 were included in the final analysis. Serum biomarkers were listed into the following broad categories for ease of discussion: immune markers and markers of inflammationhormones as biomarkers, coagulation and vasculature, genetic polymorphisms, antioxidants and oxidative stressapoptosis and degradation pathways, and protein markers. Glial fibrillary acidic protein(GFAP), S100, and neurons specific enolase (NSE) were the most prominent and frequently cited markers. Amongst these three, no single serum biomarker demonstrated neither superior sensitivity nor specificity compared to the other two, therefore noninvasive panels should incorporate these three serum biomarkers to retain sensitivity and maximize specificity for TBI 4).


1)

Mendes Arent A, de Souza LF, Walz R, Dafre AL. Perspectives on Molecular Biomarkers of Oxidative Stress and Antioxidant Strategies in Traumatic Brain Injury. Biomed Res Int. 2014;2014:723060. Epub 2014 Feb 13. Review. PubMed PMID: 24689052.
2)

Papa L, Edwards D, Ramia M. Exploring Serum Biomarkers for Mild Traumatic Brain Injury. In: Kobeissy FH, editor. Brain Neurotrauma: Molecular, Neuropsychological, and Rehabilitation Aspects. Boca Raton (FL): CRC Press/Taylor & Francis; 2015. Chapter 22. PubMed PMID: 26269900.
3)

Richter S, Winzeck S, Czeiter E, Amrein K, Kornaropoulos EN, Verheyden J, Sugar G, Yang Z, Wang K, Maas AIR, Steyerberg E, Büki A, Newcombe VFJ, Menon DK; Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury Magnetic Resonance Imaging (CENTER-TBI MRI) Sub-study Participants and Investigators. Serum biomarkers identify critically ill traumatic brain injury patients for MRI. Crit Care. 2022 Nov 29;26(1):369. doi: 10.1186/s13054-022-04250-3. PMID: 36447266.
4)

Mozaffari K, Dejam D, Duong C, Ding K, French A, Ng E, Preet K, Franks A, Kwan I, Phillips HW, Kim DY, Yang I. Systematic Review of Serum Biomarkers in Traumatic Brain Injury. Cureus. 2021 Aug 10;13(8):e17056. doi: 10.7759/cureus.17056. PMID: 34522534; PMCID: PMC8428323.

Traumatic brain injury epidemiology in Europe

Traumatic brain injury epidemiology in Europe

In 2018 a systematic review provided a comprehensive, up-to-date summary of traumatic brain injury (TBI) epidemiology in Europe, describing incidence, mortality, age, and sex distribution, plus severity, mechanism of injury, and time trends. PubMed, CINAHL, EMBASE, and Web of Science were searched in January 2015 for observational, descriptive, English language studies reporting incidence, mortality, or case fatality of TBI in Europe. There were no limitations according to date, age, or TBI severity. Methodological quality was assessed using the Methodological Evaluation of Observational Research checklist. Data were presented narratively. Sixty-six studies were included in the review. Country-level data were provided in 22 studies, regional population or treatment center catchment area data were reported by 44 studies. Crude incidence rates varied widely. For all ages and TBI severities, crude incidence rates ranged from 47.3 per 100,000, to 694 per 100,000 population per year (country-level studies) and 83.3 per 100,000, to 849 per 100,000 population per year (regional-level studies). Crude mortality rates ranged from 9 to 28.10 per 100,000 population per year (country-level studies), and 3.3 to 24.4 per 100,000 population per year (regional-level studies.) The most common mechanisms of injury were traffic accidents and falls. Over time, the contribution of traffic accidents to total TBI events may be reducing. Case ascertainment and definitions of TBI are variable. Improved standardization would enable more accurate comparisons 1).


In 2016 aimed to estimate the hospital-based incidence, population-wide mortality, and the contribution of TBI to injury-related mortalities in European countries, and to provide European summary estimates for these indicators.

For this cross-sectional analysis, we obtained population data from Eurostat for hospital discharges and causes of death in European countries in 2012. Outcomes of interest were TBIs that required hospital admission or were fatal. We calculated age-adjusted hospital discharge rates and mortality rates and extrapolated data to 28 European Union countries and all 48 states in Europe. We present between-country comparisons, pooled age-adjusted rates, and comparisons with all-injury rates.

In 2012, 1 375 974 hospital discharges (data from 24 countries) and 33 415 deaths (25 countries) related to TBI were identified. The pooled age-adjusted hospital discharge rate was 287·2 per 100 000 (95% CI 232·9-341·5) and the pooled age-adjusted mortality rate was 11·7 per 100 000 (9·9-13·6). TBI caused 37% (95% CI 36-38) of all injury-related deaths in the analysed countries. Extrapolating our results, we estimate 56 946 (95% CI 47 286-66 099) TBI-related deaths and 1 445 526 (1 172 996-1 717 039) hospital discharges occurred in 2012 in the European Union (population 508·5 million) and about 82 000 deaths and about 2·1 million hospital discharges in the whole of Europe (population 737 million). We noted substantial between-country differences.

TBI is an important cause of death and hospital admissions in Europe. The substantial between-country differences observed warrant further study and suggest that the true burden of TBI in Europe has not yet been captured. Rigorous epidemiological studies are needed to fully quantify the effect of TBI on society. Despite a great degree of consistency in data reporting across countries already being achieved, further efforts in this respect could improve the validity of between-country comparisons 2).


In 2015 a total, 28 epidemiological studies on TBI from 16 European countries were identified in the literature. A great variation was found in case definitions and case ascertainment between studies. Falls and road traffic accidents (RTA) were the two most frequent causes of TBI, with falls being reported more frequently than RTA 3).

A search was conducted in the PubMed electronic database using the terms: epidemiology, incidence, brain injur*, head injur* and Europe. Only articles published in English and reporting on data collected in Europe between 1990 and 2014 were included. In total, 28 epidemiological studies on TBI from 16 European countries were identified in the literature. A great variation was found in case definitions and case ascertainment between studies. Falls and road traffic accidents (RTA) were the two most frequent causes of TBI, with falls being reported more frequently than RTA. In most of the studies a peak TBI incidence was seen in the oldest age groups. In the meta-analysis, an overall incidence rate of 262 per 100,000 for admitted TBI was derived.

Interpretation of published epidemiologic studies is confounded by differences in inclusion criteria and case ascertainment. Nevertheless, changes in epidemiological patterns are found: falls are now the most common cause of TBI, most notably in elderly patients. Improvement of the quality of standardised data collection for TBI is mandatory for reliable monitoring of epidemiological trends and to inform appropriate targeting of prevention campaigns 4).

In 2006 it was difficult to reach a consensus on all epidemiological findings across the 23 published European studies because of critical differences in methods employed across the reports 5).

In a retrospectivelongitudinal study of all TBI patients treated in ICU between 2013-2018, 77% (n=171) were male and the median age was 46 (Q1-Q3: 28-62). The most common mechanism of injury was fall from less than two meters (<2m) followed by road traffic accidents (RTA). The proportion of injuries due to RTA increased over the six-year period (p=0.006). 41.4% (n=92) of injuries had reported alcohol involvement. Patients with falls <2m had double the median age and double the rate of alcohol involvement compared to those suffering RTA (p<0.001, p<0.001). The neurosurgical intervention rate was 74% (n=165). The median duration of ICU admission and of intracranial pressure monitoring, advanced ventilation, and inotropic therapy increased over the six-year period (p=0.031, p=0.038, p=0.033, p<0.001). This study’s findings could inform precise and impactful public prevention measures. The increasing duration of ICU admission and of other interventions should be examined further for their effect on patient outcomes and resource consumption 6).

Traumatic brain injury epidemiology in Finland

A coordinated strategy to evaluate this public health problem in Romania would first of all rely on a related advanced monitoring system, to provide precise information about the epidemiology, clinical and paraclinical data, but concerning the social and economic connected consequences, too 7).

Traumatic brain injury epidemiology in Spain


1)

Brazinova A, Rehorcikova V, Taylor MS, Buckova V, Majdan M, Psota M, Peeters W, Feigin V, Theadom A, Holkovic L, Synnot A. Epidemiology of Traumatic Brain Injury in Europe: A Living Systematic Review. J Neurotrauma. 2018 Dec 19. doi: 10.1089/neu.2015.4126. Epub ahead of print. PMID: 26537996.
2)

Majdan M, Plancikova D, Brazinova A, Rusnak M, Nieboer D, Feigin V, Maas A. Epidemiology of traumatic brain injuries in Europe: a cross-sectional analysis. Lancet Public Health. 2016 Dec;1(2):e76-e83. doi: 10.1016/S2468-2667(16)30017-2. Epub 2016 Nov 29. PMID: 29253420.
3) , 4)

Peeters W, van den Brande R, Polinder S, Brazinova A, Steyerberg EW, Lingsma HF, Maas AI. Epidemiology of traumatic brain injury in Europe. Acta Neurochir (Wien). 2015 Oct;157(10):1683-96. doi: 10.1007/s00701-015-2512-7. Epub 2015 Aug 14. PubMed PMID: 26269030.
5)

Tagliaferri F, Compagnone C, Korsic M, Servadei F, Kraus J. A systematic review of brain injury epidemiology in Europe. Acta Neurochir (Wien). 2006 Mar;148(3):255-68; discussion 268. Review. PubMed PMID: 16311842.
6)

Forrest C, Healy V, Plant R. Temporal Trends in Traumatic Brain Injury. Ir Med J. 2022 May 25;115(5):597. PMID: 35696279.
7)

Popescu C, Anghelescu A, Daia C, Onose G. Actual data on epidemiological evolution and prevention endeavours regarding traumatic brain injury. J Med Life. 2015 Jul-Sep;8(3):272-7. Review. PubMed PMID: 26351526; PubMed Central PMCID: PMC4556905.

Severe traumatic brain injury outcome

Severe traumatic brain injury outcome

Females exhibited more favorable cerebral physiology post-Traumatic Brain Injury, particularly better mitochondrial function, and reduced excitotoxicity, but this did not translate into better clinical outcomes compared to males. Future studies need to further explore potential sex differences in secondary injury mechanisms in TBI 1).


deep learning model of head computed tomography and clinical information can be used to predict 6-month severe traumatic brain injury outcome 2).


Younger age, modified Fisher scale (mFS) score, and Intracerebral hemorrhage volume are associated with Intracranial pressure elevation in patients with a severe traumatic brain injury. Imaging features may stratify patients by their risk of subsequent ICP elevation 3).


There has been a secular trend towards reduced incidence of severe traumatic brain injury in the first world, driven by public health interventions such as seatbelt legislation, helmet use, and workplace health and safety regulations. This has paralleled improved outcomes following TBI delivered in a large part by the widespread establishment of specialised neurointensive care 4).

The impact of a moderate to severe brain injury depends on the following:

Severity of initial injury

Rate/completeness of physiological recovery

Functions affected

Meaning of dysfunction to the individual

Resources available to aid recovery

Areas of function not affected by TBI

see Effect of trauma center designation in severe traumatic brain injury outcome


Mortality or severe disability affects the majority of patients after severe traumatic brain injury (TBI). Adherence to the brain trauma foundation severe traumatic brain injury guidelines has overall improved outcomes; however, traditional as well as novel interventions towards intracranial hypertension and secondary brain injury have come under scrutiny after series of negative randomized controlled trials. In fact, it would not be unfair to say there has been no single major breakthrough in the management of severe TBI in the last two decades. One plausible hypothesis for the aforementioned failures is that by the time treatment is initiated for neuroprotection, or physiologic optimization, irreversible brain injury has already set in. Lazaridis et al., and others, have developed predictive models based on machine learning from continuous time series of intracranial pressure and partial pressure of brain tissue oxygen. These models provide accurate predictions of physiologic crises events in a timely fashion, offering the opportunity for an earlier application of targeted interventions. In a article, Lazaridis et al., review the rationale for prediction, discuss available predictive models with examples, and offer suggestions for their future prospective testing in conjunction with preventive clinical algorithm5).


Determining the prognostic significance of clinical factors for patients with severe head injury can lead to an improved understanding of the pathophysiology of head injury and to improvement in therapy. A technique known as the sequential Bayes method has been used previously for the purpose of prognosis. The application of this method assumes that prognostic factors are statistically independent. It is now known that they are not. Violation of the assumption of independence may produce errors in determining prognosis. As an alternative technique for predicting the outcome of patients with severe head injury, a logistic regression model is proposed. A preliminary evaluation of the method using data from 115 patients with head injury shows the feasibility of using early data to predict outcome accurately and of being able to rank input variables in order of their prognostc significance. 6).


A prospective and consecutive series of 225 patients with severe head injuries who were managed in a uniform way was analyzed to relate outcome to several clinical variables. Good recovery or moderate disability were achieved by 56% of the patients, 10% remained severely disabled or vegetative, and 34% died. Factors important in predicting a poor outcome included the presence of intracranial hematoma, increasing agemotor impairment, impaired or absent eye movements or pupillary light reflexes, early hypotensionhypoxemia or hypercarbia, and raised intracranial pressure over 20 mm Hg despite artificial ventilation. Most of these predictive factors were assessed on admission, but a subset of 158 patients was identified in whom coma was present on admission and was known to have persisted at least until the following day. Although the mortality in this subset (40%) was higher than in the total series, it was lower than in several comparable reported series of patients with severe head injury. Predictive correlations were equally strong in the entire series and in the subset of 158 patients with coma. A plea is made for inclusion in the definition of “severe head injury” of all patients who do not obey commands or utter recognizable words on admission to the hospital after early resuscitation 7).


Survival rate of isolated severe TBI patients who required an emergent neurosurgical intervention could be time dependent. These patients might benefit from expedited process (computed tomographic scan, neurosurgical consultation, etc.) to shorten the time to surgical intervention 8).

The impact of a moderate to severe brain injury can include:

Cognitive deficits including difficulties with:

Attention Concentration Distractibility Memory Speed of Processing Confusion Perseveration Impulsiveness Language Processing “Executive functions” Speech and Language

not understanding the spoken word (receptive aphasia) difficulty speaking and being understood (expressive aphasia) slurred speech speaking very fast or very slow problems reading problems writing Sensory

difficulties with interpretation of touch, temperature, movement, limb position and fine discrimination Perceptual

the integration or patterning of sensory impressions into psychologically meaningful data Vision

partial or total loss of vision weakness of eye muscles and double vision (diplopia) blurred vision problems judging distance involuntary eye movements (nystagmus) intolerance of light (photophobia) Hearing

decrease or loss of hearing ringing in the ears (tinnitus) increased sensitivity to sounds Smell

loss or diminished sense of smell (anosmia) Taste

loss or diminished sense of taste Seizures

the convulsions associated with epilepsy that can be several types and can involve disruption in consciousness, sensory perception, or motor movements Physical Changes

Physical paralysis/spasticity Chronic pain Control of bowel and bladder Sleep disorders Loss of stamina Appetite changes Regulation of body temperature Menstrual difficulties Social-Emotional

Dependent behaviors Emotional ability Lack of motivation Irritability Aggression Depression Disinhibition Denial/lack of awareness


Both single predictors from early clinical examination and multiple hospitalization variables/parameters can be used to determine the long-term prognosis of TBI. Predictive models like the IMPACT or CRASH prognosis calculator (based on large sample sizes) can predict mortality and unfavorable outcomes. Moreover, imaging techniques like MRI (Magnetic Resonance Imaging) can also predict consciousness recovery and mental recovery in severe TBI, while biomarkers associated with stress correlate with, and hence can be used to predict, severity and mortality. All predictors have limitations in clinical application. Further studies comparing different predictors and models are required to resolve limitations of current predictors 9).

Clinical outcome prediction following traumatic brain injury (TBI) is a widely investigated field of research. Several outcome prediction models have been developed for prognosis after TBI. There are two main prognostic models: International Mission for Prognosis and Clinical Trials in Traumatic Brain Injury (IMPACT) prognosis calculator and the Corticosteroid Randomization after Significant Head Injury (CRASH) prognosis calculator. The prognosis model has three or four levels:

(1) model A included age, motor GCS, and pupil reactivity

(2) model B included predictors from model A with CT characteristics

(3) model C included predictors from model B with laboratory parameters.

In consideration of the fact that interventions after admission, such as ICP management also have prognostic value for outcome predictions and may improve the models’ performance, Yuan F et al developed another prediction model (model D) which includes ICP. With the development of molecular biology, a handful of brain injury biomarkers were reported that may improve the predictive power of prognostic models, including neuron-specific enolase (NSE), glial fibrillary acid protein (GFAP), S-100β protein, tumour necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), myelin basic protein (MBP), cleaved tau protein (C-tau), spectrin breakdown products (SBDPs), and ubiquitin C-terminal hydrolase-L1 (UCH-L1), and sex hormones. A total of 40 manuscripts reporting 11 biomarkers were identified in the literature. Many substances have been implicated as potential biomarkers for TBI; however, no single biomarker has shown the necessary sensitivity and specificity for predicting outcome. The limited number of publications in this field underscores the need for further investigation. Through fluid biomarker analysis, the advent of multi-analyte profiling technology has enabled substantial advances in the diagnosis and treatment of a variety of conditions. Application of this technology to create a bio-signature for TBI using multiple biomarkers in combination will hopefully facilitate much-needed advances. We believe that further investigations about brain injury biomarkers may improve the predictive power of the contemporary outcome calculators and prognostic models, and eventually improve the care of patients with TBI 10).


Injury site, injury type, and injury degree are the main risk factors for post-traumatic epilepsyTraumatic brain injury outcome can be affected by early post-traumatic epilepsy11).

Insurance and racial disparities continue to exist for TBI patients. Insurance status appears to have an impact on short- and long-term outcomes to a greater degree than patient race 12).

CRASH

IMPACT

Traumatic brain injury mortality.

see Quality of Life after Brain Injury.

Traumatic brain injury complications.

Statins have been shown to improve traumatic brain injury outcome in animal models. The aim of a study was to determine the effect of preinjury statins on outcomes in TBI patients.

Lokhandwala et al. performed a 4-y (2014-2017) review of a TBI database and included all patients aged ≥18 y with severe isolated TBI. Patients were stratified into those who were on statins and those who were not and were matched (1:2 ratio) using propensity score matching. The primary outcome was in-hospital mortality. The secondary outcomes were skilled nursing facility disposition, Glasgow Outcome Scale-extended score, and hospital and intensive care unit length of stay (LOS).

They identified 1359 patients, of which 270 were matched (statin: 90, no-statin: 180). Mean age was 55 ± 8y, median Glasgow Coma Scale was 10 (8-12), and median head-abbreviated injury scale was 3 (3-5). Matched groups were similar in age, mechanism of injury, Glasgow Coma Scale, Injury Severity Score, neurosurgical intervention, type and size of intracranial hemorrhage, and preinjury anticoagulant or antiplatelet use. The overall in-hospital mortality rate was 18%. Patients who received statins had lower rates of in-hospital mortality (11% versus 21%, P = 0.01), skilled nursing facility disposition (19% versus 28%; P = 0.04), and a higher median Glasgow Outcome Scale-extended (11 [9-13] versus 9 [8-10]; P = 0.04). No differences were found between the two groups in terms of hospital LOS (6 [4-9] versus 5 [3-8]; P = 0.34) and intensive care unit LOS (3 [3-6] versus 4 [3-5]; P = 0.09).

Preinjury statin use in isolated traumatic brain injury patients is associated with improved outcomes. This finding warrants further investigations to evaluate the potential beneficial role of statins as a therapeutic drug in a TBI 13).


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Svedung Wettervik TM, Hånell A, Howells T, Enblad P, Lewén A. Females Exhibit Better Cerebral Pressure Autoregulation, Less Mitochondrial Dysfunction, and Reduced Excitotoxicity following Severe Traumatic Brain Injury. J Neurotrauma. 2022 May 19. doi: 10.1089/neu.2022.0097. Epub ahead of print. PMID: 35587145.
2)

Pease M, Arefan D, Barber J, Yuh E, Puccio A, Hochberger K, Nwachuku E, Roy S, Casillo S, Temkin N, Okonkwo DO, Wu S; TRACK-TBI Investigators. Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans. Radiology. 2022 Apr 26:212181. doi: 10.1148/radiol.212181. Epub ahead of print. PMID: 35471108.
3)

Murray NM, Wolman DN, Mlynash M, Threlkeld ZD, Christensen S, Heit JJ, Harris OA, Hirsch KG. Early Head Computed Tomography Abnormalities Associated with Elevated Intracranial Pressure in Severe Traumatic Brain Injury. J Neuroimaging. 2020 Nov 4. doi: 10.1111/jon.12799. Epub ahead of print. PMID: 33146933.
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Khellaf A, Khan DZ, Helmy A. Recent advances in traumatic brain injury. J Neurol. 2019 Sep 28. doi: 10.1007/s00415-019-09541-4. [Epub ahead of print] PubMed PMID: 31563989.
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Lazaridis C, Rusin CG, Robertson CS. Secondary Brain Injury: Predicting and Preventing Insults. Neuropharmacology. 2018 Jun 6. pii: S0028-3908(18)30279-X. doi: 10.1016/j.neuropharm.2018.06.005. [Epub ahead of print] Review. PubMed PMID: 29885419.
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Stablein DM, Miller JD, Choi SC, Becker DP. Statistical methods for determining prognosis in severe head injury. Neurosurgery. 1980 Mar;6(3):243-8. PubMed PMID: 6770283.
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Miller JD, Butterworth JF, Gudeman SK, Faulkner JE, Choi SC, Selhorst JB, Harbison JW, Lutz HA, Young HF, Becker DP. Further experience in the management of severe head injury. J Neurosurg. 1981 Mar;54(3):289-99. PubMed PMID: 7463128.
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Matsushima K, Inaba K, Siboni S, Skiada D, Strumwasser AM, Magee GA, Sung GY, Benjaminm ER, Lam L, Demetriades D. Emergent operation for isolated severe traumatic brain injury: Does time matter? J Trauma Acute Care Surg. 2015 Aug 28. [Epub ahead of print] PubMed PMID: 26317818.
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Gao L, Wu X. Prediction of clinical outcome in severe traumatic brain injury. Front Biosci (Landmark Ed). 2015 Jan 1;20:763-771. PubMed PMID: 25553477.
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Gao J, Zheng Z. Development of prognostic models for patients with traumatic brain injury: a systematic review. Int J Clin Exp Med. 2015 Nov 15;8(11):19881-5. eCollection 2015. Review. PubMed PMID: 26884899; PubMed Central PMCID: PMC4723744.
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Liu Z, Chen Q, Chen Z, Wang J, Tian D, Wang L, Liu B, Zhang S. Clinical analysis on risk factors and prognosis of early post-traumatic epilepsy. Arq Neuropsiquiatr. 2019 Jul 15;77(6):375-380. doi: 10.1590/0004-282×20190071. PubMed PMID: 31314838.
12)

Schiraldi M, Patil CG, Mukherjee D, Ugiliweneza B, Nuño M, Lad SP, Boakye M. Effect of Insurance and Racial Disparities on Outcomes in Traumatic Brain Injury. J Neurol Surg A Cent Eur Neurosurg. 2015 Mar 23. [Epub ahead of print] PubMed PMID: 25798799.
13)

Lokhandwala A, Hanna K, Gries L, Zeeshan M, Ditillo M, Tang A, Hamidi M, Joseph B. Preinjury Statins Are Associated With Improved Survival in Patients With Traumatic Brain Injury. J Surg Res. 2019 Aug 16;245:367-372. doi: 10.1016/j.jss.2019.07.081. [Epub ahead of print] PubMed PMID: 31425877.

Traumatic brain injury mortality prediction

Traumatic brain injury mortality prediction

Identifying patients with high risk of traumatic brain injury mortality is important to maximize the resource for trauma care, and so that family members receive appropriate counsel and treatment decisions 1) 2).


Zheng et al. developed and validate a radiomic prediction model using initial non-contrast computed tomography (CT) at admission to predict in-hospital mortality in patients with traumatic brain injury (TBI).

A total of 379 TBI patients from three cohorts were categorized into training, internal validation, and external validation sets. After filtering the unstable features with the minimum redundancy maximum relevance approach, the CT-based radiomics signature was selected by using the least absolute shrinkage and selection operator (LASSO) approach. A personalized predictive nomogram incorporating the radiomic signature and clinical features was developed using a multivariate logistic model to predict in-hospital mortality in patients with TBI. The calibration, discrimination, and clinical usefulness of the radiomics signature and nomogram were evaluated.

The radiomic signature consisting of 12 features had areas under the curve (AUCs) of 0.734, 0.716, and 0.706 in the prediction of in-hospital mortality in the internal and two external validation cohorts. The personalized predictive nomogram integrating the radiomic and clinical features demonstrated significant calibration and discrimination with AUCs of 0.843, 0.811, and 0.834 in the internal and two external validation cohorts. Based on decision curve analysis (DCA), both the radiomic features and nomogram were found to be clinically significant and useful.

This predictive nomogram incorporating the CT-based radiomic signature and clinical features had maximum accuracy and played an optimized role in the early prediction of in-hospital mortality. The results of this study provide vital insights for the early warning of death in TBI patients 3).


One widely applied predictor of mortality outcome is the Trauma and Injury Severity Score (TRISS), which shows good discrimination in identifying the patients with TBI at high risk of mortality 4).


The Corticosteroid Randomization after Significant Head Injury CRASH and the International Mission for Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury [IMPACT]) based on large clinical trial datasets have shown good discrimination and have enabled accurate outcome predictions 5) 6) 7).


A study predicts a strong correlation between respiratory failure, pathological pupillary response, a higher ISS, and substantial midline shift with poor outcomes in elderly patients sustaining an isolated severe TBI 8).


Nine studies demonstrated prognostic value of the FOUR score in predicting mortality and functional outcomes. Thirty-two studies demonstrated equivalency or superiority of the FOUR score compared to Glasgow Coma Scale in prediction of mortality and functional outcomes.

The FOUR score has been shown to be a useful outcome predictor in many patients with depressed level of consciousness. It displays good inter-rater reliability among physicians and nurses 9).


The purpose of a study was to build a model of machine learning (ML) for the prediction of mortality in patients with isolated moderate and severe traumatic brain injury (TBI).

Hospitalized adult patients registered in the Trauma Registry System between January 2009 and December 2015 were enrolled in this study. Only patients with an Abbreviated Injury Scale (AIS) score ≥ 3 points related to head injuries were included in this study. A total of 1734 (1564 survival and 170 non-survival) and 325 (293 survival and 32 non-survival) patients were included in the training and test sets, respectively.

Using demographics and injury characteristics, as well as patient laboratory data, predictive tools (e.g., [logistic regression]] [LR], support vector machine [SVM], decision tree [DT], naive Bayes [NB], and artificial neural networks [ANN]) were used to determine the mortality of individual patients. The predictive performance was evaluated by accuracy, sensitivity, and specificity, as well as by area under the curve (AUC) measures of receiver operator characteristic curves. In the training set, all five ML models had a specificity of more than 90% and all ML models (except the NB) achieved an accuracy of more than 90%. Among them, the ANN had the highest sensitivity (80.59%) in mortality prediction. Regarding performance, the ANN had the highest AUC (0.968), followed by the LR (0.942), SVM (0.935), NB (0.908), and DT (0.872). In the test set, the ANN had the highest sensitivity (84.38%) in mortality prediction, followed by the SVM (65.63%), LR (59.38%), NB (59.38%), and DT (43.75%).

The ANN model provided the best prediction of mortality for patients with isolated moderate and severe TBI 10).


A study concluded that The Marshall CT score was more accurate for prediction of mortality on 2 weeks, at one month, and at three months were than The Marshall CT score with higher ROC. The correlation of the Rotterdam CT score with mortality was significant 11).


The GCS as a single variable may have limited value as a predictor of functional outcome 12).


Serial basal blood glucose, serum insulin, cortisol, growth hormone, glucagon and catecholamine examinations were performed in 81 brain-injured patients. 32 patients with severe injuries of other parts of the body (chest, abdomen, limbs or polytrauma), and 17 patients with non-traumatic acute brain lesions served as double control. In the brain-injured patients there is a close relation between changes of the state of consciousness and those of basal blood glucose levels: the deeper coma the higher and wider is the pathological glucose-level range. Four types of blood-glucose changes could be identified in the background of which different alterations of each hormone level were observed. Fatal outcome could be predicted in a non-diabetic patient in the first days when seeing: 1) Fasting hyperglycaemia above 14 mmol/l; 2) Fluctuating basal blood glucose levels between 5 and 22 mmol/l; 3) Deeply depressed and unchanged basal insulin level; 4) Extremely high cortisol level; 5) Decreased plasma epinephrine level. These changes in the carbohydrate metabolism seen after acute brain lesions are not identical to diabetes mellitus 13).

Artificial neural network for traumatic brain injury mortality prediction.


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Densmore JC, Lim HJ, Oldham KT, Guice KS. Outcomes and delivery of care in pediatric injury. Journal of pediatric surgery. 2006; 41(1):92–8; discussion -8. Epub 2006/01/18. https://doi.org/10.1016/j. jpedsurg.2005.10.013 PMID: 16410115.
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Rogers SC, Campbell BT, Saleheen H, Borrup K, Lapidus G. Using trauma registry data to guide injury prevention program activities. The Journal of trauma. 2010; 69(4 Suppl):S209–13. Epub 2010/10/22. https://doi.org/10.1097/TA.0b013e3181f1e9fe PMID: 20938310.
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Zheng RZ, Zhao ZJ, Yang XT, Jiang SW, Li YD, Li WJ, Li XH, Zhou Y, Gao CJ, Ma YB, Pan SM, Wang Y. Initial CT-based radiomics nomogram for predicting in-hospital mortality in patients with traumatic brain injury: a multicenter development and validation study. Neurol Sci. 2022 Feb 24. doi: 10.1007/s10072-022-05954-8. Epub ahead of print. PMID: 35199252.
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Wong GK, Teoh J, Yeung J, Chan E, Siu E, Woo P, et al. Outcomes of traumatic brain injury in Hong Kong: validation with the TRISS, CRASH, and IMPACT models. Journal of clinical neuroscience: official journal of the Neurosurgical Society of Australasia. 2013; 20(12):1693–6. Epub 2013/09/03. https://doi. org/10.1016/j.jocn.2012.12.032 PMID: 23993210.
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Han J, King NK, Neilson SJ, Gandhi MP, Ng I. External validation of the CRASH and IMPACT prognostic models in severe traumatic brain injury. J Neurotrauma. 2014; 31(13):1146–52. Epub 2014/02/27. https://doi.org/10.1089/neu.2013.3003 PMID: 24568201.
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Sun H, Lingsma HF, Steyerberg EW, Maas AI. External Validation of the International Mission for Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury: Prognostic Models for Traumatic Brain Injury on the Study of the Neuroprotective Activity of Progesterone in Severe Traumatic Brain Injuries Trial. J Neurotrauma. 2016; 33(16):1535–43. Epub 2015/12/15. https://doi.org/10.1089/neu.2015.4164 PMID: 26652051.
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Perel P, Arango M, Clayton T, Edwards P, Komolafe E, Poccock S, et al. Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients. BMJ. 2008; 336(7641):425–9. Epub 2008/02/14. https://doi.org/10.1136/bmj.39461.643438.25 PMID: 18270239
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Ostermann RC, Joestl J, Tiefenboeck TM, Lang N, Platzer P, Hofbauer M. Risk factors predicting prognosis and outcome of elderly patients with isolated traumatic brain injury. J Orthop Surg Res. 2018 Nov 3;13(1):277. doi: 10.1186/s13018-018-0975-y. PubMed PMID: 30390698; PubMed Central PMCID: PMC6215630.
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Almojuela A, Hasen M, Zeiler FA. The Full Outline of UnResponsiveness (FOUR) Score and Its Use in Outcome Prediction: A Scoping Systematic Review of the Adult Literature. Neurocrit Care. 2018 Nov 8. doi: 10.1007/s12028-018-0630-9. [Epub ahead of print] Review. PubMed PMID: 30411302.
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Rau CS, Kuo PJ, Chien PC, Huang CY, Hsieh HY, Hsieh CH. Mortality prediction in patients with isolated moderate and severe traumatic brain injury using machine learning models. PLoS One. 2018 Nov 9;13(11):e0207192. doi: 10.1371/journal.pone.0207192. eCollection 2018. PubMed PMID: 30412613.
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Mohammadifard M, Ghaemi K, Hanif H, Sharifzadeh G, Haghparast M. Marshall and Rotterdam Computed Tomography scores in predicting early deaths after brain trauma. Eur J Transl Myol. 2018 Jul 16;28(3):7542. doi: 10.4081/ejtm.2018.7542. eCollection 2018 Jul 10. PubMed PMID: 30344974; PubMed Central PMCID: PMC6176390.
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Pentelényi T. Significance of endocrine studies in the general assessment and prediction of fatal outcome in head injury. Acta Neurochir Suppl (Wien). 1992;55:21-4. PubMed PMID: 1414538.

Traumatic brain injury epidemiology

Traumatic brain injury epidemiology

Traumatic brain injury (TBI) is a critical public health and socio-economic problem throughout the world, making epidemiological monitoring of incidence, prevalence and outcome necessary.

It is one of leading causes of mortality and disability worldwide and is estimated to surpass many diseases by 2020 1) 2).

It is the leading cause of mortality and morbidity in children 3).

Nonaccidental head injury, as seen in domestic child abuse cases, is often associated with spine injury, and spinal subdural hematoma is the most frequent diagnosis. While spinal epidural hematomas are a rare occurrence, the incidence of spontaneous epidural hematomas occurring in nonaccidental head injury patients is even lower 4).


In 2019, relevant articles and registries were identified via systematic review; study quality was higher in the high-income countries (HICs) than in the low- and middle-income countries (LMICs). Sixty-nine million (95% CI 64-74 million) individuals worldwide are estimated to sustain a TBI each year. The proportion of TBIs resulting from road traffic accidents was greatest in Africa and Southeast Asia (both 56%) and lowest in North America (25%). The incidence of RTA was similar in Southeast Asia (1.5% of the population per year) and Europe (1.2%). The overall incidence of TBI per 100,000 people was greatest in North America (1299 cases, 95% CI 650-1947) and Europe (1012 cases, 95% CI 911-1113) and least in Africa (801 cases, 95% CI 732-871) and the Eastern Mediterranean (897 cases, 95% CI 771-1023). The LMICs experience nearly 3 times more cases of TBI proportionally than HICs.

Sixty-nine million (95% CI 64-74 million) individuals are estimated to suffer TBI from all causes each year, with the Southeast Asian and Western Pacific regions experiencing the greatest overall burden of disease. Head injury following road traffic collision is more common in LMICs, and the proportion of TBIs secondary to road traffic collision is likewise greatest in these countries. Meanwhile, the estimated incidence of TBI is highest in regions with higher-quality data, specifically in North America and Europe 5).

Traumatic brain injury (TBI) is a public health problem in Ethiopia. We need more knowledge about the epidemiology and neurosurgical management of TBI patients to identify possible focus areas for quality improvement and preventive efforts.

In a prospective cross-sectional study (2012-2016) at the four teaching hospitals in Addis Ababa, Ethiopia. All surgically treated TBI patients were included, and details on clinical presentation, injury types, and trauma causes were registered.

They included 1087 patients (mean age 29 years; 8.7% females; 17.1% < 18 years of age). Only 15.5% of TBIs were classified as severe (Glasgow Coma Scale (GCS) score 3-8). Depressed skull fracture (DSF; 44.9%) and epidural hematoma (EDH; 39%) were the most frequent injuries. Very few patients were polytraumatized (3.1%). Assault was the most common injury mechanism (69.9%) followed by road traffic accidents (RTA; 15.8%) and falls (8.1%). More than 80% of patients came from within 200 kms of the hospitals, but the median time to admission was 24 hours. Most assault victims (80.4%) were injured more than 50 kms from the hospitals, whereas 46% of RTA victims came from the urban area. Delayed admission was associated with higher GCS scores and non-severe TBI (p < 0.01).

The injury panorama delayed admission, and few operations for severe TBI are linked to a substantial patient selection both before and after hospital admission. The results also suggest that there should be a geographical framework for tailored guidelines, preventive efforts, and development of prehospital and hospital services 6).

Sun et al. conducted a nationally representative door-to-door survey in the general population across all age groups in 31 provinces in mainland China in 2013.

All participants were reviewed for a history of physician-diagnosed TBI by trained investigators using a structured questionnaire. TBI survivors were considered as prevalent cases at the prevalent time. The present study also examined the odds of TBI as a function of sex, age, and other demographical variables using logistic regression model. + Of 583,870 participants, 2,673 individuals had suffered from a TBI during their past life, yielding a weighted prevalence of being 442.4 (95% CI 342.2-542.6) per 100,000 person. The TBI prevalence increased with increasing age. The present study observed the multiadjusted ORs of TBI were 1.9 (95% CI 1.8-2.1) for the male, 1.9 (95% CI 1.2-3.1) for the farmers, 1.9 (95% CI 1.2-3.3) for the retiree or homemakers, 3.4 (95% CI 1.5-7.7), and 2.8 (95% CI 1.1-6.6) for those whose education were primary school and high school, respectively. The most common external cause was road traffic accidents among those who were aged 18-34 years old and those whose educational levels were middle school in both genders.

The results indicate TBI was substantially prevalent among Chinese population and underscore the need to develop national strategies to improve the safe education on road and traffic of TBI in rural residents and some subgroup population 7).

Every 15 seconds someone suffers a traumatic brain injury (TBI) in the United States. TBI causes more deaths in males <35 years old than all other diseases combined, and it is estimated that 2% of the U.S. population lives with TBI-associated disability. Despite extensive research and success in animal studies, successful drug therapies have proved elusive in clinical trials 8).

The Centers for Disease Control and Prevention (CDC) estimate that more than 1.7 million each year in USA sustain TBI. Of these, approximately 1.4 million are treated and released from emergency centers, 275,000 are hospitalized, 80,000 suffer long-term disability and 52,000 die 9) ,and another 235,000 are hospitalized for non-fatal TBI 10).

Incidence of TBI in all industrialized countries is comparable to the U.S., with estimates ranging from 150 to more than 300 per 100,000

Annual incidence of approximately 250-600 patients per 100,000, and mortality of 17 cases per 100,000.

It is one of the most common causes of death in ordinary accidents, natural disasters, or warfare.

These injuries frequently occur outside, leaving injured individuals exposed to environmental temperature extremes before they are transported to a hospital.

Each year, approximately 100,000 patients require neurosurgical evacuation of an intracranial hematoma in the United States 11).

There are strong and demographically stable associations between TBI and substance use. These associations may not only increase the odds of injury but impair the quality of post injury recovery 12).

The exact incidence is unavailable in India.

From August 2012 to May 2013 at Department of Neurosurgery, S.C.B. Medical College, Cuttack, Odisha, India. All the pertinent details from case records of hundred and forty-seven children <15 years with TBI were analyzed. Follow-up was done for 6 months at outpatients department.

Age wise, incidence and severity of TBI is more common in 10-15 years. Males outnumber females with a male: female ratio 2.19:1. Overall, road traffic accident (RTA) is the commonest mode of injury. Assault is not uncommon (7.48% cases). Falls is common in <5 years while RTA is common in 5-15 years. The extradural hematoma was the most common injury pattern; however, surgical consideration was maximal for fracture skull. Overall mortality was 7.48%. Diffuse axonal injury has the maximum individual potential for mortality. We noticed excellent recovery in 68.7%, disabilities in 17.68%, and persistent vegetative state in 5.45% cases.

TBI in children carries good outcome, if resuscitated and referred early to a neurotrauma center, and managed subsequently on an individualized basis with a well-organized team approach. Severe TBI in children has a poor outcome 13).

Traumatic brain injury (TBI) is a common reason for presentation at the emergency department (ED) and hospital admission in Europe.

In total, 28 epidemiological studies on TBI from 16 European countries were identified in the literature. A great variation was found in case definitions and case ascertainment between studies. Falls and road traffic accidents (RTA) were the two most frequent causes of TBI, with falls being reported more frequently than RTA 14).

In 2006 it was difficult to reach a consensus on all epidemiological findings across the 23 published European studies because of critical differences in methods employed across the reports 15).

Traumatic brain injury epidemiology in Spain

2015

A search was conducted in the PubMed electronic database using the terms: epidemiology, incidence, brain injur*, head injur* and Europe. Only articles published in English and reporting on data collected in Europe between 1990 and 2014 were included. In total, 28 epidemiological studies on TBI from 16 European countries were identified in the literature. A great variation was found in case definitions and case ascertainment between studies. Falls and road traffic accidents (RTA) were the two most frequent causes of TBI, with falls being reported more frequently than RTA. In most of the studies a peak TBI incidence was seen in the oldest age groups. In the meta-analysis, an overall incidence rate of 262 per 100,000 for admitted TBI was derived.

Interpretation of published epidemiologic studies is confounded by differences in inclusion criteria and case ascertainment. Nevertheless, changes in epidemiological patterns are found: falls are now the most common cause of TBI, most notably in elderly patients. Improvement of the quality of standardised data collection for TBI is mandatory for reliable monitoring of epidemiological trends and to inform appropriate targeting of prevention campaigns 16).

A coordinated strategy to evaluate this public health problem in Romania would first of all rely on a related advanced monitoring system, to provide precise information about the epidemiology, clinical and paraclinical data, but concerning the social and economic connected consequences, too 17).

see Traumatic brain injury in skiers.


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Tagliaferri F, Compagnone C, Korsic M, Servadei F, Kraus J. A systematic review of brain injury epidemiology in Europe. Acta Neurochir (Wien). 2006 Mar;148(3):255-68; discussion 268. Review. PubMed PMID: 16311842.
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Popescu C, Anghelescu A, Daia C, Onose G. Actual data on epidemiological evolution and prevention endeavours regarding traumatic brain injury. J Med Life. 2015 Jul-Sep;8(3):272-7. Review. PubMed PMID: 26351526; PubMed Central PMCID: PMC4556905.

Pediatric traumatic brain injury guidelines

Pediatric traumatic brain injury guidelines

see Guidelines for the Management of Pediatric Severe Traumatic Brain Injury, Third Edition

In a systematic review and guideline appraisal for pediatric clinical practice guidelines (CPGs) concerning the acute management of Pediatric Traumatic Brain Injury. Targeted guideline creation specific to the pediatric population has the potential to improve the quality of acute TBI clinical practice guidelines (CPGs).

Furthermore, it is crucial to address the applicability of a guideline to translate the CPG from a published manuscript into clinically relevant local practice tools and for resource limited practice settings 1).

Guidelines for Diagnosing and Managing Pediatric Concussion

Guidelines.


Thromboprophylaxis in Traumatic brain injury:

Low-molecular-weight heparin (LMWH) prophylaxis in pediatric traumatic brain injury appears to be more effective than unfractionated heparin (UH) in preventing venous thromboembolism (VTE). Large, multicenter prospective studies are warranted to confirm the superiority of LMWH over UH in pediatric patients with traumatic brain injury. Moreover, outcomes of VTE prophylaxis in the very young remain understudied; therefore, dedicated studies to evaluate this population are needed 2).


1)

Appenteng R, Nelp T, Abdelgadir J, Weledji N, Haglund M, Smith E, Obiga O, Sakita FM, Miguel EA, Vissoci CM, Rice H, Vissoci JRN, Staton C. A systematic review and quality analysis of pediatric traumatic brain injury clinical practice guidelines. PLoS One. 2018 Aug 2;13(8):e0201550. doi: 10.1371/journal.pone.0201550. eCollection 2018. PubMed PMID: 30071052; PubMed Central PMCID: PMC6072093.
2)

van Erp IA, Gaitanidis A, El Moheb M, Kaafarani HMA, Saillant N, Duhaime AC, Mendoza AE. Low-molecular-weight heparin versus unfractionated heparin in pediatric traumatic brain injury. J Neurosurg Pediatr. 2021 Feb 12:1-6. doi: 10.3171/2020.9.PEDS20615. Epub ahead of print. PMID: 33578391.

Severe traumatic brain injury treatment

Severe traumatic brain injury treatment

There are currently no established treatments for the underlying pathophysiology in TBI and while neuro-rehabilitation efforts are promising, there are currently is a lack of consensus regarding rehabilitation following TBI of any severity 1).

see Severe traumatic brain injury guidelines.

see also Pediatric traumatic brain injury guidelines.

Severe traumatic brain injury (TBI) is currently managed in the intensive care unit with a combined medical-surgical approach. Treatment aims to prevent additional brain damage and to optimise conditions for brain recovery. TBI is typically considered and treated as one pathological entity, although in fact it is a syndrome comprising a range of lesions that can require different therapies and physiological goals. Owing to advances in monitoring and imaging, there is now the potential to identify specific mechanisms of brain damage and to better target treatment to individuals or subsets of patients. Targeted treatment is especially relevant for elderly people-who now represent an increasing proportion of patients with TBI-as preinjury comorbidities and their therapies demand tailored management strategies. Progress in monitoring and in understanding pathophysiological mechanisms of TBI could change current management in the intensive care unit, enabling targeted interventions that could ultimately improve outcomes 2).

Monitoring

see Intracranial pressure monitoring for severe traumatic brain injury.

Hormonal replacement

Hormonal analysis should be considered in patients with moderate-to-severe traumatic brain injury, so that appropriate hormonal replacement can be done to optimize the clinical outcome 3).

Case series

Data from 729 severe traumatic brain injury patients admitted between 1996 and 2016 were used. Treatment was guided by controlling intracranial pressure and cerebral perfusion pressure according to a local protocol.

Cerebral perfusion pressurepressure reactivity index curves were fitted automatically using a previously published curve-fitting heuristic from the relationship between pressure reactivity index and cerebral perfusion pressure. The cerebral perfusion pressure values at which this “U-shaped curve” crossed the fixed threshold from intact to impaired pressure reactivity (pressure reactivity index = 0.3) were denoted automatically the “lower” and “upper” cerebral perfusion pressure limits of reactivity, respectively. The percentage of time with cerebral perfusion pressure below (%cerebral perfusion pressure < lower limit of reactivity), above (%cerebral perfusion pressure > upper limit of reactivity), or within these reactivity limits (%cerebral perfusion pressure within limits of reactivity) was calculated for each patient and compared across dichotomized Glasgow Outcome Scores. After adjusting for age, initial Glasgow Coma Scale, and mean intracranial pressure, percentage of time with cerebral perfusion pressure less than lower limit of reactivity was associated with unfavorable outcome (odds ratio %cerebral perfusion pressure < lower limit of reactivity, 1.04; 95% CI, 1.02-1.06; p < 0.001) and mortality (odds ratio, 1.06; 95% CI, 1.04-1.08; p < 0.001).

Individualized autoregulation-guided cerebral perfusion pressure management may be a plausible alternative to fixed cerebral perfusion pressure threshold management in severe traumatic brain injury patients. Prospective randomized research will help define which autoregulation-guided method is beneficial, safe, and most practical 4).

Medicaments

Despite the incidence of these injuries and their substantial socioeconomic implications, no specific pharmacological intervention is available for clinical use.

see Progesterone for acute traumatic brain injury.

see 21-aminosteroids for severe traumatic brain injury.

Neuroprotection

see Neuroprotection in traumatic Brain Injury

see Decompressive craniectomy for severe traumatic brain injury.

Cell-based therapies

Cell-based therapies are currently being investigated in treating neurotrauma due to their ability to secrete neurotrophic factors and anti-inflammatory cytokines that can regulate the hostile milieu associated with chronic neuroinflammation found in TBI. In tandem, the stimulation and mobilization of endogenous stem/progenitor cells from the bone marrow through granulocyte colony stimulating factor (G-CSF) poses as an attractive therapeutic intervention for chronic TBI.

The potential of a combined therapy of human umbilical cord blood cells (hUCB) and G-CSF at the acute stage of TBI to counteract the progressive secondary effects of chronic TBI using the controlled cortical impact model.

Four different groups of adult Sprague Dawley rats were treated with saline alone, G-CSF+saline, hUCB+saline or hUCB+G-CSF, 7-days post CCI moderate TBI. Eight weeks after TBI, brains were harvested to analyze hippocampal cell loss, neuroinflammatory response, and neurogenesis by using immunohistochemical techniques. Results revealed that the rats exposed to TBI treated with saline exhibited widespread neuroinflammation, impaired endogenous neurogenesis in DG and SVZ, and severe hippocampal cell loss. hUCB monotherapy suppressed neuroinflammation, nearly normalized the neurogenesis, and reduced hippocampal cell loss compared to saline alone. G-CSF monotherapy produced partial and short-lived benefits characterized by low levels of neuroinflammation in striatum, DG, SVZ, and corpus callosum and fornix, a modest neurogenesis, and a moderate reduction of hippocampal cells loss. On the other hand, combined therapy of hUCB+G-CSF displayed synergistic effects that robustly dampened neuroinflammation, while enhancing endogenous neurogenesis and reducing hippocampal cell loss. Vigorous and long-lasting recovery of motor function accompanied the combined therapy, which was either moderately or short-lived in the monotherapy conditions. These results suggest that combined treatment rather than monotherapy appears optimal for abrogating histophalogical and motor impairments in chronic TBI 5).

Research

Research in traumatic brain injury (TBI) is challenging for several reasons; in particular, the heterogeneity between patients regarding causes, pathophysiology, treatment, and outcome. Advances in basic science have failed to translate into successful clinical treatments, and the evidence underpinning guideline recommendations is weak. Because clinical research has been hampered by non-standardised data collection, restricted multidisciplinary collaboration, and the lack of sensitivity of classification and efficacy analyses, multidisciplinary collaborations are now being fostered. Approaches to deal with heterogeneity have been developed by the IMPACT study group. These approaches can increase statistical power in clinical trials by up to 50% and are also relevant to other heterogeneous neurological diseases, such as stroke and subarachnoid haemorrhage. Rather than trying to limit heterogeneity, we might also be able to exploit it by analysing differences in treatment and outcome between countries and centres in comparative effectiveness research. This approach has great potential to advance care in patients with TBI 6).

Anticoagulation Resumption after traumatic brain injury

Anticoagulation Resumption after traumatic brain injury.

Thromboprophylaxis

The early administration of venous thromboembolism (VTE) chemoprophylaxis within 24 h after admission in patients with severe TBI did not increase the risk of intracranial bleeding progression 7).

Transcutaneous Vagus Nerve Stimulation for Severe Traumatic Brain Injury

see Transcutaneous Vagus Nerve Stimulation for Severe Traumatic Brain Injury.

References

1)

Marklund N, Bellander BM, Godbolt A, Levin H, McCrory P, Thelin EP. Treatments and rehabilitation in the acute and chronic state of traumatic brain injury. J Intern Med. 2019 Mar 18. doi: 10.1111/joim.12900. [Epub ahead of print] PubMed PMID: 30883980.
2)

Stocchetti N, Carbonara M, Citerio G, Ercole A, Skrifvars MB, Smielewski P, Zoerle T, Menon DK. Severe traumatic brain injury: targeted management in the intensive care unit. Lancet Neurol. 2017 Jun;16(6):452-464. doi: 10.1016/S1474-4422(17)30118-7. Review. PubMed PMID: 28504109.
3)

Prasanna KL, Mittal RS, Gandhi A. Neuroendocrine dysfunction in acute phase of moderate-to-severe traumatic brain injury: A prospective study. Brain Inj. 2015;29(3):336-342. PubMed PMID: 25671810.
4)

Donnelly J, Czosnyka M, Adams H, Robba C, Steiner LA, Cardim D, Cabella B, Liu X, Ercole A, Hutchinson PJ, Menon DK, Aries MJH, Smielewski P. Individualizing Thresholds of Cerebral Perfusion Pressure Using Estimated Limits of Autoregulation. Crit Care Med. 2017 Sep;45(9):1464-1471. doi: 10.1097/CCM.0000000000002575. PubMed PMID: 28816837.
5)

Acosta SA, Tajiri N, Shinozuka K, Ishikawa H, Sanberg PR, Sanchez-Ramos J, Song S, Kaneko Y, Borlongan CV. Combination therapy of human umbilical cord blood cells and granulocyte colony stimulating factor reduces histopathological and motor impairments in an experimental model of chronic traumatic brain injury. PLoS One. 2014 Mar 12;9(3):e90953. doi: 10.1371/journal.pone.0090953. eCollection 2014. PubMed PMID: 24621603.
6)

Maas AI, Murray GD, Roozenbeek B, Lingsma HF, Butcher I, McHugh GS, Weir J, Lu J, Steyerberg EW; International Mission on Prognosis Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) Study Group. Advancing care for traumatic brain injury: findings from the IMPACT studies and perspectives on future research. Lancet Neurol. 2013 Dec;12(12):1200-10. doi: 10.1016/S1474-4422(13)70234-5. Epub 2013 Oct 17. PubMed PMID: 24139680; PubMed Central PMCID: PMC3895622.
7)

Störmann P, Osinloye W, Freiman TM, Seifert V, Marzi I, Lustenberger T. Early Chemical Thromboprophylaxis Does not Increase the Risk of Intracranial Hematoma Progression in Patients with Isolated Severe Traumatic Brain Injury. World J Surg. 2019 Jul 2. doi: 10.1007/s00268-019-05072-1. [Epub ahead of print] PubMed PMID: 31267142.

Cervical traumatic spinal cord injury outcome

Cervical traumatic spinal cord injury outcome

Injury to the spine and spinal cord is one of the common cause of disability and death. Several factors affect the outcome; but which are these factors (alone and in combination), are determining the outcomes are still unknown.

Based on parameters from the International Standards, physicians are able to inform patients about the predicted long-term outcomes, including the ability to walk, with high accuracy. In those patients who cannot participate in a reliable physical neurological examination, magnetic resonance imaging and electrophysiological examinations may provide useful diagnostic and prognostic information. As clinical research on this topic continues, the prognostic value of the reviewed diagnostic assessments will become more accurate in the near future. These advances will provide useful information for physicians to counsel tSCI patients and their families during the catastrophic initial phase after the injury 1).

In cervical traumatic spinal cord injury (TSCI), the therapeutic effect of timing of surgery on neurological recovery remains uncertain. Additionally, the relationship between the extent of decompression, imaging biomarker evidence of injury severity, and the outcome are incompletely understood.

Aarabi et al., investigated the effect of timing of decompression on long-term neurological outcome in patients with complete spinal cord decompression confirmed on postoperative MRI. AIS grade conversion was determined in 72 AIS grades A, B, and C patients 6 months after confirmed decompression. Thirty-two patients underwent decompressive surgery ultra-early (<12 hours), 25 early (12-24 hours), and 15 late (>24-138.5 hours) after injury. Age, gender, injury mechanism, intramedullary lesion length (IMLL) on MRI, admission ASIA motor score, and surgical technique were not statistically different between groups. Motor complete patients (p=0.009) and those with fracture-dislocations (p=0.01) tended to be operated earlier. Improvement of one grade or more was present in 55.6% in AIS grade A, 60.9% in AIS grade B, and 86.4% in AIS grade C patients. Admission AIS motor score (p=0.0004) and pre-operative IMLL (p=0.00001) were the strongest predictors of neurological outcome. AIS grade improvement occurred in 65.6%, 60%, and 80% of patients who underwent decompression ultra-early, early, and late, respectively (p=0.424). Multiple regression analysis revealed that IMLL was the only significant variable predictive of AIS grade conversion to a better grade (odds ratio, 0.908; CI, 0.862-0.957; p<0.001).

They conclude that in patients with postoperative MRI confirmation of complete decompression following cervical TSCI, pre-operative IMLL, not the timing of surgery, determine the long-term neurological outcome 2).


Preclinical and class III clinical data suggest improved outcomes by maintaining the mean arterial pressure > 85 mm Hg and avoiding hypoxemia at least for 7 days following cervical SCI, and this level of monitoring and support should occur in the ICU 3).


100 cases of patients under 18 years at accident with acute traumatic cervical spinal cord injury admitted to spinal cord injury SCI centers participating in the European Multi-center study about SCI (EMSCI) between January 2005 and April 2016 were reviewed. According to their age at the accident, age 13 to 17, patients were selected for the adolescent group. After applying in- and exclusion criteria 32 adolescents were included. Each adolescent patient was matched with two adult SCI patients for analysis.

ASIA Impairment scale (AIS) grade, neurological, sensory, motor level, total motor score, and Spinal Cord Independence Measure (SCIM III) total score.

Mean AIS conversion, neurological, motor and sensory levels, as well as total motor score, showed no significant statistical difference in adolescents compared to the adult control group after a follow up of 6 months. Significantly higher final SCIM scores (p < 0.05) in the adolescent group compared to adults as well as a strong trend for a higher gain in SCIM score (p < 0.061) between first and last follow up was found.

Neurological outcome after traumatic cervical SCI is not superior in adolescents compared to adults in this cohort. Significantly higher SCIM scores indicate more functional gain for adolescent patients after traumatic cervical SCI. Juvenile age appears to be an independent predictor for a better functional outcome. 4).


A prospective observational study at single-center with all patients with cervical spinal cord injury (SCI), attending our hospital within a week of injury during a period of October 2011 to July 2013 was included for analysis. Demographic factors such as age, gender, etiology of injury, preoperative American Spinal Injury Association (ASIA) grade, upper (C2-C4) versus lower (C5-C7) cervical level of injury, image factors on magnetic resonance imaging (MRI), and timing of intervention were studied. Change in neurological status by one or more ASIA grade from the date of admission to 6 months follow-up was taken as an improvement. Functional grading was assessed using the functional independence measure (FIM) scale at 6 months follow-up.

A total of 39 patients with an acute cervical spine injury, managed surgically were included in this study. Follow-up was available for 38 patients at 6 months. No improvement was noted in patients with ASIA Grade A. Maximum improvement was noted in ASIA Grade D group (83.3%). The improvement was more significant in lower cervical region injuries. Patients with cord contusion showed no improvement as opposed to those with just edema wherein; the improvement was seen in 62.5% of patients. The percentage of improvement in cord edema ≤3 segments (75%) was significantly higher than edema with >3 segments (42.9%). Maximum improvement in FIM score was noted in ASIA Grade C and patients who had edema (especially ≤3 segments) in MRI cervical spine.

Complete cervical SCI, upper-level cervical cord injury, patients showing MRI contusion, edema >3 segments group have a worst improvement in neurological status at 6 months follow-up 5).


A total of 66 patients diagnosed with traumatic cervical SCI were selected for neurological assessment (using the International standards for neurological classification of spinal cord injury [ISNCSCI]) and functional evaluation (based on the Korean version Modified Barthel Index [K-MBI] and Functional Independence Measure [FIM]) at admission and upon discharge. All of the subjects received a preliminary electrophysiological assessment, according to which they were divided into two groups as follows: those with cervical radiculopathy (the SCI/Rad group) and those without (the SCI group).

A total of 32 patients with cervical SCI (48.5%) had cervical radiculopathy. The initial ISNCSCI scores for sensory and motor, K-MBI, and total FIM did not significantly differ between the SCI group and the SCI/Rad group. However, at discharge, the ISNCSCI scores for motor, K-MBI, and FIM of the SCI/Rad group showed less improvement (5.44±8.08, 15.19±19.39 and 10.84±11.49, respectively) than those of the SCI group (10.76±9.86, 24.79±19.65 and 17.76±15.84, respectively) (p<0.05). In the SCI/Rad group, the number of involved levels of cervical radiculopathy was negatively correlated with the initial and follow-up motors score by ISNCSCI.

Cervical radiculopathy is not rare in patients with traumatic cervical SCI, and it can impede neurological and functional improvement. Therefore, detection of combined cervical radiculopathy by electrophysiological assessment is essential for the accurate prognosis of cervical SCI patients in the rehabilitation unit 6).

References

1)

van Middendorp JJ, Goss B, Urquhart S, Atresh S, Williams RP, Schuetz M. Diagnosis and prognosis of traumatic spinal cord injury. Global Spine J. 2011 Dec;1(1):1-8. doi: 10.1055/s-0031-1296049. PubMed PMID: 24353930; PubMed Central PMCID: PMC3864437.
2)

Aarabi B, Akhtar-Danesh N, Chryssikos T, Shanmuganathan K, Schwartzbauer G, Simard MJ, Olexa J, Sansur C, Crandall K, Mushlin H, Kole M, Le E, Wessell A, Pratt N, Cannarsa G, Diaz Lomangino C, Scarboro M, Aresco C, Oliver J, Caffes N, Carbine S, Kanami M. Efficacy of Ultra-Early (<12 hours), Early (12-24 hours), and Late (>24-138.5 hours) Surgery with MRI-Confirmed Decompression in AIS grades A, B, and C Cervical Spinal Cord Injury. J Neurotrauma. 2019 Jul 16. doi: 10.1089/neu.2019.6606. [Epub ahead of print] PubMed PMID: 31310155.
3)

Schwartzbauer G, Stein D. Critical Care of Traumatic Cervical Spinal Cord Injuries: Preventing Secondary Injury. Semin Neurol. 2016 Dec;36(6):577-585. Epub 2016 Dec 1. Review. PubMed PMID: 27907962.
4)

Geuther M, Grassner L, Mach O, Klein B, Högel F, Voth M, Bühren V, Maier D, Abel R, Weidner N, Rupp R, Fürstenberg CH; EMSCI study group, Schneidmueller D. Functional outcome after traumatic cervical spinal cord injury is superior in adolescents compared to adults. Eur J Paediatr Neurol. 2018 Dec 11. pii: S1090-3798(18)30247-2. doi: 10.1016/j.ejpn.2018.12.001. [Epub ahead of print] PubMed PMID: 30579697.
5)

Srinivas BH, Rajesh A, Purohit AK. Factors affecting the outcome of acute cervical spine injury: A prospective study. Asian J Neurosurg. 2017 Jul-Sep;12(3):416-423. doi: 10.4103/1793-5482.180942. PubMed PMID: 28761518; PubMed Central PMCID: PMC5532925.
6)

Kim SY, Kim TU, Lee SJ, Hyun JK. The prognosis for patients with traumatic cervical spinal cord injury combined with cervical radiculopathy. Ann Rehabil Med. 2014 Aug;38(4):443-9. doi: 10.5535/arm.2014.38.4.443. Epub 2014 Aug 28. PubMed PMID: 25229022; PubMed Central PMCID: PMC4163583.