injury

Spinal cord injury epidemiology

Spinal cord injury epidemiology

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see also Cervical spine fracture epidemiology.

Thoracolumbar spine fracture epidemiology

Pediatric cervical spine injury epidemiology.

Spinal cord injury epidemiology is changing as preventative interventions reduce injuries in younger individuals, and there is an increased incidence of incomplete injuries in aging populations. With decompressive surgery and proactive interventions to improve spinal cord perfusion, early treatment has become more intensive. Accurate data, including specialized outcome measures, are crucial to understanding the impact of epidemiological and treatment trends. Dedicated SCI clinical research and data networks and registries have been established in the United States, Canada, Europe, and several other countries.

Traumatic spinal cord injuries (TSCIs) affect up to 500,000 people worldwide each year, and their high morbidity is associated with substantial individual and societal burden and socioeconomic impact 1) 2).

TSCIs most commonly affect young males and result from road traffic accidents, but recent reports also highlight their increasing incidence in older adults as a result of low-energy falls 3) 4) 5).

Kelly-Hedrick et al. reviewed four registry networks, The NACTN Spinal Cord Injury Registry, The Spinal Cord Injury Model Systems (SCIMS) Database, The Rick Hansen Spinal Cord Injury Registry (RHSCIR), and the European Multi-Center Study about Spinal Cord Injury Study (EMSCI). They compared the registries’ focuses, data platforms, advanced analytics use, and impacts. They also describe how registries’ data can be combined with EHR or shared using federated analysis to protect registrants’ identities. These registries have identified changes in epidemiology, recovery patterns, complication incidence, and the impact of practice changes like early decompression. They’ve also revealed latent disease-modifying factors, helped develop clinical trial stratification models and served as matched control groups in clinical trials. Advancing SCI clinical science for personalized medicine requires advanced analytical techniques, including machine learning, counterfactual analysis, and the creation of digital twins. Registries and other data sources help drive innovation in SCI clinical science 6).

1)

WHO. Spinal Cord Injury, Fact Sheet. Available at 2013 http://www.who.int/mediacentre/factsheets/fs384/en/
2)

Singh A., Tetreault L., Kalsi-Ryan S., Nouri A., Fehlings M.G. (2014). Global prevalence and incidence of traumatic spinal cord injury. Clin. Epidemiol. 6, 309–331
3)

Noonan V.K., Fingas M., Farry A., Baxter D., Singh A., Fehlings M.G., Dvorak M.F. (2012). Incidence and prevalence of spinal cord injury in Canada: a national perspective. Neuroepidemiology 38, 219–226
4)

Selvarajah S., Hammond E.R., Haider A.H., Abularrage C.J., Becker D., Dhiman N., Hyder O., Gupta D., Black J.H., 3rd, Schneider E.B. (2014). The burden of acute traumatic spinal cord injury among adults in the United States: an update. J. Neurotrauma 31, 228–238
5)

Wyndaele M., Wyndaele J.J. (2006). Incidence, prevalence and epidemiology of spinal cord injury: what learns a worldwide literature survey? Spinal Cord 44, 523–529
6)

Kelly-Hedrick M, Abd-El-Barr M, Aarabi B, Curt A, Howley SP, Harrop JS, Kirshblum S, Neal CJ, Noonan VK, Park C, Ugiliweneza B, Tator C, Toups EG, Fehlings MG, Williamson T, Guest J. The Importance of Prospective Registries and Clinical Research Networks in the Evolution of Spinal Cord Injury Care. J Neurotrauma. 2022 Dec 28. doi: 10.1089/neu.2022.0450. Epub ahead of print. PMID: 36576020.

Pediatric traumatic brain injury outcome

Pediatric traumatic brain injury outcome

see also Traumatic brain injury outcome.

Latest articles

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.

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 GFAP, UCH-L1, S100B, 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 NSE, Tau, UCH-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).

Systematic reviews

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 inflammation, hormones as biomarkers, coagulation and vasculature, genetic polymorphisms, antioxidants and oxidative stress, apoptosis 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).

S100B in mild traumatic brain injury

S100B in mild traumatic brain injury

Latest articles

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).

Ireland

In a retrospective, longitudinal 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).

Finland

Traumatic brain injury epidemiology in Finland

Romania

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).

Spain

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).

A 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).

Impact

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

Effect of trauma center designation in severe traumatic brain injury outcome

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 algorithms 5).

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 age, motor impairment, impaired or absent eye movements or pupillary light reflexes, early hypotension, hypoxemia 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).

Prediction

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 epilepsy. Traumatic brain injury outcome can be affected by early post-traumatic epilepsy. 11).

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

CRASH

IMPACT

IMPACT

Mortality

Traumatic brain injury mortality.

Quality of Life after Brain Injury

see Quality of Life after Brain Injury.

Traumatic brain injury complications

Traumatic brain injury complications.

Statins

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).

References

1)

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.
4)

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.
5)

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.
6)

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.
7)

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.
8)

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.
9)

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.
10)

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.
11)

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.

Incomplete spinal cord injury

Incomplete spinal cord injury

Any residual motor or sensory function is more than 3 segments below the level of the injury.

Look for signs of preserved long-tract function.

Signs of incomplete lesion:

  1. sensation (including position sense) or voluntary movement in the LEs in the presence of a cervical or thoracic spinal cord injury

  2. “sacral sparing”: preserved sensation around the anus, voluntary rectal sphincter contraction, or voluntary toe flexion

  3. an injury does not qualify as incomplete with preserved sacral reflexes alone (e.g. bulbocavernosus)

An incomplete spinal cord injury is the term used to describe damage to the spinal cord that is not absolute. The incomplete injury will vary enormously from person to person and will be entirely dependant on the way the spinal cord has been compromised.

An “incomplete” spinal cord injury involves preservation of motor or sensory function below the level of injury in the spinal cord.

If the patient has the ability to contract the anal sphincter voluntarily or to feel a pinprick or touch around the anus, the injury is considered to be incomplete. The nerves in this area are connected to the very lowest region of the spine, the sacral region, and retaining sensation and function in these parts of the body indicates that the spinal cord is only partially damaged. This includes a phenomenon known as sacral sparing.

The true extent of many incomplete injuries isn’t fully known until 6-8 weeks post injury. The spinal cord normally goes into what is called spinal shock after it has been damaged. The swelling and fluid masses showing on any resultant X-ray, MRI or CT scans, may well mask the true nature of the underlying injury. It is not uncommon for someone who is completely paralysed at the time of injury to get a partial or very near full recovery from their injuries after spinal shock has subsided.

Types

Central cord syndrome

Central cord syndrome.

Anterior cord syndrome

Anterior cord syndrome.

Brown-Séquard syndrome

Brown-Séquard syndrome.

Posterior cord syndrome

Posterior cord syndrome: rare

Treatment

The results of kinesiotherapy treatment in patients after incomplete spinal cord injury (iSCI) are inconclusive, mostly due to different, subjective evaluation methods. A study aimed to evaluate the range of functional regeneration in long-term 13 months follow-up using comparative neurophysiological tests after uniform kinesiotherapy in patients with thoracic iSCI.

Material and methods: Comparative tests were performed of sensory perception in dermatomes Th1-S1, electromyography (at rest-rEMG and during maximal contraction-mcEMG) in the muscles of the trunk and lower extremities, electroneurography (ENG) of the motor fibers of the lower extremities, and motor-evoked potential induced transcranially (MEP) before and after treatment in 25 iSCI patients. All subjects were treated with the same kinesiotherapeutic procedures.

A moderate increase was found in amplitudes in rEMG and mcEMG recordings from the rectus abdominis and rectus femoris muscles, MEPs amplitudes, and amplitudes after peroneal nerve stimulations in ENG studies. There was no improvement in sensory perception.

Following the proposed kinesiotherapy algorithm, patients after thoracic iSCI presented a moderate more motor than sensory functions improvement. Applied neurorehabilitation evoked normalization of muscle tension, moderate improvement of rectus abdominis and rectus femoris muscles motor units activity, and motor central and peripheral neural impulses transmission. The comparative neurophysiological assessment provides more precise and objective insight into the functional status of afferent and efferent systems than the classical clinical approach in iSCI patients 1).

Outcome

Following incomplete spinal cord injuries, neonatal mammals display a remarkable degree of behavioral recovery.

Previously, it has been demonstrated in neonatal mice a wholesale re-establishment and reorganization of synaptic connections from some descending axon tracts (Boulland et al., 2013).

To assess the potential cellular mechanisms contributing to this recovery, Chawla et al., have characterized a variety of cellular sequelae following thoracic compression injuries, focusing particularly on cell loss and proliferation, inflammation and reactive gliosis, and the dynamics of specific types of synaptic terminals. Early during the period of recovery, regressive events dominated. Tissue loss near the injury was severe, with about 80% loss of neurons and a similar loss of axons that later make up the white matter. There was no sign of neurogenesis, no substantial astroglial or microglial proliferation, no change in the ratio of M1 and M2 microglia and no appreciable generation of the terminal complement peptide C5a. One day after injury the number of synaptic terminals on lumbar motoneurons had dropped by a factor of 2, but normalized by 6 days. The ratio of VGLUT1/2+ to VGAT+ terminals remained similar in injured and uninjured spinal cords during this period. By 24 days after injury, when functional recovery is nearly complete, the density of 5HT+ fibers below the injury site had increased by a factor of 2.5. Altogether this study shows that cellular reactions are diverse and dynamic. Pronounced recovery of both excitatory and inhibitory terminals and an increase in serotonergic innervation below the injury, coupled with a general lack of inflammation and reactive gliosis, are likely to contribute to the recovery 2).

1)

Wincek A, Huber J, Leszczyńska K, Fortuna W, Okurowski S, Tabakow P. Results of a long-term uniform system of neurorehabilitation in patients with incomplete thoracic spinal cord injury. Ann Agric Environ Med. 2022 Mar 21;29(1):94-102. doi: 10.26444/aaem/135554. Epub 2021 Apr 15. PMID: 35352911.
2)

Chawla RS, Züchner M, Mastrangelopoulou M, Lambert FM, Glover JC, Boulland JL. Cellular reactions and compensatory tissue re-organization during spontaneous recovery after spinal cord injury in neonatal mice. Dev Neurobiol. 2016 Dec 29. doi: 10.1002/dneu.22479. [Epub ahead of print] PubMed PMID: 28033684.

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

Artificial neural network for traumatic brain injury mortality prediction.

1)

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.
2)

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.
3)

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.
4)

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.
5)

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.
6)

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.
7)

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
8)

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.
9)

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.
10)

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.
11)

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.
12)

Zafonte RD, Hammond FM, Mann NR, Wood DL, Black KL, Millis SR. Relationship between Glasgow coma scale and functional outcome. Am J Phys Med Rehabil. 1996 Sep-Oct;75(5):364-9. PubMed PMID: 8873704.
13)

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.

Electrical stimulation for peripheral nerve injury treatment

Electrical stimulation for peripheral nerve injury treatment

Peripheral nerve injury afflicts individuals from all walks of life. Despite the peripheral nervous system’s intrinsic ability to regenerate, many patients experience incomplete functional recovery. Surgical repair aims to expedite this recovery process in the most thorough manner possible. However, full recovery is still rarely seen especially when nerve injury is compounded with polytrauma where surgical repair is delayed. Pharmaceutical strategies supplementary to nerve microsurgery have been investigated but surgery remains the only viable option 1).

Electrical stimulation is regarded pivotal to promote repair of nerve injury, however, failed to get extensive application in vivo due to the challenges in noninvasive electrical loading accompanying with construction of biomimetic cell niche.

Building on decades of experimental evidence in animal models, several recent, prospective, randomized clinical trials have affirmed electrical stimulation as a clinically translatable technique to enhance functional recovery in patients with peripheral nerve injuries requiring surgical treatment 2).

Implantable wireless stimulators can deliver therapeutic electrical stimulation to injured peripheral nerve tissue. Implantable wireless nerve stimulators might represent a novel means of facilitating therapeutic electrical stimulation in both intraoperative and postoperative settings 3).

Zhang et al. demonstrated a new concept of magneto responsive electric 3D matrix for remote and wireless electrical stimulation. By the preparation of magnetoelectric core/shell structured Fe3 O4 @BaTiO3 NPs-loaded hyaluronan/collagen hydrogels, which recapitulate considerable magneto-electricity and vital features of native neural extracellular matrix, the enhancement of neurogenesis both in cellular level and spinal cord injury in vivo with external pulsed magnetic field applied is proved. The findings pave the way for a novel class of remote controlling and delivering electricity through extracellular niches-mimicked hydrogel network, arising prospects not only in neurogenesis but also in human-computer interaction with higher resolution 4).

The frequency of stimulation is an important factor in the success of both quality and quantity of axon regeneration as well as growth of the surrounding myelin and blood vessels that support the axon. Histological analysis and measurement of regeneration showed that low frequency stimulation had a more successful outcome than high frequency stimulation on regeneration of damaged sciatic nerves.

The use of autologous nerve grafting procedures that involve redirection of regenerative donor nerve fibers into the graft conduit has been successful in restoring target muscle function. Localized delivery of soluble neurotrophic factors may help promote the rate of axon regeneration observed within these graft conduits.

An expanding area of nerve regeneration research deals with the development of scaffolding and bio-conduits. Scaffolding developed from biomaterial would be useful in nerve regeneration if they successfully exhibit essentially the same role as the endoneurial tubes and Schwann cell do in guiding regrowing axons.

The surgeon, who treats nerve injuries, should have knowledge about how peripheral nerves react to trauma, particularly an understanding about the extensive pathophysiological alterations that occur both in the peripheral and in the central nervous system. A large number of factors influence the functional outcome, where the surgeon only can affect a few of them. In view of the new knowledge about the delicate intracellular signaling pathways that are rapidly initiated in neurons and in nonneuronal cells with the purpose to induce nerve regeneration, the timing of nerve repair and reconstruction after injury has gained more interest. It is crucial to understand and to utilize the inborn mechanisms for survival and regeneration of neurons and for activation, survival, and proliferation of the Schwann cells and other cells that are acting after a nerve injury. Thus, experimental and clinical data clearly point toward the advantage of early nerve repair and reconstruction of injuries. Following an appropriate diagnosis of a nerve injury, the nerve should be promptly repaired or reconstructed, and new rehabilitation strategies should early be initiated. Considering nerve transfers in the treatment arsenal can shorten the time of nerve reinnervation of muscle targets. Timing of nerve repair and reconstruction is crucial after nerve injury 5).

1)

Willand MP, Nguyen MA, Borschel GH, Gordon T. Electrical Stimulation to Promote Peripheral Nerve Regeneration. Neurorehabil Neural Repair. 2016 Jun;30(5):490-6. doi: 10.1177/1545968315604399. Epub 2015 Sep 10. PMID: 26359343.
2)

Zuo KJ, Gordon T, Chan KM, Borschel GH. Electrical stimulation to enhance peripheral nerve regeneration: Update in molecular investigations and clinical translation. Exp Neurol. 2020 Oct;332:113397. doi: 10.1016/j.expneurol.2020.113397. Epub 2020 Jul 3. PMID: 32628968.
3)

MacEwan MR, Gamble P, Stephen M, Ray WZ. Therapeutic electrical stimulation of injured peripheral nerve tissue using implantable thin-film wireless nerve stimulators. J Neurosurg. 2018 Feb 9:1-10. doi: 10.3171/2017.8.JNS163020. Epub ahead of print. PMID: 29424647.
4)

Zhang Y, Chen S, Xiao Z, Liu X, Wu C, Wu K, Liu A, Wei D, Sun J, Zhou L, Fan H. Magnetoelectric Nanoparticles Incorporated Biomimetic Matrix for Wireless Electrical Stimulation and Nerve Regeneration. Adv Healthc Mater. 2021 Jun 27:e2100695. doi: 10.1002/adhm.202100695. Epub ahead of print. PMID: 34176235.
5)

Dahlin LB. The role of timing in nerve reconstruction. Int Rev Neurobiol. 2013;109:151-64. doi: 10.1016/B978-0-12-420045-6.00007-9. Review. PubMed PMID: 24093611.

Iatrogenic Iliac Artery Injury

Iatrogenic Iliac Artery Injury

Vascular complications, which we rarely encounter during lumbosacral stabilization surgeries, can be life-threatening if they are not treated quickly. These arterial injuries occur during screw insertion. The presentation with the common iliac artery injury during the decortication process in transverse processes with ‘Pedicle awl‘ will be the first case in the literature as far as Koban et al. know.

Iatrogenic vascular laceration is a rare but well-known complication of posterior lumbar disc surgery (PLUDS).

In a study, the incidence of iatrogenic major vascular injuries in lumbar discectomy was 1 in 1249 operations (0.08%) 1)

Literature review

Akhaddar et al. performed a review of the literature to evaluate the management of this life-threatening complication. A total of 54 papers containing 100 cases of vascular laceration following PLUDS between 1969 and 2018 were analyzed with their representative case with a left common iliac artery (CIA) laceration during a posterior approach for a far lateral L4-L5 disc herniation. There were 54 females and 35 males (12 cases with unreported gender) with ages ranging from 20 to 72 years. The most commonly involved spinal level was L4-L5 (n = 67). The duration from the causative surgery to the symptom of the vascular injury ranged from 0 to 50 h (mean, 7.3 h). Only 47.3% of patients underwent postoperative imaging and the most commonly injured vessel was the CIA (n = 49). Vascular repair, open surgery, and/or an endovascular procedure was performed in 95 patients. The most frequent complications were deep venous thrombosis in the leg and pulmonary emboli, where a complete recovery was seen in 75.3% of patients. The mortality rate was 18.8%. In hemodynamically unstable cases, an emergent exploratory laparotomy was life-saving even without vascular imaging, although angiography with/without endovascular intervention may be used in stable patients 2).

Sealing of common iliac artery or abdominal aortic lesions as a complication of lumbar-disc surgery with a stent graft is effective and is suggested as an excellent alternative to open surgery for iatrogenic great-vessel injuries, particularly in critical conditions 3)

Case reports

Bojarski et al. presented the case of a 57-year-old patient who received surgery for critical degenerative lumbal spinal stenosis on the L4-L5 level. The diagnosis was based on strong right sciatica and neurogenic claudication. A bilateral laminotomy from the right and a microdiscectomy were performed. During surgery, no bleeding from the intervertebral space was observed and blood pressure was low but stable from the beginning. After surgery, the patient was in good general and neurological condition, without preoperative right-sided sciatica. Within a few hours after the operation, the circulatory and respiratory systems were stable with normal saturation and the patient did not report shortness of breath. Paleness of the skin and mucous membranes was observed. Follow-up morphology tests performed at 6 and 10.5 hours after surgery showed a decrease in the level of erythrocytes. The patient had palpable tenderness in the left hypochondriac region. Suspicion of bleeding into the abdominal cavity from arteries or iliac veins was stated. Immediately, an angio-computed tomography (CT) of the abdominal cavity was performed, which confirmed the presence of a hematoma in the peritoneal space and a pseudoaneurysm of the left iliac artery. The patient was urgently transported to the Vascular Surgery Clinic, where a Y-type covered stent was implanted percutaneously into both iliac arteries. After the procedure, there were symptoms of ischaemia in the left lower extremity and intermittent claudication. A Doppler study showed signs of narrowing at the stent level on the left side. The patient was reoperated after a CT check-up and a second stent was implanted into the left iliac artery, which allowed vasodilation and true flow in the artery.

Suggest that both the neurosurgeon and anaesthesiologist should have been aware of the possibility of such a rare but life-threatening complication as iliac vessel damage during lumbar discectomy surgery. A quick diagnosis and implementation of a proper procedure reduces the high mortality rate caused by this complication. In cases of a sudden unjustified drop in blood pressure during lumbar discectomy, an immediate laparotomy should be performed to find and repair the site of laceration of a vessel. In patients who are stable hemodynamically, performing an angio-CT function of the abdominal cavity is suggested and the damaged artery should be treated with a covered stent 4).

LUMBOSACRAL DECOMPRESSION AND STABILIZATION SURGERY WAS PERFORMED IN A 57-YEAR-OLD PATIENT WITH L1-S1 Spinal stenosis and scoliosis. After the stabilization process was completed; while decorticating the transverse processes with ‘pedicle awl‘, the tool fell to the paravertebral region and then active arterial hemorrhage was observed on the surgical site. Hemostasis was achieved in the surgical field, but a rapid progressive drop was observed in the patient’s blood pressure. The surgery was quickly terminated and the patient was turned to the supine position. Vascular surgeons opened the abdomen with midline laparotomy and approximately 2600 cc hematoma was evacuated from the retroperitoneum. The 5 mm defect in the left common iliac artery was repaired by primary suturing. The patient had no problem in postoperative follow-up and was discharged on the 10th postoperative day.

In these complications that we rarely encounter in lumbosacral stabilization surgeries, perioperative findings should be evaluated well, and rapid intervention should be made in cases where vascular injury is considered. One must remember that every tool used during surgery can be dangerous even in an experienced hand 5).

A 31 year old woman was admitted to the neurosurgery department with L5 right-sided sciatica and an associated radiculopathy, and paraesthesia of the first toe of the right foot. She had previously undergone surgical correction of a L4 – L5 lumbar disc herniation, as well as a left oophorectomy and chemotherapy for ovarian neoplasia. A right L5 hemilaminectomy associated with right L5 – S1 foraminotomy and L5 – S1 discectomy was performed with the patient in the ventral position. The procedure was carried out without any apparent complications. In the first three post-operative days the patient complained persistently of orthostatic hypotension and a drop in haemoglobin was observed. Computed tomography angiography revealed what appeared to be a complete transection of the right common iliac artery and vein, with active haemorrhage, and a large pseudoaneurysm. Immediate surgery was carried out with reconstruction consisting of a 9 mm Dacron graft interposed in the right common iliac artery, as well as ligation of the right common iliac vein, which was not amenable to repair. The post-operative period was uneventful. The patient was discharged on day 13 with normal lower limb pulses and mild oedema of the right lower limb, controlled with elastic compression stockings.

Iatrogenic injuries of the large abdominal vessels during spinal surgery is rare but serious. Close patient surveillance and remaining vigilant for these life threatening vascular lesions are crucial in the peri-operative period of spinal surgery 6).

References

1)

Denli Yalvac ES, Balak N. The probability of iatrogenic major vascular injury in lumbar discectomy. Br J Neurosurg. 2020 Jun;34(3):290-298. doi: 10.1080/02688697.2020.1736261. Epub 2020 Mar 9. PMID: 32148105.
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Akhaddar A, Alaoui M, Turgut M, Hall W. Iatrogenic vascular laceration during posterior lumbar disc surgery: a literature review. Neurosurg Rev. 2021 Apr;44(2):821-842. doi: 10.1007/s10143-020-01311-5. Epub 2020 May 12. PMID: 32399729.
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Canaud L, Hireche K, Joyeux F, D’Annoville T, Berthet JP, Marty-Ané C, Alric P. Endovascular repair of aorto-iliac artery injuries after lumbar-spine surgery. Eur J Vasc Endovasc Surg. 2011 Aug;42(2):167-71. doi: 10.1016/j.ejvs.2011.04.011. Epub 2011 May 17. PMID: 21592826.
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Bojarski P, Solonynko B, Stapinska-Syniec A, Sobstyl M, Nazarewski S. Rare iatrogenic iliac artery injury during lumbar disc surgery – a case report. Pol Merkur Lekarski. 2021 Apr 18;49(290):150-152. PMID: 33895764.
5)

Koban O, Akar E, Öğrenci A, Yilmaz M, Dalbayrak S. Any Instrument in Surgeon’s Hand Can Be Fatal: Unusual İliac Artery Injury in Lumbar Spinal Deformity Surgery [published online ahead of print, 2020 Aug 7]. World Neurosurg. 2020;S1878-8750(20)31749-6. doi:10.1016/j.wneu.2020.07.217
6)

Moutinho M, Silvestre L, Belo D, Soares T, Pedro LM. Complete Disruption of The Iliac Vessels During Spinal Surgery With Delayed Presentation. EJVES Short Rep. 2019;43:33-36. Published 2019 May 23. doi:10.1016/j.ejvssr.2019.04.008

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).

Epidemiology in Ethiopia

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).

Epidemiology in China

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).

Epidemiology in the United States

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).

Epidemiology in India

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).

Epidemiology in Europe

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).

Spain

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).

Romania

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).

Traumatic brain injury in skiers

see Traumatic brain injury in skiers.

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Hyder AA, Wunderlich CA, Puvanachandra P, Gururaj G, Kobusingye OC. The impact of traumatic brain injuries: A global perspective. NeuroRehabilitation 2007;22:341-53. Back to cited text no. 1
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Lopez AD, Murray CC. The global burden of disease, 1990-2020. Nat Med 1998;4:1241-3.
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K. S. Quayle, D. M. Jaffe, N. Kuppermann et al., “Diagnostic testing for acute head injury in children: when are head computed tomography and skull radiographs indicated?” Pediatrics, vol. 99, no. 5, article e11, 1997.
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Rangwala SD, Birk DM, Tobin MK, Hahn YS, Nikas DC. Spontaneous Resolution of Spinal Epidural Hematoma Resulting from Domestic Child Abuse: Case Report. Pediatr Neurosurg. 2016 Sep 20. [Epub ahead of print] PubMed PMID: 27644085.
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Dewan MC, Rattani A, Gupta S, Baticulon RE, Hung YC, Punchak M, Agrawal A, Adeleye AO, Shrime MG, Rubiano AM, Rosenfeld JV, Park KB. Estimating the global incidence of traumatic brain injury. J Neurosurg. 2018 Apr 1:1-18. doi: 10.3171/2017.10.JNS17352. [Epub ahead of print] PubMed PMID: 29701556.
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Laeke T, Tirsit A, Kassahun A, Sahlu A, Debebe T, Yesehak B, Masresha S, Deyassa N, Moen BE, Lund-Johansen M, Sundstrøm T. Prospective study of surgery for traumatic brain injury in Addis Ababa, Ethiopia: Trauma causes, injury types and clinical presentation. World Neurosurg. 2021 Feb 7:S1878-8750(21)00184-4. doi: 10.1016/j.wneu.2021.02.003. Epub ahead of print. PMID: 33567370.
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Sun D, Jiang B, Ru X, Sun H, Fu J, Wu S, Wang L, Wang L, Zhang M, Liu B, Wang W; for the NESS-China investigators. Prevalence and Altered Causes of Traumatic Brain Injury in China: A Nationwide Survey in 2013. Neuroepidemiology. 2019 Dec 18:1-8. doi: 10.1159/000501911. [Epub ahead of print] PubMed PMID: 31851999.
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Maas, A. I. R., Menon, D. K., et al. (2012). “Re-orientation of clinical research in traumatic brain injury: report of an international workshop on comparative effectiveness research.” Journal of Neurotrauma 29(1): 32-46.
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Faul M, Xu L, Wald MM & Coronado VG. (2010). Traumatic Brain Injury in the United States: Emergency Department Visits, Hospitalizations and Deaths 2002–2006. Centers for Disease Control and Prevention, National Center for Injury Prevention and Control
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Corrigan JD, Selassie AW, Orman JA. The epidemiology of traumatic brain injury. J Head Trauma Rehabil 2010; 25: 72–80.
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Feinberg M, Mai JC, Ecklund J. Neurosurgical Management in Traumatic Brain Injury. Semin Neurol. 2015 Feb;35(1):50-56. Epub 2015 Feb 25. PubMed PMID: 25714867.
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Ilie G, Mann RE, Hamilton H, Adlaf EM, Boak A, Asbridge M, Rehm J, Cusimano MD. Substance Use and Related Harms Among Adolescents With and Without Traumatic Brain Injury. J Head Trauma Rehabil. 2014 Nov 25. [Epub ahead of print] PubMed PMID: 25427256.
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Satapathy MC, Dash D, Mishra SS, Tripathy SR, Nath PC, Jena SP. Spectrum and outcome of traumatic brain injury in children <15 years: A tertiary level experience in India. Int J Crit Illn Inj Sci. 2016 Jan-Mar;6(1):16-20. PubMed PMID: 27051617.
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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.
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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.