Applicability and clinical utility of the German rivermead post-concussion symptoms questionnaire in proxies of children after traumatic brain injury: an instrument validation study.

BACKGROUND: The German Rivermead Post-Concussion Symptoms Questionnaire (RPQ) can be used to assess post-concussion symptoms (PCS) after traumatic brain injury (TBI) in adults, adolescents, and children. METHODS: In this study, we examined the psychometric properties of the German RPQ proxy version (N = 146) for children (8-12 years) after TBI at the item, total and scale score level. Construct validity was analyzed using rank correlations with the proxy-assessed Post-Concussion Symptoms Inventory (PCSI-P), the Patient Health Questionnaire 9 (PHQ-9), and the Generalized Anxiety Disorder Scale 7 (GAD-7). Furthermore, sensitivity testing was performed concerning subjects' sociodemographic and injury-related characteristics. Differential item functioning (DIF) was analyzed to assess the comparability of RPQ proxy ratings for children with those for adolescents. RESULTS: Good internal consistency was demonstrated regarding Cronbach's α (0.81-0.90) and McDonald's ω (0.84-0.92). The factorial validity of a three-factor model was superior to the original one-factor model. Proxy ratings of the RPQ total and scale scores were strongly correlated with the PCSI-P (ϱ = 0.50-0.69), as well as moderately to strongly correlated with the PHQ-9 (ϱ = 0.49-0.65) and the GAD-7 (ϱ = 0.44-0.64). The DIF analysis revealed no relevant differences between the child and adolescent proxy versions. CONCLUSIONS: The German RPQ proxy is a psychometrically reliable and valid instrument for assessing PCS in children after TBI. Therefore, RPQ self- and proxy-ratings can be used to assess PCS in childhood as well as along the lifespan of an individual after TBI.

Refining outcome prediction after traumatic brain injury with machine learning algorithms.

Outcome after traumatic brain injury (TBI) is typically assessed using the Glasgow outcome scale extended (GOSE) with levels from 1 (death) to 8 (upper good recovery). Outcome prediction has classically been dichotomized into either dead/alive or favorable/unfavorable outcome. Binary outcome prediction models limit the possibility of detecting subtle yet significant improvements. We set out to explore different machine learning methods with the purpose of mapping their predictions to the full 8 grade scale GOSE following TBI. The models were set up using the variables: age, GCS-motor score, pupillary reaction, and Marshall CT score. For model setup and internal validation, a total of 866 patients could be included. For external validation, a cohort of 369 patients were included from Leuven, Belgium, and a cohort of 573 patients from the US multi-center ProTECT III study. Our findings indicate that proportional odds logistic regression (POLR), random forest regression, and a neural network model achieved accuracy values of 0.3-0.35 when applied to internal data, compared to the random baseline which is 0.125 for eight categories. The models demonstrated satisfactory performance during external validation in the data from Leuven, however, their performance were not satisfactory when applied to the ProTECT III dataset.

Trauma diagnostic-related target proteins and their detection techniques.

Trauma is a significant health issue that not only leads to immediate death in many cases but also causes severe complications, such as sepsis, thrombosis, haemorrhage, acute respiratory distress syndrome and traumatic brain injury, among trauma patients. Target protein identification technology is a vital technique in the field of biomedical research, enabling the study of biomolecular interactions, drug discovery and disease treatment. It plays a crucial role in identifying key protein targets associated with specific diseases or biological processes, facilitating further research, drug design and the development of treatment strategies. The application of target protein technology in biomarker detection enables the timely identification of newly emerging infections and complications in trauma patients, facilitating expeditious medical interventions and leading to reduced post-trauma mortality rates and improved patient prognoses. This review provides an overview of the current applications of target protein identification technology in trauma-related complications and provides a brief overview of the current target protein identification technology, with the aim of reducing post-trauma mortality, improving diagnostic efficiency and prognostic outcomes for patients.

Weight-Drop Method for Inducing Closed Head Diffuse Traumatic Brain Injury.

Traumatic brain injury (TBI) is one of the foremost causes of disability and death globally. Prerequisites for successful therapy of disabilities associated with TBI involved improved knowledge of the neurobiology of TBI, measurement of quantitative changes in recovery dynamics brought about by therapy, and the translation of quantitative methodologies and techniques that were successful in tracking recovery in preclinical models to human TBI. Frequently used animal models of TBI in research and development include controlled cortical impact, fluid percussion injury, blast injury, penetrating blast brain injury, and weight-drop impact acceleration models. Preclinical models of TBI benefit from controlled injury settings and the best prospects for biometric quantification of injury and therapy-induced gradual recovery from disabilities. Impact acceleration closed head TBI paradigm causes diffuse TBI (DTBI) without substantial focal brain lesions in rats. DTBI is linked to a significant rate of death, morbidity, and long-term disability. DTBI is difficult to diagnose at the time of hospitalization with imaging techniques making it challenging to take prompt therapeutic action. The weight-drop method without craniotomy is an impact acceleration closed head DTBI model that is used to induce mild/moderate diffuse brain injuries in rodents. Additionally, we have characterized neuropathological and neurobehavioral outcomes of the weight-drop model without craniotomy for inducing closed head DTBI of graded severity with a range of mass of weights (50-450 gm). This chapter also discusses techniques and protocols for measuring numerous functional disabilities and pathological changes in the brain brought on by DTBI.

Management of Head Trauma.

Traumatic brain injury (TBI) represents a heterogenous spectrum of disease. It is essential to rapidly assess a patient's neurologic status and implement measures to prevent secondary brain injury. Intracranial hypertension, a common sequela of TBI, is managed in a tiered and systematic fashion, starting with the least invasive and moving toward the most invasive. TBI has long-lasting effects on patients and their families and represents a substantial financial and social influence on society. Research regarding the prognosis and treatment of TBI is essential to limit the influence of this widespread disease.

Predictive value of the Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory rate and Systolic blood pressure score (TRIAGES) for the short-term mortality of older patients with isolated traumatic brain injury: a retrospective cohort study.

OBJECTIVES: This study aimed to evaluate the effectiveness of the Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory rate and Systolic blood pressure score (TRIAGES) in predicting 24-hour in-hospital mortality among patients aged 65 years and older with isolated traumatic brain injury (TBI). DESIGN: A retrospective, single-centre cohort study. SETTING: This study was conducted at a government-run tertiary comprehensive hospital. PARTICIPANTS: This study included 982 patients aged 65 years or older with isolated TBI, who were admitted to the emergency department between 1 January 2020 and 31 December 2021. INTERVENTIONS: None. PRIMARY OUTCOME: 24-hour in-hospital mortality was the primary outcome. RESULTS: Among the 982 patients, 8.75% died within 24 hours of admission. The non-survivors typically had higher TRIAGES and lower GCS scores. Logistic regression showed significant associations of both TRIAGES and GCS with mortality; the adjusted ORs were 1.98 (95% CI 1.74 to 2.25) for TRIAGES and 0.72 (95% CI 0.68 to 0.77) for GCS. Receiver operating characteristic (ROC) analysis indicated an area under the ROC curve of 0.86 for GCS and 0.88 for TRIAGES, with a significant difference (p=0.012). However, precision-recall curve (PRC) analysis revealed an area under the PRC of 0.38 for GCS and 0.47 for TRIAGES, without a significant difference (p=0.107). CONCLUSIONS: The TRIAGES system is a promising tool for predicting 24-hour in-hospital mortality in older patients with TBI, demonstrating comparable or slightly superior efficacy to the GCS. Further multicentre studies are recommended for validation.

Utilizing ultra-early continuous physiologic data to develop automated measures of clinical severity in a traumatic brain injury population.

Determination of prognosis in the triage process after traumatic brain injury (TBI) is difficult to achieve. Current severity measures like the Trauma and injury severity score (TRISS) and revised trauma score (RTS) rely on additional information from the Glasgow Coma Scale (GCS) and the Injury Severity Score (ISS) which may be inaccurate or delayed, limiting their usefulness in the rapid triage setting. We hypothesized that machine learning based estimations of GCS and ISS obtained through modeling of continuous vital sign features could be used to rapidly derive an automated RTS and TRISS. We derived variables from electrocardiograms (ECG), photoplethysmography (PPG), and blood pressure using continuous data obtained in the first 15 min of admission to build machine learning models of GCS and ISS (ML-GCS and ML-ISS). We compared the TRISS and RTS using ML-ISS and ML-GCS and its value using the actual ISS and GCS in predicting in-hospital mortality. Models were tested in TBI with systemic injury (head abbreviated injury scale (AIS) ≥ 1), and isolated TBI (head AIS ≥ 1 and other AIS ≤ 1). The area under the receiver operating characteristic curve (AUROC) was used to evaluate model performance. A total of 21,077 cases (2009-2015) were in the training set. 6057 cases from 2016 to 2017 were used for testing, with 472 (7.8%) severe TBI (GCS 3-8), 223 (3.7%) moderate TBI (GCS 9-12), and 5913 (88.5%) mild TBI (GCS 13-15). In the TBI with systemic injury group, ML-TRISS had similar AUROC (0.963) to TRISS (0.965) in predicting mortality. ML-RTS had AUROC (0.823) and RTS had AUROC 0.928. In the isolated TBI group, ML-TRISS had AUROC 0.977, and TRISS had AUROC 0.983. ML-RTS had AUROC 0.790 and RTS had AUROC 0.957. Estimation of ISS and GCS from machine learning based modeling of vital sign features can be utilized to provide accurate assessments of the RTS and TRISS in a population of TBI patients. Automation of these scores could be utilized to enhance triage and resource allocation during the ultra-early phase of resuscitation.

Identification of novel blood-based extracellular vesicles biomarker candidates with potential specificity for traumatic brain injury in polytrauma patients.

Objective: The goal of this study was to identify changes in extracellular vesicles (EV) surface proteins specific to traumatic brain injury (TBI), which could be used as a diagnostic and prognostic tool in polytrauma patients. Summary Background Data: Known serum TBI-specific biomarkers (S100B, NSE, and GFAP), which can predict the severity and outcome of isolated TBI, lose their predictive value in the presence of additional extracranial injuries. Extracellular vesicles (EVs) are released from cells in response to various stimuli and carry specific cargo/surface molecules that could be used for tracking injury-responding cells. Methods: EVs were isolated using size exclusion chromatography (SEC) from the plasma of two groups of patients (with isolated TBI, ISS≥16, AIShead≥4, n=10; and polytraumatized patients without TBI ISS≥16, AIShead=0, n=10) collected in the emergency room and 48 h after trauma. EVs' surface epitope expression was investigated using a neurospecific multiplex flow cytometry assay and compared with healthy controls (n=10). Three enrichments of EV epitopes found to be specific to TBI were validated by western blot. Results: The expression of 10 EV epitopes differed significantly among the patient and control groups, and five of these epitopes (CD13, CD196, MOG, CD133, and MBP) were TBI-specific. The increased expression of CD196, CD13, and MOG-positive EVs was validated by western blot. Conclusion: Our data showed that TBI is characterized by a significant increase of CD13, CD196, MOG, CD133, and MBP-positive EVs in patients' plasma. A high level of MOG-positive EVs negatively correlated with the Glasgow Coma Scale score at admission and could be an indicator of poor neurological status.

Prevalence of fatigue and cognitive impairment after traumatic brain injury.

BACKGROUND: Following traumatic brain injury (TBI) some patients develop lingering comorbid symptoms of fatigue and cognitive impairment. The mild cognitive impairment self-reported by patients is often not detected with neurocognitive tests making it difficult to determine how common and severe these symptoms are in individuals with a history of TBI. This study was conducted to determine the relative prevalence of fatigue and cognitive impairment in individuals with a history of TBI. METHODS: The Fatigue and Altered Cognition Scale (FACs) digital questionnaire was used to assess self-reported fatigue and cognitive impairment. Adults aged 18-70 were digitally recruited for the online anonymous study. Eligible participants provided online consent, demographic data, information about lifetime TBI history, and completed the 20 item FACs questionnaire. RESULTS: A total of 519 qualifying participants completed the online digital study which included 204 participants with a history of TBI of varied cause and severity and 315 with no history of TBI. FACs Total Score was significantly higher in the TBI group (57.7 ± 22.2) compared to non-TBI (39.5 ± 23.9; p<0.0001) indicating more fatigue and cognitive impairment. When stratified by TBI severity, FACs score was significantly higher for all severity including mild (53.9 ± 21.9, p<0.0001), moderate (54.8 ± 24.4, p<0.0001), and severe (59.7 ± 20.9, p<0.0001) TBI. Correlation analysis indicated that more severe TBI was associated with greater symptom severity (p<0.0001, r = 0.3165). Ancillary analysis also suggested that FACs scores may be elevated in participants with prior COVID-19 infection but no history of TBI. CONCLUSIONS: Adults with a history of even mild TBI report significantly greater fatigue and cognitive impairment than those with no history of TBI, and symptoms are more profound with greater TBI severity.

Efficacy of a virtual reality-based cognitive interactive training program for children with traumatic brain injuries: study protocol for a parallel-group randomized controlled trial.

BACKGROUND: Traumatic brain injury (TBI) is a leading cause of disability in children. Cognitive rehabilitation for this population is critical for their long-term health outcomes. This trial aims to evaluate the efficacy of a virtual reality-based program (VICT) for training executive functions in children with TBI. METHODS: A parallel group randomized controlled trial will be conducted among up to 32 children with TBI. Children in the intervention group will receive the VICT training while children in the control group will play a comparable VR game without executive function training. Each participant will be assessed at baseline, post-intervention, and 1-month follow-up. Outcomes will include core executive functions, attention, and health-related quality of life measured by computerized tasks or standardized questionnaires. DISCUSSION: Cognitive rehabilitation is among the top healthcare needs for pediatric TBI patients. Virtual reality-based training is promising due to its versatile content, flexibility, and potential cost savings for both patients and providers. Findings of this trial will provide data on the efficacy of the VICT program on core executive functions, attention problems, and health-related quality of life and serve as the empirical foundation for future larger multi-site effectiveness trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT04526639 . Registered on August 18, 2020.

TRAUMATIC BRAIN INJURY AND ITS IMPLICATIONS FOR BEHAVIORAL HEALTH FACTORS.

The constant increase in the level of traumatic brain injuries in recent years, the frequent cases of disability and mortality associated with them require in-depth comprehensive research to study the problem on the ground, its medical, social, and economic aspects, which is very important for improving organizational measures to reduce traumatization among all age groups of the population. Objectives - to determine the presence and nature of structural damage associated with traumatic brain injury. The presence and nature of structural damage associated with traumatic brain injury. The studies included data on the treatment of victims with traumatic brain injuries from 2016 to 2020 on the basis of the Surgical Clinic of the Azerbaijan Medical University. Among the victims, men accounted for 77.9% and women 22.1%. In a prospective comparative study, after signing informed consent, 299 people of different sexes were included, of which 90 were victims with isolated TBI. The inclusion criteria for the study were as follows: victims with a verified diagnosis of TBI; age over 18; patients without concomitant somatic pathology. In a gender-comparative analysis of the revealed data, an injury combined with fractures of the bones of the extremities was recorded in 77 (81.1%) males and 18 of their female opponents, who also received TBI and accounted for 18.9%. Also high, especially in the male half of the examined injured persons, was the frequency of occurrence of TBI combinations with rib fractures and injuries of the chest organs, such injuries were registered in 41 victims, which accounted for 77.4% of all the above combined TBI. Somewhat less in both sex groups was TBI in combination with traumatic injuries of organs and tissues of the abdominal region, as well as with mixed injuries (χ2 criterion is 2.066; Df=4; p=0.724). The lowest level of TBI was observed in people under the age of 20 and older than 70 years, in other groups this figure increased sharply, reaching a maximum at the age of 20-29 and 40-49 years, and stabilized in the age groups over 49 years. The maximum number of cases associated with partial or complete loss of consciousness was recorded in persons aggravated by simultaneous traumatization of the upper or lower extremities and chest, as well as in isolated TBI.

Symptoms and Functional Outcomes Among Traumatic Brain Injury Patients 3- to 12-Months Post-Injury.

BACKGROUND: Patients with traumatic brain injury (TBI) experience a variety of physical, cognitive, and affective symptoms. However, the evolution of symptoms, especially during the 3- to 12-month convalescence period (when recovery of function is still possible), is understudied. OBJECTIVE: This study aims to identify symptoms and the relationships with functional outcomes that occur during the 3- to 12-month period after a TBI. METHODS: Participants who were 3 to 12 months post-TBI were recruited from a South Florida TBI clinic from May 2022 to June 2023. Clinical data were obtained from the electronic health record. Participants completed the Brain Injury Association of Virginia Symptom Checklist, Neuro-Quality of Life Cognitive Function, Anxiety, Depression, and Sleep Disturbance assessments to report symptoms, and the Disability Rating Scale and Satisfaction with Life Scale. Descriptive statistics were used to characterize demographics and symptoms. Linear regression was performed to analyze the relationships between symptoms and outcomes. RESULTS: A total of N = 39 patients participated in the study. Memory problems and difficulty concentrating were the most common symptoms. Hospital length of stay, intensive care unit length of stay, cognitive, and physical symptoms were significantly associated with the Disability Rating Scale score. Physical, cognitive, depressive, and anxiety symptoms had significant associations with the Satisfaction with Life Scale. CONCLUSION: Cognitive symptoms should be integrated into the clinical care of rehabilitating TBI patients. Nurses should monitor for physical, affective, and cognitive symptoms during the recovery phase of TBI.

Traumatic Brain Injury, Psychological Trauma Exposure, and Anxious and Depressive Symptoms in a Clinical Population.

BACKGROUND: Approximately 90% of adults endorse psychological trauma exposure. However, barriers to assessment of psychological trauma and sequelae include limited access to care, lack of standardized assessments in nonpsychiatric settings, and comorbid diagnoses, such as traumatic brain injury (TBI), that may mimic psychiatric syndromes. OBJECTIVES: This study aims to assess the prevalence rates of psychological trauma exposure and TBI to understand the relationship of these experiences with current psychiatric symptoms. METHODS: This is a cross-sectional study of a convenience sample of adult patients (age 18 years and older) referred for outpatient evaluation at a neuropsychology clinic in the Western United States between September 2021 and October 2022. Patients completed a clinical interview to assess their history of psychological trauma, TBI, and current psychiatric symptoms. RESULTS: A total of 118 patients met inclusion criteria. Patients in the TBI group (n = 83) endorsed significantly higher rates of childhood trauma and prior physical, emotional, and sexual abuse compared with the No TBI group (n = 35). Psychological trauma exposure and TBI significantly predicted current anxiety and depressive symptoms, but there was no interaction between these experiences in predicting current psychiatric symptoms. CONCLUSIONS: Individuals with prior TBI experienced psychological trauma, particularly childhood trauma, at a significantly higher rate than those without TBI. Psychological trauma exposure and TBI independently predicted anxious and depressive symptoms, suggesting both may be viable treatment targets. Evaluation of prior psychological trauma exposure during evaluation of TBI may provide opportunities for trauma-informed care and may allow for improved outpatient treatment planning.

Impact of Triage Systems on Time to Diagnosis and Treatment of Traumatic Brain Injuries.

BACKGROUND: Intracerebral hemorrhage (ICH) is a potential complication from traumatic brain injury, with a 30-day mortality rate of 35-52%. Rapid diagnosis allows for earlier treatment, which impacts patient outcomes. A trauma activation (TA) is called when injury severity meets institutional criteria. The patient is immediately roomed, and a multispecialty team is present. A trauma evaluation (TE) occurs when injuries are identified after standard triage processes. OBJECTIVES: Our aim was to determine whether TA patients with ICH were diagnosed and treated more rapidly than TE patients. METHODS: This was a retrospective study of patients presenting to trauma centers within a large hospital system diagnosed with traumatic ICH between January 2018 and December 2018. Patients were categorized as TA or TE patients. The time to diagnosis was compared between groups, and additional times were evaluated, including time to imaging, computed tomography interpretation, and treatment. RESULTS: A total of 294 patients were included. Groups had similar demographic characteristics and medical history; there was no difference in head Abbreviated Injury Score, Injury Severity Score, or anticoagulant use. Time to diagnosis was decreased for TA patients compared with TE patients (p < 0.0001). In addition, TA patients received treatment sooner (median 107 min) than TE patients (184.5 min) (p < 0.0001). CONCLUSIONS: Diagnosis and treatment times were significantly faster in TA patients than in TE patients. Given the similarities in injury severity between groups, the increased time to treatment may be detrimental for patients. Trauma activations are a resource-heavy process, but TE delays care. These data suggest that an intermediary process may be beneficial.

A pilot clinical study to estimate intracranial pressure utilising cerebral photoplethysmograms in traumatic brain injury patients.

PURPOSE: In this research, a non-invasive intracranial pressure (nICP) optical sensor was developed and evaluated in a clinical pilot study. The technology relied on infrared light to probe brain tissue, using photodetectors to capture backscattered light modulated by vascular pulsations within the brain's vascular tissue. The underlying hypothesis was that changes in extramural arterial pressure could affect the morphology of recorded optical signals (photoplethysmograms, or PPGs), and analysing these signals with a custom algorithm could enable the non-invasive calculation of intracranial pressure (nICP). METHODS: This pilot study was the first to evaluate the nICP probe alongside invasive ICP monitoring as a gold standard. nICP monitoring occurred in 40 patients undergoing invasive ICP monitoring, with data randomly split for machine learning. Quality PPG signals were extracted and analysed for time-based features. The study employed Bland-Altman analysis and ROC curve calculations to assess nICP accuracy compared to invasive ICP data. RESULTS: Successful acquisition of cerebral PPG signals from traumatic brain injury (TBI) patients allowed for the development of a bagging tree model to estimate nICP non-invasively. The nICP estimation exhibited 95% limits of agreement of 3.8 mmHg with minimal bias and a correlation of 0.8254 with invasive ICP monitoring. ROC curve analysis showed strong diagnostic capability with 80% sensitivity and 89% specificity. CONCLUSION: The clinical evaluation of this innovative optical nICP sensor revealed its ability to estimate ICP non-invasively with acceptable and clinically useful accuracy. This breakthrough opens the door to further technological refinement and larger-scale clinical studies in the future. TRIAL REGISTRATION: NCT05632302, 11th November 2022, retrospectively registered.

Human factor engineering of point-of-care near infrared spectroscopy device for intracranial hemorrhage detection in Traumatic Brain Injury: A multi-center comparative study using a hybrid methodology.

OBJECTIVE: This study assessed machine learning powered Near-infrared spectroscopy based (mNIRS) device's usability and human factor ergonomics in four distinct healthcare provider groups. BACKGROUND: Traumatic Brain Injury (TBI) is a global concern with significant well-being implications. Timely intracranial hemorrhage (ICH) detection is crucial. mNIRS offers efficient non-invasive TBI screening. METHODS: Two device utilization stages involved operators (N = 21) and TBI-suspected subjects (n = 120). A hybrid approach used qualitative and quantitative methods, utilizing a 57-item survey and task completion time. RESULTS: All groups positively perceived user-interface, physical, cognitive, and organizational ergonomics. The device's ease of use, calibration, size, cognitive support, and integration gained appreciation. Training reduced task completion time from 16.5 to 13.2 s. CONCLUSION: mNIRS-based CEREBO® proves usable for TBI point-of-care assessment. Positive feedback from diverse healthcare groups validates design and cost-effectiveness alignment. A hybrid approach, training, and practice scans enhance usage and experience.

Story Grammar Analyses Capture Discourse Improvement in the First 2 Years Following a Severe Traumatic Brain Injury.

PURPOSE: Narration within a story grammar framework requires speakers to organize characters and events logically. Despite abundant research characterizing narrative deficits following a traumatic brain injury (TBI), the evolution of narrative story grammar over the first 2 years post-TBI has rarely been explored. This study analyzed story grammar in complex narratives of adults with and without severe TBI to (a) examine between-group differences and (b) investigate longitudinal changes over the first 2 years post-TBI. METHOD: Story grammar analyses of Cinderella narratives from 57 participants with TBI and 57 participants with no brain injury yielded measures of productivity (total number of episodes, total number of story grammar elements), elaboration (total number of elaborated-complete episodes, mean number of episodic elements per episode), and completeness (total number of incomplete episodes). Mann-Whitney U tests compared measures across groups; generalized estimating equation (GEE) models identified predictors of change, including recovery time (3, 6, 9, 12, and 24 months post-TBI) and demographic/injury-related characteristics. RESULTS: Between-group differences were statistically significant for all productivity and elaboration measures at 3, 6, and 9 months post-TBI; one productivity measure and one elaboration measure at 12 months; and none of the measures at 24 months. GEE models showed significant improvements in all productivity and elaboration measures over the first 24 months post-TBI, with educational attainment and duration of posttraumatic amnesia affecting recovery. Incomplete episodes only showed between-group differences at 12 months and did not capture recovery. CONCLUSION: Productivity and elaboration are key story grammar variables that (a) differentiate complex narration in individuals with and without severe TBI and (b) capture narrative improvements over the first 2 years post-TBI. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25148999.

Association of mild traumatic brain injury, post-traumatic stress disorder, and other comorbidities on photosensitivity.

SIGNIFICANCE: Photosensitivity is common after mild traumatic brain injury. However, this study demonstrates that photosensitivity is also impacted by common comorbidities that often occur with mild traumatic brain injury. Understanding how physical and psychological traumas impact photosensitivity can help improve provider care to trauma survivors and guide novel therapeutic interventions. PURPOSE: This study aimed to characterize the association between mild traumatic brain injury and common comorbidities on photosensitivity in post-9/11 veterans. METHODS: Existing data from the Translational Research Center for TBI and Stress Disorders cohort study were analyzed including traumatic brain injury history and post-traumatic stress disorder clinical diagnostic interviews; sleep quality, anxiety, and depression symptoms self-report questionnaires; and photosensitivity severity self-report from the Neurobehavioral Symptom Inventory. Analysis of covariance and multiple ordinal regression models were used to assess associations between mild traumatic brain injury and common comorbidities with photosensitivity severity. RESULTS: Six hundred forty-one post-9/11 veterans were included in this study. An initial analysis showed that both mild traumatic brain injury and current post-traumatic stress disorder diagnosis were independently associated with higher photosensitivity ratings compared with veterans without either condition, with no interaction observed between these two conditions. Results of the ordinal regression models demonstrated positive associations between degree of photosensitivity and the number of mild traumatic brain injuries during military service and current post-traumatic stress disorder symptom severity, particularly hyperarousal symptoms, even when controlling for other factors. In addition, the degree of sleep disturbances and current anxiety symptoms were both positively associated with photosensitivity ratings, whereas depression symptoms, age, and sex were not. CONCLUSIONS: Repetitive mild traumatic brain injury, post-traumatic stress disorder, anxiety, and sleep disturbances were all found to significantly impact photosensitivity severity and are therefore important clinical factors that eye care providers should consider when managing veterans with a history of deployment-related trauma reporting photosensitivity symptoms.