Importance: Up to 30% of individuals who sustain a mild traumatic brain injury (mTBI) develop persisting symptoms after concussion (PSAC). Identifying acute risk factors for PSAC can enhance clinical care in adults with concussion.Objective: To evaluate summary odds ratio (OR) estimates for acute factors associated with PSAC in adults with mTBI.Data Sources: For this systematic review and meta-analysis, a systematic search of Ovid MEDLINE, Embase, PsycINFO, CINAHL, SPORTDiscus, and the Cochrane Central Register of Clinical Trials (studies published from 1970 to February 15, 2024) and backward reference searching was performed on February 15, 2024. Search terms were mTBI, concussion, prognostic variables, predictors, and PSAC.Study Selection: Peer-reviewed studies in English that reported clinical factors collected within 1 month (≤28 days) of injury and associated with poor outcome, specifically PSAC, more than 1 month after concussion were included. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline was followed.Data Extraction and Synthesis: Independent extraction and quality assessment were performed by 2 author reviewers. Study characteristics and ORs were extracted using the Modified Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prognostic Factor Studies. Risk of bias was assessed using the Quality in Prognostic Studies tool. Three-level meta-analytic models examined factors associated with PSAC 1, 3, and 6 months after mTBI.Main Outcomes and Measures: Adjusted OR (AOR) estimates for the association of acute clinical measures with PSAC.Results: Thirty-four studies were reviewed; data were extracted from 15 studies (44.1%) included in the meta-analysis (592 406 adults with concussion; mean age, 29.3 years [range, 16-89 years]; 57.8% male). Acute concentration difficulty was associated with greatest odds of PSAC across all time points (AOR, 3.43 [95% CI, 1.85-6.36]). Medical history of anxiety and/or depression or of sleep disorders (AOR, 2.47 [95% CI, 1.62-3.78]) and clinical signs (loss of consciousness and amnesia; AOR, 1.90 [95% CI, 1.28-2.84]) were associated with increased odds of PSAC across all time points. At 1 month (AOR, 3.12 [95% CI, 1.43-6.82]) and 6 months (AOR, 26.81 [95% CI, 3.42-210.06]), difficulty concentrating was associated with greatest odds of PSAC, while medical history of anxiety and/or depression or of sleep disorders was associated with greatest odds of PSAC at 3 months (AOR, 2.92 [95% CI, 1.39-6.14]).Conclusions and Relevance: In this systematic review and meta-analysis, acute cognitive symptoms, medical history of anxiety and/or depression or of sleep disorders, and the presence of clinical signs (loss of consciousness and amnesia) were the factors associated with greatest odds of PSAC in adults across all time points. The findings suggest that evaluating specific acute symptoms and signs may contribute to the prognosis of PSAC in adults.

Current assessment tools for sport-related concussion are limited by a reliance on subjective interpretation and patient symptom reporting. Robotic assessments may provide more objective and precise measures of neurological function than traditional clinical tests. To determine the reliability of assessments of sensory, motor and cognitive function conducted with the KINARM end-point robotic device in young adult elite athletes. Sixty-four randomly selected healthy, young adult elite athletes participated. Twenty-five individuals (25 M, mean age±SD, 20.2±2.1 years) participated in a within-season study, where three assessments were conducted within a single season (assessments labeled by session: S1, S2, S3). An additional 39 individuals (28M; 22.8±6.0 years) participated in a year-to-year study, where annual pre-season assessments were conducted for three consecutive seasons (assessments labeled by year: Y1, Y2, Y3). Forty-four parameters from five robotic tasks (Visually Guided Reaching, Position Matching, Object Hit, Object Hit and Avoid, and Trail Making B) and overall Task Scores describing performance on each task were quantified. Test-retest reliability was determined by intra-class correlation coefficients (ICCs) between the first and second, and second and third assessments. In the within-season study, ICCs were ≥0.50 for 68% of parameters between S1 and S2, 80% of parameters between S2 and S3, and for three of the five Task Scores both between S1 and S2, and S2 and S3. In the year-to-year study, ICCs were ≥0.50 for 64% of parameters between Y1 and Y2, 82% of parameters between Y2 and Y3, and for four of the five Task Scores both between Y1 and Y2, and Y2 and Y3. Overall, the results suggest moderate-to-good test-retest reliability for the majority of parameters measured by the KINARM robot in healthy young adult elite athletes. Future work will consider the potential use of this information for clinical assessment of concussion-related neurological deficits.

Growth hormone deficiency (GHD) is a potential consequence of traumatic brain injury (TBI), including sport-related concussion (SRC). GH stimulation testing is required for definitive diagnosis; however, this is resource intensive and can be associated with adverse symptoms or risks. Measurement of serum IGF-1 is more practical and accessible, and pituitary tumour patients with hypopituitarism and low serum IGF-1 have been shown to have a high probability of GHD. We aimed to evaluate IGF-1 measurement for diagnosing GHD in our local TBI population. We conducted a retrospective chart review of patients evaluated for GHD at the TBI clinic and referred for GH stimulation testing with insulin tolerance test (ITT) or glucagon stimulation test (GST) since December 2013. We obtained demographics, TBI severity, IGF-1, data pertaining to pituitary function, and GH stimulation results. IGF-1 values were used to calculate z-scores per age and gender specific reference ranges. Receiver operator curve analysis was performed to evaluate diagnostic threshold of IGF-1 z-score for determining GHD by GST or ITT. Sixty four patient charts were reviewed. 48 patients had mild, six had moderate, eight had severe TBI, and two had non-traumatic brain injuries. 47 patients underwent ITT or GST. 27 were confirmed to have GHD (peak hGH < 5 μg/L). IGF-1 level was within the age and gender specific reference range for all patients with confirmed GHD following GH stimulation testing. Only one patient had a baseline IGF-1 level below the age and gender specific reference range; this patient had a normal response to GH stimulation testing. ROC analysis showed IGF-1 z-score AUC f, confirming lack of diagnostic utility. Baseline IGF-1 is not a useful predictor of GHD in our local TBI population, and therefore has no value as a screening tool. TBI patients undergoing pituitary evaluation will require a dynamic test of GH reserve.

Analysis of fluid metabolites has the potential to provide insight into the neuropathophysiology of injury in patients with traumatic brain injury (TBI). Using a ¹H nuclear magnetic resonance (NMR)-based quantitative metabolic profiling approach, this study determined (1) if urinary metabolites change during recovery in patients with mild to severe TBI; (2) whether changes in urinary metabolites correlate to injury severity; (3) whether biological pathway analysis reflects mechanisms that mediate neural damage/repair throughout TBI recovery. Urine samples were collected within 7 days and at 6-months post-injury in male participants (n = 8) with mild-severe TBI. Samples were analyzed with NMR-based quantitative spectroscopy for metabolomic profiles and analyzed with multivariate statistical and machine learning-based analyses. Lower levels of homovanillate (R = −0.74, p ≤ 0.001), L-methionine (R = −0.78, p < 0.001), and thymine (R = −0.85, p < 0.001) negatively correlated to injury severity. Pathway analysis revealed purine metabolism to be a primary pathway (p < 0.01) impacted by TBI. This study provides pilot data to support the use of urinary metabolites in clinical practice to better interpret biochemical changes underlying TBI severity and recovery. The discovery of urinary metabolites as biomarkers may assist in objective and rapid identification of TBI severity and prognosis. Thus, ¹H NMR metabolomics has the potential to facilitate the adaptation of treatment programs that are personalized to the patient’s needs.

A 61-year-old man sustained a mild traumatic brain injury (mTBI) following a pedestrian versus vehicle traffic accident. Post injury, he began to experience symptoms including light-headedness, spatial disorientation, nausea, fatigue and prominent dizziness brought on by postural change, physical activity or eye movements. Symptoms of dizziness persisted for over 5 years, despite numerous extensive and rigorous vestibular and vision therapy regimens. All investigations suggested normal peripheral and central vestibular functioning. The patient underwent 10 sessions of repetitive transcranial magnetic stimulation (rTMS) treatment, with stimulation of the left dorsolateral prefrontal cortex at 70% of resting motor threshold and a frequency of 10 Hz. Dizziness symptom severity and frequency were reduced by greater than 50% at 3 months post treatment, with a clinically significant reduction of dizziness disability from 40 to 21 points on the Dizziness Handicap Inventory. We propose rTMS as a safe, effective and cost-effective treatment option for patients who experience persistent post-traumatic dizziness secondary to mTBI.

The assessment, management, and prognostication of spinal cord injury (SCI) mainly rely upon observer-based ordinal scales measures. ¹H nuclear magnetic resonance (NMR) spectroscopy provides an effective approach for the discovery of objective biomarkers from biofluids. These biomarkers have the potential to aid in understanding recovery following SCI. This proof-of-principle study determined: (a) If temporal changes in blood metabolites reflect the extent of recovery following SCI; (b) whether changes in blood-derived metabolites serve as prognostic indicators of patient outcomes based on the spinal cord independence measure (SCIM); and (c) whether metabolic pathways involved in recovery processes may provide insights into mechanisms that mediate neural damage and repair. Morning blood samples were collected from male complete and incomplete SCI patients (n = 7) following injury and at 6 months post-injury. Multivariate analyses were used to identify changes in serum metabolic profiles and were correlated to clinical outcomes. Specifically, acetyl phosphate, 1,3,7-trimethyluric acid, 1,9-dimethyluric acid, and acetic acid significantly related to SCIM scores. These preliminary findings suggest that specific metabolites may serve as proxy measures of the SCI phenotype and prognostic markers of recovery. Thus, serum metabolite analysis combined with machine learning holds promise in understanding the physiology of SCI and aiding in prognosticating outcomes following injury.