Blood biomarkers for mild traumatic brain injury: a selective review of unresolved issues.

BACKGROUND: The use of blood biomarkers after mild traumatic brain injury (mTBI) has been widely studied. We have identified eight unresolved issues related to the use of five commonly investigated blood biomarkers: neurofilament light chain, ubiquitin carboxy-terminal hydrolase-L1, tau, S100B, and glial acidic fibrillary protein. We conducted a focused literature review of unresolved issues in three areas: mode of entry into and exit from the blood, kinetics of blood biomarkers in the blood, and predictive capacity of the blood biomarkers after mTBI. FINDINGS: Although a disruption of the blood brain barrier has been demonstrated in mild and severe traumatic brain injury, biomarkers can enter the blood through pathways that do not require a breach in this barrier. A definitive accounting for the pathways that biomarkers follow from the brain to the blood after mTBI has not been performed. Although preliminary investigations of blood biomarkers kinetics after TBI are available, our current knowledge is incomplete and definitive studies are needed. Optimal sampling times for biomarkers after mTBI have not been established. Kinetic models of blood biomarkers can be informative, but more precise estimates of kinetic parameters are needed. Confounding factors for blood biomarker levels have been identified, but corrections for these factors are not routinely made. Little evidence has emerged to date to suggest that blood biomarker levels correlate with clinical measures of mTBI severity. The significance of elevated biomarker levels thirty or more days following mTBI is uncertain. Blood biomarkers have shown a modest but not definitive ability to distinguish concussed from non-concussed subjects, to detect sub-concussive hits to the head, and to predict recovery from mTBI. Blood biomarkers have performed best at distinguishing CT scan positive from CT scan negative subjects after mTBI.

A Kinetic Model for Blood Biomarker Levels After Mild Traumatic Brain Injury.

Traumatic brain injury (TBI) imposes a significant economic and social burden. The diagnosis and prognosis of mild TBI, also called concussion, is challenging. Concussions are common among contact sport athletes. After a blow to the head, it is often difficult to determine who has had a concussion, who should be withheld from play, if a concussed athlete is ready to return to the field, and which concussed athlete will develop a post-concussion syndrome. Biomarkers can be detected in the cerebrospinal fluid and blood after traumatic brain injury and their levels may have prognostic value. Despite significant investigation, questions remain as to the trajectories of blood biomarker levels over time after mild TBI. Modeling the kinetic behavior of these biomarkers could be informative. We propose a one-compartment kinetic model for S100B, UCH-L1, NF-L, GFAP, and tau biomarker levels after mild TBI based on accepted pharmacokinetic models for oral drug absorption. We approximated model parameters using previously published studies. Since parameter estimates were approximate, we did uncertainty and sensitivity analyses. Using estimated kinetic parameters for each biomarker, we applied the model to an available post-concussion biomarker dataset of UCH-L1, GFAP, tau, and NF-L biomarkers levels. We have demonstrated the feasibility of modeling blood biomarker levels after mild TBI with a one compartment kinetic model. More work is needed to better establish model parameters and to understand the implications of the model for diagnostic use of these blood biomarkers for mild TBI.

Evaluation of standard and semantically-augmented distance metrics for neurology patients.

BACKGROUND: Patient distances can be calculated based on signs and symptoms derived from an ontological hierarchy. There is controversy as to whether patient distance metrics that consider the semantic similarity between concepts can outperform standard patient distance metrics that are agnostic to concept similarity. The choice of distance metric can dominate the performance of classification or clustering algorithms. Our objective was to determine if semantically augmented distance metrics would outperform standard metrics on machine learning tasks. METHODS: We converted the neurological findings from 382 published neurology cases into sets of concepts with corresponding machine-readable codes. We calculated patient distances by four different metrics (cosine distance, a semantically augmented cosine distance, Jaccard distance, and a semantically augmented bipartite distance). Semantic augmentation for two of the metrics depended on concept similarities from a hierarchical neuro-ontology. For machine learning algorithms, we used the patient diagnosis as the ground truth label and patient findings as machine learning features. We assessed classification accuracy for four classifiers and cluster quality for two clustering algorithms for each of the distance metrics. RESULTS: Inter-patient distances were smaller when the distance metric was semantically augmented. Classification accuracy and cluster quality were not significantly different by distance metric. CONCLUSION: Although semantic augmentation reduced inter-patient distances, we did not find improved classification accuracy or improved cluster quality with semantically augmented patient distance metrics when applied to a dataset of neurology patients. Further work is needed to assess the utility of semantically augmented patient distances.

Corneal confocal microscopy is efficient, well-tolerated, and reproducible.

In order to develop an efficient, reproducible, and well-tolerated protocol for assessing corneal innervation, 11 normal subjects underwent corneal confocal microscopy (CCM) using a Heidelberg Retinal Tomography III microscope. Five standardized locations were sampled in the left eye and one centrally in the right. The protocol was repeated 1-4 weeks later. A blinded technician measured nerve fiber length (NFL) and tortuosity coefficient (TC). The relationship between image location and NFL and TC was assessed using one-way analysis of variance, and reproducibility determined using relative intertrial variability and intraclass correlation coefficients. NFL reproducibility was maximized by averaging four or more images from the left eye, or one central image from both eyes. TC was less reproducible. CCM is a rapid, well-tolerated, and reproducible method for assessing corneal innervation.

Adverse interactions between herbal and dietary substances and prescription medications: a clinical survey.

CONTEXT: Patients often combine prescription medications with herbal and dietary substances (herein referred to as herbal medicines). A variety of potential adverse herb-drug interactions exist based on the pharmacological properties of herbal and prescription medications. OBJECTIVE: To determine the incidence of potential and observed adverse herb-drug interactions in patients using herbal medicines with prescription medications. DESIGN: Consecutive patients were questioned about their use of herbal medicines in 6 outpatient clinics. Patients reporting use of these products provided a list of their prescription medications, which were reviewed for any potential adverse herb-drug interactions using a comprehensive natural medicine database. Any potential adverse herb-drug interactions prompted a review of the patient's chart for evidence of an observed adverse herb-drug interaction. MAIN OUTCOME MEASURE: The rate of potential and observed adverse herb-drug interactions. RESULTS: Eight hundred four patients were surveyed, and 122 (15%) used herbal medicines. Eighty-five potential adverse herb-drug interactions were found in 49 patients (40% of herbal medicine users). Twelve possible adverse herb-drug interactions in 8 patients (7% of herbal medicine users) were observed. In all 12 cases, the severity scores were rated as mild, including 8 cases of hypoglycemia in diabetics taking nopal (prickly pear cactus). CONCLUSIONS: A substantial number of potential adverse herb-drug interactions were detected and a small number of adverse herb-drug interactions observed, particularly in diabetics taking nopal. Screening for herbal medicine usage in 804 patients did not uncover any serious adverse interactions with prescription medications.