Background: Prognostication is very important to clinicians and families during the early management of severe traumatic brain injury (sTBI), however, there are no gold standard biomarkers to determine prognosis in sTBI. As has been demonstrated in several diseases, early measurement of serum metabolomic profiles can be used as sensitive and specific biomarkers to predict outcomes. Methods: We prospectively enrolled 59 adults with sTBI (Glasgow coma scale, GCS ≤ 8) in a multicenter Canadian TBI (CanTBI) study. Serum samples were drawn for metabolomic profiling on the 1st and 4th days following injury. The Glasgow outcome scale extended (GOSE) was collected at 3- and 12-months post-injury. Targeted direct infusion liquid chromatography-tandem mass spectrometry (DI/LC–MS/MS) and untargeted proton nuclear magnetic resonance spectroscopy (¹H-NMR) were used to profile serum metabolites. Multivariate analysis was used to determine the association between serum metabolomics and GOSE, dichotomized into favorable (GOSE 5–8) and unfavorable (GOSE 1–4), outcomes. Results: Serum metabolic profiles on days 1 and 4 post-injury were highly predictive (Q² > 0.4–0.5) and highly accurate (AUC > 0.99) to predict GOSE outcome at 3- and 12-months post-injury and mortality at 3 months. The metabolic profiles on day 4 were more predictive (Q² > 0.55) than those measured on day 1 post-injury. Unfavorable outcomes were associated with considerable metabolite changes from day 1 to day 4 compared to favorable outcomes. Increased lysophosphatidylcholines, acylcarnitines, energy-related metabolites (glucose, lactate), aromatic amino acids, and glutamate were associated with poor outcomes and mortality. Discussion: Metabolomic profiles were strongly associated with the prognosis of GOSE outcome at 3 and 12 months and mortality following sTBI in adults. The metabolic phenotypes on day 4 post-injury were more predictive and significant for predicting the sTBI outcome compared to the day 1 sample. This may reflect the larger contribution of secondary brain injury (day 4) to sTBI outcome. Patients with unfavorable outcomes demonstrated more metabolite changes from day 1 to day 4 post-injury. These findings highlighted increased concentration of neurobiomarkers such as N-acetylaspartate (NAA) and tyrosine, decreased concentrations of ketone bodies, and decreased urea cycle metabolites on day 4 presenting potential metabolites to predict the outcome. The current findings strongly support the use of serum metabolomics, that are shown to be better than clinical data, in determining prognosis in adults with sTBI in the early days post-injury. Our findings, however, require validation in a larger cohort of adults with sTBI to be used for clinical practice.

Background: Diagnosis and prognostication of severe traumatic brain injury (sTBI) continue to be problematic despite years of research efforts. There are currently no clinically reliable biomarkers, though advances in protein biomarkers are being made. Utilizing Omics technology, particularly metabolomics, may provide new diagnostic biomarkers for sTBI. Several published studies have attempted to determine the specific metabolites and metabolic pathways involved; these studies will be reviewed. Aims: This scoping review aims to summarize the current literature concerning metabolomics in sTBI, review the comprehensive data, and identify commonalities, if any, to define metabolites with potential clinical use. In addition, we will examine related metabolic pathways through pathway analysis. Methods: Scoping review methodology was used to examine the current literature published in Embase, Scopus, PubMed, and Medline. An initial 1090 publications were identified and vetted with specific inclusion criteria. Of these, 20 publications were selected for further examination and summary. Metabolic data was classified using the Human Metabolome Database (HMDB) and arranged to determine the ‘recurrent’ metabolites and classes found in sTBI. To help understand potential mechanisms of injury, pathway analysis was performed using these metabolites and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database. Results: Several metabolites related to sTBI and their effects on biological pathways were identified in this review. Across the literature, proline, citrulline, lactate, alanine, valine, leucine, and serine all decreased in adults post sTBI, whereas both octanoic and decanoic acid increased. Hydroxy acids and organooxygen compounds generally increased following sTBI, while most carboxylic acids decreased. Pathway analysis showed significantly affected glycine and serine metabolism, glycolysis, branched-chain amino acid (BCAA) metabolism, and other amino acid metabolisms. Interestingly, no tricarboxylic acid cycle metabolites were affected. Conclusion: Aside from a select few metabolites, classification of a metabolic profile proved difficult due to significant ambiguity between study design, sample size, type of sample, metabolomic detection techniques, and other confounding variables found in sTBI literature. Given the trends found in some studies, further metabolomics investigation of sTBI may be useful to identify clinically relevant metabolites.

Background: Fluctuating course of delirium and complexities of ICU care mean delirium symptoms are hard to identify or commonly confused with other disorders. Delirium is difficult to diagnose, and clinicians and researchers may combine assessments from multiple tools. We evaluated diagnostic accuracy of different combinations of delirium assessments performed in each enrolled patient.Methods: Data were obtained from a previously conducted cross-sectional study. Eligible adult patients who remained admitted to ICU for >24 hours with at least one family member present were consecutively enrolled as patient-family dyads. Clinical delirium assessments (Intensive Care Delirium Screening Checklist [ICSDC] and Confusion Assessment Method-ICU [CAM-ICU]) were completed twice daily by bedside nurse or trained research assistant, respectively. Family delirium assessments (Family Confusion Assessment Method and Sour Seven) were completed once daily by family members. We pooled all delirium assessment tools in a single two-class latent model and pairwise (i.e., combined, clinical or family assessments) Bayesian analyses.Results: Seventy-three patient-family dyads were included. Among clinical delirium assessments, the ICDSC had lower sensitivity (0.72; 95% Bayesian Credible [BC] interval 0.54–0.92) and higher specificity (0.90; 95%BC, 0.82–0.97) using Bayesian analyses compared to pooled latent class analysis and CAM-ICU had higher sensitivity (0.90; 95%BC, 0.70–1.00) and higher specificity (0.94; 95%BC, 0.80–1.00). Among family delirium assessments, the Family Confusion Assessment Method had higher sensitivity (0.83; 95%BC, 0.71–0.92) and higher specificity (0.93; 95%BC, 0.84–0.98) using Bayesian analyses compared to pooled latent class analysis and the Sour Seven had higher specificity (0.85; 95%BC, 0.67–0.99) but lower sensitivity (0.64; 95%BC 0.47–0.82).Conclusions: Results from delirium assessment tools are often combined owing to imperfect reference standards for delirium measurement. Pairwise Bayesian analyses that explicitly accounted for each tool’s (performed within same patient) prior sensitivity and specificity indicate that two combined clinical or two combined family delirium assessment tools have fair diagnostic accuracy.

Objective: The aim of the study was to test the hypothesis that the development of luteal phase dominant follicles (LPDFs) as women age is associated with abnormal luteal function. Methods: Luteal and antral follicle diameter were quantified in ovulatory women of midreproductive age (MRA; 18-35 y; n = 9) and advanced reproductive age (ARA; 45-55 y; n = 16) every 1 to 3 days during one complete interovulatory interval. Blood was drawn at each visit and assayed for progesterone, estradiol, inhibin A, follicle-stimulating hormone, and luteinizing hormone. Luteal diameter and hormone profiles were compared within MRA and ARA women with versus without LPDFs. Results: Luteal growth and regression profiles were similar in MRA women with typical versus no LPDFs (13.9, 14.8 mm; P > 0.1); however, luteal phase estradiol and progesterone were greater in MRA women with typical (91.1 ng/L, 8.81 μg/L) versus no (48.8 ng/L, 7.32 μg/L) LPDFs, respectively (LPDF effect, P < 0.1). In the ARA group, mean luteal diameter was lowest in women with atypical LPDFs (12.3 mm), greatest in those with typical LPDFs (16.0 mm), and moderate in those with no LPDFs (13.6 mm), (P < 0.1). Reduced luteal growth in ARA women with atypical versus typical and/or no LPDFs occurred simultaneously to greater luteal phase estradiol (199 vs 69.0, 78.4 ng/L) lower progesterone (7.38 vs 10.7, 13.8 ug/L), and lower inhibin A (36.3, 35.6, 51.2) (P < 0.1). Conclusions: The development of LPDFs as women age was associated with reduced luteal growth, greater estradiol, lower progesterone, and lower inhibin A. These findings provide preliminary evidence that variations in antral folliculogenesis contribute to luteal insufficiency during the menopausal transition.

Background: In 2019, SARS-CoV-2, the novel coronavirus, entered the world scene, presenting a global health crisis with a broad spectrum of clinical manifestations. Recognizing the significance of metabolomics as the omics closest to symptomatology, it has become a useful tool for predicting clinical outcomes. Several metabolomic studies have indicated variations in the metabolome corresponding to different disease severities, highlighting the potential of metabolomics to unravel crucial insights into the pathophysiology of SARS-CoV-2 infection. Methods: The PRISMA guidelines were followed for this scoping review. Three major scientific databases were searched: PubMed, the Directory of Open Access Journals (DOAJ), and BioMed Central, from 2020 to 2024. Initially, 2938 articles were identified and vetted with specific inclusion and exclusion criteria. Of these, 42 articles were retrieved for analysis and summary. Results: Metabolites were identified that were repeatedly noted to change with COVID-19 and its severity. Phenylalanine, glucose, and glutamic acid increased with severity, while tryptophan, proline, and glutamine decreased, highlighting their association with COVID-19 severity. Additionally, pathway analysis revealed that phenylalanine, tyrosine and tryptophan biosynthesis, and arginine biosynthesis were the most significantly impacted pathways in COVID-19 severity. Conclusions: COVID-19 severity is intricately linked to significant metabolic alterations that span amino acid metabolism, energy production, immune response modulation, and redox balance.

OBJECTIVES (BACKGROUND): Delirium remains frequently undetected by healthcare providers; partnering with family may be a novel way to identify and manage delirium. This study explores the feasibility of a family-administered intervention for delirium prevention, detection, and management. DESIGN: Pilot randomized controlled trial. SETTING: Two Canadian ICUs. SUBJECTS: Patient-family pairs (dyads) were included. Eligible patients had no primary brain injury, a Richmond Agitation-Sedation Scale score of greater than or equal to –3, and were expected to remain in the ICU for at least 24 hours to complete all study assessments. INTERVENTIONS: Dyads were randomly assigned to either standard care (control) or the intervention, which included delirium education and family-administered checklists with prevention/management strategies and a detection tool (“Sour Seven”). MEASUREMENTS AND MAIN RESULTS: Outcomes included feasibility indicators, enrollment and completion rates, and psychological outcomes (Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, and the Kessler Psychologic Distress (K-10) scales in the ICU and at 1- and 3-month follow-ups. Between January 2020 and June 2023, during the height of the COVID pandemic, 197 patient–family pairs were approached, with 64 (32%) consenting to participate; participation required both the patient and a family member. Despite recruitment challenges, 75% of families completed in-ICU questionnaires, and 38% completed all follow-ups. The family members in the intervention group demonstrated increased delirium knowledge compared with baseline delirium knowledge, and engagement in prevention strategies, with 8 of 19 (42%) family members identifying delirium using the Sour Seven. At the 3-month follow-up, seven family members showed significant anxiety, and five showed significant depression. Observations of ICU rounds revealed limited delirium discussions. CONCLUSIONS: This pilot study demonstrated the feasibility of family-administered delirium care in ICU settings. However, the likely impact of the COVID-19 pandemic cannot be overlooked. The study faced recruitment challenges and demonstrated the difficulties of family involvement in delirium care, particularly during restricted family presence. A full evaluation of effectiveness requires a hypothesis-testing trial with procedural adjustments to streamline data collection and strengthen family-care team partnerships. TRIAL REGISTRATION: Clinicaltrials.gov (NCT04099472).