Utility of serum chemokine-like factor 1 as a biomarker of severity and prognosis after severe traumatic brain injury: A prospective observational study.

BACKGROUND: Chemokine-like factor 1 (CKLF1) may be involved in the inflammatory response and secondary brain injury after severe traumatic brain injury (sTBI). We determined serum CKLF1 levels of sTBI patients to further investigate the correlation of CKLF1 levels with disease severity, functional prognosis, and 180-day mortality of sTBI. METHODS: Serum CKLF1 levels were measured at admission in 119 sTBI patients and at entry into study in 119 healthy controls. Serum CKLF levels of 50 patients were also quantified at days 1-3, 5, and 7 after admission. Glasgow coma scale (GCS) scores and Rotterdam computerized tomography (CT) classification were utilized to assess disease severity. Extended Glasgow outcome scale (GOSE) scores were recorded to evaluate function prognosis at 180 days after sTBI. Relations of serum CKLF1 levels to 180-day poor prognosis (GOSE scores of 1-4) and 180-day mortality were analyzed using univariate analysis, followed by multivariate analysis. Receiver-operating characteristic (ROC) curve was built to investigate prognostic predictive capability. RESULTS: Serum CKLF1 levels of sTBI patients increased at admission, peaked at day 2, and then gradually decreased; they were significantly higher during the 7 days after sTBI than in healthy controls. Differences of areas under ROC curve (areas under the curve [AUCs]) were not significant among the six time points. Multivariate analysis showed that serum CKLF1 levels were independently correlated with GCS scores, Rotterdam CT classification, and GOSE scores. Serum CKLF1 levels were significantly higher in non-survivors than in survivors and in poor prognosis patients than in good prognosis patients. Serum CKLF1 levels independently predicted 180-day poor prognosis and 180-day mortality, and had high 180-day prognosis and mortality predictive abilities, and their AUCs were similar to those of GCS scores and Rotterdam CT classification. Combination model containing serum CKLF1, GCS scores, and Rotterdam CT classification performed more efficiently than any of them alone in predicting mortality and poor prognosis. The models were visually described using nomograms, which were comparatively stable under calibration curve and were relatively of clinical benefit under decision curve. CONCLUSION: Serum CKLF1 levels are significantly associated with disease severity, poor 180-day prognosis, and 180-day mortality in sTBI patients. Hence, complement CKLF1 may serve as a potential prognostic biomarker of sTBI.

Predicting outcome after aneurysmal subarachnoid hemorrhage by exploitation of signal complexity: a prospective two-center cohort study.

BACKGROUND: Signal complexity (i.e. entropy) describes the level of order within a system. Low physiological signal complexity predicts unfavorable outcome in a variety of diseases and is assumed to reflect increased rigidity of the cardio/cerebrovascular system leading to (or reflecting) autoregulation failure. Aneurysmal subarachnoid hemorrhage (aSAH) is followed by a cascade of complex systemic and cerebral sequelae. In aSAH, the value of entropy has not been established yet. METHODS: aSAH patients from 2 prospective cohorts (Zurich-derivation cohort, Aachen-validation cohort) were included. Multiscale Entropy (MSE) was estimated for arterial blood pressure, intracranial pressure, heart rate, and their derivatives, and compared to dichotomized (1-4 vs. 5-8) or ordinal outcome (GOSE-extended Glasgow Outcome Scale) at 12 months using uni- and multivariable (adjusted for age, World Federation of Neurological Surgeons grade, modified Fisher (mFisher) grade, delayed cerebral infarction), and ordinal methods (proportional odds logistic regression/sliding dichotomy). The multivariable logistic regression models were validated internally using bootstrapping and externally by assessing the calibration and discrimination. RESULTS: A total of 330 (derivation: 241, validation: 89) aSAH patients were analyzed. Decreasing MSE was associated with a higher likelihood of unfavorable outcome independent of covariates and analysis method. The multivariable adjusted logistic regression models were well calibrated and only showed a slight decrease in discrimination when assessed in the validation cohort. The ordinal analysis revealed its effect to be linear. MSE remained valid when adjusting the outcome definition against the initial severity. CONCLUSIONS: MSE metrics and thereby complexity of physiological signals are independent, internally and externally valid predictors of 12-month outcome. Incorporating high-frequency physiological data as part of clinical outcome prediction may enable precise, individualized outcome prediction. The results of this study warrant further investigation into the cause of the resulting complexity as well as its association to important and potentially preventable complications including vasospasm and delayed cerebral ischemia.

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.

Psychometric properties and factor structure of the traditional Chinese version of the Community Integration Questionnaire-Revised in traumatic brain injury survivors.

This study aimed to translate and validate the traditional Chinese version of the Community Integration Questionnaire-Revised (TC-CIQ-R) in patients with traumatic brain injury (TBI). We included participants aged ≥20 years and diagnosed as having TBI for ≥6 months from neurosurgical clinics. The 18-item TC-CIQ-R, Participation Measure - 3 Domains, 4 Dimensions (PM-3D4D), Extended Glasgow Outcome Scale (GOSE), and Taiwanese Quality of Life After Brain Injury (TQOLIBRI) were completed. The sample included 180 TBI survivors (54% male, mean age 47 years) of whom 87% sustained a mild TBI. Exploratory factor analysis extracted four factors - home integration, social integration, productivity, and electronic social networking - which explained 63.03% of the variation, after discarding the tenth item with a factor loading of 0.25. For criterion-related validity, the TC-CIQ-R was significantly correlated with the PM-3D4D; convergent validity was exhibited by demonstrating the associations between the TC-CIQ-R and TQOLIBRI. Known-group validity testing revealed significant differences in the subdomain and total scores of the TC-CIQ-R between participants with a mean GOSE score of ≤6 and >7 (all P  < 0.001). The TC-CIQ-R exhibited acceptable Cronbach's α values (0.68-0.88). We suggest the 17-item TC-CIQ-R as a valid tool for rehabilitation professionals, useful for both clinical practice and research in assessing community integration levels following TBI.

Long-term pituitary function and functional and patient-reported outcomes in severe acquired brain injury.

OBJECTIVE: Assessment of posttraumatic hypothalamic-pituitary dysfunctions is expected to be the most relevant assessment to offer patients with severe intracranial affection. In this study, we aim to investigate the prevalence of hypopituitarism in patients with severe acquired traumatic brain injury (TBI) compared with nontraumatic brain injury (NTBI) and to relate pituitary insufficiency to functional and patient-reported outcomes. DESIGN: This is a prospective study. METHODS: We included patients admitted for inpatient neurorehabilitation after severe TBI (N = 42) and NTBI (N = 18). The patients underwent a pituitary function assessment at a mean of 2.4 years after the injury. Functional outcome was assessed by using Functional Independence Measure and Glasgow Outcome Scale-Extended (both 1 year after discharge from neurorehabilitation) and patient-reported outcome was assessed by using Multiple Fatigue Inventory-20 and EQ-5D-3L. RESULTS: Hypopituitarism was reported in 10/42 (24%) patients with TBI and 7/18 (39%) patients with NTBI (P = .23). Insufficiencies affected 1 axis in 14/17 (82%) patients (13 hypogonadotropic hypogonadism and 1 growth hormone [GH] deficiency) and 2 axes in 3/17 (18%) patients (1 hypogonadotropic hypogonadism and GH deficiency, and 2 hypogonadotropic hypogonadism and arginin vasopressin deficiency). None had central hypoadrenalism or central hypothyroidism. In patients with both TBI and NTBI, pituitary status was unrelated to functioning and ability scores at 1 year and to patient-reported outcome scores at a mean of 2.4 years after the injury. CONCLUSION: Patients with severe acquired brain injury may develop long-term hypothalamus-pituitary insufficiency, with an equal occurrence in patients with TBI and NTBI. In both types of patients, mainly isolated deficiencies, most commonly affecting the gonadal axis, were seen. Insufficiencies were unrelated to functional outcomes and patient-reported outcomes, probably reflecting the complexity and heterogeneous manifestations in both patient groups.

A systematic review and meta-analysis on abnormal posturing among brain injury patients.

BACKGROUND: Abnormal motor posturing (AMP), exhibiting as decorticate, decerebrate, or opisthotonos, is regularly noticed among children and adults. OBJECTIVE: This systematic review and meta-analysis examined the risk factors and outcome of posturing among severe head and brain injury subjects. METHODS: Based on the inclusion and exclusion criteria and using MeSH terms: "decerebrate posturing", "opisthotonic posturing", "brain injury", and/or "cerebral injury" articles were searched on Scopus, PubMed, Science Direct, and google scholar databases. Observational studies, case series, and case reports were included. RESULTS: A total of 1953 studies were retrieved initially, and based on the selection criteria, 20 studies were finally selected for review and were analyzed for meta-analysis based on the mortality between the hematomas. The functional outcomes of this study are the risk factors, mortality rate and Glasgow Outcome Scale. Decerebrative patients were higher among the studies related to head injury surgeries. Males were mainly treated for decerebrate postures compared with the female subjects. Extradural hematoma and acute subdural hematoma with cerebral contusion were quite common in the surgical mass lesions. CONCLUSION: The findings reported that the lesion types, the operative procedures, and the age of the decerebrating patients with brain injuries are the significant prognostic factors determining the survival outcomes.

ANTECEDENTES: Postura motora anormal (AMP), exibindo-se como decorticada, descerebrada ou opistótono, é regularmente observada entre crianças e adultos. OBJETIVO: Esta revisão sistemática e metanálise examinou os fatores de risco e os resultados da postura entre indivíduos com lesões graves na cabeça e no cérebro. MéTODOS: Com base nos critérios de inclusão e exclusão e usando termos MeSH: artigos sobre "postura descerebrada", "postura opistótona", "lesão cerebral" e/ou "lesão cerebral" foram pesquisados nas bases de dados Scopus, PubMed, Science Direct e Google Scholar. Foram incluídos estudos observacionais, séries de casos e relatos de casos. RESULTADOS: Um total de 1.953 estudos foram recuperados inicialmente e, com base nos critérios de seleção, 20 estudos foram finalmente selecionados para revisão e analisados para metanálise com base na mortalidade entre os hematomas. Os resultados funcionais deste estudo são os fatores de risco, taxa de mortalidade e Escala de Resultados de Glasgow. Os pacientes descerebrados foram maiores entre os estudos relacionados a cirurgias de traumatismo cranioencefálico. Os homens foram tratados principalmente para posturas descerebradas em comparação com as mulheres. Hematoma extradural e hematoma subdural agudo com contusão cerebral foram bastante comuns nas lesões de massa cirúrgica. CONCLUSãO: Os achados relataram que os tipos de lesões, os procedimentos operatórios e a idade dos pacientes descerebrados com lesões cerebrais são os fatores prognósticos significativos que determinam os resultados de sobrevivência.

Predicting the Severity and Discharge Prognosis of Traumatic Brain Injury Based on Intracranial Pressure Data Using Machine Learning Algorithms.

OBJECTIVE: This study aimed to explore the potential of employing machine learning algorithms based on intracranial pressure (ICP), ICP-derived parameters, and their complexity to predict the severity and short-term prognosis of traumatic brain injury (TBI). METHODS: A single-center prospectively collected cohort of neurosurgical intensive care unit admissions was analyzed. We extracted ICP-related data within the first 6 hours and processed them using complex algorithms. To indicate TBI severity and short-term prognosis, Glasgow Coma Scale score on the first postoperative day and Glasgow Outcome Scale-Extended score at discharge were used as binary outcome variables. A univariate logistic regression model was developed to predict TBI severity using only mean ICP values. Subsequently, 3 multivariate Random Forest (RF) models were constructed using different combinations of mean and complexity metrics of ICP-related data. To avoid overfitting, five-fold cross-validations were performed. Finally, the best-performing multivariate RF model was used to predict patients' discharge Glasgow Outcome Scale-Extended score. RESULTS: The logistic regression model exhibited limited predictive ability with an area under the curve (AUC) of 0.558. Among multivariate models, the RF model, combining the mean and complexity metrics of ICP-related data, achieved the most robust ability with an AUC of 0.815. Finally, in terms of predicting discharge Glasgow Outcome Scale-Extended score, this model had a consistent performance with an AUC of 0.822. Cross-validation analysis confirmed the performance. CONCLUSIONS: This study demonstrates the clinical utility of the RF model, which integrates the mean and complexity metrics of ICP data, in accurately predicting the TBI severity and short-term prognosis.

Prediction for the prognosis of diffuse axonal injury using automated pupillometry.

OBJECTIVE: Previous studies have reported various predictive indicators of diffuse axonal injury (DAI), but no consensus has not been reached. Although the efficiency of automated pupillometry in patients with consciousness disorder has been widely reported, there are few reports of its use in patients with DAI. This study aimed to investigate the significance of pupillary findings in predicting the prognosis of DAI. PATIENTS AND METHODS: We included patients admitted to our center with a diagnosis of DAI from June 1, 2021 to June 30, 2022. Pupillary findings in both eyes were quantitatively measured by automated pupillometry every 2 hours after admission. We statistically examined the correlations between automated pupillometry parameters, the patients' characteristics, and outcomes such as the Glasgow Outcome Scale Extended (GOSE) after 6 months from injury, the time to follow command, and so on. RESULTS: Among 22 patients included in this study, five had oculomotor nerve palsy. Oculomotor nerve palsy was correlated with all outcomes, whereas Marshall computed tomography (CT) classification, Injury severity score (ISS) and DAI grade were correlated with few outcomes. Some of the automated pupillometry parameters were significantly correlated with GOSE at 6 months after injury, and many during the first 24 hours of measurement were correlated with the time to follow command. Most of these results were not affected by adjustment using sedation period, ISS or Marshall CT classification. A subgroup analysis of patients without oculomotor nerve palsy revealed that many of the automated pupillometry parameters during the first 24 hours of measurement were significantly correlated with most of the outcomes. The cutoff values that differentiated a good prognosis (GOSE 5-8) from a poor prognosis (GOSE 1-4) were constriction velocity (CV) 1.43 (AUC = 0.81(0.62-1), p = 0.037) and maximum constriction velocity (MCV) 2.345 (AUC = 0.78 (0.58-0.98), p = 0.04). The cutoff values that differentiated the time to follow command into within 7 days and over 8 days were percentage of constriction 8 (AUC = 0.89 (0.68-1), p = 0.011), CV 0.63 (AUC = 0.92 (0.78-1), p = 0.013), MCV 0.855 (AUC = 0.9 (0.74-1), p = 0.017) and average dilation velocity 0.175 (AUC = 0.95 (0.86-1), p = 0.018). CONCLUSIONS: The present results indicate that pupillary findings in DAI are a strong predictive indicator of the prognosis, and that quantitative measurement of them using automated pupillometry could facilitate enhanced prediction for the prognosis of DAI.

Effect of Peri-operative Blood Transfusion on Neurological Outcome Following Aneurysmal Subarachnoid Hemorrhage: A Prospective Observational Study.

BACKGROUND: Anemia is a common complication of aneurysmal subarachnoid hemorrhage and is associated with unfavorable outcomes. Whether the physiological benefits of transfusion for anemia surpass the risk of blood transfusion remains to be determined. OBJECTIVES: The primary outcome was to evaluate the impact of peri-operative blood transfusion on the long-term neurological outcome, assessed by Glasgow Outcome Scale Extended at 3 months. The secondary outcomes included the impact of transfusion on the short-term neurological outcome, assessed by Modified Rankin Score at discharge/7 days, and on the incidence of vasospasm, infarction, re-exploration, tracheostomy, and length of hospital stay. MATERIAL AND METHODS: This prospective observational study was conducted on 185 patients with aneurysmal subarachnoid hemorrhage undergoing clipping of the aneurysmal neck. In our study, blood transfusion was administered to keep the target Hb around 10 g/dL. RESULTS: Unfavorable long-term outcome was found in 27/97 (28%) of patients who received a blood transfusion as compared to 13/74 (18%) of patients who did not receive a transfusion (P = 0.116). Patients receiving transfusion had more chances of an unfavorable outcome at discharge/7 days as compared to those not transfused [44/103 (43%) versus 22/80 (27%)], P = 0.025. There were increased chances of vasospasm, infarction, re-exploration, tracheostomy, and increased length of hospital stay in patients receiving transfusion (P < 0.05). CONCLUSIONS: The use of blood transfusion in patients with aneurysmal subarachnoid hemorrhage was associated with increased neurological complications and hence an unfavorable short-term outcome. However, when used judiciously as per the clinical requirements, blood transfusion did not have a significant effect on long-term neurological outcome.

Surrogate Perception of Disability after Hospitalization for Traumatic Brain Injury.

BACKGROUND: The Glasgow Outcome Scale Extended (GOSE) is a measure of recovery after traumatic brain injury (TBI). Public surveys rate some GOSE states as worse than death. Direct family experience caring for patients with TBI may impact views of post-TBI disability. STUDY DESIGN: We conducted a national cross-sectional computer-adaptive survey of surrogates of TBI dependents incurring injury more than 1 year earlier. Using a standard gamble approach in randomized order, surrogates evaluated preferences for post-TBI GOSE states from GOSE 2 (bedridden, unaware) to GOSE 8 (good recovery). We calculated median (interquartile range [IQR]) health utilities for each post-TBI state, ranging from -1 to 1, with 0 as reference (death = GOSE 1), and assessed sociodemographic associations using proportional odds logistic regression modeling. RESULTS: Of 515 eligible surrogates, 298 (58%) completed scenarios. Surrogates were median aged 46 (IQR 35 to 60), 54% married, with Santa Clara strength of faith 14 (10 to 18). TBI dependents had a median GOSE5 (3 to 7). Median (IQR) health utility ratings for GOSE 2, GOSE 3, and GOSE 4 were -0.06 (-0.50 to -0.01), -0.01 (-0.30 to 0.45), and 0.30 (-0.01 to 0.80), rated worse than death by 91%, 65%, and 40%, respectively. Surrogates rated GOSE 4 (daily partial help) worse than the general population. Married surrogates rated GOSE 4 higher (p < 0.01). Higher strength of faith was associated with higher utility scores across GOSE states (p = 0.034). CONCLUSIONS: In this index study of surrogate perceptions about disability after TBI, poor neurologic outcomes-vegetative, needing all-day or partial daily assistance-were perceived as worse than death by at least 1 in 3 surrogates. Surrogate perceptions differed from the unexposed public. Long-term perceptions about post-TBI disability may inform earlier, tailored shared decision-making after neurotrauma.

Machine learning models for predicting in-hospital outcomes after non-surgical treatment among patients with moderate-to-severe traumatic brain injury.

AIM: This study aims to develop prediction models for in-hospital outcomes after non-surgical treatment among patients with moderate-to-severe traumatic brain injury (TBI). METHOD: We conducted a retrospective review of patients hospitalized for moderate-to-severe TBI in our department from 2011 to 2020. Five machine learning (ML) algorithms and the conventional logistic regression (LR) model were employed to predict in-hospital mortality and the Glasgow Outcome Scale (GOS) functional outcomes. These models utilized clinical and routine blood data collected upon admission. RESULTS: This study included a total of 196 patients who received only non-surgical treatment after moderate-to-severe TBI. When predicting mortality, ML models achieved area under the curve (AUC) values of 0.921 to 0.994 using clinical and routine blood data, and 0.877 to 0.982 using only clinical data. In comparison, LR models yielded AUCs of 0.762 and 0.730 respectively. When predicting the GOS outcome, ML models achieved AUCs of 0.870 to 0.915 using clinical and routine blood data, and 0.858 to 0.927 using only clinical data. In comparison, the LR model yielded AUCs of 0.798 and 0.787 respectively. Repeated internal validation showed that the contributions of routine blood data for prediction models may depend on different prediction algorithms and different outcome measurements. CONCLUSION: The study reported ML-based prediction models that provided rapid and accurate predictions on short-term outcomes after non-surgical treatment among patients with moderate-to-severe TBI. The study also highlighted the superiority of ML models over conventional LR models and proposed the complex contributions of routine blood data in such predictions.

Efficacy and Safety of Extracranial-Intracranial Bypass Surgery for Posterior Circulation Aneurysms: A Systematic Review and Single-Arm Meta-Analysis.

OBJECTIVE: Treating complex posterior circulation aneurysms poses challenges, and extracranial to intracranial (EC-IC) bypass techniques are potential therapeutic options. However, the safety and efficacy of this approach for posterior circulation aneurysms remain unclear. The study's objective was to assess the safety and efficacy of EC-IC bypass in these aneurysms. METHODS: Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, we conducted a systematic review on EC-IC revascularization for posterior circulation aneurysms. Included studies had at least 4 patients and reported data on mortality, patency, complications, or clinical outcomes. Favorable clinical outcomes were defined as modified Rankin Scale below 3 or Glasgow Outcome Scale above 3, and complications were any issues related to the bypass procedure. RESULTS: From 3036 articles reviewed, 22 studies involving 196 patients who underwent 210 EC-IC bypass procedures for posterior circulation aneurysms were selected. The median follow-up period of 14 studies was 31.66 months (6-61 months). Final follow-up indicated a high bypass patency rate of 96% [95% confidence interval [CI]: 91%-100%; I2 = 12%], with a mortality rate of 5% [95% CI: 1%-9%; I2 = 0%]. Additionally, 83% [95% CI: 70%-96%; I2 = 77%] of patients showed good outcomes at the last follow-up. Complications were observed in 40% [95% CI: 26%-55%; I2 = 80%]. Heterogeneity was associated with specific studies. CONCLUSIONS: EC-IC bypass procedures are a viable treatment option for posterior circulation aneurysms, with high bypass patency rates and favorable clinical outcomes. However, complications, especially neurological deficits, exist. Open revascularization remains essential for neurovascular surgeons dealing with complex aneurysms.

Temporal Profiles of P-Tau, T-Tau, and P-Tau:Tau Ratios in Cerebrospinal Fluid and Blood from Moderate-Severe Traumatic Brain Injury Patients and Relationship to 6-12 Month Global Outcomes.

Traumatic brain injury (TBI) can initiate progressive injury responses, which are linked to increased risk of neurodegenerative diseases known as "tauopathies." Increased post-TBI tau hyperphosphorylation has been reported in brain tissue and biofluids. Acute-to-chronic TBI total (T)-tau and phosphorylated (P)-tau temporal profiles in the cerebrospinal fluid (CSF) and serum and their relationship to global outcome is unknown. Our multi-site longitudinal study examines these concurrent profiles acutely (CSF and serum) and also characterizes the acute- to-chronic serum patterns. Serial serum and CSF samples from individuals with moderate-to-severe TBI were obtained from two cohorts (acute, subacute, and chronic samples from University of Pittsburgh [UPitt] [n = 286 unique subjects] and acute samples from Baylor College of Medicine [BCM] [n = 114 unique subjects]) and assayed for T-tau and P-tau using the Rolling Circle Amplification-Surround Optical Fiber ImmunoAssay platform. Biokinetic analyses described serum T-tau and P-tau temporal patterns. T-tau and P-tau levels are compared with those in healthy controls (n = 89 for both CSF and serum), and univariate/multivariable associations are made with global outcome, including the Disability Rating Scale (DRS) and the Glasgow Outcome Scale-Extended (GOS-E) scores at 3 and 6 months post-TBI (BCM cohort) and at 6 and 12 months post-TBI (UPitt cohort). For both the UPitt and BCM cohorts, temporal increases in median serum and CSF T-tau and P-tau levels occurred over the first 5 days post-injury, while the initial increases of P-tau:T-tau ratio plateaued by day 4 post-injury (UPitt: n = 99, BCM: n = 48). Biokinetic analyses with UPitt data showed novel findings that T-tau (n = 74) and P-tau (n = 87) reached delayed maximum levels at 4.5 and 5.1 days, while exhibiting long serum half-lives (152 and 123 days), respectively. The post-TBI rise in acute (days 2-6) serum P-tau (up to 276-fold) far outpaced that of T-tau (7.3-fold), leading to a P-tau:T-tau increase of up to 267-fold, suggesting a shift toward tau hyperphosphorylation. BCM analyses showed that days 0-6 mean CSF T-tau and P-tau levels and P-tau:T-tau ratios were associated with greater disability (DRS) (n = 48) and worse global outcome (GOS-E) (n = 48) 6 months post-injury. Days 0-6 mean serum T-tau, P-tau, and P-tau:T-tau ratio were not associated with outcome in either cohort (UPitt: n = 145 [DRS], n = 154 [GOS-E], BCM: n = 99 [DRS and GOS-E]). UPitt multivariate models showed that higher chronic (months 1-6) mean P-tau levels and P-tau:T-tau ratio, but not T-tau levels, are associated with greater disability (DRS: n = 119) and worse global outcomes (GOS-E: n = 117) 12 months post-injury. This work shows the potential importance of monitoring post-TBI T-tau and P-tau levels over time. This multi-site longitudinal study features concurrent acute TBI T-tau and P-tau profiles in CSF and serum, and also characterizes acute-to-chronic serum profiles. Longitudinal profiles, along with no temporal concordance between trajectory groups over time, imply a sustained post-TBI shift in tau phosphorylation dynamics that may favor tauopathy development chronically.

Late Blood Levels of Neurofilament Light Correlate With Outcome in Patients With Traumatic Brain Injury.

Neurofilament light (NF-L) is an axonal protein that has shown promise as a traumatic brain injury (TBI) biomarker. Serum NF-L shows a rather slow rise after injury, peaking after 1-2 weeks, although some studies suggest that it may remain elevated for months after TBI. The aim of this study was to examine if plasma NF-L levels several months after the injury correlate with functional outcome in patients who have sustained TBIs of variable initial severity. In this prospective study of 178 patients with TBI and 40 orthopedic injury controls, we measured plasma NF-L levels in blood samples taken at the follow-up appointment on average 9 months after injury. Patients with TBI were divided into two groups (mild [mTBI] vs. moderate-to-severe [mo/sTBI]) according to the severity of injury assessed with the Glasgow Coma Scale upon admission. Recovery and functional outcome were assessed using the Extended Glasgow Outcome Scale (GOSE). Higher levels of NF-L at the follow-up correlated with worse outcome in patients with moderate-to-severe TBI (Spearman's rho = -0.18; p < 0.001). In addition, in computed tomography-positive mTBI group, the levels of NF-L were significantly lower in patients with GOSE 7-8 (median 18.14; interquartile range [IQR] 9.82, 32.15) when compared with patients with GOSE <7 (median 73.87; IQR 32.17, 110.54; p = 0.002). In patients with mTBI, late NF-L levels do not seem to provide clinical benefit for late-stage assessment, but in patients with initially mo/sTBI, persistently elevated NF-L levels are associated with worse outcome after TBI and may reflect ongoing brain injury.

Lysophospholipids Are Associated With Outcomes in Hospitalized Patients With Mild Traumatic Brain Injury.

Mild traumatic brain injury (mTBI) accounts for 70-90% of all TBI cases. Lipid metabolites have important roles in plasma membrane biogenesis, function, and cell signaling. As TBI can compromise plasma membrane integrity and alter brain cell function, we sought to identify circulating phospholipid alterations after mTBI, and determine if these changes were associated with clinical outcomes. Patients with mTBI (Glasgow Coma Score [GCS] ≥13 and loss of consciousness <30 min) were recruited. A total of 84 mTBI subjects were enrolled after admission to a level I trauma center, with the majority having evidence of traumatic intracranial hemorrhage on brain computed tomography (CT). Plasma samples were collected within 24 h of injury with 32 mTBI subjects returning at 3 months after injury for a second plasma sample to be collected. Thirty-five healthy volunteers were enrolled as controls and had a one-time blood draw. Lipid metabolomics was performed on plasma samples from each subject. Fold change of selected lipid metabolites was determined. Multivariable regression models were created to test associations between lipid metabolites and discharge and 6-month Glasgow Outcomes Scale-Extended (GOSE) outcomes (dichotomized between "good" [GOSE ≥7] and "bad" [GOSE ≤6] functional outcomes). Plasma levels of 31 lipid metabolites were significantly associated with discharge GOSE using univariate models; three of these metabolites were significantly increased, while 14 were significantly decreased in subjects with good outcomes compared with subjects with poor outcomes. In multivariable logistic regression models, higher circulating levels of the lysophospholipids (LPL) 1-linoleoyl-glycerophosphocholine (GPC) (18:2), 1-linoleoyl-GPE (18:2), and 1-linolenoyl-GPC (18:3) were associated with both good discharge GOSE (odds ratio [OR] 12.2 [95% CI 3.35, 58.3], p = 5.23 × 10-4; OR 9.43 [95% CI 2.87, 39.6], p = 7.26 × 10-4; and OR 5.26 [95% CI 1.99, 16.7], p = 2.04 × 10-3, respectively) and 6-month (OR 4.67 [95% CI 1.49, 17.7], p = 0.013; OR 2.93 [95% CI 1.11, 8.87], p = 0.039; and OR 2.57 [95% CI 1.08, 7.11], p = 0.046, respectively). Compared with healthy volunteers, circulating levels of these three LPLs were decreased early after injury and had normalized by 3 months after injury. Logistic regression models to predict functional outcomes were created by adding each of the described three LPLs to a baseline model that included age and sex. Including 1-linoleoyl-GPC (18:2) (8.20% improvement, p = 0.009), 1-linoleoyl-GPE (18:2) (8.85% improvement, p = 0.021), or 1-linolenoyl-GPC (18:3) (7.68% improvement, p = 0.012), significantly improved the area under the curve (AUC) for predicting discharge outcomes compared with the baseline model. Models including 1-linoleoyl-GPC (18:2) significantly improved AUC for predicting 6-month outcomes (9.35% improvement, p = 0.034). Models including principal components derived from 25 LPLs significantly improved AUC for prediction of 6-month outcomes (16.0% improvement, p = 0.020). Our results demonstrate that higher plasma levels of LPLs (1-linoleoyl-GPC, 1-linoleoyl-GPE, and 1-linolenoyl-GPC) after mTBI are associated with better functional outcomes at discharge and 6 months after injury. This class of phospholipids may represent a potential therapeutic target.

The Association Between Gender and Clinical Outcomes in Patients With Moderate to Severe Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

INTRODUCTION: Traumatic brain injuries (TBIs) are a significant cause of morbidity and mortality in the United States. but have a disproportionate impact on patients based on gender. This systematic review and meta-analysis aim to compare gender differences in clinical outcomes between male and female adult trauma patients with moderate and severe TBI. METHODS: Studies assessing gender differences in outcomes following TBIs on PubMed, Google Scholar, EMBASE, and ProQuest were searched. Meta-analysis was performed for outcomes including in-hospital mortality, hospital length of stay, intensive care unit length of stay, and Glasgow outcome scale (GOS) at 6 mo. RESULTS: Eight studies were included for analysis with 26,408 female and 63,393 male patients. Meta-analysis demonstrated that males had a significantly lower risk of mortality than females (RR: 0.88; 95% CI 0.78, 0.99; P = 0.0001). Females had a shorter hospital length of stay (mean difference -1.4 d; 95% CI - 1.6 d, -1.2 d). No significant differences were identified in intensive care unit length of stay (mean difference -3.0 d; 95% CI -7.0 d, 1.1 d; P = 0.94) or GOS at 6 mo (mean difference 0.2 d; 95% CI -0.9 d, 1.4 d; P = 1). CONCLUSIONS: Compared to male patients, female patients with moderate and severe TBI had a significantly higher in-hospital mortality risk. There were no significant differences in long-term outcomes between genders based on GOS at 6 mo. These findings warrant further investigation into the etiology of these gender disparities and their impact on additional clinical outcome measures.

Predictors of unfavourable outcome in adults with suspected central nervous system infections: a prospective cohort study.

Suspected central nervous system (CNS) infections may pose a diagnostic challenge, and often concern severely ill patients. We aim to identify predictors of unfavourable outcome to prioritize diagnostics and treatment improvements. Unfavourable outcome was assessed on the Glasgow Outcome Scale at hospital discharge, defined by a score of 1 to 4. Of the 1152 episodes with suspected CNS infection, from two Dutch prospective cohorts, the median age was 54 (IQR 37-67), and 563 episodes (49%) occurred in women. The final diagnoses were categorized as CNS infection (N = 358 episodes, 31%), CNS inflammatory disease (N = 113, 10%), non-infectious non-inflammatory neurological disorder (N = 388, 34%), non-neurological infection (N = 252, 22%), and other systemic disorder (N = 41, 4%). Unfavourable outcome occurred in 412 of 1152 (36%), and 99 died (9%). Predictors for unfavourable outcomes included advanced age, absence of headache, tachycardia, altered mental state, focal cerebral deficits, cranial nerve palsies, low thrombocytes, high CSF protein, and the final diagnosis of CNS inflammatory disease (odds ratio 4.5 [95% confidence interval 1.5-12.6]). Episodes suspected of having a CNS infection face high risk of experiencing unfavourable outcome, stressing the urgent need for rapid and accurate diagnostics. Amongst the suspected CNS infection group, those diagnosed with CNS inflammatory disease have the highest risk.

Machine learning based outcome prediction of microsurgically treated unruptured intracranial aneurysms.

Machine learning (ML) has revolutionized data processing in recent years. This study presents the results of the first prediction models based on a long-term monocentric data registry of patients with microsurgically treated unruptured intracranial aneurysms (UIAs) using a temporal train-test split. Temporal train-test splits allow to simulate prospective validation, and therefore provide more accurate estimations of a model's predictive quality when applied to future patients. ML models for the prediction of the Glasgow outcome scale, modified Rankin Scale (mRS), and new transient or permanent neurological deficits (output variables) were created from all UIA patients that underwent microsurgery at the Kepler University Hospital Linz (Austria) between 2002 and 2020 (n = 466), based on 18 patient- and 10 aneurysm-specific preoperative parameters (input variables). Train-test splitting was performed with a temporal split for outcome prediction in microsurgical therapy of UIA. Moreover, an external validation was conducted on an independent external data set (n = 256) of the Department of Neurosurgery, University Medical Centre Hamburg-Eppendorf. In total, 722 aneurysms were included in this study. A postoperative mRS > 2 was best predicted by a quadratic discriminant analysis (QDA) estimator in the internal test set, with an area under the receiver operating characteristic curve (ROC-AUC) of 0.87 ± 0.03 and a sensitivity and specificity of 0.83 ± 0.08 and 0.71 ± 0.07, respectively. A Multilayer Perceptron predicted the post- to preoperative mRS difference > 1 with a ROC-AUC of 0.70 ± 0.02 and a sensitivity and specificity of 0.74 ± 0.07 and 0.50 ± 0.04, respectively. The QDA was the best model for predicting a permanent new neurological deficit with a ROC-AUC of 0.71 ± 0.04 and a sensitivity and specificity of 0.65 ± 0.24 and 0.60 ± 0.12, respectively. Furthermore, these models performed significantly better than the classic logistic regression models (p < 0.0001). The present results showed good performance in predicting functional and clinical outcomes after microsurgical therapy of UIAs in the internal data set, especially for the main outcome parameters, mRS and permanent neurological deficit. The external validation showed poor discrimination with ROC-AUC values of 0.61, 0.53 and 0.58 respectively for predicting a postoperative mRS > 2, a pre- and postoperative difference in mRS > 1 point and a GOS < 5. Therefore, generalizability of the models could not be demonstrated in the external validation. A SHapley Additive exPlanations (SHAP) analysis revealed that this is due to the most important features being distributed quite differently in the internal and external data sets. The implementation of newly available data and the merging of larger databases to form more broad-based predictive models is imperative in the future.

Outcomes following poor-grade aneurysmal subarachnoid haemorrhage: a prospective observational study.

BACKGROUND: Up to 35% of aneurysmal subarachnoid haemorrhage (aSAH) cases may present as poor grade, defined as World Federation of Neurosurgical Societies (WFNS) grades IV and V. In this study, we evaluate functional outcomes and prognostic factors. METHODS: This prospective study included all patients referred to a national, centralized neurosurgical service with a diagnosis of poor-grade aSAH between 01/01/2016 and 31/12/2019. Multivariable logistic regression models were used to estimate probability of poor functional outcomes, defined as a Glasgow Outcome Scale (GOS) of 1-3 at 3 months. RESULTS: Two hundred fifty-seven patients were referred, of whom 116/257 (45.1%) underwent treatment of an aneurysm, with 97/116 (84%) treated within 48 h of referral. Median age was 62 years (IQR 51-69) with a female predominance (167/257, 65%). Untreated patients tended to be older; 123/141 (87%) had WFNS V, 60/141 (45%) unreactive pupils and 21/141 (16%) circulatory arrest. Of all referred patients, poor outcome occurred in 169/230 (73.5%). Unreactive pupils or circulatory arrest conferred a universally poor prognosis, with mortality in 55/56 (98%) and 19/19 (100%), respectively. The risk of a poor outcome was 14.1% (95% CI 4.5-23.6) higher in WFNS V compared with WFNS IV. Age was important in patients without circulatory arrest or unreactive pupils, with risk of a poor outcome increasing by 1.8% per year (95% CI 1-2.7). In patients undergoing aneurysm securement, 48/101 (47.5%) had a poor outcome, with age, rebleeding, vasospasm and cerebrospinal fluid (CSF) diversion being important prognosticators. The addition of serum markers did not add significant discrimination beyond the clinical presentation. CONCLUSIONS: The overall outcomes of WFNS IV and V aSAH remain poor, mainly due to the devastating effects of the original haemorrhage. However, in patients selected for aneurysm securement, good outcomes can be achieved in more than half of patients. Age, pre-intervention rebleeding, vasospasm, and CSF diversion are important prognostic factors.