Multimodal MRI reveals brainstem connections that sustain wakefulness in human consciousness.

Consciousness is composed of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that underlie awareness in the human brain, but knowledge about the subcortical networks that sustain arousal in humans is incomplete. Here, we aimed to map the connectivity of a proposed subcortical arousal network that sustains wakefulness in the human brain, analogous to the cortical default mode network (DMN) that has been shown to contribute to awareness. We integrated data from ex vivo diffusion magnetic resonance imaging (MRI) of three human brains, obtained at autopsy from neurologically normal individuals, with immunohistochemical staining of subcortical brain sections. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain. Deterministic and probabilistic tractography analyses of the ex vivo diffusion MRI data revealed projection, association, and commissural pathways linking dAAN nodes with one another and with DMN nodes. Complementary analyses of in vivo 7-tesla resting-state functional MRI data from the Human Connectome Project identified the dopaminergic ventral tegmental area in the midbrain as a widely connected hub node at the nexus of the subcortical arousal and cortical awareness networks. Our network-based autopsy methods and connectivity data provide a putative neuroanatomic architecture for the integration of arousal and awareness in human consciousness.

Transcranial Doppler cerebrovascular reactivity: Thresholds for clinical significance in cerebrovascular disease.

BACKGROUND AND PURPOSE: Thresholds for abnormal transcranial Doppler cerebrovascular reactivity (CVR) studies are poorly understood, especially for patients with cerebrovascular disease. Using a real-world cohort with cerebral arterial stenosis, we sought to describe a clinically significant threshold for carbon dioxide reactivity (CO2R) and vasomotor range (VMR). METHODS: CVR studies were performed during conditions of breathing room air normally, breathing 8% carbon dioxide air mixture, and hyperventilation. The mean and standard deviation (SD) of CO2R and VMR were calculated for the unaffected side in patients with unilateral stenosis; a deviation of 2 SDs below the mean was chosen as the threshold for abnormal. Receiver operating characteristic (ROC) curves for both sides for patients with unilateral and bilateral stenosis were evaluated for sensitivity (Sn) and specificity (Sp). RESULTS: A total of 133 consecutive CVR studies were performed on 62 patients with stenosis with mean±SD age 55±16 years. Comorbidities included hypertension (60%), diabetes (15%), stroke (40%), and smoking (35%). In patients with unilateral stenosis, mean±SD CO2R for the unaffected side was 1.86±0.53%, defining abnormal CO2R as <0.80%. Mean±SD CO2R for the affected side was 1.27±0.90%. The CO2R threshold predicted abnormal acetazolamide single-photon emission computed tomography (SPECT) (Sn = .73, Sp = .79), CT/MRI perfusion abnormality (Sn = .42, Sp = .77), infarction on MRI (Sn = .45, Sp = .76), and pressure-dependent exam (Sn = .50, Sp = .76). For the unaffected side, mean±SD VMR was 39.5±15.8%, defining abnormal VMR as <7.9%. For the affected side, mean±SD VMR was 26.5±17.8%. The VMR threshold predicted abnormal acetazolamide SPECT (Sn = .46, Sp = .94), infarction on MRI (Sn = .27, Sp = .94), and pressure-dependent exam (Sn = .31, Sp = .90). CONCLUSIONS: In patients with multiple vascular risk factors, a reasonable threshold for clinically significant abnormal CO2R is <0.80% and VMR is <7.9%. Noninvasive CVR may aid in diagnosing and risk stratifying patients with stenosis.

Predicting Functional Dependency in Patients with Disorders of Consciousness: A TBI-Model Systems and TRACK-TBI Study.

OBJECTIVE: It is not currently possible to predict long-term functional dependency in patients with disorders of consciousness (DoC) after traumatic brain injury (TBI). Our objective was to fit and externally validate a prediction model for 1-year dependency in patients with DoC ≥ 2 weeks after TBI. METHODS: We included adults with TBI enrolled in TBI Model Systems (TBI-MS) or Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) studies who were not following commands at rehabilitation admission or 2 weeks post-injury, respectively. We fit a logistic regression model in TBI-MS and validated it in TRACK-TBI. The primary outcome was death or dependency at 1 year post-injury, defined using the Disability Rating Scale. RESULTS: In the TBI-MS Discovery Sample, 1,960 participants (mean age 40 [18] years, 76% male, 68% white) met inclusion criteria, and 406 (27%) were dependent 1 year post-injury. In a TBI-MS held out cohort, the dependency prediction model's area under the receiver operating characteristic curve was 0.79 (95% CI 0.74-0.85), positive predictive value was 53% and negative predictive value was 86%. In the TRACK-TBI external validation (n = 124, age 40 [16] years, 77% male, 81% white), the area under the receiver operating characteristic curve was 0.66 (0.53, 0.79), equivalent to the standard IMPACTcore + CT score (p = 0.8). INTERPRETATION: We developed a 1-year dependency prediction model using the largest existing cohort of patients with DoC after TBI. The sensitivity and negative predictive values were greater than specificity and positive predictive values. Accuracy was diminished in an external sample, but equivalent to the IMPACT model. Further research is needed to improve dependency prediction in patients with DoC after TBI. ANN NEUROL 2023;94:1008-1023.

Sustaining wakefulness: Brainstem connectivity in human consciousness.

Consciousness is comprised of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that modulate awareness in the human brain, but knowledge about the subcortical networks that sustain arousal is lacking. We integrated data from ex vivo diffusion MRI, immunohistochemistry, and in vivo 7 Tesla functional MRI to map the connectivity of a subcortical arousal network that we postulate sustains wakefulness in the resting, conscious human brain, analogous to the cortical default mode network (DMN) that is believed to sustain self-awareness. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain by correlating ex vivo diffusion MRI with immunohistochemistry in three human brain specimens from neurologically normal individuals scanned at 600-750 µm resolution. We performed deterministic and probabilistic tractography analyses of the diffusion MRI data to map dAAN intra-network connections and dAAN-DMN internetwork connections. Using a newly developed network-based autopsy of the human brain that integrates ex vivo MRI and histopathology, we identified projection, association, and commissural pathways linking dAAN nodes with one another and with cortical DMN nodes, providing a structural architecture for the integration of arousal and awareness in human consciousness. We release the ex vivo diffusion MRI data, corresponding immunohistochemistry data, network-based autopsy methods, and a new brainstem dAAN atlas to support efforts to map the connectivity of human consciousness.

Distinguishing Distinct Neural Systems for Proximal vs Distal Upper Extremity Motor Control After Acute Stroke.

BACKGROUND AND OBJECTIVES: The classic and singular pattern of distal greater than proximal upper extremity motor deficits after acute stroke does not account for the distinct structural and functional organization of circuits for proximal and distal motor control in the healthy CNS. We hypothesized that separate proximal and distal upper extremity clinical syndromes after acute stroke could be distinguished and that patterns of neuroanatomical injury leading to these 2 syndromes would reflect their distinct organization in the intact CNS. METHODS: Proximal and distal components of motor impairment (upper extremity Fugl-Meyer score) and strength (Shoulder Abduction Finger Extension score) were assessed in consecutively recruited patients within 7 days of acute stroke. Partial correlation analysis was used to assess the relationship between proximal and distal motor scores. Functional outcomes including the Box and Blocks Test (BBT), Barthel Index (BI), and modified Rankin scale (mRS) were examined in relation to proximal vs distal motor patterns of deficit. Voxel-based lesion-symptom mapping was used to identify regions of injury associated with proximal vs distal upper extremity motor deficits. RESULTS: A total of 141 consecutive patients (49% female) were assessed 4.0 ± 1.6 (mean ± SD) days after stroke onset. Separate proximal and distal upper extremity motor components were distinguishable after acute stroke (p = 0.002). A pattern of proximal more than distal injury (i.e., relatively preserved distal motor control) was not rare, observed in 23% of acute stroke patients. Patients with relatively preserved distal motor control, even after controlling for total extent of deficit, had better outcomes in the first week and at 90 days poststroke (BBT, ρ = 0.51, p < 0.001; BI, ρ = 0.41, p < 0.001; mRS, ρ = 0.38, p < 0.001). Deficits in proximal motor control were associated with widespread injury to subcortical white and gray matter, while deficits in distal motor control were associated with injury restricted to the posterior aspect of the precentral gyrus, consistent with the organization of proximal vs distal neural circuits in the healthy CNS. DISCUSSION: These results highlight that proximal and distal upper extremity motor systems can be selectively injured by acute stroke, with dissociable deficits and functional consequences. Our findings emphasize how disruption of distinct motor systems can contribute to separable components of poststroke upper extremity hemiparesis.

Clinical and Electroencephalographic Predictors of Seizures and Status Epilepticus in 12,450 Critically Ill Adults: A Retrospective Cohort Study.

OBJECTIVES: Status epilepticus (SE) is associated with significantly higher morbidity and mortality than isolated seizures. Our objective was to identify clinical diagnoses and rhythmic and periodic electroencephalogram patterns (RPPs) associated with SE and seizures. DESIGN: Retrospective cohort study. SETTING: Tertiary-care hospitals. SUBJECTS: Twelve thousand four hundred fifty adult hospitalized patients undergoing continuous electroencephalogram (cEEG) monitoring in selected participating sites in the Critical Care EEG Monitoring Research Consortium database (February 2013 to June 2021). INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: We defined an ordinal outcome in the first 72 hours of cEEG: no seizures, isolated seizures without SE, or SE (with or without isolated seizures). Composite groups included isolated seizures or SE (AnySz) and no seizure or isolated seizures. In this cohort (mean age: 60 ± 17 yr), 1,226 patients (9.8%) had AnySz and 439 patients (3.5%) had SE. In a multivariate model, factors independently associated with SE were cardiac arrest (9.2% with SE; adjusted odds ratio, 8.8 [6.3-12.1]), clinical seizures before cEEG (5.7%; 3.3 [2.5-4.3]), brain neoplasms (3.2%; 1.6 [1.0-2.6]), lateralized periodic discharges (LPDs) (15.4%; 7.3 [5.7-9.4]), brief potentially ictal rhythmic discharges (BIRDs) (22.5%; 3.8 [2.6-5.5]), and generalized periodic discharges (GPDs) (7.2%; 2.4 [1.7-3.3]). All above variables and lateralized rhythmic delta activity (LRDA) were also associated with AnySz. Factors disproportionately increasing odds of SE over isolated seizures were cardiac arrest (7.3 [4.4-12.1]), clinical seizures (1.7 [1.3-2.4]), GPDs (2.3 [1.4-3.5]), and LPDs (1.4 [1.0-1.9]). LRDA had lower odds of SE compared with isolated seizures (0.5 [0.3-0.9]). RPP modifiers did not improve SE prediction beyond RPPs presence/absence ( p = 0.8). CONCLUSIONS: Using the largest existing cEEG database, we identified specific predictors of SE (cardiac arrest, clinical seizures prior to cEEG, brain neoplasms, LPDs, GPDs, and BIRDs) and seizures (all previous and LRDA). These findings could be used to tailor cEEG monitoring for critically ill patients.

Predicting Functional Dependency in Patients with Disorders of Consciousness: A TBI-Model Systems and TRACK-TBI Study.

Importance: There are currently no models that predict long-term functional dependency in patients with disorders of consciousness (DoC) after traumatic brain injury (TBI). Objective: Fit, test, and externally validate a prediction model for 1-year dependency in patients with DoC 2 or more weeks after TBI. Design: Secondary analysis of patients enrolled in TBI Model Systems (TBI-MS, 1988-2020, Discovery Sample) or Transforming Research and Clinical Knowledge in TBI (TRACK-TBI, 2013-2018, Validation Sample) and followed 1-year post-injury. Setting: Multi-center study at USA rehabilitation hospitals (TBI-MS) and acute care hospitals (TRACK-TBI). Participants: Adults with TBI who were not following commands at rehabilitation admission (TBI-MS; days post-injury vary) or 2-weeks post-injury (TRACK-TBI). Exposures: In the TBI-MS database (model fitting and testing), we screened demographic, radiological, clinical variables, and Disability Rating Scale (DRS) item scores for association with the primary outcome. Main Outcome: The primary outcome was death or complete functional dependency at 1-year post-injury, defined using a DRS-based binary measure (DRS Depend ), indicating need for assistance with all activities and concomitant cognitive impairment. Results: In the TBI-MS Discovery Sample, 1,960 subjects (mean age 40 [18] years, 76% male, 68% white) met inclusion criteria and 406 (27%) were dependent at 1-year post-injury. A dependency prediction model had an area under the receiver operating characteristic curve (AUROC) of 0.79 [0.74, 0.85], positive predictive value of 53%, and negative predictive value of 86% for dependency in a held-out TBI-MS Testing cohort. Within the TRACK-TBI external validation sample (N=124, age 40 [16], 77% male, 81% white), a model modified to remove variables not collected in TRACK-TBI, had an AUROC of 0.66 [0.53, 0.79], equivalent to the gold-standard IMPACT core+CT score (0.68; 95% AUROC difference CI: -0.2 to 0.2, p=0.8). Conclusions and Relevance: We used the largest existing cohort of patients with DoC after TBI to develop, test and externally validate a prediction model of 1-year dependency. The model’s sensitivity and negative predictive value were greater than specificity and positive predictive value. Accuracy was diminished in an external sample, but equivalent to the best-available models. Further research is needed to improve dependency prediction in patients with DoC after TBI.

Automated detection of axonal damage along white matter tracts in acute severe traumatic brain injury.

New techniques for individualized assessment of white matter integrity are needed to detect traumatic axonal injury (TAI) and predict outcomes in critically ill patients with acute severe traumatic brain injury (TBI). Diffusion MRI tractography has the potential to quantify white matter microstructure in vivo and has been used to characterize tract-specific changes following TBI. However, tractography is not routinely used in the clinical setting to assess the extent of TAI, in part because focal lesions reduce the robustness of automated methods. Here, we propose a pipeline that combines automated tractography reconstructions of 40 white matter tracts with multivariate analysis of along-tract diffusion metrics to assess the presence of TAI in individual patients with acute severe TBI. We used the Mahalanobis distance to identify abnormal white matter tracts in each of 18 patients with acute severe TBI as compared to 33 healthy subjects. In all patients for which a FreeSurfer anatomical segmentation could be obtained (17 of 18 patients), including 13 with focal lesions, the automated pipeline successfully reconstructed a mean of 37.5 ± 2.1 white matter tracts without the need for manual intervention. A mean of 2.5 ± 2.1 tracts resulted in partial or failed reconstructions and needed to be reinitialized upon visual inspection. The pipeline detected at least one abnormal tract in all patients (mean: 9.1 ± 7.9) and accurately discriminated between patients and controls (AUC: 0.91). The number and neuroanatomic location of abnormal tracts varied across patients and levels of consciousness. The premotor, temporal, and parietal sections of the corpus callosum were the most commonly damaged tracts (in 10, 9, and 8 patients, respectively), consistent with prior histopathological studies of TAI. TAI measures were not associated with concurrent behavioral measures of consciousness. In summary, we provide proof-of-principle evidence that an automated tractography pipeline has translational potential to detect and quantify TAI in individual patients with acute severe TBI.

The biomechanical signature of loss of consciousness: computational modelling of elite athlete head injuries.

Sports related head injuries can cause transient neurological events including loss of consciousness and dystonic posturing. However, it is unknown why head impacts that appear similar produce distinct neurological effects. The biomechanical effect of impacts can be estimated using computational models of strain within the brain. Here, we investigate the strain and strain rates produced by professional American football impacts that led to loss of consciousness, posturing or no neurological signs. We reviewed 1280 National Football League American football games and selected cases where the team's medical personnel made a diagnosis of concussion. Videos were then analysed for signs of neurological events. We identified 20 head impacts that showed clear video signs of loss of consciousness and 21 showing clear abnormal posturing. Forty-one control impacts were selected where there was no observable evidence of neurological signs, resulting in 82 videos of impacts for analysis. Video analysis was used to guide physical reconstructions of these impacts, allowing us to estimate the impact kinematics. These were then used as input to a detailed 3D high-fidelity finite element model of brain injury biomechanics to estimate strain and strain rate within the brain. We tested the hypotheses that impacts producing loss of consciousness would be associated with the highest biomechanical forces, that loss of consciousness would be associated with high forces in brainstem nuclei involved in arousal and that dystonic posturing would be associated with high forces in motor regions. Impacts leading to loss of consciousness compared to controls produced higher head acceleration (linear acceleration; 81.5 g ± 39.8 versus 47.9 ± 21.4; P = 0.004, rotational acceleration; 5.9 krad/s2 ± 2.4 versus 3.5 ± 1.6; P < 0.001) and in voxel-wise analysis produced larger brain deformation in many brain regions, including parts of the brainstem and cerebellum. Dystonic posturing was also associated with higher deformation compared to controls, with brain deformation observed in cortical regions that included the motor cortex. Loss of consciousness was specifically associated with higher strain rates in brainstem regions implicated in maintenance of consciousness, including following correction for the overall severity of impact. These included brainstem nuclei including the locus coeruleus, dorsal raphé and parabrachial complex. The results show that in head impacts producing loss of consciousness, brain deformation is disproportionately seen in brainstem regions containing nuclei involved in arousal, suggesting that head impacts produce loss of consciousness through a biomechanical effect on key brainstem nuclei involved in the maintenance of consciousness.

Volume replacement is associated with a diminished osmolar effect of mannitol in patients with acute brain injury.

INTRODUCTION: Animal experiments recently demonstrated that replacing urinary loses with crystalloid diminishes the therapeutic effect of mannitol by reducing the increase in osmolality. We aimed to investigate whether this effect is similarly seen in in brain-injured patients by studying the association between total body fluid balance (TBB) and the osmolar response to mannitol. METHODS: We performed a retrospective cohort study of adult patients with acute brain injury between 2015 and 2021 who received ≥ 2 doses of mannitol within 8 hours and no intercurrent concentrated saline solution. We analyzed the association between the change in TBB (∆TBB) and change in osmolality (∆Osm) before and after mannitol in a linear model, both as univariate and after adjustment for common confounding factors. RESULTS: Of 6,145 patients who received mannitol, 155 patients met inclusion criteria (mean age 60 ± 17 years, 48% male, 83% white). The mean total mannitol dose was 2 ± 0.5 g/kg and the mean change in plasma osmolality was 7.9 ± 7.1 mOsm/kg. Each 1 L increase in ∆TBB was associated with a change of -1.1 mOsm/L in ∆Osm (95% CI [-2.2, -0.02], p = 0.045). The magnitude of association was similar to that of total mannitol dose and remained consistent in an adjusted model and after excluding outliers. CONCLUSIONS: In patients with acute brain injury, a positive TBB is associated with a diminished mannitol-induced increase in plasma osmolality. Future prospective studies are needed to confirm these findings and their influence on the therapeutic effect of mannitol.

Cerebrovascular injuries in traumatic brain injury.

Traumatic brain injury is a complex and highly heterogeneous disease due to the host of concomitant injuries that may accompany the initial insult. Due to the dynamic interplay between the injuries that may arise, the management of these injuries is challenging. In a small subset of patients with traumatic brain injury, cerebral vascular injury may occur, which presents its own diagnostic and therapeutic challenges. These vascular injuries often present in a delayed fashion, thereby going unnoticed by clinicians. Early recognition and treatment of these injuries is crucial, given their high morbidity and mortality. Through a critical review of the literature, we present the spectrum of cerebrovascular injuries that may occur with traumatic brain injury and discuss classification systems that are used to stratify cerebrovascular injury. We then focus on the diagnosis of cerebral vascular injury using different neuroimaging modalities. Lastly, we explore the treatment of these injuries ranging from antiplatelet therapies to endovascular and open vascular procedures. By highlighting the pitfalls and challenges of this complex disease, we hope to provide clinicians with the framework to recognize and treat vascular injuries that are seen in patients with traumatic brain injury.

Applications of Advanced MRI to Disorders of Consciousness.

Disorder of consciousness (DoC) after severe brain injury presents numerous challenges to clinicians, as the diagnosis, prognosis, and management are often uncertain. Magnetic resonance imaging (MRI) has long been used to evaluate brain structure in patients with DoC. More recently, advances in MRI technology have permitted more detailed investigations of the brain's structural integrity (via diffusion MRI) and function (via functional MRI). A growing literature has begun to show that these advanced forms of MRI may improve our understanding of DoC pathophysiology, facilitate the identification of patient consciousness, and improve the accuracy of clinical prognostication. Here we review the emerging evidence for the application of advanced MRI for patients with DoC.

Comparison of Common Outcome Measures for Assessing Independence in Patients Diagnosed with Disorders of Consciousness: A Traumatic Brain Injury Model Systems Study.

Patients with disorders of consciousness (DoC) after traumatic brain injury (TBI) recover to varying degrees of functional dependency. Dependency is difficult to measure but critical for interpreting clinical trial outcomes and prognostic counseling. In participants with DoC (i.e., not following commands) enrolled in the TBI Model Systems National Database (TBIMS NDB), we used the Functional Independence Measure (FIM®) as the reference to evaluate how accurately the Glasgow Outcome Scale-Extended (GOSE) and Disability Rating Scale (DRS) assess dependency. Using the established FIM-dependency cut-point of <80, we measured the classification performance of literature-derived GOSE and DRS cut-points at 1-year post-injury. We compared the area under the receiver operating characteristic curve (AUROC) between the DRSDepend, a DRS-derived marker of dependency, and the data-derived optimal GOSE and DRS cut-points. Of 18,486 TBIMS participants, 1483 met inclusion criteria (mean [standard deviation (SD)] age = 38 [18] years; 76% male). The sensitivity of GOSE cut-points of ≤3 and ≤4 (Lower Severe and Upper Severe Disability, respectively) for identifying FIM-dependency were 97% and 98%, but specificities were 73% and 51%, respectively. The sensitivity of the DRS cut-point of ≥12 (Severe Disability) for identifying FIM-dependency was 60%, but specificity was 100%. The DRSDepend had a sensitivity of 83% and a specificity of 94% for classifying FIM-dependency, with a greater AUROC than the data-derived optimal GOSE (≤3, p = 0.01) and DRS (≥10, p = 0.008) cut-points. Commonly used GOSE and DRS cut-points have limited specificity or sensitivity for identifying functional dependency. The DRSDepend identifies FIM-dependency more accurately than the GOSE and DRS cut-points, but requires further validation.

Understanding Delays in MRI-based Selection of Large Vessel Occlusion Stroke Patients for Endovascular Thrombectomy.

PURPOSE: Given the efficacy of endovascular thrombectomy (EVT), optimizing systems of delivery is crucial. Magnetic resonance imaging (MRI) is the gold standard for evaluating tissue viability but may require more time to obtain and interpret. We sought to identify determinants of arrival-to-puncture time for patients who underwent MRI-based EVT selection in a real-world setting. METHODS: Patients were identified from a prospectively maintained database from 2011-2019 that included demographics, presentations, treatments, and outcomes. Process times were obtained from the medical charts. MRI times were obtained from time stamps on the first sequence. Linear and logistic regressions were used to infer explanatory variables of arrival-to-puncture times and effects of arrival-to-puncture time on functional outcomes. RESULTS: In this study 192 patients (median age 70 years, 57% women, 12% non-white) underwent MRI-based EVT selection. 66% also underwent computed tomography (CT) at the hub before EVT. General anesthesia was used for 33%. Among the entire cohort, the median arrival-to-puncture was 102 min; however, among those without CT it was 77 min. Longer arrival-to-puncture times independently reduced the odds of 90-day good outcome (∆mRS ≤ 2 from pre-stroke, aOR = 0.990, 95%CI = 0.981-0.999, p = 0.040) when controlling for age, NIHSS, and good reperfusion (TICI 2b-3). Independent determinants of longer arrival-to-puncture were CT plus MRI (ß = 0.205, p = 0.003), non-white race/ethnicity (ß = 0.162, p = 0.012), coronary disease (ß = 0.205, p = 0.001), and general anesthesia (ß = 0.364, p < 0.0001). CONCLUSION: Minimizing arrival-to-puncture time is important for outcomes. Real-world challenges exist in an MRI-based EVT selection protocol; avoiding double imaging is key to saving time. Racial/ethnic disparities require further study. Understanding variables associated with delay will inform protocol changes.

Association of Traumatic Brain Injury With the Risk of Developing Chronic Cardiovascular, Endocrine, Neurological, and Psychiatric Disorders.

Importance: Increased risk of neurological and psychiatric conditions after traumatic brain injury (TBI) is well-defined. However, cardiovascular and endocrine comorbidity risk after TBI in individuals without these comorbidities and associations with post-TBI mortality have received little attention. Objective: To assess the incidence of cardiovascular, endocrine, neurological, and psychiatric comorbidities in patients with mild TBI (mTBI) or moderate to severe TBI (msTBI) and analyze associations between post-TBI comorbidities and mortality. Design, Setting, and Participants: This prospective longitudinal cohort study used hospital-based patient registry data from a tertiary academic medical center to select patients without any prior clinical comorbidities who experienced TBI from 2000 to 2015. Using the same data registry, individuals without head injuries, the unexposed group, and without target comorbidities were selected and age-, sex-, and race-frequency-matched to TBI subgroups. Patients were followed-up for up to 10 years. Data were analyzed in 2021. Exposures: Mild or moderate to severe head trauma. Main Outcomes and Measures: Cardiovascular, endocrine, neurologic, and psychiatric conditions were defined based on International Classification of Diseases, Ninth Revision (ICD-9) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10). Associations between TBI and comorbidities, as well as associations between the comorbidities and mortality, were analyzed. Results: A total of 4351 patients with mTBI (median [IQR] age, 45 [29-57] years), 4351 patients with msTBI (median [IQR] age, 47 [30-58] years), and 4351 unexposed individuals (median [IQR] age, 46 [30-58] years) were included in analyses. In each group, 45% of participants were women. mTBI and msTBI were significantly associated with higher risks of cardiovascular, endocrine, neurologic, and psychiatric disorders compared with unexposed individuals. In particular, hypertension risk was increased in both mTBI (HR, 2.5; 95% CI, 2.1-2.9) and msTBI (HR, 2.4; 95% CI, 2.0-2.9) groups. Diabetes risk was increased in both mTBI (HR, 1.9; 95% CI, 1.4-2.7) and msTBI (HR, 1.9; 95% CI, 1.4-2.6) groups, and risk of ischemic stroke or transient ischemic attack was also increased in mTBI (HR, 2.2; 95% CI, 1.4-3.3) and msTBI (HR, 3.6; 95% CI, 2.4-5.3) groups. All comorbidities in the TBI subgroups emerged within a median (IQR) of 3.49 (1.76-5.96) years after injury. Risks for post-TBI comorbidities were also higher in patients aged 18 to 40 years compared with age-matched unexposed individuals: hypertension risk was increased in the mTBI (HR, 5.9; 95% CI, 3.9-9.1) and msTBI (HR, 3.9; 95% CI, 2.5-6.1) groups, while hyperlipidemia (HR, 2.3; 95% CI, 1.5-3.4) and diabetes (HR, 4.6; 95% CI, 2.1-9.9) were increased in the mTBI group. Individuals with msTBI, compared with unexposed patients, had higher risk of mortality (432 deaths [9.9%] vs 250 deaths [5.7%]; P < .001); postinjury hypertension (HR, 1.3; 95% CI, 1.1-1.7), coronary artery disease (HR, 2.2; 95% CI, 1.6-3.0), and adrenal insufficiency (HR, 6.2; 95% CI, 2.8-13.0) were also associated with higher mortality. Conclusions and Relevance: These findings suggest that TBI of any severity was associated with a higher risk of chronic cardiovascular, endocrine, and neurological comorbidities in patients without baseline diagnoses. Medical comorbidities were observed in relatively young patients with TBI. Comorbidities occurring after TBI were associated with higher mortality. These findings suggest the need for a targeted screening program for multisystem diseases after TBI, particularly chronic cardiometabolic diseases.

Regional Distribution of Brain Injury After Cardiac Arrest: Clinical and Electrographic Correlates.

BACKGROUND AND OBJECTIVES: Disorders of consciousness, EEG background suppression, and epileptic seizures are associated with poor outcome after cardiac arrest. Our objective was to identify the distribution of diffusion MRI-measured anoxic brain injury after cardiac arrest and to define the regional correlates of disorders of consciousness, EEG background suppression, and seizures. METHODS: We analyzed patients from a single-center database of unresponsive patients who underwent diffusion MRI after cardiac arrest (n = 204). We classified each patient according to recovery of consciousness (command following) before discharge, the most continuous EEG background (burst suppression vs continuous), and the presence or absence of seizures. Anoxic brain injury was measured with the apparent diffusion coefficient (ADC) signal. We identified ADC abnormalities relative to controls without cardiac arrest (n = 48) and used voxel lesion symptom mapping to identify regional associations with disorders of consciousness, EEG background suppression, and seizures. We then used a bootstrapped lasso regression procedure to identify robust, multivariate regional associations with each outcome variable. Last, using area under receiver operating characteristic curves, we then compared the classification ability of the strongest regional associations to that of brain-wide summary measures. RESULTS: Compared to controls, patients with cardiac arrest demonstrated ADC signal reduction that was most significant in the occipital lobes. Disorders of consciousness were associated with reduced ADC most prominently in the occipital lobes but also in deep structures. Regional injury more accurately classified patients with disorders of consciousness than whole-brain injury. Background suppression mapped to a similar set of brain regions, but regional injury could no better classify patients than whole-brain measures. Seizures were less common in patients with more severe anoxic injury, particularly in those with injury to the lateral temporal white matter. DISCUSSION: Anoxic brain injury was most prevalent in posterior cerebral regions, and this regional pattern of injury was a better predictor of disorders of consciousness than whole-brain injury measures. EEG background suppression lacked a specific regional association, but patients with injury to the temporal lobe were less likely to have seizures. Regional patterns of anoxic brain injury are relevant to the clinical and electrographic sequelae of cardiac arrest and may hold importance for prognosis. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that disorders of consciousness after cardiac arrest are associated with widely lower ADC values on diffusion MRI and are most strongly associated with reductions in occipital ADC.

Midline Shift Greater than 3 mm Independently Predicts Outcome After Ischemic Stroke.

BACKGROUND: Cerebral edema is associated with worse outcome after acute stroke; however, the minimum clinically relevant threshold remains unknown. This study aimed to identify the minimal degree of midline shift (MLS) that predicts outcome in a cohort encompassing a broad range of patients with acute stroke. METHODS: Patient-level data from six acute stroke clinical trials were combined with endovascular thrombectomy registries from two academic referral centers, generating a combined cohort of 1977 patients. MLS was extracted from the original trial data or measured on computed tomography or magnetic resonance imaging that was obtained a median of 47.0 h (interquartile range 27.0-75.1 h) after stroke onset. Logistic regression was performed to identify predictors of poor outcome and the minimal clinically relevant MLS threshold. RESULTS: The presence of MLS was a predictor of poor outcome, independent of baseline clinical and demographic factors (adjusted odds ratio 4.46, 95% confidence interval 3.56-5.59, p < 0.001). Examining the full range of MLS values identified, a value of greater than 3 mm was the critical threshold that significantly predicted poor outcome (adjusted odds ratio 3.20 [1.31-7.82], p = 0.011). CONCLUSIONS: These results show that the presence of MLS predicts poor outcome and, specifically, MLS value greater than 3 mm is an important threshold across a variety of clinical settings. These findings may have relevance for the design and interpretation of future trials for antiedema therapies.

Transcranial-Doppler-Measured Vasospasm Severity is Associated with Delayed Cerebral Infarction After Subarachnoid Hemorrhage.

BACKGROUND: Angiographic vasospasm after aneurysmal subarachnoid hemorrhage (aSAH) is associated with delayed cerebral ischemia (DCI)-related cerebral infarction (radiological DCI) and worsened neurological outcome. Transcranial Doppler (TCD) measurements of cerebral blood flow velocity are commonly used after aSAH to screen for vasospasm; however, their association with cerebral infarction is not well characterized. We sought to determine whether time-varying TCD-measured vasospasm severity is associated with cerebral infarction and investigate the performance characteristics of different time/severity cutoffs for predicting cerebral infarction. METHODS: We conducted a retrospective single-center cohort study of consecutive adult patients with aSAH with at least one TCD study between 2011 and 2020. The primary outcome was radiological DCI, defined as a cerebral infarction developing at least 2 days after any surgical or endovascular intervention without an alternative cause. Cox proportional hazards models were used to examine associations between time-varying vasospasm severity and radiological DCI. Optimal TCD-based time/severity thresholds for predicting radiological DCI were then determined. RESULTS: Of 262 patients with aSAH who underwent TCD studies, 27 (10%) developed radiological DCI. Patients with radiological DCI had higher modified Fisher scale scores and trended toward earlier onset of vasospasm. Adjusted for age, Hunt and Hess scores, and modified Fisher scale scores, the worst-vessel vasospasm severity was associated with radiological DCI (adjusted hazard ratio 1.7 [95% confidence interval 1.1-2.4]). Vasospasm severity within a specific vessel was associated with risk of delayed infarction in the territory supplied by that vessel. Optimal discrimination of patients with radiological DCI was achieved with thresholds of mild vasospasm on days 4-5 or moderate vasospasm on days 6-9, with negative predictive values greater than 90% and positive predictive values near 20%. CONCLUSIONS: TCD-measured vasospasm severity is associated with radiological DCI after aSAH. An early, mild TCD-based vasospasm severity threshold had a high negative predictive value, supporting its role as a screening tool to identify at-risk patients.

Disorders of Consciousness Associated With COVID-19: A Prospective Multimodal Study of Recovery and Brain Connectivity.

BACKGROUND AND OBJECTIVES: In patients with severe coronavirus disease 2019 (COVID-19), disorders of consciousness (DoC) have emerged as a serious complication. The prognosis and pathophysiology of COVID-DoC remain unclear, complicating decisions about continuing life-sustaining treatment. We describe the natural history of COVID-DoC and investigate its associated brain connectivity profile. METHODS: In a prospective longitudinal study, we screened consecutive patients with COVID-19 at our institution. We enrolled critically ill adult patients with a DoC unexplained by sedation or structural brain injury and who were planned to undergo a brain MRI. We performed resting-state fMRI and diffusion MRI to evaluate functional and structural connectivity compared to healthy controls and patients with DoC resulting from severe traumatic brain injury (TBI). We assessed the recovery of consciousness (command following) and functional outcomes (Glasgow Outcome Scale Extended [GOSE] and the Disability Rating Scale [DRS]) at hospital discharge and 3 and 6 months after discharge. We also explored whether clinical variables were associated with recovery from COVID-DoC. RESULTS: After screening 1,105 patients with COVID-19, we enrolled 12 with COVID-DoC. The median age was 63.5 years (interquartile range 55-76.3 years). After the exclusion of 1 patient who died shortly after enrollment, all of the remaining 11 patients recovered consciousness 0 to 25 days (median 7 [5-14.5] days) after the cessation of continuous IV sedation. At discharge, all surviving patients remained dependent: median GOSE score 3 (1-3) and median DRS score 23 (16-30). Ultimately, however, except for 2 patients with severe polyneuropathy, all returned home with normal cognition and minimal disability: at 3 months, median GOSE score 3 (3-3) and median DRS score 7 (5-13); at 6 months, median GOSE score 4 (4-5), median DRS score 3 (3-5). Ten patients with COVID-DoC underwent advanced neuroimaging; functional and structural brain connectivity in those with COVID-DoC was diminished compared to healthy controls, and structural connectivity was comparable to that in patients with severe TBI. DISCUSSION: Patients who survived invariably recovered consciousness after COVID-DoC. Although disability was common after hospitalization, functional status improved over the ensuing months. While future research is necessary, these prospective findings inform the prognosis and pathophysiology of COVID-DoC. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov identifier: NCT04476589.

Therapies to Restore Consciousness in Patients with Severe Brain Injuries: A Gap Analysis and Future Directions.

BACKGROUND/OBJECTIVE: For patients with disorders of consciousness (DoC) and their families, the search for new therapies has been a source of hope and frustration. Almost all clinical trials in patients with DoC have been limited by small sample sizes, lack of placebo groups, and use of heterogeneous outcome measures. As a result, few therapies have strong evidence to support their use; amantadine is the only therapy recommended by current clinical guidelines, specifically for patients with DoC caused by severe traumatic brain injury. To foster and advance development of consciousness-promoting therapies for patients with DoC, the Curing Coma Campaign convened a Coma Science Work Group to perform a gap analysis. METHODS: We consider five classes of therapies: (1) pharmacologic; (2) electromagnetic; (3) mechanical; (4) sensory; and (5) regenerative. For each class of therapy, we summarize the state of the science, identify gaps in knowledge, and suggest future directions for therapy development. RESULTS: Knowledge gaps in all five therapeutic classes can be attributed to the lack of: (1) a unifying conceptual framework for evaluating therapeutic mechanisms of action; (2) large-scale randomized controlled trials; and (3) pharmacodynamic biomarkers that measure subclinical therapeutic effects in early-phase trials. To address these gaps, we propose a precision medicine approach in which clinical trials selectively enroll patients based upon their physiological receptivity to targeted therapies, and therapeutic effects are measured by complementary behavioral, neuroimaging, and electrophysiologic endpoints. CONCLUSIONS: This personalized approach can be realized through rigorous clinical trial design and international collaboration, both of which will be essential for advancing the development of new therapies and ultimately improving the lives of patients with DoC.