Faculty Bibliography

Use of thoracoabdominal normothermic regional perfusion (TA-NRP) during donation after circulatory death (DCD) is an important advance in organ donation. Prior to establishing TA-NRP, the brachiocephalic, left carotid, and left subclavian arteries are ligated, thereby eliminating anterograde brain blood flow via the carotid and vertebral arteries. While theoretical concerns have been voiced that TA-NRP after DCD may restore brain blood flow via collaterals, there have been no studies to confirm or refute this possibility. We evaluated brain blood flow using intraoperative transcranial Doppler (TCD) in two DCD TA-NRP cases. Pre-extubation, anterior and posterior circulation brain blood flow waveforms were present in both cases, similar to the waveforms detected in a control patient on mechanical circulatory support undergoing cardiothoracic surgery. Following declaration of death and initiation of TA-NRP, no brain blood flow was detected in either case. Additionally, there was absence of brainstem reflexes, no response to noxious stimuli and no respiratory effort. These TCD results demonstrate that DCD with TA-NRP did not restore brain blood flow.

INTRODUCTION/BACKGROUND:Uniform case definitions are required to ensure harmonised reporting of neurological syndromes associated with SARS-CoV-2. Moreover, it is unclear how clinicians perceive the relative importance of SARS-CoV-2 in neurological syndromes, which risks under- or over-reporting. METHODS:We invited clinicians through global networks, including the World Federation of Neurology, to assess ten anonymised vignettes of SARS-CoV-2 neurological syndromes. Using standardised case definitions, clinicians assigned a diagnosis and ranked association with SARS-CoV-2. We compared diagnostic accuracy and assigned association ranks between different settings and specialties and calculated inter-rater agreement for case definitions as "poor" (κ ≤ 0.4), "moderate" or "good" (κ > 0.6). RESULTS:1265 diagnoses were assigned by 146 participants from 45 countries on six continents. The highest correct proportion were cerebral venous sinus thrombosis (CVST, 95.8%), Guillain-Barré syndrome (GBS, 92.4%) and headache (91.6%) and the lowest encephalitis (72.8%), psychosis (53.8%) and encephalopathy (43.2%). Diagnostic accuracy was similar between neurologists and non-neurologists (median score 8 vs. 7/10, p = 0.1). Good inter-rater agreement was observed for five diagnoses: cranial neuropathy, headache, myelitis, CVST, and GBS and poor agreement for encephalopathy. In 13% of vignettes, clinicians incorrectly assigned lowest association ranks, regardless of setting and specialty. CONCLUSION/CONCLUSIONS:The case definitions can help with reporting of neurological complications of SARS-CoV-2, also in settings with few neurologists. However, encephalopathy, encephalitis, and psychosis were often misdiagnosed, and clinicians underestimated the association with SARS-CoV-2. Future work should refine the case definitions and provide training if global reporting of neurological syndromes associated with SARS-CoV-2 is to be robust.

BACKGROUND:The utility of head computed tomography (CT) in predicting elevated intracranial pressure (ICP) is known to be limited in traumatic brain injury; however, few data exist in patients with spontaneous intracranial hemorrhage. METHODS:We conducted a retrospective review of prospectively collected data in patients with nontraumatic intracranial hemorrhage (subarachnoid hemorrhage [SAH] or intraparenchymal hemorrhage [IPH]) who underwent external ventricular drain (EVD) placement. Head CT scans performed immediately prior to EVD placement were quantitatively reviewed for features suggestive of elevated ICP, including temporal horn diameter, bicaudate index, basal cistern effacement, midline shift, and global cerebral edema. The modified Fisher score (mFS), intraventricular hemorrhage score, and IPH volume were also measured, as applicable. We calculated the accuracy, positive predictive value (PPV), and negative predictive value (NPV) of these radiographic features for the coprimary outcomes of elevated ICP (> 20 mm Hg) at the time of EVD placement and at any time during the hospital stay. Multivariable backward stepwise logistic regression analysis was performed to identify significant radiographic factors associated with elevated ICP. RESULTS:Of 608 patients with intracranial hemorrhages enrolled during the study time frame, 243 (40%) received an EVD and 165 (n = 107 SAH, n = 58 IPH) had a preplacement head CT scan available for rating. Elevated opening pressure and elevated ICP during hospitalization were recorded in 48 of 152 (29%) and 103 of 165 (62%), respectively. The presence of ≥ 1 radiographic feature had only 32% accuracy for identifying elevated opening pressure (PPV 30%, NPV 58%, area under the curve [AUC] 0.537, 95% asymptotic confidence interval [CI] 0.436-0.637, P = 0.466) and 59% accuracy for predicting elevated ICP during hospitalization (PPV 63%, NPV 40%, AUC 0.514, 95% asymptotic CI 0.391-0.638, P = 0.820). There was no significant association between the number of radiographic features and ICP elevation. Head CT scans without any features suggestive of elevated ICP occurred in 25 of 165 (15%) patients. However, 10 of 25 (40%) of these patients had elevated opening pressure, and 15 of 25 (60%) had elevated ICP during their hospital stay. In multivariable models, mFS (adjusted odds ratio [aOR] 1.36, 95% CI 1.10-1.68) and global cerebral edema (aOR 2.93, 95% CI 1.27-6.75) were significantly associated with elevated ICP; however, their accuracies were only 69% and 60%, respectively. All other individual radiographic features had accuracies between 38 and 58% for identifying intracranial hypertension. CONCLUSIONS:More than 50% of patients with spontaneous intracranial hemorrhage without radiographic features suggestive of elevated ICP actually had ICP > 20 mm Hg during EVD placement or their hospital stay. Morphological head CT findings were only 32% and 59% accurate in identifying elevated opening pressure and ICP elevation during hospitalization, respectively.

BACKGROUND:Limited data exists evaluating predictors of long-term outcomes after hospitalization for COVID-19. METHODS:We conducted a prospective, longitudinal cohort study of patients hospitalized for COVID-19. The following outcomes were collected at 6 and 12-months post-diagnosis: disability using the modified Rankin Scale (mRS), activities of daily living assessed with the Barthel Index, cognition assessed with the telephone Montreal Cognitive Assessment (t-MoCA), Neuro-QoL batteries for anxiety, depression, fatigue and sleep, and post-acute symptoms of COVID-19. Predictors of these outcomes, including demographics, pre-COVID-19 comorbidities, index COVID-19 hospitalization metrics, and life stressors, were evaluated using multivariable logistic regression. RESULTS:Of 790 COVID-19 patients who survived hospitalization, 451(57%) completed 6-month (N = 383) and/or 12-month (N = 242) follow-up, and 77/451 (17%) died between discharge and 12-month follow-up. Significant life stressors were reported in 121/239 (51%) at 12-months. In multivariable analyses, life stressors including financial insecurity, food insecurity, death of a close contact and new disability were the strongest independent predictors of worse mRS, Barthel Index, depression, fatigue, and sleep scores, and prolonged symptoms, with adjusted odds ratios ranging from 2.5 to 20.8. Other predictors of poor outcome included older age (associated with worse mRS, Barthel, t-MoCA, depression scores), baseline disability (associated with worse mRS, fatigue, Barthel scores), female sex (associated with worse Barthel, anxiety scores) and index COVID-19 severity (associated with worse Barthel index, prolonged symptoms). CONCLUSIONS:Life stressors contribute substantially to worse functional, cognitive and neuropsychiatric outcomes 12-months after COVID-19 hospitalization. Other predictors of poor outcome include older age, female sex, baseline disability and severity of index COVID-19.

OBJECTIVE:We explored the relationship between markers of infection and inflammation and mortality in patients with acute ischemic stroke who underwent thrombectomy. METHODS:We performed retrospective chart review of stroke patients who underwent thrombectomy at two tertiary academic centers between December 2018 and November 2020. Associations between discharge mortality, WBC count, neutrophil percentage, fever, culture data, and antibiotic treatment were analyzed using the Wilcoxon rank sum test, Student's t-test, and Fisher's exact test. Independent predictors of mortality were identified with multivariable analysis. Analyses were repeated excluding COVID-positive patients. RESULTS:Of 248 patients who underwent thrombectomy, 41 (17 %) died prior to discharge. Mortality was associated with admission WBC count (11 [8-14] vs. 9 [7-12], p = 0.0093), admission neutrophil percentage (78 % ± 11 vs. 71 % ± 14, p = 0.0003), peak WBC count (17 [13-22] vs. 12 [9-15], p < 0.0001), fever (71 % vs. 27 %, p < 0.0001), positive culture (44 % vs. 15 %, p < 0.0001), and days treated with antibiotics (3 [1-7] vs. 1 [0-4], p < 0.0001). After controlling for age, admission NIHSS and post-thrombectomy ASPECTS score, mortality was associated with admission WBC count (OR 13, CI 1.32-142, p = 0.027), neutrophil percentage (OR 1.03, CI 1.0-1.07, p = 0.045), peak WBC count (OR 301, CI 24-5008, p < 0.0001), fever (OR 24.2, CI 1.77-332, p < 0.0001), and positive cultures (OR 4.24, CI 1.87-9.62, p = 0.0006). After excluding COVID-positive patients (n = 14), peak WBC count, fever and positive culture remained independent predictors of mortality. CONCLUSION/CONCLUSIONS:Markers of infection and inflammation are associated with discharge mortality after thrombectomy. Further study is warranted to investigate the causal relationship of these markers with clinical outcome.

BACKGROUND:Post-acute sequelae of COVID-19 (PASC) includes a heterogeneous group of patients with variable symptomatology, who may respond to different therapeutic interventions. Identifying phenotypes of PASC and therapeutic strategies for different subgroups would be a major step forward in management. METHODS:In a prospective cohort study of patients hospitalized with COVID-19, 12-month symptoms and quantitative outcome metrics were collected. Unsupervised hierarchical cluster analyses were performed to identify patients with: (1) similar symptoms lasting ≥4 weeks after acute SARS-CoV-2 infection, and (2) similar therapeutic interventions. Logistic regression analyses were used to evaluate the association of these symptom and therapy clusters with quantitative 12-month outcome metrics (modified Rankin Scale, Barthel Index, NIH NeuroQoL). RESULTS:Among 242 patients, 122 (50%) reported ≥1 PASC symptom (median 3, IQR 1-5) lasting a median of 12-months (range 1-15) post-COVID diagnosis. Cluster analysis generated three symptom groups: Cluster1 had few symptoms (most commonly headache); Cluster2 had many symptoms including high levels of anxiety and depression; and Cluster3 primarily included shortness of breath, headache and cognitive symptoms. Cluster1 received few therapeutic interventions (OR 2.6, 95% CI 1.1-5.9), Cluster2 received several interventions, including antidepressants, anti-anxiety medications and psychological therapy (OR 15.7, 95% CI 4.1-59.7) and Cluster3 primarily received physical and occupational therapy (OR 3.1, 95%CI 1.3-7.1). The most severely affected patients (Symptom Cluster 2) had higher rates of disability (worse modified Rankin scores), worse NeuroQoL measures of anxiety, depression, fatigue and sleep disorder, and a higher number of stressors (all P<0.05). 100% of those who received a treatment strategy that included psychiatric therapies reported symptom improvement, compared to 97% who received primarily physical/occupational therapy, and 83% who received few interventions (P = 0.042). CONCLUSIONS:We identified three clinically relevant PASC symptom-based phenotypes, which received different therapeutic interventions with varying response rates. These data may be helpful in tailoring individual treatment programs.

Encephalopathy, a common condition among patients hospitalized with COVID-19, can be a challenge to manage and negatively affect prognosis. While encephalopathy may present clinically as delirium, subsyndromal delirium, or coma and may be a result of systemic causes such as hypoxia, COVID-19 has also been associated with more prolonged encephalopathy due to less common but nevertheless severe complications, such as inflammation of the brain parenchyma (with or without cerebrovascular involvement), demyelination, or seizures, which may be disproportionate to COVID-19 severity and require specific management. Given the large number of patients hospitalized with severe acute respiratory syndrome coronavirus-2 infection, even these relatively unlikely complications are increasingly recognized and are particularly important because they require specific management. Therefore, the aim of this review is to provide pragmatic guidance on the management of COVID-19 encephalopathy through consensus agreement of the Global COVID-19 Neuro Research Coalition. A systematic literature search of MEDLINE, medRxiv, and bioRxiv was conducted between January 1, 2020, and June 21, 2021, with additional review of references cited within the identified bibliographies. A modified Delphi approach was then undertaken to develop recommendations, along with a parallel approach to score the strength of both the recommendations and the supporting evidence. This review presents analysis of contemporaneous evidence for the definition, epidemiology, and pathophysiology of COVID-19 encephalopathy and practical guidance for clinical assessment, investigation, and both acute and long-term management.