Spinal epidural arteriovenous fistula with nerve root enhancement mimicking myeloradiculitis: a case report.

BACKGROUND: Gadolinium enhancement of spinal nerve roots on magnetic resonance imaging (MRI) has rarely been reported in spinal dural arteriovenous fistula (SDAVF). Nerve root enhancement and cerebrospinal fluid (CSF) pleocytosis can be deceptive and lead to a misdiagnosis of myeloradiculitis. We report a patient who was initially diagnosed with neurosarcoid myeloradiculitis due to spinal nerve root enhancement, mildly inflammatory cerebrospinal fluid, and pulmonary granulomas, who ultimately was found to have an extensive symptomatic SDAVF. CASE PRESENTATION: A 52-year-old woman presented with a longitudinally extensive spinal cord lesion with associated gadolinium enhancement of the cord and cauda equina nerve roots, and mild lymphocytic pleocytosis. Pulmonary lymph node biopsy revealed non-caseating granulomas and neurosarcoid myeloradiculitis was suspected. She had rapid and profound clinical deterioration after a single dose of steroids. Further work-up with spinal angiography revealed a thoracic SDAVF, which was surgically ligated leading to clinical improvement. CONCLUSIONS: This case highlights an unexpected presentation of SDAVF with nerve root enhancement and concurrent pulmonary non-caseating granulomas, leading to an initial misdiagnosis with neurosarcoidosis. Nerve root enhancement has only rarely been described in cases of SDAVF; however, as this case highlights, it is an important consideration in the differential diagnosis of non-inflammatory causes of longitudinally extensive myeloradiculopathy with nerve root enhancement. This point is highly salient due to the importance of avoiding misdiagnosis of SDAVF, as interventions such as steroids or epidural injections used to treat inflammatory or infiltrative mimics may worsen symptoms in SDAVF. We review the presentation, diagnosis, and management of SDAVF as well as a proposed diagnostic approach to differentiating SDAVF from inflammatory myeloradiculitis.

Fluorescein Angiography Findings in Susac Syndrome: A Multicenter Retrospective Case Series.

BACKGROUND: Susac syndrome is a vasculopathy, resulting in the classic triad of branch retinal artery occlusion (BRAO), inner ear ischemia, and brain ischemia. In this retrospective chart review, we characterize fluorescein angiography (FA) findings and other ancillary studies in Susac syndrome, including the appearance of persistent disease activity and the occurrence of new subclinical disease on FA. METHODS: This multicenter, retrospective case series was institutional review board-approved and included patients with the complete triad of Susac syndrome evaluated with FA, contrasted MRI of the brain, and audiometry from 2010 to 2020. The medical records were reviewed for these ancillary tests, along with demographics, symptoms, visual acuity, visual field defects, and findings on fundoscopy. Clinical relapse was defined as any objective evidence of disease activity during the follow-up period after initial induction of clinical quiescence. The main outcome measure was the sensitivity of ancillary testing, including FA, MRI, and audiometry, to detect relapse. RESULTS: Twenty of the 31 (64%) patients had the complete triad of brain, retinal, and vestibulocochlear involvement from Susac syndrome and were included. Median age at diagnosis was 43.5 years (range 21-63), and 14 (70%) were women. Hearing loss occurred in 20 (100%), encephalopathy in 13 (65%), vertigo in 15 (75%), and headaches in 19 (95%) throughout the course of follow-up. Median visual acuity at both onset and final visit was 20/20 in both eyes. Seventeen (85%) had BRAO at baseline, and 10 (50%) experienced subsequent BRAO during follow-up. FA revealed nonspecific leakage from previous arteriolar damage in 20 (100%), including in patients who were otherwise in remission. Of the 11 episodes of disease activity in which all testing modalities were performed, visual field testing/fundoscopy was abnormal in 4 (36.4%), MRI brain in 2 (18.2%), audiogram in 8 (72.7%), and FA in 9 (81.8%). CONCLUSIONS: New leakage on FA is the most sensitive marker of active disease. Persistent leakage represents previous damage, whereas new areas of leakage suggest ongoing disease activity that requires consideration of modifying immunosuppressive therapy.

Clinical Metagenomic Sequencing for Diagnosis of Meningitis and Encephalitis.

BACKGROUND: Metagenomic next-generation sequencing (NGS) of cerebrospinal fluid (CSF) has the potential to identify a broad range of pathogens in a single test. METHODS: In a 1-year, multicenter, prospective study, we investigated the usefulness of metagenomic NGS of CSF for the diagnosis of infectious meningitis and encephalitis in hospitalized patients. All positive tests for pathogens on metagenomic NGS were confirmed by orthogonal laboratory testing. Physician feedback was elicited by teleconferences with a clinical microbial sequencing board and by surveys. Clinical effect was evaluated by retrospective chart review. RESULTS: We enrolled 204 pediatric and adult patients at eight hospitals. Patients were severely ill: 48.5% had been admitted to the intensive care unit, and the 30-day mortality among all study patients was 11.3%. A total of 58 infections of the nervous system were diagnosed in 57 patients (27.9%). Among these 58 infections, metagenomic NGS identified 13 (22%) that were not identified by clinical testing at the source hospital. Among the remaining 45 infections (78%), metagenomic NGS made concurrent diagnoses in 19. Of the 26 infections not identified by metagenomic NGS, 11 were diagnosed by serologic testing only, 7 were diagnosed from tissue samples other than CSF, and 8 were negative on metagenomic NGS owing to low titers of pathogens in CSF. A total of 8 of 13 diagnoses made solely by metagenomic NGS had a likely clinical effect, with 7 of 13 guiding treatment. CONCLUSIONS: Routine microbiologic testing is often insufficient to detect all neuroinvasive pathogens. In this study, metagenomic NGS of CSF obtained from patients with meningitis or encephalitis improved diagnosis of neurologic infections and provided actionable information in some cases. (Funded by the National Institutes of Health and others; PDAID ClinicalTrials.gov number, NCT02910037.).

COVID-19 severity and age increase the odds of delirium in hospitalized adults with confirmed SARS-CoV-2 infection: a cohort study.

BACKGROUND: Despite recognition of the neurologic and psychiatric complications associated with SARS-CoV-2 infection, the relationship between coronavirus disease 19 (COVID-19) severity on hospital admission and delirium in hospitalized patients is poorly understood. This study sought to measure the association between COVID-19 severity and presence of delirium in both intensive care unit (ICU) and acute care patients by leveraging an existing hospital-wide systematic delirium screening protocol. The secondary analyses included measuring the association between age and presence of delirium, as well as the association between delirium and safety attendant use, restraint use, discharge home, and length of stay. METHODS: In this single center retrospective cohort study, we obtained electronic medical record (EMR) data using the institutional Epic Clarity database to identify all adults diagnosed with COVID-19 and hospitalized for at least 48-h from February 1-July 15, 2020. COVID-19 severity was classified into four groups. These EMR data include twice-daily delirium screenings of all patients using the Nursing Delirium Screening Scale (non-ICU) or CAM-ICU (ICU) per existing hospital-wide protocols. RESULTS: A total of 99 patients were diagnosed with COVID-19, of whom 44 patients required ICU care and 17 met criteria for severe disease within 24-h of admission. Forty-three patients (43%) met criteria for delirium at any point in their hospitalization. Of patients with delirium, 24 (56%) were 65 years old or younger. After adjustment, patients meeting criteria for the two highest COVID-19 severity groups within 24-h of admission had 7.2 times the odds of having delirium compared to those in the lowest category [adjusted odds ratio (aOR) 7.2; 95% confidence interval (CI) 1.9, 27.4; P = 0.003]. Patients > 65 years old had increased odds of delirium compared to those < 45 years old (aOR 8.7; 95% CI 2.2, 33.5; P = 0.003). Delirium was associated with increased odds of safety attendant use (aOR 4.5; 95% CI 1.0, 20.7; P = 0.050), decreased odds of discharge home (aOR 0.2; 95% CI 0.06, 0.6; P = 0.005), and increased length of stay (aOR 7.5; 95% CI 2.0, 13; P = 0.008). CONCLUSIONS: While delirium is common in hospitalized patients of all ages with COVID-19, it is especially common in those with severe disease on hospital admission and those who are older. Patients with COVID-19 and delirium, compared to COVID-19 without delirium, are more likely to require safety attendants during hospitalization, less likely to be discharged home, and have a longer length of stay. Individuals with COVID-19, including younger patients, represent an important population to target for delirium screening and management as delirium is associated with important differences in both clinical care and disposition.

Postoperative delirium prediction using machine learning models and preoperative electronic health record data.

BACKGROUND: Accurate, pragmatic risk stratification for postoperative delirium (POD) is necessary to target preventative resources toward high-risk patients. Machine learning (ML) offers a novel approach to leveraging electronic health record (EHR) data for POD prediction. We sought to develop and internally validate a ML-derived POD risk prediction model using preoperative risk features, and to compare its performance to models developed with traditional logistic regression. METHODS: This was a retrospective analysis of preoperative EHR data from 24,885 adults undergoing a procedure requiring anesthesia care, recovering in the main post-anesthesia care unit, and staying in the hospital at least overnight between December 2016 and December 2019 at either of two hospitals in a tertiary care health system. One hundred fifteen preoperative risk features including demographics, comorbidities, nursing assessments, surgery type, and other preoperative EHR data were used to predict postoperative delirium (POD), defined as any instance of Nursing Delirium Screening Scale ≥2 or positive Confusion Assessment Method for the Intensive Care Unit within the first 7 postoperative days. Two ML models (Neural Network and XGBoost), two traditional logistic regression models ("clinician-guided" and "ML hybrid"), and a previously described delirium risk stratification tool (AWOL-S) were evaluated using the area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, positive likelihood ratio, and positive predictive value. Model calibration was assessed with a calibration curve. Patients with no POD assessments charted or at least 20% of input variables missing were excluded. RESULTS: POD incidence was 5.3%. The AUC-ROC for Neural Net was 0.841 [95% CI 0. 816-0.863] and for XGBoost was 0.851 [95% CI 0.827-0.874], which was significantly better than the clinician-guided (AUC-ROC 0.763 [0.734-0.793], p < 0.001) and ML hybrid (AUC-ROC 0.824 [0.800-0.849], p < 0.001) regression models and AWOL-S (AUC-ROC 0.762 [95% CI 0.713-0.812], p < 0.001). Neural Net, XGBoost, and ML hybrid models demonstrated excellent calibration, while calibration of the clinician-guided and AWOL-S models was moderate; they tended to overestimate delirium risk in those already at highest risk. CONCLUSION: Using pragmatically collected EHR data, two ML models predicted POD in a broad perioperative population with high discrimination. Optimal application of the models would provide automated, real-time delirium risk stratification to improve perioperative management of surgical patients at risk for POD.

The association of post-operative delirium with patient-reported outcomes and mortality after lung transplantation.

Post-operative delirium after lung transplantation is common. Its associations with health-related quality of life (HRQL), depression, and mortality remains unknown. In 236 lung transplant recipients, HRQL and depressive symptoms were assessed as part of a structured survey battery before and after transplantation. Surveys included the Geriatric Depressive Scale (GDS) and Short Form 12 (SF12). Delirium was assessed throughout the post-operative intensive care unit (ICU) stay with Confusion Assessment Method for ICU. Delirium and mortality data were extracted from electronic medical records. We examined associations between delirium and changes in depressive symptoms and HRQL using linear mixed effects models and association between delirium and mortality with Cox-proportional hazard models. Post-operative delirium occurred in 34 participants (14%). Delirium was associated with attenuated improvements in SF12-PCS (difference ₋4.0; 95%CI: -7.4, -0.7) but not SF12-MCS (difference 2.2; 95%CI: -0.7,5.7) or GDS (difference ₋0.4; 95%CI: -1.5,0.7). Thirty-two participants died during the study period. Delirium was associated with increased adjusted hazard risk of mortality (HR 17.9, 95%CI: 4.4,72.5). Delirium after lung transplantation identifies a group at increased risk for poorer HRQL and death within the first post-operative year. Further studies should investigate potential causal links between delirium, and poorer HRQL and mortality risk after lung transplantation.

Derivation, Validation, Sustained Performance, and Clinical Impact of an Electronic Medical Record-Based Perioperative Delirium Risk Stratification Tool.

BACKGROUND: Postoperative delirium is an important problem for surgical inpatients and was the target of a multidisciplinary quality improvement project at our institution. We developed and tested a semiautomated delirium risk stratification instrument, Age, WORLD backwards, Orientation, iLlness severity, Surgery-specific risk (AWOL-S), in 3 independent cohorts from our tertiary care hospital and describe its performance characteristics and impact on clinical care. METHODS: The risk stratification instrument was derived with elective surgical patients who were admitted at least overnight and received at least 1 postoperative delirium screen (Nursing Delirium Screening Scale [NuDESC] or Confusion Assessment Method for the Intensive Care Unit [CAM-ICU]) and preoperative cognitive screening tests (orientation to place and ability to spell WORLD backward). Using data pragmatically collected between December 7, 2016, and June 15, 2017, we derived a logistic regression model predicting probability of delirium in the first 7 postoperative hospital days. A priori predictors included age, cognitive screening, illness severity or American Society of Anesthesiologists physical status, and surgical delirium risk. We applied model odds ratios to 2 subsequent cohorts ("validation" and "sustained performance") and assessed performance using area under the receiver operator characteristic curves (AUC-ROC). A post hoc sensitivity analysis assessed performance in emergency and preadmitted patients. Finally, we retrospectively evaluated the use of benzodiazepines and anticholinergic medications in patients who screened at high risk for delirium. RESULTS: The logistic regression model used to derive odds ratios for the risk prediction tool included 2091 patients. Model AUC-ROC was 0.71 (0.67-0.75), compared with 0.65 (0.58-0.72) in the validation (n = 908) and 0.75 (0.71-0.78) in the sustained performance (n = 3168) cohorts. Sensitivity was approximately 75% in the derivation and sustained performance cohorts; specificity was approximately 59%. The AUC-ROC for emergency and preadmitted patients was 0.71 (0.67-0.75; n = 1301). After AWOL-S was implemented clinically, patients at high risk for delirium (n = 3630) had 21% (3%-36%) lower relative risk of receiving an anticholinergic medication perioperatively after controlling for secular trends. CONCLUSIONS: The AWOL-S delirium risk stratification tool has moderate accuracy for delirium prediction in a cohort of elective surgical patients, and performance is largely unchanged in emergent/preadmitted surgical patients. Using AWOL-S risk stratification as a part of a multidisciplinary delirium reduction intervention was associated with significantly lower rates of perioperative anticholinergic but not benzodiazepine, medications in those at high risk for delirium. AWOL-S offers a feasible starting point for electronic medical record-based postoperative delirium risk stratification and may serve as a useful paradigm for other institutions.

An Implementation-Effectiveness Study of a Perioperative Delirium Prevention Initiative for Older Adults.

BACKGROUND: Postoperative delirium is a common and serious problem for older adults. To better align local practices with delirium prevention consensus guidelines, we implemented a 5-component intervention followed by a quality improvement (QI) project at our institution. METHODS: This hybrid implementation-effectiveness study took place at 2 adult hospitals within a tertiary care academic health care system. We implemented a 5-component intervention: preoperative delirium risk stratification, multidisciplinary education, written memory aids, delirium prevention postanesthesia care unit (PACU) orderset, and electronic health record enhancements between December 1, 2017 and June 30, 2018. This was followed by a department-wide QI project to increase uptake of the intervention from July 1, 2018 to June 30, 2019. We tracked process outcomes during the QI period, including frequency of preoperative delirium risk screening, percentage of "high-risk" screens, and frequency of appropriate PACU orderset use. We measured practice change after the interventions using interrupted time series analysis of perioperative medication prescribing practices during baseline (December 1, 2016 to November 30, 2017), intervention (December 1, 2017 to June 30, 2018), and QI (July 1, 2018 to June 30, 2019) periods. Participants were consecutive older patients (≥65 years of age) who underwent surgery during the above timeframes and received care in the PACU, compared to a concurrent control group <65 years of age. The a priori primary outcome was a composite of perioperative American Geriatrics Society Beers Criteria for Potentially Inappropriate Medication Use (Beers PIM) medications. The secondary outcome, delirium incidence, was measured in the subset of older patients who were admitted to the hospital for at least 1 night. RESULTS: During the 12-month QI period, preoperative delirium risk stratification improved from 67% (714 of 1068 patients) in month 1 to 83% in month 12 (776 of 931 patients). Forty percent of patients were stratified as "high risk" during the 12-month period (4246 of 10,494 patients). Appropriate PACU orderset use in high-risk patients increased from 19% in month 1 to 85% in month 12. We analyzed medication use in 7212, 4416, and 8311 PACU care episodes during the baseline, intervention, and QI periods, respectively. Beers PIM administration decreased from 33% to 27% to 23% during the 3 time periods, with adjusted odds ratio (aOR) 0.97 (95% confidence interval [CI], 0.95-0.998; P = .03) per month during the QI period in comparison to baseline. Delirium incidence was 7.5%, 9.2%, and 8.5% during the 3 time periods with aOR of delirium of 0.98 (95% CI, 0.91-1.05, P = .52) per month during the QI period in comparison to baseline. CONCLUSIONS: A perioperative delirium prevention intervention was associated with reduced administration of Beers PIMs to older adults.

Whole-Genome mRNA Gene Expression Differs Between Patients With and Without Delirium.

OBJECTIVE: To identify differences in gene expression between patients with in-hospital delirium from a known etiology (urinary tract infection [UTI]) and patients with delirium from an unknown etiology, as well as from nondelirious patients. METHODS: Thirty patients with delirium (8 with UTI) and 21 nondelirious patients (11 with UTI) were included in this prospective case-control study. Transcriptomic profiles from messenger RNA sequencing of peripheral blood were analyzed for gene expression and disease-specific pathway enrichment patterns, correcting for systemic inflammatory response syndrome. Genes and pathways with significant differential activity based on Fisher exact test ( P < .05, |Z score| >2) are reported. RESULTS: Patients with delirium with UTI, compared to patients with delirium without UTI, exhibited significant activation of interferon signaling, upstream cytokines, and transcription regulators, as well as significant inhibition of actin cytoskeleton, integrin, paxillin, glioma invasiveness signaling, and upstream growth factors. All patients with delirium, compared to nondelirious patients, had significant complement system activation. Among patients with delirium without UTI, compared to nondelirious patients without UTI, there was significant activation of elF4 and p7056 K signaling. CONCLUSIONS: Differences exist in gene expression between delirious patients due to UTI presence, as well as due to the presence of delirium alone. Transcriptional profiling may help develop etiology-specific biomarkers for patients with delirium.

Evaluation of a multicomponent pathway to address inpatient delirium on a neurosciences ward.

BACKGROUND: Delirium is a frequent and detrimental complication of inpatient hospitalization. Multicomponent intervention in selected groups has been shown to prevent and treat delirium, though little data exists on the effect of intervention in neurological patients. We studied the efficacy of a multicomponent delirium care pathway implemented on a largely neurology and neurosurgery hospital ward among unselected patients. METHODS: We incorporated a multicomponent delirium care pathway into the workflow of a university hospital for patients older than 50 years. The pathway involved risk-stratification for development of delirium, delirium screening, and non-pharmacologic behavioral prevention and intervention. We then retrospectively reviewed admissions before and after implementation of the care pathway. Our primary endpoint was incidence of delirium; secondary endpoints included delirium days, length of stay, restraint use, readmission rates, and discharge disposition. RESULTS: Seven hundred ninety eight admissions from before the delirium care pathway went into effect and 797 admissions from afterwards were reviewed. Baseline characteristics between groups were similar. Delirium incidence between the two groups did not change (7.0% before vs 7.2% after, p = 0.89). Length of stay among delirious patients significantly decreased after implementation of the delirium care pathway (9.60 before vs 7.06 after, ß = - 0.16, adjusted p-value = 0.001). CONCLUSION: Implementation of a delirium care pathway on a neurosciences ward was not associated with changes in the rate of delirium development, though length of stay among delirious patients decreased. In a largely neurologic population, multicomponent intervention to prevent and treat delirium may not change delirium incidence, but may be effective in mitigating delirium complications.

Validation of a Nurse-Based Delirium-Screening Tool for Hospitalized Patients.

BACKGROUND: Guidelines recommend daily delirium monitoring of hospitalized patients. Available delirium-screening tools have not been validated for use by nurses among diverse inpatients. OBJECTIVE: We sought to validate the Nursing Delirium-Screening Scale (Nu-DESC) under these circumstances. METHODS: A blinded cross-sectional and quality-improvement study was conducted from August 2015-February 2016. Nurses׳ Nu-DESC scores were compared to delirium diagnosis according to Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) criteria. A total of 405 consecutive hospitalized patients were included. Nu-DESC-positive (threshold score ≥2) patients were matched with equal numbers of Nu-DESC-negative patients, by sex, age, and nursing unit. Nurses recorded a Nu-DESC score for each patient on every 12-hour shift. A Nu-DESC-blinded evaluator interviewed patients for 2 consecutive days. Delirium diagnosis was determined by physicians using DSM-5 criteria applied to collected research data. Sensitivity and specificity of the Nu-DESC were calculated. In an exploratory analysis, the performance of the Nu-DESC was analyzed with the addition of bedside measures of attention. RESULTS: The sensitivity of the Nu-DESC at a threshold of ≥2 was 42% (95% CI: 33-53%). Specificity was 98% (97-98%). At a threshold of ≥1, sensitivity was 67% (52-80%) and specificity 93% (90-95%). Similar results were found with the addition of attention tasks. CONCLUSION: The Nu-DESC is a specific delirium detection tool, but it is not sensitive at the usually proposed cut point of ≥2. Using a threshold of ≥1 or adding a test of attention increase sensitivity with a minor decrease in specificity.

Predicting inpatient delirium: The AWOL delirium risk-stratification score in clinical practice.

Inpatient delirium improves with multicomponent interventions by hospital staff, though the resources needed are often limited. Risk-stratification to predict delirium is a useful first step to help triage resources, but the performance of risk-stratification as part of a functioning multicomponent pathway has not been assessed. We retrospectively studied the performance of a validated delirium prediction rule, the AWOL score, as a part of a multicomponent delirium care pathway in practice on a university hospital ward. We reviewed the hospitalizations of patients 50 years or older for evidence of delirium and extracted the AWOL score from nursing documentation (n = 347). The area under the receiver operating characteristic curve (AUC) was 0.83 (95% CI 0.77-0.89) for all cases and 0.73 (95% CI 0.60-0.85) when cases of prevalent delirium were removed. Involving minimal additional assessment, this nursing-based risk stratification score performed well as part of a multicomponent delirium care pathway.

Baylisascaris procyonis-Associated Meningoencephalitis in a Previously Healthy Adult, California, USA.

After severe neurocognitive decline developed in an otherwise healthy 63-year-old man, brain magnetic resonance imaging showed eosinophilic meningoencephalitis and enhancing lesions. The patient tested positive for antibodies to Baylisascaris spp. roundworms, was treated with albendazole and dexamethasone, and showed improvement after 3 months. Baylisascariasis should be considered for all patients with eosinophilic meningitis.

CXCL13 plus interleukin 10 is highly specific for the diagnosis of CNS lymphoma.

Establishing the diagnosis of focal brain lesions in patients with unexplained neurologic symptoms represents a challenge. The goal of this study is to provide evidence supporting functional roles for CXC chemokine ligand (CXCL)13 and interleukin (IL)-10 in central nervous system (CNS) lymphomas and to evaluate the utility of each as prognostic and diagnostic biomarkers. We demonstrate for the first time that elevated CXCL13 concentration in cerebrospinal fluid (CSF) is prognostic and that CXCL13 and CXCL12 mediate chemotaxis of lymphoma cells isolated from CNS lymphoma lesions. Expression of the activated form of Janus kinase 1 supported a role for IL-10 in prosurvival signaling. We determined the concentration of CXCL13 and IL-10 in CSF of CNS lymphoma patients and control cohorts including inflammatory and degenerative neurologic disease in a multicenter study involving 220 patients. Bivariate elevated CXCL13 plus IL-10 was 99.3% specific for primary and secondary CNS lymphoma, with sensitivity significantly greater than reference standard CSF tests. These results identify CXCL13 and IL-10 as potentially important biomarkers of CNS lymphoma that merit further evaluation and support incorporation of CXCL13 and IL-10 into diagnostic algorithms for the workup of focal brain lesions in which lymphoma is a consideration.

Moving Beyond Metabolic Encephalopathy: An Update on Delirium Prevention, Workup, and Management.

Delirium is a condition that frequently complicates hospitalization and consists of an acute decline in orientation and attention, often accompanied by other cognitive changes. Delirium is tied to multiple detrimental outcomes both in the short and long term, including cognitive and functional decline, inpatient complications, and mortality. Postoperative, elderly medical, and critical care patients have been identified as populations at particular risk. In this review, the authors discuss current theories on pathophysiology, recommended workup, and evidence-based prevention and management of inpatient delirium. In general, instituting a system of active screening of at-risk populations and nonpharmacologic interventions for prevention and treatment seems to be the most effective method of addressing delirium. More research is needed to clarify the etiology of delirium and develop safe therapeutic options that address the underlying pathophysiology.

A Prospective Comparison of Informant-based and Performance-based Dementia Screening Tools to Predict In-Hospital Delirium.

Dementia is an important risk factor for delirium, but the optimal strategy for incorporating cognitive impairment into delirium risk assessment at the time of hospital admission is unknown. We compared 2 informant-based screening tools for dementia and mild cognitive impairment [AD8 and D=(MC)] to the Mini Mental State Examination (MMSE) and Mini-cog in predicting hospital-acquired delirium. This prospective cohort study at an academic medical center consisted of 162 medical inpatients over age 50 years without delirium upon admission. Each participant was evaluated using the MMSE, Mini-cog, AD8, and D=(MC) upon admission and was assessed daily for delirium. An MMSE≤24 carried a 5.5 [95% confidence intervals (CI), 2.7-11.1] relative risk for delirium, whereas cognitive impairment detected by the Mini-cog, D=(MC), or AD8 carried a 2-fold risk. Adding the D=(MC) to the MMSE increased the sensitivity for predicting delirium from 52% (range, 32% to 73%) for the MMSE alone to 65% (range, 46% to 85%) if either test was positive. If both were positive, specificity was maximized at 97% (range, 94% to 100%), but sensitivity was 17% (range, 2% to 33%). The MMSE and Mini-cog identify a large proportion of patients at risk for hospital-acquired delirium, but the combination of performance-based and an informant-based screens may maximize specificity and sensitivity.

Adult-onset central nervous system hemophagocytic lymphohistiocytosis: a case report.

BACKGROUND: Hemophagocytic lymphohistiocytosis (HLH) is a clinical syndrome with both genetic and acquired causes characterized by elevated cytokine levels, hyperinflammation, and overactivation of lymphocytes and macrophages. It is typically a systemic disease with variable degrees of CNS involvement. Cases with predominantly central nervous system (CNS) involvement are very rare, with the vast majority of these occurring in infants and young children. This report documents a case of adult-onset CNS-HLH involving a middle-aged man. CASE PRESENTATION: A 55 year-old man developed progressive left hemiparesis and aphasia over the course of several months. Brain MRI showed multifocal, mass-like enhancing lesions with increased susceptibility consistent with blood products. An extensive workup for infectious, autoimmune, and neoplastic etiologies was significant only for a markedly elevated serum ferritin at 1456 ng/mL. Two brain biopsies showed a non-specific inflammatory process. The patient was treated empirically with steroids and plasmapheresis, but he continued to suffer a progressive neurological decline and died one year after onset of neurological symptoms. Autopsy revealed profound histiocytic infiltration, perivascular lymphocytosis, and emperipolesis, compatible with CNS-HLH. CONCLUSION: This case report describes an exceedingly rare presentation of an adult patient with CNS predominant HLH. This diagnosis should be considered in the differential diagnosis of adults presenting with progressive brain lesions, even in the absence of typical systemic signs of HLH.

Transcobalamin receptor antibodies in autoimmune vitamin B12 central deficiency.

Vitamin B12 is critical for hematopoiesis and myelination. Deficiency can cause neurologic deficits including loss of coordination and cognitive decline. However, diagnosis relies on measurement of vitamin B12 in the blood, which may not accurately reflect the concentration in the brain. Using programmable phage display, we identified an autoantibody targeting the transcobalamin receptor (CD320) in a patient with progressive tremor, ataxia, and scanning speech. Anti-CD320 impaired cellular uptake of cobalamin (B12) in vitro by depleting its target from the cell surface. Despite a normal serum concentration, B12 was nearly undetectable in her cerebrospinal fluid (CSF). Immunosuppressive treatment and high-dose systemic B12 supplementation were associated with increased B12 in the CSF and clinical improvement. Optofluidic screening enabled isolation of a patient-derived monoclonal antibody that impaired B12 transport across an in vitro model of the blood-brain barrier (BBB). Autoantibodies targeting the same epitope of CD320 were identified in seven other patients with neurologic deficits of unknown etiology, 6% of healthy controls, and 21.4% of a cohort of patients with neuropsychiatric lupus. In 132 paired serum and CSF samples, detection of anti-CD320 in the blood predicted B12 deficiency in the brain. However, these individuals did not display any hematologic signs of B12 deficiency despite systemic CD320 impairment. Using a genome-wide CRISPR screen, we found that the low-density lipoprotein receptor serves as an alternative B12 uptake pathway in hematopoietic cells. These findings dissect the tissue specificity of B12 transport and elucidate an autoimmune neurologic condition that may be amenable to immunomodulatory treatment and nutritional supplementation.

Diagnostic yield of electroencephalography in the medical and surgical intensive care unit.

BACKGROUND: To determine the incidence of electrographic seizures during continuous electroencephalography (cEEG) in the medical and surgical ICU. METHODS: We retrospectively reviewed the records of all adults who underwent cEEG in our medical and surgical ICU over a 4.5 year period. Patients with acute brain injury were excluded. Our primary outcome was cEEG documentation of an electrographic seizure, defined as a rhythmic discharge or spike and wave pattern demonstrating definite evolution and lasting at least 10 s. To assess inter-rater variability in cEEG interpretation, two electrophysiologists independently reviewed all available cEEGs of subjects with electrographic seizures documented on their clinical cEEG report and those of an equal number of randomly selected subjects from the remaining cohort. RESULTS: Kappa analysis showed a value of 0.88, indicating excellent inter-rater agreement. Electrographic seizures were identified in 12 of 105 patients (11 %, 95 % CI 5-18 %). This rate did not change after excluding patients with a history of seizure, remote brain injury, or seizure-like events before cEEG. In an ordinal logistic regression model controlling for age, sex, and SOFA score, electrographic seizures were associated with lower odds of good outcomes on the Glasgow Outcome Scale at discharge (OR 0.3, 95 % CI 0.1-0.8). CONCLUSION: In a tertiary care medical and surgical ICU, electrographic seizures were seen on 11 % of cEEGs ordered for the evaluation of encephalopathy, and were associated with worse functional outcomes at discharge. Our findings confirm the results of a prior study suggesting a substantial burden of electrographic seizures in critically ill encephalopathic patients.