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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.

BackgroundDespite 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.MethodsIn 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.ResultsA 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

BackgroundAccurate, 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.MethodsThis 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.ResultsPOD 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

Despite the association between cognitive impairment and delirium, little is known about whether genetic differences that confer cognitive resilience also confer resistance to delirium. To investigate whether older adults without postoperative delirium, compared with those with postoperative delirium, are more likely to have specific single nucleotide polymorphisms (SNPs) in the FKBP5, KIBRA, KLOTHO, MTNR1B, and SIRT1 genes known to be associated with cognition or delirium. This prospective nested matched exploratory case-control study included 94 older adults who underwent orthopedic surgery and screened for postoperative delirium. Forty-seven subjects had incident delirium, and 47 age-matched controls were not delirious. The primary study outcome was genotype frequency for the five SNPs. Compared with participants with delirium, those without delirium had higher adjusted odds of KIBRA SNP rs17070145 CT/TT [vs. CC; adjusted odds ratio (aOR) 2.80, 95% confidence interval (CI) 1.03, 7.54; p = 0.04] and MTNR1B SNP rs10830963 CG/GG (vs. CC; aOR 4.14, 95% CI 1.36, 12.59; p = 0.01). FKBP5 SNP rs1360780 CT/TT (vs. CC) demonstrated borderline increased adjusted odds of not developing delirium (aOR 2.51, 95% CI 1.00, 7.34; p = 0.05). Our results highlight the relevance of KIBRA, MTNR1B, and FKBP5 in understanding the complex relationship between delirium, cognition, and sleep, which warrant further study in larger, more diverse populations.

ImportanceCerebrospinal fluid (CSF) cytologic testing and flow cytometry are insensitive for diagnosing neoplasms of the central nervous system (CNS). Such clinical phenotypes can mimic infectious and autoimmune causes of meningoencephalitis.ObjectiveTo ascertain whether CSF metagenomic next-generation sequencing (mNGS) can identify aneuploidy, a hallmark of malignant neoplasms, in difficult-to-diagnose cases of CNS malignant neoplasm.Design, setting, and participantsTwo case-control studies were performed at the University of California, San Francisco (UCSF). The first study used CSF specimens collected at the UCSF Clinical Laboratories between July 1, 2017, and December 31, 2019, and evaluated test performance in specimens from patients with a CNS malignant neoplasm (positive controls) or without (negative controls). The results were compared with those from CSF cytologic testing and/or flow cytometry. The second study evaluated patients who were enrolled in an ongoing prospective study between April 1, 2014, and July 31, 2019, with presentations that were suggestive of neuroinflammatory disease but who were ultimately diagnosed with a CNS malignant neoplasm. Cases of individuals whose tumors could have been detected earlier without additional invasive testing are discussed.Main outcomes and measuresThe primary outcome measures were the sensitivity and specificity of aneuploidy detection by CSF mNGS. Secondary subset analyses included a comparison of CSF and tumor tissue chromosomal abnormalities and the identification of neuroimaging characteristics that were associated with test performance.ResultsAcross both studies, 130 participants were included (median [interquartile range] age, 57.5 [43.3-68.0] years; 72 men [55.4%]). The test performance study used 125 residual laboratory CSF specimens from 47 patients with a CNS malignant neoplasm and 56 patients with other neurological diseases. The neuroinflammatory disease study enrolled 12 patients and 17 matched control participants. The sensitivity of the CSF mNGS assay was 75% (95% CI, 63%-85%), and the specificity was 100% (95% CI, 96%-100%). Aneuploidy was detected in 64% (95% CI, 41%-83%) of the patients in the test performance study with nondiagnostic cytologic testing and/or flow cytometry, and in 55% (95% CI, 23%-83%) of patients in the neuroinflammatory disease study who were ultimately diagnosed with a CNS malignant neoplasm. Of the patients in whom aneuploidy was detected, 38 (90.5%) had multiple copy number variations with tumor fractions ranging from 31% to 49%.Conclusions and relevanceThis case-control study showed that CSF mNGS, which has low specimen volume requirements, does not require the preservation of cell integrity, and was orginally developed to diagnose neurologic infections, can also detect genetic evidence of a CNS malignant neoplasm in patients in whom CSF cytologic testing and/or flow cytometry yielded negative results with a low risk of false-positive results.

BackgroundDelirium is associated with poor clinical outcomes that could be improved with targeted interventions.ObjectiveTo determine whether a multicomponent delirium care pathway implemented across seven specialty nonintensive care units is associated with reduced hospital length of stay (LOS). Secondary objectives were reductions in total direct cost, odds of 30-day hospital readmission, and rates of safety attendant and restraint use.MethodsThis retrospective cohort study included 22,708 hospitalized patients (11,018 preintervention) aged ≥50 years encompassing seven nonintensive care units: neurosciences, medicine, cardiology, general and specialty surgery, hematology-oncology, and transplant. The multicomponent delirium care pathway included a nurse-administered delirium risk assessment at admission, nurse-administered delirium screening scale every shift, and a multicomponent delirium intervention. The primary study outcome was LOS for all units combined and the medicine unit separately. Secondary outcomes included total direct cost, odds of 30-day hospital readmission, and rates of safety attendant and restraint use.ResultsAdjusted mean LOS for all units combined decreased by 2% post intervention (proportional change, 0.98; 95% CI, 0.96-0.99; P = .0087). Medicine unit adjusted LOS decreased by 9% (proportional change, 0.91; 95% CI, 0.83-0.99; P = .028). For all units combined, adjusted odds of 30-day readmission decreased by 14% (odds ratio [OR], 0.86; 95% CI, 0.80-0.93; P = .0002). Medicine unit adjusted cost decreased by 7% (proportional change, 0.93; 95% CI, 0.89-0.96; P = .0002).ConclusionThis multicomponent hospital-wide delirium care pathway intervention is associated with reduced hospital LOS, especially for patients on the medicine unit. Odds of 30-day readmission decreased throughout the entire cohort.

BackgroundPostoperative 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.MethodsThis 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

BackgroundPostoperative 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.MethodsThis 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

OBJECTIVE:To identify molecular correlates of primary angiitis of the CNS (PACNS) through proteomic analysis of CSF from a biopsy-proven patient cohort. METHODS:Using mass spectrometry, we quantitatively compared the CSF proteome of patients with biopsy-proven PACNS (n = 8) to CSF from individuals with noninflammatory conditions (n = 11). Significantly enriched molecular pathways were identified with a gene ontology workflow, and high confidence hits within enriched pathways (fold change >1.5 and concordant Benjamini-Hochberg-adjusted p < 0.05 on DeSeq and t test) were identified as differentially regulated proteins. RESULTS:Compared to noninflammatory controls, 283 proteins were differentially expressed in the CSF of patients with PACNS, with significant enrichment of the complement cascade pathway (C4-binding protein, CD55, CD59, properdin, complement C5, complement C8, and complement C9) and neural cell adhesion molecules. A subset of clinically relevant findings were validated by Western blot and commercial ELISA. CONCLUSIONS:In this exploratory study, we found evidence of deregulation of the alternative complement cascade in CSF from biopsy-proven PACNS compared to noninflammatory controls. More specifically, several regulators of the C3 and C5 convertases and components of the terminal cascade were significantly altered. These preliminary findings shed light on a previously unappreciated similarity between PACNS and systemic vasculitides, especially anti-neutrophil cytoplasmic antibody-associated vasculitis. The therapeutic implications of this common biology and the diagnostic and therapeutic utility of individual proteomic findings warrant validation in larger cohorts.

ObjectiveTo characterize the most common neurologic diagnoses leading to hospitalization for homeless compared to housed individuals and to assess whether homelessness is an independent risk factor for 30-day readmission after an admission for a neurologic illness.MethodsWe performed a retrospective serial cross-sectional study using data from the Healthcare Cost and Utilization Project California State Inpatient Database from 2006 to 2011. Adult patients with a primary neurologic discharge diagnosis were included. The primary outcome was 30-day readmission. We used multilevel logistic regression to examine the association between homelessness and readmission after adjustment for patient factors.ResultsWe identified 1,082,347 patients with a neurologic primary diagnosis. The rate of homelessness was 0.37%. The most common indications for hospitalization among homeless patients were seizure and traumatic brain injury, both of which were more common in the homeless compared to housed population (19.3% vs 8.1% and 31.9% vs 9.2%, respectively, p < 0.001). A multilevel mixed-effects model controlling for patient age, sex, race, insurance type, comorbid conditions, and clustering on the hospital level found that homelessness was associated with increased 30-day readmission (odds ratio 1.5, 95% confidence interval 1.4-1.6, p < 0.001). This association persisted after this analysis was repeated within specific diagnoses (patients with epilepsy, trauma, encephalopathy, and neuromuscular disease).ConclusionThe most common neurologic reasons for admission among homeless patients are seizure and traumatic brain injury; these patients are at high risk for readmission. Future interventions should target the drivers of readmissions in this vulnerable population.

BackgroundStudies of emergent neuroimaging in the management of patients presenting with a breakthrough seizure are lacking. We sought to determine how often emergent computed tomography (CT) scans are obtained in patients with known epilepsy presenting with a seizure and how often acute abnormalities are found.MethodsThis multicenter retrospective cohort study was performed in the emergency department at 2 academic medical centers. The primary outcomes were percentage of visits where a CT scan was obtained, whether CT findings represented acute abnormalities, and whether these findings changed acute management.ResultsOf the 396 visits included, CT scans were obtained in 39%, and 8% of these scans demonstrated acute abnormalities. Patients who were older, had status epilepticus, a brain tumor, head trauma, or an abnormal examination were all significantly more likely to undergo acute neuroimaging (P < .05). In the multivariable model, only history of brain tumor (odds ratio [OR] 5.88, 95% confidence interval [CI], 1.33-26.1) and head trauma as a result of seizure (OR 3.92, 95% CI, 1.01-15.2) reached statistical significance in predicting an acutely abnormal scan. The likelihood of an acute imaging abnormality in visits for patients without a history of brain tumor or head trauma as a result of the seizure was 2.7% (2 visits). Both of these patients had abnormal neurological examinations.ConclusionObtaining an emergent CT scan for patients with epilepsy presenting with a seizure may be avoidable in most cases, but might be indicated for patients with a history of brain tumor or head trauma as a result of seizure.

BACKGROUND:Delirium affects more than seven million hospitalized adults in the United States annually. However, its impact on postdischarge healthcare utilization remains unclear. OBJECTIVE:To determine the association between delirium and 30-day hospital readmission. DESIGN:A retrospective cohort study. SETTING:A general community medical and surgical hospital. PATIENTS:All adults who were at least 65 years old, without a history of delirium or alcohol-related delirium, and were hospitalized from September 2010 to March 2015. MEASUREMENTS:The patients deemed at risk for or displaying symptoms of delirium were screened by nurses using the Confusion Assessment Method with a followup by a staff psychiatrist for a subset of screen-positive patients. Patients with delirium confirmed by a staff psychiatrist were compared with those without delirium. The primary outcome was the 30-day readmission rate. The secondary outcomes included emergency department (ED) visits 30 days postdischarge, mortality during hospitalization and 30 days postdischarge, and discharge location. RESULTS:The cohort included 718 delirious patients and 7,927 nondelirious patients. Using an unweighted multivariable logistic regression, delirium was determined to be significantly associated with the increased odds of readmission within 30 days of discharge (odds ratio (OR): 2.60; 95% CI, 1.96-3.44; P < .0001). Delirium was also significantly (P < .0001) associated with ED visits within 30 days postdischarge (OR: 2.18; 95% CI: 1.77-2.69) and discharge to a facility (OR: 2.52; 95% CI: 2.09-3.01). CONCLUSIONS:Delirium is a significant predictor of hospital readmission, ED visits, and discharge to a location other than home. Delirious patients should be targeted to reduce postdischarge healthcare utilization.

BackgroundDelirium 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.MethodsWe 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.ResultsSeven 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, β = - 0.16, adjusted p-value = 0.001).ConclusionImplementation 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.

BackgroundDelirium 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.MethodsWe 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.ResultsSeven 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, β = - 0.16, adjusted p-value = 0.001).ConclusionImplementation 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.

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.

Central nervous system (CNS) lymphoma can present a diagnostic challenge. Currently, there is no consensus regarding what presurgical evaluation is warranted or how to proceed when lesions are not surgically accessible. We conducted a review of the literature on CNS lymphoma diagnosis (1966 to October 2011) to determine whether a common diagnostic algorithm can be generated. We extracted data regarding the usefulness of brain and body imaging, serum and cerebrospinal fluid (CSF) studies, ophthalmologic examination, and tissue biopsy in the diagnosis of CNS lymphoma. Contrast enhancement on imaging is highly sensitive at the time of diagnosis: 98.9% in immunocompetent lymphoma and 96.1% in human immunodeficiency virus-related CNS lymphoma. The sensitivity of CSF cytology is low (2%-32%) but increases when combined with flow cytometry. Cerebrospinal fluid lactate dehydrogenase isozyme 5, β2-microglobulin, and immunoglobulin heavy chain rearrangement studies have improved sensitivity over CSF cytology (58%-85%) but have only moderate specificity (85%). New techniques of proteomics and microRNA analysis have more than 95% specificity in the diagnosis of CNS lymphoma. Positive CSF cytology, vitreous biopsy, or brain/leptomeningeal biopsy remain the current standard for diagnosis. A combined stepwise systematic approach outlined here may facilitate an expeditious, comprehensive presurgical evaluation for cases of suspected CNS lymphoma.