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Altered mental status is a nonspecific diagnosis that encompasses a wide spectrum of disease and is frequently cited as a reason for both hospital admission and inpatient neurologic consultation. There are numerous etiologies of altered mental status, and so although many are facile with the workup of this potentially life-threatening entity, it can nevertheless be overwhelming. Our goal was to provide a practical framework embedded in a current, comprehensive review of the epidemiology, clinical evaluation, and management of undifferentiated altered mental status. We pay particular attention to the management of a critical yet underdiagnosed subtype of altered mental status: delirium.

ImportanceDespite discrete etiologies leading to delirium, it is treated as a common end point in hospital and in clinical trials, and delirium research may be hampered by the attempt to treat all instances of delirium similarly, leaving delirium management as an unmet need. An individualized approach based on unique patterns of delirium pathophysiology, as reflected in predisposing factors and precipitants, may be necessary, but there exists no accepted method of grouping delirium into distinct etiologic subgroups.ObjectiveTo conduct a systematic review to identify potential predisposing and precipitating factors associated with delirium in adult patients agnostic to setting.Evidence ReviewA literature search was performed of PubMed, Embase, Web of Science, and PsycINFO from database inception to December 2021 using search Medical Subject Headings (MeSH) terms consciousness disorders, confusion, causality, and disease susceptibility, with constraints of cohort or case-control studies. Two reviewers selected studies that met the following criteria for inclusion: published in English, prospective cohort or case-control study, at least 50 participants, delirium assessment in person by a physician or trained research personnel using a reference standard, and results including a multivariable model to identify independent factors associated with delirium.FindingsA total of 315 studies were included with a mean (SD) Newcastle-Ottawa Scale score of 8.3 (0.8) out of 9. Across 101 144 patients (50 006 [50.0%] male and 49 766 [49.1%] female patients) represented (24 015 with delirium), studies reported 33 predisposing and 112 precipitating factors associated with delirium. There was a diversity of factors associated with delirium, with substantial physiological heterogeneity.Conclusions and RelevanceIn this systematic review, a comprehensive list of potential predisposing and precipitating factors associated with delirium was found across all clinical settings. These findings may be used to inform more precise study of delirium’s heterogeneous pathophysiology and treatment.

Even low-acuity patients suffer from disrupted sleep in the hospital in part due to routine overnight vital sign (VS) checks. When invasive monitoring is not needed, vital sign monitoring devices (VSMDs) similar to consumer-grade health monitors may play a role in promoting sleep, which can aid healing and recovery.We provided one VSMD to neuroscience ward patients during their hospital stays and used surveys to assess patient and nurse attitudes toward the device and the impact of the device on patient comfort. We also compared VSMD-streamed vS data to nurse-recorded vS data in the chart to evaluate the consistency of data streaming and data concordance between the device and nurse-collected vital sign values.21 patients and 15 nurses enrolled. Overall, patients and nurses responded positively to the device and patients preferred wearing the device to receiving manual vital checks overnight. The most common device-related cause of sleep disruption per patients was device weight (29%). Device vS were concordant with nurse vS on average but there was significant variance in agreement between nurse and device values.Patients and nurses feel positively about the use of VSMDs and their use in the hospital. The device we tested may be limited in its sleep promotion by its weight and patient comfort assessment. Further research is needed to assess the precision of the device in measuring vital signs when used in a clinical setting. Future studies should compare VSMD models and assess their impacts on patient sleep in the absence of manual vS checks overnight.Funding provided by the SaraEvan Williams Foundation Endowed Neurohospitalist Chair at UCSF.

A 67-year-old woman was admitted to our hospital for progressive weakness, dysphagia, muscle pain, and weight loss. Here we detail the clinical problem solving involved in diagnosing and treating her immune-mediated necrotizing myopathy caused by anti-HMGCoA reductase autoantibodies. Interestingly, this diagnosis coincided with discovery of a gastrointestinal stromal tumor (GIST) and positivity for anti-nuclear matrix protein (anti-NXP2), another myositis specific autoantibody.

Author(s): Donovan, Anne L; Braehler, Matthias R; Robinowitz, David L; Lazar, Ann A; Finlayson, Emily; Rogers, Stephanie; Douglas, Vanja C; Whitlock, Elizabeth L; Anesthesia Resident Quality Improvement Committee | Abstract: 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 l65 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.ResultsDuring 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.ConclusionsA perioperative delirium prevention intervention was associated with reduced administration of Beers PIMs to older adults.

Importance Cerebrospinal 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. Objective To 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 participants Two 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 measures The 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. Results Across 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 relevance This 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.

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.

BACKGROUND: Delirium is associated with poor clinical outcomes that could be improved with targeted interventions. OBJECTIVE: To 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. METHODS: This 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. RESULTS: Adjusted 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). CONCLUSION: This 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.

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 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.

Neuromonitoring with electroencephalography (EEG) is an essential tool in neurological prognostication post-cardiac arrest. EEG allows reliable and real-time assessment of early changes in background patterns, development of seizures and epileptiform activity, as well as testing for background reactivity to stimuli despite use of sedation or targeted temperature management. Delayed emergence of consciousness post-cardiac arrest is common, therefore longitudinal monitoring of EEG allows the detection of trends indicative of neurological improvement before coma recovery can be observed clinically. In this review, we summarize essential recent literature in EEG monitoring for neurological prognostication post-cardiac arrest in the context of targeted temperature management, with a particular focus on the importance of the evolution of EEG patterns in the first few days following resuscitation.

Background: To date, 750 000 patients with COVID-19 worldwide have required mechanical ventilation and thus are at high risk of acute brain dysfunction (coma and delirium). We aimed to investigate the prevalence of delirium and coma, and risk factors for delirium in critically ill patients with COVID-19, to aid the development of strategies to mitigate delirium and associated sequelae. Methods: This multicentre cohort study included 69 adult intensive care units (ICUs), across 14 countries. We included all patients (aged ≥18 years) admitted to participating ICUs with severe acute respiratory syndrome coronavirus 2 infection before April 28, 2020. Patients who were moribund or had life-support measures withdrawn within 24 h of ICU admission, prisoners, patients with pre-existing mental illness, neurodegenerative disorders, congenital or acquired brain damage, hepatic coma, drug overdose, suicide attempt, or those who were blind or deaf were excluded. We collected de-identified data from electronic health records on patient demographics, delirium and coma assessments, and management strategies for a 21-day period. Additional data on ventilator support, ICU length of stay, and vital status was collected for a 28-day period. The primary outcome was to determine the prevalence of delirium and coma and to investigate any associated risk factors associated with development of delirium the next day. We also investigated predictors of number of days alive without delirium or coma. These outcomes were investigated using multivariable regression. Findings: Between Jan 20 and April 28, 2020, 4530 patients with COVID-19 were admitted to 69 ICUs, of whom 2088 patients were included in the study cohort. The median age of patients was 64 years (IQR 54 to 71) with a median Simplified Acute Physiology Score (SAPS) II of 40·0 (30·0 to 53·0). 1397 (66·9%) of 2088 patients were invasively mechanically ventilated on the day of ICU admission and 1827 (87·5%) were invasively mechanical ventilated at some point during hospitalisation. Infusion with sedatives while on mechanical ventilation was common: 1337 (64·0%) of 2088 patients were given benzodiazepines for a median of 7·0 days (4·0 to 12·0) and 1481 (70·9%) were given propofol for a median of 7·0 days (4·0 to 11·0). Median Richmond Agitation–Sedation Scale score while on invasive mechanical ventilation was –4 (–5 to –3). 1704 (81·6%) of 2088 patients were comatose for a median of 10·0 days (6·0 to 15·0) and 1147 (54·9%) were delirious for a median of 3·0 days (2·0 to 6·0). Mechanical ventilation, use of restraints, and benzodiazepine, opioid, and vasopressor infusions, and antipsychotics were each associated with a higher risk of delirium the next day (all p≤0·04), whereas family visitation (in person or virtual) was associated with a lower risk of delirium (p

Dementia is a common problem. Dementia is most often due to a neurodegenerative condition such as Alzheimer disease, but a number of systemic diseases can also cause dementia. These disorders are important to recognize because many are treatable. Each neurodegenerative disease is associated to a varying degree with a number of systemic complications including dysphagia and aspiration, delirium and agitation, depression, falls, orthostatic hypotension, sleep disorders, and gastrointestinal and genitourinary problems. Understanding the prevalence of these problems in the various dementias and the current evidence regarding prevention and treatment is critical in order to provide optimal care to this vulnerable population.

Author(s): Whitlock, Elizabeth L; Braehler, Matthias R; Kaplan, Jennifer A; Finlayson, Emily; Rogers, Stephanie E; Douglas, Vanja; Donovan, Anne L | Abstract: BackgroundPostoperative 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.MethodsThe 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.ResultsThe 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.ConclusionsThe 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.

Background: Studies 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. Methods: This 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. Results: Of 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. Conclusion: Obtaining 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.

BackgroundMetagenomic next-generation sequencing (NGS) of cerebrospinal fluid (CSF) has the potential to identify a broad range of pathogens in a single test.MethodsIn 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.ResultsWe 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.ConclusionsRoutine 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.).

Key Points Question Can machine learning be used to predict incident delirium in newly hospitalized patients using only data available in the electronic health record shortly after admission? Findings In this cohort study, classification models were trained using 5 different machine learning algorithms on 14 227 hospital stays and validated on a prospective test set of 3996 hospital stays. The gradient boosting machine model performed best, with an area under the receiver operating characteristic curve of 0.855. Meaning Machine learning can accurately predict delirium risk using electronic health record data on admission and outperforms the nurse-administered prediction rules currently used., This study describes the development and prognostic accuracy of 5 machine learning models designed to predict incident delirium in newly hospitalized patients without known cognitive impairment using clinical variables derived from the patients’ electronic health record (EHR)., Importance Current methods for identifying hospitalized patients at increased risk of delirium require nurse-administered questionnaires with moderate accuracy. Objective To develop and validate a machine learning model that predicts incident delirium risk based on electronic health data available on admission. Design, Setting, and Participants Retrospective cohort study evaluating 5 machine learning algorithms to predict delirium using 796 clinical variables identified by an expert panel as relevant to delirium prediction and consistently available in electronic health records within 24 hours of admission. The training set comprised 14 227 adult patients with non–intensive care unit hospital stays and no delirium on admission who were discharged between January 1, 2016, and August 31, 2017, from UCSF Health, a large academic health institution. The test set comprised 3996 patients with hospital stays who were discharged between August 1, 2017, and November 30, 2017. Exposures Patient demographic characteristics, diagnoses, nursing records, laboratory results, and medications available in electronic health records during hospitalization. Main Outcomes and Measures Delirium was defined as a positive Nursing Delirium Screening Scale or Confusion Assessment Method for the Intensive Care Unit score. Models were assessed using the area under the receiver operating characteristic curve (AUC) and compared against the 4-point scoring system AWOL (age >79 years, failure to spell world backward, disorientation to place, and higher nurse-rated illness severity), a validated delirium risk–assessment tool routinely administered in this cohort. Results The training set included 14 227 patients (5113 [35.9%] aged >64 years; 7335 [51.6%] female; 687 [4.8%] with delirium), and the test set included 3996 patients (1491 [37.3%] aged >64 years; 1966 [49.2%] female; 191 [4.8%] with delirium). In total, the analysis included 18 223 hospital admissions (6604 [36.2%] aged >64 years; 9301 [51.0%] female; 878 [4.8%] with delirium). The AWOL system achieved a baseline AUC of 0.678. The gradient boosting machine model performed best, with an AUC of 0.855. Setting specificity at 90%, the model had a 59.7% (95% CI, 52.4%-66.7%) sensitivity, 23.1% (95% CI, 20.5%-25.9%) positive predictive value, 97.8% (95% CI, 97.4%-98.1%) negative predictive value, and a number needed to screen of 4.8. Penalized logistic regression and random forest models also performed well, with AUCs of 0.854 and 0.848, respectively. Conclusions and Relevance Machine learning can be used to estimate hospital-acquired delirium risk using electronic health record data available within 24 hours of hospital admission. Such a model may allow more precise targeting of delirium prevention resources without increasing the burden on health care professionals.

Magnetic resonance neurography (MRN) is an important tool to detect abnormalities of peripheral nerves. This pictorial review demonstrates the MRN features of a variety of neuropathies affecting the lumbosacral plexus (LSP) and lower extremity nerves, drawn from over 1200 MRNs from our institution and supplemented by the literature. Abnormalities can be due to spinal compression, extraspinal compression, malignancy, musculoskeletal disease, iatrogenesis, inflammation, infection, and idiopathic disorders. We discuss indications and limitations of MRN in diagnosing LSP neuropathies. As MRN becomes more widely used, physicians must become familiar with the differential diagnosis of abnormalities detectable with MRN of the LSP.

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.

Objective: To examine national 30-day readmission rates for patients hospitalized with neurologic disorders. Methods: Using the University HealthSystem Consortium (UHC) database, we identified 554,399 index neurologic admissions from October 2011 through January 2015. We collected information regarding age, race, insurance payer, Medicare severity diagnosis-related group, and severity of illness. We examined readmission by diagnosis and performed multivariable logistic regression to determine predictors of readmission. Results: The unplanned readmission rate was 11.0%. Rates of unplanned readmission were highest for patients with peripheral nerve disorders (21.9%), CNS neoplasms (21.0%), nonhypertensive encephalopathy (15.5%), arterial stenosis (15.4%), and bacterial CNS infections (14.5%). In multivariable analysis, higher severity of illness and public health insurance coverage predicted higher rates of 30-day readmission. Conclusion: We found significant variation in readmission rates for different neurologic disorders. These data provide insight into management of neurologic disease nationally, offering policymakers realistic goals for standards of care and challenging health care providers to develop systems-based solutions that will improve transitions of care for those at highest risk of readmission with neurologic disease.

To 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.We 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.We 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,The 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.

ObjectiveTo identify molecular correlates of primary angiitis of the CNS (PACNS) through proteomic analysis of CSF from a biopsy-proven patient cohort.MethodsUsing 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.ResultsCompared 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.ConclusionsIn 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.

The central nervous system (CNS) has a dedicated network of blood vessels to support the physiological activity of the brain, spinal cord and meninges. Consequently, inflammation of CNS vasculature can have devastating effects on neurological function. A lack of understanding regarding the molecular pathology of CNS vasculitis impedes the development of better diagnostics and effective therapies. Here, we analyze the proteome of cerebrospinal fluid from patients with biopsy-confirmed Primary Angiitis of the Central Nervous System (PACNS) relative to non-inflammatory control patients and patients with Reversible Cerebral Vasoconstrictive Syndrome (RCVS), a syndrome that clinically mimics PACNS in several aspects. In PACNS, we find significant elevation of apolipoproteins, immunoglobulins and complement cascade components. Notably, we find a bias towards activation of the alternative complement pathway with elevated levels of the terminal cascade component, complement C5. Given the recent treatment successes of Anti-Neutrophil Cytoplasmic Antibody (ANCA) vasculitis with the C5 receptor inhibitor, CCX168 (Avacopan), our results suggest that complement C5 inhibitors may also prove useful as therapeutic interventions for PACNS.

Supplemental Digital Content is available in the text, Central nervous system (CNS) involvement occurs in 5 to 10% of individuals with disseminated histoplasmosis. Most experience has been derived from small single center case series, or case report literature reviews. Therefore, a larger study of central nervous system (CNS) histoplasmosis is needed in order to guide the approach to diagnosis, and treatment. A convenience sample of 77 patients with histoplasmosis infection of the CNS was evaluated. Data was collected that focused on recognition of infection, diagnostic techniques, and outcomes of treatment. Twenty nine percent of patients were not immunosuppressed. Histoplasma antigen, or anti-Histoplasma antibodies were detected in the cerebrospinal fluid (CSF) in 75% of patients. One year survival was 75% among patients treated initially with amphotericin B, and was highest with liposomal, or deoxycholate formulations. Mortality was higher in immunocompromised patients, and patients 54 years of age, or older. Six percent of patients relapsed, all of whom had the acquired immunodeficiency syndrome (AIDS), and were poorly adherent with treatment. While CNS histoplasmosis occurred most often in immunocompromised individuals, a significant proportion of patients were previously, healthy. The diagnosis can be established by antigen, and antibody testing of the CSF, and serum, and antigen testing of the urine in most patients. Treatment with liposomal amphotericin B (AMB-L) for at least 1 month; followed by itraconazole for at least 1 year, results in survival among the majority of individuals. Patients should be followed for relapse for at least 1 year, after stopping therapy.

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, β = − 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.

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.

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.

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.

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.

Background and Purpose: Medicine hospitalist programs have effectively incorporated hospitalist-run discharge clinics into clinical practice to help bridge the vulnerable transition periods after hospital discharge. A neurohospitalist discharge clinic would similarly allow continuity with the inpatient provider while addressing challenges in the coordination of neurologic care. We anticipated that this would afford a greater total number of patients to be seen and at a shorter interval. Methods: The number of posthospital discharge patients who were seen in general continuity per month in the 6 months prior to establishment of neurohospitalist discharge clinic and those seen over 1 full calendar year 6 months after clinic began was compared by reviewing medical records. Average length of time between discharge from hospital and first clinic visit was compared between patients seen in general neurology continuity clinic and those seen in discharge clinic. Results: There was a significant increase in the average number of postdischarge visits per month after initiation of neurohospitalist discharge clinic compared to prior (16.1 visits vs 10.5 visits, P = .001). Patients were seen significantly sooner after hospitalization in discharge clinic (35.9 ± 4.3 days) compared to those seen in general continuity clinic during the same time epoch (57.6 ± 4.1 days; p < 0.001). Conclusions: Creation of a neurohospitalist discharge clinic was effective in increasing posthospital discharge follow-up frequency and shortening duration of time to follow-up.

To study the effect of a neurohospitalist service on length of stay, cost, patient satisfaction, and education at an academic medical center.This was a retrospective cohort study using administrative data, educational surveys, and standardized patient satisfaction surveys to compare outcomes in the 21 months before (n = 343) and 27 months after (n = 436) the introduction of a neurohospitalist service in October 2006 at a single tertiary care academic medical center.The most common diagnoses treated in both periods were demyelinating disease, neuromuscular disease, seizure, CNS infection, and cerebrovascular disease. Mean length of stay was reduced during the neurohospitalist period compared with that during the preneurohospitalist period (4.6 days vs 6.3 days; p0.001), but there was no difference in median cost ($6,758 vs $7,241; p = 0.25) or in-hospital mortality (1.6 vs 1.2%; p = 0.61). After adjustment for diagnosis, admission source, and severity of illness, both length of stay (coefficient -1.85, 95% confidence interval [CI] -2.47 to -1.24) and cost (coefficient -1,558, 95% CI -2,645 to -470) were reduced during the neurohospitalist period. Thirty-day readmission rates were not different between the 2 periods in adjusted analysis. There were no differences in patient satisfaction or resident trainee satisfaction between the 2 periods, but medical student satisfaction was higher on standard educator evaluations after the neurohospitalist program was introduced.The introduction of a neurohospitalist service at an academic medical center coincided with a reduction in length of stay and cost and a nonsignificant trend toward improvement in medical student satisfaction without affecting mortality, readmission rates, or patient satisfaction.

Object Spinal dural arteriovenous fistulas (SDAVFs) cause myelopathy through arterialization of the perimedullary venous plexus and venous congestion of the spinal cord. The authors hypothesized that the craniocaudal extent of engorgement of intrathecal draining veins between the fistula site and the point of drainage out of the thecal sac correlates with the degree of myelopathy. Methods A retrospective review of the authors' institution's radiology databases identified 31 patients with SDAVFs who had undergone digital subtraction angiography (DSA) and MRI examinations of the spine. The authors counted the number of vertebral body levels of spinal cord enhancement and intrathecal vessel enhancement on T1-weighted postcontrast MRI studies. They also counted the number of levels of cord hyperintensity and intrathecal flow voids on T2-weighted MRI studies. On DSA, the authors identified the number of vertebral body levels of dilated intrathecal draining veins and outflow points from intrathecal veins to epidural veins. Functional status of the patients at the time of diagnosis was assessed using the Aminoff-Logue scale (ALS). Results Enlargement of the intrathecal draining veins averaged 10 ± 7.7 spinal levels on DSA. Patients with enlarged draining veins extending 10 or more spinal levels on DSA had worse ALS scores (mean gait 3.4, mean micturition 1.5) than patients with draining veins extending fewer than 10 levels (mean gait 1.8, mean micturition 0.6; p = 0.009 and 0.02, respectively). The number of vertebral body levels of enlarged draining veins correlated with the ALS score (gait r = 0.42, p = 0.009; and micturition r = 0.55, p = 0.0006). More extensive enlarged draining veins were associated with more spinal cord T2 hyperintensity, T2 intrathecal flow voids, and T1 vessel enhancement but not cord enhancement. Conclusions The craniocaudal extent of enlarged intrathecal veins draining SDAVF correlates with patient functional status, providing further insight into the pathophysiology of venous hypertensive myelopathy.

Summary The rapid expansion of neurohospitalist programs nationally has been fueled by recent graduates as well as by practicing neurologists increasingly choosing this career direction. An inpatient-focused job is compelling from an intellectual perspective as it allows the opportunity to treat acute disorders where new treatments are constantly emerging. Challenges entail arranging coverage, defining financial models of reimbursement, expanding into rural and international settings, and assuring proper training for those entering this emerging field. A diverse set of opportunities in both practice and academics are viable career options. Those choosing to embark on the neurohospitalist path have the opportunity to lead the field through a time of tremendous growth and change for years to come.

Altered mental status is a common reason for neurologic consultation. Although it is often due to a systemic infection or metabolic derangement, a host of other etiologies can lead to irreversible brain injury if they are not promptly identified and treated. A systematic approach to the patient is important, with an understanding of when to initiate a more advanced and potentially more resource-intense diagnostic workup.: The last decade has seen advances in both the diagnosis and treatment of altered mental status. A significant step forward in the diagnosis of patients with otherwise unexplained encephalitis has been the identification of numerous antibodies associated with paraneoplastic and nonparaneoplastic autoimmune encephalitis. The use of continuous electroencephalography has shown that a significant proportion of otherwise unexplained altered mental status may be caused by nonconvulsive seizures. Several studies have demonstrated that proactive, multicomponent interventions may be effective in preventing hospital-acquired delirium. The recent introduction of dexmedetomidine may lead to decreased rates of delirium in the intensive care unit if the results of clinical trials are borne out in practice.: This article discusses causes of altered mental status, an initial approach to evaluating the patient, and elements of the advanced diagnostic workup. The article concludes with a general discussion of prevention and treatment.

Transient ischemic attack (TIA) is common with well over 300,000 Emergency Department (ED) visits for TIA in the United States each year.1 The ED management for this common presentation is particularly challenging because TIA symptoms are by definition evanescent in nature, which makes them difficult for patients to describe, and because TIA symptoms can mimic diverse alternate diagnoses such as migraine or seizure, which makes the diagnosis more complex. Furthermore, the stakes for making an accurate diagnosis are high because there has been a growing appreciation that the early risk of stroke after TIA is high,2 and that urgent evaluation and intervention may be effective at reducing this risk.3,4 Therefore, developing efficient and effective processes of care for ED patients with TIA has been a major goal for emergency medicine and stroke neurology. Various models of care such as routine inpatient admission,5 Emergency Department observation units,6 or expedited outpatient follow-up clinics with stroke specialists3,4 have been proposed to help address this need but significant practice variation remains.7 Within this context, the potential role of urgent neurology consultation in the ED has received relatively less attention. Instead, previous studies have focused on the impact of consultation for ED patients generally10, or a neurologist’s role within a stroke center or stroke network specifically,11 or on the outcomes of inpatients with stroke who are under the care of a neurologist rather than an internist.12-17 Less is known about the impact of urgent neurology consultation in the emergency department (ED) for patients with TIA. Since the availability of neurologists for urgent consultation is often constrained and since the value-added by an urgent neurology consultation is unknown,8, 9 better information on the impact of neurology consultation on process measures and outcomes is required for policymakers and clinicians to make rational decisions on how to optimize the care for these patients. Therefore, we conducted a secondary data analysis of a cohort of ED patients diagnosed with TIA to examine associations between neurology consultation and process and outcome measures. Our goals were 1) to examine the factors that were associated with urgent neurology consultation for TIA; 2) to examine the association between neurology consultation and process improvements such as increased use of antithrombotic agents (aspirin, clopidogrel, ticlopidine, heparin, or warfarin), increased use of neuroimaging, increased utilization of anticoagulation for atrial fibrillation; and 3) to examine the association of these process improvements on clinical outcomes as measured by the number of strokes and major adverse events within 90 days of presentation.

To develop a practical informant-based screening tool that reliably identifies patients with mild cognitive impairment (MCI) and dementia, we analyzed data from a sample of patients and normal controls seen in a memory clinic. All patients were evaluated with the Clinical Dementia Rating scale. Individual Clinical Dementia Rating responses were dichotomized and entered into a forward stepwise multivariable logistic regression model. Four independent predictors of MCI and dementia thus identified were combined into a prediction rule that was validated in a separate cohort drawn from the same clinic. Using a cut point of 2 or more positive responses to the 4 questions, the final prediction rule had sensitivity of 95% (95% confidence interval (CI): 92-97%) for MCI or dementia, and a specificity of 91% (95% CI: 86-95%). When applied to the validation cohort, the sensitivity for MCI or dementia was 96% (95% CI: 94-98%), and the specificity was 96% (95% CI: 92-98%). Using both cohorts, the positive likelihood ratio for MCI or dementia was 15.6 (95% CI: 14.0-17.3) and the negative likelihood ratio was 0.05 (95% CI: 0.04-0.07). This tool has the potential to identify patients who warrant further cognitive evaluation in busy outpatient or emergency department settings.