Age-associated dementia among older people aging with HIV in the US: a modeling study.

OBJECTIVE: Almost 400 000 people with HIV (PWH) in the United States are over age 55 years and at risk for age-associated dementias (AAD), including Alzheimer's disease and vascular contributions to cognitive impairment and dementia (VCID). We projected the cumulative incidence and mortality associated with AAD among PWH at least 60 years in the United States compared with the general population. DESIGN/METHODS: Integrating the CEPAC and AgeD-Pol models, we simulated two cohorts of male and female individuals at least 60 years old: PWH, and general US population. We estimated AAD incidence and AAD-associated mortality rates. Projected outcomes included AAD cumulative incidence, life expectancy, and quality-adjusted life-years (QALYs). We performed sensitivity and scenario analyses on AAD-specific (e.g. incidence) and HIV-specific (e.g. disengagement from HIV care) parameters, as well as premature aging among PWH. RESULTS: We projected that 22.1%/16.3% of 60-year-old male individuals/female individuals with HIV would develop AAD by 80 years compared with 15.9%/13.3% of male individuals/female individuals in the general population. Accounting for age-associated and dementia-associated quality of life, 60-year-old PWH would have a lower life expectancy (QALYs): 17.4 years (14.1 QALYs) and 16.8 years (13.4 QALYs) for male and female individuals, respectively, compared with the general population [men, 21.7 years (18.4 QALYs); women, 24.7 years (20.2 QALYs)]. AAD cumulative incidence was most sensitive to non-HIV-related mortality, engagement in HIV care, and AAD incidence rates. CONCLUSION: Projected estimates of AAD-associated morbidity, mortality, and quality of life can inform decision-makers and health systems planning as the population of PWH ages. Improved AAD prevention, treatment, and supportive care planning are critical for people aging with HIV.

Persistence of intact HIV-1 proviruses in the brain during antiretroviral therapy.

HIV-1 reservoir cells that circulate in peripheral blood during suppressive antiretroviral therapy (ART) have been well characterized, but little is known about the dissemination of HIV-1-infected cells across multiple anatomical tissues, especially the CNS. Here, we performed single-genome, near full-length HIV-1 next-generation sequencing to evaluate the proviral landscape in distinct anatomical compartments, including multiple CNS tissues, from 3 ART-treated participants at autopsy. While lymph nodes and, to a lesser extent, gastrointestinal and genitourinary tissues represented tissue hotspots for the persistence of intact proviruses, we also observed intact proviruses in CNS tissue sections, particularly in the basal ganglia. Multi-compartment dissemination of clonal intact and defective proviral sequences occurred across multiple anatomical tissues, including the CNS, and evidence for the clonal proliferation of HIV-1-infected cells was found in the basal ganglia, in the frontal lobe, in the thalamus and in periventricular white matter. Deep analysis of HIV-1 reservoirs in distinct tissues will be informative for advancing HIV-1 cure strategies.

Approximately 39 million people in the world live with HIV infection. Currently available treatments can reduce the amount of virus to near undetectable levels. But they do not eliminate the virus. A reservoir of HIV-infected cells persists during treatment. If treatment stops, these cells can cause rebounding virus levels and a return of symptoms. As a result, patients living with HIV must remain on treatment their entire lives. HIV reservoir cells often do not express viral proteins, making them hard for the immune system to find and destroy. Many of these reservoir cells occur in lymph nodes, which makes them difficult for researchers to access for study. Learning more about where these cells hide in the body may enable scientists to develop new treatments to help eliminate them. Sun et al. show that HIV reservoir cells exist in many body tissues, including the brain. In the experiments, Sun et al. used single HIV genome sequencing to identify HIV genetic sequences in the brain and other body tissues from three recently deceased individuals with HIV. The individuals agreed to donate their tissues for postmortem studies before their deaths. All received antiretroviral therapy until death. The experiments identified functional HIV genetic sequences in lymph nodes and gastrointestinal tissues, known hotspots for HIV-infected cells. Sun et al. also found genetically intact HIV in brain tissue from two of the individuals. The HIV genetic sequences were identical to sequences found in other body tissues. This discovery suggests HIV-infected cells had divided into more HIV-infected cells and spread. The results suggest that cells harboring intact HIV invade the brain and persist there for extended periods during antiretroviral therapy. To eradicate the virus, interventions targeting HIV reservoir cells must be able to reach the brain. This new information may help researchers developing HIV-reservoir targeting drugs decide which candidates will likely be the most effective. Future studies may also shed light on how HIV reaches the brain and how the infected cells escape destruction by immune cells, which may suggest more treatment strategies.

Brain health scores to predict neurological outcomes from electronic health records.

BACKGROUND: Preserving brain health is a critical priority in primary care, yet screening for these risk factors in face-to-face primary care visits is challenging to scale to large populations. We aimed to develop automated brain health risk scores calculated from data in the electronic health record (EHR) enabling population-wide brain health screening in advance of patient care visits. METHODS: This retrospective cohort study included patients with visits to an outpatient neurology clinic at Massachusetts General Hospital, between January 2010 and March 2021. Survival analysis with an 11-year follow-up period was performed to predict the risk of intracranial hemorrhage, ischemic stroke, depression, death and composite outcome of dementia, Alzheimer's disease, and mild cognitive impairment. Variables included age, sex, vital signs, laboratory values, employment status and social covariates pertaining to marital, tobacco and alcohol status. Random sampling was performed to create a training (70%) set for hyperparameter tuning in internal 5-fold cross validation and an external hold-out testing (30%) set of patients, both stratified by age. Risk ratios for high and low risk groups were evaluated in the hold-out test set, using 1000 bootstrapping iterations to calculate 95% confidence intervals (CI). RESULTS: The cohort comprised 17,040 patients with an average age of 49 ± 15.6 years; majority were males (57 %), White (78 %) and non-Hispanic (80 %). The low and high groups average risk ratios [95 % CI] were: intracranial hemorrhage 0.46 [0.45-0.48] and 2.07 [1.95-2.20], ischemic stroke 0.57 [0.57-0.59] and 1.64 [1.52-1.69], depression 0.68 [0.39-0.74] and 1.29 [0.78-1.38], composite of dementia 0.27 [0.26-0.28] and 3.52 [3.18-3.81] and death 0.24 [0.24-0.24] and 3.96 [3.91-4.00]. CONCLUSIONS: Simple risk scores derived from routinely collected EHR accurately quantify the risk of developing common neurologic and psychiatric diseases. These scores can be computed automatically, prior to medical care visits, and may thus be useful for large-scale brain health screening.

Mogamulizumab for Treatment of Human T-lymphotropic Virus Type 1-Associated Myelopathy/Tropical Spastic Paraparesis: A Single-Center US-based Series.

BACKGROUND: Human T-lymphotropic virus type 1 (HTLV-1)-associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a chronic neurological condition characterized by progressive myelopathic symptoms including spasticity, pain, weakness, and urinary symptoms, without proven treatments. Mogamulizumab (MOG) is a monoclonal antibody that binds CCR4 and leads to the clearance of HTLV-1-infected CCR4+ cells. A phase 1-2a study in Japan evaluated MOG for the treatment of HAM/TSP and reported decreases in HTLV-1 proviral load and neuroinflammatory markers, with clinical improvement in some participants. METHODS: We administered MOG 0.1 mg/kg every 8 weeks to individuals with HAM/TSP as a compassionate and palliative treatment. Patients who received MOG had (1) a positive peripheral HTLV-1 antibody, (2) progressive myelopathic symptoms, and (3) a diagnosis of HAM/TSP. RESULTS: Four female patients, ages 45-68, received MOG (range, 2-6 infusions) between 1 November 2019 and 30 November 2022. Two patients with <3 years of symptoms had milder disease, with Osame scores <4. The other 2, with >7 years of symptoms, had Osame scores >5. One patient, with 6 total treatments, received dose-reduced MOG after she developed a rash at the initial dose. The 2 patients with milder baseline disease reported symptomatic improvement and saw reductions in Osame and/or modified Ashworth scale scores during follow-up. The other 2 patients showed no improvement. All 4 developed rashes after receiving MOG-a treatment-limiting event in some cases. CONCLUSIONS: Clinical trials are needed including diverse patient populations to assess the potential role of MOG for HAM/TSP. Our findings may help inform the development of these trials.

Cognitive concerns are a risk factor for mortality in people with HIV and coronavirus disease 2019.

BACKGROUND: Data supporting dementia as a risk factor for coronavirus disease 2019 (COVID-19) mortality relied on ICD-10 codes, yet nearly 40% of individuals with probable dementia lack a formal diagnosis. Dementia coding is not well established for people with HIV (PWH), and its reliance may affect risk assessment. METHODS: This retrospective cohort analysis of PWH with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR positivity includes comparisons to people without HIV (PWoH), matched by age, sex, race, and zipcode. Primary exposures were dementia diagnosis, by International Classification of Diseases (ICD)-10 codes, and cognitive concerns, defined as possible cognitive impairment up to 12 months before COVID-19 diagnosis after clinical review of notes from the electronic health record. Logistic regression models assessed the effect of dementia and cognitive concerns on odds of death [odds ratio (OR); 95% CI (95% confidence interval)]; models adjusted for VACS Index 2.0. RESULTS: Sixty-four PWH were identified out of 14 129 patients with SARS-CoV-2 infection and matched to 463 PWoH. Compared with PWoH, PWH had a higher prevalence of dementia (15.6% vs. 6%, P  = 0.01) and cognitive concerns (21.9% vs. 15.8%, P  = 0.04). Death was more frequent in PWH ( P  < 0.01). Adjusted for VACS Index 2.0, dementia [2.4 (1.0-5.8), P  = 0.05] and cognitive concerns [2.4 (1.1-5.3), P  = 0.03] were associated with increased odds of death. In PWH, the association between cognitive concern and death trended towards statistical significance [3.92 (0.81-20.19), P  = 0.09]; there was no association with dementia. CONCLUSION: Cognitive status assessments are important for care in COVID-19, especially among PWH. Larger studies should validate findings and determine long-term COVID-19 consequences in PWH with preexisting cognitive deficits.

What Can We Still Learn from Brain Autopsies in COVID-19?

Neuropathological findings have been published from ∼900 patients who died with or from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, representing less than 0.01% of the close to 6.4 million deaths reported to the World Health Organization 2 years into the coronavirus disease 2019 (COVID-19) pandemic. In this review, we extend our prior work summarizing COVID-19 neuropathology by including information on published autopsies up to June 2022, and neuropathological studies in children, COVID-19 variants, secondary brain infections, ex vivo brain imaging, and autopsies performed in countries outside of the United States or Europe. We also summarize research studies that investigate mechanisms of neuropathogenesis in nonhuman primates and other models. While a pattern of cerebrovascular pathology and microglial-predominant inflammation remains the primary COVID-19-associated neuropathological finding, there is no singular understanding of the mechanisms that underlie neurological symptoms in acute COVID-19 or the post-acute COVID-19 condition. Thus, it is paramount that we incorporate microscopic and molecular findings from brain tissue into what we know about the clinical disease so that we attain best practice guidance and direct research priorities for the study of the neurological morbidity of COVID-19.

Classification of neurologic outcomes from medical notes using natural language processing.

Neurologic disability level at hospital discharge is an important outcome in many clinical research studies. Outside of clinical trials, neurologic outcomes must typically be extracted by labor intensive manual review of clinical notes in the electronic health record (EHR). To overcome this challenge, we set out to develop a natural language processing (NLP) approach that automatically reads clinical notes to determine neurologic outcomes, to make it possible to conduct larger scale neurologic outcomes studies. We obtained 7314 notes from 3632 patients hospitalized at two large Boston hospitals between January 2012 and June 2020, including discharge summaries (3485), occupational therapy (1472) and physical therapy (2357) notes. Fourteen clinical experts reviewed notes to assign scores on the Glasgow Outcome Scale (GOS) with 4 classes, namely 'good recovery', 'moderate disability', 'severe disability', and 'death' and on the Modified Rankin Scale (mRS), with 7 classes, namely 'no symptoms', 'no significant disability', 'slight disability', 'moderate disability', 'moderately severe disability', 'severe disability', and 'death'. For 428 patients' notes, 2 experts scored the cases generating interrater reliability estimates for GOS and mRS. After preprocessing and extracting features from the notes, we trained a multiclass logistic regression model using LASSO regularization and 5-fold cross validation for hyperparameter tuning. The model performed well on the test set, achieving a micro average area under the receiver operating characteristic and F-score of 0.94 (95% CI 0.93-0.95) and 0.77 (0.75-0.80) for GOS, and 0.90 (0.89-0.91) and 0.59 (0.57-0.62) for mRS, respectively. Our work demonstrates that an NLP algorithm can accurately assign neurologic outcomes based on free text clinical notes. This algorithm increases the scale of research on neurological outcomes that is possible with EHR data.

Machine Learning Approaches to Understand Cognitive Phenotypes in People With HIV.

Cognitive disorders are prevalent in people with HIV (PWH) despite antiretroviral therapy. Given the heterogeneity of cognitive disorders in PWH in the current era and evidence that these disorders have different etiologies and risk factors, scientific rationale is growing for using data-driven models to identify biologically defined subtypes (biotypes) of these disorders. Here, we discuss the state of science using machine learning to understand cognitive phenotypes in PWH and their associated comorbidities, biological mechanisms, and risk factors. We also discuss methods, example applications, challenges, and what will be required from the field to successfully incorporate machine learning in research on cognitive disorders in PWH. These topics were discussed at the National Institute of Mental Health meeting on "Biotypes of CNS Complications in People Living with HIV" held in October 2021. These ongoing research initiatives seek to explain the heterogeneity of cognitive phenotypes in PWH and their associated biological mechanisms to facilitate clinical management and tailored interventions.

Neuropathological features of SARS-CoV-2 delta and omicron variants.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continually evolving resulting in variants with increased transmissibility, more severe disease, reduced effectiveness of treatments or vaccines, or diagnostic detection failure. The SARS-CoV-2 Delta variant (B.1.617.2 and AY lineages) was the dominant circulating strain in the United States from July to mid-December 2021, followed by the Omicron variant (B.1.1.529 and BA lineages). Coronavirus disease 2019 (COVID-19) has been associated with neurological sequelae including loss of taste/smell, headache, encephalopathy, and stroke, yet little is known about the impact of viral strain on neuropathogenesis. Detailed postmortem brain evaluations were performed for 22 patients from Massachusetts, including 12 who died following infection with Delta variant and 5 with Omicron variant, compared to 5 patients who died earlier in the pandemic. Diffuse hypoxic injury, occasional microinfarcts and hemorrhage, perivascular fibrinogen, and rare lymphocytes were observed across the 3 groups. SARS-CoV-2 protein and RNA were not detected in any brain samples by immunohistochemistry, in situ hybridization, or real-time quantitative PCR. These results, although preliminary, demonstrate that, among a subset of severely ill patients, similar neuropathological features are present in Delta, Omicron, and non-Delta/non-Omicron variant patients, suggesting that SARS-CoV-2 variants are likely to affect the brain by common neuropathogenic mechanisms.

High-depth sequencing characterization of viral dynamics across tissues in fatal COVID-19 reveals compartmentalized infection.

SARS-CoV-2 distribution and circulation dynamics are not well understood due to challenges in assessing genomic data from tissue samples. We develop experimental and computational workflows for high-depth viral sequencing and high-resolution genomic analyses from formalin-fixed, paraffin-embedded tissues and apply them to 120 specimens from six subjects with fatal COVID-19. To varying degrees, viral RNA is present in extrapulmonary tissues from all subjects. The majority of the 180 viral variants identified within subjects are unique to individual tissue samples. We find more high-frequency (>10%) minor variants in subjects with a longer disease course, with one subject harboring ten such variants, exclusively in extrapulmonary tissues. One tissue-specific high-frequency variant was a nonsynonymous mutation in the furin-cleavage site of the spike protein. Our findings suggest adaptation and/or compartmentalized infection, illuminating the basis of extrapulmonary COVID-19 symptoms and potential for viral reservoirs, and have broad utility for investigating human pathogens.

Using CSF Proteomics to Investigate Herpesvirus Infections of the Central Nervous System.

Herpesviruses have complex mechanisms enabling infection of the human CNS and evasion of the immune system, allowing for indefinite latency in the host. Herpesvirus infections can cause severe complications of the central nervous system (CNS). Here, we provide a novel characterization of cerebrospinal fluid (CSF) proteomes from patients with meningitis or encephalitis caused by human herpes simplex virus 1 (HSV-1), which is the most prevalent human herpesvirus associated with the most severe morbidity. The CSF proteome was compared with those from patients with meningitis or encephalitis due to human herpes simplex virus 2 (HSV-2) or varicella-zoster virus (VZV, also known as human herpesvirus 3) infections. Virus-specific differences in CSF proteomes, most notably elevated 14-3-3 family proteins and calprotectin (i.e., S100-A8 and S100-A9), were observed in HSV-1 compared to HSV-2 and VZV samples, while metabolic pathways related to cellular and small molecule metabolism were downregulated in HSV-1 infection. Our analyses show the feasibility of developing CNS proteomic signatures of the host response in alpha herpes infections, which is paramount for targeted studies investigating the pathophysiology driving virus-associated neurological disorders, developing biomarkers of morbidity, and generating personalized therapeutic strategies.

Identifying Modifiable Predictors of COVID-19 Vaccine Side Effects: A Machine Learning Approach.

Side effects of COVID-19 or other vaccinations may affect an individual's safety, ability to work or care for self or others, and/or willingness to be vaccinated. Identifying modifiable factors that influence these side effects may increase the number of people vaccinated. In this observational study, data were from individuals who received an mRNA COVID-19 vaccine between December 2020 and April 2021 and responded to at least one post-vaccination symptoms survey that was sent daily for three days after each vaccination. We excluded those with a COVID-19 diagnosis or positive SARS-CoV2 test within one week after their vaccination because of the overlap of symptoms. We used machine learning techniques to analyze the data after the first vaccination. Data from 50,484 individuals (73% female, 18 to 95 years old) were included in the primary analysis. Demographics, history of an epinephrine autoinjector prescription, allergy history category (e.g., food, vaccine, medication, insect sting, seasonal), prior COVID-19 diagnosis or positive test, and vaccine manufacturer were identified as factors associated with allergic and non-allergic side effects; vaccination time 6:00-10:59 was associated with more non-allergic side effects. Randomized controlled trials should be conducted to quantify the relative effect of modifiable factors, such as time of vaccination.

Network autonomic analysis of post-acute sequelae of COVID-19 and postural tachycardia syndrome.

BACKGROUND: The autonomic nervous system (ANS) is a complex network where sympathetic and parasympathetic domains interact inside and outside of the network. Correlation-based network analysis (NA) is a novel approach enabling the quantification of these interactions. The aim of this study is to assess the applicability of NA to assess relationships between autonomic, sensory, respiratory, cerebrovascular, and inflammatory markers on post-acute sequela of COVID-19 (PASC) and postural tachycardia syndrome (POTS). METHODS: In this retrospective study, datasets from PASC (n = 15), POTS (n = 15), and matched controls (n = 11) were analyzed. Networks were constructed from surveys (autonomic and sensory), autonomic tests (deep breathing, Valsalva maneuver, tilt, and sudomotor test) results using heart rate, blood pressure, cerebral blood flow velocity (CBFv), capnography, skin biopsies for assessment of small fiber neuropathy (SFN), and various inflammatory markers. Networks were characterized by clusters and centrality metrics. RESULTS: Standard analysis showed widespread abnormalities including reduced orthostatic CBFv in 100%/88% (PASC/POTS), SFN 77%/88%, mild-to-moderate dysautonomia 100%/100%, hypocapnia 87%/100%, and elevated inflammatory markers. NA showed different signatures for both disorders with centrality metrics of vascular and inflammatory variables playing prominent roles in differentiating PASC from POTS. CONCLUSIONS: NA is suitable for a relationship analysis between autonomic and nonautonomic components. Our preliminary analyses indicate that NA can expand the value of autonomic testing and provide new insight into the functioning of the ANS and related systems in complex disease processes such as PASC and POTS.

Development and Evaluation of a Natural Language Processing Annotation Tool to Facilitate Phenotyping of Cognitive Status in Electronic Health Records: Diagnostic Study.

BACKGROUND: Electronic health records (EHRs) with large sample sizes and rich information offer great potential for dementia research, but current methods of phenotyping cognitive status are not scalable. OBJECTIVE: The aim of this study was to evaluate whether natural language processing (NLP)-powered semiautomated annotation can improve the speed and interrater reliability of chart reviews for phenotyping cognitive status. METHODS: In this diagnostic study, we developed and evaluated a semiautomated NLP-powered annotation tool (NAT) to facilitate phenotyping of cognitive status. Clinical experts adjudicated the cognitive status of 627 patients at Mass General Brigham (MGB) health care, using NAT or traditional chart reviews. Patient charts contained EHR data from two data sets: (1) records from January 1, 2017, to December 31, 2018, for 100 Medicare beneficiaries from the MGB Accountable Care Organization and (2) records from 2 years prior to COVID-19 diagnosis to the date of COVID-19 diagnosis for 527 MGB patients. All EHR data from the relevant period were extracted; diagnosis codes, medications, and laboratory test values were processed and summarized; clinical notes were processed through an NLP pipeline; and a web tool was developed to present an integrated view of all data. Cognitive status was rated as cognitively normal, cognitively impaired, or undetermined. Assessment time and interrater agreement of NAT compared to manual chart reviews for cognitive status phenotyping was evaluated. RESULTS: NAT adjudication provided higher interrater agreement (Cohen κ=0.89 vs κ=0.80) and significant speed up (time difference mean 1.4, SD 1.3 minutes; P<.001; ratio median 2.2, min-max 0.4-20) over manual chart reviews. There was moderate agreement with manual chart reviews (Cohen κ=0.67). In the cases that exhibited disagreement with manual chart reviews, NAT adjudication was able to produce assessments that had broader clinical consensus due to its integrated view of highlighted relevant information and semiautomated NLP features. CONCLUSIONS: NAT adjudication improves the speed and interrater reliability for phenotyping cognitive status compared to manual chart reviews. This study underscores the potential of an NLP-based clinically adjudicated method to build large-scale dementia research cohorts from EHRs.

Development and validation of the age-associated dementia policy (AgeD-Pol) computer simulation model in the USA and Europe.

OBJECTIVE: To develop and validate a novel, microsimulation model that accounts for the prevalence and incidence of age-associated dementias (AAD), disease progression and associated mortality. DESIGN, DATA SOURCES AND OUTCOME MEASURES: We developed the AAD policy (AgeD-Pol) model, a microsimulation model to simulate the natural history, morbidity and mortality associated with AAD. We populated the model with age-stratified and sex-stratified data on AAD prevalence, AAD incidence and mortality among people with AAD. We first performed internal validation using data from the Adult Changes in Thought (ACT) cohort study. We then performed external validation of the model using data from the Framingham Heart Study, the Rotterdam Study and Kaiser Permanente Northern California (KPNC). We compared model-projected AAD cumulative incidence and mortality with published cohort data using mean absolute percentage error (MAPE) and root-mean-square error (RMSE). RESULTS: In internal validation, the AgeD-Pol model provided a good fit to the ACT cohort for cumulative AAD incidence, 10.4% (MAPE, 0.2%) and survival, 66.5% (MAPE, 8.8%), after 16 years of follow-up among those initially aged 65-69 years. In the external validations, the model-projected lifetime cumulative incidence of AAD was 30.5%-32.4% (females) and 16.7%-23.0% (males), using data from the Framingham and Rotterdam cohorts, and AAD cumulative incidence was 21.5% over 14 years using KPNC data. Model projections demonstrated a good fit to all three cohorts (MAPE, 0.9%-9.0%). Similarly, model-projected survival provided good fit to the Rotterdam (RMSE, 1.9-3.6 among those with and without AAD) and KPNC cohorts (RMSE, 7.6-18.0 among those with AAD). CONCLUSIONS: The AgeD-Pol model performed well when validated to published data for AAD cumulative incidence and mortality and provides a useful tool to project the AAD disease burden for health systems planning in the USA.

Identifying Patients With Delirium Based on Unstructured Clinical Notes: Observational Study.

BACKGROUND: Delirium in hospitalized patients is a syndrome of acute brain dysfunction. Diagnostic (International Classification of Diseases [ICD]) codes are often used in studies using electronic health records (EHRs), but they are inaccurate. OBJECTIVE: We sought to develop a more accurate method using natural language processing (NLP) to detect delirium episodes on the basis of unstructured clinical notes. METHODS: We collected 1.5 million notes from >10,000 patients from among 9 hospitals. Seven experts iteratively labeled 200,471 sentences. Using these, we trained three NLP classifiers: Support Vector Machine, Recurrent Neural Networks, and Transformer. Testing was performed using an external data set. We also evaluated associations with delirium billing (ICD) codes, medications, orders for restraints and sitters, direct assessments (Confusion Assessment Method [CAM] scores), and in-hospital mortality. F1 scores, confusion matrices, and areas under the receiver operating characteristic curve (AUCs) were used to compare NLP models. We used the φ coefficient to measure associations with other delirium indicators. RESULTS: The transformer NLP performed best on the following parameters: micro F1=0.978, macro F1=0.918, positive AUC=0.984, and negative AUC=0.992. NLP detections exhibited higher correlations (φ) than ICD codes with deliriogenic medications (0.194 vs 0.073 for ICD codes), restraints and sitter orders (0.358 vs 0.177), mortality (0.216 vs 0.000), and CAM scores (0.256 vs -0.028). CONCLUSIONS: Clinical notes are an attractive alternative to ICD codes for EHR delirium studies but require automated methods. Our NLP model detects delirium with high accuracy, similar to manual chart review. Our NLP approach can provide more accurate determination of delirium for large-scale EHR-based studies regarding delirium, quality improvement, and clinical trails.

Using plasma proteomics to investigate viral infections of the central nervous system including patients with HIV-associated neurocognitive disorders.

State-of-the-art liquid chromatography/mass spectrometry (LC/MS)-based proteomic technologies, using microliter amounts of patient plasma, can detect and quantify several hundred plasma proteins in a high throughput fashion, allowing for the discovery of clinically relevant protein biomarkers and insights into the underlying pathobiological processes. Using such an in-house developed high throughput plasma proteomics allowed us to identify and quantify > 400 plasmas proteins in 15 min per sample, i.e., a throughput of 100 samples/day. We demonstrated the clinical applicability of our method in this pilot study by mapping the plasma proteomes from patients infected with human immunodeficiency virus (HIV) or herpes virus, both groups with involvement of the central nervous system (CNS). We found significant disease-specific differences in the plasma proteomes. The most notable difference was a decrease in the levels of several coagulation-associated proteins in HIV vs. herpes virus, among other dysregulated biological pathways providing insight into the differential pathophysiology of HIV compared to herpes virus infection. In a subsequent analysis, we found several plasma proteins associated with immunity and metabolism to differentiate patients with HIV-associated neurocognitive disorders (HAND) compared to cognitively normal people with HIV (PWH), suggesting the presence of plasma-based biomarkers to distinguishing HAND from cognitively normal PWH. Overall, our high-throughput plasma proteomics pipeline enables the identification of distinct proteomic signatures of HIV and herpes virus, which may help illuminate divergent pathophysiology behind virus-associated neurological disorders.

Functional Compartmentalization of Antibodies in the Central Nervous System During Chronic HIV Infection.

The central nervous system (CNS) has emerged as a critical HIV reservoir. Thus, interventions aimed at controlling and eliminating HIV must include CNS-targeted strategies. Given the inaccessibility of the brain, efforts have focused on cerebrospinal fluid (CSF), aimed at defining biomarkers of HIV-disease in the CNS, including HIV-specific antibodies. However, how antibodies traffic between the blood and CNS, and whether specific antibody profiles track with HIV-associated neurocognitive disorders (HAND) remains unclear. Here, we comprehensively profiled HIV-specific antibodies across plasma and CSF from 20 antiretroviral therapy (ART) naive or treated persons with HIV. CSF was populated by IgG1 and IgG3 antibodies, with reduced Fc-effector profiles. While ART improved plasma antibody functional coordination, CSF profiles were unaffected by ART and were unrelated to HAND severity. These data point to a functional sieving of antibodies across the blood-brain barrier, providing previously unappreciated insights for the development of next-generation therapeutics targeting the CNS reservoir.

Clinical and neuroradiologic characteristics in varicella zoster virus reactivation with central nervous system involvement.

OBJECTIVE: To investigate the clinical and magnetic resonance imaging (MRI) characteristics of patients with varicella zoster virus (VZV) reactivation involving the cranial nerves and central nervous system (CNS). METHODS: This is a retrospective, multi-center case-series of 37 patients with VZV infection affecting the cranial nerves and CNS. RESULTS: The median age was 71 years [IQR 51.5-76]; 21 (57%) were men. Cerebrospinal fluid (CSF) was available in 24/37 (65%); median CSF white blood cell count was 11 [IQR 2-23] cells/µL and protein was 45.5 [IQR 34.5-75.5] mg/dL. VZV polymerase chain reaction (PCR) assays were positive in 6/21 (29%) CSF and 8/9 (89%) ocular samples. Clinical involvement included the optic nerve in 12 (32%), other cranial nerves in 20 (54%), brain parenchyma in 12 (32%) and spinal cord or nerve roots in 4 (11%). Twenty-seven/28 immunocompetent patients' MRIs were available for review (96%). Of the 27, 18 had T1 postcontrast fat saturated sequences without motion artifact to evaluate for cranial nerve enhancement and optic perineuritis (OPN). Eight/18 (44%) demonstrated OPN. All 8 experienced vision loss: 3 optic neuritis, 1 acute retinal necrosis, and 3 CNS vasculitis with 1 central and 1 branch retinal artery occlusion and 1 uveitis. Diplopic patients had cranial nerve and cavernous sinus enhancement. All immunosuppressed patients were imaged. Seven/9 (88%) had extensive neuraxis involvement, including encephalitis, vasculitis and transverse myelitis; one case had OPN. CONCLUSION: OPN is a frequent manifestation in VZV-associated vision loss among immunocompetent patients. Immunosuppressed patients had greater neuraxis involvement. Optimizing MRI protocols may improve early diagnosis in VZV reactivation.

Prolonged Unconsciousness is Common in COVID-19 and Associated with Hypoxemia.

OBJECTIVE: The purpose of this study was to estimate the time to recovery of command-following and associations between hypoxemia with time to recovery of command-following. METHODS: In this multicenter, retrospective, cohort study during the initial surge of the United States' pandemic (March-July 2020) we estimate the time from intubation to recovery of command-following, using Kaplan Meier cumulative-incidence curves and Cox proportional hazard models. Patients were included if they were admitted to 1 of 3 hospitals because of severe coronavirus disease 2019 (COVID-19), required endotracheal intubation for at least 7 days, and experienced impairment of consciousness (Glasgow Coma Scale motor score <6). RESULTS: Five hundred seventy-one patients of the 795 patients recovered command-following. The median time to recovery of command-following was 30 days (95% confidence interval [CI] = 27-32 days). Median time to recovery of command-following increased by 16 days for patients with at least one episode of an arterial partial pressure of oxygen (PaO2 ) value ≤55 mmHg (p < 0.001), and 25% recovered ≥10 days after cessation of mechanical ventilation. The time to recovery of command-following  was associated with hypoxemia (PaO2 ≤55 mmHg hazard ratio [HR] = 0.56, 95% CI = 0.46-0.68; PaO2 ≤70 HR = 0.88, 95% CI = 0.85-0.91), and each additional day of hypoxemia decreased the likelihood of recovery, accounting for confounders including sedation. These findings were confirmed among patients without any imagining evidence of structural brain injury (n = 199), and in a non-overlapping second surge cohort (N = 427, October 2020 to April 2021). INTERPRETATION: Survivors of severe COVID-19 commonly recover consciousness weeks after cessation of mechanical ventilation. Long recovery periods are associated with more severe hypoxemia. This relationship is not explained by sedation or brain injury identified on clinical imaging and should inform decisions about life-sustaining therapies. ANN NEUROL 2022;91:740-755.