Brain injury in COVID-19 is associated with dysregulated innate and adaptive immune responses.

COVID-19 is associated with neurological complications including stroke, delirium and encephalitis. Furthermore, a post-viral syndrome dominated by neuropsychiatric symptoms is common, and is seemingly unrelated to COVID-19 severity. The true frequency and underlying mechanisms of neurological injury are unknown, but exaggerated host inflammatory responses appear to be a key driver of COVID-19 severity. We investigated the dynamics of, and relationship between, serum markers of brain injury [neurofilament light (NfL), glial fibrillary acidic protein (GFAP) and total tau] and markers of dysregulated host response (autoantibody production and cytokine profiles) in 175 patients admitted with COVID-19 and 45 patients with influenza. During hospitalization, sera from patients with COVID-19 demonstrated elevations of NfL and GFAP in a severity-dependent manner, with evidence of ongoing active brain injury at follow-up 4 months later. These biomarkers were associated with elevations of pro-inflammatory cytokines and the presence of autoantibodies to a large number of different antigens. Autoantibodies were commonly seen against lung surfactant proteins but also brain proteins such as myelin associated glycoprotein. Commensurate findings were seen in the influenza cohort. A distinct process characterized by elevation of serum total tau was seen in patients at follow-up, which appeared to be independent of initial disease severity and was not associated with dysregulated immune responses unlike NfL and GFAP. These results demonstrate that brain injury is a common consequence of both COVID-19 and influenza, and is therefore likely to be a feature of severe viral infection more broadly. The brain injury occurs in the context of dysregulation of both innate and adaptive immune responses, with no single pathogenic mechanism clearly responsible.

Getting what you pay for: impact of copayments on physical therapy and opioid initiation, timing, and continuation for newly diagnosed low back pain.

BACKGROUND CONTEXT: Physical therapy (PT) is an important component of low back pain (LBP) management. Despite established guidelines, heterogeneity in medical management remains common. PURPOSE: We sought to understand how copayments impact timing and utilization of PT in newly diagnosed LBP. STUDY DESIGN/SETTING: The IBM Watson Health MarketScan claims database was used in a longitudinal setting. PATIENT SAMPLE: Adult patients with LBP. OUTCOME MEASURES: The primary outcomes-of-interest were timing and overall utilization of PT services. Additional outcomes-of-interest included timing of opioid prescribing. METHODS: Actual and inferred copayments based on nonnonprimary care provider visit claims were used to evaluate the relationship between PT copayment and incidence of PT initiation. Multivariable regression models were used to evaluate factors influencing PT usage. RESULTS: Overall, 2,467,389 patients were included. PT initiation, among those with at ≥1 PT service during the year after LBP diagnosis (30.6%), occurred at a median of 8 days postdiagnosis (IQR 1-55). Among those with at least one PT encounter, incidence of subsequent PT visits was significantly lower for those with high initial PT copayments. High initial PT copayments, while inversely correlated with PT utilization, were directly correlated with subsequent opioid use (0.77 prescriptions/patient [$0 PT copayment] versus 1.07 prescriptions/patient [$50-74 PT copayment]; 1.15 prescriptions/patient [$75+ PT copayment]). Among patients with known opioid and PT copayments, higher PT copayments were correlated with faster opioid use while higher opioid copayments were correlated with faster PT use (Spearman p<.05). For multivariable whole-cohort analyses, incidence of PT initiation among patients with inferred copayments in the 50-75th and 75-100th percentiles was significantly lower than those below the 50th percentile (HR=0.893 [95%CI 0.887-0.899] and HR=0.905 [95%CI 0.899-0.912], respectively). CONCLUSIONS: Higher PT copayments correlated with reduced PT utilization; higher PT copayments and lower opioid copayments were independent contributors to delayed PT initiation and higher opioid use. In patients covered by plans charging high PT copayments, opioid use was significantly higher. Copays may impact long-term adherence to PT.

Extraction of Unstructured Electronic Health Records to Evaluate Glioblastoma Treatment Patterns.

PURPOSE: Data on lines of therapy (LOTs) for cancer treatment are important for clinical oncology research, but LOTs are not explicitly recorded in electronic health records (EHRs). We present an efficient approach for clinical data abstraction and a flexible algorithm to derive LOTs from EHR-based medication data on patients with glioblastoma multiforme (GBM). METHODS: Nonclinicians were trained to abstract the diagnosis of GBM from EHRs, and their accuracy was compared with abstraction performed by clinicians. The resulting data were used to build a cohort of patients with confirmed GBM diagnosis. An algorithm was developed to derive LOTs using structured medication data, accounting for the addition and discontinuation of therapies and drug class. Descriptive statistics were calculated and time-to-next-treatment (TTNT) analysis was performed using the Kaplan-Meier method. RESULTS: Treating clinicians as the gold standard, nonclinicians abstracted GBM diagnosis with a sensitivity of 0.98, specificity 1.00, positive predictive value 1.00, and negative predictive value 0.90, suggesting that nonclinician abstraction of GBM diagnosis was comparable with clinician abstraction. Of 693 patients with a confirmed diagnosis of GBM, 246 patients contained structured information about the types of medications received. Of them, 165 (67.1%) received a first-line therapy (1L) of temozolomide, and the median TTNT from the start of 1L was 179 days. CONCLUSION: We described a workflow for extracting diagnosis of GBM and LOT from EHR data that combines nonclinician abstraction with algorithmic processing, demonstrating comparable accuracy with clinician abstraction and highlighting the potential for scalable and efficient EHR-based oncology research.

Translational Models in Glioma Immunotherapy Research.

Immunotherapy is a promising therapeutic domain for the treatment of gliomas. However, clinical trials of various immunotherapeutic modalities have not yielded significant improvements in patient survival. Preclinical models for glioma research should faithfully represent clinically observed features regarding glioma behavior, mutational load, tumor interactions with stromal cells, and immunosuppressive mechanisms. In this review, we dive into the common preclinical models used in glioma immunology, discuss their advantages and disadvantages, and highlight examples of their utilization in translational research.

Opioid Usage in Lumbar Disc Herniation Patients with Nonsurgical, Early Surgical, and Late Surgical Treatments.

OBJECTIVE: To assess opioid usage in surgical and nonsurgical patients with lumbar disc herniation receiving different treatments and timing of treatments. METHODS: Individuals with newly diagnosed lumbar intervertebral disc herniation without myelopathy were queried from a health claims database. Patients were categorized into 3 cohorts: nonsurgical, early surgery, and late surgery. Early surgery cohort patients underwent surgery within 30 days postdiagnosis; late surgery cohort patients had surgery after 30 days but before 1 year postdiagnosis. The index date was defined as the diagnosis date for nonsurgical patients and the initial surgery date for surgical patients. The primary outcome was the average daily opioid morphine milligram equivalents (MME) prescribed. Additional outcomes included percentage of opioid-using patients and cumulative opioid burden. RESULTS: Inclusion criteria were met by 573,082 patients: 533,226 patients received nonsurgical treatments, 22,312 patients received early surgery, and 17,544 patients received late surgery. Both surgical cohorts experienced a postsurgical increase in opioid usage, which then sharply declined and gradually plateaued, with daily opioid MME consistently lower in the early versus late surgery cohort. The early surgery cohort also consistently had a lower prevalence of opioid-using patients than the late surgery cohort. Patients receiving nonsurgical treatment demonstrated the highest 1-year post index cumulative opioid burden, and the early surgery cohort consistently had lower cumulative opioid MME than the late surgery cohort. CONCLUSIONS: Early surgery in patients with lumbar disc herniation is associated with lower long-term average daily MME, incidence of opioid use, and 1-year cumulative MME burden compared with nonsurgical and late surgery treatment approaches.

Selective prediction for extracting unstructured clinical data.

OBJECTIVE: While there are currently approaches to handle unstructured clinical data, such as manual abstraction and structured proxy variables, these methods may be time-consuming, not scalable, and imprecise. This article aims to determine whether selective prediction, which gives a model the option to abstain from generating a prediction, can improve the accuracy and efficiency of unstructured clinical data abstraction. MATERIALS AND METHODS: We trained selective classifiers (logistic regression, random forest, support vector machine) to extract 5 variables from clinical notes: depression (n = 1563), glioblastoma (GBM, n = 659), rectal adenocarcinoma (DRA, n = 601), and abdominoperineal resection (APR, n = 601) and low anterior resection (LAR, n = 601) of adenocarcinoma. We varied the cost of false positives (FP), false negatives (FN), and abstained notes and measured total misclassification cost. RESULTS: The depression selective classifiers abstained on anywhere from 0% to 97% of notes, and the change in total misclassification cost ranged from -58% to 9%. Selective classifiers abstained on 5%-43% of notes across the GBM and colorectal cancer models. The GBM selective classifier abstained on 43% of notes, which led to improvements in sensitivity (0.94 to 0.96), specificity (0.79 to 0.96), PPV (0.89 to 0.98), and NPV (0.88 to 0.91) when compared to a non-selective classifier and when compared to structured proxy variables. DISCUSSION: We showed that selective classifiers outperformed both non-selective classifiers and structured proxy variables for extracting data from unstructured clinical notes. CONCLUSION: Selective prediction should be considered when abstaining is preferable to making an incorrect prediction.

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses.

To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1-11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely.

Immunometabolism, a new therapeutic development for immunotherapies of high-grade gliomas: a narrative review.

BACKGROUND AND OBJECTIVE: Immunotherapy has yielded significant improvements in survival for many cancer types, but its impact on glioblastoma (GBM) has been relatively muted. There is a growing interest in understanding the role of cancer metabolism and its role in tumor growth and therapeutic response. Thus, it is equally important to consider the clinical implications of immune cell metabolism on cancer progression and implications for therapeutic development. Our objective is to present new developments in immunometabolic research that are relevant to immunotherapy development for high-grade gliomas. METHODS: A literature search and review was conducted, regarding original research articles studying metabolic pathways of immune cells in high-grade gliomas. Searches were conducted in PubMed and Embase databases on May 15 and June 13, 2022. English-language original research articles were selected and prioritized based on their inclusion of findings related to metabolic changes in myeloid and lymphoid cells in the glioma tumor microenvironment. KEY CONTENT AND FINDINGS: There are many metabolic mechanisms by which immune cells in high-grade gliomas, like GBM, contribute to tumor growth and persistence via immunosuppression and high therapeutic resistance. There are also several ways that metabolic optimization has already been shown to improve immunotherapies already in clinical trials or in use, including dendritic cell vaccines and chimeric antigen receptor T cells. CONCLUSIONS: The implications of immunometabolic research presented here should be taken into consideration in future research and immunotherapy development of high-grade gliomas for our best chances at improving patient survival.

Profiling Real-Time Aroma from Green Tea Infusion during Brewing.

Aroma substances are the most crucial criteria for the sensory evaluation of tea quality, and also key attractors influencing consumers to make the decision for purchasing tea. Understanding the aromatic properties of tea infusion during different brewing time is crucial to control the tea aromatic quality. Here, headspace and direct immersion solid-phase microextraction (HS-SPME and DI-SPME), coupled with GC-MS, were employed to investigate the impact of brewing time on the changes of the volatile features of green tea infusion. Esters, aldehydes, alcohols, fatty acids, and alkaloids were the predominant volatile groups from tea infusions. Two to three minutes was identified as the best duration for the tea brewing that can maximize the abundance of aromatic chemicals in the headspace emitted from the tea infusions. The variation of the key aromatic contributors between the tea infusion and the headspace over the infusion tended to equilibrate during the tea brewing process. This study provides a theory-based reference method by analyzing the real-time aromatic characteristics in green tea. The optimal time was determined for aromatic quality control, and the complementary relationship between the volatiles in the headspace and its counterpart, tea infusion, was primarily elucidated.

Health Care Resource Utilization in Management of Opioid-Naive Patients With Newly Diagnosed Neck Pain.

Importance: Research has uncovered heterogeneity and inefficiencies in the management of idiopathic low back pain, but few studies have examined longitudinal care patterns following newly diagnosed neck pain. Objective: To understand health care utilization in patients with new-onset idiopathic neck pain. Design, Setting, and Participants: This cross-sectional study used nationally sourced longitudinal data from the IBM Watson Health MarketScan claims database (2007-2016). Participants included adult patients with newly diagnosed neck pain, no recent opioid use, and at least 1 year of continuous postdiagnosis follow-up. Exclusion criteria included prior or concomitant diagnosis of traumatic cervical disc dislocation, vertebral fractures, myelopathy, and/or cancer. Only patients with at least 1 year of prediagnosis lookback were included. Data analysis was performed from January 2021 to January 2022. Main Outcomes and Measures: The primary outcome of interest was 1-year postdiagnosis health care expenditures, including costs, opioid use, and health care service utilization. Early services were those received within 30 days of diagnosis. Multivariable regression models and regression-adjusted statistics were used. Results: In total, 679 030 patients (310 665 men [45.6%]) met the inclusion criteria, of whom 7858 (1.2%) underwent surgery within 1 year of diagnosis. The mean (SD) age was 44.62 (14.87) years among nonsurgical patients and 49.69 (9.53) years among surgical patients. Adjusting for demographics and comorbidities, 1-year regression-adjusted health care costs were $24 267.55 per surgical patient and $515.69 per nonsurgical patient. Across all health care services, $95 379 949 was accounted for by nonsurgical patients undergoing early imaging who did not receive any additional conservative therapy or epidural steroid injections, for a mean (SD) of $477.53 ($1375.60) per patient and median (IQR) of $120.60 ($20.70-$452.37) per patient. On average, patients not undergoing surgery, physical therapy, chiropractic manipulative therapy, or epidural steroid injection, who underwent either early advanced imaging (magnetic resonance imaging or computed tomography) or both early advanced and radiographic imaging, accumulated significantly elevated health care costs ($850.69 and $1181.67, respectively). Early conservative therapy was independently associated with 24.8% (95% CI, 23.5%-26.2%) lower health care costs. Conclusions and Relevance: In this cross-sectional study, early imaging without subsequent intervention was associated with significantly increased health care spending among patients with newly diagnosed idiopathic neck pain. Early conservative therapy was associated with lower costs, even with increased frequency of therapeutic services, and may have reduced long-term care inefficiency.

Pediatric Trauma Center Access, Regional Injury Burden, and Socioeconomic Disadvantage.

This cross-sectional study assesses whether populations in socioeconomically disadvantaged regions in the US lack timely access to pediatric trauma centers.