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HIV-Associated CD8 Encephalitis: A UK Case Series and Review of Histopathologically Confirmed Cases

ABSTRACT: HIV-associated CD8-encephalitis (HIV-CD8E) is a severe inflammatory disorder dominated by infiltration of the brain by CD8+ T-lymphocytes. It occurs in people with HIV, typically when the virus is apparently well-controlled by antiretroviral treatment (ART). HIV-CD8E presents with symptoms and signs related to marked cerebral inflammation and swelling, and can lead to coma and death unless treated promptly with corticosteroids. Risk events such as intercurrent infection, antiretroviral therapy interruption, immune reconstitution inflammatory syndrome (IRIS) after starting ART, and concomitant associations such as cerebrospinal fluid (CSF) HIV viral escape have been identified, but the pathogenesis of the disorder is not known. We present the largest case series of HIV-CD8E to date (n = 23), representing histopathologically confirmed cases in the UK. We also summarize the global literature representing all previously published cases with histopathological confirmation (n = 30). A new variant of HIV-CD8E is described, occurring on a background of HIV encephalitis (HIVE).Together these series, totalling 53 patients, provide new insights. CSF HIV viral escape was a frequent finding in HIV-CD8E occurring in 68% of those with CSF available and tested; ART interruption and IRIS were important, both occurring in 27%. Black ethnicity appeared to be a key risk factor; all but two UK cases were African, as were the majority of the previously published cases in which ethnicity was stated. We discuss potential pathogenic mechanisms, but there is no unifying explanation over all the HIV-CD8E scenarios.

SUBMITTER: Lucas S

PROVIDER: S-EPMC8047670 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAlong with the increasing use of immune checkpoint inhibitors comes a surge in immune-related toxicity. Here, we review the currently available data regarding neurological immune adverse events, and more specifically aseptic meningitis and encephalitis, and present treatment and diagnostic recommendations. Furthermore, we present five cases of immunotherapy-induced aseptic meningitis and encephalitis treated at our institution.Recent findingsNeurological immune-related adverse events, including aseptic meningitis and encephalitis, secondary to checkpoint inhibitors are a rare but complex and clinically relevant entity, comprising a wide range of diseases, most often presenting with symptoms with a wide range of differential diagnoses. Our case-series highlights the challenges of such entities and the importance of properly identifying and managing aseptic meningitis and encephalitis.SummaryCheckpoint inhibitor-induced meningoencephalitis warrants prompt investigations and treatment. Properly diagnosing aseptic meningitis, encephalitis, or mixed presentations may guide the treatment decision, as highlighted by our case-series. After rapid exclusion of alternative diagnoses, urgent corticosteroids are the therapeutic backbone but this could change in favour of highly specific cytokine-directed treatment options.Plain language summaryAseptic meningitis and encephalitis with immune checkpoint inhibitors: a single centre case-series and review of the literature Over the course of the past decade, checkpoint inhibitors have revolutionized cancer care. With their favourable toxicity profile and potential for durable and deep responses, they have become ubiquitous across the field of oncology. Furthermore, combination checkpoint inhibitors are also gaining ground, with increased efficacy and, unfortunately, immune-related toxicity. While there are guidelines based on extensive clinical experience for frequent adverse events, uncommon entities are less readily identified and treated. Neurological immune-related adverse events secondary to checkpoint inhibitors are a rare but complex entity, comprising a wide range of diseases, most often presenting with aspecific symptoms. In this paper, we discuss a single institution case-series of patients with autoimmune aseptic meningitis and encephalitis, and we perform a narrative literature review on this subject. We conclude with our treatment recommendations based on available evidence.

Project description:IntroductionSince COVID-19 outbreak, various studies mentioned the occurrence of neurological disorders. Of these, encephalitis is known as a critical neurological complication in COVID-19 patients. Numerous case reports and case series have found encephalitis in relation to COVID-19, which have not been systematically reviewed. This study aims to evaluate the clinical symptoms, diagnosis, treatment, and outcome of COVID-19-associated encephalitis.MethodsWe used the Pubmed/Medline, Embase, and Web of Science databases to search for reports on COVID-19-associated encephalitis from January 1, 2019, to March 7, 2021. The irrelevant studies were excluded based on screening and further evaluation. Then, the information relating diagnosis, treatment, clinical manifestations, comorbidities, and outcome was extracted and evaluated.ResultsFrom 4455 initial studies, 45 articles met our criteria and were selected for further evaluation. Included publications reported an overall number of 53 COVID-19-related encephalitis cases. MRI showed hyperintensity of brain regions including white matter (44.68%), temporal lobe (17.02%), and thalamus (12.76%). Also, brain CT scan revealed the hypodensity of the white matter (17.14%) and cerebral hemorrhages/hemorrhagic foci (11.42%) as the most frequent findings. The IV methylprednisolone/oral prednisone (36.11%), IV immunoglobulin (27.77%), and acyclovir (16.66%) were more preferred for COVID-19 patients with encephalitis. From the 46 patients, 13 (28.26%) patients were died in the hospital.ConclusionIn this systematic review, characteristics of COVID-19-associated encephalitis including clinical symptoms, diagnosis, treatment, and outcome were described. COVID-19-associated encephalitis can accompany with other neurological symptoms and involve different brain. Although majority of encephalitis condition are reversible, but it can lead to life-threatening status. Therefore, further investigation of COVID-19-associated encephalitis is required.

Project description:In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to detect outbreaks early, monitor the trends, and implement prevention and control measures. We have applied newly developed machine learning approaches to identify laboratory-confirmed dengue cases from 4,894 emergency department patients with dengue-like illness (DLI) who received laboratory tests. Among them, 60.11% (2942 cases) were confirmed to have dengue. Using just four input variables [age, body temperature, white blood cells counts (WBCs) and platelets], not only the state-of-the-art deep neural network (DNN) prediction models but also the conventional decision tree (DT) and logistic regression (LR) models delivered performances with receiver operating characteristic (ROC) curves areas under curves (AUCs) of the ranging from 83.75% to 85.87% [for DT, DNN and LR: 84.60% ± 0.03%, 85.87% ± 0.54%, 83.75% ± 0.17%, respectively]. Subgroup analyses found all the models were very sensitive particularly in the pre-epidemic period. Pre-peak sensitivities (<35 weeks) were 92.6%, 92.9%, and 93.1% in DT, DNN, and LR respectively. Adjusted odds ratios examined with LR for low WBCs [≤ 3.2 (x103/μL)], fever (≥38°C), low platelet counts [< 100 (x103/μL)], and elderly (≥ 65 years) were 5.17 [95% confidence interval (CI): 3.96-6.76], 3.17 [95%CI: 2.74-3.66], 3.10 [95%CI: 2.44-3.94], and 1.77 [95%CI: 1.50-2.10], respectively. Our prediction models can readily be used in resource-poor countries where viral/serologic tests are inconvenient and can also be applied for real-time syndromic surveillance to monitor trends of dengue cases and even be integrated with mosquito/environment surveillance for early warning and immediate prevention/control measures. In other words, a local community hospital/clinic with an instrument of complete blood counts (including platelets) can provide a sentinel screening during outbreaks. In conclusion, the machine learning approach can facilitate medical and public health efforts to minimize the health threat of dengue epidemics. However, laboratory confirmation remains the primary goal of surveillance and outbreak investigation.

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HIV-Associated CD8 Encephalitis: A UK Case Series and Review of Histopathologically Confirmed Cases

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