Benedict Daniel Michael

Post-COVID-19 condition (PCC), also known as long COVID, is a heterogeneous condition marked by persistent symptoms following acute SARS-CoV-2 infection. As approximately 6% of people who have experienced acute COVID-19 are estimated to develop PCC, the potential population is vast. Many of the key symptoms of PCC reflect involvement of the nervous system, ranging from cognitive impairment (‘brain fog’), headaches and fatigue to anxiety and depression. This Review summarizes the spectrum of neurological and psychological symptoms that occur following acute SARS-CoV-2 infection, with a particular focus on the international consensus-based core outcome set for PCC. We also explore the proposed underlying mechanisms, including evidence for immune system dysregulation, microvascular dysfunction and volumetric changes on neuroimaging. In addition, we review ongoing and completed large-scale treatment trials. Growing evidence suggests a bidirectional interaction between symptoms traditionally considered neurobiological in origin, such as cognitive deficits and headache, and those within the purview of psychiatry, such as anxiety and depression. PCC represents an opportunity to better understand the long-term consequences of acute infection and improve management strategies and outcomes, not only for people with the condition but also for those with other post-viral syndromes that affect brain health.

Background: Interictal epileptiform discharges (IEDs) are transient spikes or waves that occur in electroencephalography (EEG) records and can help support the diagnosis and classification of epilepsy. High-throughput machine learning models aim to automate the detection of IEDs. Previous evaluations of machine learning models have reported non-inferiority compared to human experts, but these studies predominantly use small datasets of pre-selected, ‘IED rich’ records, which are not representative of clinical practice. Therefore, this study aims to analyse the accuracy of machine learning models in a large, routine, clinically representative cohort. Methods: All routine EEGs performed in a large regional hospital in England were identified between June 2024 and February 2025. EEG records were run through the commercial machine learning model P15 and automated IED reports generated. The sensitivity, specificity, positive and negative predictive value of P15-detected IEDs were evaluated using the final clinical report as a reference standard. Results: Of 484 EEG records, 53 were reported to contain at least one IED in the final clinical report. At P15’s default sensitivity setting, sensitivity for IED detection was 81.1% (95% CI:77.6–84.6), specificity 59.9% (95% CI: 55.5–64.2), positive predictive value 19.9% (95% CI:16.3–23.5) and negative predictive value 96.3% (95% CI:94.6–98.0). Discussion: This large-scale study of a machine learning model for identification of IEDs in a representative clinical population found a high negative predictive value suggesting that this may be a useful tool to rule out IEDs. However, the low positive predictive value demonstrates the potential for over-calling IEDs in routine EEGs. Future research should evaluate machine learning models alongside clinical feedback before this approach can have sufficient utility in direct clinical care.

It is well recognized that many pandemic viruses are associated with neurologic complications, most recently with COVID-19. After the outbreak of the COVID-19 pandemic, neurologic surveillance platforms were implemented to characterize the complications of COVID-19. Surveillance platforms are invaluable in providing timely data, informing clinical practice, and directing future research. Lessons learned from recent neurologic surveillance networks include the importance of global and cross-specialty collaboration. It is critical for future surveillance systems to consider these aspects, as it will also serve to improve representation of low and middle-income countries (LMICs) and communities. Trainees played a critical role in the success of neurologic surveillance networks; as frontline health care workers, they were able to provide timely data collection, and their fresh insights are important for future pandemic surveillance system development. In this article, we review the methods of recent neurologic surveillance networks and discuss their strengths and limitations. We explore the outlook for pandemic surveillance platforms and the crucial role global collaboration plays in ensuring that LMICs are represented. We review the role of trainees in pandemic surveillance networks and discuss how it is vital to encourage their continued involvement to ensure that, as future health care leaders, they are prepared to manage future pandemics effectively.

The blood-brain barrier (BBB) protects the brain from pathogenic microorganisms. Neurologic complications from viral infections, including herpes simplex virus, varicella zoster virus, HIV, Japanese encephalitis virus, and SARS-CoV-2, are linked to BBB dysfunction and loss of barrier integrity. Increased BBB permeability associated with viral infections can occur through several mechanisms, such as direct neurotropism, Trojan horse mechanisms, or systemic infection and inflammation. Viruses cause direct and indirect immune-mediated damage. Understanding these neuroimmune mechanisms is critical to establish therapeutic strategies to protect BBB function. This review describes the effect of viral infection on the BBB, clinical methods to assess BBB integrity, and clinical management approaches to address viral-induced BBB damage.

Purpose of review: Viral encephalitis is a potentially devastating condition of cerebral inflammation manifest as a combination of fever, altered mentation, and sometimes focal neurological signs and seizures. In this review we explore the new developments in understanding of the epidemiology, pathogenesis and treatment options. Recent findings: The WHO technical brief is a landmark document which sets the stage for the advancement of the surveillance, prevention and management of viral encephalitis. Adjunctive dexamethasone given in herpes simplex virus encephalitis is not associated with a worse outcome or CSF viral persistence but may not significantly improve overall outcome. Simple interventions in resource limited settings can significantly increase the proportion of patients with a syndrome or aetiological diagnosis of viral encephalitis. Summary of implications: This review highlights ongoing research further elucidating the underlying pathophysiological mechanisms of brain injury, paving the way for adjunctive targeted immunotherapy which can ameliorate those aspects of the inflammatory response contributing to brain injury. Nevertheless, large-scale networks are required to establish the prospective, adaptive platform trials necessary. Pending this, as laid out in the WHO Technical Brief on encephalitis, preventive measures have the potential to save lives, including surveillance, vector control, and uptake of established and emerging vaccines.

It is established that patients hospitalised with COVID-19 often have ongoing morbidity affecting activity of daily living (ADL), employment, and mental health. However, little is known about the relative outcomes in patients with COVID-19 neurological or psychiatric complications. We conducted a UK multicentre case–control study of patients hospitalised with COVID-19 (controls) and those who developed COVID-19 associated acute neurological or psychiatric complications (cases). Among the 651 patients, [362 (55%) cases and 289 (45%) controls], a higher proportion of cases had impairment in ADLs (199 [68.9%] vs 101 [51.8%], OR 2.06, p < 0.0002) and reported symptoms impacting employment (159 [58.2%] vs 69 [35.6%] OR 2.53, p < 0.0001). There was no significant difference in the proportion with depression or anxiety between case and control groups overall. For cases, impairment of ADLs was associated with increased risk in female sex, age > 50 years and hypertension (OR 5.43, p < 0.003, 3.11, p = 0.02, 3.66, p = 0.04). Those receiving either statins or angiotensin converting enzyme (ACE) inhibitors had a lower risk of impairment in ADLs (OR 0.09, p = 0.0006, 0.17, p = 0.03). Patients with neurological or psychiatric complications of COVID-19 had worse functional outcomes than those with respiratory COVID-19 alone in terms of ADLs and employment. Female sex, age > 50 years, and hypertension were associated with worse outcomes, and statins or ACE inhibitors with better outcomes.

Neurological complications, including encephalopathy and stroke, occur in a significant proportion of COVID-19 cases but viral protein is seldom detected in the brain parenchyma. To model this situation, we developed a novel low-inoculum K18-hACE2 mouse model of SARS-CoV-2 infection during which active viral replication was consistently seen in mouse lungs but not in the brain. We found that several mediators previously associated with encephalopathy in clinical samples were upregulated in the lung, including CCL2, and IL-6. In addition, several inflammatory mediations, including CCL4, IFNγ, IL-17A, were upregulated in the brain, associated with microglial reactivity. Parallel in vitro experiments demonstrated that the filtered supernatant from SARS-CoV-2 virion exposed brain endothelial cells induced activation of uninfected microglia. This model successfully recreates SARS-CoV-2 virus-associated para-infectious brain inflammation which can be used to study the pathophysiology of the neurological complications and the identification of potential immune targets for treatment.

The spectrum, pathophysiology and recovery trajectory of persistent post-COVID-19 cognitive deficits are unknown, limiting our ability to develop prevention and treatment strategies. We report the 1-year cognitive, serum biomarker and neuroimaging findings from a prospective, national study of cognition in 351 COVID-19 patients who required hospitalization, compared with 2,927 normative matched controls. Cognitive deficits were global, associated with elevated brain injury markers and reduced anterior cingulate cortex volume 1 year after COVID-19. Severity of the initial infective insult, postacute psychiatric symptoms and a history of encephalopathy were associated with the greatest deficits. There was strong concordance between subjective and objective cognitive deficits. Longitudinal follow-up in 106 patients demonstrated a trend toward recovery. Together, these findings support the hypothesis that brain injury in moderate to severe COVID-19 may be immune-mediated, and should guide the development of therapeutic strategies.