Background Coronaviruses mainly affect the respiratory system; however, there are reports of SARS-CoV and MERS-CoV causing neurological manifestations. We aimed at discussing the various neurological manifestations of SARS-CoV-2 infection and to estimate the prevalence of each of them. Methods We searched the following electronic databases; PubMed, MEDLINE, Scopus, EMBASE, Google Scholar, EBSCO, Web of Science, Cochrane Library, WHO database, and ClinicalTrials.gov . Relevant MeSH terms for COVID-19 and neurological manifestations were used. Randomized controlled trials, non-randomized controlled trials, case-control studies, cohort studies, cross-sectional studies, case series, and case reports were included in the study. To estimate the overall proportion of each neurological manifestations, the study employed meta-analysis of proportions using a random-effects model. Results Pooled prevalence of each neurological manifestations are, smell disturbances (35.8%; 95% CI 21.4–50.2), taste disturbances (38.5%; 95%CI 24.0–53.0), myalgia (19.3%; 95% CI 15.1–23.6), headache (14.7%; 95% CI 10.4–18.9), dizziness (6.1%; 95% CI 3.1–9.2), and syncope (1.8%; 95% CI 0.9–4.6). Pooled prevalence of acute cerebrovascular disease was (2.3%; 95%CI 1.0–3.6), of which majority were ischaemic stroke (2.1%; 95% CI 0.9–3.3), followed by haemorrhagic stroke (0.4%; 95% CI 0.2–0.6), and cerebral venous thrombosis (0.3%; 95% CI 0.1–0.6). Conclusions Neurological symptoms are common in SARS-CoV-2 infection, and from the large number of cases reported from all over the world daily, the prevalence of neurological features might increase again. Identifying some neurological manifestations like smell and taste disturbances can be used to screen patients with COVID-19 so that early identification and isolation is possible.

People with schizophrenia are at greater risk of obesity, Type 2 diabetes, dyslipidaemia and hypertension than the general population. This results in an increased incidence of cardiovascular disease (CVD) and reduced life expectancy, over and above that imposed by their mental illness through suicide. Several levels of evidence from data linkage analyses to clinical trials demonstrate that treatment-related metabolic disturbances are commonplace in this patient group, and that the use of certain second-generation antipsychotics may compound the risk of developing the metabolic syndrome and CVD. In addition, smoking, poor diet, reduced physical activity and alcohol or drug abuse are prevalent in people with schizophrenia and contribute to the overall CVD risk. Management and minimization of metabolic risk factors are pertinent when providing optimal care to patients with schizophrenia. This review recommends a framework for the assessment, monitoring and management of patients with schizophrenia in the UK clinical setting.

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