METHODS: We searched PubMed, Medline, Cochrane library, ClinicalTrials.gov, and EMBASE for studies from December 31, 2019, to December 15, 2020, enrolling consecutive patients with COVID-19 presenting with neurologic manifestations. Risk of bias was examined with the Joanna Briggs Institute scale. A random-effects meta-analysis was performed, and pooled prevalence and 95% confidence intervals (CIs) were calculated for neurologic manifestations. Odds ratio (ORs) and 95% CIs were calculated to determine the association of neurologic manifestations with disease severity and mortality. Presence of heterogeneity was assessed with I 2, meta-regression, and subgroup analyses. Statistical analyses were conducted in R version 3.6.2.

RESULTS: Of 2,455 citations, 350 studies were included in this review, providing data on 145,721 patients with COVID-19, 89% of whom were hospitalized. Forty-one neurologic manifestations (24 symptoms and 17 diagnoses) were identified. Pooled prevalence of the most common neurologic symptoms included fatigue (32%), myalgia (20%), taste impairment (21%), smell impairment (19%), and headache (13%). A low risk of bias was observed in 85% of studies; studies with higher risk of bias yielded higher prevalence estimates. Stroke was the most common neurologic diagnosis (pooled prevalence 2%). In patients with COVID-19 ≥60 years of age, the pooled prevalence of acute confusion/delirium was 34%, and the presence of any neurologic manifestations in this age group was associated with mortality (OR 1.80, 95% CI 1.11-2.91).

DISCUSSION: Up to one-third of patients with COVID-19 analyzed in this review experienced at least 1 neurologic manifestation. One in 50 patients experienced stroke. In those >60 years of age, more than one-third had acute confusion/delirium; the presence of neurologic manifestations in this group was associated with nearly a doubling of mortality. Results must be interpreted with the limitations of observational studies and associated bias in mind.

OBJECTIVES: This paper assesses the initial responses of major farming and food systems to COVID-19 in 25 Asian countries, and considers the implications for resilience, food and nutrition security and recovery policies by the governments.

METHODS: A conceptual systems model was specified including key pathways linking the direct and indirect effects of COVID-19 to the resilience and performance of the four principal Asian farming and food systems, viz, lowland rice based; irrigated wheat based; hill mixed; and dryland mixed systems. Based on this framework, a systematic survey of 2504 key informants (4% policy makers, 6% researchers or University staff, 6% extension workers, 65% farmers, and 19% others) in 20 Asian countries was conducted and the results assessed and analysed.

RESULTS AND CONCLUSION: The principal Asian farming and food systems were moderately resilient to COVID-19, reinforced by government policies in many countries that prioritized food availability and affordability. Rural livelihoods and food security were affected primarily because of disruptions to local labour markets (especially for off-farm work), farm produce markets (notably for perishable foods) and input supply chains (i.e., seeds and fertilisers). The overall effects on system performance were most severe in the irrigated wheat based system and least severe in the hill mixed system, associated in the latter case with greater resilience and diversification and less dependence on external inputs and long market chains. Farming and food systems' resilience and sustainability are critical considerations for recovery policies and programmes, especially in relation to economic performance that initially recovered more slowly than productivity, natural resources status and social capital. Overall, the resilience of Asian farming and food systems was strong because of inherent systems characteristics reinforced by public policies that prioritized staple food production and distribution as well as complementary welfare programmes. With the substantial risks to plant- and animal-sourced food supplies from future zoonoses and the institutional vulnerabilities revealed by COVID-19, efforts to improve resilience should be central to recovery programmes.

OBJECTIVES: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis.

DESIGN, SETTING, AND PARTICIPANTS: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017.

MAIN OUTCOMES AND MEASURES: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis.

RESULTS: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4%) were female. Most patients (n = 3685 [84.7%]) were from low- and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 [62.8%]), followed by strabismus (n = 429 [10.2%]) and proptosis (n = 309 [7.4%]). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis was more common in LMICs even after adjusting for age (odds ratio for low-income countries vs upper-middle-income countries and HICs, 17.92 [95% CI, 12.94-24.80], and for lower-middle-income countries vs upper-middle-income countries and HICs, 5.74 [95% CI, 4.30-7.68]).