6 research outputs found
The prevalence and long-term health effects of Long Covid among hospitalised and non-hospitalised populations: A systematic review and meta-analysis
BACKGROUND: The aim of this study was to systematically synthesise the global evidence on the prevalence of persistent symptoms in a general post COVID-19 population. METHODS: A systematic literature search was conducted using multiple electronic databases (MEDLINE and The Cochrane Library, Scopus, CINAHL, and medRxiv) until January 2022. Studies with at least 100 people with confirmed or self-reported COVID-19 symptoms at ≥28 days following infection onset were included. Patient-reported outcome measures and clinical investigations were both assessed. Results were analysed descriptively, and meta-analyses were conducted to derive prevalence estimates. This study was pre-registered (PROSPERO-ID: CRD42021238247). FINDINGS: 194 studies totalling 735,006 participants were included, with five studies conducted in those <18 years of age. Most studies were conducted in Europe (n = 106) or Asia (n = 49), and the time to follow-up ranged from ≥28 days to 387 days. 122 studies reported data on hospitalised patients, 18 on non-hospitalised, and 54 on hospitalised and non-hospitalised combined (mixed). On average, at least 45% of COVID-19 survivors, regardless of hospitalisation status, went on to experience at least one unresolved symptom (mean follow-up 126 days). Fatigue was frequently reported across hospitalised (28.4%; 95% CI 24.7%-32.5%), non-hospitalised (34.8%; 95% CI 17.6%-57.2%), and mixed (25.2%; 95% CI 17.7%-34.6%) cohorts. Amongst the hospitalised cohort, abnormal CT patterns/x-rays were frequently reported (45.3%; 95% CI 35.3%-55.7%), alongside ground glass opacification (41.1%; 95% CI 25.7%-58.5%), and impaired diffusion capacity for carbon monoxide (31.7%; 95% CI 25.8%-3.2%). INTERPRETATION: Our work shows that 45% of COVID-19 survivors, regardless of hospitalisation status, were experiencing a range of unresolved symptoms at ∼ 4 months. Current understanding is limited by heterogeneous study design, follow-up durations, and measurement methods. Definition of subtypes of Long Covid is unclear, subsequently hampering effective treatment/management strategies. FUNDING: No funding
The Association between Circulating Branched Chain Amino Acids and the Temporal Risk of Developing Type 2 Diabetes Mellitus: A Systematic Review & Meta-Analysis
Introduction: Recent studies have concluded that elevated circulating branched chain amino acids (BCAA) are associated with the pathogenesis of type 2 diabetes mellitus (T2DM) and obesity. However, the development of this association over time and the quantification of the strength of this association for individual BCAAs prior to T2DM diagnosis remains unexplored. Methods: A systematic search was conducted using the Healthcare Databases Advance Search (HDAS) via the National Institute for Health and Care Excellence (NICE) website. The data sources included EMBASE, MEDLINE and PubMed for all papers from inception until November 2021. Nine studies were identified in this systematic review and meta-analysis. Stratification was based on follow-up times (0-6, 6-12 and 12 or more years) and controlling of body mass index (BMI) through the specific assessment of overweight cohorts was also undertaken. Results: The meta-analysis revealed a statistically significant positive association between BCAA concentrations and the development of T2DM, with valine OR = 2.08 (95% CI = 2.04-2.12, p = 12 years follow-up for valine (OR = 2.08, 1.86 and 2.14, p < 0.05 each), leucine (OR = 2.10, 2.25 and 2.16, p < 0.05 each) and isoleucine (OR = 2.12, 1.90 and 2.16, p < 0.05 each) demonstrated. Conclusion: Plasma BCAA concentrations are associated with T2DM incidence across all temporal subgroups. We suggest the potential utility of BCAAs as an early biomarker for T2DM irrespective of follow-up time
The prevalence and long-term health effects of Long Covid among hospitalised and non-hospitalised populations: A systematic review and meta-analysisResearch in context
Summary: Background: The aim of this study was to systematically synthesise the global evidence on the prevalence of persistent symptoms in a general post COVID-19 population. Methods: A systematic literature search was conducted using multiple electronic databases (MEDLINE and The Cochrane Library, Scopus, CINAHL, and medRxiv) until January 2022. Studies with at least 100 people with confirmed or self-reported COVID-19 symptoms at ≥28 days following infection onset were included. Patient-reported outcome measures and clinical investigations were both assessed. Results were analysed descriptively, and meta-analyses were conducted to derive prevalence estimates. This study was pre-registered (PROSPERO-ID: CRD42021238247). Findings: 194 studies totalling 735,006 participants were included, with five studies conducted in those <18 years of age. Most studies were conducted in Europe (n = 106) or Asia (n = 49), and the time to follow-up ranged from ≥28 days to 387 days. 122 studies reported data on hospitalised patients, 18 on non-hospitalised, and 54 on hospitalised and non-hospitalised combined (mixed). On average, at least 45% of COVID-19 survivors, regardless of hospitalisation status, went on to experience at least one unresolved symptom (mean follow-up 126 days). Fatigue was frequently reported across hospitalised (28.4%; 95% CI 24.7%–32.5%), non-hospitalised (34.8%; 95% CI 17.6%–57.2%), and mixed (25.2%; 95% CI 17.7%–34.6%) cohorts. Amongst the hospitalised cohort, abnormal CT patterns/x-rays were frequently reported (45.3%; 95% CI 35.3%–55.7%), alongside ground glass opacification (41.1%; 95% CI 25.7%–58.5%), and impaired diffusion capacity for carbon monoxide (31.7%; 95% CI 25.8%–3.2%). Interpretation: Our work shows that 45% of COVID-19 survivors, regardless of hospitalisation status, were experiencing a range of unresolved symptoms at ∼ 4 months. Current understanding is limited by heterogeneous study design, follow-up durations, and measurement methods. Definition of subtypes of Long Covid is unclear, subsequently hampering effective treatment/management strategies. Funding: No funding