Neurological symptoms in hospitalised patients with COVID-19 and their association with in-hospital mortality

Objectives. To evaluate the spectrum of neurological symptoms in patients with COVID-19 during the first 14 days of hospitalisation and its association with in-hospital mortality. Material and methods. We included 200 patients with RT-PCR-confirmed COVID-19 admitted to University Hospital in Krakow, Poland. In 164 patients, a detailed questionnaire concerning neurological symptoms and signs was performed prospectively within 14 days of hospitalisation. In the remaining 36 patients, such questionnaires were completed retrospectively based on daily observations in the Department of Neurology. Results. During hospitalisation, 169 patients (84.5%) experienced neurological symptoms; the most common were: fatigue (62.5%), decreased mood (45.5%), myalgia (43.5%), and muscle weakness (42.5%). Patients who died during hospitalisation compared to the remainder were older (79 [70.5–88.5] vs. 63.5 [51–77] years, p = 0.001), and more often had decreased level of consciousness (50.0% vs. 9.3%, p < 0.001), delirium (33.3% vs. 4.4%, p < 0.001), arterial hypotension (50.0% vs. 19.6%, p = 0.005) or stroke during (18.8% vs. 3.3%, p = 0.026) or before hospitalisation (50.0% vs. 7.1, p < 0.001), whereas those who survived more often suffered from headache (42.1% vs. 0%, p = 0.012) or decreased mood (51.7% vs. 0%, p = 0.003). Conclusions. Most hospitalised patients with COVID-19 experience neurological symptoms. Decreased level of consciousness, delirium, arterial hypotension, and stroke during or before hospitalisation increase the risk of in-hospital mortality

Introduction of a multiplex amplicon sequencing assay to quantify DNA methylation in target cytosine markers underlying four selected epigenetic clocks

Abstract Background DNA methylation analysis has proven to be a powerful tool for age assessment. However, the implementation of epigenetic age prediction in diagnostics or routine forensic casework requires appropriate laboratory methods. In this study, we aimed to compare the performance of large-scale DNA methylation analysis protocols that show promise in terms of accuracy, throughput, multiplexing capacity, and high sensitivity. Results The protocols were designed to target a predefined panel of 161 genomic CG/CA sites from four known estimators of epigenetic age-related parameters, optimized and validated using artificially methylated controls or blood samples. We successfully targeted 96% of these loci using two enrichment protocols: Ion AmpliSeq™, an amplicon-based method integrated with Ion Torrent S5, and SureSelectXT Methyl-Seq, a hybridization-based method followed by MiSeq FGx sequencing. Both protocols demonstrated high accuracy and robustness. Although hybridization assays have greater multiplexing capabilities, the best overall performance was observed for the amplicon-based protocol with the lowest variability in DNA methylation at 25 ng of starting DNA, mean observed marker coverage of ~ 6.7 k reads, and accuracy of methylation quantification with a mean absolute difference between observed and expected methylation beta value of 0.054. The Ion AmpliSeq method correlated strongly with genome-scale EPIC microarray data (R = 0.91) and showed superiority in terms of methylation measurement accuracy. Method-to-method bias was accounted for by the use of linear transformation, which provided a highly accurate prediction of calendar age with a mean absolute error of less than 5 years for the VISAGE and Hannum age clocks used. The pace of aging (PoAm) and the mortality risk score (MRS) estimators included in our panel represent next-generation clocks, were found to have low to moderate correlations with the VISAGE and Hannum models (R < 0.75), and thus may capture different aspects of epigenetic aging. Conclusions We propose a laboratory tool that allows the quantification of DNA methylation in cytosines underlying four different clocks, thus providing broad information on epigenetic aging while maintaining a reasonable number of CpG markers, opening the way to a wide range of applications in forensics, medicine, and healthcare

Metabolic syndrome is associated with similar long-term prognosis in non-obese and obese patients. An analysis of 45 615 patients from the nationwide LIPIDOGRAM 2004-2015 cohort studies

Aims We aimed to evaluate the association between metabolic syndrome (MetS) and long-term all-cause mortality. Methods The LIPIDOGRAM studies were carried out in the primary care in Poland in 2004, 2006 and 2015. MetS was diagnosed based on the National Cholesterol Education Program, Adult Treatment Panel III (NCEP/ATP III) and Joint Interim Statement (JIS) criteria. The cohort was divided into four groups: non-obese patients without MetS, obese patients without MetS, non-obese patients with MetS and obese patients with MetS. Differences in all-cause mortality was analyzed using Kaplan-Meier and Cox regression analyses. Results 45,615 participants were enrolled (mean age 56.3, standard deviation: 11.8 years; 61.7% female). MetS was diagnosed in 14,202 (31%) by NCEP/ATP III criteria, and 17,216 (37.7%) by JIS criteria. Follow-up was available for 44,620 (97.8%, median duration 15.3 years) patients. MetS was associated with increased mortality risk among the obese (hazard ratio, HR: 1.88 [95% CI, 1.79-1.99] and HR: 1.93 [95% CI 1.82-2.04], according to NCEP/ATP III and JIS criteria, respectively) and non-obese individuals (HR: 2.11 [95% CI 1.85-2.40] and 1.7 [95% CI, 1.56-1.85] according to NCEP/ATP III and JIS criteria respectively). Obese patients without MetS had a higher mortality risk than non-obese patients without MetS (HR: 1.16 [95% CI 1.10-1.23] and HR: 1.22 [95%CI 1.15-1.30], respectively in subgroups with NCEP/ATP III and JIS criteria applied). Conclusions MetS is associated with increased all-cause mortality risk in non-obese and obese patients. In patients without MetS obesity remains significantly associated with mortality. The concept of metabolically healthy obesity should be revised