Myotonic dystrophy type 1 in the COVID-19 era.

INTRODUCTION: Myotonic dystrophy type 1 (DM1) is the most prevalent muscular dystrophy in adults. People with DM1 might represent a high-risk population for respiratory infections, including COVID-19. Our aim was to evaluate the characteristics of COVID-19 infection and vaccination rate in DM1 patients. METHODS: This cross-sectional cohort study included 89 patients from the Serbian registry for myotonic dystrophies. Mean age at testing was 48.4 ± 10.4 years with 41 (46.1%) male patients. Mean duration of the disease was 24.0 ± 10.3 years. RESULTS: COVID-19 infection was reported by 36 (40.4%) DM1 patients. Around 14% of patients had a more severe form of COVID-19 requiring hospitalization. The severity of COVID-19 was in accordance with the duration of DM1. A severe form of COVID-19 was reported in 20.8% of patients who were not vaccinated against SARS-CoV-2 and in none of the vaccinated ones. The majority of 89 tested patients (66.3%) were vaccinated against SARS-CoV-2. About half of them (54.2%) received three doses and 35.6% two doses of vaccine. Mild adverse events after vaccination were recorded in 20.3% of patients. CONCLUSIONS: The percentage of DM1 patients who suffered from COVID-19 was like in general population, but with more severe forms in DM1, especially in patients with longer DM1 duration. The study indicated an overall favorable safety profile of COVID-19 vaccines among individuals with DM1 and its ability to protect them from severe COVID-19.

Admission Predictors of Mortality in Hospitalized COVID-19 Patients-A Serbian Cohort Study.

BACKGROUND: Early prediction of COVID-19 patients' mortality risk may be beneficial in adequate triage and risk assessment. Therefore, we aimed to single out the independent morality predictors of hospitalized COVID-19 patients among parameters available on hospital admission. METHODS: An observational, retrospective-prospective cohort study was conducted on 703 consecutive COVID-19 patients hospitalized in the University Clinical Center Kragujevac between September and December 2021. Patients were followed during the hospitalization, and in-hospital mortality was observed as a primary end-point. Within 24 h of admission, patients were sampled for blood gas and laboratory analysis, including complete blood cell count, inflammation biomarkers and other biochemistry, coagulation parameters, and cardiac biomarkers. Socio-demographic and medical history data were obtained using patients' medical records. RESULTS: The overall prevalence of mortality was 28.4% (n = 199). After performing multiple regression analysis on 20 parameters, according to the initial univariate analysis, only four independent variables gave statistically significant contributions to the model: SaO2 < 88.5 % (aOR 3.075), IL-6 > 74.6 pg/mL (aOR 2.389), LDH > 804.5 U/L (aOR 2.069) and age > 69.5 years (aOR 1.786). The C-index of the predicted probability calculated using this multivariate logistic model was 0.740 (p < 0.001). CONCLUSIONS: Parameters available on hospital admission can be beneficial in predicting COVID-19 mortality.