ObjectivesTo describe patients with autoimmune inflammatory rheumatic diseases (AIRD) who had COVID-19 disease; to compare patients who required hospital admission with those who did not and assess risk factors for hospital admission related to COVID-19.MethodsAn observational longitudinal study was conducted during the pandemic peak of severe acute respiratory syndrome coronavirus 2 (1 March 2020 to 24 April). All patients attended at the rheumatology outpatient clinic of a tertiary hospital in Madrid, Spain with a medical diagnosis of AIRD and with symptomatic COVID-19 were included. The main outcome was hospital admission related to COVID-19. The covariates were sociodemographic, clinical and treatments. We ran a multivariable logistic regression model to assess risk factors for the hospital admission.ResultsThe study population included 123 patients with AIRD and COVID-19. Of these, 54 patients required hospital admission related to COVID-19. The mean age on admission was 69.7 (15.7) years, and the median time from onset of symptoms to hospital admission was 5 (3–10) days. The median length of stay was 9 (6–14) days. A total of 12 patients died (22%) during admission. Compared with outpatients, the factors independently associated with hospital admission were older age (OR: 1.08; p=0.00) and autoimmune systemic condition (vs chronic inflammatory arthritis) (OR: 3.55; p=0.01). No statistically significant findings for exposure to disease-modifying antirheumatic drugs were found in the final model.ConclusionOur results suggest that age and having a systemic autoimmune condition increased the risk of hospital admission, whereas disease-modifying antirheumatic drugs were not associated with hospital admission.

River biofilms that grow on wet benthic surface are mainly composed of bacteria, algae, cyanobacteria and protozoa embedded in a polysaccharide matrix. The effects of increased river water temperature on biofilm formation were investigated. A laboratory experiment was designed employing two temperatures (11.1-13.2°C, night-day; 14.7-16.0°C, night-day) and two nutrient levels (0.054 mg P l(-1), 0.75 mg N l(-1); 0.54 mg P l(-1), 7.5 mg N l(-1)). Biofilm formation at the higher temperature was faster, while the biomass of the mature biofilm was mainly determined by nutrient availability. The specific response of the three microbial groups that colonized the substrata (algae, bacteria and ciliates) was modulated by interactions between them. The greater bacterial growth rate and earlier bacterial colonization at the higher temperature and higher nutrient status was not translated into the accrual of higher bacterial biomass. This may result from ciliates grazing on the bacteria, as shown by an earlier increase in peritrichia at higher temperatures, and especially at high nutrient conditions. Temperature and ciliate grazing might determine the growth of a distinctive bacterial community under warming conditions. Warmer conditions also produced a thicker biofilm, while functional responses were much less evident (increases in the heterotrophic utilization of polysaccharides and peptides, but no increase in primary production and respiration). Increasing the temperature of river water might lead to faster biofilm recolonization after disturbances, with a distinct biofilm community structure that might affect the trophic web. Warming effects would be expected to be more relevant under eutrophic conditions.

Aims: In this pandemic, it is essential for rheumatologists and patients to know the relationship between COVID-19 and inflammatory rheumatic diseases (IRDs). We wanted to assess the role of targeted synthetic or biologic disease-modifying antirheumatic drugs (ts/bDMARDs) and other variables in the development of moderate-severe COVID-19 disease in IRD. Methods: An observational longitudinal study was conducted during the epidemic peak in Madrid (1 March to 15 April 2020). All patients attended at the rheumatology outpatient clinic of a tertiary hospital in Madrid with a medical diagnosis of IRD were included. Main outcome: hospital admission related to COVID-19. Independent variable: ts/bDMARDs. Covariates: sociodemographic, comorbidities, type of IRD diagnosis, glucocorticoids, non-steroidal anti-inflammatory drugs (NSAIDs), and conventional synthetic disease-modifying antirheumatic drugs (csDMARDs). Incidence rate (IR) of hospital admission related to COVID-19 was expressed per 1000 patient-months. Cox multiple regression analysis was run to examine the influence of ts/bDMARDs and other covariates on IR of hospital admission related to COVID-19. Results: A total of 3951 IRD patients were included (5896 patient-months). Methotrexate was the csDMARD most used. Eight hundred and two patients were on ts/bDMARDs, mainly anti-TNF agents, and Rtx. Hospital admissions related to COVID-19 occurred in 54 patients (1.36%) with an IR of 9.15 (95% confidence interval: 7–11.9). In the multivariate analysis, older, male, comorbidities, and specific systemic autoimmune conditions (Sjögren, polychondritis, Raynaud, and mixed connective tissue disease) had more risk of hospital admissions. Exposition to ts/bDMARDs did not achieve statistical significance. Use of glucocorticoids, NSAIDs, and csDMARDs dropped from the final model. Conclusion: This study provides additional evidence in IRD patients regarding susceptibility to moderate–severe infection related to COVID-19.

Our objective is to develop and validate a predictive model based on the random forest algorithm to estimate the readmission risk to an outpatient rheumatology clinic after discharge. We included patients from the Hospital Clínico San Carlos rheumatology outpatient clinic, from 1 April 2007 to 30 November 2016, and followed-up until 30 November 2017. Only readmissions between 2 and 12 months after the discharge were analyzed. Discharge episodes were chronologically split into training, validation, and test datasets. Clinical and demographic variables (diagnoses, treatments, quality of life (QoL), and comorbidities) were used as predictors. Models were developed in the training dataset, using a grid search approach, and performance was compared using the area under the receiver operating characteristic curve (AUC-ROC). A total of 18,662 discharge episodes were analyzed, out of which 2528 (13.5%) were followed by outpatient readmissions. Overall, 38,059 models were developed. AUC-ROC, sensitivity, and specificity of the reduced final model were 0.653, 0.385, and 0.794, respectively. The most important variables were related to follow-up duration, being prescribed with disease-modifying anti-rheumatic drugs and corticosteroids, being diagnosed with chronic polyarthritis, occupation, and QoL. We have developed a predictive model for outpatient readmission in a rheumatology setting. Identification of patients with higher risk can optimize the allocation of healthcare resources.

Background: In this pandemia, it is essential for rheumatologist and patients to know the relationship between COVID-19 and inflammatory rheumatic diseases (IRD). We want to assess the role of targeted synthetic or biologic disease modifying antirheumatic drugs (ts/bDMARDs) and other variables in the development of moderate-severe COVID-19 disease in IRD. Methods: An observational longitudinal study was conducted (1stMar to 15thApr 2020). All patients from the rheumatology outpatient clinic from a hospital in Madrid with a medical diagnosis of IRD were included. Main outcome: hospital admission related to COVID-19. Independent variable: ts/bDMARDs. Covariates: sociodemographic, comorbidities, type of IRD diagnosis, glucocorticoids, NSAIDs and conventional synthetic DMARDs (csDMARDs). Incidence rate (IR) of hospital admission related to COVID-19, was expressed per 1,000 patients-month. Cox multivariate regression analysis was run to examine the influence of ts/bDMARDs and other covariates on IR. Results: 3,591 IRD patients were included (5,896 patients-month). Concerning csDMARDs, methotrexate was the most used followed by antimalarials. 802 patients were on ts/bDMARDs, mainly anti-TNF agents, and rituximab. Hospital admissions related to COVID-19 occurred in 54 patients (1.36%) with an IR of 9.15 [95%CI: 7-11.9]. In the multivariate analysis, older, male gender, presence of comorbidities and specific systemic autoimmune conditions (Sjoegren, polychondritis, Raynaud and mixed connective tissue disease) had more risk of hospital admissions regardless other factors. Exposition to ts/bDMARDs did not achieve statistical signification. Use of glucocorticoids, NSAIDs, and csDMARDs dropped from the final model. Conclusion: This study provides additional evidence in IRD patients regarding susceptibility to moderate-severe infection related to COVID-19.