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Background COVID‐19 disease progression is characterized by hyperinflammation and risk stratification may aid in early aggressive treatment and advanced planning. The aim of this study was to assess whether suPAR and other markers measured at hospital admission can predict the severity of COVID‐19. Methods The primary outcome measure in this international, multi‐centre, prospective, observational study with adult patients hospitalized primarily for COVID‐19 was the association of WHO Clinical Progression Scale (WHO‐CPS) with suPAR, ferritin, CRP, albumin, LDH, eGFR, age, procalcitonin, and interleukin‐6. Admission plasma suPAR levels were determined using the suPARnostic ® ELISA and suPARnostic ® Turbilatex assays. Results Seven hundred and sixty‐seven patients, 440 (57.4%) males and 327 (42.6%) females, were included with a median age of 64 years. Log‐suPAR levels significantly correlated with WHO‐CPS score, with each doubling of suPAR increasing the score by one point ( p < .001). All the other markers were also correlated with WHO‐CPS score. Admission suPAR levels were significantly lower in survivors (7.10 vs. 9.63, 95% CI 1.47–3.59, p < .001). A linear model (SALGA) including suPAR, serum albumin, serum lactate dehydrogenase, eGFR, and age can best estimate the WHO‐CPS score and survival. Combining all five parameters in the SALGA model can improve the accuracy of discrimination with an AUC of 0.80 (95% CI: 0.759–0.836). Conclusions suPAR levels significantly correlated with WHO‐CPS score, with each doubling of suPAR increasing the score by one point. The SALGA model may serve as a quick tool for predicting disease severity and survival at admission.

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Osteoporosis is the prevalent cause of fractures in an ever-aging population, with an established correlation between daily activities and way of life. We aimed to delineate differences in onset of osteoporosis, T-score progression, quality of life, and correlation to prevalence, types, and severity of fractures in age-comparable populations of rural and metropolitan habitats in this multicenter, retrospective double-blind study. We evaluated data derived from the medical files of two comparable groups of osteoporotic patients: group A (n = 530, rural area) and group B (n = 171, metropolitan area). Both groups received comparable treatment for osteoporosis. Comparison was performed on the basis of osteoporosis onset, T-score in a maximum of 8 years follow-up, fracture types [American Academy of Orthopaedic Surgeons (AO) categorization], and type of treatment followed. Quality of life was assessed by use of specialized questionnaires. From the minimum 4-year follow-up of all patients included in the research, there was a statistically significant difference in favor of the rural population in all research parameters. Rural populations presented with osteoporosis at a later age than their metropolitan counterparts, exhibiting favorable T-scores with comparable treatments and simpler fractures (AO categorization). Metropolitan habitats and life therein have a deleterious effect on osteoporosis onset and response to treatment. Rural populations are diagnosed with osteoporosis on a later age, with better compliance and improved treatment outcome. Fracture categorization shows increased severity in the metropolitan populace and a suggested correlation between a poor-quality way of life and decreased activity levels.