Background The impact of statins on COVID-19 outcomes is important given the high prevalence of their use among individuals at risk for severe COVID-19. Our aim is to assess whether patients receiving chronic statin treatment who are hospitalized with COVID-19 have reduced in-hospital mortality if statin therapy is maintained during hospitalization. Methods This work is a cross-sectional, observational, retrospective multicenter study that analyzed 2921 patients who required hospital admission at 150 Spanish centers included in the nationwide SEMI-COVID-19 Network. We compared the clinical characteristics and COVID-19 disease outcomes between patients receiving chronic statin therapy who maintained this therapy during hospitalization versus those who did not. Propensity score matching was used to match each statin user whose therapy was maintained during hospitalization to a statin user whose therapy was withdrawn during hospitalization. Results After propensity score matching, continuation of statin therapy was associated with lower all-cause mortality (OR 0.67, 0.54–0.83, p < 0.001); lower incidence of acute kidney injury (AKI) (OR 0.76,0.6–0.97, p = 0.025), acute respiratory distress syndrome (ARDS) (OR 0.78, 0.69- 0.89, p < 0.001), and sepsis (4.82% vs 9.85%, p = 0.008); and less need for invasive mechanical ventilation (IMV) (5.35% vs 8.57, p < 0.001) compared to patients whose statin therapy was withdrawn during hospitalization. Conclusions Patients previously treated with statins who are hospitalized for COVID-19 and maintain statin therapy during hospitalization have a lower mortality rate than those in whom therapy is withdrawn. In addition, statin therapy was associated with a decreased probability that patients with COVID-19 will develop AKI, ARDS, or sepsis and decreases the need for IMV.

3D imaging of the bone vasculature is of key importance in the understanding of skeletal disease. As blood vessels in bone are deeply encased in the calcified matrix, imaging techniques that are applicable to soft tissues are generally difficult or impossible to apply to the skeleton. While canals in cortical bone can readily be identified and characterised in X-ray computed tomographic data in 3D, the soft tissue comprising blood vessels that are putatively contained within the canal structures does not provide sufficient image contrast necessary for image segmentation. Here, we report an approach that allows for rapid, simultaneous visualisation of calcified bone tissue and the vasculature within the calcified bone matrix. Using synchrotron X-ray phase contrast-enhanced tomography we show exemplar data with intracortical capillaries uncovered at sub-micrometre level without the need for any staining or contrast agent. Using the tibiofibular junction of 15 week-old C57BL/6 mice post mortem, we show the bone cortical porosity simultaneously along with the soft tissue comprising the vasculature. Validation with histology confirms that we can resolve individual capillaries. This imaging approach could be easily applied to other skeletal sites and transgenic models, and could improve our understanding of the role the vasculature plays in bone disease.

Background. Spain has been one of the countries most affected by the COVID-19 pandemic. Objective. To create a registry of patients with COVID-19 hospitalized in Spain in order to improve our knowledge of the clinical, diagnostic, therapeutic, and prognostic aspects of this disease. Methods. A multicentre retrospective cohort study, including consecutive patients hospitalized with confirmed COVID-19 throughout Spain. Epidemiological and clinical data, additional tests at admission and at seven days, treatments administered, and progress at 30 days of hospitalization were collected from electronic medical records. Results. Up to April 30th 2020, 6,424 patients from 109 hospitals were included. Their median age was 69.1 years (range: 18-102 years) and 56.9% were male. Prevalences of hypertension, dyslipidemia, and diabetes mellitus were 50.2%, 39.7%, and 18.7%, respectively. The most frequent symptoms were fever (86.2%) and cough (76.5%). High values of ferritin (72.4%), lactate dehydrogenase (70.2%), and D-dimer (61.5%), as well as lymphopenia (52.6%), were frequent. The most used antiviral drugs were hydroxychloroquine (85.7%) and lopinavir/ritonavir (62.4%). 31.5% developed respiratory distress. Overall mortality rate was 21.1%, with a marked increase with age (50-59 years: 4.2%, 60-69 years: 9.1%, 70-79 years: 21.4%, 80-89 years: 42.5%, ≥ 90 years: 51.1%). Conclusions. The SEMI-COVID-19 Network provides data on the clinical characteristics of patients with COVID-19 hospitalized in Spain. Patients with COVID-19 hospitalized in Spain are mostly severe cases, as one in three patients developed respiratory distress and one in five patients died. These findings confirm a close relationship between advanced age and mortality.

Background The WHO ordinal severity scale has been used to predict mortality and guide trials in COVID-19. However, it has its limitations. Objective The present study aims to compare three classificatory and predictive models: the WHO ordinal severity scale, the model based on inflammation grades, and the hybrid model. Design Retrospective cohort study with patient data collected and followed up from March 1, 2020, to May 1, 2021, from the nationwide SEMI-COVID-19 Registry. The primary study outcome was in-hospital mortality. As this was a hospital-based study, the patients included corresponded to categories 3 to 7 of the WHO ordinal scale. Categories 6 and 7 were grouped in the same category. Key Results A total of 17,225 patients were included in the study. Patients classified as high risk in each of the WHO categories according to the degree of inflammation were as follows: 63.8% vs. 79.9% vs. 90.2% vs. 95.1% ( p <0.001). In-hospital mortality for WHO ordinal scale categories 3 to 6/7 was as follows: 0.8% vs. 24.3% vs. 45.3% vs. 34% ( p <0.001). In-hospital mortality for the combined categories of ordinal scale 3a to 5b was as follows: 0.4% vs. 1.1% vs. 11.2% vs. 27.5% vs. 35.5% vs. 41.1% ( p <0.001). The predictive regression model for in-hospital mortality with our proposed combined ordinal scale reached an AUC=0.871, superior to the two models separately. Conclusions The present study proposes a new severity grading scale for COVID-19 hospitalized patients. In our opinion, it is the most informative, representative, and predictive scale in COVID-19 patients to date. Supplementary Information The online version contains supplementary material available at 10.1007/s11606-022-07511-7.

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