Conclusion: There are at least 6 biomarkers where higher concentrations are associated with an increased risk of abdominal aortic aneurysm (AAA). Summary: Most important clinical risk factors for AAA have been identified through epidemiologic studies. They include advanced age, male sex, white race, smoking and family history. AAA pathophysiology involves inflammatory cells infiltrating the wall of the aorta with proteolysis of elastin and collagen in the media and adventitia. There is also smooth muscle cell apoptosis associated with thinning of the media (Nordon IM et al, Nat Rev Cardiol 2011;8:92-102). Some studies have also identified circulating inflammatory hemostatic proteolytic and extracellular matrix biomarkers associated with AAA presence or progression (Golledge J et al, Circulation 2008;118:2382-92). However, few studies have examined multiple biomarkers simultaneously. The authors focused on already measured biomarkers in the Atherosclerosis Risk in Communities (ARIC) cohort, to examine association of multiple circulating biomarkers with incident AAA. Biomarkers of inflammation, hemostasis, thrombin generation, cardiac dysfunction and vascular stiffness were identified with incident AAAs during follow-up using hospital discharge codes in the ARIC cohort. Six biomarkers (white blood cell count, fibrinogen, D-dimer, troponin T, N-terminal pro-brain natriuretic peptide and high-sensitivity C-reactive protein) were strongly associated with AAA incidence. Compared with having none of these 6 biomarkers in the highest quartile, hazard ratios for AAA with those with 1, 2, 3, 4, or 6 biomarkers in the highest quartile were 2, 3.3, 4.0, and 9.9, respectively (P for trend <.0001) after adjustment for other risk factors. Comment: The authors' results suggest that multiple positive biomarkers can identify a subgroup of patients at high risk for AAA. However, biomarkers in this study were measured only once and not at the same time. Biologic availability or change over time in biomarkers potentially could attenuate or enhance reported hazard ratios. In addition, the authors were not able to consider biomarkers such as procollagen or its degradation products. A failure to account for these and other potential biomarkers could also potentially overestimate or underestimate hazard ratios. Finally, the study documents as association of biomarkers with AAA but not a cause and effect relationship.

Background The COVID-19 pandemic has led highly developed healthcare systems to the brink of collapse due to the large numbers of patients being admitted into hospitals. One of the potential prognostic indicators in patients with COVID-19 is frailty. The degree of frailty could be used to assist both the triage into intensive care, and decisions regarding treatment limitations. Our study sought to determine the interaction of frailty and age in elderly COVID-19 ICU patients. Methods A prospective multicentre study of COVID-19 patients ≥ 70 years admitted to intensive care in 138 ICUs from 28 countries was conducted. The primary endpoint was 30-day mortality. Frailty was assessed using the clinical frailty scale. Additionally, comorbidities, management strategies and treatment limitations were recorded. Results The study included 1346 patients (28% female) with a median age of 75 years (IQR 72–78, range 70–96), 16.3% were older than 80 years, and 21% of the patients were frail. The overall survival at 30 days was 59% (95% CI 56–62), with 66% (63–69) in fit, 53% (47–61) in vulnerable and 41% (35–47) in frail patients (p < 0.001). In frail patients, there was no difference in 30-day survival between different age categories. Frailty was linked to an increased use of treatment limitations and less use of mechanical ventilation. In a model controlling for age, disease severity, sex, treatment limitations and comorbidities, frailty was independently associated with lower survival. Conclusion Frailty provides relevant prognostic information in elderly COVID-19 patients in addition to age and comorbidities. Trial registration Clinicaltrials.gov: NCT04321265, registered 19 March 2020.

No abstract

The funder had no role in the design and conduct of the study, collection, management, analysis,

Rational To evaluate the respective impact of standard oxygen, high-flow nasal cannula (HFNC) and noninvasive ventilation (NIV) on oxygenation failure rate and mortality in COVID-19 patients admitted to intensive care units (ICUs). Methods Multicenter, prospective cohort study (COVID-ICU) in 137 hospitals in France, Belgium, and Switzerland. Demographic, clinical, respiratory support, oxygenation failure, and survival data were collected. Oxygenation failure was defined as either intubation or death in the ICU without intubation. Variables independently associated with oxygenation failure and Day-90 mortality were assessed using multivariate logistic regression. Results From February 25 to May 4, 2020, 4754 patients were admitted in ICU. Of these, 1491 patients were not intubated on the day of ICU admission and received standard oxygen therapy (51%), HFNC (38%), or NIV (11%) (P < 0.001). Oxygenation failure occurred in 739 (50%) patients (678 intubation and 61 death). For standard oxygen, HFNC, and NIV, oxygenation failure rate was 49%, 48%, and 60% (P < 0.001). By multivariate analysis, HFNC (odds ratio [OR] 0.60, 95% confidence interval [CI] 0.36–0.99, P = 0.013) but not NIV (OR 1.57, 95% CI 0.78–3.21) was associated with a reduction in oxygenation failure). Overall 90-day mortality was 21%. By multivariable analysis, HFNC was not associated with a change in mortality (OR 0.90, 95% CI 0.61–1.33), while NIV was associated with increased mortality (OR 2.75, 95% CI 1.79–4.21, P < 0.001). Conclusion In patients with COVID-19, HFNC was associated with a reduction in oxygenation failure without improvement in 90-day mortality, whereas NIV was associated with a higher mortality in these patients. Randomized controlled trials are needed.