Background During the COVID-19 pandemic, the scarcity of resources has necessitated triage of critical care for patients with the disease. In patients aged 65 years and older, triage decisions are regularly based on degree of frailty measured by the Clinical Frailty Scale (CFS). However, the CFS could also be useful in patients younger than 65 years. We aimed to examine the association between CFS score and hospital mortality and between CFS score and admission to intensive care in adult patients of all ages with COVID-19 across Europe. Methods This analysis was part of the COVID Medication (COMET) study, an international, multicentre, retrospective observational cohort study in 63 hospitals in 11 countries in Europe. Eligible patients were aged 18 years and older, had been admitted to hospital, and either tested positive by PCR for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or were judged to have a high clinical likelihood of having SARS-CoV-2 infection by the local COVID-19 expert team. CFS was used to assess level of frailty: fit (CFS 1-3), mildly frail (CFS 4-5), or frail (CFS 6-9). The primary outcome was hospital mortality. The secondary outcome was admission to intensive care. Data were analysed using a multivariable binary logistic regression model adjusted for covariates (age, sex, number of drugs prescribed, and type of drug class as a proxy for comorbidities). Findings Between March 30 and July 15, 2020, 2434 patients (median age 68 years [IQR 55-77]; 1480 [61%] men, 954 [30%] women) had CFS scores available and were included in the analyses. In the total sample and in patients aged 65 years and older, frail patients and mildly frail patients had a significantly higher risk of hospital mortality than fit patients (total sample: CFS 6-9 vs CFS 1-3 odds ratio [OR] 2•71 [95% CI 2•04-3•60], p<0•0001 and CFS 4-5 vs CFS 1-3 OR 1•54 [1•16-2•06], p=0•0030; age ≥65 years: CFS 6-9 vs CFS 1-3 OR 2•90 [2•12-3•97], p<0•0001 and CFS 4-5 vs CFS 1-3 OR 1•64 [1•20-2•25], p=0•0020). In patients younger than 65 years, an increased hospital mortality risk was only observed in frail patients (CFS 6-9 vs CFS 1-3 OR 2•22 [1•08-4•57], p=0•030; CFS 4-5 vs CFS 1-3 OR 1•08 [0•48-2•39], p=0•86). Frail patients had a higher incidence of admission to intensive care than fit patients (CFS 6-9 vs CFS 1-3 OR 1•54 [1•21-1•97], p=0•0010), whereas mildly frail patients had a lower incidence than fit patients (CFS 4-5 vs CFS 1-3 OR 0•71 [0•55-0•92], p=0•0090). Among patients younger than 65 years, frail patients had an increased incidence of admission to intensive care (CFS 6-9 vs CFS 1-3 OR 2•96 [1•98-4•43], p<0•0001), whereas mildly frail patients had no significant difference in incidence compared with fit patients (CFS 4-5 vs CFS 1-3 OR 0•93 [0•63-1•38], p=0•72). Among patients aged 65 years and older, frail patients had no significant difference in the incidence of admission to intensive care compared with fit patients (CFS 6-9 vs CFS 1-3 OR 1•27 [0•92-1•75], p=0•14), whereas mildly frail patients had a lower incide...

Bacterial protein toxins are powerful tools for elucidating signaling mechanisms in eukaryotic cells. A number of bacterial protein toxins, e.g. cholera toxin, pertussis toxin (PTx), or Pasteurella multocida toxin (PMT), target heterotrimeric G proteins and have been used to stimulate or block specific signaling pathways or to demonstrate the contribution of their target proteins in cellular effects. PMT is a major virulence factor of P. multocida causing pasteurellosis in man and animals and is responsible for atrophic rhinitis in pigs. PMT modulates various signaling pathways, including phospholipase C␤ and RhoA, by acting on the heterotrimeric G proteins G␣ q and G␣ 12/13 , respectively. Here we report that PMT is a powerful activator of G i protein. We show that PMT decreases basal isoproterenol and forskolin-stimulated cAMP accumulation in intact Swiss 3T3 cells, inhibits adenylyl cyclase activity in cell membrane preparations, and enhances the inhibition of cAMP accumulation caused by lysophosphatidic acid via endothelial differentiation gene receptors. PMT-mediated inhibition of cAMP production is independent of toxin activation of G␣ q and/or G␣ 12/13 . Although the effects of PMT are not inhibited by PTx, PMT blocks PTx-catalyzed ADP-ribosylation of G i . PMT also inhibits steadystate GTPase activity and GTP binding of G i in Swiss 3T3 cell membranes stimulated by lysophosphatidic acid. The data indicate that PMT is a novel activator of G i , modulating its GTPase activity and converting it into a PTx-insensitive state.

Some anti-cancer treatments (e. g., immunotherapies) determine, on the long term, a durable survival in a small percentage of treated patients; in graphical terms, long-term survivors typically give rise to a plateau in the right tail of the survival curve. In analysing these datasets, medians are unable to recognize the presence of this plateau. To account for long-term survivors, both value-frameworks of ASCO and ESMO have incorporated post-hoc corrections that upgrade the framework scores when a survival plateau is present. However, the empiric nature of these post-hoc corrections is self-evident. To capture the presence of a survival plateau by quantitative methods, two approaches have thus far been proposed: the milestone method and the area-under-the-curve (AUC) method. The first approach identifies a long-term time-point in the follow-up (“milestone”) at which survival percentages are extracted. The second approach, which is based on the measurement of AUC of survival curves, essentially is the rearrangement of previous methods determining mean lifetime survival; similarly to the milestone method, the application of AUC can be “restricted” to a pre-specified time-point of the follow-up. This Mini-Review examines the literature published on this topic. The main characteristics of these two methods are highlighted along with their advantages and disadvantages. The conclusion is that both the milestone method and the AUC method are able to capture the presence of a survival plateau.

The restricted mean survival time (RMST) is a relatively new parameter proposed to improve the analysis of survival curves. As opposed to the median, the RMST has the advantage of capturing the overall shape of the survival curve, including the so-called "right tail." One limitation of RMST lies in the mathematical complexity of its calculation (model-dependent analysis). In the present report, we describe a model-independent method that simplifies the calculation of RMST. The estimation approach (trapezoidal rule) is the same as that commonly employed in pharmacokinetics. In the analysis of 6 survival curves, the performance of the model-independent method was virtually the same as that of model-dependent methods.

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