Notes

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6% (15/110) had initial visits resulting in hospitalization compared to 3.1% (4/127) of included participants (
 = .003). The rate of emergency department visits within 28 days was similar in both groups. Clinical and microbiological failures were significantly more common in included patients [26% (33/127) vs. 1.8% (2/110),
 < .001; 7.9% (10/127) vs. 0% (0/110),
 = .003; respectively].

While differences were observed between included and excluded patients, the excluded group did not represent a more 'complicated' population. The present study shows the importance of collecting data on patients excluded from randomized controlled trials.
While differences were observed between included and excluded patients, the excluded group did not represent a more 'complicated' population. The present study shows the importance of collecting data on patients excluded from randomized controlled trials.
The area of ligand efficiency indices (LEIs) in drug discovery has developed significantly since the initial publications nearly 20 years ago. A large number of different LEIs have been defined and applied with certain degrees of success and acceptance in the community. An overall view emphasizing more the common elements than the differences is needed.

In this review, the author accentuates the numerical and algebraic relationships among the different LEIs and proposes the notion of 'ligand efficiency index' (LEI) as a vector variable comprising two interrelated components that provide 'direction' and 'distance' along the drug discovery process. The same concept had been suggested before relating to the graphical representation of the content of Structure-Activity Databases (SAR-Databases).

The extension of the concept of ligand efficiency from a scalar to a vector will help to unify the different formulations by emphasizing the relationship among the different variables. It should also provide an algebraically robust framework to critically assess the value of LEIs, and to incorporate them routinely in various workflows and protocols. Only cautious and rigorous testing by the community could provide a definitive proof of their possible value as reliable optimization variables in drug discovery.
The extension of the concept of ligand efficiency from a scalar to a vector will help to unify the different formulations by emphasizing the relationship among the different variables. It should also provide an algebraically robust framework to critically assess the value of LEIs, and to incorporate them routinely in various workflows and protocols. Only cautious and rigorous testing by the community could provide a definitive proof of their possible value as reliable optimization variables in drug discovery.
The coronavirus 2019 (COVID-19) pandemic has resulted in profound global impact, with older adults at greater risk of serious physical health outcomes. It is essential to also understand generational differences in psychosocial impacts to identify appropriate prevention and intervention targets. Across generational groups, this study examined (1) rates of precautions and adaptive and maladaptive health behaviors, (2) differences in levels of anxiety, and (3) rates of COVID-related concerns during Wave 1 of COVID-19 in Canada.

We analyzed data from 2 Canadian population-based data sets the Canadian Perspective Survey Series Impact of COVID-19 survey (
= 4,627; March 29 to April 3, 2020), and Crowdsourcing Impacts of COVID-19 on Canadians-Your Mental Health (
= 45,989; April 24 to May 11, 2020).

We categorized generational age group. Participants self-reported changes in behaviors and COVID-related concerns, and a validated measure assessed anxiety symptoms.

There are generational differences in behavioral responses to the pandemic. Adaptive health habits (e.g., exercise) were comparable across groups, while changes in maladaptive health habits (e.g., substance use) were highest among younger age groups, particularly Millennials (15 to 34 years old). COVID-related precautions were also highest among the younger generations, with Generation X (35 to 54 years old) exhibiting the highest rate of precautionary behavior. Results also revealed that the highest rate of clinically significant anxiety is among Millennials (36.0%; severe anxiety = 15.7%), and the younger generations have the highest rates of COVID-related concerns.

These early data are essential in understanding at-risk groups given the unpredictable nature of the pandemic and its potential long-term implications.
These early data are essential in understanding at-risk groups given the unpredictable nature of the pandemic and its potential long-term implications.
Popliteal artery injury is associated with a high risk of limb loss; identifying factors associated with increased morbidity and mortality is hampered by its rare occurrence and confounding factors. Anecdotal observations suggest delay in diagnosis of obese patients may be associated with amputation. this website We aimed to determine whether there is an increased risk of early amputation and if diagnosis is delayed in obese patients with popliteal artery injuries.

We conducted a retrospective cohort study using National Trauma Data Bank (NTDB) data from 2013 to 2017. We extracted those sustaining popliteal artery injury, assigning obesity class based on body mass index. We included select demographic and clinical variables, using time to imaging as a surrogate for time to diagnosis. Statistical models were used to calculate the impact of obesity on amputation rates and time to diagnosis.

We identified 4803 popliteal artery injuries in the data set; 3289 met inclusion criteria. We calculated an 8.5% overall amputation rate, which was not significantly different between obese (N = 1305; 39.7%) and nonobese (N = 1984; 60.3%) patients. Statistical analysis identified peripheral vascular disease, diabetes, and smoking as risk factors for amputation. Time to imaging was similar for obese and nonobese patients.

Analysis of NTDB data suggests that obesity is associated with neither increased early amputation rate nor longer time to imaging in patients with popliteal artery injury. However, our study suggests that underlying comorbidities of peripheral vascular disease and diabetes are associated with an increased risk for amputation in these patients.
Analysis of NTDB data suggests that obesity is associated with neither increased early amputation rate nor longer time to imaging in patients with popliteal artery injury. However, our study suggests that underlying comorbidities of peripheral vascular disease and diabetes are associated with an increased risk for amputation in these patients.
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