COVID-19 Infection: Implications for Perioperative and Critical Care Physicians.

Healthcare systems worldwide are responding to Coronavirus Disease 2019 (COVID-19), an emerging infectious syndrome caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus. Patients with COVID-19 can progress from asymptomatic or mild illness to hypoxemic respiratory failure or multisystem organ failure, necessitating intubation and intensive care management. Healthcare providers, and particularly anesthesiologists, are at the frontline of this epidemic, and they need to be aware of the best available evidence to guide therapeutic management of patients with COVID-19 and to keep themselves safe while doing so. Here, the authors review COVID-19 pathogenesis, presentation, diagnosis, and potential therapeutics, with a focus on management of COVID-19-associated respiratory failure. The authors draw on literature from other viral epidemics, treatment of acute respiratory distress syndrome, and recent publications on COVID-19, as well as guidelines from major health organizations. This review provides a comprehensive summary of the evidence currently available to guide management of critically ill patients with COVID-19

Nonexponential decay of an unstable quantum system: Small-QQ-value s-wave decay

We study the decay process of an unstable quantum system, especially the deviation from the exponential decay law. We show that the exponential period no longer exists in the case of the s-wave decay with small $Q$ value, where the $Q$ value is the difference between the energy of the initially prepared state and the minimum energy of the continuous eigenstates in the system. We also derive the quantitative condition that this kind of decay process takes place and discuss what kind of system is suitable to observe the decay.Comment: 17 pages, 6 figure

Hierarchical Regression for Multiple Comparisons in a Case-Control Study of Occupational Risks for Lung Cancer

BACKGROUND Occupational studies often involve multiple comparisons and therefore suffer from false positive findings. Semi-Bayes adjustment methods have sometimes been used to address this issue. Hierarchical regression is a more general approach, including Semi-Bayes adjustment as a special case, that aims at improving the validity of standard maximum-likelihood estimates in the presence of multiple comparisons by incorporating similarities between the exposures of interest in a second-stage model. METHODOLOGY/PRINCIPAL FINDINGS We re-analysed data from an occupational case-control study of lung cancer, applying hierarchical regression. In the second-stage model, we included the exposure to three known lung carcinogens (asbestos, chromium and silica) for each occupation, under the assumption that occupations entailing similar carcinogenic exposures are associated with similar risks of lung cancer. Hierarchical regression estimates had smaller confidence intervals than maximum-likelihood estimates. The shrinkage toward the null was stronger for extreme, less stable estimates (e.g., "specialised farmers": maximum-likelihood OR: 3.44, 95%CI 0.90-13.17; hierarchical regression OR: 1.53, 95%CI 0.63-3.68). Unlike Semi-Bayes adjustment toward the global mean, hierarchical regression did not shrink all the ORs towards the null (e.g., "Metal smelting, converting and refining furnacemen": maximum-likelihood OR: 1.07, Semi-Bayes OR: 1.06, hierarchical regression OR: 1.26). CONCLUSIONS/SIGNIFICANCE Hierarchical regression could be a valuable tool in occupational studies in which disease risk is estimated for a large amount of occupations when we have information available on the key carcinogenic exposures involved in each occupation. With the constant progress in exposure assessment methods in occupational settings and the availability of Job Exposure Matrices, it should become easier to apply this approach

A flexible Bayesian hierarchical model of preterm birth risk among US Hispanic subgroups in relation to maternal nativity and education

<p>Abstract</p> <p>Background</p> <p>Previous research has documented heterogeneity in the effects of maternal education on adverse birth outcomes by nativity and Hispanic subgroup in the United States. In this article, we considered the risk of preterm birth (PTB) using 9 years of vital statistics birth data from New York City. We employed finer categorizations of exposure than used previously and estimated the risk dose-response across the range of education by nativity and ethnicity.</p> <p>Methods</p> <p>Using Bayesian random effects logistic regression models with restricted quadratic spline terms for years of completed maternal education, we calculated and plotted the estimated posterior probabilities of PTB (gestational age < 37 weeks) for each year of education by ethnic and nativity subgroups adjusted for only maternal age, as well as with more extensive covariate adjustments. We then estimated the posterior risk difference between native and foreign born mothers by ethnicity over the continuous range of education exposures.</p> <p>Results</p> <p>The risk of PTB varied substantially by education, nativity and ethnicity. Native born groups showed higher absolute risk of PTB and declining risk associated with higher levels of education beyond about 10 years, as did foreign-born Puerto Ricans. For most other foreign born groups, however, risk of PTB was flatter across the education range. For Mexicans, Central Americans, Dominicans, South Americans and "Others", the protective effect of foreign birth diminished progressively across the educational range. Only for Puerto Ricans was there no nativity advantage for the foreign born, although small numbers of foreign born Cubans limited precision of estimates for that group.</p> <p>Conclusions</p> <p>Using flexible Bayesian regression models with random effects allowed us to estimate absolute risks without strong modeling assumptions. Risk comparisons for any sub-groups at any exposure level were simple to calculate. Shrinkage of posterior estimates through the use of random effects allowed for finer categorization of exposures without restricting joint effects to follow a fixed parametric scale. Although foreign born Hispanic women with the least education appeared to generally have low risk, this seems likely to be a marker for unmeasured environmental and behavioral factors, rather than a causally protective effect of low education itself.</p

Re-interpreting conventional interval estimates taking into account bias and extra-variation

BACKGROUND: The study design with the smallest bias for causal inference is a perfect randomized clinical trial. Since this design is often not feasible in epidemiologic studies, an important challenge is to model bias properly and take random and systematic variation properly into account. A value for a target parameter might be said to be "incompatible" with the data (under the model used) if the parameter's confidence interval excludes it. However, this "incompatibility" may be due to bias and/or extra-variation. DISCUSSION: We propose the following way of re-interpreting conventional results. Given a specified focal value for a target parameter (typically the null value, but possibly a non-null value like that representing a twofold risk), the difference between the focal value and the nearest boundary of the confidence interval for the parameter is calculated. This represents the maximum correction of the interval boundary, for bias and extra-variation, that would still leave the focal value outside the interval, so that the focal value remained "incompatible" with the data. We describe a short example application concerning a meta analysis of air versus pure oxygen resuscitation treatment in newborn infants. Some general guidelines are provided for how to assess the probability that the appropriate correction for a particular study would be greater than this maximum (e.g. using knowledge of the general effects of bias and extra-variation from published bias-adjusted results). SUMMARY: Although this approach does not yet provide a method, because the latter probability can not be objectively assessed, this paper aims to stimulate the re-interpretation of conventional confidence intervals, and more and better studies of the effects of different biases

Melody Girl

Illustration of woman playing piano and man sitting in chair smokinghttps://scholarsjunction.msstate.edu/cht-sheet-music/6488/thumbnail.jp

Vasectomy, cigarette smoking, and age at first sexual intercourse as risk factors for prostate cancer in middle-aged men.

A population-based case-control study was conducted in men aged 60 or less to assess the risk of prostate cancer associated with vasectomy and other factors. Data were obtained from 216 case-control pairs by telephone interviews; this number represented 55% of all eligible cases. The matched pairs relative risk (RR) for vasectomy in ever married men was 1.4 with a 95% confidence interval (CI) of 0.9-2.3. There was a positive association between the number of years since vasectomy and prostate cancer risk (1-sided P = 0.01). Early age at first sexual intercourse was associated with increased prostate cancer risk (age less than 17 vs. 21+, RR = 2.3, 95% CI = 1.3, 4.0) but there were no consistent associations with number of sexual partners or frequency of sexual intercourse. Cigarette smoking was also associated with increased risk of prostate cancer (RR = 1.9, 95% CI = 1.2, 3.0) and there was a positive dose-response relationship with years of smoking (1-sided P = 0.001). We discuss the possible implication of the low response rate on each of these findings. To determine whether the association with vasectomy might have a hormonal basis, we compared levels of testosterone (T) and testosterone binding globulin-binding capacity (TeBG-bc) in 33 of the vasectomized control men with levels in 33 non-vasectomized controls of the same age, weight and height. T levels were higher in vasectomized than in non-vasectomized controls (1-sided P = 0.06). The ratio of T to TeBG-bc (an index of bioavailable T) was 13.5% higher in vasectomized men (1-sided P = 0.03)

Association of 6-Minute Walk Performance and Physical Activity With Incident Ischemic Heart Disease Events and Stroke in Peripheral Artery Disease.

BackgroundWe determined whether poorer 6-minute walk performance and lower physical activity levels are associated with higher rates of ischemic heart disease (IHD) events in people with lower extremity peripheral artery disease (PAD).Methods and resultsFive hundred ten PAD participants were identified from Chicago-area medical centers and followed prospectively for 19.0±9.5 months. At baseline, participants completed the 6-minute walk and reported number of blocks walked during the past week (physical activity). IHD events were systematically adjudicated and consisted of new myocardial infarction, unstable angina, and cardiac death. For 6-minute walk, IHD event rates were 25/170 (14.7%) for the third (poorest) tertile, 10/171 (5.8%%) for the second tertile, and 6/169 (3.5%) for the first (best) tertile (P=0.003). For physical activity, IHD event rates were 21/154 (13.6%) for the third (poorest) tertile, 15/174 (8.6%) for the second tertile, and 5/182 (2.7%) for the first (best) tertile (P=0.001). Adjusting for age, sex, race, smoking, body mass index, comorbidities, and physical activity, participants in the poorest 6-minute walk tertile had a 3.28-fold (95% CI 1.17 to 9.17, P=0.024) higher hazard for IHD events, compared with those in the best tertile. Adjusting for confounders including 6-minute walk, participants in the poorest physical activity tertile had a 3.72-fold (95% CI 1.24 to 11.19, P=0.019) higher hazard for IHD events, compared with the highest tertile.ConclusionsSix-minute walk and physical activity predict IHD event rates in PAD. Further study is needed to determine whether interventions that improve 6-minute walk, physical activity, or both can reduce IHD events in PAD

Tuning thermal properties and microphase separation in aliphatic polyester ABA copolymers

Four alkyl substituted β-lactones were investigated as monomers in ring opening polymerisation to produce a family of poly(3-hydroxyalkanoate)s. Homopolymers were synthesised using a robust aluminium salen catalyst, resulting in polymers with low dispersity (Đ < 1.1) and predictable molecular weights. ABA triblock copolymers were prepared using poly(L-lactic acid) as the A block and the afore- mentioned poly(3-hydroxyalkanoate) as the B block via a sequential addition method. Characterisation of these copolymers determined they were well controlled with low dispersities and predictable molecular weight. DSC analysis determined copolymers prepared from β-butyrolactone or β-valerolactone yielded polymers with tunable and predictable thermal properties. Copolymers prepared from β-heptanolactone yielded a microphase separated material as indicated by SAXS, with two distinct Tgs. The polymers could be readily cast into flexible films and their improved tensile properties were explored