Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Hierarchical modeling of nonlinear multivariate spatio-temporal dynamical systems in the presence of uncertainty

Title from PDF of title page (University of Missouri--Columbia, viewed on July 31, 2013).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Dissertation advisor: Dr. Christopher K. WikleIncludes bibliographical references.Vita.Ph. D. University of Missouri--Columbia 2012."July 2012"[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Dynamic spatio-temporal models are statistical models that specify the joint distribution of a spatio-temporal process as the product of a series of conditional models whereby the current value of the process is conditioned on the process at the previous time point. Spatio-temporal dynamical models are often truer to the underlying scientific etiology of the process than their descriptive, covariance-based, counterpart, but are overparameterized even in simple linear settings (the curse of dimensionality). This problem is even worse in nonlinear settings. The use of mechanistic models to motivate the parameterization of a dynamical spatio-temporal model provides a way of reducing the dimensionality of the parameter space while still including important dynamics. However, in certain situations the numerical solutions to the mechanistic models are computationally expensive, and so using them within a Bayesian hierarchical model is not feasible. For these situations, one can use computer model emulators, computationally inexpensive statistical surrogates for the complex mechanistic model. In this dissertation, we provide several examples of using mechanistic models to motivate the parameterization of Bayesian hierarchical models for multivariate, nonlinear spatio-temporal models describing lower trophic level marine ecosystem dynamics. These examples include the use of a forest of one-dimensional computer model emulators to model a three-dimensional scientific process, emulator-assisted data assimilation, and the use of mechanistic models to motivate the parameterization of multivariate dynamical spatio-temporal models that exhibit quadratic nonlinearity.Includes bibliographical references

Positioning Patronage: Lanyer's Salve Deus Rex Judæorum and the Countess of Cumberland in Time and Place

This article places the composition and publication of Aemilia Lanyer's Salve Deus Rex Judæorum within the context of particular periods in the life of Margaret Russell, Countess of Cumberland and her daughter, Anne Clifford, Countess of Dorset. Lanyer's use of mirroring, shared discourse, possible worlds and reconstruction of memory all relate to these periods and were designed to engage the interest of Russell and Clifford. Through the identification of the period of the women's stay in Cookham in 1604, Lanyer's poetic strategies – directly appealing to Russell – can be identified. Lanyer's decision to publish her verse collection in 1610 was also influenced by events in the lives of Russell and Clifford, thus providing insight into Lanyer's canny understanding of patronage in the period

International Organizations Count

This special issue seeks to move forward the development of an empirical research agenda that takes seriously the complexity of how international organizations (IOs) function and the need to study that complexity at all levels of analysis by using robust research tools. We advocate for a broad empirical research approach that molds and sharpens theories about IOs by conducting systematic tests in large-sample environments. Two themes create a common thread throughout this issue. First, shifting the focus from whether IOs matter to how they work requires acknowledgment of the contingency of cause and effect. A second common thread lies in the authors' treatment of IO membership as an aggregate phenomenon—that is, as a set of institutions and relationships evolving over time and with many members rather than as a single organization. </jats:p