Publications

Objectives To evaluate whether SARS-CoV-2 infection in residents of long-term care (LTC) facilities is associated with higher mortality after the acute phase of infection, and to estimate survival in uninfected residents. Design Extended follow-up of a previous, propensity score-matched, retrospective cohort study based on the Swedish Senior Alert register. Setting LTC facilities in Sweden. Participants n=3604 LTC residents with documented SARS-CoV-2 until 15 September 2020 matched to 3604 uninfected controls using time-dependent propensity scores on age, sex, health status, comorbidities, prescription medications, geographical region and Senior Alert registration time. In a secondary analysis (n=3731 in each group), geographical region and Senior Alert registration time were not matched for in order to increase the follow-up time in controls and allow for an estimation of median survival. Primary outcome measures All-cause mortality until 24 October 2020, tracked using the National Cause of Death Register. Results Median age was 87 years and 65% were women. Excess mortality peaked at 5 days after documented SARS-CoV-2-infection (HR 21.5, 95% CI 15.9 to 29.2), after which excess mortality decreased. From the second month onwards, mortality rate became lower in infected residents than controls. The HR for death during days 61–210 of follow-up was 0.76 (95% CI 0.62 to 0.93). The median survival of uninfected controls was 1.6 years, which was much lower than the national life expectancy in Sweden at age 87 (5.05 years in men, 6.07 years in women). Conclusions The risk of death after SARS-CoV-2 infection in LTC residents peaked after 5 days and decreased after 2 months, probably because the frailest residents died during the acute phase, leaving healthier residents remaining. The limited life expectancy in this population suggests that LTC resident status should be accounted for when estimating years of life lost due to COVID-19.

Letters17 March 2020Evidence Relating Health Care Provider Burnout and Quality of CareDaniel S. Tawfik, MD, MS and John P.A. Ioannidis, MD, DScDaniel S. Tawfik, MD, MSStanford University, Stanford, California (D.S.T., J.P.I.) and John P.A. Ioannidis, MD, DScStanford University, Stanford, California (D.S.T., J.P.I.)Author, Article, and Disclosure Informationhttps://doi.org/10.7326/L19-0827 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:We thank Drs. Mathur and VanderWeele for their comment but believe that they harbor 2 misconceptions. They refer to a test of publication bias, but the literature on these methods has long concluded that none of the tests available (including the EST) is strictly or specifically a test of publication bias (1). In their recent methodological work, Drs. Mathur and VanderWeele unfortunately continue to fuel this misconception and even propose new tests of publication bias (2). We avoided using the definitive term "test of publication bias" in our review and instead only mentioned "potential bias." The EST offers ...References1. Sterne JA, Sutton AJ, Ioannidis JP, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ. 2011;343:d4002. [PMID: 21784880] doi:10.1136/bmj.d4002 CrossrefMedlineGoogle Scholar2. Mathur MB, VanderWeele TJ. Sensitivity analysis for publication bias [preprint]. 29 March 2019. Accessed at https://osf.io/s9dp6 on 20 December 2019. doi:10.31219/osf.io/s9dp6 Google Scholar3. Ioannidis JPA. Clarifications on the application and interpretation of the test for excess significance and its extensions. J Math Psychol. 2013;57:184-7. CrossrefGoogle Scholar4. Ioannidis JP, Trikalinos TA. An exploratory test for an excess of significant findings. Clin Trials. 2007;4:245-53. [PMID: 17715249] CrossrefMedlineGoogle Scholar5. Terrin N, Schmid CH, Lau J, et al. Adjusting for publication bias in the presence of heterogeneity. Stat Med. 2003;22:2113-26. [PMID: 12820277] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: Stanford University, Stanford, California (D.S.T., J.P.I.)Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M19-1152. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoEvidence Relating Health Care Provider Burnout and Quality of Care Daniel S. Tawfik , Annette Scheid , Jochen Profit , Tait Shanafelt , Mickey Trockel , Kathryn C. Adair , J. Bryan Sexton , and John P.A. Ioannidis Evidence Relating Health Care Provider Burnout and Quality of Care Maya B. Mathur and Tyler J. VanderWeele Metrics Cited byBurnout, mental health, physical symptoms, and coping behaviors in healthcare workers in Belize amidst COVID-19 pandemic: A nationwide cross-sectional studyNurses burnout, resilience and its association with safety culture: a cross sectional study 17 March 2020Volume 172, Issue 6Page: 438-439KeywordsDisclosureHealth care providersHealth care qualitySafety ePublished: 17 March 2020 Issue Published: 17 March 2020 Copyright & PermissionsCopyright © 2020 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...

We implemented an attack against WEP, the link-layer security protocol for 802.11 networks. The attack was described in a recent paper by Fluhrer, Mantin, and Shamir. With our implementation, and permission of the network administrator, we were able to recover the 128 bit secret key used in a production network, with a passive attack. The WEP standard uses RC4 IVs improperly, and the attack exploits this design failure. This paper describes the attack, how we implemented it, and some optimizations to make the attack more efficient. We conclude that 802.11 WEP is totally insecure, and we provide some recommendations. 1

Constrained coding plays a crucial role in high-speed communication links by restricting bit sequences to reduce the adverse effects imposed by the characterist

<p>PDF - 132KB, Fraction of small and large CEC and non-CEC associated grants by year.</p>

Crossover designs may contribute evidence in a fifth of systematic reviews, but few meta-analyses make use of their full data. The results of crossover trials tend to agree with those of parallel arm trials, although there was a trend for more conservative treatment effect estimates in parallel arm trials.

The rapid and continuing progress in gene discovery for complex diseases is fueling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but the quality and completeness of reporting varies. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies, building on the principles established by previous reporting guidelines. These recommendations aim to enhance the transparency of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct, or analysis. A detailed Explanation and Elaboration document is published on the EJHG website.