88 research outputs found
High-Volume versus Low-Volume for Esophageal Resections for Cancer: The Essential Role of Case-Mix Adjustments based on Clinical Data
Background: Most studies addressing the volume-outcome relationship in complex surgical procedures use hospital mortality as the sole outcome measure and are rarely based on detailed clinical data. The lack of reliable information about comorbidities and tumor stages makes the conclusions of these studies debatable. The purpose of this study was to compare outcomes for esophageal resections for cancer in low- versus high-volume hospitals, using an extensive set of variables concerning case-mix and outcome measures, including long-term survival. Methods: Clinical data, from 903 esophageal resections performed between January 1990 and December 1999, were retrieved from the original patients' files. Three hundred and forty-two patients were operated on in 11 low-volume hospitals (<7 resections/year) and 561 in a single high-volume center. Results: Mortality and morbidity rates were significantly lower in the high-volume center, which had an in-hospital mortality of 5 vs 13% (P < .001). On multivariate analysis, hospital volume, but also the presence of comorbidity proved to be strong prognostic factors predicting in-hospital mortality (ORs 3.05 and 2.34). For stage I and II disease, there was a significantly better 5-year survival in the high-volume center. (P = .04). Conclusions: Hospital volume and comorbidity patterns are important determinants of outcome in esophageal cancer surgery. Strong clinical endpoints such as in-hospital mortality and survival can be used as performance indicators, only if they are joined by reliable case-mix information
Remote detection of invasive alien species
The spread of invasive alien species (IAS) is recognized as the most severe threat to biodiversity outside of climate change and anthropogenic habitat destruction. IAS negatively impact ecosystems, local economies, and residents. They are especially problematic because once established, they give rise to positive feedbacks, increasing the likelihood of further invasions and spread. The integration of remote sensing (RS) to the study of invasion, in addition to contributing to our understanding of invasion processes and impacts to biodiversity, has enabled managers to monitor invasions and predict the spread of IAS, thus supporting biodiversity conservation and management action. This chapter focuses on RS capabilities to detect and monitor invasive plant species across terrestrial, riparian, aquatic, and human-modified ecosystems. All of these environments have unique species assemblages and their own optimal methodology for effective detection and mapping, which we discuss in detail
To which world regions does the valenceâdominance model of social perception apply?
Over the past 10 years, Oosterhof and Todorovâs valenceâdominance model has emerged as the most prominent account of
how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social
judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether
these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorovâs methodology across
11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorovâs original analysis strategy,
the valenceâdominance model generalized across regions. When we used an alternative methodology to allow for correlated
dimensions, we observed much less generalization. Collectively, these results suggest that, while the valenceâdominance
model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed
when we use different extraction methods and correlate and rotate the dimension reduction solution.C.L. was supported by the Vienna Science and Technology Fund (WWTF VRG13-007);
L.M.D. was supported by ERC 647910 (KINSHIP); D.I.B. and N.I. received funding from
CONICET, Argentina; L.K., F.K. and Ă. Putz were supported by the European Social
Fund (EFOP-3.6.1.-16-2016-00004; âComprehensive Development for Implementing
Smart Specialization Strategies at the University of PĂ©csâ). K.U. and E. Vergauwe were
supported by a grant from the Swiss National Science Foundation (PZ00P1_154911 to E.
Vergauwe). T.G. is supported by the Social Sciences and Humanities Research Council
of Canada (SSHRC). M.A.V. was supported by grants 2016-T1/SOC-1395 (Comunidad
de Madrid) and PSI2017-85159-P (AEI/FEDER UE). K.B. was supported by a grant
from the National Science Centre, Poland (number 2015/19/D/HS6/00641). J. Bonick
and J.W.L. were supported by the Joep Lange Institute. G.B. was supported by the Slovak
Research and Development Agency (APVV-17-0418). H.I.J. and E.S. were supported
by a French National Research Agency âInvestissements dâAvenirâ programme grant
(ANR-15-IDEX-02). T.D.G. was supported by an Australian Government Research
Training Program Scholarship. The Raipur Group is thankful to: (1) the University
Grants Commission, New Delhi, India for the research grants received through its
SAP-DRS (Phase-III) scheme sanctioned to the School of Studies in Life Science;
and (2) the Center for Translational Chronobiology at the School of Studies in Life
Science, PRSU, Raipur, India for providing logistical support. K. Ask was supported by
a small grant from the Department of Psychology, University of Gothenburg. Y.Q. was
supported by grants from the Beijing Natural Science Foundation (5184035) and CAS
Key Laboratory of Behavioral Science, Institute of Psychology. N.A.C. was supported
by the National Science Foundation Graduate Research Fellowship (R010138018). We
acknowledge the following research assistants: J. Muriithi and J. Ngugi (United States
International University Africa); E. Adamo, D. Cafaro, V. Ciambrone, F. Dolce and E.
Tolomeo (Magna GrĂŠcia University of Catanzaro); E. De Stefano (University of Padova);
S. A. Escobar Abadia (University of Lincoln); L. E. Grimstad (Norwegian School of
Economics (NHH)); L. C. Zamora (Franklin and Marshall College); R. E. Liang and R.
C. Lo (Universiti Tunku Abdul Rahman); A. Short and L. Allen (Massey University, New
Zealand), A. AteĆ, E. GĂŒneĆ and S. Can Ăzdemir (BoÄaziçi University); I. Pedersen and T.
Roos (Ă
bo Akademi University); N. Paetz (Escuela de ComunicaciĂłn MĂłnica Herrera);
J. Green (University of Gothenburg); M. Krainz (University of Vienna, Austria); and B.
Todorova (University of Vienna, Austria). The funders had no role in study design, data
collection and analysis, decision to publish or preparation of the manuscript.https://www.nature.com/nathumbehav/am2023BiochemistryGeneticsMicrobiology and Plant Patholog
WHO global research priorities for antimicrobial resistance in human health
The WHO research agenda for antimicrobial resistance (AMR) in human health has identified 40 research priorities to be addressed by the year 2030. These priorities focus on bacterial and fungal pathogens of crucial importance in addressing AMR, including drug-resistant pathogens causing tuberculosis. These research priorities encompass the entire people-centred journey, covering prevention, diagnosis, and treatment of antimicrobial-resistant infections, in addition to addressing the overarching knowledge gaps in AMR epidemiology, burden and drivers, policies and regulations, and awareness and education. The research priorities were identified through a multistage process, starting with a comprehensive scoping review of knowledge gaps, with expert inputs gathered through a survey and open call. The priority setting involved a rigorous modified Child Health and Nutrition Research Initiative approach, ensuring global representation and applicability of the findings. The ultimate goal of this research agenda is to encourage research and investment in the generation of evidence to better understand AMR dynamics and facilitate policy translation for reducing the burden and consequences of AMR
Women who Sexually Offend Display Three Main Offense Styles: A Re-Examination of the Descriptive Model of Female Sexual Offending
This study examined a theory constructed to describe the offense process of women who sexually offend-the Descriptive Model of Female Sexual Offending (DMFSO). In particular, this report sets out to establish whether the original three pathways (or offending styles) identified within United Kingdom convicted female sexual offenders and described within the DMFSO (i.e., Explicit-Approach, Directed-Avoidant, Implicit-Disorganized) were applicable to a small sample (N = 36) of North American women convicted of sexual offending. Two independent raters examined the offense narratives of the sample and-using the DMFSO-coded each script according to whether it fitted one of the three original pathways. Results suggested that the three existing pathways of the DMFSO represented a reasonable description of offense pathways for a sample of North American women convicted of sexual offending. No new pathways were identified. A new "Offense Pathway Checklist" devised to aid raters' decision making is described and future research and treatment implications explored
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