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Many biomedical publications refer to data obtained from collections of biosamples. Sharing such bioresources (biological samples, data, and databases) is paramount for the present governance of research. Recognition of the effort involved in generating, maintaining, and sharing high quality bioresources is poorly organized, which does not encourage sharing. At publication level, the recognition of such resources is often neglected and/or highly heterogeneous. This is a true handicap for the traceability of bioresource use. The aim of this article is to propose, for the first time, a guideline for reporting bioresource use in research articles, named CoBRA: Citation of BioResources in journal Articles.
As standards for citing bioresources are still lacking, the members of the journal editors subgroup of the Bioresource Research Impact Factor (BRIF) initiative developed a standardized and appropriate citation scheme for such resources by informing stakeholders about the subject and raising awareness among scientists and in science editors' networks, mapping this topic among other relevant initiatives, promoting actions addressed to stakeholders, launching surveys, and organizing focused workshops.
The European Association of Science Editors has adopted BRIF's suggestion to incorporate statements on biobanks in the Methods section of their guidelines. The BRIF subgroup agreed upon a proposed citation system: each individual bioresource that is used to perform a study and that is mentioned in the Methods section should be cited as an individual "reference [BIORESOURCE]" according to a delineated format. The EQUATOR (Enhancing the QUAlity and Transparency Of health Research) network mentioned the proposed reporting guideline in their "guidelines under development" section.
Evaluating bioresources' use and impact requires that publications accurately cite such resources. Adopting the standard citation scheme described here will improve the quality of bioresource reporting and will allow their traceability in scientific publications, thus increasing the recognition of bioresources' value and relevance to research. Please see related article: http://dx.doi.org/10.1186/s12916-015-0284-9 .
BMC Medicine 02/2015; 13(33). DOI:10.1186/s12916-015-0266-y · 7.28 Impact Factor
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One of every 150 hospitalized patients experiences a lethal adverse event; nearly half of these events involves surgical patients. Although variations in surgeon performance and quality have been reported in the literature, less is known about the influence of anesthesiologists on outcomes after major surgery. Our goal of this study was to determine whether there is significant variation in outcomes between anesthesiologists after controlling for patient case mix and hospital quality.
Using clinical data from the New York State Cardiac Surgery Reporting System, we conducted a retrospective observational study of 7920 patients undergoing isolated coronary artery bypass graft surgery. Multivariable logistic regression modeling was used to examine the variation in death or major complications (Q-wave myocardial infarction, renal failure, stroke) across anesthesiologists, controlling for patient demographics, severity of disease, comorbidities, and hospital quality.
Anesthesiologist performance was quantified using fixed-effects modeling. The variability across anesthesiologists was highly significant (P < 0.001). Patients managed by low-performance anesthesiologists (corresponding to the 25th percentile of the distribution of anesthesiologist risk-adjusted outcomes) experienced nearly twice the rate of death or serious complications (adjusted rate 3.33%; 95% confidence interval [CI], 3.09%-3.58%) as patients managed by high-performance anesthesiologists (corresponding to the 75th percentile) (adjusted rate 1.82%; 95% CI, 1.58%-2.10%). This performance gap was observed across all patient risk groups.
The rate of death or major complications among patients undergoing coronary artery bypass graft surgery varies markedly across anesthesiologists. These findings suggest that there may be opportunities to improve perioperative management to improve outcomes among high-risk surgical patients.
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