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Background Cefazolin surgical prophylaxis is associated with better patient outcomes; however, its use in penicillin-allergic patients is controversial. We evaluated the safety of cefazolin as surgical prophylaxis in penicillin-allergic patients, including those with anaphylaxis histories. Methods We conducted a pre and postintervention quality improvement evaluation of an institution-wide policy change at a tertiary-care hospital, before (October 2017–January 2018), during (February 2018–September 2018), and after (October 2018–October 2019) transition to routine cefazolin prophylaxis for penicillin-allergic patients, including those with anaphylaxis histories but excluding severe delayed reactions (eg, Stevens-Johnson syndrome). Retrospective data was collected on all surgical prophylaxis patients with penicillin-anaphylactic histories between October 2017 and September 2018. From October 2018, we prospectively reviewed adverse events with cefazolin. Primary outcome was adverse events in penicillin-allergic patients receiving cefazolin perioperatively. Results From October 2017 to October 2019, 27,467 operations were performed. Of 220 patients with penicillin-anaphylactic histories reviewed prior to the full policy change, no statistically significant differences were reported in allergic reactions (P = .70), surgical site infections (P = 1.00), or adverse events (P = .32) with cefazolin compared to other antibiotics. Postpolicy implementation, cefazolin usage increased 18.2%, while vancomycin and clindamycin decreased by 11.4% and 62.0%, respectively. No anaphylaxis was documented in penicillin-allergic patients receiving cefazolin in either the review or quality assurance follow-up after the change. Of 3 patients developing reactions to cefazolin, none had histories of penicillin allergy. Surgical site infection rates were similar between pre and postpolicy time periods (P = .842). Conclusion Administration of cefazolin in penicillin-anaphylactic patients for surgical prophylaxis appears to be safe.

Objective The manuscript discusses landmark studies using abbreviated MRI for breast cancer screening. This includes abbreviated dynamic contrast enhanced MRI and diffusion weighted imaging. Our institutional experience with abbreviated MR protocol for breast cancer screening is also described. Conclusion Abbreviated MRI protocols were found to demonstrate value for screening of breast cancer. It has been shown that abbreviated protocol MRI provides similar diagnostic sensitivities to full protocol MRI for breast cancer in women with increased lifetime risk. Our institutional abbreviated MRI protocol for breast cancer offers improved time and workflow efficiencies and has the potential to increase the number of breast cancers detected and the detection of pathologically relevant invasive breast cancer at earlier stages.

In recent years, the prequalified rigid connections of radius-cut reduced beam section (RBS) have been widely used in the design and construction of steel moment frames. Despite extensive investigations performed on the seismic performance of RBS connections, there is little research into the impact of these connections upon the elastic story drift in steel moment frames. In the current study, a precise formulation (partially based on a previous research) has been developed so as to evaluate the amount of stiffness variation or amplified elastic drift introduced by radius-cut RBS connections in a story of steel moment frames. Herein, by defining a novel and accurate method along with the method of virtual work, the amplified elastic drift of a 2-dimensional one-story single-span moment frame due to utilizing radius-cut RBS connections is calculated. The reliability and accuracy of the presented approach are validated using finite element modeling of the moment frame. Sensitivity analyses are also conducted upon the RBS connection parameters to derive the most effective parameters on the amount of elastic drift in steel moment frames. Then, by employing a statistical approach called response surface method (RSM) and combining findings of this study with some premises considered in a previous research, rigorous amplification factor of elastic drift formulas based on utilizing each of IPE and HEA beams in a story (from the first to the last one) with RBS connections are developed. Ultimately, two simple, linear, and functional amplification factor of elastic story drift formulas for each set of IPE and HEA story beams with RBS connections are proposed for designers. The scope of these formulas will be expanded to plate girders as well.

Data Envelopment Analysis (DEA) requires deterministic input/output data for efficiency evaluation of a set of Decision Making Units (DMUs). When there are more than one set of input/output data for each DMU, however, such requirement is infeasible. Stochastic DEA (SDEA), where input/output data are assumed to be stochastic, is a natural approach for such applications. Performance evaluation of DMUs in SDEA naturally calls for ranking methods that can account for stochastic fluctuations of the input/output, and hence the efficiency score. None of the proposed methods in the current literature incorporates all the information in the efficiency score distributions for ranking DMUs. To fill this gap, we introduce two ranking methods, a partial and a linear, for performance evaluation in SDEA using the reliability function of the efficiency scores. Our proposed partial ranking is based on the notion of stochastic ordering, while our linear ordering is a weighted average of the reliability function of the efficiency scores. Special cases of our proposed linear ranking method include mean and median ordering in SDEA. Our proposed partial ordering provides a notion for stochastic dominance using which one can define a natural notion of admissibility as a minimal performance requirement. We demonstrate how the proposed ranking methods can be implemented and illustrate the methods using the Grundfeld data, analyzed using both parametric and non-parametric approaches.

The knowledge of geological strata sequences and their exact boundaries depths is of a great importance in the characterization of oil and gas reservoirs. The aim of automated well-to-well correlation approaches is to facilitate and accelerate the procedure of geological boundary detection. In this study, we implement an automatic well-to-well correlation approach based on pattern extraction from well-logs. The well-log patterns are recognized by calculating several statistical and fractal parameters. As a fractal parameter, we select the wavelet standard deviation exponent, calculated by the discrete wavelet transform. Furthermore, to select the proper wavelet function, as the heart of wavelet transform, the energy to Shannon entropy ratio criterion is implemented. The statistical pattern recognition parameters of this study include average value, maximum to minimum ratio, coefficient of variation, and the trend angle of well-log data (i.e., Gamma ray log) in a window around the geological boundary. Moreover, the analysis of variance (ANOVA) tool and the Tukey multiple comparison method are implemented to evaluate the effectiveness of each parameter (i.e., fractal or statistical parameters) during the determination of boundary depths. The gamma ray logs from three wells of an oil field are used as a dataset for the evaluation of our algorithm. The outputs of our methodology are also compared with the new detrended fluctuation analysis (DFA) method, which show promising outcomes over it. The results show that the average value of the signal, among the analyzed parameters, is the most effective parameter; however, implementing the combination of all fractal and statistical parameters can improve the accuracy of the geological boundary detection.