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Objective To examine changes in representation of women among first authors of original research published in high impact general medical journals from 1994 to 2014 and investigate differences between journals. Design Observational study. Study sample All original research articles published in Annals of Internal Medicine , Archives of Internal Medicine, The BMJ, JAMA, The Lancet, and the New England Journal of Medicine (NEJM) for one issue every alternate month from February 1994 to June 2014. Main exposures Time and journal of publication. Main outcome measures Prevalence of female first authorship and its adjusted association with time of publication and journal, assessed using a multivariable logistic regression model that accounted for number of authors, study type and specialty/topic, continent where the study was conducted, and the interactions between journal and time of publication, study type, and continent. Estimates from this model were used to calculate adjusted odds ratios against the mean across the six journals, with 95% confidence intervals and P values to describe the associations of interest. Results The gender of the first author was determined for 3758 of the 3860 articles considered; 1273 (34%) were women. After adjustment, female first authorship increased significantly from 27% in 1994 to 37% in 2014 (P<0.001). The NEJM seemed to follow a different pattern, with female first authorship decreasing; it also seemed to decline in recent years in The BMJ but started substantially higher (approximately 40%), and The BMJ had the highest total proportion of female first authors. Compared with the mean across all six journals, first authors were significantly less likely to be female in the NEJM (adjusted odds ratio 0.68, 95% confidence interval 0.53 to 0.89) and significantly more likely to be female in The BMJ (1.30, 1.01 to 1.66) over the study period. Conclusions The representation of women among first authors of original research in high impact general medical journals was significantly higher in 2014 than 20 years ago, but it has plateaued in recent years and has declined in some journals. These results, along with the significant differences seen between journals, suggest that underrepresentation of research by women in high impact journals is still an important concern. The underlying causes need to be investigated to help to identify practices and strategies to increase women’s influence on and contributions to the evidence that will determine future healthcare policies and standards of clinical practice.

New STS risk models have been developed for heart valve surgery combined with CABG. These are the first valve plus CABG models that also include risk prediction for individual major morbidities, composite major morbidity or mortality, and short and prolonged length of stay.

Background This study’s objective was to develop a risk model incorporating procedure type and patient factors to be used for case-mix adjustment in the analysis of hospital-specific operative mortality rates after congenital cardiac operations. Methods Included were patients of all ages undergoing cardiac operations, with or without cardiopulmonary bypass, at centers participating in The Society of Thoracic Surgeons Congenital Heart Surgery Database during January 1, 2010, to December 31, 2013. Excluded were isolated patent ductus arteriosus closures in patients weighing less than or equal to 2.5 kg, centers with more than 10% missing data, and patients with missing data for key variables. Data from the first 3.5 years were used for model development, and data from the last 0.5 year were used for assessing model discrimination and calibration. Potential risk factors were proposed based on expert consensus and selected after empirically comparing a variety of modeling options. Results The study cohort included 52,224 patients from 86 centers with 1,931 deaths (3.7%). Covariates included in the model were primary procedure, age, weight, and 11 additional patient factors reflecting acuity status and comorbidities. The C statistic in the validation sample was 0.858. Plots of observed-vs-expected mortality rates revealed good calibration overall and within subgroups, except for a slight overestimation of risk in the highest decile of predicted risk. Removing patient preoperative factors from the model reduced the C statistic to 0.831 and affected the performance classification for 12 of 86 hospitals. Conclusions The risk model is well suited to adjust for case mix in the analysis and reporting of hospital-specific mortality for congenital heart operations. Inclusion of patient factors added useful discriminatory power and reduced bias in the calculation of hospital-specific mortality metrics.