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BackgroundLong-term follow-up for clinician-scientist training programs is sparse. We describe the outcomes of clinician-scientist scholars in the National Heart Lung and Blood Institute (NHLBI) K12 program in emergency care research up to 8.7 years after matriculation in the program.MethodsThis was a cohort study of faculty clinician-scientist scholars enrolled in a NHLBI K12 research training program at 6 sites across the US, with median follow-up 7.7 years (range 5.7-8.7 years) from the date of matriculation. Scholars completed electronic surveys in 2017 and 2019, with the 2019 survey collecting information for their current work setting, percent time for research, and grant funding from all sources. We used NIH RePorter and online resources to verify federal grants through March 2021. The primary outcome was a funded career development award (CDA) or research project grant (RPG) where the scholar was principal investigator. We included funding from all federal sources and national foundations.ResultsThere were 43 scholars, including 16 (37%) women. Over the follow-up period, 32 (74%) received an individual CDA or RPG, with a median of 36 months (range 9-83 months) after entering the program. Of the 43 scholars, 23 (54%) received a CDA and 22 (51%) received an RPG, 7 (16%) of which were R01s. Of the 23 scholars who received a CDA, 13 (56%) subsequently had an RPG funded. Time to CDA or RPG did not differ by sex (women vs. men log-rank test p = 0.27) or specialty training (emergency medicine versus other specialties, p = 0.59).ConclusionsAfter 7 years of follow-up for this NHLBI K12 emergency care research training program, three quarters of clinician-scientist scholars had obtained CDA or RPG funding, with no notable differences by sex or clinical training.

Study objectiveWe assess the productivity, outcomes, and experiences of participants in the National Institutes of Health/National Heart, Lung, and Blood Institute-funded K12 institutional research training programs in emergency care research.MethodsWe used a mixed-methods study design to evaluate the 6 K12 programs, including 2 surveys, participant interviews, scholar publications, grant submissions, and funded grants. The training program lasted from July 1, 2011, through June 30, 2017. We tracked scholars for a minimum of 3 years and up to 5 years, beginning with date of entry into the program. We interviewed program participants by telephone using open-ended prompts.ResultsThere were 94 participants, including 43 faculty scholars, 13 principal investigators, 30 non-principal investigator primary mentors, and 8 program administrators. The survey had a 74% overall response rate, including 95% of scholars. On entry to the program, scholars were aged a median of 37 years (interquartile range [IQR] 34 to 40 years), with 16 women (37%), and represented 11 disciplines. Of the 43 scholars, 40 (93%) submitted a career development award or research project grant during or after the program; 26 (60%) have secured independent funding as of August 1, 2017. Starting with date of entry into the program, the median time to grant submission was 19 months (IQR 11 to 27 months) and time to funding was 33 months (IQR 27 to 39 months). Cumulative median publications per scholar increased from 7 (IQR 4 to 15.5) at program entry to 21 (IQR 11 to 33.5) in the first post-K12 year. We conducted 57 semistructured interviews and identified 7 primary themes.ConclusionThis training program produced 43 interdisciplinary investigators in emergency care research, with demonstrated productivity in grant funding and publications.

PURPOSE The purpose of this study was to explore family medicine graduates' attitudes and perspectives on modifiable and unmodifiable factors that influenced their scope of practice and career choices. By understanding how these factors intersect to influence desired and actual scope of practice decisions, we hope to inform strategies to address training and health care workforce needs. METHODS During 5 focus group discussions, comprised of a total of 32 family physicians who either resided in or attended a residency program in western North Carolina, we explored family physicians' attitudes and perspectives on their desired and actual scope of practice. We used thematic analysis to identify patterns in the qualitative data. RESULTS We created a conceptual framework to understand the complex factors which influence family physicians' scope of practice. Personal factors were found to impact desired scope, while workplace, environmental, and population factors influenced actual scope of practice. Stressors in each of these 4 categories often caused family physicians to narrow their scope of practice. Our study highlights specific supports that, if in place, enable physicians to maintain their desired broad scope of practice. CONCLUSIONS Our study indicates that the national trend toward family physicians narrowing their scope of practice can be addressed by providing specific supports during training, residency, and mid-career. Understanding personal, workplace, environmental, and population factors that influence scope of practice can inform specific interventions that create desirable jobs for family physicians and improve their ability to meet changing population needs. Key words: family; rural; scope of practice; workforce, INTRODUCTION There is a trend towards an increased scope of practice in the field of family medicine as a whole but individual family physicians' scope of practice has been decreasing [...]

Objectives: To investigate the risk of atrial fibrillation (AF) with sodium-glucose cotransporter-2 inhibitors (SGLT2is) compared to dipeptidyl peptidase-4 inhibitor (DPP4i) use in older US adults and across diverse subgroups. Methods: We conducted a retrospective cohort analysis using claims data from 15% random samples of Medicare fee-for-service beneficiaries. Patients were adults with type 2 diabetes (T2D), no preexisting AF, and were newly initiated on SGLT2i or DPP4i. The outcome was the first incident AF. Inverse probability treatment weighting (IPTW) was used to balance the baseline covariates between the treatment groups including sociodemographics, comorbidities, and comedications. Cox regression models were used to assess the effect of SGLT2i compared to DPP4i on incident AF. Results: Of the 97,436 eligible individuals (mean age 71.2 ± 9.8 years, 54.6% women), 1.01% (n = 983) had incident AF over a median follow-up of 361 days. The adjusted incidence rate was 8.39 (95% CI: 6.67-9.99) and 11.70 (95% CI: 10.9-12.55) per 1,000 person-years in the SGLT2i and DPP4i groups, respectively. SGLT2is were associated with a significantly lower risk of incident AF (HR 0.73; 95% CI, 0.57 to 0.91; p = 0.01) than DPP4is. The risk reduction of incident AF was significant in non-Hispanic White individuals and subgroups with existing atherosclerotic cardiovascular diseases and chronic kidney disease. Conclusion: Compared to the use of DPP4i, that of SGLT2i was associated with a lower risk of AF in patients with T2D. Our findings contribute to the real-world evidence regarding the effectiveness of SGLT2i in preventing AF and support a tailored therapeutic approach to optimize treatment selection based on individual characteristics. [ABSTRACT FROM AUTHOR]

The clinical implications of ankle-brachial index (ABI) cutpoints are not well defined in patients with chronic kidney disease (CKD) despite increased prevalence of high ABI attributed to arterial stiffness. We examined the relationship of ABI with cardiovascular disease (CVD) and all-cause mortality among CKD patients. Three thousand six hundred twenty-seven participants without clinical peripheral artery disease (PAD) at baseline from the Chronic Renal Insufficiency Cohort Study were included. ABI was obtained per standard protocol and CVD events were confirmed by medical record adjudication. A U-shaped association of ABI with PAD, myocardial infarction (MI), composite CVD, and all-cause mortality was observed. Individuals with an ABI between 1.0 and

Objectives COVID-19, since its emergence in December 2019, has globally impacted research. Over 360 000 COVID-19-related manuscripts have been published on PubMed and preprint servers like medRxiv and bioRxiv, with preprints comprising about 15% of all manuscripts. Yet, the role and impact of preprints on COVID-19 research and evidence synthesis remain uncertain. Materials and Methods We propose a novel data-driven method for assigning weights to individual preprints in systematic reviews and meta-analyses. This weight termed the "confidence score" is obtained using the survival cure model, also known as the survival mixture model, which takes into account the time elapsed between posting and publication of a preprint, as well as metadata such as the number of first 2-week citations, sample size, and study type. Results Using 146 preprints on COVID-19 therapeutics posted from the beginning of the pandemic through April 30, 2021, we validated the confidence scores, showing an area under the curve of 0.95 (95% CI, 0.92-0.98). Through a use case on the effectiveness of hydroxychloroquine, we demonstrated how these scores can be incorporated practically into meta-analyses to properly weigh preprints. Discussion It is important to note that our method does not aim to replace existing measures of study quality but rather serves as a supplementary measure that overcomes some limitations of current approaches. Conclusion Our proposed confidence score has the potential to improve systematic reviews of evidence related to COVID-19 and other clinical conditions by providing a data-driven approach to including unpublished manuscripts. [ABSTRACT FROM AUTHOR]

BackgroundThe clinical utility of genotype-guided (pharmacogenetically based) dosing of warfarin has been tested only in small clinical trials or observational studies, with equivocal results.MethodsWe randomly assigned 1015 patients to receive doses of warfarin during the first 5 days of therapy that were determined according to a dosing algorithm that included both clinical variables and genotype data or to one that included clinical variables only. All patients and clinicians were unaware of the dose of warfarin during the first 4 weeks of therapy. The primary outcome was the percentage of time that the international normalized ratio (INR) was in the therapeutic range from day 4 or 5 through day 28 of therapy.ResultsAt 4 weeks, the mean percentage of time in the therapeutic range was 45.2% in the genotype-guided group and 45.4% in the clinically guided group (adjusted mean difference, [genotype-guided group minus clinically guided group], -0.2; 95% confidence interval, -3.4 to 3.1; P=0.91). There also was no significant between-group difference among patients with a predicted dose difference between the two algorithms of 1 mg per day or more. There was, however, a significant interaction between dosing strategy and race (P=0.003). Among black patients, the mean percentage of time in the therapeutic range was less in the genotype-guided group than in the clinically guided group. The rates of the combined outcome of any INR of 4 or more, major bleeding, or thromboembolism did not differ significantly according to dosing strategy.ConclusionsGenotype-guided dosing of warfarin did not improve anticoagulation control during the first 4 weeks of therapy. (Funded by the National Heart, Lung, and Blood Institute and others; COAG ClinicalTrials.gov number, NCT00839657.).

Prediction modeling for clinical decision making is of great importance and needed to be updated frequently with the changes of patient population and clinical practice. Existing methods are either done in an ad hoc fashion, such as model recalibration or focus on studying the relationship between predictors and outcome and less so for the purpose of prediction. In this article, we propose a dynamic logistic state space model to continuously update the parameters whenever new information becomes available. The proposed model allows for both time‐varying and time‐invariant coefficients. The varying coefficients are modeled using smoothing splines to account for their smooth trends over time. The smoothing parameters are objectively chosen by maximum likelihood. The model is updated using batch data accumulated at prespecified time intervals, which allows for better approximation of the underlying binomial density function. In the simulation, we show that the new model has significantly higher prediction accuracy compared to existing methods. We apply the method to predict 1 year survival after lung transplantation using the United Network for Organ Sharing data. [ABSTRACT FROM AUTHOR]