Promoting a gender-affirming environment in research: implications for research nurses.

Background: Approximately 25 million people around the world identify as transgender, and the numbers are growing. While visibility of transgender communities has increased, significant healthcare disparities remain. Transgender individuals report being less inclined to share their sex assigned at birth due to fear of stigmatization and mistrust of the medical community. The mistrust and inequity experienced by transgender individuals are not limited to clinical care and may extend to clinical research as well. Aim and method: The aim of this paper is to start a conversation about barriers to participating in research and the role of research staff, specifically the Clinical Research Nurse, in promoting engagement of transgender individuals in clinical research trials. Discussion and conclusions: A discussion of safety considerations, data integrity, and implications for data management is included. Because disparities may result in large part from lack of education and knowledge on best practices for providing care for this population, recommendations for fostering a culture of competence and gender-affirming care among research professionals featuring the role of the research nurse will be discussed.

Relationship of urologic complications with health-related quality of life and perceived value of health in men and women with type 1 diabetes: the Diabetes Control and Complications Trial/Epidemiology of Interventions and Complications (DCCT/EDIC) cohort.

OBJECTIVE: Limited information exists about the influence of urologic complications on health-related quality of life (HRQOL) in patients with type 1 diabetes. RESEARCH DESIGN AND METHODS: We studied 664 men and 580 women from the Diabetes Control and Complications Trial/Epidemiology of Interventions and Complications Study: mean ages were 51.6 ± 6.6 and 50.6 ± 7.2 years and duration of diabetes was 29.5 ± 4.8 and 29.8 ± 5.1 years, respectively. We assessed associations of sexual dysfunction, lower urinary tract symptoms (LUTS), and, in women, urinary incontinence (UI) with general quality of life (SF-36), perceived value of health (EuroQol-5), diabetes-related quality of life (Diabetes Quality of Life Scale [DQOL]), and psychiatric symptoms (Symptom Checklist 90-R). RESULTS: In both men and women, urologic complications adversely affected HRQOL and psychiatric symptoms, even after accounting for history of depression leading to treatment. Multivariable analyses accounting for the presence of diabetic retinopathy, neuropathy, and nephropathy also revealed substantial independent effects. In men, for example, the odds (95% CI) of a low DQOL score (≤25th percentile) were 3.01 (1.90-4.75) times greater with erectile dysfunction and 2.65 (1.68-4.18) times greater with LUTS and in women, 2.04 (1.25-3.35) times greater with sexual dysfunction and 2.71 (1.72-4.27) times greater with UI/LUTS combined compared with men and women without such complications. Similar effects were observed for the other measures. CONCLUSIONS: Sexual dysfunction and urinary complications with type 1 diabetes are associated with decreased quality of life and perceived value of health and with higher levels of psychiatric symptoms, even after accounting for other diabetes complications and depression treatment.

Rationale and design of the glycemia reduction approaches in diabetes: a comparative effectiveness study (GRADE).

OBJECTIVE: The epidemic of type 2 diabetes (T2DM) threatens to become the major public health problem of this century. However, a comprehensive comparison of the long-term effects of medications to treat T2DM has not been conducted. GRADE, a pragmatic, unmasked clinical trial, aims to compare commonly used diabetes medications, when combined with metformin, on glycemia-lowering effectiveness and patient-centered outcomes. RESEARCH DESIGN AND METHODS: GRADE was designed with support from a U34 planning grant from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The consensus protocol was approved by NIDDK and the GRADE Research Group. Eligibility criteria for the 5,000 metformin-treated subjects include <5 years' diabetes duration, ≥ 30 years of age at time of diagnosis, and baseline hemoglobin A1c (A1C) of 6.8-8.5% (51-69 mmol/mol). Medications representing four classes (sulfonylureas, dipeptidyl peptidase 4 inhibitors, glucagon-like peptide 1 receptor agonists, and insulin) will be randomly assigned and added to metformin (minimum-maximum 1,000-2,000 mg/day). The primary metabolic outcome is the time to primary failure defined as an A1C ≥ 7% (53 mmol/mol), subsequently confirmed, over an anticipated mean observation period of 4.8 years (range 4-7 years). Other long-term metabolic outcomes include the need for the addition of basal insulin after a confirmed A1C >7.5% (58 mmol/mol) and, ultimately, the need to implement an intensive basal/bolus insulin regimen. The four drugs will also be compared with respect to selected microvascular complications, cardiovascular disease risk factors, adverse effects, tolerability, quality of life, and cost-effectiveness. CONCLUSIONS: GRADE will compare the long-term effectiveness of major glycemia-lowering medications and provide guidance to clinicians about the most appropriate medications to treat T2DM. GRADE begins recruitment at 37 centers in the U.S. in 2013.

Efficacy and cost-effectiveness of an automated screening algorithm in an inpatient clinical trial.

INTRODUCTION: Screening and recruitment for clinical trials can be costly and time-consuming. Inpatient trials present additional challenges because enrollment is time sensitive based on length of stay. We hypothesized that using an automated prescreening algorithm to identify eligible subjects would increase screening efficiency and enrollment and be cost-effective compared to manual review of a daily admission list. METHODS: Using a before-and-after design, we compared time spent screening, number of patients screened, enrollment rate, and cost-effectiveness of each screening method in an inpatient diabetes trial conducted at Massachusetts General Hospital. Manual chart review (CR) involved reviewing a daily list of admitted patients to identify eligible subjects. The automated prescreening (APS) method used an algorithm to generate a daily list of patients with glucose levels ≥ 180 mg/dL, an insulin order, and/or admission diagnosis of diabetes mellitus. The census generated was then manually screened to confirm eligibility and eliminate patients who met our exclusion criteria. We determined rates of screening and enrollment and cost-effectiveness of each method based on study sample size. RESULTS: Total screening time (prescreening and screening) decreased from 4 to 2 h, allowing subjects to be approached earlier in the course of the hospital stay. The average number of patients prescreened per day increased from 13 ± 4 to 30 ± 16 (P < 0.0001). Rate of enrollment increased from 0.17 to 0.32 patients per screening day. Developing the computer algorithm added a fixed cost of US$3000 to the study. Based on our screening and enrollment rates, the algorithm was cost-neutral after enrolling 12 patients. Larger sample sizes further favored screening with an algorithm. By contrast, higher recruitment rates favored individual CR. LIMITATIONS: Because of the before-and-after design of this study, it is possible that unmeasured factors contributed to increased enrollment. CONCLUSION: Using a computer algorithm to identify eligible patients for a clinical trial in the inpatient setting increased the number of patients screened and enrolled, decreased the time required to enroll them, and was less expensive. Upfront investment in developing a computerized algorithm to improve screening may be cost-effective even for relatively small trials, especially when the recruitment rate is expected to be low.

Changes in glycemic control from 1996 to 2006 among adults with type 2 diabetes: a longitudinal cohort study.

BACKGROUND: Our objectives were to examine temporal changes in HbA1c and lipid levels over a 10-year period and to identify predictors of metabolic control in a longitudinal patient cohort. METHODS: We identified all adults within our hospital network with T2DM who had HbA1c's measured in both 1996 and 2006 (longitudinal cohort). For patients with no data in 2006, we used hospital and social security records to distinguish patients lost to follow-up from those who died after 1996. We compared characteristics of the 3 baseline cohorts (longitudinal, lost to f/u, died) and examined metabolic trends in the longitudinal cohort. RESULTS: Of the 4944 patients with HbA1c measured in 1996, 1772 (36%) had an HbA1c measured in 2006, 1296 (26%) were lost to follow-up, and 1876 (38%) had died by 2006. In the longitudinal cohort, mean HbA1c decreased by 0.4 +/- 1.8% over the ten-year span (from 8.2% +/- 1.7% to 7.8% +/- 1.4%) and mean total cholesterol decreased by 49.3 (+/- 46.5) mg/dL. In a multivariate model, independent predictors of HbA1c decline included older age (OR 1.41 per decade, 95% CI: 1.3-1.6, p < 0.001), baseline HbA1c (OR 2.9 per 1% increment, 2.6 - 3.2, p < 0.001), and speaking English (OR 2.1, 1.4-3.1, p < 0.001). CONCLUSIONS: Despite having had diabetes for an additional 10 years, patients in our longitudinal cohort had better glycemic and cholesterol control in 2006 than 1996. Greatest improvements occurred in patients with the highest levels in the baseline year.