Impact of the Dobbs v Jackson Women's Health Organization decision on retention of Indiana medical students for residency.

BACKGROUND: As medical students consider residency training programs, access to comprehensive training in abortion care and the legal climate influencing abortion care provision are likely to affect their decision process. OBJECTIVE: This study aimed to determine medical students' desire to stay in a state with an abortion ban for residency. STUDY DESIGN: A cross-sectional survey was distributed to all medical students at a large allopathic medical school. Anonymous survey questions investigated the likelihood of seeking residency training in states with abortion restrictions and the likelihood of considering obstetrics and gynecology as a specialty. Qualitative responses were also captured. RESULTS: The survey was distributed to 1424 students, and 473 responses yielded a 33.2% completion rate; 66.8% of students were less likely to pursue residency training in Indiana following a proposed abortion ban. Moreover, 70.0% of students were less likely to pursue residency in a state with abortion restrictions. Approximately half of respondents (52.2%) were less likely to pursue obstetrics and gynecology as a specialty after proposed abortion restrictions. Qualitative remarks encompassed 6 themes: comprehensive health care access, frustration with the political climate, impact on health care providers, relocation, advocacy, and personal beliefs and ethical considerations. CONCLUSION: Most medical students expressed decreased likelihood of remaining in Indiana or in states with abortion restrictions for residency training. The field of obstetrics and gynecology has been negatively affected, with medical students indicating lower likelihood to pursue obstetrics and gynecology. Regardless of specialty, the physician shortage may be exacerbated in states with abortion restrictions. The overturn of Roe v Wade has the potential for significant effects on medical student plans for residency training location, thereby shaping the future of the physician workforce.

Twelve-Week 24/7 Ambulatory Artificial Pancreas With Weekly Adaptation of Insulin Delivery Settings: Effect on Hemoglobin A1c and Hypoglycemia.

OBJECTIVE: Artificial pancreas (AP) systems are best positioned for optimal treatment of type 1 diabetes (T1D) and are currently being tested in outpatient clinical trials. Our consortium developed and tested a novel adaptive AP in an outpatient, single-arm, uncontrolled multicenter clinical trial lasting 12 weeks. RESEARCH DESIGN AND METHODS: Thirty adults with T1D completed a continuous glucose monitor (CGM)-augmented 1-week sensor-augmented pump (SAP) period. After the AP was started, basal insulin delivery settings used by the AP for initialization were adapted weekly, and carbohydrate ratios were adapted every 4 weeks by an algorithm running on a cloud-based server, with automatic data upload from devices. Adaptations were reviewed by expert study clinicians and patients. The primary end point was change in hemoglobin A1c (HbA1c). Outcomes are reported adhering to consensus recommendations on reporting of AP trials. RESULTS: Twenty-nine patients completed the trial. HbA1c, 7.0 ± 0.8% at the start of AP use, improved to 6.7 ± 0.6% after 12 weeks (-0.3, 95% CI -0.5 to -0.2, P < 0.001). Compared with the SAP run-in, CGM time spent in the hypoglycemic range improved during the day from 5.0 to 1.9% (-3.1, 95% CI -4.1 to -2.1, P < 0.001) and overnight from 4.1 to 1.1% (-3.1, 95% CI -4.2 to -1.9, P < 0.001). Whereas carbohydrate ratios were adapted to a larger extent initially with minimal changes thereafter, basal insulin was adapted throughout. Approximately 10% of adaptation recommendations were manually overridden. There were no protocol-related serious adverse events. CONCLUSIONS: Use of our novel adaptive AP yielded significant reductions in HbA1c and hypoglycemia.

Feasibility of Long-Term Closed-Loop Control: A Multicenter 6-Month Trial of 24/7 Automated Insulin Delivery.

BACKGROUND: In the past few years, the artificial pancreas-the commonly accepted term for closed-loop control (CLC) of blood glucose in diabetes-has become a hot topic in research and technology development. In the summer of 2014, we initiated a 6-month trial evaluating the safety of 24/7 CLC during free-living conditions. RESEARCH DESIGN AND METHODS: Following an initial 1-month Phase 1, 14 individuals (10 males/4 females) with type 1 diabetes at three clinical centers in the United States and one in Italy continued with a 5-month Phase 2, which included 24/7 CLC using the wireless portable Diabetes Assistant (DiAs) developed at the University of Virginia Center for Diabetes Technology. Median subject characteristics were age 45 years, duration of diabetes 27 years, total daily insulin 0.53 U/kg/day, and baseline HbA1c 7.2% (55 mmol/mol). RESULTS: Compared with the baseline observation period, the frequency of hypoglycemia below 3.9 mmol/L during the last 3 months of CLC was lower: 4.1% versus 1.3%, P < 0.001. This was accompanied by a downward trend in HbA1c from 7.2% (55 mmol/mol) to 7.0% (53 mmol/mol) at 6 months. HbA1c improvement was correlated with system use (Spearman r = 0.55). The user experience was favorable with identified benefit particularly at night and overall trust in the system. There were no serious adverse events, severe hypoglycemia, or diabetic ketoacidosis. CONCLUSION: We conclude that CLC technology has matured and is safe for prolonged use in patients' natural environment. Based on these promising results, a large randomized trial is warranted to assess long-term CLC efficacy and safety.

Randomized Crossover Comparison of Personalized MPC and PID Control Algorithms for the Artificial Pancreas.

OBJECTIVE: To evaluate two widely used control algorithms for an artificial pancreas (AP) under nonideal but comparable clinical conditions. RESEARCH DESIGN AND METHODS: After a pilot safety and feasibility study (n = 10), closed-loop control (CLC) was evaluated in a randomized, crossover trial of 20 additional adults with type 1 diabetes. Personalized model predictive control (MPC) and proportional integral derivative (PID) algorithms were compared in supervised 27.5-h CLC sessions. Challenges included overnight control after a 65-g dinner, response to a 50-g breakfast, and response to an unannounced 65-g lunch. Boluses of announced dinner and breakfast meals were given at mealtime. The primary outcome was time in glucose range 70-180 mg/dL. RESULTS: Mean time in range 70-180 mg/dL was greater for MPC than for PID (74.4 vs. 63.7%, P = 0.020). Mean glucose was also lower for MPC than PID during the entire trial duration (138 vs. 160 mg/dL, P = 0.012) and 5 h after the unannounced 65-g meal (181 vs. 220 mg/dL, P = 0.019). There was no significant difference in time with glucose <70 mg/dL throughout the trial period. CONCLUSIONS: This first comprehensive study to compare MPC and PID control for the AP indicates that MPC performed particularly well, achieving nearly 75% time in the target range, including the unannounced meal. Although both forms of CLC provided safe and effective glucose management, MPC performed as well or better than PID in all metrics.

Multinational Home Use of Closed-Loop Control Is Safe and Effective.

OBJECTIVE: To evaluate the efficacy of a portable, wearable, wireless artificial pancreas system (the Diabetes Assistant [DiAs] running the Unified Safety System) on glucose control at home in overnight-only and 24/7 closed-loop control (CLC) modes in patients with type 1 diabetes. RESEARCH DESIGN AND METHODS: At six clinical centers in four countries, 30 participants 18-66 years old with type 1 diabetes (43% female, 96% non-Hispanic white, median type 1 diabetes duration 19 years, median A1C 7.3%) completed the study. The protocol included a 2-week baseline sensor-augmented pump (SAP) period followed by 2 weeks of overnight-only CLC and 2 weeks of 24/7 CLC at home. Glucose control during CLC was compared with the baseline SAP. RESULTS: Glycemic control parameters for overnight-only CLC were improved during the nighttime period compared with baseline for hypoglycemia (time <70 mg/dL, primary end point median 1.1% vs. 3.0%; P < 0.001), time in target (70-180 mg/dL: 75% vs. 61%; P < 0.001), and glucose variability (coefficient of variation: 30% vs. 36%; P < 0.001). Similar improvements for day/night combined were observed with 24/7 CLC compared with baseline: 1.7% vs. 4.1%, P < 0.001; 73% vs. 65%, P < 0.001; and 34% vs. 38%, P < 0.001, respectively. CONCLUSIONS: CLC running on a smartphone (DiAs) in the home environment was safe and effective. Overnight-only CLC reduced hypoglycemia and increased time in range overnight and increased time in range during the day; 24/7 CLC reduced hypoglycemia and increased time in range both overnight and during the day. Compared with overnight-only CLC, 24/7 CLC provided additional hypoglycemia protection during the day.

A review of prevention strategies for gestational diabetes: is there a missing X-factor?

Gestational diabetes affects up to one in five pregnancies and can have significant consequences for both mother and baby. There have been great efforts to identify strategies to prevent gestational diabetes during pregnancy. These efforts have been extended to the pre-pregnancy and postpartum periods to address limitations during pregnancy. In this review we explore how diet, exercise and lifestyle modification can be used to prevent gestational diabetes.

Identifying Key Intervention Opportunities During a Pregnancy Complicated by Diabetes: a Review of Acute Complications of Diabetes During Pregnancy.

Diabetes in pregnancy is associated with significant and sometimes devastating acute complications. It is important that all health care providers are aware of possible complications at each stage of pregnancy so that we can prevent these complications whenever possible and reduce morbidity when they do occur. Most complications associated with diabetes during pregnancy have reduced incidence when blood glucose and blood pressure are optimally controlled. Yet, it is always best to try to optimize diabetes and any comorbidities prior to conception.

Adjustment of Open-Loop Settings to Improve Closed-Loop Results in Type 1 Diabetes: A Multicenter Randomized Trial.

CONTEXT: Closed-loop control (CLC) relies on an individual's open-loop insulin pump settings to initialize the system. Optimizing open-loop settings before using CLC usually requires significant time and effort. OBJECTIVE: The objective was to investigate the effects of a one-time algorithmic adjustment of basal rate and insulin to carbohydrate ratio open-loop settings on the performance of CLC. DESIGN: This study reports a multicenter, outpatient, randomized, crossover clinical trial. PATIENTS: Thirty-seven adults with type 1 diabetes were enrolled at three clinical sites. INTERVENTIONS: Each subject's insulin pump settings were subject to a one-time algorithmic adjustment based on 1 week of open-loop (i.e., home care) data collection. Subjects then underwent two 27-hour periods of CLC in random order with either unchanged (control) or algorithmic adjusted basal rate and carbohydrate ratio settings (adjusted) used to initialize the zone-model predictive control artificial pancreas controller. Subject's followed their usual meal-plan and had an unannounced exercise session. MAIN OUTCOMES AND MEASURES: Time in the glucose range was 80-140 mg/dL, compared between both arms. RESULTS: Thirty-two subjects completed the protocol. Median time in CLC was 25.3 hours. The median time in the 80-140 mg/dl range was similar in both groups (39.7% control, 44.2% adjusted). Subjects in both arms of CLC showed minimal time spent less than 70 mg/dl (median 1.34% and 1.37%, respectively). There were no significant differences more than 140 mg/dL. CONCLUSIONS: A one-time algorithmic adjustment of open-loop settings did not alter glucose control in a relatively short duration outpatient closed-loop study. The CLC system proved very robust and adaptable, with minimal (<2%) time spent in the hypoglycemic range in either arm.