Utility of Repeat Sampling in Bilateral Aldosterone Suppression During Adrenal Vein Sampling for Primary Aldosteronism.

Primary aldosteronism (PA) is the most common form of secondary hypertension. Accurate subtyping of PA is essential to identify unilateral disease, as adrenalectomy improves outcomes. Subtyping PA requires adrenal vein sampling (AVS), which is technically challenging and results from AVS may not always be conclusive. We present a case of a 37-year-old man with PA whose AVS studies were inconclusive due to apparent bilateral aldosterone suppression (ABAS). As a result, our patient was misdiagnosed as having bilateral PA and medically managed until a repeat AVS showed lateralization to the right adrenal gland. ABAS is an underrecognized phenomenon that may confound the subtyping of PA. We recommend repeating AVS in such cases and discuss strategies to minimize ABAS.

Combining an Electrochemical Continuous Glucose Sensor With an Insulin Delivery Cannula: A Feasibility Study.

BACKGROUND: Combining a continuous glucose monitor with an insulin delivery cannula (CGM-IS) could benefit clinical outcomes. We evaluated the feasibility of a single-needle insertion electrochemical investigational CGM-IS (Pacific Diabetes Technologies, Portland, Oregon) in type 1 diabetes adults. METHODS: Following 48 hours run-in using a Medtronic 780G in manual mode with a commercial insulin set, 12 participants commenced insulin delivery using the CGM-IS. A standardized test meal was eaten on the mornings of days 1 and 4. Venous samples were collected every 10 minutes one hour prior to and 15 minutes post-meal for four hours. CGM-IS glucose measurements were post-processed with a single capillary blood calibration during warm-up and benchmarked against YSI. A Dexcom G6 sensor was worn post-consent to study end. RESULTS: Mean absolute relative difference (MARD) for the CGM-IS glucose measurements was 9.2% (484 paired data points). Consensus error grid revealed 88.6% within zone A and 100% in A + B. Mean (SD) % bias was -3.5 (11.7) %. There were 35 paired YSI readings <100 mg/dL cutoff and 449 ≥100 mg/dL with 81.4% within ±15 mg/dL or ±15%, and 89.9% within ±20 mg/dL or ±20%. Two cannula occlusions required discontinuation of insulin delivery: one at 70 hours post insertion and another during the day 4 meal test. Mean (SD) Dexcom glucose measurements during run-in and between meal tests was respectively 161.3 ± 27.3 mg/dL versus 158.0 ± 25.6 mg/dL; P = .39 and corresponding mean total daily insulin delivered by the pump was 58.0 ± 25.4 Units versus 57.1 ± 28.8 Units; P = .47. CONCLUSIONS: Insulin delivery and glucose sensing with the investigational CGM-IS was feasible. Longer duration studies are needed.

Advances in Automated Insulin Delivery with the Medtronic 780G: The Australian Experience.

Aim: To assess the real-world performance of MiniMed™ 780G for Australians with type 1 diabetes (T1D) following advanced hybrid closed loop (AHCL) activation and to evaluate the effect of changing from MiniMed 670/770G to 780G. Methods: We analyzed deidentified Carelink™ continuous glucose monitoring (CGM) data from Australian users from January 2020 to December 2022, including the proportion attaining three major consensus targets: Glucose management indicator (GMI <7.0%), time in range (TIR 70-180 mg/dL >70%), and time below range (TBR 70 mg/dL <4%). Results: Comparing 670/770G users (n = 5676) for mean ± standard deviation 364 ± 244 days with 780G users (n = 3566) for 146 ± 145 days, the latter achieved a higher TIR (72.6% ± 10.6% vs. 67.3% ± 11.4%; P < 0.001), lower time above range (TAR) (25.5% ± 10.9% vs. 30.6% ± 11.7%; P < 0.001), and lower GMI (6.9% ± 0.4% vs. 7.2% ± 0.4%; P < 0.001) without compromising TBR (1.9% ± 1.8% vs. 2.0% ± 1.8%; P = 0.0015). Of 1051 670/770G users transitioning to 780G, TIR increased (70.0% ± 10.7% to 74.0% ± 10.2%; P < 0.001), TAR decreased (28.1% ± 10.9% to 24.0% ± 10.7%; P < 0.001), and TBR was unchanged. The percentage of users attaining all three CGM targets was higher in 780G users (50.1% vs. 29.5%; P < 0.001). CGM metrics were stable at 12 months post-transition. Conclusion: Real-world data from Australia shows that a higher proportion of MiniMed 780G users meet clinical targets for CGM consensus metrics compared to MiniMed 670/770G users and glucose control was sustained over 12 months.

Effects of aromatase inhibitor therapy on adiposity and cardiometabolic health in postmenopausal women: a controlled cohort extension study.

Purpose: We previously demonstrated that 12 months of aromatase inhibitor (AI) treatment was not associated with a difference in body composition or other markers of cardiometabolic health when compared to controls. Here we report on the pre-planned extension of the study. The pre-specified primary hypothesis was that AI therapy for 24 months would lead to increased visceral adipose tissue (VAT) area when compared to controls. Methods: We completed a 12-month extension to our prospective 12-month cohort study of 52 women commencing AI treatment (median age 64.5 years) and 52 women with breast pathology not requiring endocrine therapy (63.5 years). Our primary outcome of interest was VAT area. Secondary and exploratory outcomes included other measures of body composition, hepatic steatosis, measures of atherosclerosis and vascular reactivity. Using mixed models and the addition of a fourth time point, we increased the number of study observations by 79 and were able to rigorously determine the treatment effect. Results: Among study completers (AI = 39, controls = 40), VAT area was comparable between groups over 24 months, the mean-adjusted difference was -1.54 cm2 (95% CI: -14.9; 11.9, P = 0.79). Both groups demonstrated parallel and continuous increases in VAT area over the observation period that did not diverge or change between groups. No statistically significant difference in our secondary and exploratory outcomes was observed between groups. Conclusions: While these findings provide reassurance that short-to-medium-term exposure to AI therapy is not associated with metabolically adverse changes when compared to controls, risk evolution should be less focussed on the AI-associated effect and more on the general development of cardiovascular risk over time.