Elizabeth Littlejohn

Multivariable adaptive closed-loop control of an artificial pancreas without meal and activity announcement.

BACKGROUND Accurate closed-loop control is essential for developing artificial pancreas (AP) systems that adjust insulin infusion rates from insulin pumps. Glucose concentration information from continuous glucose monitoring (CGM) systems is the most important information for the control system. Additional physiological measurements can provide valuable information that can enhance the accuracy of the control system. Proportional-integral-derivative control and model predictive control have been popular in AP development. Their implementations to date rely on meal announcements (e.g., bolus insulin dose based on insulin:carbohydrate ratios) by the user. Adaptive control techniques provide a powerful alternative that do not necessitate any meal or activity announcements. MATERIALS AND METHODS Adaptive control systems based on the generalized predictive control framework are developed by extending the recursive modeling techniques. Physiological signals such as energy expenditure and galvanic skin response are used along with glucose measurements to generate a multiple-input-single-output model for predicting future glucose concentrations used by the controller. Insulin-on-board (IOB) is also estimated and used in control decisions. The controllers were tested with clinical studies that include seven cases with three different patients with type 1 diabetes for 32 or 60 h without any meal or activity announcements. RESULTS The adaptive control system kept glucose concentration in the normal preprandial and postprandial range (70-180 mg/dL) without any meal or activity announcements during the test period. After IOB estimation was added to the control system, mild hypoglycemic episodes were observed only in one of the four experiments. This was reflected in a plasma glucose value of 56 mg/dL (YSI 2300 STAT; Yellow Springs Instrument, Yellow Springs, OH) and a CGM value of 63 mg/dL). CONCLUSIONS Regulation of blood glucose concentration with an AP using adaptive control techniques was successful in clinical studies, even without any meal and physical activity announcement.

Multivariable Adaptive Identification and Control for Artificial Pancreas Systems

A constrained weighted recursive least squares method is proposed to provide recursive models with guaranteed stability and better performance than models based on regular identification methods in predicting the variations of blood glucose concentration in patients with Type 1 Diabetes. Use of physiological information from a sports armband improves glucose concentration prediction and enables earlier recognition of the effects of physical activity on glucose concentration. Generalized predictive controllers (GPC) based on these recursive models are developed. The performance of GPC for artificial pancreas systems is illustrated by simulations with UVa-Padova simulator and clinical studies. The controllers developed are good candidates for artificial pancreas systems with no announcements from patients.

Antimüllerian hormone levels are independently related to ovarian hyperandrogenism and polycystic ovaries

OBJECTIVE To determine the relationship of antimüllerian hormone (AMH) levels to polycystic ovaries and ovarian androgenic function. DESIGN Prospective case-control study. SETTING General clinical research center. PARTICIPANT(S) Eumenorrheic asymptomatic volunteers without (V-NO; n = 19; reference population) or with (V-PCO; n = 28) a polycystic ovary and hyperandrogenemic anovulatory subjects grouped according to ovarian function into typical PCOS (PCOS-T; n = 37) and atypical PCOS (PCOS-A; n = 18). INTERVENTION(S) Pelvic ultrasonography, short dexamethasone androgen-suppression test (SDAST), and GnRH agonist (GnRHag) test. MAIN OUTCOME MEASURE(S) Baseline AMH levels were related to polycystic ovary status, testosterone response to SDAST, and 17-hydroxyprogesterone response to GnRHag test. RESULT(S) AMH levels correlated with SDAST and GnRHag test outcomes. AMH was elevated (>6.2 ng/mL) in 32% of V-PCO versus 5% V-NO. The 21% of V-PCO who met Rotterdam PCOS criteria all had functional ovarian hyperandrogenism, but AMH levels were similar to nonhyperandrogenic V-PCO. AMH >10.7 ng/mL discriminated V-PCO from PCOS with 96% specificity and 41% sensitivity for PCOS-T, and insignificantly for PCOS-A. CONCLUSION(S) AMH levels are independently related to ovarian androgenic function and polycystic ovaries. Very high AMH levels are specific but insensitive for PCOS. In the absence of hyperandrogenism, moderate AMH elevation in women with normal-variant polycystic ovaries seems to indicate an enlarged oocyte pool.

An Integrated Multivariable Artificial Pancreas Control System

Objective: The objective was to develop a closed-loop (CL) artificial pancreas (AP) control system that uses continuous measurements of glucose concentration and physiological variables, integrated with a hypoglycemia early alarm module to regulate glucose concentration and prevent hypoglycemia. Materials and Methods: Eleven open-loop (OL) and 9 CL experiments were performed. A multivariable adaptive artificial pancreas (MAAP) system was used for the first 6 CL experiments. An integrated multivariable adaptive artificial pancreas (IMAAP) system consisting of MAAP augmented with a hypoglycemia early alarm system was used during the last 3 CL experiments. Glucose values and physical activity information were measured and transferred to the controller every 10 minutes and insulin suggestions were entered to the pump manually. All experiments were designed to be close to real-life conditions. Results: Severe hypoglycemic episodes were seen several times during the OL experiments. With the MAAP system, the occurrence of severe hypoglycemia was decreased significantly (P < .01). No hypoglycemia was seen with the IMAAP system. There was also a significant difference (P < .01) between OL and CL experiments with regard to percentage of glucose concentration (54% vs 58%) that remained within target range (70-180 mg/dl). Conclusions: Integration of an adaptive control and hypoglycemia early alarm system was able to keep glucose concentration values in target range in patients with type 1 diabetes. Postprandial hypoglycemia and exercise-induced hypoglycemia did not occur when this system was used. Physical activity information improved estimation of the blood glucose concentration and effectiveness of the control system.

Hypoglycemia Early Alarm Systems Based On Multivariable Models.

Hypoglycemia is a major challenge of artificial pancreas systems and a source of concern for potential users and parents of young children with Type 1 diabetes (T1D). Early alarms to warn the potential of hypoglycemia are essential and should provide enough time to take action to avoid hypoglycemia. Many alarm systems proposed in the literature are based on interpretation of recent trends in glucose values. In the present study, subject-specific recursive linear time series models are introduced as a better alternative to capture glucose variations and predict future blood glucose concentrations. These models are then used in hypoglycemia early alarm systems that notify patients to take action to prevent hypoglycemia before it happens. The models developed and the hypoglycemia alarm system are tested retrospectively using T1D subject data. A Savitzky-Golay filter and a Kalman filter are used to reduce noise in patient data. The hypoglycemia alarm algorithm is developed by using predictions of future glucose concentrations from recursive models. The modeling algorithm enables the dynamic adaptation of models to inter-/intra-subject variation and glycemic disturbances and provides satisfactory glucose concentration prediction with relatively small error. The alarm systems demonstrate good performance in prediction of hypoglycemia and ultimately in prevention of its occurrence.

Blunted sleep-related luteinizing hormone rise in healthy premenarcheal pubertal girls with elevated body mass index.

OBJECTIVE Our objective was to determine whether excessive adiposity is associated with alteration of the normal hormonal changes of early pubertal girls. DESIGN AND PARTICIPANTS Healthy 6.4- to 9.5-yr-old, prepubertal (PRE, n = 20) and 9.4- to 13.0-yr-old pubertal premenarcheal volunteers (PUB, n = 20) were divided into excessive-weight (EW) or normal-weight (NW) groups according to the 85th percentile body mass index. INTERVENTIONS AND SETTING: Overnight blood sampling; GnRH agonist (GnRHag), low-dose ACTH, oral glucose tolerance tests, and pelvic ultrasonograms were performed in our Clinical Research Center. RESULTS EW girls were similar in age and baseline and ACTH- and GnRHag-stimulated androgen levels to stage-matched NW girls. However, the sleep-related LH rise was blunted in EW-PUB girls compared with NW-PUB girls. The sleep-related rise of mean LH in EW-PUB [0.68 +/- 0.35 (sem) U/liter] was insignificant, less than that of NW-PUB (2.1 +/- 0.45, P < 0.05) and not significantly different from that of PRE girls (0.08+/-0.03). EW-PUB had slower LH pulse frequency and a lower rise in LH pulse amplitude during sleep than NW-PUB girls (both P < 0.05). Overnight FSH patterns paralleled LH patterns, whereas estradiol levels were similar in stage-matched NW and EW groups, differing between stages as expected. Early morning and peak LH, FSH, and estradiol responses to GnRHag were similar in EW-PUB and NW-PUB and significantly greater than those of PRE girls. CONCLUSIONS Healthy EW-PUB girls have significantly blunted sleep-related LH production. These data suggest that excess adiposity, in the absence of sex steroid excess, may subtly suppress hypothalamic-pituitary-gonadal function in premenarcheal pubertal girls.

Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System

A novel meal-detection algorithm is developed based on continuous glucose measurements. Bergmans minimal model is modified and used in an unscented Kalman filter for state estimations. The estimated rate of appearance of glucose is used for meal detection. Data from nine subjects are used to assess the performance of the algorithm. The results indicate that the proposed algorithm works successfully with high accuracy. The average change in glucose levels between the meals and the detection points is 16(±9.42) [mg/dl] for 61 successfully detected meals and snacks. The algorithm is developed as a new module of an integrated multivariable adaptive artificial pancreas control system. Meal detection with the proposed method is used to administer insulin boluses and prevent most of postprandial hyperglycemia without any manual meal announcements. A novel meal bolus calculation method is proposed and tested with the UVA/Padova simulator. The results indicate significant reduction in hyperglycemia.

Determination of the source of androgen excess in functionally atypical polycystic ovary syndrome by a short dexamethasone androgen-suppression test and a low-dose ACTH test

BACKGROUND Polycystic ovary syndrome (PCOS) patients typically have 17-hydroxyprogesterone (17OHP) hyperresponsiveness to GnRH agonist (GnRHa) (PCOS-T). The objective of this study was to determine the source of androgen excess in the one-third of PCOS patients who atypically lack this type of ovarian dysfunction (PCOS-A). METHODS Aged-matched PCOS-T (n= 40), PCOS-A (n= 20) and controls (n= 39) were studied prospectively in a General Clinical Research Center. Short (4 h) and long (4-7 day) dexamethasone androgen-suppression tests (SDAST and LDAST, respectively) were compared in subsets of subjects. Responses to SDAST and low-dose adrenocorticotropic hormone (ACTH) were then evaluated in all. RESULTS Testosterone post-SDAST correlated significantly with testosterone post-LDAST and 17OHP post-GnRHa (r = 0.671-0.672), indicating that all detect related aspects of ovarian dysfunction. An elevated dehydroepiandrosterone peak in response to ACTH, which defined functional adrenal hyperandrogenism, was similarly prevalent in PCOS-T (27.5%) and PCOS-A (30%) and correlated significantly with baseline dehydroepiandrosterone sulfate (DHEAS) (r = 0.708). Functional ovarian hyperandrogenism was detected by subnormal testosterone suppression by SDAST in most (92.5%) PCOS-T, but significantly fewer PCOS-A (60%, P< 0.01). Glucose intolerance was absent in PCOS-A, but present in 30% of PCOS-T (P < 0.001). Most of the PCOS-A cases with normal testosterone suppression in response to SDAST (5/8) lacked evidence of adrenal hyperandrogenism and were obese. CONCLUSIONS Functional ovarian hyperandrogenism was not demonstrable by SDAST in 40% of PCOS-A. Most of these cases had no evidence of adrenal hyperandrogenism. Obesity may account for most hyperandrogenemic anovulation that lacks a glandular source of excess androgen, and the SDAST seems useful in making this distinction.

Intractable early childhood obesity as the initial sign of insulin resistant hyperinsulinism and precursor of polycystic ovary syndrome.

OBJECTIVE We report that intractable early childhood obesity may be associated with severe insulin resistance syndromes (pseudo-Cushings syndrome and pseudo-acromegaly) and precede polycystic ovary syndrome (PCOS). STUDY DESIGN/RESULTS Patient 1 had prepubertal obesity followed by early puberty and was diagnosed with pseudo-Cushings syndrome and insulin resistance at 10.3 years. Oligomenorrhea, androgen excess, and type 2 diabetes mellitus (DM2) emerged at 13.5 years. Patient 2 developed intractable prepubertal obesity followed by atypical true sexual precocity and pseudo-Cushings syndrome in early childhood. By 11.3 years, oligomenorrhea, androgen excess, and DM2 had appeared. Patient 3 had prepubertal overgrowth in weight and height and was diagnosed with pseudo-acromegaly, menstrual irregularity, androgen excess, and impaired glucose tolerance at 14.3 years of age. Patient 4 had prepubertal overgrowth that evolved into pseudo-acromegaly, insulin resistance, secondary amenorrhea, and androgen excess at 15.6 years. CONCLUSIONS Intractable prepubertal obesity was recognized to culminate in early childhood pseudo-Cushings syndrome or pseudo-acromegaly, which are manifestations of insulin-resistant hyperinsulinism, and to herald adolescent PCOS.

LH Dynamics in Overweight Girls with Premature Adrenarche and Slowly Progressive Sexual Precocity

Background. Excess adiposity and premature adrenarche (PA) are risk factors for the development of polycystic ovary syndrome (PCOS). Methods. Girls with slowly progressive precocious breast development, who were overweight and had PA (SPPOPA, 6.2–8.2 years, ), overweight PA (6.6–10.8 years, ), and overweight premenarcheal controls (OW-PUB, 10.6–12.8 years, ) underwent hormonal sleep testing and GnRH agonist (GnRHag) and ACTH tests. Results. Despite an insignificant sleep-related increase in LH and prepubertal baseline hormone levels, SPPOPA peak LH and estradiol responses to GnRHag were intermediate between those of PA and OW-PUB, the LH being significantly different from both. Conclusions. GnRHag tests indicate that SPPOPA is a slowly progressive form of true puberty with blunted LH dynamics. These results argue against the prepubertal hyperandrogenism of excess adiposity or PA enhancing LH secretion or causing ovarian hyperandrogenism prior to menarche. Excess adiposity may contribute to both the early onset and slow progression of puberty.