Monetary reinforcement for self-monitoring of blood glucose among young people with type 1 diabetes: evaluating effects on psychosocial functioning.

AIMS: To explore the auxiliary psychosocial effects of a monetary reinforcement intervention targeting self-monitoring of blood glucose among young people with Type 1 diabetes. METHODS: Sixty young people with Type 1 diabetes, HbA1c concentrations between 58 and 119 mmol/mol (7.5-13.0%), and average self-monitoring of blood glucose <4 times per day were randomized to either enhanced usual care or a 24-week intervention of monetary rewards for self-monitoring of blood glucose and associated behaviours (e.g. uploading glucose meters). Data were collected from the young people and their parents at baseline, during the intervention (6, 12 and 24 weeks) and after the intervention (36 weeks). RESULTS: Linear mixed models were used to evaluate the intervention effects on psychosocial outcomes, adjusting for corresponding baseline levels and potential moderation by baseline level. The intervention reduced diabetes distress at week 6 among young people who had average and high baseline distress. It also reduced diabetes distress at weeks 12 and 24 among those with low baseline distress. The intervention also reduced young person-reported diabetes-related family conflict and diabetes-related interference among those with high baseline scores in these areas; however, the intervention worsened young person-reported diabetes interference among those with low baseline interference. Effects were medium-sized and time-limited. CONCLUSIONS: Findings indicate predominantly positive impacts of monetary reinforcement interventions on psychosocial outcomes, although effects varied by outcome and time point. Whereas early improvements in diabetes distress were observed for all who received the intervention, improvements in other areas varied according to the level of psychosocial challenge at baseline. Incorporating psychosocial interventions may bolster and maintain effects over time.

Predicting successful induction of oocyte maturation after gonadotropin-releasing hormone agonist (GnRHa) trigger.

STUDY QUESTION: Are there factors predicting the number of total and mature oocytes retrieved after controlled ovarian hyperstimulation (COH) utilizing a gonadotropin-releasing hormone (GnRH) antagonist protocol and a GnRH agonist (GnRHa) to induce oocyte maturation? SUMMARY ANSWER: Peak estradiol (E2) level, post-trigger LH and progesterone and the magnitude of LH rise are independent predictors of the total number of oocytes and mature oocytes retrieved. WHAT IS KNOWN ALREADY: Despite multiple follicular development in high responders, oocyte retrieval after a GnRHa trigger in a small subset of patients fails to obtain a substantial number of total oocytes or mature oocytes. STUDY DESIGN, SIZE AND DURATION: A retrospective chart review of all autologous and oocyte donation cycles utilizing a GnRHa antagonist protocol where GnRHa was used for the induction of oocyte maturation between 1 April 2003 and 31 December 2011. PARTICIPANTS/MATERIALS, SETTING AND METHODS: A total of 508 autologous and donor IVF/ICSI cycles utilizing a GnRH antagonist protocol for COH and GnRHa for the induction of oocyte maturation at a university-based tertiary fertility center. MAIN RESULTS AND THE ROLE OF CHANCE: Peak E2 on the day of trigger (r = 0.19, P < 0.001), post-trigger LH (r = 0.12, P = 0.009) and progesterone (r = 0.47, P < 001) and LH rise (r = 0.18, P < 0.001) all positively correlated with the number of total and mature oocytes retrieved. The true incidence of empty follicle syndrome was 1.4% (7/508). There was no post-trigger LH or progesterone cut-off value for the prediction of oocyte yield. However, all cases of empty follicle syndrome occurred in patients with post-trigger LH <15 IU/l and P ≤ 3.5 ng/ml. The findings of this study may also be due to chance since it was a retrospective study and not prospectively designed. LIMITATION, REASONS FOR CAUTION: This is a retrospective chart review and therefore subject to bias. Serum hormone measurements were performed between 8 and 12 h after GnRHa trigger rather than a standardized time period following trigger administration. Therefore, peak levels of LH may have been missed due to the short ascending limb of LH rise lasting approximately 4 h after GnRHa trigger. WIDER IMPLICATIONS OF THE FINDINGS: The results of this study can be generalized to high responders utilizing a GnRH antagonist protocol for COH and a GnRHa for the induction of oocyte maturation. The use of alternative stimulation regimens or medications will limit the ability to generalize the results of this study to other populations. STUDY FUNDING/COMPETING INTEREST(S): This study was not funded, and there are no conflicts of interest. TRIAL REGISTRATION NUMBER: n/a.

Importance of bone mineral density measurements in evaluating fragility bone fracture risk in Asian Indian men.

UNLABELLED: We evaluated the effect of BMD on fracture risk prediction using FRAX® among Asian Indian men when used in conjunction with clinical risk factors. A majority of our subjects were either osteopenic or osteoporotic, and their fracture risk increased when FRAX® was used in conjunction with femur neck T-scores. INTRODUCTION: Asian Indian men living in the United States may represent a population that is at high and underappreciated risk for fragility bone fractures. PURPOSE: To evaluate the effect of BMD on fracture risk prediction using FRAX® among Asian Indian men when used in conjunction with clinical risk factors. METHODS: Forty four Asian Indian men (mean age 64.9 (±8.4) years) who had lived in the United States for an average of 33.6 (±10.6) years underwent BMD measurement at the proximal femur. Subjects were subjected to a general physical exam and history of fracture, hip fracture in a parent, current smoking and alcohol use, and diagnosis of inflammatory arthritis was obtained. Data from each subject were entered into the FRAX® algorithm and 10-year fracture probabilities were calculated using clinical risk factors (CRFs) alone and in combination with femur neck T-scores. RESULTS: Thirteen subjects (29.5%) had femur neck T-scores ≥ -1.0, 28 (63.6%) T-scores between -1.0 and -2.5, and three (6.8%) T-scores < -2.5. The 10-year probability of a major osteoporotic fracture based on a combination of clinical risk factors and femur neck T-scores was significantly higher than the fracture probability based on clinical risk factors alone (t(43) = 2.58, p = 0.01). CONCLUSIONS: Among Asian Indian men, the 10-year probability of a major osteoporotic fracture increases when femur neck T-scores are added to clinical risk factors in the FRAX® algorithm, and this population have a high fracture probability even in the absence of clinical risk factors.