https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:51174  95th percentile for age < 18 years, and systolic BP > 130 and/or diastolic BP > 80 mmHg for age ≥ 18 years. Multivariable Generalised Estimating Equations were used to examine demographic and clinical factors associated with BP in the hypertensive range across all visits. Results: Data from 6338 young people (male 52.6%) attending 24 participating centres across 36,655 T1D healthcare visits were included; 2812 (44.4%) had BP recorded at last visit. Across all visits, 19.4% of youth aged < 18 years and 21.7% of those aged ≥ 18 years met criteria for hypertension. In both age groups, BP in the hypertensive range was associated with male sex, injection (vs. pump) therapy, higher HbA1c, and higher body mass index. Conclusions: There is a high proportion of adolescents and young adults reported with BP persistently in hypertensive ranges. Findings flag the additive contribution of hypertension to the well-established body of evidence indicating a need to review healthcare models for adolescents and young adults with T1D.]]> Wed 28 Feb 2024 15:58:15 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52328 3 months, aged ≤21 years) for all 4 years from 2018 to 2021. Statistical models were adjusted, among others, for technology use. Results: Sixty-five centers provided telemedicine during COVID-19. Among those centers naive to telemedicine before the pandemic (n = 22), four continued only face-to-face visits. Centers that transitioned partially to telemedicine (n = 32) showed a steady increase in HbA1c between 2018 and 2021 (p < 0.001). Those that transitioned mainly to telemedicine (n = 33 %) improved HbA1c in 2021 compared to 2018 (p < 0.001). Conclusions: Changes to models of care delivery driven by the pandemic showed significant associations with HbA1c shortly after the pandemic outbreak and 2 years of follow-up. The association appeared independent of the concomitant increase in technology use among youth with type 1 diabetes.]]> Wed 17 Apr 2024 15:23:53 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:24093 0.05). Protein loads of 75 and 100 g resulted in lower glycaemic excursions than control in the 60-120 min postprandial interval, but higher excursions in the 180-300 min interval. In comparison with 20 g glucose, the large protein loads resulted in significantly delayed and sustained glucose excursions, commencing at 180 min and continuing to 5 h. Conclusions: Seventy-five grams or more of protein alone significantly increases postprandial glycaemia from 3 to 5 h in people with Type 1 diabetes mellitus using intensive insulin therapy. The glycaemic profiles resulting from high protein loads differ significantly from the excursion from glucose in terms of time to peak glucose and duration of the glycaemic excursion. This research supports recommendations for insulin dosing for large amounts of protein.]]> Wed 11 Apr 2018 17:03:56 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20396 Wed 11 Apr 2018 15:20:35 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20481 Wed 11 Apr 2018 14:29:37 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:12138 Wed 11 Apr 2018 11:47:44 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:14765 Wed 11 Apr 2018 11:44:11 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49861 Wed 07 Jun 2023 13:41:43 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:35891 3 months attending diabetes centres in Newcastle, Australia. Rates of overweight and obesity were compared with matched population survey results. Results: Data from 308 youth and 283 young adults were included. In girls, significantly higher prevalence of overweight and obesity were seen in the 5–8 (43% vs. 18%), 13–16 (41% vs. 27%), 18–24 (46% vs. 34%) and 25–30 (60% vs. 43%) years age groups; whereas in boys increased prevalence was observed in the 5–8 years age group only (41% vs. 18%). Rates of overweight and obesity increased with age across sexes. In youth, BMI standard deviation score was correlated with socio‐economic status, insulin regimen, blood pressure and blood lipids (P < 0.05). In adults, BMI was positively associated with blood pressure, and longer diabetes duration (P < 0.02). Conclusions: Overweight and obesity are over‐represented in young persons with type 1 diabetes, particularly girls. As overweight is associated with other cardiovascular disease markers early intervention is paramount.]]> Wed 06 Apr 2022 13:57:00 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49023 Wed 03 May 2023 12:38:05 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:36525 Wed 01 Jul 2020 11:21:51 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49963 Tue 20 Jun 2023 14:36:29 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46326 Tue 15 Nov 2022 12:13:53 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:43119 Tue 13 Sep 2022 14:32:31 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42869 Tue 06 Sep 2022 09:31:19 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:51324 1 week. The closed-loop set-point was temporarily increased 2 h pre-exercise and a snack eaten if plasma glucose was ≤126 mg/dL pre-exercise. Exercise commenced at ∼16:00. A standardized meal was eaten at ∼20:40. Hypoglycemic events were defined as a continuous glucose monitor (CGM) reading <70 mg/dL for ≥15 min. Four-hour postevening meal and overnight (00:00-06:00) CGM metrics for exercise were compared with the prior nonexercise day. Results: There was no severe hypoglycemia. Between 00:00 and 06:00, the proportion of nights with hypoglycemia did not differ postexercise versus control for HIE (18% vs. 11%; P = 0.688), RE (4% vs. 14%; P = 0.375), and MIE (7% vs. 14%; P = 0.625). Time in range (TIR) (70-180 mg/dL), >75% for all nights, did not differ between exercise conditions and control. Hypoglycemia episodes postmeal after exercise versus control did not differ for HIE (22% vs. 7%; P = 0.219) and MIE (10% vs. 14%; P > 0.999), but were greater post-RE (39% vs. 10%; P = 0.012). Conclusions: Overnight TIR was excellent with AID without increased hypoglycemia postexercise between 00:00 and 06:00 compared with nonexercise days. In contrast, hypoglycemia risk was increased after the first meal post-RE, suggesting the importance of greater vigilance and specific guidelines for meal-time dosing, particularly with vigorous RE. ACTRN12618000905268.]]> Thu 31 Aug 2023 14:35:00 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30981 Thu 27 Jan 2022 15:56:46 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:51868 75 mmol/mol (>9.0%) in 2004 (p = .873), 2010 (p = .10) or 2016 (p = .630). Mean HbA1c decreased from 2004 to 2016 in the 10-13 year (69 mmol/mol (8.4%) vs. 57 mmol/mol (7.4%), p = <.001) and 14-17 year group (72 mmol/mol (8.7%) vs. 63 mmol/mol (7.9%), p = <.001). Prior to the implementation of MDI and CSII in 2004 only 10% of 10-13 year olds and 8% of 14-17 year olds achieved the international target for glycemic control (HbA1c 53 mmol/mol [<7.0%]). In 2016, this increased to 31% of 10-13 year olds and 21% of 14-17 year olds. CONCLUSIONS: BMI-SDS did not increase with the change to intensive insulin therapy despite a doubling in the number of adolescents achieving the recommended glycemic target of <7.0% (53 mmol/mol). HbA1c was not associated with weight gain.]]> Thu 21 Sep 2023 10:24:57 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30992 Thu 09 Dec 2021 11:05:01 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:36160 Thu 09 Dec 2021 11:04:05 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46812 n = 44 articles) and few studies comparing to the reference standard (n = 10 articles) of a diagnostic interview. This review shows that a variety of tools have been used to screen and identify disordered eating behaviours and eating disorders in people with T1D. Future research including comparison to a gold standard diagnostic interview is warranted to further evaluate the validity and reliability of available tools.]]> Thu 01 Dec 2022 10:32:13 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:9586 0.05). Mean gram error and meal size were negatively correlated (r = -0.70, P < 0.0001). The longer children had been CHO counting the greater the mean percentage error (r = 0.173, P = 0.014). Core foods in non-standard quantities were most frequently inaccurately estimated, while individually labelled foods were most often accurately estimated. Conclusions: Children with Type 1 diabetes and their caregivers can estimate the carbohydrate content of meals with reasonable accuracy. Teaching CHO counting in gram increments did not improve accuracy compared with CHO portions or exchanges. Large meals tended to be underestimated and snacks overestimated. Repeated age-appropriate education appears necessary to maintain accuracy in carbohydrate estimations.]]> Sat 24 Mar 2018 08:39:11 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:7614 Sat 24 Mar 2018 08:34:43 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:1443 Sat 24 Mar 2018 08:28:07 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:16009 Sat 24 Mar 2018 08:19:29 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:13337 Sat 24 Mar 2018 08:17:02 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:10521 8.0% (79% v 62% city, 56% capital) and lowest proportion < 7% (4% v 7%, 22%) (both P < 0.001). Fewer young people made unplanned use of acute services for diabetes crisis management in the capital (24% v 49% city, 50% regional area; P < 0.001). In the regional area, routine review did not occur reliably even annually, with marked attrition of patients from adult services after the first year of contact. Conclusion: Inadequate routine specialist care, poor diabetes self-management and frequent use of acute services for crisis management, particularly in regional areas, suggest service redesign is needed to encourage young people’s engagement.]]> Sat 24 Mar 2018 08:13:58 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21443 Sat 24 Mar 2018 08:05:43 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21267 Sat 24 Mar 2018 07:54:42 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:19680 Sat 24 Mar 2018 07:53:39 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:28288 Sat 24 Mar 2018 07:41:23 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29188 Sat 24 Mar 2018 07:31:38 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30983 1c, height SD score [SDS], overweight/obesity) and type 1 diabetes/CD versus type 1 diabetes, adjusting for sex, age, and diabetes duration. Results: Biopsy-confirmed CD was present in 1,835 youths (3.5%) and was diagnosed at a median age of 8.1 years (interquartile range 5.3–11.2 years). Diabetes duration at CD diagnosis was <1 year in 37% of youths, >1–2 years in 18% of youths, >3–5 years in 23% of youths, and >5 years in 17% of youths. CD prevalence ranged from 1.9% in the T1DX to 7.7% in the ADDN and was higher in girls than boys (4.3% vs. 2.7%, P < 0.001). Children with coexisting CD were younger at diabetes diagnosis compared with those with type 1 diabetes only (5.4 vs. 7.0 years of age, P < 0.001) and fewer were nonwhite (15 vs. 18%, P < 0.001). Height SDS was lower in those with CD (0.36 vs. 0.48, adjusted P < 0.001) and fewer were overweight/obese (34 vs. 37%, adjusted P < 0.001), whereas mean HbA_1c values were comparable: 8.3 ± 1.5% (67 ± 17 mmol/mol) versus 8.4 ± 1.6% (68 ± 17 mmol/mol). Conclusions: CD is a common comorbidity in youth with type 1 diabetes. Differences in CD prevalence may reflect international variation in screening and diagnostic practices, and/or CD risk. Although glycemic control was not different, the lower height SDS supports close monitoring of growth and nutrition in this population.]]> Sat 24 Mar 2018 07:27:34 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:22661 Sat 24 Mar 2018 07:15:39 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49520 Sat 20 May 2023 12:32:19 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:44787 Mon 24 Oct 2022 09:17:37 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:32314 Mon 23 Sep 2019 12:52:02 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:32330 Mon 23 Sep 2019 12:41:35 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:33614 Mon 23 Sep 2019 11:34:11 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:47558 Mon 23 Jan 2023 13:04:40 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49565 Mon 22 May 2023 09:20:15 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:51762 Mon 18 Sep 2023 14:23:57 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38497 10% or 86 mmol/mol) were screened for psychological disorders using a validated tool; this was the only indicator with <50% estimated adherence. Adherence by care type was: 86.1% for diagnosis (95% CI 76.7 to 92.7); 78.8% for routine care (95% CI 65.4 to 88.9) and 83.9% for emergency care (95% CI 78.4 to 88.5). Conclusions: Most indicators for care of children with type 1 diabetes mellitus were adhered to. However, there remains room to improve adherence to guidelines for optimization of practice consistency and minimization of future disease burden.]]> Mon 11 Oct 2021 16:05:06 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:44181 Mon 10 Oct 2022 10:48:25 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52984 Mon 06 Nov 2023 10:46:55 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39852 Fri 22 Jul 2022 13:14:52 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39985 Fri 22 Jul 2022 13:00:18 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:40131 1c < 65 mmol/mol (8.1%), received a 50 g protein, 30 g carbohydrate, low-fat (< 1 g) breakfast drink over five consecutive days at home. A standard insulin dose (100%) was compared with additional doses of 115, 130, 145 and 160% for the protein, in randomized order. Doses were commenced 15-min pre-drink and delivered over 3 h using a combination bolus with 65% of the standard dose given up front. Postprandial glycaemia was assessed by 4 h of continuous glucose monitoring. Results: The 100% dosing resulted in postprandial hyperglycaemia. From 120 min, ≥ 130% doses resulted in significantly lower postprandial glycaemic excursions compared with 100% (P < 0.05). A 130% dose produced a mean (sd) glycaemic excursion that was 4.69 (2.42) mmol/l lower than control, returning to baseline by 4 h (P < 0.001). From 120 min, there was a significant increase in the risk of hypoglycaemia compared with control for 145% [odds ratio (OR) 25.4, 95% confidence interval (CI) 5.5–206; P < 0.001) and 160% (OR 103, 95% CI 19.2–993; P < 0.001). Some 81% (n = 21) of participants experienced hypoglycaemia following a 160% dose, whereas 58% (n = 15) experienced hypoglycaemia following a 145% dose. There were no hypoglycaemic events reported with 130%. Conclusions: The addition of 30% more insulin to a standard dose for a high-protein meal, delivered using a combination bolus, improves postprandial glycaemia without increasing the risk of hypoglycaemia.]]> Fri 15 Jul 2022 09:55:16 AEST ]]>