Supplementary information files for Relationships between exposure to gestational diabetes treatment and neonatal anthropometry: Evidence from the Born in Bradford (BiB)

© the authors, CC-BY NCSupplementary files for article Relationships between exposure to gestational diabetes treatment and neonatal anthropometry: Evidence from the Born in Bradford (BiB)Objectives To examine the relationships between gestational diabetes mellitus (GDM) treatment and neonatal anthropometry.Methods Covariate-adjusted multivariable linear regression analyses were used in 9,907 offspring of the Born in Bradford cohort. GDM treatment type (lifestyle changes advice only, lifestyle changes and insulin or lifestyle changes and metformin) was the exposure, offspring not exposed to GDM the control, and birth weight, head, mid-arm and abdominal circumference, and subscapular and triceps skinfold thickness the outcomes.Results Lower birth weight in offspring exposed to insulin (-117.2g (95% CI -173.8,-60.7)) and metformin (-200.3g (-328.5,-72.1)) than offspring not exposed to GDM was partly attributed to lower gestational age at birth and greater proportion of Pakistani mothers in the treatment groups. Higher subscapular skinfolds in offspring exposed to treatment compared to offspring not exposed to GDM was partly attributed to higher maternal glucose concentrations at diagnosis. In fully adjusted analyses, GDM treatment was associated with lower weight, smaller abdominal circumference and skinfolds at birth than offspring not exposed to GDM. Metformin was associated with smaller mid-arm circumference (-0.3cm (-0.6,-0.07)) than insulin in fully adjusted models with no other differences found.Conclusions for Practice Offspring exposed to GDM treatment were lighter and smaller at birth than offspring not exposed to GDM. Metformin-exposed offspring had largely comparable birth anthropometric characteristics to those exposed to insulin.</p

Associations of clinical, psychological, and sociodemographic characteristics and ecological momentary assessment completion in the 10-week Hypo-METRICS study: Hypoglycaemia MEasurements ThResholds and ImpaCtS

Introduction: Reporting of hypoglycaemia and its impact in clinical studies is often retrospective and subject to recall bias. We developed the Hypo-METRICS app to measure the daily physical, psychological, and social impact of hypoglycaemia in adults with type 1 and insulin-treated type 2 diabetes in real-time using ecological momentary assessment (EMA). To help assess its utility, we aimed to determine Hypo-METRICS app completion rates and factors associated with completion.Methods: Adults with diabetes recruited into the Hypo-METRICS study were given validated patient-reported outcome measures (PROMs) at baseline. Over 10 weeks, they wore a blinded continuous glucose monitor (CGM), and were asked to complete three daily EMAs about hypoglycaemia and aspects of daily functioning, and two weekly sleep and productivity PROMs on the bespoke Hypo-METRICS app.  We conducted linear regression to determine factors associated with app engagement, assessed by EMA and PROM completion rates and CGM metrics.Results: In 602 participants (55% men; 54% type 2 diabetes; median(IQR) age 56 (45-66) years; diabetes duration 19 (11-27) years; HbA1c 57 (51-65) mmol/mol), median(IQR) overall app completion rate was 91 (84-96)%, ranging from 90 (81-96)%, 89 (80-94)% and 94(87-97)% for morning, afternoon and evening check-ins, respectively. Older age, routine CGM use, greater time below 3.0 mmol/L, and active sensor time were positively associated with app completion. Discussion: High app completion across all app domains and participant characteristics indicates the Hypo-METRICS app is an acceptable research tool for collecting detailed data on hypoglycaemia frequency and impact in real-time.</p

Associations of clinical, psychological, and sociodemographic characteristics and ecological momentary assessment completion in the 10-week Hypo-METRICS study: Hypoglycaemia MEasurements ThResholds and ImpaCtS

Introduction: Reporting of hypoglycaemia and its impact in clinical studies is often retrospective and subject to recall bias. We developed the Hypo-METRICS app to measure the daily physical, psychological, and social impact of hypoglycaemia in adults with type 1 and insulin-treated type 2 diabetes in real-time using ecological momentary assessment (EMA). To help assess its utility, we aimed to determine Hypo-METRICS app completion rates and factors associated with completion.Methods: Adults with diabetes recruited into the Hypo-METRICS study were given validated patient-reported outcome measures (PROMs) at baseline. Over 10 weeks, they wore a blinded continuous glucose monitor (CGM), and were asked to complete three daily EMAs about hypoglycaemia and aspects of daily functioning, and two weekly sleep and productivity PROMs on the bespoke Hypo-METRICS app.  We conducted linear regression to determine factors associated with app engagement, assessed by EMA and PROM completion rates and CGM metrics.Results: In 602 participants (55% men; 54% type 2 diabetes; median(IQR) age 56 (45-66) years; diabetes duration 19 (11-27) years; HbA1c 57 (51-65) mmol/mol), median(IQR) overall app completion rate was 91 (84-96)%, ranging from 90 (81-96)%, 89 (80-94)% and 94(87-97)% for morning, afternoon and evening check-ins, respectively. Older age, routine CGM use, greater time below 3.0 mmol/L, and active sensor time were positively associated with app completion. Discussion: High app completion across all app domains and participant characteristics indicates the Hypo-METRICS app is an acceptable research tool for collecting detailed data on hypoglycaemia frequency and impact in real-time.</p

Relationship Between Sensor-Detected Hypoglycemia and Patient-Reported Hypoglycemia in People With Type 1 and Insulin-Treated Type 2 Diabetes: The Hypo-METRICS Study

OBJECTIVE Use of continuous glucose monitoring (CGM) has led to greater detection of hypoglycemia; the clinical significance of this is not fully understood. The Hypoglycaemia–Measurement, Thresholds and Impacts (Hypo-METRICS) study was designed to investigate the rates and duration of sensor-detected hypoglycemia (SDH) and their relationship with person-reported hypoglycemia (PRH) in people living with type 1 diabetes (T1D) and insulin-treated type 2 diabetes (T2D) with prior experience of hypoglycemia. RESEARCH DESIGN AND METHODS We recruited 276 participants with T1D and 321 with T2D who wore a blinded CGM and recorded PRH in the Hypo-METRICS app over 10 weeks. Rates of SDH <70 mg/dL, SDH <54 mg/dL, and PRH were expressed as median episodes per week. Episodes of SDH were matched to episodes of PRH that occurred within 1 h. RESULTS Median [interquartile range] rates of hypoglycemia were significantly higher in T1D versus T2D; for SDH <70 mg/dL (6.5 [3.8–10.4] vs. 2.1 [0.8–4.0]), SDH <54 mg/dL (1.2 [0.4–2.5] vs. 0.2 [0.0–0.5]), and PRH (3.9 [2.4–5.9] vs. 1.1 [0.5–2.0]). Overall, 65% of SDH <70 mg/dL was not associated with PRH, and 43% of PRH had no associated SDH. The median proportion of SDH associated with PRH in T1D was higher for SDH <70 mg/dL (40% vs. 22%) and SDH <54 mg/dL (47% vs. 25%) than in T2D. CONCLUSIONS The novel findings are that at least half of CGM hypoglycemia is asymptomatic, even below 54 mg/dL, and many reported symptomatic hypoglycemia episodes happen above 70 mg/dL. In the clinical and research setting, these episodes cannot be used interchangeably, and both need to be recorded and addressed.</p

Associations Between Hypoglycemia Awareness Status and Symptoms of Hypoglycemia Among Adults with Type 1 or Insulin-Treated Type 2 Diabetes Using the Hypo-METRICS Smartphone Application

Introduction: This study examined associations between hypoglycemia awareness status and hypoglycemia symptoms reported in real-time using the novel Hypoglycaemia-MEasurement, ThResholds and ImpaCtS (Hypo-METRICS) smartphone application (app) among adults with insulin-treated type 1 (T1D) or type 2 diabetes (T2D). Methods: Adults who experienced at least one hypoglycemic episode in the previous 3 months were recruited to the Hypo-METRICS study. They prospectively reported hypoglycemia episodes using the app for 10 weeks. Any of eight hypoglycemia symptoms were considered present if intensity was rated between "A little bit" to "Very much" and absent if rated "Not at all." Associations between hypoglycemia awareness (as defined by Gold score) and hypoglycemia symptoms were modeled using mixed-effects binary logistic regression, adjusting for glucose monitoring method and diabetes duration. Results: Of 531 participants (48% T1D, 52% T2D), 45% were women, 91% white, and 59% used Flash or continuous glucose monitoring. Impaired awareness of hypoglycemia (IAH) was associated with lower odds of reporting autonomic symptoms than normal awareness of hypoglycemia (NAH) (T1D odds ratio [OR] 0.43 [95% confidence interval {CI} 0.25-0.73], P = 0.002); T2D OR 0.51 [95% CI 0.26-0.99], P = 0.048), with no differences in neuroglycopenic symptoms. In T1D, relative to NAH, IAH was associated with higher odds of reporting autonomic symptoms at a glucose concentration 70 mg/dL (OR 2.18 [95% CI 1.21-3.94], P = 0.010). Conclusion: The Hypo-METRICS app is sensitive to differences in hypoglycemia symptoms according to hypoglycemia awareness in both diabetes types. Given its high ecological validity and low recall bias, the app may be a useful tool in research and clinical settings. The clinical trial registration number is NCT04304963

A Comparison of the Rates of Clock-Based Nocturnal Hypoglycemia and Hypoglycemia While Asleep Among People Living with Diabetes: Findings from the Hypo-METRICS Study

Introduction Nocturnal hypoglycemia is generally calculated between 00:00 and 06:00. However, those hours may not accurately reflect sleeping patterns and it is unknown whether this leads to bias. We therefore compared hypoglycemia rates whilst asleep to those of clock-based nocturnal hypoglycemia in adults with type 1 (T1D) or insulin-treated type 2 diabetes (T2D). Methods Participants from the Hypo-METRICS study wore a blinded continuous glucose monitor and a Fitbit Charge 4 activity monitor for 10 weeks. They recorded details of episodes of hypoglycemia using a smartphone app. Sensor-detected hypoglycemia (SDH) and person-reported hypoglycemia (PRH) were categorized as nocturnal (00:00-06:00hrs) vs diurnal and whilst asleep vs awake defined by Fitbit sleeping intervals. Paired sample Wilcoxon tests were used to examine the differences in hypoglycemia rates. Results 574 participants (47% T1D, 45% women, 89% White, median (IQR) age 56 (45-66) years and HbA1c 7.3% (6.8-8.0)) were included. Median sleep duration was 6.1h (5.2-6.8), bedtime and waking time approximately 23:30 and 07:30 respectively. There were higher median weekly rates of SDH and PRH whilst asleep than clock-based nocturnal SDH and PRH among people with T1D, especially for SDH<70 mg/dL (1.7 vs 1.4, p<0.001). Higher weekly rates of SDH whilst asleep than nocturnal SDH were found among people with T2D, especially for SDH<70 mg/dL (0.8 vs 0.7, p<0.001). Conclusion Using 00:00 to 06:00 as a proxy for sleeping hours may underestimate hypoglycemia whilst asleep. Future hypoglycemia research should consider the use of sleep trackers to record sleep and reflect hypoglycemia whilst asleep more accurately

A Comparison of the Rates of Clock-Based Nocturnal Hypoglycemia and Hypoglycemia While Asleep Among People Living with Diabetes: Findings from the Hypo-METRICS Study

Introduction Nocturnal hypoglycemia is generally calculated between 00:00 and 06:00. However, those hours may not accurately reflect sleeping patterns and it is unknown whether this leads to bias. We therefore compared hypoglycemia rates whilst asleep to those of clock-based nocturnal hypoglycemia in adults with type 1 (T1D) or insulin-treated type 2 diabetes (T2D). Methods Participants from the Hypo-METRICS study wore a blinded continuous glucose monitor and a Fitbit Charge 4 activity monitor for 10 weeks. They recorded details of episodes of hypoglycemia using a smartphone app. Sensor-detected hypoglycemia (SDH) and person-reported hypoglycemia (PRH) were categorized as nocturnal (00:00-06:00hrs) vs diurnal and whilst asleep vs awake defined by Fitbit sleeping intervals. Paired sample Wilcoxon tests were used to examine the differences in hypoglycemia rates. Results 574 participants (47% T1D, 45% women, 89% White, median (IQR) age 56 (45-66) years and HbA1c 7.3% (6.8-8.0)) were included. Median sleep duration was 6.1h (5.2-6.8), bedtime and waking time approximately 23:30 and 07:30 respectively. There were higher median weekly rates of SDH and PRH whilst asleep than clock-based nocturnal SDH and PRH among people with T1D, especially for SDH<70 mg/dL (1.7 vs 1.4, p<0.001). Higher weekly rates of SDH whilst asleep than nocturnal SDH were found among people with T2D, especially for SDH<70 mg/dL (0.8 vs 0.7, p<0.001). Conclusion Using 00:00 to 06:00 as a proxy for sleeping hours may underestimate hypoglycemia whilst asleep. Future hypoglycemia research should consider the use of sleep trackers to record sleep and reflect hypoglycemia whilst asleep more accurately