Reducing the burden of hypoglycaemia in people with diabetes through increased understanding: design of the Hypoglycaemia REdefining SOLutions for better liVEs (Hypo-RESOLVE) project

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.

The impact of hypoglycaemia on daily functioning among adults with diabetes: a prospective observational study using the Hypo-METRICS app

AIMS/HYPOTHESIS

The aim of this work was to examine the impact of hypoglycaemia on daily functioning among adults with type 1 diabetes or insulin-treated type 2 diabetes, using the novel Hypo-METRICS app.

METHODS

For 70 consecutive days, 594 adults (type 1 diabetes, n=274; type 2 diabetes, n=320) completed brief morning and evening Hypo-METRICS 'check-ins' about their experienced hypoglycaemia and daily functioning. Participants wore a blinded glucose sensor (i.e. data unavailable to the participants) for the study duration. Days and nights with or without person-reported hypoglycaemia (PRH) and/or sensor-detected hypoglycaemia (SDH) were compared using multilevel regression models.

RESULTS

Participants submitted a mean ± SD of 86.3±12.5% morning and 90.8±10.7% evening check-ins. For both types of diabetes, SDH alone had no significant associations with the changes in daily functioning scores. However, daytime and night-time PRH (with or without SDH) were significantly associated with worsening of energy levels, mood, cognitive functioning, negative affect and fear of hypoglycaemia later that day or while asleep. In addition, night-time PRH (with or without SDH) was significantly associated with worsening of sleep quality (type 1 and type 2 diabetes) and memory (type 2 diabetes). Further, daytime PRH (with or without SDH), was associated with worsening of fear of hyperglycaemia while asleep (type 1 diabetes), memory (type 1 and type 2 diabetes) and social functioning (type 2 diabetes).

CONCLUSIONS/INTERPRETATION

This prospective, real-world study reveals impact on several domains of daily functioning following PRH but not following SDH alone. These data suggest that the observed negative impact is mainly driven by subjective awareness of hypoglycaemia (i.e. PRH), through either symptoms or sensor alerts/readings and/or the need to take action to prevent or treat episodes.

Estimating risk of consequences following hypoglycaemia exposure using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials

AIMS/HYPOTHESIS

Whether hypoglycaemia increases the risk of other adverse outcomes in diabetes remains controversial, especially for hypoglycaemia episodes not requiring assistance from another person. An objective of the Hypoglycaemia REdefining SOLutions for better liVEs (Hypo-RESOLVE) project was to create and use a dataset of pooled clinical trials in people with type 1 or type 2 diabetes to examine the association of exposure to all hypoglycaemia episodes across the range of severity with incident event outcomes: death, CVD, neuropathy, kidney disease, retinal disorders and depression. We also examined the change in continuous outcomes that occurred following a hypoglycaemia episode: change in eGFR, HbA1c, blood glucose, blood glucose variability and weight.

METHODS

Data from 84 trials with 39,373 participants were pooled. For event outcomes, time-updated Cox regression models adjusted for age, sex, diabetes duration and HbA1c were fitted to assess association between: (1) outcome and cumulative exposure to hypoglycaemia episodes; and (2) outcomes where an acute effect might be expected (i.e. death, acute CVD, retinal disorders) and any hypoglycaemia exposure within the last 10 days. Exposures to any hypoglycaemia episode and to episodes of given severity (levels 1, 2 and 3) were examined. Further adjustment was then made for a wider set of potential confounders. The within-person change in continuous outcomes was also summarised (median of 40.4 weeks for type 1 diabetes and 26 weeks for type 2 diabetes). Analyses were conducted separately by type of diabetes.

RESULTS

The maximally adjusted association analysis for type 1 diabetes found that cumulative exposure to hypoglycaemia episodes of any level was associated with higher risks of neuropathy, kidney disease, retinal disorders and depression, with risk ratios ranging from 1.55 (p=0.002) to 2.81 (p=0.002). Associations of a similar direction were found when level 1 episodes were examined separately but were significant for depression only. For type 2 diabetes cumulative exposure to hypoglycaemia episodes of any level was associated with higher risks of death, acute CVD, kidney disease, retinal disorders and depression, with risk ratios ranging from 2.35 (p<0.0001) to 3.00 (p<0.0001). These associations remained significant when level 1 episodes were examined separately. There was evidence of an association between hypoglycaemia episodes of any kind in the previous 10 days and death, acute CVD and retinal disorders in both type 1 and type 2 diabetes, with rate ratios ranging from 1.32 (p=0.017) to 2.68 (p<0.0001). These associations varied in magnitude and significance when examined separately by hypoglycaemia level. Within the range of hypoglycaemia defined by levels 1, 2 and 3, we could not find any evidence of a threshold at which risk of these consequences suddenly became pronounced.

CONCLUSIONS/INTERPRETATION

These data are consistent with hypoglycaemia being associated with an increased risk of adverse events across several body systems in diabetes. These associations are not confined to severe hypoglycaemia requiring assistance.

Risk factors and prediction of hypoglycaemia using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials

AIMS/HYPOTHESIS

The objective of the Hypoglycaemia REdefining SOLutions for better liVES (Hypo-RESOLVE) project is to use a dataset of pooled clinical trials across pharmaceutical and device companies in people with type 1 or type 2 diabetes to examine factors associated with incident hypoglycaemia events and to quantify the prediction of these events.

METHODS

Data from 90 trials with 46,254 participants were pooled. Analyses were done for type 1 and type 2 diabetes separately. Poisson mixed models, adjusted for age, sex, diabetes duration and trial identifier were fitted to assess the association of clinical variables with hypoglycaemia event counts. Tree-based gradient-boosting algorithms (XGBoost) were fitted using training data and their predictive performance in terms of area under the receiver operating characteristic curve (AUC) evaluated on test data. Baseline models including age, sex and diabetes duration were compared with models that further included a score of hypoglycaemia in the first 6 weeks from study entry, and full models that included further clinical variables. The relative predictive importance of each covariate was assessed using XGBoost's importance procedure. Prediction across the entire trial duration for each trial (mean of 34.8 weeks for type 1 diabetes and 25.3 weeks for type 2 diabetes) was assessed.

RESULTS

For both type 1 and type 2 diabetes, variables associated with more frequent hypoglycaemia included female sex, white ethnicity, longer diabetes duration, treatment with human as opposed to analogue-only insulin, higher glucose variability, higher score for hypoglycaemia across the 6 week baseline period, lower BP, lower lipid levels and treatment with psychoactive drugs. Prediction of any hypoglycaemia event of any severity was greater than prediction of hypoglycaemia requiring assistance (level 3 hypoglycaemia), for which events were sparser. For prediction of level 1 or worse hypoglycaemia during the whole follow-up period, the AUC was 0.835 (95% CI 0.826, 0.844) in type 1 diabetes and 0.840 (95% CI 0.831, 0.848) in type 2 diabetes. For level 3 hypoglycaemia, the AUC was lower at 0.689 (95% CI 0.667, 0.712) for type 1 diabetes and 0.705 (95% CI 0.662, 0.748) for type 2 diabetes. Compared with the baseline models, almost all the improvement in prediction could be captured by the individual's hypoglycaemia history, glucose variability and blood glucose over a 6 week baseline period.

CONCLUSIONS/INTERPRETATION

Although hypoglycaemia rates show large variation according to sociodemographic and clinical characteristics and treatment history, looking at a 6 week period of hypoglycaemia events and glucose measurements predicts future hypoglycaemia risk.

Development of a new health-related quality of life measure for people with diabetes who experience hypoglycaemia: the Hypo-RESOLVE QoL

AIMS/HYPOTHESIS

Valid and reliable patient-reported outcome measures are vital for assessing disease impact, responsiveness to healthcare and the cost-effectiveness of interventions. A recent review has questioned the ability of existing measures to assess hypoglycaemia-related impacts on health-related quality of life for people with diabetes. This mixed-methods project was designed to produce a novel health-related quality of life patient-reported outcome measure in hypoglycaemia: the Hypo-RESOLVE QoL.

METHODS

Three studies were conducted with people with diabetes who experience hypoglycaemia. In Stage 1, a comprehensive health-related quality of life framework for hypoglycaemia was elicited from semi-structured interviews (N=31). In Stage 2, the content validity and acceptability of draft measure content were tested via three waves of cognitive debriefing interviews (N=70 people with diabetes; N=14 clinicians). In Stage 3, revised measure content was administered alongside existing generic and diabetes-related measures in a large cross-sectional observational survey to assess psychometric performance (N=1246). The final measure was developed using multiple evidence sources, incorporating stakeholder engagement.

RESULTS

A novel conceptual model of hypoglycaemia-related health-related quality of life was generated, featuring 19 themes, organised by physical, social and psychological aspects. From a draft version of 76 items, a final 14-item measure was produced with satisfactory structural (χ2=472.27, df=74, p<0.001; comparative fit index =0.943; root mean square error of approximation =0.069) and convergent validity with related constructs (r=0.46-0.59), internal consistency (α=0.91) and test-retest reliability (intraclass correlation coefficient =0.87).

CONCLUSIONS/INTERPRETATION

The Hypo-RESOLVE QoL is a rigorously developed patient-reported outcome measure assessing the health-related quality of life impacts of hypoglycaemia. The Hypo-RESOLVE QoL has demonstrable validity and reliability and has value for use in clinical decision-making and as a clinical trial endpoint.

DATA AVAILABILITY

All data generated or analysed during this study are included in the published article and its online supplementary files ( https://doi.org/10.15131/shef.

DATA

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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 <54 than >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 while asleep with those of clock-based nocturnal hypoglycemia in adults with type 1 diabetes (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 (00:00-06:00 h) versus diurnal and while asleep versus awake defined by Fitbit sleeping intervals. Paired-sample Wilcoxon tests were used to examine the differences in hypoglycemia rates. Results: A total of 574 participants [47% T1D, 45% women, 89% white, median (interquartile range) age 56 (45-66) years, and hemoglobin A1c 7.3% (6.8-8.0)] were included. Median sleep duration was 6.1 h (5.2-6.8), bedtime and waking time ∼23:30 and 07:30, respectively. There were higher median weekly rates of SDH and PRH while 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 while 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 while asleep. Future hypoglycemia research should consider the use of sleep trackers to record sleep and reflect hypoglycemia while asleep more accurately. The trial registration number is NCT04304963.

Counterregulatory hormone and symptom responses to hypoglycaemia in people with type 1 diabetes, insulin-treated type 2 diabetes or without diabetes: the Hypo-RESOLVE hypoglycaemic clamp study

AIM

The sympathetic nervous and hormonal counterregulatory responses to hypoglycaemia differ between people with type 1 and type 2 diabetes and may change along the course of diabetes, but have not been directly compared. We aimed to compare counterregulatory hormone and symptom responses to hypoglycaemia between people with type 1 diabetes, insulin-treated type 2 diabetes and controls without diabetes, using a standardised hyperinsulinaemic-hypoglycaemic clamp.

MATERIALS

We included 47 people with type 1 diabetes, 15 with insulin-treated type 2 diabetes, and 32 controls without diabetes. Controls were matched according to age and sex to the people with type 1 diabetes or with type 2 diabetes. All participants underwent a hyperinsulinaemic-euglycaemic-(5.2 ± 0.4 mmol/L)-hypoglycaemic-(2.8 ± 0.13 mmol/L)-clamp.

RESULTS

The glucagon response was lower in people with type 1 diabetes (9.4 ± 0.8 pmol/L, 8.0 [7.0-10.0]) compared to type 2 diabetes (23.7 ± 3.7 pmol/L, 18.0 [12.0-28.0], p < 0.001) and controls (30.6 ± 4.7, 25.5 [17.8-35.8] pmol/L, p < 0.001). The adrenaline response was lower in type 1 diabetes (1.7 ± 0.2, 1.6 [1.3-5.2] nmol/L) compared to type 2 diabetes (3.4 ± 0.7, 2.6 [1.3-5.2] nmol/L, p = 0.001) and controls (2.7 ± 0.4, 2.8 [1.4-3.9] nmol/L, p = 0.012). Growth hormone was lower in people with type 2 diabetes than in type 1 diabetes, at baseline (3.4 ± 1.6 vs 7.7 ± 1.3 mU/L, p = 0.042) and during hypoglycaemia (24.7 ± 7.1 vs 62.4 ± 5.8 mU/L, p = 0.001). People with 1 diabetes had lower overall symptom responses than people with type 2 diabetes (45.3 ± 2.7 vs 58.7 ± 6.4, p = 0.018), driven by a lower neuroglycopenic score (27.4 ± 1.8 vs 36.7 ± 4.2, p = 0.012).

CONCLUSION

Acute counterregulatory hormone and symptom responses to experimental hypoglycaemia are lower in people with type 1 diabetes than in those with long-standing insulin-treated type 2 diabetes and controls.

The impact of prior exposure to hypoglycaemia on the inflammatory response to a subsequent hypoglycaemic episode

BACKGROUND

Hypoglycaemia has been shown to induce a systemic pro-inflammatory response, which may be driven, in part, by the adrenaline response. Prior exposure to hypoglycaemia attenuates counterregulatory hormone responses to subsequent hypoglycaemia, but whether this effect can be extrapolated to the pro-inflammatory response is unclear. Therefore, we investigated the effect of antecedent hypoglycaemia on inflammatory responses to subsequent hypoglycaemia in humans.

METHODS

Healthy participants (n = 32) were recruited and randomised to two 2-h episodes of either hypoglycaemia or normoglycaemia on day 1, followed by a hyperinsulinaemic hypoglycaemic (2.8 ± 0.1 mmol/L) glucose clamp on day 2. During normoglycaemia and hypoglycaemia, and after 24 h, 72 h and 1 week, blood was drawn to determine circulating immune cell composition, phenotype and function, and 93 circulating inflammatory proteins including hs-CRP.

RESULTS

In the group undergoing antecedent hypoglycaemia, the adrenaline response to next-day hypoglycaemia was lower compared to the control group (1.45 ± 1.24 vs 2.68 ± 1.41 nmol/l). In both groups, day 2 hypoglycaemia increased absolute numbers of circulating immune cells, of which lymphocytes and monocytes remained elevated for the whole week. Also, the proportion of pro-inflammatory CD16+-monocytes increased during hypoglycaemia. After ex vivo stimulation, monocytes released more TNF-α and IL-1β, and less IL-10 in response to hypoglycaemia, whereas levels of 19 circulating inflammatory proteins, including hs-CRP, increased for up to 1 week after the hypoglycaemic event. Most of the inflammatory responses were similar in the two groups, except the persistent pro-inflammatory protein changes were partly blunted in the group exposed to antecedent hypoglycaemia. We did not find a correlation between the adrenaline response and the inflammatory responses during hypoglycaemia.

CONCLUSION

Hypoglycaemia induces an acute and persistent pro-inflammatory response at multiple levels that occurs largely, but not completely, independent of prior exposure to hypoglycaemia. Clinical Trial information Clinicaltrials.gov no. NCT03976271 (registered 5 June 2019).

The impact of hypoglycaemia on quality of life among adults with type 1 diabetes: Results from "YourSAY: Hypoglycaemia"

AIMS

Research on hypoglycaemia and quality of life (QoL) has focused mostly on severe hypoglycaemia and psychological outcomes, with less known about other aspects of hypoglycaemia (e.g., self-treated episodes) and impacts on other QoL domains (e.g., relationships). Therefore, we examined the impact of all aspects of hypoglycaemia on QoL in adults with type 1 diabetes (T1DM).

METHODS

Participants completed an online survey, including assessment of hypoglycaemia-specific QoL (using the 12-item Hypoglycaemia Impact Profile). Mann-Whitney U tests examined differences in hypoglycaemia-specific QoL by hypoglycaemia frequency, severity, and awareness. Hierarchical linear regression examined associations with QoL.

RESULTS

Participants were 1028 adults with T1DM (M ± SD age: 47 ± 15 years; diabetes duration: 27 ± 16 years). Severe and self-treated hypoglycaemia and impaired awareness negatively impacted on overall QoL and several QoL domains, including leisure activities, physical health, ability to keep fit/be active, sleep, emotional well-being, spontaneity, independence, work/studies, and dietary freedom. Diabetes distress was most strongly associated with hypoglycaemia-specific QoL, followed by generic emotional well-being, fear of hypoglycaemia, and confidence in managing hypoglycaemia. Hypoglycaemia frequency and awareness were no longer significantly associated with QoL once psychological factors were considered.

CONCLUSIONS

Hypoglycaemia negatively impacts on several QoL domains. Psychological factors supersede the effect of hypoglycaemia frequency and awareness in accounting for this negative impact.

Glucose variability and mood in people with type 1 diabetes using ecological momentary assessment

OBJECTIVE

Mood fluctuations related to blood glucose excursions are a commonly reported source of diabetes-distress, but research is scarce. We aimed to assess the relationship between real-time glucose variability and mood in adults with type 1 diabetes (T1D) using ecological momentary assessments.

METHODS

In this prospective observational study, participants wore a masked continuous glucose monitor and received prompts on their smartphone 6 times a day to answer questions about their current mood (Profile Of Mood States (POMS)-SF (dimensions: Anxiety, Depressive symptoms, Anger, Fatigue, Vigor)) for 14 days. Mixed model analyses examined associations over time between daily Coefficient of Variation (CV) of blood glucose and mean and variability (CV) of POMS scores. Further, within-person differences in sleep and nocturnal hypoglycemia were explored.

RESULTS

18 people with T1D (10 female, mean age 44.3 years) participated. A total of 264 out of 367 days (70.2%) could be included in the analyses. No overall significant associations were found between CV of blood glucose and mean and CV of POMS scores, however, nocturnal hypoglycemia moderated the associations between CV of blood glucose and POMS scales (mean Fatigue Estimate 1.998, p < .006, mean Vigor Estimate -3.308, p < .001; CV Anger Estimate 0.731p = 0.02, CV Vigor Estimate -0.525, p = .006).

CONCLUSION

We found no overall relationship between real-time glycemic variability and mood per day. Further research into within-person differences such as sleep and nocturnal hypoglycemia is warranted.

Assessing the Content Validity, Acceptability, and Feasibility of the Hypo-METRICS App: Survey and Interview Study

BACKGROUND

The Hypoglycaemia - MEasurement, ThResholds and ImpaCtS (Hypo-METRICS) smartphone app was developed to investigate the impact of hypoglycemia on daily functioning in adults with type 1 diabetes mellitus or insulin-treated type 2 diabetes mellitus. The app uses ecological momentary assessments, thereby minimizing recall bias and maximizing ecological validity. It was used in the Hypo-METRICS study, a European multicenter observational study wherein participants wore a blinded continuous glucose monitoring device and completed the app assessments 3 times daily for 70 days.

OBJECTIVE

The 3 aims of the study were to explore the content validity of the app, the acceptability and feasibility of using the app for the duration of the Hypo-METRICS study, and suggestions for future versions of the app.

METHODS

Participants who had completed the 70-day Hypo-METRICS study in the United Kingdom were invited to participate in a brief web-based survey and an interview (approximately 1h) to explore their experiences with the app during the Hypo-METRICS study. Thematic analysis of the qualitative data was conducted using both deductive and inductive methods.

RESULTS

A total of 18 adults with diabetes (type 1 diabetes: n=10, 56%; 5/10, 50% female; mean age 47, SD 16 years; type 2 diabetes: n=8, 44%; 2/8, 25% female; mean age 61, SD 9 years) filled out the survey and were interviewed. In exploring content validity, participants overall described the Hypo-METRICS app as relevant, understandable, and comprehensive. In total, 3 themes were derived: hypoglycemia symptoms and experiences are idiosyncratic; it was easy to select ratings on the app, but day-to-day changes were perceived as minimal; and instructions could be improved. Participants offered suggestions for changes or additional questions and functions that could increase engagement and improve content (such as providing more examples with the questions). In exploring acceptability and feasibility, 5 themes were derived: helping science and people with diabetes; easy to fit in, but more flexibility wanted; hypoglycemia delaying responses and increasing completion time; design, functionality, and customizability of the app; and limited change in awareness of symptoms and impact. Participants described using the app as a positive experience overall and as having a possible, although limited, intervention effect in terms of both hypoglycemia awareness and personal impact.

CONCLUSIONS

The Hypo-METRICS app shows promise as a new research tool to assess the impact of hypoglycemia on an individual's daily functioning. Despite suggested improvements, participants' responses indicated that the app has satisfactory content validity, overall fits in with everyday life, and is suitable for a 10-week research study. Although developed for research purposes, real-time assessments may have clinical value for monitoring and reviewing hypoglycemia symptom awareness and personal impact.

Diabetes Technology Meeting 2022

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 3 to November 5, 2022. Meeting topics included (1) the measurement of glucose, insulin, and ketones; (2) virtual diabetes care; (3) metrics for managing diabetes and predicting outcomes; (4) integration of continuous glucose monitor data into the electronic health record; (5) regulation of diabetes technology; (6) digital health to nudge behavior; (7) estimating carbohydrates; (8) fully automated insulin delivery systems; (9) hypoglycemia; (10) novel insulins; (11) insulin delivery; (12) on-body sensors; (13) continuous glucose monitoring; (14) diabetic foot ulcers; (15) the environmental impact of diabetes technology; and (16) spinal cord stimulation for painful diabetic neuropathy. A live demonstration of a device that can allow for the recycling of used insulin pens was also presented.

Producing a preference-based quality of LIFE measure to quantify the impact of HYPOGLYCAEMIA on people living with diabetes: A mixed-methods research protocol

BACKGROUND

Assessment of patient-reported outcome measures (PROMs), including quality of life (QoL), is essential in diabetes research and care. However, a recent review concluded that current hypoglycaemia-specific PROMs have limited evidence of validity, reliability and responsiveness for assessing the impact of hypoglycaemia on QoL in people living with diabetes. None of the PROMs identified could be used directly to inform the cost-effectiveness of treatments and interventions. There is a need for a new hypoglycaemia-specific QoL PROM, which can be used directly to inform economic evaluations.

AIMS

This project has three aims: (a) To develop draft PROM content for measuring the impact of hypoglycaemia on QoL in adults with diabetes. (b) To refine the draft content using cognitive debriefing interviews and psychometrics. This will result in a condition-specific PROM that can be used to quantify the impact of hypoglycaemia upon QoL. (c) To generate a preference-based measure (PBM) that will enable utility values to be calculated for economic evaluation.

METHODS

A mixed-methods, three-stage design is used: (a) Qualitative interviews will inform the draft PROM content. (b) Cognitive debriefing interview data will be used to refine the draft PROM content. The PROM will be administered in a large-scale survey to enable psychometric validation. Final item selection for the PROM will be informed by psychometric performance, translatability assessment and input from stakeholder groups. (c) A classification system will be generated, comprising a reduced number of items from the PROM. A valuation survey will be conducted to derive a value set for the PBM.

Psychometric properties of an innovative smartphone application to investigate the daily impact of hypoglycemia in people with type 1 or type 2 diabetes: The Hypo-METRICS app

INTRODUCTION

The aim of this study was to determine the acceptability and psychometric properties of the Hypo-METRICS (Hypoglycemia MEasurement, ThResholds and ImpaCtS) application (app): a novel tool designed to assess the direct impact of symptomatic and asymptomatic hypoglycemia on daily functioning in people with insulin-treated diabetes.

MATERIALS AND METHODS

100 adults with type 1 diabetes mellitus (T1DM, n = 64) or insulin-treated type 2 diabetes mellitus (T2DM, n = 36) completed three daily 'check-ins' (morning, afternoon and evening) via the Hypo-METRICs app across 10 weeks, to respond to 29 unique questions about their subjective daily functioning. Questions addressed sleep quality, energy level, mood, affect, cognitive functioning, fear of hypoglycemia and hyperglycemia, social functioning, and work/productivity. Completion rates, structural validity, internal consistency, and test-retest reliability were explored. App responses were correlated with validated person-reported outcome measures to investigate convergent (rs>±0.3) and divergent (rs<±0.3) validity.

RESULTS

Participants' mean±SD age was 54±16 years, diabetes duration was 23±13 years, and most recent HbA1c was 56.6±9.8 mmol/mol. Participants submitted mean±SD 191±16 out of 210 possible 'check-ins' (91%). Structural validity was confirmed with multi-level confirmatory factor analysis showing good model fit on the adjusted model (Comparative Fit Index >0.95, Root-Mean-Square Error of Approximation <0.06, Standardized Root-Mean-square Residual<0.08). Scales had satisfactory internal consistency (all ω≥0.5), and high test-retest reliability (rs≥0.7). Convergent and divergent validity were demonstrated for most scales.

CONCLUSION

High completion rates and satisfactory psychometric properties demonstrated that the Hypo-METRICS app is acceptable to adults with T1DM and T2DM, and a reliable and valid tool to explore the daily impact of hypoglycemia.

Coordination of glucose monitoring, self-care behaviour and mental health: achieving precision monitoring in diabetes

Monitoring of glucose plays an essential role in the management of diabetes. However, to fully understand and meaningfully interpret glucose levels, additional information on context is necessary. Important contextual factors include data on behaviours such as eating, exercise, medication-taking and sleep, as well as data on mental health aspects such as stress, affect, diabetes distress and depressive symptoms. This narrative review provides an overview of the current state and future directions of precision monitoring in diabetes. Precision monitoring of glucose has made great progress over the last 5 years with the emergence of continuous glucose monitoring (CGM), automated analysis of new glucose variables and visualisation of CGM data via the ambulatory glucose profile. Interestingly, there has been little progress in the identification of subgroups of people with diabetes based on their glycaemic profile. The integration of behavioural and mental health data could enrich such identification of subgroups to stimulate precision medicine. There are a handful of studies that have used innovative methodology such as ecological momentary assessment to monitor behaviour and mental health in people's everyday life. These studies indicate the importance of the interplay between behaviour, mental health and glucose. However, automated integration and intelligent interpretation of these data sources are currently not available. Automated integration of behaviour, mental health and glucose could lead to the identification of certain subgroups that, for example, show a strong association between mental health and glucose in contrast to subgroups that show independence of mental health and glucose. This could inform precision diagnostics and precision therapeutics. We identified just-in-time adaptive interventions as a potential means by which precision monitoring could lead to precision therapeutics. Just-in-time adaptive interventions consist of micro-interventions that are triggered in people's everyday lives when a certain problem is identified using monitored behaviour, mental health and glucose variables. Thus, these micro-interventions are responsive to real-life circumstances and are adaptive to the specific needs of an individual with diabetes. We conclude that, with current developments in big data analysis, there is a huge potential for precision monitoring in diabetes.

Hypo-METRICS: Hypoglycaemia-MEasurement, ThResholds and ImpaCtS-A multi-country clinical study to define the optimal threshold and duration of sensor-detected hypoglycaemia that impact the experience of hypoglycaemia, quality of life and health economic outcomes: The study protocol

INTRODUCTION

Hypoglycaemia is a significant burden to people living with diabetes and an impediment to achieving optimal glycaemic outcomes. The use of continuous glucose monitoring (CGM) has improved the capacity to assess duration and level of hypoglycaemia. The personal impact of sensor-detected hypoglycaemia (SDH) is unclear. Hypo-METRICS is an observational study designed to define the threshold and duration of sensor glucose that provides the optimal sensitivity and specificity for events that people living with diabetes experience as hypoglycaemia.

METHODS

We will recruit 600 participants: 350 with insulin-treated type 2 diabetes, 200 with type 1 diabetes and awareness of hypoglycaemia and 50 with type 1 diabetes and impaired awareness of hypoglycaemia who have recent experience of hypoglycaemia. Participants will wear a blinded CGM device and an actigraphy monitor to differentiate awake and sleep times for 10 weeks. Participants will be asked to complete three short surveys each day using a bespoke mobile phone app, a technique known as ecological momentary assessment. Participants will also record all episodes of self-detected hypoglycaemia on the mobile app. We will use particle Markov chain Monte Carlo optimization to identify the optimal threshold and duration of SDH that have optimum sensitivity and specificity for detecting patient-reported hypoglycaemia. Key secondary objectives include measuring the impact of symptomatic and asymptomatic SDH on daily functioning and health economic outcomes.

ETHICS AND DISSEMINATION

The protocol was approved by local ethical boards in all participating centres. Study results will be shared with participants, in peer-reviewed journal publications and conference presentations.

The 12-Item Hypoglycemia Impact Profile (HIP12): psychometric validation of a brief measure of the impact of hypoglycemia on quality of life among adults with type 1 or type 2 diabetes

INTRODUCTION

The aim of this study was to determine the psychometric properties of the 12-Item Hypoglycemia Impact Profile (HIP12), a brief measure of the impact of hypoglycemia on quality of life (QoL) among adults with type 1 (T1D) or type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

Adults with T1D (n=1071) or T2D (n=194) participating in the multicountry, online study, 'Your SAY: Hypoglycemia', completed the HIP12. Psychometric analyses were undertaken to determine acceptability, structural validity, internal consistency, convergent/divergent validity, and known-groups validity.

RESULTS

Most (98%) participants completed all items on the HIP12. The expected one-factor solution was supported for T1D, T2D, native English speaker, and non-native English speaker groups. Internal consistency was high across all groups (ω=0.91-0.93). Convergent and divergent validity were satisfactory. Known-groups validity was demonstrated for both diabetes types, by frequency of severe hypoglycemia (0 vs ≥1 episode in the past 12 months) and self-treated episodes (<2 vs 2-4 vs ≥5 per week). The measure also discriminated by awareness of hypoglycemia in those with T1D.

CONCLUSIONS

The HIP12 is an acceptable, internally consistent, and valid tool for assessing the impact of hypoglycemia on QoL among adults with T1D. The findings in the relatively small sample with T2D are encouraging and warrant replication in a larger sample.

Generation of post-meal insulin correction boluses in type 1 diabetes simulation models for in-silico clinical trials: More realistic scenarios obtained using a decision tree approach

BACKGROUND AND OBJECTIVE

In type 1 diabetes (T1D) research, in-silico clinical trials (ISCTs) notably facilitate the design/testing of new therapies. Published simulation tools embed mathematical models of blood glucose (BG) and insulin dynamics, continuous glucose monitoring (CGM) sensors, and insulin treatments, but lack a realistic description of some aspects of patient lifestyle impacting on glucose control. Specifically, to effectively simulate insulin correction boluses, required to treat post-meal hyperglycemia (BG > 180 mg/dL), the timing of the bolus may be influenced by subjects' behavioral attitudes. In this work, we develop an easily interpretable model of the variability of correction bolus timing observed in real data, and embed it into a popular simulation tool for ISCTs.

METHODS

Using data collected in 196 adults with T1D monitored in free-living conditions, we trained a decision tree (DT) model to classify whether a correction bolus is injected in a future time window, based on predictors collected back in time, related to CGM data, previous insulin boluses and subject's characteristics. The performance was compared to that of a logistic regression classifier with LASSO regularization (LC), trained on the same dataset. After validation, the DT was embedded within a popular T1D simulation tool and an ISCT was performed to compare the simulated correction boluses against those observed in a subset of data not used for model training.

RESULTS

The DT provided better classification performance (accuracy: 0.792, sensitivity: 0.430, specificity: 0.878, precision: 0.455) than the LC and presented good interpretability. The most predictive features were related to CGM (and its temporal variations), time since the last insulin bolus, and time of the day. The correction boluses simulated by the DT, after implementation in the simulation tool, showed a good agreement with real-world data.

CONCLUSIONS

The DT developed in this work represents a simple set of rules to mimic the same timing of correction boluses observed on real data. The inclusion of the model in simulation tools allows investigators to perform ISCTs that more realistically represent the patient behavior in taking correction boluses and the post-prandial BG response. In the future, more complex models can be investigated.

The impact of hypoglycaemia in children and adolescents with type 1 diabetes on parental quality of life and related outcomes: A systematic review

This systematic review aims to summarize and critically evaluate the current evidence regarding the impact of hypoglycaemia in children and adolescents with type 1 diabetes on parental quality of life. MEDLINE, PsycINFO, CINAHL, and the Cochrane Library were searched. Inclusion criteria were: 1) quantitative design, 2) included parents of children or adolescents with type 1 diabetes, 3) assessment of hypoglycemia in children/adolescents with type 1 diabetes, 4) assessment of parent quality of life (or related domains of life), and 5) analysis of the relationship(s) between the child's hypoglycaemia and parents' quality of life. The data were summarised in accordance with Synthesis Without Meta-Analysis Guidelines. Twelve studies were included, reporting data from 1895 parents across six countries. Ten studies were cross-sectional; two included prospective data. Evidence suggested that greater frequency and severity of hypoglycemia was associated with greater parental fear of hypoglycemia, emotional distress and family burden. Children's hypoglycaemia has a negative impact on the well-being of parents, but there is an absence of evidence regarding the impact on their overall quality of life. Research into the hypoglycaemia-specific quality of life of parents is needed to explore the impact on various areas, such as social and physical dimensions.

Investigating the day-to-day impact of hypoglycaemia in adults with type 1 or type 2 diabetes: design and validation protocol of the Hypo-METRICS application

INTRODUCTION

Hypoglycaemia is a frequent adverse event and major barrier for achieving optimal blood glucose levels in people with type 1 or type 2 diabetes using insulin. The Hypo-RESOLVE (Hypoglycaemia-Redefining SOLutions for better liVEs) consortium aims to further our understanding of the day-to-day impact of hypoglycaemia. The Hypo-METRICS (Hypoglycaemia-MEasurement, ThResholds and ImpaCtS) application (app) is a novel app for smartphones. This app is developed as part of the Hypo-RESOLVE project, using ecological momentary assessment methods that will minimise recall bias and allow for robust investigation of the day-to-day impact of hypoglycaemia. In this paper, the development and planned psychometric analyses of the app are described.

METHODS AND ANALYSIS

The three phases of development of the Hypo-METRICS app are: (1) establish a working group-comprising diabetologists, psychologists and people with diabetes-to define the problem and identify relevant areas of daily functioning; (2) develop app items, with user-testing, and implement into the app platform; and (3) plan a large-scale, multicountry study including interviews with users and psychometric validation. The app includes 7 modules (29 unique items) assessing: self-report of hypoglycaemic episodes (during the day and night, respectively), sleep quality, well-being/cognitive function, social interactions, fear of hypoglycaemia/hyperglycaemia and work/productivity. The app is designed for use within three fixed time intervals per day (morning, afternoon and evening). The first version was released mid-2020 for use (in conjunction with continuous glucose monitoring and activity tracking) in the Hypo-METRICS study; an international observational longitudinal study. As part of this study, semistructured user-experience interviews and psychometric analyses will be conducted.

ETHICS AND DISSEMINATION

Use of the novel Hypo-METRICS app in a multicountry clinical study has received ethical approval in each of the five countries involved (Oxford B Research Ethics Committee, CMO Region Arnhem-Nijmegen, Ethikkommission der Medizinischen Universität Graz, Videnskabsetisk Komite for Region Hovedstaden and the Comite Die Protection Des Personnes SUD Mediterranne IV). The results from the study will be published in peer review journals and presented at national and international conferences.

TRIAL REGISTRATION NUMBER

NCT04304963.

Unmet support needs relating to hypoglycaemia among adults with type 1 diabetes: Results of a multi-country web-based qualitative study

OBJECTIVE

Hypoglycaemic episodes and fear of hypoglycaemia can be burdensome for adults with type 1 diabetes. This study explored support needs relating to hypoglycaemia among adults with type 1 diabetes living in Denmark, Germany, the Netherlands and the United Kingdom.

RESEARCH DESIGN AND METHODS

Respondents participated in a web-based qualitative study involving four open-ended questions that asked what they wished other people understood about hypoglycaemia and what other people could do differently to support them with hypoglycaemia. Responses were analyzed using reflexive thematic analysis.

RESULTS

Participants were 219 adults with type 1 diabetes (mean ± SD age 39 ± 13 years; mean ± SD diabetes duration 20 ± 14 years). They described unmet needs relating to: (1) Clinical support, involving access to new diabetes technologies, training on hypoglycaemia prevention, personalised care and psychological support; (2) Practical support, involving family and friends better supporting them with hypoglycaemia management and prevention; (3) Education for other people, involving others becoming more informed about hypoglycaemia; and (4) An appreciation of the burden, involving others recognizing the experience and impact of episodes, and the burden of living with the risk of hypoglycaemia.

CONCLUSIONS

Adults with type 1 diabetes report several unmet support needs relating to hypoglycaemia. Service delivery should be person-centred and prioritise the individual's support needs. Clinical conversations are needed to identify the individual's support needs and develop tailored support plans. People with diabetes and their family members should be offered hypoglycaemia-specific education and training.

Function and Emotion in Everyday Life With Type 1 Diabetes (FEEL-T1D): Protocol for a Fully Remote Intensive Longitudinal Study

BACKGROUND

Although short-term blood glucose levels and variability are thought to underlie diminished function and emotional well-being in people with type 1 diabetes (T1D), these relationships are poorly understood. The Function and Emotion in Everyday Life with T1D (FEEL-T1D) study focuses on investigating these short-term dynamic relationships among blood glucose levels, functional ability, and emotional well-being in adults with T1D.

OBJECTIVE

The aim of this study is to present the FEEL-T1D study design, methods, and study progress to date, including adaptations necessitated by the COVID-19 pandemic to implement the study fully remotely.

METHODS

The FEEL-T1D study will recruit 200 adults with T1D in the age range of 18-75 years. Data collection includes a comprehensive survey battery, along with 14 days of intensive longitudinal data using blinded continuous glucose monitoring, ecological momentary assessments, ambulatory cognitive tasks, and accelerometers. All study procedures are conducted remotely by mailing the study equipment and by using videoconferencing for study visits.

RESULTS

The study received institutional review board approval in January 2019 and was funded in April 2019. Data collection began in June 2020 and is projected to end in December 2021. As of June 2021, after 12 months of recruitment, 124 participants have enrolled in the FEEL-T1D study. Approximately 87.6% (7082/8087) of ecological momentary assessment surveys have been completed with minimal missing data, and 82.0% (82/100) of the participants provided concurrent continuous glucose monitoring data, ecological momentary assessment data, and accelerometer data for at least 10 of the 14 days of data collection.

CONCLUSIONS

Thus far, our reconfiguration of the FEEL-T1D protocol to be implemented remotely during the COVID-19 pandemic has been a success. The FEEL-T1D study will elucidate the dynamic relationships among blood glucose levels, emotional well-being, cognitive function, and participation in daily activities. In doing so, it will pave the way for innovative just-in-time interventions and produce actionable insights to facilitate tailoring of diabetes treatments to optimize the function and well-being of individuals with T1D.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/30901.

The suitability of patient-reported outcome measures used to assess the impact of hypoglycaemia on quality of life in people with diabetes: a systematic review using COSMIN methods

AIMS/HYPOTHESIS

It is generally accepted that hypoglycaemia can negatively impact the quality of life (QoL) of people living with diabetes. However, the suitability of patient-reported outcome measures (PROMs) used to assess this impact is unclear. The aim of this systematic review was to identify PROMs used to assess the impact of hypoglycaemia on QoL and examine their quality and psychometric properties.

METHODS

Systematic searches (MEDLINE, EMBASE, PsycINFO, CINAHL and The Cochrane Library databases) were undertaken to identify published articles reporting on the development or validation of hypoglycaemia-specific PROMs used to assess the impact of hypoglycaemia on QoL (or domains of QoL) in adults with diabetes. A protocol was developed and registered with PROSPERO (registration no. CRD42019125153). Studies were assessed for inclusion at title/abstract stage by one reviewer. Full-text articles were scrutinised where considered relevant or potentially relevant or where doubt existed. Twenty per cent of articles were assessed by a second reviewer. PROMS were evaluated, according to COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidelines, and data were extracted independently by two reviewers against COSMIN criteria. Assessment of each PROM's content validity included reviewer ratings (N = 16) of relevance, comprehensiveness and comprehensibility: by researchers (n = 6); clinicians (n = 6); and adults with diabetes (n = 4).

RESULTS

Of the 214 PROMs used to assess the impact of hypoglycaemia on QoL (or domains of QoL), seven hypoglycaemia-specific PROMS were identified and subjected to full evaluation: the Fear of Hypoglycemia 15-item scale; the Hypoglycemia Fear Survey; the Hypoglycemia Fear Survey version II; the Hypoglycemia Fear Survey-II short-form; the Hypoglycemic Attitudes and Behavior Scale; the Hypoglycemic Confidence Scale; and the QoLHYPO questionnaire. Content validity was rated as 'inconsistent', with most as '(very) low' quality, while structural validity was deemed 'unsatisfactory'. Other measurement properties (e.g. reliability) varied, and evidence gaps were apparent across all PROMs. None of the identified studies addressed cross-cultural validity or measurement error. Criterion validity and responsiveness were not assessed due to the lack of a 'gold standard' measure of the impact of hypoglycaemia on QoL against which to compare the PROMS.

CONCLUSIONS/INTERPRETATION

None of the hypoglycaemia-specific PROMs identified had sufficient evidence to demonstrate satisfactory validity, reliability and responsiveness. All were limited in terms of content and structural validity, which restricts their utility for assessing the impact of hypoglycaemia on QoL in the clinic or research setting. Further research is needed to address the content validity of existing PROMs, or the development of new PROM(s), for the purpose of assessing the impact of hypoglycaemia on QoL.

PROSPERO REGISTRATION

CRD42019125153.

The consequences of hypoglycaemia

Hypoglycaemia (blood glucose concentration below the normal range) has been recognised as a complication of insulin treatment from the very first days of the discovery of insulin, and remains a major concern for people with diabetes, their families and healthcare professionals today. Acute hypoglycaemia stimulates a stress response that acts to restore circulating glucose, but plasma glucose concentrations can still fall too low to sustain normal brain function and cardiac rhythm. There are long-term consequences of recurrent hypoglycaemia, which are still not fully understood. This paper reviews our current understanding of the acute and cumulative consequences of hypoglycaemia in insulin-treated diabetes.

Associations of Time in Range and Other Continuous Glucose Monitoring-Derived Metrics With Well-Being and Patient-Reported Outcomes: Overview and Trends

Time in glucose ranges is increasingly relevant for research and clinical practice. Whereas the clinical validity of these metrics has been demonstrated with regard to long-term complications, their associations with patient-reported outcomes such as well-being, diabetes distress, and fear of hypoglycemia remain an open research question. This article reviews existing evidence on links between times in glycemic ranges and patient-reported outcomes. It also describes a novel research approach of using ecological momentary assessment to analyze on a more granular level in real time possible associations of these parameters of glycemic control and patient-reported outcomes. Such an approach could further our understanding of how glucose and patient-reported outcomes may be interconnected.

Hyperinsulinaemic-hypoglycaemic glucose clamps in human research: a systematic review of the literature

AIMS/HYPOTHESIS

The hyperinsulinaemic-hypoglycaemic glucose clamp technique has been developed and applied to assess effects of and responses to hypoglycaemia under standardised conditions. However, the degree to which the methodology of clamp studies is standardised is unclear. This systematic review examines how hyperinsulinaemic-hypoglycaemic clamps have been performed and elucidates potential important differences.

METHODS

A literature search in PubMed and EMBASE was conducted. Articles in English published between 1980 and 2018, involving adults with or without diabetes, were included.

RESULTS

A total of 383 articles were included. There was considerable variation in essential methodology of the hypoglycaemic clamp procedures, including the insulin dose used (49-fold difference between the lowest and the highest rate), the number of hypoglycaemic steps (range 1-6), the hypoglycaemic nadirs (range 2.0-4.3 mmol/l) and the duration (ranging from 5 to 660 min). Twenty-seven per cent of the articles reported whole blood glucose levels, most venous levels. In 70.8% of the studies, a dorsal hand vein was used for blood sampling, with some form of hand warming to arterialise venous blood in 78.8% of these. Key information was missing in 61.9% of the articles.

CONCLUSIONS/INTERPRETATION

Although the hyperinsulinaemic-hypoglycaemic clamp procedure is considered the gold standard to study experimental hypoglycaemia, a uniform standard with key elements on how to perform these experiments is lacking. Methodological differences should be considered when comparing results between hypoglycaemic clamp studies.

PROSPERO REGISTRATION

This systematic review is registered in PROSPERO (CRD42019120083).

Mathematical Models of Meal Amount and Timing Variability With Implementation in the Type-1 Diabetes Patient Decision Simulator

BACKGROUND

In type 1 diabetes (T1D) research, in-silico clinical trials (ISCTs) have proven effective in accelerating the development of new therapies. However, published simulators lack a realistic description of some aspects of patient lifestyle which can remarkably affect glucose control. In this paper, we develop a mathematical description of meal carbohydrates (CHO) amount and timing, with the aim to improve the meal generation module in the T1D Patient Decision Simulator (T1D-PDS) published in Vettoretti et al.

METHODS

Data of 32 T1D subjects under free-living conditions for 4874 days were used. Univariate probability density function (PDF) parametric models with different candidate shapes were fitted, individually, against sample distributions of: CHO amounts of breakfast (CHOB), lunch (CHOL), dinner (CHOD), and snack (CHOS); breakfast timing (TB); and time between breakfast-lunch (TBL) and between lunch-dinner (TLD). Furthermore, a support vector machine (SVM) classifier was developed to predict the occurrence of a snack in future fixed-length time windows. Once embedded inside the T1D-PDS, an ISCT was performed.

RESULTS

Resulting PDF models were: gamma (CHOB, CHOS), lognormal (CHOL, TB), loglogistic (CHOD), and generalized-extreme-values (TBL, TLD). The SVM showed a classification accuracy of 0.8 over the test set. The distributions of simulated meal data were not statistically different from the distributions of the real data used to develop the models (α = 0.05).

CONCLUSIONS

The models of meal amount and timing variability developed are suitable for describing real data. Their inclusion in modules that describe patient behavior in the T1D-PDS can permit investigators to perform more realistic, reliable, and insightful ISCTs.

Reducing the burden of hypoglycaemia in people with diabetes through increased understanding: design of the Hypoglycaemia REdefining SOLutions for better liVEs (Hypo-RESOLVE) project

BACKGROUND

Hypoglycaemia is the most frequent complication of treatment with insulin or insulin secretagogues in people with diabetes. Severe hypoglycaemia, i.e. an event requiring external help because of cognitive dysfunction, is associated with a higher risk of adverse cardiovascular outcomes and all-cause mortality, but underlying mechanism(s) are poorly understood. There is also a gap in the understanding of the clinical, psychological and health economic impact of 'non-severe' hypoglycaemia and the glucose level below which hypoglycaemia causes harm.

AIM

To increase understanding of hypoglycaemia by addressing the above issues over a 4-year period.

METHODS

Hypo-RESOLVE is structured across eight work packages, each with a distinct focus. We will construct a large, sustainable database including hypoglycaemia data from >100 clinical trials to examine predictors of hypoglycaemia and establish glucose threshold(s) below which hypoglycaemia constitutes a risk for adverse biomedical and psychological outcomes, and increases healthcare costs. We will also investigate the mechanism(s) underlying the antecedents and consequences of hypoglycaemia, the significance of glucose sensor-detected hypoglycaemia, the impact of hypoglycaemia in families, and the costs of hypoglycaemia for healthcare systems.

RESULTS

The outcomes of Hypo-RESOLVE will inform evidence-based definitions regarding the classification of hypoglycaemia in diabetes for use in daily clinical practice, future clinical trials and as a benchmark for comparing glucose-lowering interventions and strategies across trials. Stakeholders will be engaged to achieve broadly adopted agreement.

CONCLUSION

Hypo-RESOLVE will advance our understanding and refine the classification of hypoglycaemia, with the ultimate aim being to alleviate the burden and consequences of hypoglycaemia in people with diabetes.