Exploring the influence of behavioral factors on depression and anxiety scores during the COVID-19 pandemic: insights from the Virginia statewide COVIDsmart longitudinal study.

BACKGROUND: Amidst the COVID-19 pandemic, there has been growing concern about the declining mental health and healthy behaviors compared to pre-pandemic levels. Despite this, there is a lack of longitudinal studies that have examined the relationship between health behaviors and mental health during the pandemic. In response, the statewide COVIDsmart longitudinal study was launched. The study's main objective is to better understand the effects of the pandemic on mental health. Findings may provide a foundation for the identification of public health strategies to mitigate future negative impacts of the pandemic. METHODS: Following online recruitment in spring of 2021, adults, ages 18 to 87, filled out social, mental, economic, occupational, and physical health questionnaires on the digital COVIDsmart platform at baseline and through six monthly follow-ups. Changes in the participant's four health behaviors (e.g., tobacco and alcohol consumption, physical activity, and social media use), along with sex, age, loneliness score, and reported social and economic (SE) hardships, were analyzed for within-between group associations with depression and anxiety scores using Mixed Models Repeated Measures. RESULTS: In this study, of the 669 individuals who reported, the within-between group analysis indicated that younger adults (F = 23.81, p < 0.0001), loneliness (F = 234.60, p < 0.0001), SE hardships (F = 31.25, p < 0.0001), increased tobacco use (F = 3.05, p = 0.036), decreased physical activity (F = 6.88, p = 0.0002), and both positive and negative changes in social media use (F = 7.22, p = 0.0001) were significantly associated with worse depression scores. Additionally, females (F = 6.01, p = 0.015), younger adults (F = 32.30, p < 0.0001), loneliness (F = 154.59, p < 0.0001), SE hardships (F = 22.13, p < 0.0001), increased tobacco use (F = 4.87, p = 0.004), and both positive and negative changes in social media use (F = 3.51, p = 0.016) were significantly associated with worse anxiety scores. However, no significant changes were observed in the within-between group measurements of depression and anxiety scores over time (p > 0.05). Physical activity was not associated with anxiety nor was alcohol consumption with both depression and anxiety (p > 0.05). CONCLUSIONS: This study demonstrates the longitudinal changes in behaviors within the context of the COVID-19 pandemic. These findings may facilitate the design of preventative population-based health approaches during the COVID-19 pandemic or future pandemics.

A Digital Health Initiative (COVIDsmart) for Remote Data Collection and Study of COVID-19's Impact on the State of Virginia: Prospective Cohort Study.

BACKGROUND: The COVID-19 pandemic has affected people's lives beyond severe and long-term physical health symptoms. Social distancing and quarantine have led to adverse mental health outcomes. COVID-19-induced economic setbacks have also likely exacerbated the psychological distress affecting broader aspects of physical and mental well-being. Remote digital health studies can provide information about the pandemic's socioeconomic, mental, and physical impact. COVIDsmart was a collaborative effort to deploy a complex digital health research study to understand the impact of the pandemic on diverse populations. We describe how digital tools were used to capture the effects of the pandemic on the overall well-being of diverse communities across large geographical areas within the state of Virginia. OBJECTIVE: The aim is to describe the digital recruitment strategies and data collection tools applied in the COVIDsmart study and share the preliminary study results. METHODS: COVIDsmart conducted digital recruitment, e-Consent, and survey collection through a Health Insurance Portability and Accountability Act-compliant digital health platform. This is an alternative to the traditional in-person recruitment and onboarding method used for studies. Participants in Virginia were actively recruited over 3 months using widespread digital marketing strategies. Six months of data were collected remotely on participant demographics, COVID-19 clinical parameters, health perceptions, mental and physical health, resilience, vaccination status, education or work functioning, social or family functioning, and economic impact. Data were collected using validated questionnaires or surveys, completed in a cyclical fashion and reviewed by an expert panel. To retain a high level of engagement throughout the study, participants were incentivized to stay enrolled and complete more surveys to further their chances of receiving a monthly gift card and one of multiple grand prizes. RESULTS: Virtual recruitment demonstrated relatively high rates of interest in Virginia (N=3737), and 782 (21.1%) consented to participate in the study. The most successful recruitment technique was the effective use of newsletters or emails (n=326, 41.7%). The primary reason for contributing as a study participant was advancing research (n=625, 79.9%), followed by the need to give back to their community (n=507, 64.8%). Incentives were only reported as a reason among 21% (n=164) of the consented participants. Overall, the primary reason for contributing as a study participant was attributed to altruism at 88.6% (n=693). CONCLUSIONS: The COVID-19 pandemic has accelerated the need for digital transformation in research. COVIDsmart is a statewide prospective cohort to study the impact of COVID-19 on Virginians' social, physical, and mental health. The study design, project management, and collaborative efforts led to the development of effective digital recruitment, enrollment, and data collection strategies to evaluate the pandemic's effects on a large, diverse population. These findings may inform effective recruitment techniques across diverse communities and participants' interest in remote digital health studies.

Neighborhood socioeconomic inequality based on everyday mobility predicts COVID-19 infection in San Francisco, Seattle, and Wisconsin.

Race and class disparities in COVID-19 cases are well documented, but pathways of possible transmission by neighborhood inequality are not. This study uses administrative data on COVID-19 cases for roughly 2000 census tracts in Wisconsin, Seattle/King County, and San Francisco to analyze how neighborhood socioeconomic (dis)advantage predicts cumulative caseloads through February 2021. Unlike past research, we measure a neighborhood's disadvantage level using both its residents' demographics and the demographics of neighborhoods its residents visit and are visited by, leveraging daily mobility data from 45 million mobile devices. In all three jurisdictions, we find sizable disparities in COVID-19 caseloads. Disadvantage in a neighborhood's mobility network has greater impact than its residents' socioeconomic characteristics. We also find disparities by neighborhood racial/ethnic composition, which can be explained, in part, by residential and mobility-based disadvantage. Neighborhood conditions measured before a pandemic offer substantial predictive power for subsequent incidence, with mobility-based disadvantage playing an important role.

Wealth, Race, and Place: How Neighborhood (Dis)advantage From Emerging to Middle Adulthood Affects Wealth Inequality and the Racial Wealth Gap.

Do neighborhood conditions affect wealth accumulation? This study uses the National Longitudinal Survey of Youth 1979 cohort and a counterfactual estimation strategy to analyze the effect of prolonged exposure to neighborhood (dis)advantage from emerging adulthood through middle adulthood. Neighborhoods have sizable, plausibly causal effects on wealth, but these effects vary significantly by race/ethnicity and homeownership. White homeowners receive the largest payoff to reductions in neighborhood disadvantage. Black adults, regardless of homeownership, are doubly disadvantaged in the neighborhood-wealth relationship. They live in more-disadvantaged neighborhoods and receive little return to reductions in neighborhood disadvantage. Findings indicate that disparities in neighborhood (dis)advantage figure prominently in wealth inequality and the racial wealth gap.

Comparing Patch vs Pen Bolus Insulin Delivery in Type 2 Diabetes Using Continuous Glucose Monitoring Metrics and Profiles.

OBJECTIVE: CeQur Simplicity™ (CeQur, Marlborough, MA) is a 3-day insulin delivery patch designed to meet mealtime insulin requirements. A recently reported 48-week, randomized, multicenter, interventional trial compared efficacy, safety and self-reported outcomes in 278 adults with type 2 diabetes (T2D) on basal insulin therapy who initiated and managed mealtime insulin therapy with a patch pump versus insulin pen. We assessed changes in key glycemic metrics among a subset of patients who wore a continuous glucose monitoring (CGM) device. METHODS: Study participants (patch, n = 49; pen, n = 48) wore a CGM device in masked setting during the baseline period and prior to week 24. Glycemic control was assessed using international consensus guidelines for percentage of Time In Range (%TIR: >70% at 70-180 mg/dL), Time Below Range (%TBR: <4% at <70 mg/dL; <1% at <54 mg/dL), and Time Above Range (%TAR: <25% at >180 mg/dL; <5% at >250 mg/dL). RESULTS: Both the patch and pen groups achieved recommended targets in %TIR (74.1% ± 18.7%, 75.2 ± 16.1%, respectively) and marked reductions in %TAR >180 mg/dL (21.1% ± 19.9%, 19.7% ± 17.5%, respectively) but with increased %TBR <70 mg/dL (4.7% ± 5.2%, 5.1 ± 5.8, respectively), all P < .0001. No significant between-group differences in glycemic improvements or adverse events were observed. CONCLUSIONS: CGM confirmed that the patch or pen can be used to safely initiate and optimize basal-bolus therapy using a simple insulin adjustment algorithm with SMBG. Preference data suggest that use of the patch vs pen may enhance treatment adherence.

Implementation of Basal-Bolus Therapy in Type 2 Diabetes: A Randomized Controlled Trial Comparing Bolus Insulin Delivery Using an Insulin Patch with an Insulin Pen.

Background: Barriers to mealtime insulin include complexity, fear of injections, and lifestyle interference. This multicenter, randomized controlled trial evaluated efficacy, safety, and self-reported outcomes in adults with type 2 diabetes, inadequately controlled on basal insulin, initiating and managing mealtime insulin with a wearable patch versus an insulin pen. Methods: Adults with type 2 diabetes (n = 278, age: 59.2 ± 8.9 years), were randomized to patch (n = 139) versus pen (n = 139) for 48 weeks, with crossover at week 44. Baseline insulin was divided 1:1 basal: bolus. Using a pattern-control logbook, subjects adjusted basal and bolus insulin weekly using fasting and premeal glucose targets. Results: Glycated hemoglobin (HbA1c) change (least squares mean ± standard error) from baseline to week 24 (primary endpoint) improved (P < 0.0001) in both arms, -1.7% ± 0.1% and -1.6% ± 0.1% for patch and pen (-18.6 ± 1.1 and -17.5 ± 1.1 mmol/mol), and was maintained at 44 weeks. The coefficient of variation of 7-point self-monitoring blood glucose decreased more (P = 0.02) from baseline to week 44 for patch versus pen. There were no differences in adverse events, including hypoglycemia (three severe episodes per arm), and changes in weight and insulin doses. Subject-reported treatment satisfaction, quality of life, experience ratings at week 24, and device preferences at week 48 significantly favored the patch. Most health care providers preferred patch for mealtime insulin. Conclusions: Bolus insulin delivered by patch and pen using an algorithm-based weekly insulin dose titration significantly improved HbA1c in adults with type 2 diabetes, with improved subject and health care provider experience and preference for the patch.

Use of Blood Glucose Meters Featuring Color Range Indicators Improves Glycemic Control in Patients With Diabetes in Comparison to Blood Glucose Meters Without Color (ACCENTS Study).

BACKGROUND: The ability of patients to improve glycemic control depends partly on their ability to interpret and act on blood glucose results. We investigated whether switching people with diabetes to blood glucose meters (BGMs) featuring a color range indicator (CRI) could improve glycemic control compared to remaining on their current BGM without color. METHODS: 163 adults with type 1 (T1D) or type 2 diabetes (T2D) and a hemoglobin A1c (A1c) of 7.5-11% were randomized to: One Touch Verio™ (Verio), OneTouch Verio Flex™ (Flex), or controls remaining on their current BGM. Diabetes nurses had standard conversations about diabetes management with all subjects at baseline. No changes in medication, insulin dosing, or SMBG frequency were recommended. RESULTS: After 12 weeks, subjects who switched to Verio or Flex meters with CRI (n = 108) had a mean change in A1c 0.36% lower than controls (n = 55) ( P = .017). A1c reductions were greatest in T1D subjects (n = 45), with a decrease of 0.50% ( P = .004). T1D subjects using Verio meters (n = 25) contributed a 0.59% reduction compared to controls ( P < .008), whereas T1D subjects using Flex meters (n = 20) had a clinical meaningful reduction in A1c of 0.40% without reaching statistical significance ( P > .05). Verio and Flex users reported taking more action and easier understanding of diabetes management compared to previous BGMs. CONCLUSIONS: This study demonstrated that switching patients to BGMs featuring a CRI resulted in improvements in glycemic control compared to subjects using currently marketed BGMs that do not use a CRI. Registration: Clinicaltrials.gov NCT02929654 https://clinicaltrials.gov/ct2/show/NCT02929654.

Why Did People Move During the Great Recession?: The Role of Economics in Migration Decisions.

Labor migration offers an important mechanism to reallocate workers when there are regional differences in employment conditions. Whereas conventional wisdom suggests migration rates should increase during recessions as workers move out of areas that are hit hardest, initial evidence suggested that overall migration rates declined during the Great Recession, despite large regional differences in unemployment and growth rates. In this paper, we use data from the American Community Survey to analyze internal migration trends before and during the economic downturn. First, we find only a modest decline in the odds of adults leaving distressed labor market areas during the recession, which may result in part from challenges related to the housing price crash. Second, we estimate conditional logit models of destination choice for individuals who migrate across labor market areas and find a substantial effect of economic factors such as labor demand, unemployment, and housing values. We also estimate latent class conditional logit models that test whether there is heterogeneity in preferences for destination characteristics among migrants. Over all, the latent class models suggest that roughly equal percentages of migrants were motivated by economic factors before and during the recession. We conclude that fears of dramatic declines in labor migration seem to be unsubstantiated.

When love meets hate: The relationship between state policies on gay and lesbian rights and hate crime incidence.

Do public policies on gay and lesbian rights affect the incidence of hate crimes based on sexual orientation? We propose that legal inequalities increase hate crimes because they provide discursive opportunities for bias, discrimination, and violence. Legal equality, however, will reduce violence. Using annual panel data from 2000 to 2012, a period of substantial policy change, we analyze how three state policies affect reported hate crimes: same-sex partnerships, employment non-discrimination, and hate crime laws. Hate crime and employment non-discrimination laws that include sexual orientation reduce hate crime incidence. Partnership recognition increases reported hate crimes, though it may not increase actual crime incidence. Because incidence is spatially correlated, policy changes in one state yield spillover benefits in other states. These results provide some of the first quantitative evidence that public policies affect hate crimes based on sexual orientation. Findings confirm the roles of institutional heterosexism and discursive opportunities in producing hate crimes.

Comparison of rechargeable versus battery-operated insulin pumps: temperature fluctuations.

The role of continuous subcutaneous insulin infusion (insulin pumps) has become increasingly important in diabetes management, and many different types of these systems are currently available. This exploratory study focused on the reported heating issues that lithium-ion battery-powered pumps may have during charging compared with battery-operated pumps. It was found that pump temperature increased by 6.4°C during a long charging cycle of a lithiumion battery-operated pump under ambient temperatures. In an environmental-chamber kept at 35°C, the pump temperature increased by 4.4°C, which indicates that the pump temperature was above that of the recommended safety limit for insulin storage of 37°C. When designing new pumps, and when using currently available rechargeable pumps in warmer climates, the implications of these temperature increases should be taken into consideration. Future studies should also further examine insulin quality after charging.

A Comprehensive Evaluation of a Novel Color Range Indicator in Multiple Blood Glucose Meters Demonstrates Improved Glucose Range Interpretation and Awareness in Subjects With Type 1 and Type 2 Diabetes.

AIMS: We previously demonstrated that people with type 2 diabetes (T2DM) can improve their ability to categorize blood glucose (BG) results into low, in range, or high glycemic ranges after experiencing a color range indicator (CRI or ColorSure™ Technology) in a single meter. This study examined whether a CRI was effective in people with type 1 (T1) or T2DM when used in 3 glucose meters. METHODS: A total of 179 subjects (139 T2DM and 40 T1DM) classified BG values as low, in range, or high based on individual current knowledge. Subjects then experienced the CRI which showed whether different BG values were low, in range, or high. After CRI interaction, subjects repeated the classification. RESULTS: Following interaction with the CRI, subjects significantly improved their ability to categorize BG results into low, in range, and high glycemic ranges by 27.9% (T2DM) and 27.2% (T1DM) (each P < .001). Improvement was not accompanied by an increase in time spent categorizing results. There was no difference in classification ability between subjects with T1 or T2DM. There was also no correlation between HbA1c, numeracy level, test frequency, or duration of diabetes and the ability to correctly classify results. Subjects agreed the CRI feature helped them easily interpret glucose values and improved their awareness of glucose ranges. CONCLUSION: Interaction with a CRI improved the ability of subjects with T1 and T2DM to interpret and categorize BG values into recommended glycemic ranges, irrespective of the glucose meter providing the CRI insights.

Outcome Measures for Artificial Pancreas Clinical Trials: A Consensus Report.

Research on and commercial development of the artificial pancreas (AP) continue to progress rapidly, and the AP promises to become a part of clinical care. In this report, members of the JDRF Artificial Pancreas Project Consortium in collaboration with the wider AP community 1) advocate for the use of continuous glucose monitoring glucose metrics as outcome measures in AP trials, in addition to HbA1c, and 2) identify a short set of basic, easily interpreted outcome measures to be reported in AP studies whenever feasible. Consensus on a broader range of measures remains challenging; therefore, reporting of additional metrics is encouraged as appropriate for individual AP studies or study groups. Greater consistency in reporting of basic outcome measures may facilitate the interpretation of study results by investigators, regulatory bodies, health care providers, payers, and patients themselves, thereby accelerating the widespread adoption of AP technology to improve the lives of people with type 1 diabetes.

Remote Health Consultations Supported by a Diabetes Management Web Application With a New Glucose Meter Demonstrates Improved Glycemic Control.

BACKGROUND: Cloud-connected diabetes applications enable health care professionals (HCPs) to monitor patient progress and offer the potential for remote consultations. OneTouch Reveal (OTR) is a cloud-based web application that aggregates data from blood glucose (BG) meters or insulin pumps and provides analytics to help patients and HCPs make more informed treatment and lifestyle decisions. This study assessed the experience of patients using OTR and the OneTouch Verio (OTV) BG meter and determined the extent of changes in glycemic control. METHODS: Subjects with T1DM (23) or T2DM (17) uploaded BG meter results to OTR for 12 weeks. HCPs remotely reviewed progress using OTR and delivered telephone consultations at 4 and 8 weeks based on OTR insights. RESULTS: After 12 weeks, mean HbA1c decreased by 0.4% (P < .001) and 25% of subjects had a reduction of ≥1.0%. Reduction in HbA1c was similar in subjects with T1DM and T2DM, although subjects with T1DM started with higher baselines. In subjects with T2DM, mean BG decreased significantly from 175 to 161 mg/dl (P < .001) with the percentage of above-range BG results decreasing from 33% to 24%. 80% of subjects confirmed OTR detected out-of-range glucose patterns and 84% of these subjects were able to correct the underlying pattern to get BG back in-range. CONCLUSIONS: OTR web application in combination with the OTV meter helped subjects with T1DM and T2DM effectively manage their diabetes and was associated with improved BG control over 12 weeks. Real-time visibility to subject data may help HCPs deliver focused and effective remote consultations.

The Hypoglycaemia-Hyperglycaemia Minimizer System in the Management of Type 1 Diabetes.

Living with type 1 diabetes (T1D) presents many challenges in terms of daily living. Insulin users need to frequently monitor their blood glucose levels and take multiple injections per day and/or multiple boluses through an insulin infusion pump, with the consequences of failing to match the insulin dose to the body's needs resulting in hypoglycaemia and hyperglycaemia. The former can result in seizures, coma and even death; the latter can have both acute and long-term health implications. Many patients with T1D also fail to meet their treatment goals. In order to reduce the burdens of self-administering insulin, and improve efficacy and safety, there is a need to at least partially remove the patient from the loop via a closed-loop 'artificial pancreas' system. The Hypoglycaemia-Hyperglycaemia Minimizer (HHM) System, comprising a continuous, subcutaneous insulin infusion pump, continuous glucose monitor (CGM) and closed-loop insulin dosing algorithm, is able to predict changes in blood glucose and adjust insulin delivery accordingly to help keep the patient at normal glucose levels. Early clinical data indicate that this system is feasible, effective and safe, and has the potential to dramatically improve the therapeutic outcomes and quality of life for people with T1D.

Sensitivity of the Predictive Hypoglycemia Minimizer System to the Algorithm Aggressiveness Factor.

BACKGROUND: The Predictive Hypoglycemia Minimizer System ("Hypo Minimizer"), consisting of a zone model predictive controller (the "controller") and a safety supervision module (the "safety module"), aims to mitigate hypoglycemia by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The "aggressiveness factor," a pivotal variable in the system, governs the speed and magnitude of the controller's insulin dosing characteristics in response to changes in CGM levels. METHODS: Twelve adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 24 hours. This analysis focused primarily on the effect of the aggressiveness factor on the automated insulin-delivery characteristics of the controller, and secondarily on the glucose control results. RESULTS: As aggressiveness increased from "conservative" to "medium" to "aggressive," the controller recommended less insulin (-3.3% vs -14.4% vs -19.5% relative to basal) with a higher frequency (5.3% vs 14.4% vs 20.3%) during the critical times when the CGM was reading 90-120 mg/dl and decreasing. Blood glucose analyses indicated that the most aggressive setting resulted in the most desirable combination of the least time spent <70 mg/dl and the most time spent 70-180 mg/dl, particularly in the overnight period. Hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia did not occur with any of the aggressiveness values. CONCLUSION: The Hypo Minimizer's controller took preemptive action to prevent hypoglycemia based on predicted changes in CGM glucose levels. The most aggressive setting was quickest to take action to reduce insulin delivery below basal and achieved the best glucose metrics.

Interactive Exposure With a Blood Glucose Monitor With a Novel Glucose Color Range Indicator Is Associated With Improved Glucose Range Interpretation and Awareness in Patients With Type 2 Diabetes.

AIMS: The ability of patients to achieve glycemic control depends in part on their ability to interpret and act on blood glucose (BG) results. This clinical study was conducted to determine if a simple on-meter color range indicator (CRI) could improve the ability of patients to categorize BG values into low, in-range, and high glycemic ranges. METHODS: The clinical study was conducted in 59 subjects with type 2 diabetes (T2DM). Subjects classified 50 general, 15 before- and 15 after-meal BG values as low, in-range, or high based on their current knowledge. Subjects then interactively experienced the on-meter CRI, which showed whether alternate BG values were low, in-range, or high. After CRI interaction, subjects repeated the original scoring assessment followed by a survey exploring their awareness of glucose ranges. RESULTS: Following interaction with the CRI, subjects improved their ability to categorize general, before-meal and after-meal BG results by 23.4% ± 3.0% (SEM), 14.2% ± 2.4%, and 16.1% ± 2.9%, respectively (all P < .001), into low, in-range, and high glycemic ranges. Improvement was not accompanied by an increase in time spent categorizing results. There was no correlation between subject HbA1c, test frequency, or duration of diabetes and ability to correctly classify results. Subjects agreed the CRI feature helped them easily interpret glucose values and improved their awareness of glucose ranges. CONCLUSION: A short interactive session with a meter including a CRI feature improved the ability of T2DM subjects to interpret and categorize BG values into recommended ranges.

High reported treatment satisfaction in people with type 1 diabetes switching to latest generation insulin pump regardless of previous therapy.

The effects of transition by individuals with type 1 diabetes (T1D) to more recently available continuous glucose monitoring (CGM)-enabled insulin pumps from either multiple daily insulin injections (MDI) or older insulin pumps on treatment satisfaction have not been well studied. We conducted a survey to assess treatment satisfaction among users of the Animas(®) Vibe™ insulin pump, a latest generation insulin pump (LGIP) system (CGM-enabled), after switching from MDI or earlier generation insulin pumps. Individuals with T1D from 141 centers in 5 countries and 4 language areas participated in the survey. Treatment satisfaction was assessed by the Insulin Treatment Satisfaction Questionnaire (ITSQ), which was included in a 50-item online questionnaire that also assessed preference for using the LGIP compared with previous treatment and satisfaction with key LGIP features. A total of 356 individuals, ages 12-79 years, responded to the survey: mean (SD) age 38.4 (16.1) years; diabetes duration 19.1 (13.3) years; female 59%; previously treated with MDI 58%. Overall mean (SD) ITSQ scores were high among all respondents regardless of prior treatment: 95.1 (23.2) (scale: 0-132). No differences between previous-treatment groups were seen. Most (83%) of respondents rated the LGIP to be better than their previous insulin delivery system: "much better" (65%), "a bit better" (18%) regardless of age, and 95% would recommend using the LGIP to others. Use of the Animas Vibe was associated with high treatment satisfaction and perceived as a better method of insulin delivery regardless of previous insulin therapy or age.

The Insulin Treatment Satisfaction Questionnaire and Assessment of Satisfaction with a Latest-generation Insulin Pump.

Satisfaction with the latest-generation insulin pump (LGIP) was assessed in patients with diabetes mellitus enrolled in the Comparing Perception of Insulin Therapies for T1D Patients with the Aim to Improve Quality of Care (CHOICE) study. The Insulin Treatment Satisfaction Questionnaire (ITSQ), a measure of insulin treatment satisfaction, together with additional questions assessed respondents' perceptions of glucose control, their satisfaction with major LGIP features and preference for the LGIP versus their previous treatment, was used. The LGIP (Animas® Vibe™) was considered to be a better method for delivering insulin compared with their therapy before switching and was rated high for treatment satisfaction. These findings should be useful to clinicians when considering the possibility of transferring a patient from their existing treatment regimen to a LGIP.

Comparative dose accuracy of durable and patch insulin infusion pumps.

BACKGROUND: As all major insulin pump manufacturers comply with the international infusion pump standard EN 60601-2-24:1998, there may be a general assumption that all pumps are equal in insulin-delivery accuracy. This research investigates single-dose and averaged-dose accuracy of incremental basal deliveries for one patch model and three durable models of insulin pumps. METHOD: For each pump model, discrete single doses delivered during 0.5 U/h basal rate infusion over a 20 h period were measured using a time-stamped microgravimetric system. Dose accuracy was analyzed by comparing single doses and time-averaged doses to specific accuracy thresholds (±5% to ±30%). RESULTS: The percentage of single doses delivered outside accuracy thresholds of ±5%, ±10%, and ±20% were as follows: Animas OneTouch® Ping® (43.2%, 14.3%, and 1.8%, respectively), Roche Accu-Chek® Combo (50.6%, 24.4%, and 5.5%), Medtronic Paradigm® Revel™/Veo™ (54.2%, 26.7%, and 6.6%), and Insulet OmniPod® (79.1%, 60.5%, and 34.9%). For 30 min, 1 h, and 2 h averaging windows, the percentage of doses delivered outside a ±15% accuracy were as follows: OneTouch Ping (1.0%, 0.4%, and 0%, respectively), Accu-Chek Combo (4.2%, 3.5%, and 3.1%), Paradigm Revel/Veo (3.9%, 3.1%, and 2.2%), and OmniPod (33.9%, 19.9%, and 10.3%). CONCLUSIONS: This technical evaluation demonstrates significant differences in single-dose and averaged-dose accuracy among the insulin pumps tested. Differences in dose accuracy were most evident between the patch pump model and the group of durable pump models. Of the pumps studied, the Animas OneTouch Ping demonstrated the best single-dose and averaged-dose accuracy. Further research on the clinical relevance of these findings is warranted.