Insulin Adherence Research Articles

Identifying the Relationship Between CGM Time in Range and Basal Insulin Adherence in People With Type 2 Diabetes.

The study aimed to determine the relationship between basal insulin adherence and glycemic control evaluated by time in range (TIR) in people with insulin-treated type 2 diabetes (T2D), using data from both continuous glucose monitors (CGM) and connected insulin pens. Furthermore, the study aimed to determine the best basal insulin adherence metric. CGM data and basal insulin data were collected from 106 insulin-treated people (aged ≥18 years) with T2D. Three different adherence metrics were employed (dose deviation, dose deviation ≤20%, and a traditional metric) and a three-step methodology was used to measure insulin adherence level. The coefficient of determination (R2), based on a univariate linear regression analysis, was used to determine the relationship between each adherence metric and TIR. A statistically significant relationship was observed between TIR and adherence quantified as the dose deviation ≤20% metric (R2 = 0.67, P = .006). Neither the relationship between the dose deviation metric and TIR (R2 = 0.43, P = .08) nor the relationship between the traditional metric and TIR (R2 = 0.35, P =.23) was found to be statistically significant. Our study indicates a relationship between basal insulin adherence and TIR in people with insulin-treated T2D. This seems to underscore the role of basal insulin adherence for optimal glycemic outcomes and utilizing TIR as a clinical marker. Furthermore, the results suggest that the magnitude of deviation from the recommended basal insulin dose impacts glycemic control, indicating dose deviation ≤20% as a more accurate metric for quantifying adherence.

Food Insecurity and Diabetes Insulin Adherence Among Older Adults

Older adults in the United States continue to be impacted by food insecurity. Diabetes is on the rise in older adults and insulin therapy is often recommended as treatment. However, less is known about the relationship between food insecurity and insulin adherence among older adults. The current study utilized secondary data analysis methods to examine the 2021 National Health Interview Survey to explore the relationship between food insecurity and insulin adherence among adults aged 55 and older who are living with diabetes. Results of multivariable logistic regression suggest that participants experiencing food insecurity were more likely to take less insulin than needed and delay buying insulin in the past 12 months compared to participants who were food secure. Homeownership was inversely associated with taking less insulin than needed. Higher income-to-poverty ratio was also inversely associated with skipping insulin doses, taking less insulin than needed, and delaying the purchase of insulin. Our results showed that other racialized/ethnic groups (i.e., American Indian, Alaskan Native, Asian, biracial, and multiracial persons) compared to White were less likely to skip an insulin dose and take less insulin than needed. Suggesting food insecurity should be considered when insulin therapy is recommended for older adults with diabetes.

12397 Predictors Of Hospital Readmission Within Three Months Among Patients Admitted For Diabetic Ketoacidosis (dka)

Abstract Disclosure: O. Onwudiwe: None. L. Yerashevich: None. C. Onwudiwe: None. B. Baral: None. A. Acharya: None. H. Nguyen: None. Purpose: Diabetic ketoacidosis (DKA) represents a critical, life-threatening complication of diabetes, with higher rates of re-admission noted among individuals from lower socioeconomic backgrounds, those lacking insurance coverage, and those with suboptimal follow-up care. This study seeks to identify predictors of hospital readmission within three months among patients admitted for DKA in a community hospital setting. Methods: Patient data were extracted from electronic medical records from 2019 to 2021 for individuals admitted due to DKA using ICD codes. DKA diagnosis was based on the presence of hyperglycemia, high anion gap metabolic acidosis, and ketonemia. Demographic information, results of routine biochemical tests, insurance status, follow-up with primary care providers (PCP) or endocrinologists, and clinical progression were retrospectively collected from patients' records. Multivariable logistic regression analyses were conducted to identify predictors of readmission. Results: A total of 222 unique DKA admission visits were analyzed. The mean age (standard deviation) of the patients was 48 (16) years, and 58% of them were male. Among these visits, 39% had type 1 diabetes, 43% had type 2 diabetes, and 18% were newly diagnosed diabetes cases. The majority of patients were overweight, with a mean body mass index (BMI) of 27, and the mean glycated hemoglobin level was 10.8. Common triggers for DKA included insulin non-adherence (52%), infection (37.8%), and alcohol use (8.6%). Logistic regression analysis revealed that lack of follow-up significantly increased the odds of readmission within three months (B = 2.025, p = .003, Exp(B) = 7.576, 95% CI [1.952, 29.401]), as did having type 1 diabetes (B = 1.473, p = .019, Exp(B) = 4.364, 95% CI [1.272, 14.978]). However, the association between insulin adherence and readmission was not statistically significant at the conventional alpha level of 0.05 (B = 1.329, p = .112, Exp(B) = 3.777, 95% CI [0.733, 19.458]). Other demographic (age, gender, employment status, insurance status, medication compliance,) and clinical [insulin adherence, presence of infection, blood glucose level at diagnosis of DKA, and level of glycated hemoglobin (Hba1c)] variables did not significantly predict readmission within 3 months. Conclusion: DKA, being preventable with adequate insulin adherence, is also influenced by factors such as infection and lifestyle choices. The findings highlight the critical role of post-discharge follow-up care in reducing readmission rates among DKA patients. Healthcare providers should prioritize ensuring timely and comprehensive follow-up, particularly for patients with type 1 diabetes, to optimize post-hospitalization management and prevent avoidable readmissions. Presentation: 6/3/2024

Association between insulin adherence and hemoglobin A1c: A systematic review and meta-analysis

Association between insulin adherence and hemoglobin A1c: A systematic review and meta-analysis

Detailed Insights into Basal Insulin Adherence in People with Type 2 Diabetes Using a Data-Driven Assessment Method.

Basal insulin non-adherence is a challenge in people with type 2 diabetes (T2D). Using injection data recorded by a connected insulin pen, we employed a novel three-step methodology to assess three aspects of adherence (overall adherence, adherence distribution, and dose deviation) in individuals with insulin-treated T2D undergoing telemonitoring. Among participants, 52% were considered overall adherent. However, deviations from the recommended dose were observed in all participants, with increased and reduced doses being the predominant forms of non-adherence. Our study underscores the prevalence of basal insulin dosing irregularities in individuals with insulin-treated T2D undergoing telemonitoring.

The effect of USM-IAM-based counselling vs standard counselling on insulin adherence, FBS and HbA1c among patients with uncontrolled type 2 diabetes mellitus (T2DM): a randomised controlled trial

BackgroundMany patients with T2DM on insulin are not optimally controlled despite receiving standard diabetes education counselling. Poor insulin adherence may be a contributing factor. We developed and evaluated a new module [Universiti Sains Malaysia-Insulin Adherence Module (USM-IAM)] on insulin-treated patients with poorly controlled diabetes.MethodsEligibility criteria are those diagnosed with T2DM, aged between 18 and 65 years, with HbA1c between 8 and 15% and on insulin therapy for 1 year. Patients were randomly allocated to receive either the USM-IAM-based counselling or the standard counselling (SC) at baseline and the second visit. Patients were instructed to adjust insulin doses based on blood glucose levels. Outcomes were changes in adherence score, FBS and HbA1c levels from baseline to 3 months and baseline to sixth month.ResultsNinety patients were randomised to each group. The baseline sociodemographic and clinical characteristics were homogenous among groups. Ninety patients were analysed for each group. Adherence score changes between baseline to 3 months were − 8.30 (− 11.47, − 5.14) in USM-IAM-based counselling group (USM-IAM) and − 7.64 (− 10.89, − 4.40) in standard counselling group (SCG), between baseline to sixth month were − 10.21 (− 13.40, − 7.03) in USM-IAM and − 10.79 (− 14.64, − 6.97) in SCG. FBS changes between baseline to 3 months were 1.374 (0.25, 2.50) in USM-IAM and 0.438 (− 0.66, 1.54) in SCG, and between baseline to sixth month were 1.713 (0.473, 2.95) in USM-IAM and 0.998 (− 0.02, 2.01) in SCG. HbA1c changes between baseline to 3 months were 1.374 (0.25, 2.50) in USM-IAM and 0.547 (0.12, 0.98) in SCG, and between baseline to sixth month were 1.03 (0.65, 1.41) in USM-IAM and 0.617 (0.20, 1.03) in SCG. Between-subjects effects for all outcomes were not statistically significant.ConclusionBoth groups had significant improvements in adherence score and HbA1c with time, with higher improvement in patients receiving the USM-IAM. FBS reductions were significant in the intervention group but not in the control group.Trial registrationThis study protocol is registered with Clicaltrials.gov with ID NCT05125185 dated 17th November 2021.

Role of Community Health Nursing in Insulin Initiation for Type 2 Diabetes Patients: A Literature Review

Background: Insulin therapy is essential for managing type 2 diabetes in patients who do not achieve adequate glycemic control with oral medications. Despite its benefits, initiating insulin therapy presents numerous challenges due to psychological, physical, and systemic barriers. This study examines the critical role of community health nurses in facilitating the initiation and management of insulin therapy, addressing patient and healthcare provider barriers, and improving clinical outcomes. Methods: A comprehensive review of existing literature was conducted, focusing on the impact of community health nurses on diabetes management, particularly in insulin initiation and adherence. Results: : Community health nurses play a pivotal role in overcoming barriers to insulin therapy. They provide essential patient education, psychosocial support, and practical training in insulin administration. These efforts lead to improved glycemic control, higher rates of insulin adherence, and better patient satisfaction. Additionally, community health nurses facilitate collaborative care models, integrating with primary care teams to provide continuous and coordinated care. The involvement of community health nurses in diabetes management addresses both patient-related and systemic barriers. Their holistic approach includes personalized patient education, emotional support, and care coordination, significantly enhancing patient adherence and clinical outcomes. Conclusions: Community health nurses are integral to the successful initiation and management of insulin therapy in type 2 diabetes. Future research should focus on developing standardized training programs for community health nurses and exploring innovative care models that leverage their unique skills. Policy support is essential to recognize and expand the role of community health nurses in diabetes care.

Evaluation of Insulin Prescribing Patterns and Associated Burden among Ambulatory Diabetic Patients in Islamabad/Rawalpindi

Background: Diabetes Mellitus (DM) is a significant global health challenge, particularly in developing countries where it is prevalent and associated with high morbidity and mortality due to poor management and adherence to therapy. In Islamabad/Rawalpindi, the management of DM is compromised by gaps in knowledge and adherence regarding insulin use, which is crucial for effective disease control. Objective: This study aims to assess the patterns of insulin usage, adherence to therapy, and the impact of educational status on insulin management among patients with diabetes in Islamabad/Rawalpindi. Methods: A cross-sectional, descriptive, survey-based study was conducted from February to May 2023 among 240 ambulatory diabetic patients. Data were collected using structured questionnaires covering demographics, insulin usage patterns, adherence behaviors, and diabetes management knowledge. Statistical analysis was performed using SPSS version 25, employing descriptive statistics and Chi-Square tests to explore associations between variables. Results: The majority of participants (52.5%) were over 40 years old, with 55% having type 2 diabetes. Insulin pens were used by 47.1% of the participants, while 50% used syringes. Approximately 66.3% of the participants were also taking oral anti-diabetic medications. About 63.7% regularly attended routine checkups, 88.3% knew how to inject insulin, and 90.8% were aware of the timing for insulin injections. Educational interventions showed a significant impact on adherence and knowledge, with 77.5% demonstrating an understanding of diabetes. Conclusion: The study highlights the need for improved diabetes education and access to advanced insulin delivery methods to enhance adherence and management of diabetes in Islamabad/Rawalpindi. Emphasizing patient education on insulin use could lead to better disease outcomes and quality of life for diabetic patients in the region.

Factors Influencing Insulin Adherence among Outpatients with Type 2 Diabetes Mellitus and the Impact of Pharmaceutical Intervention: A Randomized Clinical Trial

Aims. This study aimed to identify and analyze the factors significantly influencing long-term insulin medication adherence among outpatients and to evaluate whether pharmaceutical interventions targeting these factors can improve patient medication adherence and glycemic control. Methods. A cohort of 180 patients was recruited from a tertiary hospital in Nanjing, China. Factors potentially influencing insulin adherence were scrutinized employing the KAP (knowledge, attitude/belief, and practice) health behavior model. Baseline characteristics were extracted from the hospital information system, while patient knowledge of the disease and medication, medication adherence, medication beliefs, and management self-efficacy were assessed, respectively, using self-developed questionnaires, MMAS-8, C-DMSES, and BMQ scales. Univariate and multivariate analyses were conducted to determine the impact of these factors on insulin adherence. Following this, participants were randomly allocated to either the intervention or control group. The intervention group received three months of weekly telephone sessions and educational interventions targeting facets such as medication knowledge and beliefs, while the control group received standard care. After the intervention, insulin adherence and glycemic control conditions of both groups were collected and re-evaluated. Results. After excluding lost-to-follow-up patients, 152 individuals were analyzed (intervention: 75 and control: 77). Multivariate analyses revealed factors influencing insulin adherence, including age, diabetes duration, health insurance status, HbA1c level, disease and medication knowledge, diabetes management self-efficacy, and medication beliefs (P<0.05). Before targeted pharmaceutical care, no significant differences existed in insulin adherence, HbA1c levels, management self-efficacy, knowledge, or medication beliefs between intervention and control groups (P>0.05). However, subsequent pharmaceutical intervention notably improved adherence, HbA1c levels, self-efficacy, knowledge, and medication beliefs (P<0.05). Conclusion. This study examines the impact of glycemic control, health insurance status, management self-efficacy, level of knowledge, and medication beliefs on improving insulin medication adherence in patients with type 2 diabetes mellitus. Targeted pharmaceutical intervention can enhance medication adherence, improve glucose control, and promote rational insulin use. This trial is registered with ChiCTR2300074444.

Development and Validation of USM-Insulin Adherence Module for Patients with Type 2 Diabetes Mellitus.

Many patients with type 2 diabetes mellitus (T2DM) do not achieve the desired glycaemic control despite being treated with insulin. Studies found this due to an improper understanding of insulin function, its intensification process and patients' negative perspective on insulin. We developed an education module to enhance adherence to insulin therapy. This study applied a mixed design. It was conducted in three phases: i) Phase I: literature search and focus group discussions (FGDs), ii) Phase II: module development and iii) Phase III: content and face validation of Universiti Sains Malaysia-Insulin Adherence Module (USM-IAM). FGDs were used to gather patients' opinions. All researchers repeatedly discussed about the module content and arrangement, the words and images used, and the grammar in producing the final draft. Specialists and target audience performed content and face validation of the module. Thirty-six participants were involved in the FGDs. Data saturation was achieved at the 4th FGD. Three themes emerged from qualitative data analysis and were incorporated into the module. USM-IAM was finalised with five units. The content validity index (CVI) was 0.92, while face validity agreements were between 86% and 97%. The CVI and face agreement for USM-IAM exceed the cut-off point for a sound module. It has good potential to be used as a resource for educating patients in enhancing insulin adherence.

Analysis of adherence and factors affecting insulin therapy outcomes in outpatients with Diabetes Mellitus

Background: Insulin is an effective diabetes treatment for outpatients with Diabetes Mellitus (DM) to maximize medication therapy. However, the level of insulin adherence is still low. This study aims to analyze adherence, glycemic control, and factors that influence the achievement of insulin therapy in Type 2 Diabetes Mellitus (T2DM) outpatients. Methods: This study was a cross-sectional study conducted on T2DM outpatients. Adherence to Refills and Medications Scale (ARMS) and Diabetes Knowledge Questionnaire (DKQ) were used to assess patients’ adherence and knowledge of insulin use. Multiple logistic regression tests were carried out to measure the effect of factors on adherence and insulin therapy outcomes. Results: Of the 141 patients adherence to insulin treatment was found to be 33.3%. Patients who achieved glycemic control assessed by Glycosylated Haemoglobin (HbA1c), Fasting Blood Glucose (FBG), and Two hours of Postprandial Blood Glucose (2hPPBG) were 36.2%, 39%, and 43.3%. The duration of insulin use had a significant effect on adherence (p-value 0.013) and 2hPPBG target (p-value 0,049), while other factors had no significance. Conclusion: Adherence to insulin therapy and glycemic control targets were found to be low. The duration of insulin use was associated with medication adherence and insulin therapy outcomes.

The impact of a statewide insulin copay cap policy for insured patients with diabetes in Utah.

Insulin affordability is a huge concern for patients with diabetes in the United States. On March 30, 2020, Utah signed House Bill 207 into law, aimed at capping copayments for insulin at $30 for a 30-day supply. The bill was enacted on January 1, 2021. To assess patient basal insulin adherence, out-of-pocket costs, health plan costs, total costs on insulin, and hemoglobin A1c (A1c) in prepolicy vs postpolicy periods. This study is a retrospective analysis using data from a regional health plan in Utah from October 1, 2019, to September 30, 2021. Inclusion criteria were fully enrolled members of all ages, under commercial insurance, with at least 1 fill for any type of insulin in both the preperiod and the postperiod. Adherence was measured by proportion of days covered (PDC). Paired t-tests and Wilcoxon sign rank tests were conducted to compare the health and economic outcomes. Out of 24,150 commercially insured individuals, a total of 244 patients were included. Across all 244 patients, there was a significant decline in monthly median out-of-pocket costs of insulin by 58.5% (P < 0.001), whereas the monthly median health plan costs of insulin increased by 22.0% (P < 0.001). The total monthly costs of insulin (the sum of out-of-pocket and health plan costs) were unchanged (P = 0.115). Only 74 patients with enough basal insulin fills in both periods were included in the analysis for PDC changes. PDC change was not statistically significant (P = 0.43). Among the 74 patients with PDC calculations, 29 patients had A1c recorded in both periods. The change in A1c was not statistically significant (P = 0.23). An insulin copayment max of $30 in Utah demonstrated lower patient out-of-pocket costs, subsidized by the health plan. PDC did not change, and HbA1c did not improve. An assessment of a longer period and on a larger population is needed.

A Three-Step Data-Driven Methodology to Assess Adherence to Basal Insulin Therapy in Patients With Insulin-Treated Type 2 Diabetes.

While health care providers (HCPs) are generally aware of the challenges concerning insulin adherence in adults with insulin-treated type 2 diabetes (T2D), data guiding identification of insulin nonadherence and understanding of injection patterns have been limited. Hence, the aim of this study was to examine detailed injection data and provide methods for assessing different aspects of basal insulin adherence. Basal insulin data recorded by a connected insulin pen and prescribed doses were collected from 103 insulin-treated patients (aged ≥18 years) with T2D from an ongoing clinical trial (NCT04981808). We categorized the data and analyzed distributions of correct doses, increased doses, reduced doses, and missed doses to quantify adherence. We developed a three-step model evaluating three aspects of adherence (overall adherence, adherence distribution, and dose deviation) offering HCPs a comprehensive assessment approach. We used data from a connected insulin pen to exemplify the use of the three-step model to evaluate overall, adherence, adherence distribution, and dose deviation using patient cases. The methodology provides HCPs with detailed access to previously limited clinical data on insulin administration, making it possible to identify specific nonadherence behavior which will guide patient-HCP discussions and potentially provide valuable insights for tailoring the most appropriate forms of support.

The Development and Validation of The Indonesian Insulin Adherence Influence Factor Questionnaire (IIAIFQ)

Background: Type 2 diabetes mellitus (DMT2) is a metabolic disease due to abnormalities in insulin secretion. Insulin is one of DMT2 therapy. Objective: This study aimed to validate a modified the insulin adherence influence factor questionnaire based on the health belief model (HBM) among Indonesian patients with DMT2. Methods: The Indonesian insulin adherence influence factor questionnaire (IIAIFQ) was developed based on modified some literature reviews and internal expert discussions. The study included 30 participants aged ≥ 17 y.o years old who had been taking insulin in the previous two months. The questionnaire consists of seven dimensions to measure HBM : perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self-efficacy, cues to action and insulin adherence. Results: The construct validity test showed that of the 34 question items in the questionnaire, 10 items were invalid, 24 others were demonstrated valid based on the Pearson Correlation (&gt;r table 0.361; p&lt;0.05; loading factor &gt; 0.5). Furthermore, 24 valid items were tested for reliability at a significance level of 0.05, and the results showed that each size had a Cronbach's Alpa &gt; 0.6 with an overall score was 0.858, indicating that all domains in the questionnaire were reliable. Conclusion: IIAIFQ based The HBM theory is a valid and reliable instrument for assessing insulin adherence in diabetes mellitus patients.

Machine learning-based prediction of medication refill adherence among first-time insulin users with type 2 diabetes

AimsThe prevalence of Type 2 Diabetes Mellitus (T2DM) is projected to be 7 % in 2030. Despite its need for long-term diabetes care, the adherence rate of injectable medications such as insulin is around 60 %, lower than the acceptable threshold of 80 %. This study aims to create classification models to predict insulin adherence among adult T2DM naïve insulin users. MethodsClinical data were extracted from Taipei Medical University Clinical Research Database (TMUCRD) from January 1st, 2004 to December 30th, 2020. A patient was regarded as adherent if his/her medication possession ratio (MPR) was at least 80 %. Seven domains of predictors were created, including demographics, baseline medications, baseline comorbidities, baseline laboratory data, healthcare resource utilization, index insulins, and the concomitant non-insulin T2DM medications. We built two Xgboost models for internal and external testing respectively. ResultsUsing a cohort of 4134 patients from Taiwan, our model achieved the Area Under the curve of the Receiver Operating Characteristic (AUROC) of the internal test was 0.782 and the AUROC of the external test was 0.771. the SHAP (SHapley Additive exPlanations) value showed that the number of prescribed medications, the number of outpatient visits, and laboratory data were predictive of future insulin adherence. ConclusionsThis is the first study to predict adherence among adult naïve insulin users. The developed model is a potential clinical decision support tool to identify possible non-adherent patients for healthcare providers to design individualized education plans.

Use of Voice-Based Conversational Artificial Intelligence for Basal Insulin Prescription Management Among Patients With Type 2 Diabetes

Optimizing insulin therapy for patients with type 2 diabetes can be challenging given the need for frequent dose adjustments. Most patients receive suboptimal doses and do not achieve glycemic control. To examine whether a voice-based conversational artificial intelligence (AI) application can help patients with type 2 diabetes titrate basal insulin at home to achieve rapid glycemic control. In this randomized clinical trial conducted at 4 primary care clinics at an academic medical center from March 1, 2021, to December 31, 2022, 32 adults with type 2 diabetes requiring initiation or adjustment of once-daily basal insulin were followed up for 8 weeks. Statistical analysis was performed from January to February 2023. Participants were randomized in a 1:1 ratio to receive basal insulin management with a voice-based conversational AI application or standard of care. Primary outcomes were time to optimal insulin dose (number of days needed to achieve glycemic control), insulin adherence, and change in composite survey scores measuring diabetes-related emotional distress and attitudes toward health technology and medication adherence. Secondary outcomes were glycemic control and glycemic improvement. Analysis was performed on an intent-to-treat basis. The study population included 32 patients (mean [SD] age, 55.1 [12.7] years; 19 women [59.4%]). Participants in the voice-based conversational AI group more quickly achieved optimal insulin dosing compared with the standard of care group (median, 15 days [IQR, 6-27 days] vs >56 days [IQR, >29.5 to >56 days]; a significant difference in time-to-event curves; P = .006) and had better insulin adherence (mean [SD], 82.9% [20.6%] vs 50.2% [43.0%]; difference, 32.7% [95% CI, 8.0%-57.4%]; P = .01). Participants in the voice-based conversational AI group were also more likely than those in the standard of care group to achieve glycemic control (13 of 16 [81.3%; 95% CI, 53.7%-95.0%] vs 4 of 16 [25.0%; 95% CI, 8.3%-52.6%]; difference, 56.3% [95% CI, 21.4%-91.1%]; P = .005) and glycemic improvement, as measured by change in mean (SD) fasting blood glucose level (-45.9 [45.9] mg/dL [95% CI, -70.4 to -21.5 mg/dL] vs 23.0 [54.7] mg/dL [95% CI, -8.6 to 54.6 mg/dL]; difference, -68.9 mg/dL [95% CI, -107.1 to -30.7 mg/dL]; P = .001). There was a significant difference between the voice-based conversational AI group and the standard of care group in change in composite survey scores measuring diabetes-related emotional distress (-1.9 points vs 1.7 points; difference, -3.6 points [95% CI, -6.8 to -0.4 points]; P = .03). In this randomized clinical trial of a voice-based conversational AI application that provided autonomous basal insulin management for adults with type 2 diabetes, participants in the AI group had significantly improved time to optimal insulin dose, insulin adherence, glycemic control, and diabetes-related emotional distress compared with those in the standard of care group. These findings suggest that voice-based digital health solutions can be useful for medication titration. ClinicalTrials.gov Identifier: NCT05081011.

Factors associated with Adherence to Insulin Self-Administration among Children and Adolescents with Type 1 DM in Iraq

Abstract Adolescents and children with type 1 diabetes have been reported to have challenges regarding adherence to treatment regimens compared with other age groups with diabetes. The study aimed to determine the level of commitment and investigate the effects of different factors on insulin adherence in type 1 diabetes patients in Iraq. This cross-sectional study included face-to-face interview questionnaires with caregivers of children and adolescents. Interviews were conducted in the Specialized Center of Endocrinology and Diabetes in Nasiriyah City, Iraq, from October 4, 2022, to March 30, 2023. The adherence questionnaire consisted of two sections; each consisted of five questions, including insulin and blood glucose recommendations. Blood samples were obtained from the patient to determine fasting blood glucose (FBG) and glycated hemoglobin (HBA1c)—results: 180 patients (86 males and 94 females) with type 1 DM. The mean age, weight, and disease duration were 10.75 (4.36) years, 36.30 (16.41) kg, and 6.24 (3.70) years, respectively. They had uncontrolled blood glucose (208.42 95.0 mg/dl) and HBA1c (9.90 2.85%). The patients (52.2%) were girls with primary school qualifications (43.3%). Most of the caregivers (parents and guardians) were either illiterate (30.6%) or had completed primary school (33.9%). In addition, the patient's families (43.9%) had low income (0.5 million ID cards). Therefore, most patients (60%) did not visit a doctor regularly or check their blood glucose. Adherence in the studied population could be higher. Focusing on raising their patients' awareness is pivotal to enhancing their medication adherence to reduce their short- and long-term diabetic complications, improve blood glucose control, and improve clinical outcomes. Keywords: Diabetes, Adherence, Insulin self-medication, Iraqi patients.

ASSOCIATION BETWEEN INSULIN THERAPY ADHERENCE AND GLYCATED HAEMOGLOBIN (HbA1c) AMONG PATIENTS WITH TYPE 2 DIABETES MELLITUS ATTENDING A COMMUNITY HEALTH CLINIC

Insulin therapy is a recommended treatment for diabetes mellitus. Despite knowing insulin is one of the recommended treatments for glycemic control, adherence to insulin therapy still plays the main challenge in achieving good control of glycated haemoglobin (HbA1c). This study aims to determine adherence and compare HbA1c levels before and after six months of insulin therapy among type 2 diabetes patients (T2DM). This cross-sectional study was conducted among 300 participants with T2DM at Sungai Buloh community health clinic, Selangor. A self-administered questionnaire Morisky Insulin Adherence Scale (MIAS), was used to measure the study adherence variable. Data were analysed using a statistical package for the social science (SPSS) version 23. 11 (3.7%) of respondents had good adherence,109 (36.3%) had moderate adherence, and 180 (60%) were poor adherence. The mean HbA1C at baseline is 9.654 mmol/L and reduced to 9.194 mmol/L after six months of insulin therapy. Education shows an association towards adherence level with p-value = 0.004 and significantly found an association between HbA1c and insulin adherence with p &lt; 0.05. The study found that most respondents have poor adherence to insulin therapy. Therefore, essential to highlight adherence issued to achieve good glycaemic control.

178-OR: Better Glycemic Control with Once-Weekly Insulin Icodec vs. Once-Daily Insulin Degludec in Insulin-Naïve Type 2 Diabetes (ONWARDS 3)

Efficacy and safety of once-weekly insulin icodec (icodec) vs once-daily insulin degludec (degludec) in insulin-naïve adults with T2D were examined in ONWARDS 3 (NCT04795531), a 26-week, randomized, double blind, double dummy, treat-to-target, phase 3a trial. Participants (n=588) were randomized 1:1 to icodec or degludec. Key outcomes are shown in the table. The primary endpoint was A1C change from baseline (BL) to week 26. Estimated mean A1C change was greater with icodec (−1.57%; BL: 8.55%) vs degludec (−1.36%; BL: 8.48%); estimated treatment difference −0.21%-points (95% CI −0.34, −0.08), confirming non-inferiority (p&amp;lt;0.0001) and superiority (p=0.0016). Level 2 or 3 hypoglycemia rates were numerically but not statistically significantly higher with icodec vs degludec in the on-treatment period. Odds of achieving A1C &amp;lt;7% without level 2 or 3 hypoglycemia were statistically significantly higher with icodec vs degludec. There were no significant differences in weekly insulin dose from week 24 to 26 or body weight change from BL to week 26 between arms. No unexpected safety findings were observed. Overall, once-weekly icodec demonstrated superior A1C reduction vs once-daily degludec with low level 2 or 3 hypoglycemia rates in both arms. Icodec may facilitate insulin treatment acceptance and adherence by reducing basal insulin injections from ≥365 to 52 per year. Disclosure I.Lingvay: Advisory Panel; Novo Nordisk A/S, Lilly Diabetes, Boehringer-Ingelheim, Sanofi, Consultant; Carmot Therapeutics, Inc., Merck Sharp &amp; Dohme Corp., Janssen Scientific Affairs, LLC, Pfizer Inc., Intercept, Intarcia, Valeritas, TargetRWE, Shionogi, Zealand Pharma, Structure, Bayer, Research Support; Novo Nordisk A/S, Boehringer-Ingelheim. M.Asong: Employee; Novo Nordisk. C.Desouza: Advisory Panel; Novo Nordisk A/S, Bayer Inc., Consultant; Asahi Kasei Corporation, Research Support; Eli Lilly and Company. P.Gourdy: Advisory Panel; Novo Nordisk, Eli Lilly and Company, Sanofi, Bayer Inc., Merck Sharp &amp; Dohme Corp., Novartis, Intercept Pharmaceuticals, Inc., Research Support; Novo Nordisk, Speaker's Bureau; Novo Nordisk, Eli Lilly and Company, Sanofi, Abbott, AstraZeneca, Boehringer-Ingelheim. S.Kar: None. A.G.Vianna: Advisory Panel; AstraZeneca, Board Member; Abbott Diabetes, Novo Nordisk, Medtronic, Research Support; Novo Nordisk, Anji Pharmaceuticals, Lilly, Speaker's Bureau; AstraZeneca, Novo Nordisk, Medtronic. T.Vilsbøll: Consultant; AstraZeneca, Boehringer Ingelheim Inc., Gilead Sciences, Inc., Eli Lilly and Company, Mundipharma, Merck &amp; Co., Inc., Novo Nordisk A/S, Sanofi, Sun Pharmaceutical Industries Ltd., Bristol-Myers Squibb Company. S.M.Vinther: Employee; Novo Nordisk. Y.Mu: Speaker's Bureau; Abbott Diabetes, Boehringer Ingelheim Inc., Novo Nordisk (China), Sanifit. Funding Novo Nordisk A/S

PCR2 The Magnitude of the Association between Insulin Adherence Based on Prescription Fill Rate Measures and Glycemic Control: A Systematic Review and Meta-Analysis

Despite studies measuring association of insulin adherence and glycemic control in type 2 diabetes mellitus (T2DM), the magnitude and significance of association remains unclear. This study aims to summarize evidence on the association between insulin adherence and glycemic control in adults with T2DM.