Weight Change and the Association with Adherence and Persistence to Diabetes Therapy: A Narrative Review

Determinants of adherence to obesity medication: A narrative review

The increasing prevalence of obesity, complex nature of this chronic disease, and risks of developing obesity-related comorbidities outline the need for sustainable and effective management for people living with obesity. In addition to behavioral interventions, obesity medications (OMs) are increasingly considered an integral part of management of people living with obesity. OM adherence is essential to achieve the health benefits of these medications. Adherence to medications, defined as the process by which patients take their medications as prescribed, is determined by a range of factors and can be broken down into phases: initiation, implementation, and persistence (the persistence phase includes discontinuation/stopping treatment). Obesity-specific challenges exist to optimize OM adherence, which may explain varying OM adherence compared with medication for other chronic diseases (diabetes, hypertension, dyslipidemia, and osteoporosis). However, lessons can be learned from other chronic diseases to improve OM adherence, for example from type 2 diabetes and hypertension. This review aims to provide practical guidance for identifying OM- and obesity-specific determinants of adherence and discusses adherence determinants per adherence phase and obesity management phase (weight gain, weight loss, and weight stabilization/regain). This practical guidance will assist with developing obesity-specific interventions to improve OM adherence. PRACTITIONER POINTS: OMs are increasingly considered as an integral part of obesity management; however, like with all chronic disease medications, low adherence to these medications is often observed, impacting their therapeutic effect. Adherence to obesity medication can be affected at any phase of obesity management (weight gain, weight loss, and weight stabilization/regain) so considering the disease phase can help identify potential reasons for low adherence. Future initiatives to improve adherence to obesity medication should be a key focus of discussions at each opportunity with healthcare professionals, including thorough evaluation and targeted education, all in a supportive and stigma-free manner.

Comparative Effects of Randomized Second-line Therapy for Type 2 Diabetes on a Composite Outcome Incorporating Glycemic Control, Body Weight, and Hypoglycemia: An Analysis of the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE)

OBJECTIVE

In Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE) (5,047 participants, mean follow-up 5.0 years), differences in glycemic control were demonstrated over time among four randomized therapies added to metformin. Weight gain and hypoglycemia are also important outcomes for people with type 2 diabetes. We compared the effects of the four randomized GRADE medications on a composite outcome incorporating glycemic deterioration, weight gain, and hypoglycemia.

RESEARCH DESIGN AND METHODS

The composite outcome was time to first occurrence of any of the following: HbA1c >7.5%, confirmed; ≥5% weight gain; or severe or recurrent nonsevere hypoglycemia. Secondary analyses included examination of individual components of the composite outcome, subgroup effects and potential mediators, and treatment satisfaction. Cumulative incidence was estimated with the Kaplan-Meier estimator. Cox proportional hazards models were used to assess pairwise group differences in risk of an outcome.

RESULTS

Risk of reaching the composite outcome (events per 100 participants per treatment year [PTYs]) was lowest with liraglutide (19 per 100 PTYs) followed by sitagliptin (26 per 100 PTYs), glargine (29 per 100 PTYs), and glimepiride (40 per 100 PTYs); all pairwise comparisons were statistically significant. The order was the same for risk of weight gain and hypoglycemia, but risk of glycemic deterioration was lowest with glargine, followed by liraglutide, glimepiride, and sitagliptin. No significant heterogeneity in risk of composite outcome was detected across prespecified covariates. Participants who reached the composite outcome had modestly but significantly lower treatment satisfaction.

CONCLUSIONS

Among participants treated with common second-line drug classes for type 2 diabetes, the liraglutide group had the lowest and glimepiride the highest risk of reaching a composite outcome encompassing glycemic deterioration, weight gain, and hypoglycemia. These findings may inform decision-making regarding type 2 diabetes therapy.

Mediating the Role of Perceived Social Support Between Frailty and Self-Perceived Burden in Elderly Patients with Diabetes

Objective

To explore the mediating effects of perceived social support between frailty and self-perceived burden (SPB) in elderly patients with diabetes and to provide a theoretical basis for reducing that burden.

Methods

A total of 169 elderly patients with diabetes who were hospitalised in the endocrinology department of a third-class hospital in Wuxi between May 2020 and July 2022 were included in this study using the convenience sampling method. Patients were assessed by the general information questionnaire, the Chinese version of the Tilburg frailty inventory (TFI), the Self-Perceived Burden Scale (SPBS) and the Perceived Social Support Scale (PSSS). The SPSS 22.0 software was used for Pearson's correlation analysis and multiple linear regression analysis. Model four of the SPSS PROCESS was used for mediating the effect analysis.

Results

The SPBS of elderly patients with diabetes was positively correlated with the TFI (P < 0.01) and negatively correlated with the PSSS (P < 0.01). The results of the Bootstrap test showed that the mediating effect of the PSSS on the relationship between the TFI and the SPBS in elderly patients with diabetes was 0.296 (95% CI: 0.007, 0.066), and the mesomeric effect accounted for 17.3% of the total effect.

Conclusion

The debilitation of elderly patients with diabetes can be reduced by decreasing their SPB through perceived social support. This can be achieved through comprehensive interventions by nurses.

Adherence to CPAP Treatment and the Risk of Recurrent Cardiovascular Events: A Meta-Analysis

Importance

The effect of continuous positive airway pressure (CPAP) on secondary cardiovascular disease prevention is highly debated.

Objective

To assess the effect of CPAP treatment for obstructive sleep apnea (OSA) on the risk of adverse cardiovascular events in randomized clinical trials.

Data Sources

PubMed (MEDLINE), EMBASE, Current Controlled Trials: metaRegister of Controlled Trials, ISRCTN Registry, European Union clinical trials database, CENTRAL (Cochrane Central Register of Controlled Trials), and ClinicalTrials.gov databases were systematically searched through June 22, 2023.

Study Selection

For qualitative and individual participant data (IPD) meta-analysis, randomized clinical trials addressing the therapeutic effect of CPAP on cardiovascular outcomes and mortality in adults with cardiovascular disease and OSA were included.

Data Extraction and Synthesis

Two reviewers independently screened records, evaluated potentially eligible primary studies in full text, extracted data, and cross-checked errors. IPD were requested from authors of the selected studies (SAVE [NCT00738179], ISAACC [NCT01335087], and RICCADSA [NCT00519597]).

Main Outcomes and Measures

One-stage and 2-stage IPD meta-analyses were completed to estimate the effect of CPAP treatment on risk of recurrent major adverse cardiac and cerebrovascular events (MACCEs) using mixed-effect Cox regression models. Additionally, an on-treatment analysis with marginal structural Cox models using inverse probability of treatment weighting was fitted to assess the effect of good adherence to CPAP (≥4 hours per day).

Results

A total of 4186 individual participants were evaluated (82.1% men; mean [SD] body mass index, 28.9 [4.5]; mean [SD] age, 61.2 [8.7] years; mean [SD] apnea-hypopnea index, 31.2 [17] events per hour; 71% with hypertension; 50.1% receiving CPAP [mean {SD} adherence, 3.1 {2.4} hours per day]; 49.9% not receiving CPAP [usual care], mean [SD] follow-up, 3.25 [1.8] years). The main outcome was defined as the first MACCE, which was similar for the CPAP and no CPAP groups (hazard ratio, 1.01 [95% CI, 0.87-1.17]). However, an on-treatment analysis by marginal structural model revealed a reduced risk of MACCEs associated with good adherence to CPAP (hazard ratio, 0.69 [95% CI, 0.52-0.92]).

Conclusions and Relevance

Adherence to CPAP was associated with a reduced MACCE recurrence risk, suggesting that treatment adherence is a key factor in secondary cardiovascular prevention in patients with OSA.

Gait Analysis, Metabolic Parameters and Adherence to the Mediterranean Diet in Patients with Type 2 Diabetes Mellitus Compared with Healthy Controls: A Pilot Study

BACKGROUND AND PURPOSE

Patients with type 2 diabetes mellitus (T2DM) are prone to developing diabetic peripheral neuropathy (DPN) with an increased risk of injuries while walking, potentially leading to plantar ulcers. We aimed to assess the early gait changes in T2DM patients without clinical signs of DPN in comparison to age-matched healthy controls (HC).

SUBJECTS AND METHODS

One hundred T2DM patients (78 women, mean age: 66.4 ± 11.5 years) and 50 age-matched HC (34 women, mean age 62.1 ± 7.9 years) were evaluated with the PODOSmart® gait analysis device. Anthropometric and biochemical data, as well as dietary habits were collected for all participants. T2DM patients also completed the Diabetes Distress (DS) self-report validated questionnaire.

RESULTS

One patient was excluded from the study due to lack of recent biochemical data. Among the T2DM patients, 88.9% reported little or no DS and 11.1% moderate DS. The T2DM group had higher body mass index, waist circumference, systolic blood pressure, glycated hemoglobin A1c, sodium, white blood cell count, triglycerides and low-density lipoprotein cholesterol, but lower high-density lipoprotein cholesterol than HC (p < 0.05 for all comparisons). The MedDiet score was satisfactory in both groups (p > 0.05). Significant differences were found between the two study groups in gaitline heel off, propulsion speed, foot progression angle, time taligrade phase, stride length, walking speed, angle attack, oscillation speed, pronation-supination toe off and clearance.

CONCLUSIONS

The T2DM patients without self-reported DS or clinical signs of DPN may exhibit significant differences in several gait parameters analyzed with PODOSmart®. Whether gait analysis can be used as an early diagnostic tool of T2DM complications should be further explored.

Treatment-Related Attributes of Diabetes Therapies and How People with Type 2 Diabetes Report Their Impact on Indicators of Medication-Taking Behaviors

Purpose

Understanding the treatment-related attributes influencing medication-taking behaviors in people with type 2 diabetes (T2D) is important for delivery of patient-centered care. This review aimed to identify and summarize studies in which people with T2D (PwD) directly indicated the treatment-related attributes associated with medication-taking behaviors or intentions.

Materials and Methods

EMBASE and PubMed were searched for studies (Jan 2005-May 2021) reporting the link between PwD-expressed diabetes treatment-related attributes and the decision to initiate, adhere to, or discontinue a T2D medication. Eligible studies reported attributes associated with oral antidiabetes drugs or injectables (not insulin). Studies not explicitly exploring the link between attributes and indicators of behaviors (eg most discrete-choice experiments [DCE] and those interrogating electronic medical records or claims databases) were excluded, as were studies where the link between attribute and behavior came from anyone but the PwD.

Results

Of the 6464 studies identified, 16 were included. Studies were conducted across multiple countries; the USA was most represented (n = 8 studies). The impact of treatment attributes was described on indicators of initiation (n = 3), adherence (n = 12), and discontinuation (n = 4). Some studies evaluated multiple behaviors. PwD perspectives were solicited by structured questionnaires (n = 10), qualitative approaches (n = 4), or DCE explicitly exploring the link to medication-taking behaviors (n = 2). Closed- (n = 9) and open-ended questions (n = 7) were employed. Across studies, several factors including glycemic efficacy (n = 9), weight change (n = 9), dosing frequency (n = 9), hypoglycemia (n = 8), gastrointestinal adverse events (n = 8), regimen complexity (n = 6), route of administration (n = 3), and cardiovascular risk (n = 1) were reported as influencing behaviors, being motivators or barriers to initiation, adherence, or discontinuation.

Conclusion

Several attributes influence how PwD take their medications. Insights gained directly from PwD have the potential to assist stakeholders in making more informed, patient-centered, treatment decisions, thus choosing and managing medications that PwD are comfortable initiating and persisting with over the longer term.