Type 1 diabetes outpatient care and treatment effectiveness during COVID-19: A single-center cohort study

Comparative Analysis of PEG-Free and PEG-Based Self-Emulsifying Drug Delivery Systems for Enhanced Oral Bioavailability of Therapeutic (Poly) Peptides

This study aims to compare the potential of Polyethylene glycol (PEG-free and PEG-based self-emulsifying drug delivery systems (SEDDS) for the oral administration of insulin glargine (IG). Hydrophobic ion pairs (HIPs) of IG are formed using various counterions. HIPs are assessed for log P octanol/water and dissociation behavior. They are incorporated into SEDDS based on polyglycerol (PG) and zwitterionic surfactant (ZW) using response surface methodology and compared to conventional PEG-SEDDS in size, stability, and log D SEDDS/release medium . Oral IG bioavailability in PG/ZW-SEDDS and PEG-SEDDS is evaluated in rats. Among the various counterions studied, IG-BIS (bis(isotridecyl)sulfosuccinate) HIPs demonstrated the highest log P and an improved dissociation profile. PG/ZW-SEDDS and PEG-SEDDS have similar ≈40 nm sizes and are stable over 24 h. Both formulations have log D > 4 in water and >2 in 50 mM phosphate buffer pH 6.8. PG/ZW-SEDDS yielded an oral bioavailability of 2.13 ± 0.66% for IG, while the employment of PEG-SEDDS resulted in an oral bioavailability of 1.15 ± 0.35%. This study highlights the prospective utilization of PEG-free SEDDS involving the concurrent application of PG and ZW surfactants, an alternative to conventional PEG surfactants, for improved oral therapeutic (poly) peptide delivery.

Factors Influencing the Behavioral Intentions and Use Behaviors of Telemedicine in Patients With Diabetes: Web-Based Survey Study

BACKGROUND

Telemedicine has great potential for diabetes management. The COVID-19 pandemic has boosted the development of telemedicine. However, the factors influencing the behavioral intentions to use and use behaviors of telemedicine in patients with diabetes in China are not clear.

OBJECTIVE

We aimed to understand the determinants of behavioral intention to use telemedicine based on an extended Unified Theory of Acceptance and Use of Technology model and to identify demographic factors associated with telemedicine use in patients with diabetes in China.

METHODS

Patients with diabetes who are aged ≥18 years were surveyed from February 1 to February 7, 2023. We distributed the survey link in 3 WeChat groups including a total of 988 patients with diabetes from the outpatient department or patients discharged from Changsha Central Hospital. Structural equation modeling was used to understand the determinants of behavioral intention. A multivariate logistic regression analysis was used to identify the demographic factors associated with telemedicine use.

RESULTS

In total, 514 questionnaires were collected. Of the respondents, 186 (36.2%) were diagnosed with COVID-19. The measurement model showed acceptable reliability, convergent validity, discriminant validity, and data fit indices. The model explained 63.8% of the variance in behavioral intention. Social influence, performance expectancy, and facilitating conditions positively influenced behavioral intention (β=.463, P<.001; β=.153, P=.02; and β=.257, P=.004, respectively). Perceived susceptibility, perceived severity, and effort expectancy had no significant impact on behavioral intention (all P>.05). The overall use of telemedicine was 20.6% (104/514). After adjusting for the behavioral intention score, the multivariate regression analysis showed that age, education, and family income were associated with telemedicine use. Telemedicine use was higher in the 40 to 59 years and 18 to 39 years age groups than in the ≥60 years age group (odds ratio [OR] 4.35, 95% CI 1.84-10.29, P=.001; OR 9.20, 95% CI 3.40-24.88, P<.001, respectively). Telemedicine use was higher in the senior high school and the university and more groups than in junior high school education and less group (OR 2.45, 95% CI 1.05-5.73, P=.04; OR 2.63, 95% CI 1.11-6.23, P=.03, respectively). Patients with a higher family income used telemedicine more often than the patients who had an annual family income ≤¥10,000 (CNY ¥1=US $0.1398; ¥10,000-¥50,000 group: OR 3.90, 95% CI 1.21-12.51, P=.02; ¥50,000-¥100,000 group: OR 3.91, 95% CI 1.19-12.79, P=.02; >¥100,000 group: OR 4.63, 95% CI 1.41-15.27, P=.01).

CONCLUSIONS

Social influence, performance expectancy, and facilitating conditions positively affected the behavioral intention of patients with diabetes to use telemedicine. Young patients, highly educated patients, and patients with high family income use telemedicine more often. Promoting behavioral intention and paying special attention to the needs of older adult patients, patients with low income, and patients with low levels of education are needed to encourage telemedicine use.