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Record W3120228623 · doi:10.2196/25122

Effectiveness of the Family Portal Function on the Lilly Connected Care Program (LCCP) for Patients With Type 2 Diabetes: Retrospective Cohort Study With Propensity Score Matching

2021· article· en· W3120228623 on OpenAlexvenueno aff
Yiyu Zhang, Chaoyuan Liu, Shuoming Luo, Jin Huang, Yuxin Yang, Xiao Ma, Xia Li, Zhiguang Zhou

Bibliographic record

VenueJMIR mhealth and uhealth · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaEli Lilly and Company
KeywordsMedicinePostprandialDiabetes mellitusGlycemicPropensity score matchingType 2 diabetesOdds ratioInternal medicineRetrospective cohort studyCohortDiabetes managementEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Diabetes is a major health concern worldwide. Family member engagement in diabetes self-management education programs can improve patients' diabetes management. However, there is limited evidence that the family portal on diabetes management apps is effective in the glycemic control of patients with diabetes. OBJECTIVE: We aimed to evaluate the effectiveness of family support through the family portal function on Lilly Connected Care Program (LCCP) platform. METHODS: This retrospective cohort study included patients with type 2 diabetes recruited to the LCCP platform from September 1, 2018, to August 31, 2019. Propensity score matching was used to match family (group A) and non-family (group B) portal use groups with similar baseline characteristics. The patients were followed up with for 12 weeks. The main objectives were differences in mean fasting blood glucose, proportion of patients achieving fasting blood glucose target <7mmol/L, mean postprandial blood glucose, proportion of patients achieving postprandial blood glucose target <10mmol/L, proportion of patients achieving both fasting blood glucose <7mmol/L and postprandial blood glucose <10mmol/L, self-monitoring of blood glucose frequency at week 12 and the number of diabetes education courses patients completed during the 12 weeks. Moreover, logistic regression analysis was used to explore the baseline factors which may be associated with the use of family portal, and odds ratios with 95% confidence intervals were calculated. RESULTS: A total of 6582 adult patients (aged ≥18 years) with type 2 diabetes who were receiving insulin therapy were enrolled in the study. Overall, 6.1% (402/6582) of the patients chose to engage their family members to use the family portal. Two groups of 394 patients were well-matched regarding baseline characteristics. After matching, mean fasting blood glucose and postprandial blood glucose at week 12 were significantly lower in group A than in group B (fasting blood glucose: 7.12 mmol/L, SD 1.70 vs 7.42 mmol/L, SD 1.88, respectively, P=.02; postprandial blood glucose: 8.56 mmol/L, SD 2.51 vs 9.10 mmol/L, SD 2.69, respectively, P=.002). When comparing group A to group B, the proportion of patients achieving both fasting blood glucose <7mmol and postprandial blood glucose <10mmol/L at week 12 (46.8% vs 39.4%, respectively, P=.04), self-monitoring of blood glucose frequency at week 12 (8.92 times per week, SD 6.77 vs 8.02 times per week, SD 5.97, respectively, P=.05) and number of diabetes education courses completed in 12 weeks (23.00, IQR9.00-38.00 vs 15.00, IQR 4.00-36.00, respectively, P<.001) was higher. Additionally, multivariate logistic regression analysis showed that higher age (OR=0.987, 95% CI 0.978-0.996, P=.006) and higher baseline fasting blood glucose (OR=0.914, 95% CI 0.859-0.972, P=.004) were correlated with less use of the family portal function, while increased baseline self-monitoring of blood glucose frequency (OR=1.022, 95% CI 1.012-1.032], P<.001) as well as increased education courses (OR=1.026, 95% CI 1.015-1.036, P<.001) were associated with more use of the family portal function. CONCLUSIONS: Family support through the LCCP family portal is effective for glycemic control and self-management behavior improvement in type 2 diabetes patients.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.374
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2021
Admission routes1
Has abstractyes

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