Health-related quality of life in elderly diabetic outpatients in Vietnam
Bibliographic record
Abstract
BACKGROUND: Health-related quality of life (HRQoL) is an important indicator for designing care and treatment services for patients with diabetes. This is especially true given its rapid increase among the elderly population in Vietnam. HRQoL data in elderly diabetic Vietnamese are currently limited. This study aimed to 1) measure the HRQoL of elderly patients with type 2 diabetes (T2DM) in Vietnam and 2) identify related factors and their relationship with HRQoL. PATIENTS AND METHODS: A cross-sectional study was conducted. We recruited 171 patients aged ≥60 years with T2DM at the Outpatient Department, National Geriatric Hospital from June to November 2015. Patients were asked to evaluate their health status using the EuroQol Five Dimensions Three Levels (EQ-5D-3L) and the Visual Analog Scale (VAS). Sociodemographic, diabetic treatment, and management characteristics were collected. Multivariate Tobit regression was used to determine which factors were associated with HRQoL, and the strength of this relationship. RESULTS: Patients reported some problems in all areas of the EQ-5D: pain/discomfort (50.9%), mobility (33.3%), anxiety/depression (24.0%), usual activities (21.1%), and self-care (10.5%). The mean EQ-5D index score was 0.80 (SD=0.20), and the mean EQ-VAS was 57.5 (SD=14.4). Patients who were male, lived in an urban area, could afford treatment, were taking fewer medications, and monitored blood pressure often (1-4 times a week) had a higher EQ-5D index when compared to other groups. Meanwhile, a longer duration of diabetes and older age were negatively associated with the EQ-5D index. Patients with any comorbidity had lower VAS scores than their counterparts. CONCLUSION: The presence of diabetes and comorbidity were responsible for a significant decrease in HRQoL. Screening and identifying health problems, providing prompt treatment, and facilitating self-management among patients have the potential to increase diabetic patients' HRQoL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".