Demographic, Clinical, and Quality of Life Profiles of Older People With Diabetes During the COVID-19 Pandemic: Cross-Sectional Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Diabetes mellitus, one of the main diseases that affects the Brazilian population older than 60 years, is defined as a divergent group of metabolic disorders that present a high level of glycemia (hyperglycemia), causing damage to various organs and systems of the body, including the heart, kidneys, eyes, and nervous system. It is believed that in 2025, in Brazil alone, there will be more than 18.5 million individuals diagnosed with diabetes mellitus. Therefore, it is important to know the individuals' quality of life in the context of life and culture. OBJECTIVE: This study aimed to assess the demographic, clinical, and quality of life profiles of older adults with diabetes during the COVID-19 pandemic in a university hospital complex in the northern Amazon region. METHODS: We conducted a cross-sectional, exploratory, noninterventional, descriptive, and analytical study using a nonrandom sample of 54 older people diagnosed with diabetes mellitus at the geriatrics outpatient clinic of the medium and high complexity university hospital in the western Brazilian Amazon between 2020 and 2022. We used 3 instruments, namely, a sociodemographic questionnaire, a clinical conditions questionnaire, and Diabetes-39. Qualitative data were described using absolute and relative frequencies. The Kolmogorov-Smirnov normality test was applied, and the z test was used for inferential analysis. SPSS software (version 27) was used for data analysis, and the significance level was 5%. RESULTS: Of the 54 interviewees, the majority were women, married, retired, and had a good quality of life. Of these, 48.1% (n=26) were infected by COVID-19, 61.5% (n=16) of whom progressed to long COVID, presenting with fatigue or muscle weakness. As for the quality of life, the "social overload" (P<.001) and "sexual functioning" (P<.001) dimensions had with low scores compared to the "energy and mobility" (P=.005), "diabetes control" (P<.001), and "anxiety and worry" (P<.001) dimensions. Quality of life was negatively impacted in the "anxiety and worry" dimension. Among those affected by COVID-19, most progressed to long COVID; however, there was a lack of data on this theme in the population of older people with diabetes. CONCLUSIONS: The majority of interviewees progressed to long COVID, with their quality of life negatively impacted in the "anxiety and worry" dimension, reflecting that health actions prioritizing mental health should be implemented by health professionals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it