Frequency of non-communicable diseases in people 50 years of age and older receiving HIV care in Latin America
Bibliographic record
Abstract
A growing population of older adults with HIV will increase demands on HIV-related healthcare. Nearly a quarter of people receiving care for HIV in Latin America are currently 50 years or older, yet little is known about the frequency of comorbidities in this population. We estimated the prevalence and incidence of non-communicable diseases (NCDs) among people 50 years of age or older (≥50yo) receiving HIV care during 2000-2015 in six centers affiliated with the Caribbean, Central and South American network for HIV epidemiology (CCASAnet).We estimated the annual prevalence, and overall prevalence and incidence of cardiovascular diseases, diabetes, hypertension, dyslipidemia, psychiatric disorders, chronic liver and renal diseases, and non-AIDS-defining cancers, and multimorbidity (more than one NCD) of people ≥50yo receiving care for HIV. Analyses were performed according to age at enrollment into HIV care (<50yo and ≥50yo).We included 3,415 patients ≥50yo, of whom 1,487(43%) were enrolled at age ≥50 years. The annual prevalence of NCDs increased from 32% to 68% and multimorbidity from 30% to 40% during 2000-2015. At the last registered visit, 53% of patients enrolled <50yo and 50% of those enrolled ≥50yo had at least one NCD. Most common NCDs at the last visit in each age-group at enrollment were dyslipidemia (36% in <50yo and 28% in ≥50yo), hypertension (17% and 18%), psychiatric disorders (15% and 10%), and diabetes (11% and 12%).The prevalence of NCDs and multimorbidity in people ≥50 years receiving care for HIV in CCASAnet centers in Latin America increased substantially in the last 15 years. Our results make evident the need of planning for provision of complex, primary care for aging adults living with HIV.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".