The projected prevalence of comorbidities and multimorbidity in people with HIV in the United States through the year 2030
Bibliographic record
Abstract
ABSTRACT Importance Estimating the medical complexity of people aging with HIV can inform clinical programs and policy to meet future healthcare needs. Objective To project the prevalence of comorbidities and multimorbidity among people with HIV (PWH) using antiretroviral therapy (ART) in the US through 2030. Design Agent-based simulation model Setting HIV clinics in the United States in the recent past (2020) and near future (2030) Participants In 2020, 674,531 PWH were using ART; 9% were men and 4% women with history of injection drug use; 60% were men who have sex with men (MSM); 8% were heterosexual men and 19% heterosexual women; 44% were non-Hispanic Black/African American (Black); 32% were non-Hispanic White (White); and 23% were Hispanic. Exposure(s) Demographic and HIV acquisition risk subgroups Main Outcomes and Measures Projected prevalence of anxiety, depression, stage ≥3 chronic kidney disease (CKD), dyslipidemia, diabetes, hypertension, cancer, end-stage liver disease (ESLD), myocardial infarction (MI), and multimorbidity (≥2 mental or physical comorbidities, other than HIV). Results We projected 914,738 PWH using ART in the US in 2030. Multimorbidity increased from 58% in 2020 to 63% in 2030. The prevalence of depression and/or anxiety was high and increased from 60% in 2020 to 64% in 2030. Hypertension and dyslipidemia decreased, diabetes and CKD increased, MI increased steeply, but there was little change in cancer and ESLD. Among Black women with history of injection drug use (oldest demographic subgroup in 2030), CKD, anxiety, hypertension, and depression were most prevalent and 93% were multimorbid. Among Black MSM (youngest demographic subgroup in 2030), depression was highly prevalent, followed by hypertension and 48% were multimorbid. Comparatively, 67% of White MSM were multimorbid in 2030 (median age in 2030=59 years) and anxiety, depression, dyslipidemia, CKD, and hypertension were highly prevalent. Conclusion and relevance The distribution of multimorbidity will continue to differ by race/ethnicity, gender, and HIV acquisition risk subgroups, and be influenced by age and risk factor distributions that reflect the impact of social disparities of the health on women, people of color, and people who use drugs. HIV clinical care models and funding are urgently required to meet the healthcare needs of people with HIV in the next decade. KEY POINTS Question How will the prevalence of multimorbidity change among people with HIV (PWH) using antiretroviral therapy in the US from 2020 to 2030? Findings In this agent-based simulation study using data from the NA-ACCORD and the CDC, multimorbidity (≥2 mental/physical comorbidities other than HIV) will increase from 58% in 2020 to 63% in 2030. The composition of comorbidities among multimorbid PWH vary by race/ethnicity, gender, and HIV acquisition risk group. Meaning HIV clinical programs and policy makers must act now to identify resources and care models to meet the increasingly complex medical needs of PWH over time, particularly mental healthcare needs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".