All-cause and Cause-specific Mortality in People With HIV in Italy in 1997–2022: Data From the Icona Cohort
Bibliographic record
Abstract
Background: Understanding the evolution and dynamics of deaths in people with HIV (PWH) is crucial to tailor interventions aiming at improving PWH long-term well-being. We aimed to assess all-cause and cause-specific mortality in PWH in Italy. Methods: PWH enrolled before antiretroviral start from Icona cohort (78 Italian HIV clinics) between 1997 and 2021 (last observation December 2022) were included. Mortality was reported as incidence rate per 100 person-years of follow-up (PYFU). The mortality incidence rate according to calendar period was estimated by Poisson regression model. Results: Overall, 17,006 PWH were included of whom 1584 (9.31%) died. The highest mortality rates were observed during the earliest calendar periods, with 2.67 (95% CI: 2.19-3.25) and 1.93 (95% CI: 1.67-2.22) deaths per 100 PYFU in 1997-1998 and 1999-2001, respectively. After 2010, mortality rates fell below 1 per 100 PYFU, reaching 0.74 (95% CI: 0.65-0.84) and 0.71 (95% CI: 0.63-0.80) in 2017-2019 and 2020-2022, respectively. A significant drop was observed for AIDS-related mortality in the first two periods from 1.45 (95% CI: 1.11-1.90) in 1997-1998 to 0.78 (95% CI: 0.62-0.97) deaths per 100 PYFU in 1999-2001. AIDS-related mortality continued to decrease in the subsequent years, with the lowest rate observed in the last two calendar periods: 0.10 (95% CI: 0.07-0.14) deaths per 100 person-years in 2017-2019 and 0.10 (95% CI: 0.08-0.15) deaths per 100 person-years in 2020-2022. Conclusions: All-cause mortality in PWH in Italy significantly decreased over time, mainly for a reduction in AIDS-related mortality.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".