Incidence, mortality and lethality of immune reconstitution inflammatory syndrome in hiv- infected patients starting highly active antiretroviral therapy: systematic review and meta-analysis
Bibliographic record
Abstract
Background The Immune Reconstitution Inflammatory Syndrome (IRIS) is a relatively frequent complication in patients who start ART and it has, over all, not been consistently described before. We made a systematic review and meta-analysis to obtain its incidence and lethality. Methods We included retrospective and prospective cohorts that unspecifically evaluated IRIS in HIV-infected adults initiating HAART, with a minimum follow-up of 6 months. We searched LILACS, PUBMED, Cochrane Library, SCOPUS and Google Scholar databases, and assessed study quality with the Newcastle-Ottawa Scale (NOS). Rates were estimated with a 95% confidence interval using binomial distribution random-effects pooled model. Results We included 8,124 patients from 8 different countries. IRIS incidence ranged from 38‰ to 314‰ patients, with a 170‰ patients as pooled index. It was most common in patients with a baseline T CD4+ ≤100 cells/mm3 and from high-income countries. Pooled mortality and lethality were 10‰ and 4%, respectively. Mortality was more frequent in patients with ≤100 cells/mm3 T CD4+ baseline count and in middle-income countries. Lethality was slightly higher in patients with lower T CD4+ baseline count, regardless of where they came from. Conclusions We found a high overall IRIS incidence in HIV HAART-naïve patients, higher in ≤100 cells/mm3 T CD4+ baseline cell count group. Nonetheless, it varies according to studied population and clinical context. Moreover, lethality was homogenous in all studies. We consider further research on costs on diagnosis and management of IRIS should be done so that cost-effective interventions to avoid this phenomenon can take place. MeSH terms: Immune Reconstitution Syndrome; HIV infections; HAART; Meta-Analysis; Humans.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".