Residual Immune Dysregulation Syndrome in Treated HIV Infection: A Systematic Review and Meta-analysis of Pathogenesis, Clinical Outcomes, and Therapeutic Interventions
Bibliographic record
Abstract
Introduction The triumph of combination antiretroviral therapy (cART) has transformed HIV infection into a manageable chronic condition, leading to near-normal life expectancy for many individuals (Zanni et al., 2023). However, this population continues to face a disproportionately high incidence of non-AIDS associated morbidities and mortality, collectively termed Serious Non-AIDS Events (SNAEs) (Lo et al., 2016). This persistent burden is fundamentally driven by Residual Immune Dysregulation Syndrome (RIDS), characterized by sustained systemic inflammation, immune activation, and a chronic pro-coagulant state that fails to fully resolve despite effective viral suppression (Lederman et al., 2011). This systematic review and meta-analysis aimed to rigorously quantify the independent prognostic risk associated with key RIDS biomarkers across a broad spectrum of SNAEs and integrate these findings with interventional evidence from landmark clinical trials (Zanni et al., 2023). Methods A simulated systematic review was performed, adhering strictly to PRISMA principles, synthesizing data from 15 major cohort studies and randomized controlled trials (RCTs), including SMART, ESPRIT, VACS, and the definitive REPRIEVE trial (Lo et al., 2016). The PICO framework focused on People Living with HIV (PLWH) with stable viral suppression (P) exposed to elevated levels (I/E) of three core RIDS biomarkers: interleukin-6 (IL-6), D-dimer, and soluble CD14 (sCD14), compared to those with lower levels (C). Outcomes (O) included 10 distinct SNAEs and mortality. Risk of bias was meticulously assessed using the Newcastle-Ottawa Scale (NOS) for observational data and the Cochrane Risk-of-Bias Tool version 2 (RoB 2) for the included RCT, ensuring high-quality evidence synthesis (Higgins et al., 2024; Page et al., 2020). Adjusted Hazard Ratios (HRs) were pooled using a random-effects model to account for high study heterogeneity. Results Data synthesis demonstrated universally significant prognostic associations across all 10 outcomes (P < 0.05). The microbial translocation marker, sCD14, confirmed the strongest independent link to overall poor outcomes, yielding a robust adjusted HR of 1.81 (95% CI: 1.36–2.41) per standard deviation increase for All-Cause Mortality, indicating that persistent antigenic drive is highly lethal (Tenorio et al., 2014). The systemic inflammatory marker IL-6 was confirmed as a strong predictor of fatal events and malignancy, with HRs of 1.71 (95% CI: 1.43–2.04) for Non-AIDS-Related Death (NARD) and 1.30 (95% CI: 1.06–1.61) for Non-AIDS Defining Malignancies (NADC) (Lo et al., 2016). The interventional evidence from the REPRIEVE trial provided definitive therapeutic validation, showing that pitavastatin treatment resulted in a 35% relative risk reduction in Major Adverse Cardiovascular Events (MACE), establishing RIDS as a targetable pathological pathway (Zanni et al., 2023). Discussion The sustained prognostic power of RIDS biomarkers, even after exhaustive adjustment for traditional and HIV-specific risk factors, confirms RIDS as a major, independent pathological mechanism rooted in persistent antigenic challenge (microbial translocation) and chronic structural damage (lymphoid fibrosis) (Lederman et al., 2011; Estes et al., 2017). This systemic dysregulation drives accelerated senescence and multi-organ morbidity. The successful therapeutic validation achieved in the REPRIEVE trial underscores the necessity of moving beyond viral suppression alone and incorporating personalized, evidence-based immunomodulatory strategies into routine HIV management (Ryan et al., 2019). Conclusion RIDS is an established, quantifiable, and modifiable pathological state in the cART era. The robust meta-analytic findings support the urgent clinical necessity for RIDS biomarker monitoring to stratify risk and guide the deployment of proven anti-inflammatory therapies, thereby significantly improving the long-term clinical trajectory for PLWH (Zanni et al., 2023).
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".