Shedding light on IRIS: from Pathophysiology to Treatment of Cryptococcal Meningitis and Immune Reconstitution Inflammatory Syndrome in HIV‐Infected Individuals
Bibliographic record
Abstract
OBJECTIVES: The aim of this work was to review current treatment options and propose alternatives for immune reconstitution inflammatory syndrome (IRIS) in HIV-infected individuals with cryptococcal meningitis (CM) (termed 'HIV-CM IRIS'). As a consequence of the immunocompromised state of these individuals, the initial immune response to CM is predominantly type 2 T helper (Th2) /Th17 rather than Th1, leading to inefficient fungal clearance at the time of antiretroviral initiation, and a subsequent overexaggeration of the Th1 response and life-threatening IRIS development. METHODS: An article-based and clinical trial-based search was conducted to investigate HIV-CM IRIS pathophysiology and current treatment practices. RESULTS: Guidelines for CM treatment, based on the Cryptococcal Optimal Antiretroviral Timing (COAT) trial, recommend delayed antiretroviral therapy (ART) following antifungal treatment. The approach aims to decrease fungal burden and allow immune balance restoration prior to ART initiation. If the initial immune balance is not restored, the fungal burden is not sufficiently reduced and there is a risk of developing IRIS post-ART, highlighted by a Th1 immune overcompensation, leading to increased mortality. The mainstay treatment for Th1-biased IRIS is corticosteroids; however, this treatment has been shown to correlate with increased mortality and significant associated adverse events. We emphasize targeting a more specific Th1 mechanism via the tumour necrosis factor (TNF)-α cytokine antagonist thalidomide, as it is the only TNF-α antagonist currently approved for use in infectious disease settings and has been shown to decrease Th1 overreaction, restoring immune balance in HIV-CM IRIS. CONCLUSIONS: Although the side effects and limitations of thalidomide must be considered, it is currently being successfully used in infectious disease settings and warrants mainstream application as a therapeutic option for treatment of IRIS in HIV-infected patients with CM.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".