Corticosteroids Use and Incidence of Severe Infections in People Living with HIV Compared to a Matched Population
Bibliographic record
Abstract
BACKGROUND: People living with HIV (PLWH) have been shown to have an increased risk of autoimmune diseases. Corticosteroids are the cornerstone of autoimmune diseases treatment, but their use is associated with an increased risk of infections. It is unclear how HIV status affects the risk of infection associated with corticosteroids use. METHODS: We conducted a retrospective cohort study from 1991 to 2011, using a medico-administrative database from Quebec. Medical billing codes were used to identify PLWH, and we matched them on age, sex, and index date with up to 4 HIV-negative controls. The exposure of interest was the use of corticosteroids, defined as a systemic corticosteroid dispensation lasting at least 20 days. The outcome of interest was hospitalization for severe infection. Crude and adjusted incidence rates ratios of infection were obtained using a random effect Poisson model, and results were stratified by HIV status. RESULTS: In total, 4798 PLWH were matched to 17 644 HIV-negative controls, among which 1083 (22.6%) PLWH and 1854 (10.5%) HIV-negative controls received at least one course of corticosteroid. The mean duration of corticosteroids use was 4 ± 4.4 months in PLWH and 1.6 ± 5.5 months in HIV-negative controls. The incidence rate ratio (IRR) for infections associated with corticosteroids use was 2.49[1.71-3.60] in PLWH and 1.32[0.71-2.47] in HIV-negative controls (P value for interaction 0.18). The most frequent infections were pulmonary infections (50.4%), followed by urinary tract infections (26%) and opportunistic infections (10.5%). CONCLUSION: Although our interaction term did not reach significance, the increased risk of infection associated with corticosteroids use was more pronounced in PLWH. However, further research with contemporary data is warranted to confirm if the risk associated with corticosteroids use remains high in PLWH with well-controlled HIV infection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".