AUTOIMMUNE DISEASE PREVALENCE IN PEOPLE LIVING WITH HIV AT CIPTO MANGUNKUSUMO GENERAL HOSPITAL: A COHORT STUDY
Bibliographic record
Abstract
PV156 / #327 Poster Topic: AS17 - Miscellaneous Background/Purpose Infection is one of the risk factors for developing autoimmune diseases (AD). Apart from Cytomegalovirus and Epstein-Barr virus infections which are often associated with AD pathogenesis, Human Immunodeficiency Virus (HIV) infections which have become epidemics may also play a role in triggering the occurrence of AD. Moreover, after HIV infection can be controlled with antiretroviral therapy (ART) which increases life expectancy for people living with HIV (PLHIV), the recovery of the immune system may have an impact on the emergence of AD manifestations. This research aimed to examine the prevalence and profile of AD in PLHIV. Methods It is a retrospective cohort study in the HIV and Infectious Diseases Integrated Service Installation, Dr. Cipto Mangunkusumo General Hospital from January 2012 to June 2024. We included all HIV patients aged 18 years old and above who were diagnosed with systemic or organ-specific AD. All data were collected from electronic and paper-based medical records. We collected the diagnosis based on ICD-10 written in the medical records. Results Of the 4235 HIV patients included in the cohort, only 61 patients (1.3%) were confirmed to have AD. As many as 55.6% were women and the mean age was 36.0 years. Only a few patients have coinfection with hepatitis B or Hepatitis C. Demographic characteristics are shown in Table 1. The most common AD were Graves disease (n=14), systemic lupus erythematosus (n=9), psoriasis vulgaris (n=7), axial spondyloarthritis (n=5), and antiphospholipid syndrome (n=4). Seven patients were presented with 2 ADs. Systemic AD were diagnosed more after >5 years following ART initiation (12 patients) and before ART initiation (11 patients), while organ-specific AD were diagnosed more in 1-5 years following ART initiation (12 patients) and before ART initiation (8 patients) (Figure 1a and 1b). Table 1. Demography characteristics of the study. Figure 1a. Systemic AD: Diagnosis Interval from ART Initiation Figure 1b. Organ-Specific AD: Diagnosis Interval from ART Initiation SLE: Systemic lupus Erythematosus, APS: Antiphospholipid Syndrome, AIHA: Autoimmune Hemolytic Anemia, ITP: Idiopathic Thrombocytopenic Purpura, GBS: Guillain-Barré syndrome Six female patients and 1 male patient were presented with 2 AD. These female patients were diagnosed with 1) APS and Crohn’s disease, 2) psoriasis vulgaris and psoriatic arthritis, 3) psoriatic arthritis and rheumatoid arthritis, 4) Graves disease and Sjögren’s syndrome, 5) AIHA and SLE, and 6) APS and SLE. Besides, 1 male patient was diagnosed with Graves disease and ITP. Conclusions AD in PLHIV in this cohort was rare. Graves’ disease was the most common organ-specific AD and was most commonly diagnosed at >1 year following ART initiation. SLE was the most common systemic AD and was most commonly diagnosed at >5 years following ART initiation and before ART initiation. Multiple AD was found in a small percentage of patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".