Epidemiological Studies on Pulmonary Pathogens in HIV-Positive and -Negative Subjects with or without Community-Acquired Pneumonia with Special Emphasis on <i>Mycoplasma pneumoniae</i>
Bibliographic record
Abstract
The prevalence of Mycoplasma pneumoniae among HIV-positive patients with community-acquired pneumonia (CAP) remains unclear. We investigated 300 HIV-positive adults (200 with CAP and 100 with no respiratory illness) and 75 HIV-negative adults with CAP for the prevalence of respiratory pathogens using culture and serology. A growth inhibition test was employed to confirm the isolates of M. pneumoniae using species-specific typing sera. The prevalence of M. pneumoniae in HIV-positive subjects was 17% by induced sputum and 11.3% by throat swab culture. The seroprevalence of anti-M. pneumoniae IgM was 11.7% by ELISA and 14.3% by the gelatin microparticle agglutination test. The prevalence of M. pneumoniae among HIV-negative cases was relatively low. Streptococcus pneumoniae was predominant (28%) among subjects with lower respiratory disease, whereas Staphylococcus aureus (15%) was common among upper respiratory symptomatic cases. Rales (P = 0.001), pharyngeal erythema (P = 0.02), cervical adenopathy (P = 0.004), skin rash (P = 0.001), and crepitations (P = 0.001) were each significantly related to M. pneumoniae positivity. Statistical significance was observed in relation to total lymphocyte count (P = 0.02) and erythrocyte sedimentation rate (P = 0.04), as well as to M. pneumoniae positivity. This study shows that the prevalence of M. pneumoniae in HIV-positive subjects is comparatively higher than in HIV-negative subjects with pulmonary symptoms, and concords with previous pilot studies carried out in Chennai, South India.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".