Lung Microbiota in People Diagnosed with HIV and Pneumonia: A Colombian Cohort Study
Bibliographic record
Abstract
The lung microbiota plays a key role in respiratory health, but its composition in individuals living with HIV and diagnosed with community-acquired pneumonia (CAP) remains underexplored. A prospective cohort study in Medellín, Colombia recruited individuals with CAP and/or HIV between 2016 and 2018. Clinical and microbiological data were collected at baseline, with bronchoalveolar lavage samples obtained at baseline and induced sputum samples collected at baseline and 6-month follow-up. Microbiota composition was analyzed in these samples using Illumina MiSeq sequencing of the 16S ribosomal RNA gene. Among 248 screened participants, 64 were included: HIV and CAP (n = 27), CAP (n = 7), and HIV (n = 30); 70.3% were males, and 76.6% were between 25 and 64 years old. The HIV and CAP group had a lower proportion of receiving antiretroviral treatment and a higher prevalence of advanced immunosuppression. The most frequent micro-organisms identified by conventional methods in the HIV and CAP group were Mycobacterium tuberculosis (40.7%) and Pneumocystis jirovecii (18.5%). The dominant phyla (Firmicutes, Proteobacteria, Fusobacteria, Bacteroidetes, and Actinobacteria) and genera (Streptococcus, Haemophilus, Veillonella, Neisseria, and Fusobacterium) were identified in the overall study population, including both baseline and 6-month follow-up samples. The HIV and CAP group showed changes in bacterial diversity and relative abundance over 6 months. These findings provide insights into the dynamic lung microbiota in individuals coinfected with HIV and CAP, highlighting the impact of HIV and CAP on microbial composition and diversity, which may inform future studies exploring clinical outcomes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".