Does the Recovery of Respiratory Viruses Impact Pulmonary Function at Baseline and 1-, 6-, and 12-Month Follow-Up in People Living with HIV and Pneumonia?
Bibliographic record
Abstract
The frequency of respiratory viruses in people living with HIV (PLHIV) and their impact on lung function remain unclear. We aimed to determine the frequency of respiratory viruses in bronchoalveolar lavage and induced sputum samples in PLHIV and correlate their presence with lung function. A prospective cohort of adults hospitalized in Medellín between September 2016 and December 2018 included three groups: group 1 = people diagnosed with HIV and a diagnosis of community-acquired pneumonia (CAP), group 2 = HIV, and group 3 = CAP. People were followed up with at months 1, 6, and 12. Clinical, microbiological, and spirometric data were collected. Respiratory viruses were detected by multiplex RT-PCR. Sixty-five patients were included. At least 1 respiratory virus was identified in 51.9%, 45.1%, and 57.1% of groups 1, 2 and 3, respectively. Among these, 89% of respiratory viruses were detected with another pathogen, mainly Mycobacterium tuberculosis (40.7%) and Pneumocystis jirovecii (22.2%). The most frequent respiratory virus was rhinovirus (24/65, 37%). On admission, 30.4% of group 1, 16.6% of group 2, and 50% of group 3 had airflow limitation, with alteration in forced expiratory volume at first second in both groups with pneumonia compared to HIV. Respiratory viruses are frequent in people diagnosed with HIV, generally coexisting with other pathogens. Pulmonary function on admission was affected in patients with pneumonia, improving significantly in the 1st, 6th, and 12th months after CAP onset.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".