Atypical bacterial pneumonia in the HIV-infected population
Bibliographic record
Abstract
Human immunodeficiency virus (HIV)-infected individuals are more susceptible to respiratory tract infections by other infectious agents (viruses, bacteria, parasites, and fungi) as their disease progresses to acquired immunodeficiency syndrome. Despite effective antiretroviral therapy, bacterial pneumonia (the most frequently occurring HIV-associated pulmonary illness) remains a common cause of morbidity and mortality in the HIV-infected population. Over the last few decades, studies have looked at the role of atypical bacterial pneumonia (i.e. pneumonia that causes an atypical clinical presentation or responds differently to typical therapeutics) in association with HIV infection. Due to the lack of available diagnostic strategies, the lack of consideration, and the declining immunity of the patient, HIV co-infections with atypical bacteria are currently believed to be underreported. Thus, following an extensive database search, this review aimed to highlight the current knowledge and gaps regarding atypical bacterial pneumonia in HIV. The authors discuss the prevalence of Chlamydophila pneumoniae, Mycoplasma pneumoniae, Coxiella burnetii, Legionella species and others in the HIV-infected population as well as their clinical presentation, methods of detection, and treatment. Further studies looking at the role of these microbes in association with HIV are required. Increased knowledge of these atypical bacteria will lead to a more rapid diagnosis of these infections, resulting in an improved quality of life for the HIV-infected population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".