Inflammatory Patterns Associated with Legionella in HIV and Pneumonia Coinfections
Bibliographic record
Abstract
Legionella infections have a propensity for occurring in HIV-infected individuals, with immunosuppressed individuals tending to present with more severe disease. However, understanding regarding the Legionella host response in immune compromised individuals is lacking. This study investigated the inflammatory profiles associated with Legionella infection in patients hospitalized with HIV and pneumonia in Medellín, Colombia from February 2007 to April 2014, and correlated these profiles with clinical outcomes. Sample aliquots from the Colombian cohort were shipped to Canada where Legionella infections and systemic cytokine profiles were determined using real-time PCR and bead-based technology, respectively. To determine the effect of Legionella coinfection on clinical outcome, a patient database was consulted, comparing laboratory results and outcomes between Legionella-positive and -negative individuals. Principal component analysis revealed higher plasma concentrations of eotaxin, IP-10 and MCP-1 (p = 0.0046) during Legionella infection. Individuals with this immune profile also had higher rates of intensive care unit admissions (adjusted relative risk 1.047 [95% confidence interval 1.027–1.066]). Results demonstrate that systemic markers of monocyte/macrophage activation and differentiation (eotaxin, MCP-1, and IP-10) are associated with Legionella infection and worse patient outcomes. Further investigations are warranted to determine how this cytokine profile may play a role in Legionella pneumonia pathogenesis or immunity.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".