Influence of Obesity on Pneumococcus Infection Risk in the Elderly
Bibliographic record
Abstract
Obesity negatively affects immune function and host defense mechanisms. Obesity is associated with chronic activation of the innate immune system and consequent local and systemic inflammation which contribute to pathologic conditions such as type-2 diabetes mellitus, cancer, psoriasis, atherosclerosis and inflammatory bowel disease. Individuals with obesity have increased susceptibility to contract viral, bacterial and fungal infections and respond sub-optimally to vaccination. In this review, we summarize research findings on the effects of obesity on immune responses to respiratory tract infections (RTI), focusing on Streptococcus pneumoniae (“pneumococcus”) infection, which is a major cause of morbidity and mortality in the US, causing community-acquired infections such as pneumonia, otitis media and meningitis. We show that the risk of infection is higher in elderly individuals and also in individuals of certain ethnic groups, although in a few reports obesity has been associated with better survival of individuals admitted to hospital with pneumococcus infection, a phenomenon known as “obesity paradox”. We discuss factors that are associated with increased risk of pneumococcal infection, such as recent infection with RTI, chronic medical conditions and immunosuppressive medications.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".