Do Aging Factors Influence the Clinical Presentation and Management of Chronic Rhinosinusitis?
Bibliographic record
Abstract
Objective/Hypothesis Chronic rhinosinusitis (CRS) is a complex inflammatory disease of the upper respiratory airways resulting from the dysregulation of immunity and epithelial defenses. More recently, the contribution of an altered nasal microbiome to the development of CRS has also been proposed. However, the impact of aging on the development of CRS has been long overlooked. Here we propose, in a hypothesis piece, that aging can influence the physiopathology of CRS and its subsequent management in an elderly population. Data Sources We summarize the recent literature findings supporting that elderly patients with CRS could be a distinct population from those with adult CRS and might require different or adjunct therapeutic approaches. Methods Review of recent literature of the effect of aging and its possible effects in CRS using 3 different databases. Conclusions Age‐dependent decrease in the levels of the S100 family proteins involved in epithelial proliferation, repair, and defenses combined with chronic inflammation might lead to an increased risk of abnormal microbial colonization and loss of microbiota diversity. Ultimately, these changes could have the potential to alter the physiopathology of CRS in the elderly. Implications Unlike in adults, in whom CRS T h 2‐skewed responses with eosinophilia are thought to play a critical role, in aging populations, a microbiome and epithelial barrier dysfunctions may instead be the pivotal agents of disease development and persistence. This supports that therapies for elderly patients may require a different management or additional targeted therapies to control the disease. Prospective studies, however, are necessary to validate this concept.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".