Socioeconomic, comorbidity, lifestyle, and quality of life comparisons between chronic rhinosinusitis phenotypes
Bibliographic record
Abstract
BACKGROUND: Chronic rhinosinusitis (CRS) is a heterogeneous group of inflammatory sinonasal disorders with key defining symptoms, but traditionally separated into phenotypes by clinical/endoscopic findings. It is not known whether the two phenotypes have differing socioeconomic, comorbidity, and lifestyle differences. This analysis of the Chronic Rhinosinusitis Epidemiology Study (CRES) database sought to analyze any key differences in the socioeconomic variables between those with CRS with nasal polyps (CRSwNPs) and those without nasal polyps (CRSsNPs). We also sought to analyze differences in comorbidities, lifestyle, and quality of life. METHODS: Patients with a confirmed diagnosis of CRS in secondary and tertiary care outpatient settings in the UK were invited to participate in a questionnaire-based case-control study. Variables included demographics, socioeconomic factors, comorbidities, lifestyle factors, and health-related quality of life (HRQoL) (level 3 evidence). RESULTS: A total of 1204 patients' data were analyzed: 553 CRSsNP and 651 CRSwNP participants. The key socioeconomic variables did not demonstrate any notable differences, nor did lifestyle variables other than alcohol consumption being higher in those with CRSwNP (P = .032), but the latter was not significant after adjusting for age and sex. Aside from confirmation of asthma being more common in CRSwNP, it was notable that this group complained less of upper respiratory tract infections (URTIs), and CRSsNP participants showed evidence of worse HRQoL scores in respect of body pain (P = .001). CONCLUSIONS: Patients with CRSwNP experience higher rates of asthma and lower rates of URTIs; patients with CRSsNP have worse body pain scores. Otherwise, there are no demonstrable significant socioeconomic, comorbidity, lifestyle, or quality of life differences between the two phenotypes. LEVEL OF EVIDENCE: 3 Laryngoscope, 131:2179-2186, 2021.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".