Nasal nitric oxide levels in hiv infection: a cross-sectional study
Bibliographic record
Abstract
Introduction. Low levels of nasal NO have been associated with increased propensity to rhinosinusitis and respiratory tract infections. Our objective was to describe nasalNOlevels in HIV-infected individuals versus healthy controls and determine possible risk factors for reduced nasal NO levels. Materials and Methods. HIV-infected individuals and healthy controls were recruited. Participants underwent nasal NO testing by standardized methods using a CLD88 chemiluminescence analyzer and completed the Sinonasal Outcome Test-20 (SNOT-20) on symptoms of rhinosinusitis. Results. Participants included 41 HIV-infected individuals with suppressed VL on antiretroviral therapy (ART group), 5HIV-infected individuals with detectable VL off ART (viremic group), and 12 healthy controls (HC group). Mean nasal NO level was 253 (+/- 77) nL/min in the ART group, 213 (+/- 48) nL/min in the viremic group, and 289 (+/- 68) nL/min in the HC group (p = 0.133; ANOVA). There was no correlation between nasal NO level and VL in viremic individuals (p = -0.200;p = 0.747). Differences were observed in mean total points on the SNOT-20 which were 19 (+/- 16)/100, 18 (+/- 26)/100, and 4 (+/- 4)/100 in the ART, viremic, and HC groups, respectively (p = 0.013; ANOVA). Conclusion. Healthy individuals, HIV patients on ART, and viremic individuals off ART display similar nasalNOlevels. However, rhinosinusitis symptoms remain prominent despite ART-treatment.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".