Hematopoietic stem cell transplantation and rhinosinusitis: The utility of screening sinus computed tomography
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To compare prehematopoietic stem cell transplantation (SCT) sinus computed tomography (CT) scans to post-SCT sinus CT scans and to evaluate the relationship between pre-SCT sinus CT scans and the incidence of otolaryngology consultation after SCT. STUDY DESIGN: Retrospective chart review. METHODS: Charts of 228 adult SCT patients from January 2003 to June 2009 with pre-SCT sinus CT scans were reviewed. Data gathered included diagnosis, type of SCT, otolaryngology referral requests, and rhinosinusitis management. Pre- and post-SCT sinus CT scans were scored using the staging system introduced by Lund and Mackay. RESULTS: Two hundred thirty-nine SCTs were performed on the 228 patients included in this study. No disease was identified on 25.1% of pre-SCT CT scans, mild sinus inflammation was identified on 60.7% of scans, 11.3% had moderate inflammation, and 2.9% had severe inflammation. Pre-SCT scans were found to be predictive of post-SCT CT scans. A significant proportion of patients demonstrated worsening of their Lund-Mackay score post-SCT. Pre-SCT CT scores had no predictive ability for otolaryngology consultations. CONCLUSIONS: Pre-SCT CT scan scores are associated with post-SCT scan scores; disease severity on CT may worsen following SCT and may be useful for stratifying patients into surgical versus non-surgical candidates. Further study is needed to outline the benefit of sinus surgery in these patients.
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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) | 0.000 | 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".