Outcomes of Endonasal Dacryocystorhinostomy Performed for Functional Nasolacrimal Obstruction With Delay on Dacryoscintigraphy
Bibliographic record
Abstract
PURPOSE: To report the demographics and outcomes of endonasal dacryocystorhinostomy (DCR) following dacryoscintigraphy (DSG) performed for a series of patients with functional epiphora. METHODS: Case series of endonasal DCR outcomes in patients with symptomatic epiphora with no evidence of lacrimal hypersecretion or lacrimal pump failure, minimal regurgitation noted on syringing, and DSG-confirmed delayed drainage. A successful outcome was defined as 80% subjective improvement or resolution of tearing on the operated side. Patient charts, DSG results, and operative records were examined, and data were collected. Relevant literature was reviewed and discussed. RESULTS: The case series included 15 eyes of 10 patients. The mean age was 61.7 years at the time of surgery. Most cases (n=13) had post-sac obstruction, retention, or delay. One patient had pre and post-sac retention. A total of 12 cases had success after endonasal DCR, and 3 cases had failure. Follow-up for all operated patients was over 6 months. There were no reported complications by the surgeon or patients. CONCLUSIONS: Patients with functional epiphora confirmed by DSG seem to have a high success rate after endonasal DCR. In patients with symptomatic epiphora with subjective patency on syringing, the use of DSG in decision-making and outcome prediction may be supported. Further studies, including clinic-based tests, to demonstrate functional obstruction are warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".