Recurrent epiphora after dacryocystorhinostomy surgery: Structural abnormalities identified with dacryocystography and long term outcomes of revision surgery
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Bibliographic record
Abstract
BACKGROUND: To investigate the aetiopathology of recurrent epiphora or stickiness after dacryocystorhinostomy (DCR) surgery, identifiable on dacryocystography (DCG), and to assess the success rates of secondary corrective surgeries. METHODS: Consecutive post-DCR DCG images from patients with recurrent symptoms were reviewed between 2012 and 2015. RESULTS: One hundred fifty-nine eyes of 137 patients were evaluated. Fifty-eight DCGs showed normal postoperative findings, 4 an upper/lower canalicular block, 13 a common canalicular block, 31 a completely closed anastomosis, 50 a narrow anastomosis, and 3 an anastomosis draining into a nasal sinus. The most successful corrective procedures for each failure category were: Lester Jones Tube (LJT) for a normal post-operative DCG (17/18 success), Sisler trephination with tubes for upper/lower canalicular block (1/2 success), redo-DCR with tube for common canalicular blockage (5/6 success), redo-DCR +/- tube for completely closed anastomosis (12/16 success), LJT followed by redo-DCR +/- tube for narrow surgical anastomosis (1/1 and 17/27 success respectively), and redo-external-DCR with tube for anastomosis into a nasal sinus (1/1 success). Redo-DCR was ineffective in patients who had good post-DCR anatomical patency (22% success). CONCLUSION: This is the first study to report success rates of redo-DCR surgery according to anatomical findings confirmed by DCG. The outcome flow diagram help clinicians recommend procedures that are most likely to be successful for their patient's specific anatomical abnormality. It also provides a visual tool for the shared decision-making process. Notably, symptomatic patients with a normal DCG post DCR are unlikely to benefit from redo-DCR, with a LJT being the recommended next step.
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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) | 0.001 | 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 it