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Record W4387472529 · doi:10.1097/scs.0000000000009783

Outcomes of Endonasal Dacryocystorhinostomy Performed for Functional Nasolacrimal Obstruction With Delay on Dacryoscintigraphy

2023· article· en· W4387472529 on OpenAlexaff
Kevin Hodgson, Ahsen Hussain

Bibliographic record

VenueJournal of Craniofacial Surgery · 2023
Typearticle
Languageen
FieldMedicine
TopicNasolacrimal Duct Obstruction Treatments
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineDacryocystorhinostomyNasolacrimal duct obstructionSurgery

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.280
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

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