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Single surgeon’s experience with Furlow palatoplasty and the fistula rate

2006· article· en· W2106551036 on OpenAlexaff
A Mak, W. T. Wong, Chi‐Kong Or, A.M.S. Poon

Bibliographic record

VenueSurgical Practice · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicinePalatoplastyIncidence (geometry)FistulaDentistrySurgeryFistulectomy

Abstract

fetched live from OpenAlex

Objective: To review the clinical data on Furlow palatoplasty and the incidence of palatal fistula. Methods: A retrospective review was conducted of clinical data and incidence of palatal fistula in all cleft palate patients undergoing Furlow palatoplasty by one surgeon in Princess Margaret Hospital from November 1997 to February 2003. Results: Of the 54 patients (29 male, 25 female) treated, five (9.3%) had positive family history of cleft lip/cleft palate. Twenty‐two patients (40.7%) had associated cleft lip and four (7.4%) had other congenital malformations. Thirty‐one palates were Veau classes I & II; 15 were class III, six were class IV, and two were submucous clefts. The mean ± SD patient age was 22.8 ± 11.9 months, and follow‐up period 50.6 ± 17.5 months with five (9.3%) defaulted. Blood loss and operation time were significantly different among the different classes of clefts. There was one case of postoperative bleeding requiring immediate opening. Three palatal fistulae occurred, all within the first 3 years of the study period. Two were repaired with no recurrences. Conclusions: The surgeon’s incidence of palatal fistula after Furlow palatoplasty is 5.6%, comparable to the low incidence reported by other surgeons using other methods of repair.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.941
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.272
Teacher spread0.261 · 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 designNot applicable
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

Citations6
Published2006
Admission routes1
Has abstractyes

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