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Record W4280501860 · doi:10.1097/prs.0000000000009267

Conjoined Twin Separation: Review of 30-Year Case Experience and Lessons Learned

2022· review· en· W4280501860 on OpenAlexaffabout
Mark Shafarenko, Ronald M. Zuker

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2022
Typereview
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsConjoined twinsMedicineSurgerySeparation (statistics)

Abstract

fetched live from OpenAlex

BACKGROUND: Conjoined twinning is a rare medical phenomenon, and numerous challenges remain with respect to surgical separation and reconstruction. The purpose of this study is to present a detailed discussion of the authors' institutional experience with eight conjoined twin separations over the past three decades, focusing on challenges and lessons gleaned from these cases. METHODS: The records of all patients who underwent conjoined twin separation at The Hospital for Sick Children in Toronto, Ontario, Canada, from 1984 to 2018 were retrospectively reviewed. RESULTS: Eight sets of conjoined twins were analyzed. Half of the sets [ n = 4 (50 percent)] were female. There were four sets (50 percent) of ischiopagus twins, three sets (37.5 percent) of omphalopagus twins, and one set (12.5 percent) of craniopagus twins. The median age at separation was 6.75 months. The mean durations of intensive care unit and hospital stay were 14.1 ± 12.9 days and 4.9 ± 4.8 months, respectively. Mean length of follow-up was 6.7 ± 4.4 years. Three deaths occurred in our series, with an overall survival rate of 81 percent. Two sets of twins experienced expander-related complications such as infection and bowel perforation. Three twins required reoperation because of flap necrosis or dehiscence after separation. CONCLUSIONS: The authors' results highlight the unique nature of each operation and the great ingenuity required in managing the particular considerations of each case and also adhering to a systematic approach of evaluation and planning. A number of novel strategies were used at the authors' center and have now become commonplace. The lessons learned from such procedures may improve care for future generations of patients. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, V.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.117
GPT teacher head0.383
Teacher spread0.266 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations11
Published2022
Admission routes2
Has abstractyes

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