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Record W4362661223 · doi:10.1097/aog.0000000000005146

Hyperthermic Intraperitoneal Chemotherapy and Interval Debulking Surgery in Conjunction With Elective Cesarean Delivery

2023· article· en· W4362661223 on OpenAlexaff
Élizabeth Tremblay, Annick Pina, Catherine Avon-Després, Frédéric Mercier, Béatrice Cormier

Bibliographic record

VenueObstetrics and Gynecology · 2023
Typearticle
Languageen
FieldMedicine
TopicIntraperitoneal and Appendiceal Malignancies
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineDebulkingGestationHyperthermic intraperitoneal chemotherapyChemotherapySurgeryPregnancyOvarian cancerStage (stratigraphy)CancerInternal medicineCytoreductive surgery

Abstract

fetched live from OpenAlex

BACKGROUND: Ovarian cancer is rare during pregnancy. For patients beyond 20 weeks of gestation who choose to continue the pregnancy, neoadjuvant chemotherapy may be initiated, followed by interval debulking surgery. Hyperthermic intraperitoneal chemotherapy (HIPEC) may be used with interval debulking surgery for stage III epithelial ovarian cancer, but data are lacking on its administration in the peripartum period. CASE: We illustrate the case of a 40-year-old patient diagnosed with stage III epithelial ovarian cancer at 27 weeks of gestation who underwent neoadjuvant chemotherapy followed by cesarean delivery at term along with interval debulking surgery and HIPEC. The intervention was well tolerated and resulted in the birth of a healthy neonate. The postoperative period was unremarkable, and the patient is disease-free after 22-months of follow-up. CONCLUSION: We demonstrate the feasibility of peripartum HIPEC. Optimal oncologic care should not be jeopardized by the peripartum state of an otherwise healthy patient.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.232
Teacher spread0.217 · 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

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