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Record W2079804526 · doi:10.4021/wjon743w

Surgical Staging of Early Stage Endometrial Cancer: Comparison Between Laparotomy and Laparoscopy

2013· article· en· W2079804526 on OpenAlexvenueno aff
Api

Bibliographic record

VenueWorld Journal of Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLymphLaparotomyLaparoscopyStage (stratigraphy)Endometrial cancerSurgeryLymph nodeCarcinomaRetrospective cohort studyCancerInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of the present study was to compare the laparotomy (LT) and laparoscopy (LS) in patients who undergone surgical staging for early stage endometrium cancer. METHODS: Retrospective data were collected and analyzed for amount of intraoperative bleeding, complication rates, total resected and laterality specific number of lymph nodes and duration of operation in patients operated with either LT or LS. RESULTS: Seventy-nine stage I endometrium cancer patients were found to be eligible for the trial purposes: 58 (73.4%) treated by LT and 21 (26.6%) treated by LS. The number of lymph nodes was similar in LT (8.9 ± 5.3) and LS (9.2 ± 4.8) (P = 0.8). In LT group, there was no difference in the number of lymph nodes between the right and left sides (10 ± 5.8 and 8.7 ± 4.8 respectively, P = 0.19); in LS group, the number of lymph nodes resected from the right side was higher than the left side (9.8 ± 5 and 7 ± 3.5 respectively, P = 0.039). The amount of intraoperative bleeding and hospitalization period were significantly higher in LT group. Seventy-nine patients had a median follow-up of 30 months. The two groups were similar for disease-free survival (P = 0.46, log rank test). CONCLUSIONS: There was no significant difference between the two methods in terms of number of total resected lymph nodes. In early stage endometrial carcinoma, LS has provided adequate staging and similar survival rates with LT.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.051
GPT teacher head0.385
Teacher spread0.334 · 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 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

Citations5
Published2013
Admission routes1
Has abstractyes

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