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Record W2143981838 · doi:10.4103/0974-1216.51908

Total laparoscopic hysterectomy for large uterus

2009· article· en· W2143981838 on OpenAlexaboutno aff
Meenakshi Sundaram, Smita Lakhotia, Chaitali Mahajan, Gayatri Manaktala, Parul Shah, Rakesh Sinha

Bibliographic record

VenueJournal of gynecological endoscopy and surgery · 2009
Typearticle
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHysterectomyLaparoscopyLaparoscopic hysterectomyUterusUterine arteryRetrospective cohort studyBlood lossSurgeryObstetricsPregnancyInternal medicineGestation

Abstract

fetched live from OpenAlex

AIM: In this review, we assessed the feasibility of total laparoscopic hysterectomy (TLH) in cases of very large uteri weighing more than 500 grams. We have analyzed whether it is possible for an experienced laparoscopic surgeon to perform efficient total laparoscopic hysterectomy for large myomatous uteri regardless of the size, number and location of the myomas. DESIGN: Retrospective review (Canadian Task Force Classification II-1) SETTING: Dedicated high volume Gynecological laparoscopy centre. PATIENTS: 173 women with symptomatic myomas who underwent total laparoscopic hysterectomy at our center. There were no exclusion criteria based on the size number or location of myomas. INTERVENTION: TLH and modifications of performing the surgery by ligating the uterine arteries prior, myomectomy followed by hysterectomy, direct morcellation after uterine artery ligation. RESULTS: 72% of patients had previous normal vaginal delivery and 28% had previous cesarean section. Average clinical size of the uterus was 18 weeks (10, 32). The average weight of the specimen was 700 grams (500, 2240). The average duration of surgery was 107 min (40, 300) and the average blood loss was 228 ml (10, 3200). CONCLUSION: Total laparoscopic hysterectomy is a technically feasible procedure. It can be performed by experienced surgeons for large uteri regardless of the size, number or location of the myomas.

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 score0.219
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.304
Teacher spread0.278 · 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

Citations39
Published2009
Admission routes1
Has abstractyes

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