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Record W2139825783 · doi:10.1002/jso.23338

The Effect of Wait Times on Oncological Outcomes From Periampullary Adenocarcinomas

2013· article· en· W2139825783 on OpenAlexaff
Spencer R. McLean, Divya J. Karsanji, Jennifer N. Wilson, Elijah Dixon, Francis Sutherland, Janice L. Pasieka, Chad G. Ball, Oliver F. Bathe

Bibliographic record

VenueJournal of Surgical Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicinePeriampullary cancerStage (stratigraphy)Retrospective cohort studySurgeryCohortResectionAdenocarcinomaPancreatectomyGeneral surgeryPancreaticoduodenectomyInternal medicineCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Overall few patients presenting with periampullary adenocarcinomas have resectable lesions. We postulated that rapid diagnosis and treatment would enhance the likelihood of successful resection, improving survival. METHODS: A retrospective analysis of patients undergoing surgery for resection of a pancreatic or periampullary lesion was conducted. Resection rate, disease stage and survival were evaluated as a function of wait times. RESULTS: Pancreatic resections were booked in 355 patients. Of 193 patients with periampullary adenocarcinomas, 119 patients (61.7%) had resectable disease. There was no difference in median time from initial physician consultation to surgery in patients with resectable and unresectable disease (61 days vs. 64 days, respectively). The likelihood of successful resection was virtually identical in patients with wait times ≤ 30 and > 30 days (from surgical consultation to procedure). There was a trend toward a higher T-stage in patients who waited >30 days for surgery (P = 0.055). However, there was no difference in survival as a function of wait time. CONCLUSIONS: This series does not demonstrate an advantage for rapid diagnosis and surgery, in terms of resection rate and survival. However, further study is required in a larger cohort of patients, to confirm these findings.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.126
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
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 head0.031
GPT teacher head0.356
Teacher spread0.325 · 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

Citations32
Published2013
Admission routes1
Has abstractyes

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