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Record W2767001480 · doi:10.1002/jso.24878

Factors affecting hospital length of stay following pelvic exenteration surgery

2017· article· en· W2767001480 on OpenAlexaff
Ying Guo, Eugene Chang, Mehtap Bozkurt, Minjeong Park, Diane Liu, Jack B. Fu

Bibliographic record

VenueJournal of Surgical Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsToronto Rehabilitation Institute
FundersNational Cancer InstituteNational Institutes of Health
KeywordsMedicinePelvic exenterationSurgeryInterquartile rangeGenitourinary systemFistulaRetrospective cohort studyPerioperativeDehiscenceAnastomosisLeiomyosarcomaInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Total pelvic exenteration are performed in patients with locally advanced or recurrent pelvic malignances. Many patients have prolong hospital length of stay (LOS), but risk factors are not clearly identified. METHODS: From 2002 through 2012, 100 consecutive patients undergoing pelvic exenteration were retrospectively reviewed. A general linear model was used to examine risk factors for prolonged hospital LOS. RESULTS: Among the 100 patients, 51 had gastrointestinal cancer, 14 had genitourinary cancer, 31 had gynecologic cancer, and 4 had sarcoma. Perioperative complications included infection (n = 44), anastomotic leak/fistula (n = 6), wound or flap dehiscence (n = 11), and ileus or bowel obstruction (n = 30). The median (Interquartile range (IQR)) hospital LOS was 15 days (10-21.5 days). On multivariate regression analysis, hospital LOS was significantly prolonged by underweight status, genitourinary cancer or sarcoma diagnosis, ≥2 infections, anastomotic leak/fistula, requiring rehabilitation consult and admission, and ≥2 consultations (P = 0.05). CONCLUSION: In patients undergoing pelvic exenteration, prolonged hospital LOS is associated with underweight status, genitourinary cancer or sarcoma diagnosis, more than one infection, anastomotic leak/fistula, requiring rehabilitation consult and admission, and more than one consultation. Further study is needed to assess whether minimizing these risk factors can improve hospital LOS in these patients.

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)0.001
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 score0.038
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.058
GPT teacher head0.366
Teacher spread0.308 · 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

Citations21
Published2017
Admission routes1
Has abstractyes

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