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Record W2885221271 · doi:10.5489/cuaj.5273

Evaluation of an enhanced recovery protocol on patients having radical cystectomy for bladder cancer

2018· article· en· W2885221271 on OpenAlexaffvenueabout
Bonnie Liu, Trustin Domes, Kunal Jana

Bibliographic record

VenueCanadian Urological Association Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCystectomyMedicineBladder cancerComplicationPerioperativeProtocol (science)UrologySurgeryCancerInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: An ERAS protocol was implemented in the Saskatoon Health region for radical cystectomy patients in 2013. This study evaluates the safety and efficacy of the protocol for patients having radical cystectomy for bladder cancer. METHODS: Length of stay, early in-hospital complication rates, 30-day readmission rates, age, and gender were collected for patients seen for bladder cancer requiring radical cystectomy in Saskatoon between January 2007 and December 2016. Of these patients, 176 were pre-ERAS implementation (control group) and 84 were post-ERAS implementation (experimental group). The data from each variable was compared between the groups using a Z-test. RESULTS: There was no significant difference in age or gender of patients between the groups. Average length of stay pre-ERAS was 14.25±14.57 days, which is significantly longer than the post-ERAS average of 10.91±8.56 days (p=0.043). There was no significant difference in 30-day readmission rate (19.87% pre-ERAS vs. 19.05% post-ERAS; p=0.873) or complication rate (51.7% pre-ERAS vs. 46.4% post-ERAS; p=0.425). CONCLUSIONS: The implementation of an ERAS protocol for radical cystectomy reduces length of stay, with no effect on early complication rates or 30-day readmission rates. This indicates that the protocol is safe for patients when compared to previous practices and is an effective means of reducing length of stay.

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)0.003
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.028
GPT teacher head0.317
Teacher spread0.289 · 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

Citations27
Published2018
Admission routes3
Has abstractyes

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