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Record W2896853556 · doi:10.1186/s12894-018-0403-y

The effect of surgery report cards on improving radical prostatectomy quality: the SuRep study protocol

2018· article· en· W2896853556 on OpenAlexafffund
Rodney H. Breau, Ravi Kumar, Luke T. Lavallée, Ilias Cagiannos, Christopher Morash, Michael Horrigan, Sonya Cnossen, Ranjeeta Mallick, Dawn Stacey, Michael Fung‐Kee‐Fung, Robin Morash, Jennifer Smylie, Kelsey Witiuk, Dean Fergusson

Bibliographic record

VenueBMC Urology · 2018
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersProstate Cancer Canada
KeywordsMedicineProstatectomyProtocol (science)UrologyGeneral surgeryProstate cancerInternal medicineAlternative medicinePathologyCancer

Abstract

fetched live from OpenAlex

BACKGROUND: The goal of radical prostatectomy is to achieve the optimal balance between complete cancer removal and preserving a patient's urinary and sexual function. Performing a wider excision of peri-prostatic tissue helps achieve negative surgical margins, but can compromise urinary and sexual function. Alternatively, sparing peri-prostatic tissue to maintain functional outcomes may result in an increased risk of cancer recurrence. The objective of this study is to determine the effect of providing surgeons with detailed information about their patient outcomes through a surgical report card. METHODS: We propose a prospective cohort quasi-experimental study. The intervention is the provision of feedback to prostate cancer surgeons via surgical report cards. These report cards will be distributed every 3 months by email and will present surgeons with detailed information, including urinary function, erectile function, and surgical margin outcomes of their patients compared to patients treated by other de-identified surgeons in the study. For the first 12 months of the study, pre-operative, 6-month, and 12-month patient data will be collected but there will be no report cards distributed to surgeons. This will form the pre-feedback cohort. After the pre-feedback cohort has completed accrual, surgeons will receive quarterly report cards. Patients treated after the provision of report cards will comprise the post-feedback cohort. The primary comparison will be post-operative function of the pre-feedback cohort vs. post-feedback cohort. The secondary comparison will be the proportion of patients with positive surgical margins in the two cohorts. Outcomes will be stratified or case-mix adjusted, as appropriate. Assuming a baseline potency of 20% and a baseline continence of 70%, 292 patients will be required for 80% power at an alpha of 5% to detect a 10% improvement in functional outcomes. Assuming 30% of patients may be lost to follow-up, a minimum sample size of 210 patients is required in the pre-feedback cohort and 210 patients in the post-feedback cohort. DISCUSSION: The findings from this study will have an immediate impact on surgeon self-evaluation and we hypothesize surgical report cards will result in improved overall outcomes of men treated with radical prostatectomy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.048
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.048
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.048
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0030.003
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0480.009

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 head0.041
GPT teacher head0.381
Teacher spread0.340 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations6
Published2018
Admission routes2
Has abstractyes

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