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Reoperation for Inguinal Hernia Recurrence in Ontario: A Population-Based Study

2016· article· en· W2531807752 on OpenAlexaffabout
Joshua Ramjist, David R. Urbach, Thérèse A. Stukel, Longdi Fu, Nancy N. Baxter

Bibliographic record

VenueJournal of the American College of Surgeons · 2016
Typearticle
Languageen
FieldMedicine
TopicHernia repair and management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineInguinal herniaGeneral surgeryHerniaSurgery

Abstract

fetched live from OpenAlex

Objective: To compare the rate of reoperation for recurrent inguinal hernia after primary repair. Methodology: A population-based retrospective cohort study, using administrative data including adult patients in Ontario, Canada undergoing primary inguinal hernia repair (IHR) from April 1, 2003 - December 31, 2012, followed to August 31, 2014. Exposure: Primary IHR techniques: open repair with mesh; open repair without mesh; laparoscopic repair Results: We identified 109,106 adults undergoing primary IHR with 5.6 year median follow-up. The 5-year cumulative risk of recurrent IHR was 1.7% in the open with mesh group, 3.2% in the open without mesh group and 3.0% in the laparoscopic group. After adjusting for patient, surgeon and institution factors, as compared to patients undergoing open repair with mesh, those undergoing open without mesh or laparoscopic repair had higher risk of recurrent IHR (hazard ratio 1.53, 95% CI, 1.33- 1.77 and 1.88, 95% CI, 1.61- 2.20 respectively, p

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.184
Threshold uncertainty score0.370

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.286
Teacher spread0.265 · 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 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

Citations5
Published2016
Admission routes2
Has abstractyes

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