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Record W2247912749

A study on comparison of retromuscular prefascial placement of mesh versus other methods of mesh placement in repair of ventral hernias.

2015· article· en· W2247912749 on OpenAlexaff
Jaypal sinh Ashoksinh Gohil, Divyesh Jayesh kumar Pathak, Jenish Yogesh kumar Sheth

Bibliographic record

VenueInternational journal of scientific research · 2015
Typearticle
Languageen
FieldMedicine
TopicHernia repair and management
Canadian institutionsPricewaterhouseCoopers (Canada)
Fundersnot available
KeywordsMedicineSeromaSurgeryVentral herniaHerniaComplication
DOInot available

Abstract

fetched live from OpenAlex

Ventral hernias repair are most routinely performed procedure in daily life of general surgeons. The objective of the present study is to compare the outcome of retromuscular repair over other methods of ventral hernia repair.90 diagnosed cases of ventral hernias were randomly split into two groups A (retromuscular meshplasty) and B(onlay, inlay & underlay meshplasty). The comparison across groups were carried out in terms of operation length, postoperative pain, wound complications, length of hospital stay &  recurrence. No difference was found between the groups regarding age, gender, type and classification of hernia. Operation length was 110min in retromuscular repair and 90min in onlay and 114min underlay method. Statistically difference was seen between these groups. Among complications recurrence, seroma, mesh infection and wound complications were seen in group B. Postoperative pain and well being score were better in retromuscular group. Retromuscular meshplasty have more advantage compare to other open methods in ventral hernia repair.Retromuscular meshplasty is still most appropriate method in open ventral hernia repair.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.308
GPT teacher head0.548
Teacher spread0.240 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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