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Record W2316198914 · doi:10.1017/s0317167100007411

Bowel Injury following Lumbar Discectomy using Minimally Invasive Retractors

2007· letter· en· W2316198914 on OpenAlexaffvenue
Aleksa Cenic, Niv Sne, Michael Lisi, Allan Okrainac, Kesava Reddy

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2007
Typeletter
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineRetractorDiscectomySurgeryMicrosurgeryLumbar disc herniationSciaticaInvasive surgeryMultifidus muscleIncidence (geometry)Blood lossLumbarLow back pain

Abstract

fetched live from OpenAlex

Prevalence of symptomatic lumbar disc herniation is 1-3% in the adult population. When conservative therapy (e.g., physiotherapy, anti-inflammatories, epidural injections, etc.) fails, open microsurgical discectomy is regarded as the treatment of choice.With this procedure, the incidence of injury to visceral bowel is reported to be 3.8 per 10,000 cases. With the recent advent of tubular retractor systems, an increasing number of surgeons are using this minimally invasive procedure to replace traditional open microsurgical discectomy. The advantages include a smaller skin incision and a muscle splitting rather than muscle incising technique. As a result post-operative pain, blood loss and length of hospital stay may decrease significantly. Multiple studies have compared the two surgical techniques with regards to their clinical outcomes. The results of these studies reveal equal if not superior clinical outcomes with the minimally invasive technique. Despite the success of the minimally invasive microdiscectomy, none of the studies reported any intraoperative complications using this novel technique.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0090.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.052
GPT teacher head0.314
Teacher spread0.261 · 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 designCase report
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

Citations1
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques→Same topicSpine and Intervertebral Disc Pathology→French-language works237,207→