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Record W2145137370 · doi:10.1017/s0317167100007599

The Learning Curve of Minimally-Invasive Lumbar Microdiscectomy

2008· article· en· W2145137370 on OpenAlexafffundvenue
Gregory S. McLoughlin, Daryl R. Fourney

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2008
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsUniversity of Saskatchewan
FundersRoyal University Hospital Foundation
KeywordsMedicineLearning curveRetractorSurgeryLumbarComputer science

Abstract

fetched live from OpenAlex

OBJECT: The safe integration into practice of a new surgical technique requires an appreciation of the learning curve. The object of this study was to assess the learning curve for minimally invasive microdiscectomy (MIM) utilizing a tubular retractor system. METHODS: A prospective evaluation of a single surgeon's first 52 consecutive MIM cases for radiculopathy secondary to single-level posterolateral lumbar disc herniation was performed. The learning curve was assessed using operative time, conversion to open rate, complications, and length of hospitalization. RESULTS: The duration of operative time decreased over the course of the study (range, 49-151 min). By case 15, operative time was typically 60 min or less. There was only one conversion to an open procedure (Case 2). Complications occurred in three cases. All but nine patients were discharged home on the day of surgery. CONCLUSION: The learning curve for MIM was demonstrated. Further assessment of this curve for a large group of surgeons is necessary before a randomized controlled trial comparing standard microdiscectomy to MIM can be conducted.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.013
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.286
Teacher spread0.242 · 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; both teacher heads agree on what is shown here.

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

Citations56
Published2008
Admission routes3
Has abstractyes

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