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Record W155740497 · doi:10.36076/ppj.2013/16/se151

An Updated Review of AutomatedPercutaneous Mechanical Lumbar Discectomyfor the Contained Herniated Lumbar Disc

2013· review· en· W155740497 on OpenAlexaboutno aff
Laxmaiah Manchikanti

Bibliographic record

VenuePain Physician · 2013
Typereview
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLumbarPercutaneousDiscectomyIntervertebral Disc DisplacementLumbar vertebraeSurgeryRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Lumbar disc prolapse, protrusion, and extrusion are the most common causes of nerve root pain and surgical interventions, and yet they account for less than 5% of all low back problems. The typical rationale for traditional surgery is that it is an effort to provide more rapid relief of pain and disability. It should be noted that the majority of patients do recover with conservative management. The primary rationale for any form of surgery for disc prolapse associated with radicular pain is to relieve nerve root irritation or compression due to herniated disc material. The primary modality of treatment continues to be either open or microdiscectomy, although several alternative techniques, including automated percutaneous mechanical lumbar discectomy, have been described. There is, however, a paucity of evidence for all decompression techniques, specifically alternative techniques including automated and laser discectomy. STUDY DESIGN: A systematic review of the literature of automated percutaneous mechanical lumbar discectomy for the contained herniated lumbar disc. OBJECTIVE: To evaluate and update the effectiveness of automated percutaneous mechanical lumbar discectomy. METHODS: The available literature on automated percutaneous mechanical lumbar discectomy in managing chronic low back and lower extremity pain was reviewed. The quality assessment and clinical relevance criteria utilized were the Cochrane Musculoskeletal Review Group criteria, as utilized for interventional techniques for randomized trials, and the criteria developed by the Newcastle-Ottawa Scale criteria for observational studies.The level of evidence was classified as good, fair, and limited or poor, based on the quality of evidence scale developed by the U.S. Preventive Services Task Force (USPSTF). Data sources included relevant literature identified through searches of PubMed and EMBASE from 1966 to September 2012, and manual searches of the bibliographies of known primary and review articles. OUTCOME MEASURES: Pain relief was the primary outcome measure. Other outcome measures were functional improvement, improvement of psychological status, opioid intake, and return to work. Short-term effectiveness was defined as one year or less, whereas long-term effectiveness was defined as greater than one year. RESULTS: Nineteen studies were included; none of the randomized trials and 19 observational studies met inclusion criteria for methodological quality assessment. Overall, 5,515 patients were studied with 4,412 patients (80%) showing positive results lasting one year or longer. Based on USPSTF criteria, the indicated evidence for automated percutaneous mechanical lumbar discectomy is limited for short- and long-term relief. LIMITATIONS: A paucity of randomized controlled trials in the literature describing automated percutaneous mechanical disc decompression. CONCLUSION: This systematic review shows limited evidence for automated percutaneous mechanical lumbar discectomy. Automated percutaneous mechanical lumbar discectomy may provide appropriate relief in properly selected patients with contained lumbar disc herniation.

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)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0150.012
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.030
GPT teacher head0.353
Teacher spread0.323 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations45
Published2013
Admission routes1
Has abstractyes

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