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Record W2079175219 · doi:10.1007/s00586-014-3670-7

Pedicle subtraction osteotomies (PSO) in the lumbar spine for sagittal deformities

2014· article· en· W2079175219 on OpenAlexaff
Pedro Berjano, Max Aebi

Bibliographic record

VenueEuropean Spine Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineSagittal planeCoronal planeSurgeryOsteotomyKyphosisLordosisDeformityLumbarNeurosurgeryRadiologyRadiography

Abstract

fetched live from OpenAlex

INTRODUCTION: The narrow correlation between sagittal alignment parameters and clinical outcomes has been widely established, demonstrating that improper sagittal alignment is a clinical condition that is associated with increased pain and limitations in patients' functional ability. INDICATION: Lumbar pedicle subtraction osteotomy (PSO) is indicated in the treatment of large sagittal (more than 25° of rigid loss of lordosis) deformities of the lumbar spine or its combination with coronal deformity, especially when they are rigid. Indication should be based on careful assessment of the severity of symptoms, functional impairment, functional expectations of the patient, general clinical condition and surgical and anesthesiological team experience. Risk should be carefully assessed and discussed to obtain appropriate informed consent. SURGICAL PROCEDURE: Surgical planning includes selection of the safest levels for the upper and lower instrumented vertebra, site of the osteotomy, modality of fixation, and, most importantly angular value of the correction goal (target lumbar lordosis). Failure to adequately obtain the necessary amount of sagittal correction is the most frequent cause of failure and reoperation. CONCLUSION: PSO is a valuable surgical procedure in correction of severe hypolordosis (=relative kyphosis) in the lumbar spine. It is a demanding procedure for the surgeon, the anesthesiologist and the intensive care team. Although its complication rate is high, it has a substantial positive impact in the quality of life of patients, including the elderly.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.292
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 teacher head, 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

Citations90
Published2014
Admission routes1
Has abstractyes

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