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Record W2896328294 · doi:10.2340/16501977-2489

Spino-pelvic alignment, balance, and functional disability in patients with low-grade degenerative lumbar spondylolisthesis

2018· article· en· W2896328294 on OpenAlexaboutno aff
Chi‐Cheng Chuang, M Liaw, L Wang, Yu‐Chi Huang, Ya‐Ping Pong, Chen Chen, Ren‐Chin Wu, Ying-Ka Ingar Lau

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsnot available
FundersChang Gung Medical Foundation
KeywordsPelvic tiltMedicineLordosisLumbarSpondylolisthesisLow back painBack painLumbar lordosisBalance (ability)SurgeryPelvisPhysical therapyRadiography

Abstract

fetched live from OpenAlex

Low-grade degenerative lumbar spondylolisthesis (DLS)is defined as less than 50% slippage of a lumbar vertebral body over the next most caudal vertebral body.Patients with DLS usually experience back pain, leg pain, and even falls.The pain intensity, static and dynamic balance, functional disability, and the spino-pelvic parameters of the radiography (pelvic incident, pelvis tilt, sacral slope, lumbar lordosis) were compared between the patients with DLS and without DLS (non-DLS).The results revealed that DLS patients were older, had greater angle of pelvic incidence and pelvic tilt, less stability and more low back pain than non-DLS patients.The pelvic tilt was the major compensating factor of spino-pelvic balance in both groups.Lumbar lordosis is positively related to body mass index.Sacral slope and lumbar lordosis contributed to partial compensation of balance of spinopelvic alignment in DLS patients, whereas sacral slope could be an indicator of fall risk in non-DLS patients.Objective: To evaluate the relationships among spino-pelvic parameters, trunk balance and functional disability in patients with degenerative lumbar spondylolisthesis.Design: Cross-sectional study.Subjects: Forty-five patients with degenerative lumbar spondylolisthesis and 32 patients without degenerative lumbar spondylolisthesis.Methods: Spino-pelvic parameters (pelvic incidence, pelvic tilt, sacral slope, lumbar lordosis) and pain severity were evaluated.Biodex balance tests (postural stability, limits of stability, modified clinical test of sensory interaction and balance, fall risk) and Quebec Back Pain Disability Scale (QBDS) scores were measured.Results: Intergroup differences were found in age, low back pain, limits of stability, pelvic incidence, pelvic tilt and some subscales of QBDS.Correlations were found: (i) in the degenerative lumbar spondylolisthesis group: between pelvic incidence and sacral slope/pelvic tilt/lumbar lordosis/height/limits of stability; sacral slope and lumbar lordosis/height/ limits of stability/modified clinical test of sensory interaction and balance (eyes closed on foam); lumbar lordosis and body mass index/QBDS/postural stability/modified clinical test of sensory interaction and balance (eyes open and eyes closed on foam); (ii) in the non-degenerative lumbar spondylolisthesis group: between pelvic incidence and pelvic tilt; pelvic tilt and sacral slope/lumbar lordosis; sacral slope and lumbar lordosis/fall risk.All spino-pelvic parameters in the degenerative lumbar spondylolisthesis group and pelvic tilt in the non-degenerative lumbar spondylolisthesis group correlated with QBDS.Conclusion: Pelvic tilt was the major compensating factor in both groups (patients with and without degenerative lumbar spondylolisthesis).Sacral slope and lumbar lordosis contributed to partial compensation in the degenerative lumbar spondylolisthesis group.Lumbar lordosis correlated with body mass index.Sacral slope could be an indicator of fall risk in the non-degenerative lumbar spondylolisthesis group.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.271
Teacher spread0.262 · 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".

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Citations16
Published2018
Admission routes1
Has abstractyes

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