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Record W2969721622 · doi:10.1007/s00586-019-06119-6

Measuring and reporting of vertebral endplate bone marrow lesions as seen on MRI (Modic changes): recommendations from the ISSLS Degenerative Spinal Phenotypes Group

2019· review· en· W2969721622 on OpenAlex
Aaron J. Fields, Michele C. Battié, Richard J. Herzog, Jeffrey G. Jarvik, Roland Krug, Thomas M. Link, Jeffrey C. Lotz, Conor W. O’Neill, Aseem Sharma

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Spine Journal · 2019
Typereview
Languageen
FieldMedicine
TopicBone and Joint Diseases
Canadian institutionsWestern University
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesInternational Society for the Study of the Lumbar Spine
KeywordsModic changesMedicineLow back painReliability (semiconductor)Magnetic resonance imagingRadiologyNeurologyPhysical medicine and rehabilitationPhysical therapyPathology

Abstract

fetched live from OpenAlex

PURPOSE: The positive association between low back pain and MRI evidence of vertebral endplate bone marrow lesions, often called Modic changes (MC), offers the exciting prospect of diagnosing a specific phenotype of chronic low back pain (LBP). However, imprecision in the reporting of MC has introduced substantial challenges, as variations in both imaging equipment and scanning parameters can impact conspicuity of MC. This review discusses key methodological factors that impact MC classification and recommends guidelines for more consistent MC reporting that will allow for better integration of research into this LBP phenotype. METHODS: Non-systematic literature review. RESULTS: The high diagnostic specificity of MC classification for a painful level contributes to the significant association observed between MC and LBP, whereas low and variable sensitivity underlies the between- and within-study variability in observed associations. Poor sensitivity may be owing to the presence of other pain generators, to the limited MRI resolution, and to the imperfect reliability of MC classification, which lowers diagnostic sensitivity and thus influences the association between MC and LBP. Importantly, magnetic field strength and pulse sequence parameters also impact detection of MC. Advances in pulse sequences may improve reliability and prove valuable for quantifying lesion severity. CONCLUSIONS: Comparison of MC data between studies can be problematic. Various methodological factors impact detection and classification of MC, and the lack of reporting guidelines hinders interpretation and comparison of findings. Thus, it is critical to adopt imaging and reporting standards that codify acceptable methodological criteria. These slides can be retrieved under Electronic Supplementary Material.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.197
GPT teacher head0.363
Teacher spread0.165 · 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