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Record W2488271697 · doi:10.1097/brs.0000000000001476

ISSLS Prize Winner: Consensus on the Clinical Diagnosis of Lumbar Spinal Stenosis

2016· article· en· W2488271697 on OpenAlexafffund
Christy Tomkins‐Lane, Markus Melloh, Jon D. Lurie, Matthew Smuck, Michele C. Battié, Brian J. C. Freeman, Dino Samartzis, Richard Hu, Thomas Barz, Kent Stuber, Michael Schneider, Andrew J. Haig, Constantin Schizas, Jason Pui Yin Cheung, Anne F. Mannion, Lukas Staub, Christine Comer, Luciana Macedo, Sang Ho Ahn, Kazuhisa Takahashi, Danielle Sandella

Bibliographic record

VenueSpine · 2016
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsUniversity of CalgaryUniversity of AlbertaCanadian Memorial Chiropractic CollegeMount Royal University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on AgingCanadian Spine SocietyInternational Society for the Study of the Lumbar Spine
KeywordsMedicineConsensus conferenceLumbar spinal stenosisLumbarRadiologyInternal medicine

Abstract

fetched live from OpenAlex

STUDY DESIGN: Delphi. OBJECTIVE: The aim of this study was to obtain an expert consensus on which history factors are most important in the clinical diagnosis of lumbar spinal stenosis (LSS). SUMMARY OF BACKGROUND DATA: LSS is a poorly defined clinical syndrome. Criteria for defining LSS are needed and should be informed by the experience of expert clinicians. METHODS: Phase 1 (Delphi Items): 20 members of the International Taskforce on the Diagnosis and Management of LSS confirmed a list of 14 history items. An online survey was developed that permits specialists to express the logical order in which they consider the items, and the level of certainty ascertained from the questions. Phase 2 (Delphi Study) Round 1: Survey distributed to members of the International Society for the Study of the Lumbar Spine. Round 2: Meeting of 9 members of Taskforce where consensus was reached on a final list of 10 items. Round 3: Final survey was distributed internationally. Phase 3: Final Taskforce consensus meeting. RESULTS: A total of 279 clinicians from 29 different countries, with a mean of 19 (±SD: 12) years in practice participated. The six top items were "leg or buttock pain while walking," "flex forward to relieve symptoms," "feel relief when using a shopping cart or bicycle," "motor or sensory disturbance while walking," "normal and symmetric foot pulses," "lower extremity weakness," and "low back pain." Significant change in certainty ceased after six questions at 80% (P < .05). CONCLUSION: This is the first study to reach an international consensus on the clinical diagnosis of LSS, and suggests that within six questions clinicians are 80% certain of diagnosis. We propose a consensus-based set of "seven history items" that can act as a pragmatic criterion for defining LSS in both clinical and research settings, which in the long term may lead to more cost-effective treatment, improved health care utilization, and enhanced patient outcomes. LEVEL OF EVIDENCE: 2.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.087
GPT teacher head0.376
Teacher spread0.288 · 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.

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

Citations134
Published2016
Admission routes2
Has abstractyes

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