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Record W4391231833 · doi:10.1097/brs.0000000000004930

Lumbar Lordosis Redistribution and Segmental Correction in Adult Spinal Deformity

2024· article· en· W4391231833 on OpenAlexaff
Bassel G. Diebo, Mariah Balmaceno-Criss, Renaud Lafage, Mohammad Daher, Manjot Singh, D. Kojo Hamilton, Justin S. Smith, Robert K. Eastlack, Richard G. Fessler, Jeffrey L. Gum, Munish C. Gupta, Richard A. Hostin, Khaled M. Kebaish, Stephen J. Lewis, Breton Line, Pierce D. Nunley, Gregory M. Mundis, Peter G. Passias, Themistocles S. Protopsaltis, Jay D. Turner, Thomas J. Buell, Justin K. Scheer, Jeffrey P. Mullin, Alex Soroceanu, Christopher P. Ames, Shay Bess, Christopher I. Shaffrey, Lawrence G. Lenke, Frank J. Schwab, Virginie Lafage, Douglas C. Burton, Alan H. Daniels

Bibliographic record

VenueSpine · 2024
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsUniversity of CalgaryUniversity of Toronto
Fundersnot available
KeywordsMedicineSurgeryLumbarLordosisDeformityRadiography

Abstract

fetched live from OpenAlex

STUDY DESIGN: Retrospective analysis of prospectively collected data. OBJECTIVE: Evaluate the impact of correcting normative segmental lordosis values on postoperative outcomes. BACKGROUND: Restoring lumbar lordosis magnitude is crucial in adult spinal deformity surgery, but the optimal location and segmental distribution remain unclear. PATIENTS AND METHODS: Patients were grouped based on offset to normative segmental lordosis values, extracted from recent publications. Matched patients were within 10% of the cohort's mean offset, less than or over 10% were undercorrected and overcorrected. Surgical technique, patient-reported outcome measures, and surgical complications were compared across groups at baseline and two years. RESULTS: In total, 510 patients with a mean age of 64.6, a mean Charlson comorbidity index 2.08, and a mean follow-up of 25 months. L4-5 was least likely to be matched (19.1%), while L4-S1 was the most likely (24.3%). More patients were overcorrected at proximal levels (T10-L2; undercorrected, U: 32.2% vs. matched, M: 21.7% vs. overcorrected, O: 46.1%) and undercorrected at distal levels (L4-S1: U: 39.0% vs. M: 24.3% vs. O: 36.8%). Postoperative Oswestry disability index was comparable across correction groups at all spinal levels except at L4-S1 and T10-L2/L4-S1, where overcorrected patients and matched were better than undercorrected (U: 32.1 vs. M: 25.4 vs. O: 26.5, P =0.005; U: 36.2 vs. M: 24.2 vs. O: 26.8, P =0.001; respectively). Patients overcorrected at T10-L2 experienced higher rates of proximal junctional failure (U: 16.0% vs. M: 15.6% vs. O: 32.8%, P <0.001) and had greater posterior inclination of the upper instrumented vertebrae (U: -9.2±9.4° vs. M: -9.6±9.1° vs. O: -12.2±10.0°, P <0.001), whereas undercorrection at these levels led to higher rates of revision for implant failure (U: 14.2% vs. M: 7.3% vs. O: 6.4%, P =0.025). CONCLUSIONS: Patients undergoing fusion for adult spinal deformity suffer higher rates of proximal junctional failure with overcorrection and increased rates of implant failure with undercorrection based on normative segmental lordosis. LEVEL OF EVIDENCE: Level IV.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.012
GPT teacher head0.293
Teacher spread0.281 · 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".

Quick stats

Citations25
Published2024
Admission routes1
Has abstractyes

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