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Record W4224132056 · doi:10.3171/2022.2.spine211210

Surgical outcomes of patients who fail to reach minimal clinically important differences: comparison of minimally invasive versus open transforaminal lumbar interbody fusion

2022· article· en· W4224132056 on OpenAlexaffabout

Bibliographic record

VenueJournal of Neurosurgery Spine · 2022
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsUniversité LavalMcGill UniversityUniversity of CalgaryUniversity of ManitobaWestern UniversityUniversity of OttawaCanada East Spine CentreDalhousie UniversityUniversity of TorontoVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMinimal clinically important differenceSpondylolisthesisLumbarDegenerative diseaseDegenerative disc diseaseBack painSpinal fusion

Abstract

fetched live from OpenAlex

OBJECTIVE: Treatment of degenerative lumbar diseases has been shown to be clinically effective with open transforaminal lumbar interbody fusion (O-TLIF) or minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF). Despite this, a substantial proportion of patients do not meet minimal clinically important differences (MCIDs) in patient-reported outcomes (PROs). The objectives of this study were to compare the proportions of patients who did not meet MCIDs after O-TLIF and MIS-TLIF and to determine potential clinical factors associated with failure to achieve MCID. METHODS: The authors performed a retrospective analysis of consecutive patients who underwent O-TLIF or MIS-TLIF for lumbar degenerative disorders and had been prospectively enrolled in the Canadian Spine Outcomes and Research Network. The authors analyzed the Oswestry Disability Index (ODI) scores, physical and mental component summary scores of SF-12, numeric rating scale (NRS) scores for leg and back pain, and EQ-5D scores of the patients in each group who did not meet the MCID of ODI at 2 years postoperatively. RESULTS: In this study, 38.8% (137 of 353) of patients in the O-TLIF cohort and 41.8% (51 of 122) of patients in the MIS-TLIF cohort did not meet the MCID of ODI at 2 years postoperatively (p = 0.59). Demographic variables and baseline PROs were similar between groups. There were improvements across the PROs of both groups through 2 years, and there were no differences in any PROs between the O-TLIF and MIS-TLIF cohorts. Multivariable logistic regression analysis demonstrated that higher baseline leg pain score (p = 0.017) and a diagnosis of spondylolisthesis (p = 0.0053) or degenerative disc disease (p = 0.022) were associated with achieving the MCID at 2 years after O-TLIF, whereas higher baseline leg pain score was associated with reaching the MCID after MIS-TLIF (p = 0.038). CONCLUSIONS: Similar proportions of patients failed to reach the MCID of ODI at 2 years after O-TLIF or MIS-TLIF. Higher baseline leg pain score was predictive of achieving the MCID in both cohorts, whereas a diagnosis of spondylolisthesis or degenerative disc disease was predictive of reaching the MCID after O-TLIF. These data provide novel insights for patient counseling and suggest that either MIS-TLIF or O-TLIF does not overcome specific patient factors to mitigate clinical success or failure in terms of the intermediate-term PROs associated with 1- to 2-level lumbar fusion surgical procedures for degenerative pathologies.

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)0.004
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.071
GPT teacher head0.372
Teacher spread0.301 · 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

Citations7
Published2022
Admission routes2
Has abstractyes

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