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Record W2529090292 · doi:10.3171/2016.3.focus1665

Predicting the minimum clinically important difference in patients undergoing surgery for the treatment of degenerative cervical myelopathy

2016· article· en· W2529090292 on OpenAlex

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

VenueNeurosurgical FOCUS · 2016
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsOntario Tech UniversityToronto Western HospitalUniversity Health Network
FundersNational Institute for Health and Care Research
KeywordsMinimal clinically important differenceMedicineMyelopathyPoisson regressionUnivariateSurgeryLinear regressionInternal medicinePhysical therapyRandomized controlled trialMultivariate statisticsPopulationStatistics

Abstract

fetched live from OpenAlex

OBJECTIVE The minimum clinically important difference (MCID) is defined as the minimum change in a measurement that a patient would identify as beneficial. Before undergoing surgery, patients are likely to inquire about the ultimate goals of the operation and of their chances of experiencing meaningful improvements. The objective of this study was to define significant predictors of achieving an MCID on the modified Japanese Orthopaedic Association (mJOA) scale at 2 years following surgery for the treatment of degenerative cervical myelopathy (DCM). METHODS Seven hundred fifty-seven patients were prospectively enrolled in either the AOSpine North America or International study at 26 global sites. Fourteen patients had a perfect preoperative mJOA score of 18 and were excluded from this analysis (n = 743). Data were collected for each participating subject, including demographic information, symptomatology, medical history, causative pathology, and functional impairment. Univariate log-binominal regression analyses were conducted to evaluate the association between preoperative clinical factors and achieving an MCID on the mJOA scale. Modified Poisson regression using robust error variances was used to create the final multivariate model and compute the relative risk for each predictor. RESULTS The sample consisted of 463 men (62.31%) and 280 women (37.69%), with an average age of 56.48 ± 11.85 years. At 2 years following surgery, patients exhibited a mean change in functional status of 2.71 ± 2.89 points on the mJOA scale. Of the 687 patients with available follow-up data, 481 (70.01%) exhibited meaningful gains on the mJOA scale, whereas 206 (29.98%) failed to achieve an MCID. Based on univariate analysis, significant predictors of achieving the MCID on the mJOA scale were younger age; female sex; shorter duration of symptoms; nonsmoking status; a lower comorbidity score and absence of cardiovascular disease; and absence of upgoing plantar responses, lower-limb spasticity, and broad-based unstable gait. The final model included age (relative risk [RR] 0.924, p < 0.0001), smoking status (RR 0.837, p = 0.0043), broad-based unstable gait (RR 0.869, p = 0.0036), and duration of symptoms (RR 0.943, p = 0.0003). CONCLUSIONS In this large multinational prospective cohort, 70% of patients treated surgically for DCM exhibited a meaningful functional gain on the mJOA scale. The key predictors of achieving an MCID on the mJOA scale were younger age, shorter duration of symptoms, nonsmoking status, and lack of significant gait impairment.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.167
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.032
GPT teacher head0.286
Teacher spread0.254 · 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