MétaCan
Menu
Back to cohort
Record W2187682327 · doi:10.1227/neu.0000000000001151

Clinical and Surgical Predictors of Complications Following Surgery for the Treatment of Cervical Spondylotic Myelopathy

2015· article· en· W2187682327 on OpenAlexaff
Lindsay Tetreault, Gamaliel Tan, Branko Kopjar, Pierre Côté, Paul M. Arnold, Natalia Nugaeva, Giuseppe Barbagallo, Michael G. Fehlings

Bibliographic record

VenueNeurosurgery · 2015
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsOntario Tech UniversityToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineSurgerySpinal surgeryMyelopathySpinal cord

Abstract

fetched live from OpenAlex

BACKGROUND: Surgery for cervical spondylotic myelopathy (CSM) is generally safe and effective. Nonetheless, complications occur in 11% to 38% of patients. Knowledge of important predictors of complications will help clinicians identify high-risk patients and institute prevention and management strategies. OBJECTIVE: To identify clinical and surgical predictors of perioperative complications in CSM patients. METHODS: Four hundred seventy-nine surgical CSM patients were enrolled in the prospective CSM-International study at 16 sites. A panel of physicians reviewed all adverse events and classified each as related or unrelated to surgery. Univariate analyses were performed to determine differences between patients who experienced a perioperative complication and those who did not. A complication prediction rule was developed using multiple logistic regression. RESULTS: Seventy-eight patients experienced 89 perioperative complications (16.25%). On univariate analysis, the major clinical risk factors were ossification of the posterior longitudinal ligament (OPLL) (P = .055), number of comorbidities (P = .002), comorbidity score (P = .006), diabetes mellitus (P = .001), and coexisting gastrointestinal (P = .039) and cardiovascular (P = .046) disorders. Patients undergoing a 2-stage surgery (P = .002) and those with a longer operative duration (P = .001) were at greater risk of perioperative complications. A final prediction model consisted of diabetes mellitus (odds ratio [OR] = 1.96, P = .060), number of comorbidities (OR = 1.20, P = .069), operative duration (OR = 1.07, P = .002), and OPLL (OR = 1.75, P = .040). CONCLUSION: Surgical CSM patients have a higher risk of perioperative complications if they have a greater number of comorbidities, coexisting diabetes mellitus, OPLL, and a longer operative duration. Surgeons can use this information to discuss the risks and benefits of surgery with patients, to plan case-specific preventive strategies, and to ensure appropriate management in the perioperative period. ABBREVIATIONS: BMI, body mass indexCSM, cervical spondylotic myelopathymJOA, modified Japanese Orthopaedic AssociationOPLL, ossification of the posterior longitudinal ligament.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.054
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.094
GPT teacher head0.348
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, 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

Citations44
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueNeurosurgerySame topicCervical and Thoracic MyelopathyFrench-language works237,207