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Record W2314198900 · doi:10.1097/brs.0000000000001020

Radiographical and Implant-Related Complications in Adult Spinal Deformity Surgery

2015· article· en· W2314198900 on OpenAlexaff
Alexandra Sorocéanu, Bassel G. Diebo, Douglas C. Burton, Justin S. Smith, Vedat Deviren, Christopher I. Shaffrey, Han Jo Kim, Gregory M. Mundis, Christopher P. Ames, Thomas J. Errico, Shay Bess, Richard A. Hostin, Robert A. Hart, Frank J. Schwab, Virginie Lafage

Bibliographic record

VenueSpine · 2015
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineOswestry Disability IndexSurgeryScoliosisQuality of life (healthcare)Spinal fusionIncidence (geometry)ImplantProspective cohort studyKyphosisUnivariate analysisDeformityLogistic regressionSpinal deformityMultivariate analysisPhysical therapyRadiographyInternal medicineLow back pain

Abstract

fetched live from OpenAlex

STUDY DESIGN: A multicenter, prospective review of surgical patients with adult spine deformity. OBJECTIVE: Assessment of the incidence, risk factor, and impact of radiographical and implant-related complications (RIC) on health-related quality of life measures. SUMMARY OF BACKGROUND DATA: This study provides assessment of the incidence of RIC in adult spinal deformity surgery and impact of these complications on need for reoperation. Risk factors for development of RIC are also assessed, as well as the impact of these complications on health-related quality of life (HRQOL) outcomes measures. METHODS: A multicenter, prospective database of surgical patients with adult spinal deformity was reviewed. All patients with complete 2-year follow-up were included. HRQOL was measured using the Oswestry Disability Index, General Health Survey (36-Item Short Form Health Survey [SF-36]), and Scoliosis Research Society-22 (SRS-22r) at baseline, 6 weeks, 1 year, and 2 years postoperatively. Univariate testing was performed as appropriate. Multivariate logistic regression modeling was used to determine independent predictors of RIC. Multivariate repeated-measures mixed models were used to examine HRQOL, accounting for confounders. RESULTS: A total of 245 patients met inclusion criteria. The incidence of RIC was 31.7% and 52.6% of those patients required reoperation. Rod breakage accounted for 47% of the implant-related complications, and proximal junctional kyphosis accounted for 54.5% of radiographical complications. Univariate analysis identified the following potential risk factors for RIC: weight, American Society of Anesthesiologists score, revision, stopping the fusion in the lower thoracic spine, worse SRS-Schwab classification modifiers (pelvic tilt++, pelvic incidence minus lumbar lordosis++, sagittal vertical axis++), higher T1 spinopelvic inclination, and higher T1 slope. Independent predictors of RIC as identified on multivariate logistic regression included American Society of Anesthesiologists (odds ratio: 1.75, P = 0.029) and sagittal vertical axis modifier ++ (odds ratio 3.43, P = 0.0001). The RIC and no RIC groups each experienced significant improvement over time, as measured on the Oswestry Disability Index (P = 0.0001), SF-36 (P = 0.0001), and SRS-22r (P = 0.0001). However, the rate of improvement over time was less for patients with RIC (SRS-22r P = 0.043, SF-36 P = 0.0001). CONCLUSION: This study identified that nearly one-third of patients undergoing adult spinal deformity surgery experienced a radiographical or implant-related complication, and that just more than one-half of these patients experiencing complication required a reoperation within 2 years of surgery. These complications significantly affected HRQOL measures. Baseline patient characteristics and parameters of the SRS-Schwab classification can be used to help identify those patients at greater risk. LEVEL OF EVIDENCE: 3.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.044
GPT teacher head0.312
Teacher spread0.267 · 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".

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Citations175
Published2015
Admission routes1
Has abstractyes

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