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Record W2921261758 · doi:10.1093/neuros/nyz016

Indicators for Nonroutine Discharge Following Cervical Deformity-Corrective Surgery: Radiographic, Surgical, and Patient-Related Factors

2019· article· en· W2921261758 on OpenAlexaff
Cole Bortz, Peter G. Passias, Frank A. Segreto, Samantha R. Horn, Virginie Lafage, Justin S. Smith, Breton Line, Gregory M. Mundis, Khaled M. Kebaish, Michael P. Kelly, Themistocles S. Protopsaltis, Daniel M. Sciubba, Alexandra Sorocéanu, Eric O. Klineberg, Douglas C. Burton, Robert A. Hart, Frank J. Schwab, Shay Bess, Christopher I. Shaffrey, Christopher P. Ames

Bibliographic record

VenueNeurosurgery · 2019
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineDeformityLogistic regressionRadiographySurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Nonroutine discharge, including discharge to inpatient rehab and skilled nursing facilities, is associated with increased cost-of-care. Given the rising prevalence of cervical deformity (CD)-corrective surgery and the necessity of value-based healthcare, it is important to identify indicators for nonroutine discharge. OBJECTIVE: To identify factors associated with nonroutine discharge after CD-corrective surgery using a statistical learning algorithm. METHODS: A retrospective review of patients ≥18 yr with discharge and baseline (BL) radiographic data. Conditional inference decision trees identified factors associated with nonroutine discharge and cut-off points at which factors were significantly associated with discharge status. A conditional variable importance table used nonreplacement sampling set of 10 000 conditional inference trees to identify influential patient/surgical factors. The binary logistic regression indicated odds of nonroutine discharge for patients with influential factors at significant cut-off points. RESULTS: Of 138 patients (61 yr, 63% female) undergoing surgery for CD (8 ± 5 levels; 49% posterior approach, 16% anterior, and 35% combined), 29% experienced nonroutine discharge. BL cervical/upper-cervical malalignment showed the strongest relationship with nonroutine discharge: C1 slope ≥ 14°, C2 slope ≥ 57°, TS-CL ≥ 57°. Patient-related factors associated with nonroutine discharge included BL gait impairment, age ≥ 59 yr and apex of CD primary driver ≥ C7. The only surgical factor associated with nonroutine discharge was fusion ≥ 8 levels. There was no relationship between nonhome discharge and reoperation within 6 mo or 1 yr (both P > .05) of index procedure. Despite no differences in BL EQ-5D (P = .946), nonroutine discharge patients had inferior 1-yr postoperative EQ-5D scores (P = .044). CONCLUSION: Severe preoperative cervical malalignment was strongly associated with nonroutine discharge following CD-corrective surgery. Age, deformity driver, and ≥ 8 level fusions were also associated with nonroutine discharge and should be taken into account to improve patient counseling and health care resource allocation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0000.000

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 head0.013
GPT teacher head0.249
Teacher spread0.237 · 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.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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