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Record W3112173731 · doi:10.1093/nop/npaa045

Management of recurrent or progressive spinal metastases: reirradiation techniques and surgical principles

2020· article· en· W3112173731 on OpenAlexaff
Rupesh Kotecha, Nicolas Dea, Jay Detsky, Arjun Sahgal

Bibliographic record

VenueNeuro-Oncology Practice · 2020
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsSunnybrook Health Science CentreVancouver General HospitalHealth Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsMedicineRadiation therapyDiseaseNeurosurgeryIntensive care medicinePalliative careSurgeryInternal medicineNursing

Abstract

fetched live from OpenAlex

With the growing incidence of new cases and the increasing prevalence of patients living longer with spine metastasis, a methodological approach to the management of patients with recurrent or progressive disease is increasing in relevance and importance in clinical practice. As a result, disease management has evolved in these patients using advanced surgical and radiotherapy technologies. Five key goals in the management of patients with spine metastases include providing pain relief, controlling metastatic disease at the treated site, improving neurologic deficits, maintaining or improving functional status, and minimizing further mechanical instability. The focus of this review is on advanced reirradiation techniques, given that the majority of patients will be treated with upfront conventional radiotherapy and further treatment on progression is often limited by the cumulative tolerance of nearby organs at risk. This review will also discuss novel surgical approaches such as separation surgery, minimally invasive percutaneous instrumentation, and laser interstitial thermal therapy, which is increasingly being coupled with spine reirradiation to maximize outcomes in this patient population. Lastly, given the complexities of managing recurrent spinal disease, this review emphasizes the importance of multidisciplinary care from neurosurgery, radiation oncology, medical oncology, neuro-oncology, rehabilitation medicine, and palliative care.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.075
GPT teacher head0.393
Teacher spread0.318 · 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 designNot applicable
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

Citations14
Published2020
Admission routes1
Has abstractyes

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