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Record W1916495479 · doi:10.1089/jpm.2015.28999.sml

ACR Appropriateness Criteria <sup>®</sup> Metastatic Epidural Spinal Cord Compression and Recurrent Spinal Metastasis

2015· article· en· W1916495479 on OpenAlexaff
Simon S. Lo, Samuel Ryu, Eric L. Chang, Nicholas Galanopoulos, Joshua Jones, Edward Y. Kim, Charlotte Dai Kubicky, Charles P. Lee, Peter S. Rose, Arjun Sahgal, Andrew E. Sloan, Bin S. Teh, Bryan Traughber, Catherine Van Poznak, Andrew D. Vassil

Bibliographic record

VenueJournal of Palliative Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineSpinal cord compressionDiseaseSpinal diseaseSpinal canalIntervention (counseling)Physical therapySpinal cordIntensive care medicineSurgeryLumbarInternal medicineNursing

Abstract

fetched live from OpenAlex

Metastatic epidural spinal cord compression (MESCC) is an oncologic emergency and if left untreated, permanent paralysis will ensue. The treatment of MESCC is governed by disease, patient, and treatment factors. Patient's preferences and goals of care are to be weighed into the treatment plan. Ideally, a patient with MESCC is evaluated by an interdisciplinary team promptly to determine the urgency of the clinical scenario. Treatment recommendations must take into consideration the risk-benefit profiles of surgical intervention and radiotherapy for the particular individual's circumstance, including neurologic status, performance status, extent of epidural disease, stability of the spine, extra-spinal disease status, and life expectancy. In patients with high spinal instability neoplastic score (SINS) or retropulsion of bone fragments in the spinal canal, surgical intervention should be strongly considered. The rate of development of motor deficits from spinal cord compression may be a prognostic factor for ultimate functional outcome, and should be taken into account when a treatment recommendation is made. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every three years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.161
GPT teacher head0.423
Teacher spread0.262 · 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 designOther design
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

Citations52
Published2015
Admission routes1
Has abstractyes

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