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Record W1918824460 · doi:10.1111/pme.12427

Particulate and Non-Particulate Steroids in Lumbar Transforaminal Epidural Injections

2014· letter· en· W1918824460 on OpenAlexaff
Rajinikanth Sundara Rajan, Anuj Bhatia

Bibliographic record

VenuePain Medicine · 2014
Typeletter
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineParticulatesLumbarAnesthesiaSurgeryChemistry

Abstract

fetched live from OpenAlex

Dear Editor, We welcome the efforts of El-Yahchouchi et al. [1] on undertaking a retrospective study of a large patient cohort to address the important issue of comparison of efficacy of particulate (triamcinolone and betamethasone) and nonparticulate (dexamethasone) lumbar transforaminal epidural steroid injections (TFESI). The authors conclude that lumbar TFESI of dexamethasone is noninferior to betamethasone and triamcinolone for treatment of radicular pain and that dexamethasone is superior to triamcinolone and betamethasone with regard to pain and functional outcome at 2 months. However, we have several questions regarding their methodology and conclusions of this article. First, particulate steroids were used in 87% (N = 3,162) of their TFESIs, whereas dexamethasone was used in only 13% (N = 481). This is a considerable difference in sample size between the particulate and nonparticulate groups, and it is reflected in the wider …

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.620
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.023
GPT teacher head0.292
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations4
Published2014
Admission routes1
Has abstractyes

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