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Record W4385460913 · doi:10.1177/17557380231191147

Cauda equina syndrome: Recognising ‘red flags’ for back pain in primary care

2023· article· en· W4385460913 on OpenAlexaff
John T Williams, Dr Henry Poon, Dr James Pumphrey, Dr Narayani Kathirgamakarthigeyan, Mr Bahram Fakouri, Mr Jaykar R. Panchmatia

Bibliographic record

VenueInnovAiT Education and inspiration for general practice · 2023
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsCauda equina syndromeMedicineReferralPrimary careCauda equinaBack painPresentation (obstetrics)Low back painPhysical therapyPediatricsSurgeryFamily medicinePathologyAlternative medicinePsychiatry

Abstract

fetched live from OpenAlex

Cauda equina syndrome is a rare, but potentially devastating condition caused by compression of the lumbosacral nerve roots, usually due to a massive disc herniation. Missed or delayed diagnosis leads to lower limb paralysis with bowel, bladder and sexual dysfunction. The aims of the article are to describe the pathophysiology, epidemiology, typical presentation, diagnostic features and red flag symptoms, presented in line with the RCGP curriculum topic guide. We have included guidance for GPs undertaking clinical assessments, including telephone appointments. This article also includes referral pathways to specialist services, long-term follow-up and community support services for these patients.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.869
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.342
Teacher spread0.314 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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