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Record W100163474 · doi:10.1155/2007/658762

Pain Characteristics and Demographics of Patients Attending a University‐Affiliated Pain Clinic in Toronto, Ontario

2007· article· en· W100163474 on OpenAlexaffabout
Angela Mailis, Balaji Yegneswaran, S. Fatima Lakha, Keith Nicholson, Amanda Steiman, Danny Siu‐Chun Ng, Marios Papagapiou, Margarita Umana, Tea Cohodarevic, Mateusz Zurowski

Bibliographic record

VenuePain Research and Management · 2007
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsToronto General HospitalToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineReferralObservational studyPhysical therapyDemographicsChronic painPopulationFamily medicineInternal medicineDemography

Abstract

fetched live from OpenAlex

BACKGROUND: Pain clinics tend to see more complex chronic pain patients than primary care settings, but the types of patients seen may differ among practices. OBJECTIVE: The aim of the present observational study was to describe the pain and demographic characteristics of patients attending a university-affiliated tertiary care pain clinic in Toronto, Ontario. METHODS: Data were collected on 1242 consecutive new patients seen over a three-year period at the Comprehensive Pain Program in central Toronto. RESULTS: Musculoskeletal problems affecting large joints and the spine were the predominant cause of pain (more prevalent in women), followed by neuropathic disorders (more prevalent in men) in patients with recognizable physical pathology. The most affected age group was in the 35- to 49-year age range, with a mean pain duration of 7.8 years before the consultation. While 77% of the Comprehensive Pain Program patients had relevant and detectable physical pathology for pain complaints, three-quarters of the overall study population also had significant associated psychological or psychiatric comorbidity. Women, in general, attended the pain clinic in greater numbers and had less apparent physical pathology than men. Finally, less than one in five patients was employed at the time of referral. CONCLUSIONS: The relevance of the data in relation to other pain clinics is discussed, as well as waiting lists and other barriers faced by chronic pain patients, pain practitioners and pain facilities in Ontario and Canada.

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)0.022
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.001
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 head0.026
GPT teacher head0.326
Teacher spread0.300 · 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 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

Citations54
Published2007
Admission routes2
Has abstractyes

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