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Record W2442801385 · doi:10.1017/cjn.2016.234

P.135 Epidemiology of spine infection in patients with history of IV drug use and HIV infection. Possibility of the secondary prevention

2016· article· en· W2442801385 on OpenAlexaffvenueabout
K Meguro, Ryan Meili, Boris Pirlot, UA Ahmad

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2016
Typearticle
Languageen
FieldMedicine
TopicInfectious Diseases and Tuberculosis
Canadian institutionsSaskatoon Medical Imaging
Fundersnot available
KeywordsMedicineIncidence (geometry)EpidemiologyOsteomyelitisRetrospective cohort studyAbscessSurgeryEpidural abscessHuman immunodeficiency virus (HIV)DiscitisPediatricsInternal medicineImmunology

Abstract

fetched live from OpenAlex

Background: One of the major risk factors for spine infection is IV drug use and HIV infection. An increase in these risk factors has coincided with increased rates of spinal infection in Saskatchewan. However, the exact incidence and the clinical significance of spine infection associated with high-risk behavior is poorly understood. Methods: A retrospective review was completed for adult patients with discitis, osteomyelitis, or epidural abscess admitted to the Royal University Hospital, University of Saskatchewan over the last eight years. Results: This study included 176 patients consisting of 41% with discitis, 69% with osteomyelitis and 45% with epidural abscess. Overall mortality was 3% and 16% of patients developed severe disability.40% of patients were intravenous drug users, 45% were hepatitis C positive and 12% were HIV positive. For the initial four years of our study we experienced 72 patients. We experienced 91 cases over the past four years. Geographical analysis showed high incidence areas within the city of Saskatoon. Conclusions: High rates of IV drug use, Hepatitis C, and HIV have important implications in terms of what measures would assist in prevention of this condition. Secondary prevention or early identification of patients may reduce the number of patients who require lengthy admission, surgery and long term care for disablity.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.006
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 head0.026
GPT teacher head0.256
Teacher spread0.230 · 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 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

Citations0
Published2016
Admission routes3
Has abstractyes

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