MétaCan
Menu
Back to cohort
Record W2419483798 · doi:10.2310/7750.2013.13075

Hospitalizations for Cellulitis in Canada: A Database Study

2014· article· en· W2419483798 on OpenAlexaffabout
Akerke Baibergenova, Aaron M. Drucker, Neil H. Shear

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineCellulitisDatabaseMEDLINEIntensive care medicineDermatology

Abstract

fetched live from OpenAlex

BACKGROUND: Cellulitis is the skin disease most commonly responsible for emergency department visits and inpatient admissions. OBJECTIVE: To determine factors associated with prolonged admissions and mortality in inpatients with cellulitis. METHODS: Data on patients with an admission diagnosis of cellulitis from 2004 to 2008 in the Canadian Discharge Abstract Database were analyzed. Factors associated with mortality and prolonged hospital stay (> 7 days) were analyzed in univariate and multivariate analysis through logistic regression. RESULTS: During the study period, 65,454 patients were hospitalized for cellulitis. Factors associated with prolonged admission included admission to or consultation by a surgical service (OR 2.30, 95% CI 2.17-2.43) and dermatology consultation (OR 4.50, 95% CI 3.92-5.17). Factors associated with mortality included surgical (OR 1.35, 95% CI 1.03-1.76) or infectious disease (OR 1.75, 95% CI 1.39-2.21) consultation. CONCLUSION: Misdiagnosis of cellulitis, suggested by the use of consulting services, may play a role in the morbidity and mortality of cellulitis 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.009
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.280
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Cutaneous Medicine and SurgerySame topicStreptococcal Infections and TreatmentsFrench-language works237,207