MétaCan
Menu
Back to cohort

Mortality from acquired bullous diseases of skin in Canadian adults 2000–2007

2012· article· en· W1532377614 on OpenAlexaffabout
Akerke Baibergenova, Martin A. Weinstock, Neil H. Shear

Bibliographic record

VenueInternational Journal of Dermatology · 2012
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Bullous Skin Diseases
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBullous pemphigoidMedicineMortality ratePemphigusDermatologyPemphigoidToxic epidermal necrolysisInternal medicineImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Bullous skin diseases are known to be associated with significant morbidity and mortality. There have been no studies on mortality from severe bullous skin diseases in Canada. METHODS: We used mortality data from the Statistics Canada website from 2000 to 2007 for three major bullous skin diseases: bullous pemphigoid; pemphigus; and toxic epidermal necrolysis (TEN). Crude and age-standardized mortality rates were calculated and compared with the corresponding US mortality rates. Linear regression was used to assess time trend and effect of gender and age on mortality rates. RESULTS: During the period of eight years, there were 115 deaths attributed to pemphigoid, 84 to pemphigus, and 44 to TEN. The crude annual mortality rate was the highest for pemphigoid (0.045 per 100,000), followed by pemphigus (0.033), and TEN (0.017). None of these conditions demonstrated significant time trends in mortality rates over the eight-year period, although a trend towards decreasing pemphigus mortality was observed (P = 0.07). No gender difference in mortality was observed, but advanced age was associated with mortality in all three conditions. CONCLUSION: Among bullous skin diseases, pemphigoid is the leading cause of mortality in Canada. This is in contrast to the USA, where TEN is the leading cause of mortality from bullous skin diseases. It is not clear whether differences in healthcare systems explain these findings.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.058
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.010
GPT teacher head0.292
Teacher spread0.282 · 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

Citations16
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of DermatologySame topicAutoimmune Bullous Skin DiseasesFrench-language works237,207