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Record W1481355164 · doi:10.1002/erv.2178

Mortality and Its Predictors in Severe Bulimia Nervosa Patients

2012· article· en· W1481355164 on OpenAlexaff
Caroline Huas, Nathalie Godart, Agnès Caille, Alexandra Pham‐Scottez, Christine Foulon, Snežana M. Divac, Guillaume Lavoisy, Julien‐Daniel Guelfi, Bruno Falissard, Frédéric Rouillon

Bibliographic record

VenueEuropean Eating Disorders Review · 2012
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsSte. Anne's Hospital
Fundersnot available
KeywordsBulimia nervosaEating disordersMedicineStandardized mortality ratioMortality ratePsychiatryDemographyPediatricsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The risk of mortality remains unclear for bulimia nervosa (BN) patients, especially the most severe. The aims of this study were to improve knowledge on BN and mortality. METHODS: With initial evaluation at admission, 258 BN (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) consecutive inpatients were included (1988-2004). Vital status was established from the French national register. Standardized Mortality Ratio (SMR) calculation and bivariate Cox analysis were performed for the hypothesised predictors of mortality. RESULTS: Mean follow-up duration was 10.5 years. Ten deaths were recorded, and the crude mortality ratio was 3.9%; SMR = 5.52 [CI95 (2.64-10.15)]. The majority of deaths were from suicide [6/10, SMR = 30.9 (5.7-68.7)]. The mean age at time of death was 29.6 years. Predictive factors were previous suicide attempt and low minimum BMI. CONCLUSIONS: Severe BN patients are at higher risk of death (mainly suicide) especially if previous suicide attempt or previous low BMI. More studies are needed to confirm these results.

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)0.002
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.041
GPT teacher head0.321
Teacher spread0.280 · 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

Citations69
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Eating Disorders ReviewSame topicEating Disorders and BehaviorsFrench-language works237,207