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Record W2075029563 · doi:10.1080/10640260500403915

How Should the Clinician Evaluate and Manage the Cardiovascular Complications of Anorexia Nervosa?

2006· article· en· W2075029563 on OpenAlexaff
Kim McCallum, Ovidio Bermudez, Chris L. Ohlemeyer, Edward P. Tyson, Maria G. Portilla, Barbara Ferdman

Bibliographic record

VenueEating Disorders · 2006
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsMcGill University
Fundersnot available
KeywordsAnorexia nervosaMalnutritionMedicinePsychiatryIntensive care medicineEating disordersAnorexiaInternal medicine

Abstract

fetched live from OpenAlex

Five to twenty percent of patients with anorexia nervosa die from their illness. One half of those patients die of medical complications (Steinhavsen, 2002). Malnutrition, dehydration, and electrolyte abnormalities may precipitate death by inducing heart failure or fatal arrhythmias. Patients and their families commonly call upon physicians to evaluate acute and ongoing risks of malnutrition and purging behaviors. Concerns about medical compromise currently tend to determine or influence insurance coverage of medical and psychiatric treatment of patients with eating disorders. There is very limited published data to guide clinicians in the evaluation, ongoing monitoring, or treatment. Surprisingly, no consensus exists regarding recommendations for either the ongoing evaluation of cardiac parameters or the clinical implications of common 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)0.001
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 score0.107
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.042
GPT teacher head0.322
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 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

Citations25
Published2006
Admission routes1
Has abstractyes

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