How Should the Clinician Evaluate and Manage the Cardiovascular Complications of Anorexia Nervosa?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".