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Record W1970403250 · doi:10.1002/eat.20191

Weight restoration in a patient with anorexia nervosa on dialysis

2005· article· en· W1970403250 on OpenAlexaff
D. Blake Woodside, Patricia Colton, Randolf Staab, Martin Schreiber, Kalam Sutandar‐Pinnock, Brittany Poynter, Tegan Sacevich

Bibliographic record

VenueInternational Journal of Eating Disorders · 2005
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsWestern UniversityQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsAnorexia nervosaDialysisComplicationMedicineIntensive care medicineAnorexiaWeight gainRenal replacement therapyDiseasePediatricsEating disordersInternal medicineBody weightPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: We report a case of weight restoration in a patient with anorexia nervosa, end-stage renal disease (ESRD) requiring dialysis, and cardiac insufficiency. METHOD: The technical challenges and ethical issues involved in her clinical management are reviewed. Renal insufficiency is a common complication of more severe anorexia nervosa. RESULTS: Progression to renal failure, when it occurs, is most typically a terminal event. There are currently no published guidelines for monitoring the weight gain of patients undergoing dialysis. CONCLUSION: We present a case of a patient who progressed from renal insufficiency to renal failure while in treatment for anorexia nervosa, and who was ultimately successfully weight restored while on renal dialysis.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0040.004
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 head0.010
GPT teacher head0.293
Teacher spread0.283 · 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 designCase report
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

Citations4
Published2005
Admission routes1
Has abstractyes

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