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Record W3107599684 · doi:10.1002/erv.2810

Retrospective analysis of hypophosphatemia rates and other clinical parameters in patients with eating disorders

2020· article· en· W3107599684 on OpenAlexaff
Candice Richardson, Paulina Huniewicz, Georgios Paslakis

Bibliographic record

VenueEuropean Eating Disorders Review · 2020
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of TorontoToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsHypophosphatemiaMedicineAnorexia nervosaEating disordersBody mass indexIntensive care unitRetrospective cohort studyPediatricsRefeeding syndromeInternal medicineMalnutritionPsychiatry

Abstract

fetched live from OpenAlex

Abstract Objective To retrospectively assess medical services of a specialist inpatient eating disorders (EDs) unit. Method We retrospectively evaluated clinical parameters of 288 inpatients classified as ‘moderately’ or ‘significantly’ medically compromised between 1 January 2016 and 30 June 2019. Results We analysed 288 patients (mean age 32.5 [SD = 11.4] years, 96% women, 76% with anorexia nervosa). Average length of stay was 38.4 (SD = 28.4) days. Average admission body mass index (BMI) was 14.8 (SD = 1.8) kg/m 2 , and 16.1 (SD = 1.9) kg/m 2 at 4 weeks. At admission, 82% of patients were considered significantly medically compromised, while 6% were deemed moderately compromised. Only 5% of patients required transfer to intensive care unit. Prevalence of hypophosphatemia was 17.7%; rates did not increase significantly between years despite more assertive re‐feeding processes. There was no association between risk classification at admission and change in BMI at 4 weeks ( F (2,166) = 0.588, p = 0.557). BMI at admission was found to be significantly associated with clinical outcome ( β = 0.92, p < 0.001). Discussion Hypophosphatemia rates did not increase despite more assertive re‐feeding over 3 years. Our results provide support for a model of treatment that simultaneously addresses the medical and psychiatric sequelae of patients with severe EDs.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.032
GPT teacher head0.330
Teacher spread0.299 · 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.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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