Retrospective analysis of hypophosphatemia rates and other clinical parameters in patients with eating disorders
Bibliographic record
Abstract
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/m2, and 16.1 (SD = 1.9) kg/m2 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.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".