IS BODY FAT PERCENTAGE A GOOD PREDICTOR OF MENSTRUAL RECOVERY IN FEMALES WITH ANOREXIA NERVOSA AFTER WEIGHT RESTORATION? A SYSTEMATIC REVIEW AND EXPLORATORY AND SELECTIVE META-ANALYSIS
Bibliographic record
Abstract
The resumption of menses (ROM) is an important outcome in anorexia nervosa treatment and is considered as a sign of recovery. Identification of relevant factors in its prediction is important in clinical practice. Therefore we aimed to conduct a systematic review and exploratory meta-analysis of the association between total body fat percentage (%BF) and ROM after weight restoration in adolescents and young adults with anorexia nervosa. The study was conducted by adhering to Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. Data were collated using meta-analysis and a narrative approach. Of the 604 articles retrieved, only seven studies comprising a total of 366 adolescent and young adult females with anorexia nervosa met the inclusion criteria and were reviewed, and preliminary results revealed three main findings. Firstly, patients who resumed their menstrual cycle had a significantly higher mean %BF when compared to those who did not, an overall effect confirmed by the meta-analysis (SMD: 3.74, 95% CI: 2.26-5.22). Secondly, %BF was found to be an independent predictor of the ROM in this population and an increase of only one unit of %BF can increase the odds of menstruation by ≈15-20%. Thirdly, despite the paucity of data, a cut-off point of %BF≈21was suggested as the minimum needed for ROM. In conclusion, a higher %BF seems to be associated with the ROM in weight-restored adolescent and young adult females with anorexia nervosa. Its assessment is important in a clinical setting, especially after complete weight restoration. The PROSPERO Registry - A systematic review and meta-analysis of the factors associated with the resumption of the menstrual cycle in females with anorexia nervosa after weight restoration (CRD42019111841).
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 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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.038 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".