The lasting impacts of relative energy deficiency in sport imposed on pregnancy health outcomes: A survey-based investigation
Bibliographic record
Abstract
BACKGROUND: Relative energy deficiency in sport (REDs) results from exposure to problematic low energy availability. It is a serious condition affecting the health and athletic performance of up to 80% of elite female athletes. REDs is established to have negative short-term effects on reproductive function, but the long-term impact of this condition is unknown. Therefore, we examined the impact of secondary amenorrhea with or without a concurrent diagnosis of REDs on perinatal health outcomes. METHODS: Postpartum individuals (≥18 years of age) completed an online questionnaire that covered demographics, reproductive history (including a diagnosis of REDs or secondary amenorrhea), and maternal/fetal health outcomes. Logistic regression was used to determine the relationship between previously diagnosed REDs or secondary amenorrhea with perinatal health outcomes. RESULTS: A total of 1025 previously pregnant participants completed the survey (33.1 ± 3.4 years, mean ± SD). Prior to pregnancy, 6.1% had been previously diagnosed with REDs and 20.5% had a history with secondary amenorrhea. Individuals diagnosed with REDs had 3.5-times higher odds of having premature labor (odds ratio, (OR) = 3.52, 95% confidence interval (95%CI): 1.26-9.81) and 2.6-times higher odds of preterm delivery (OR = 2.62, 95%CI: 1.05-6.58) compared to those who had not experienced REDs or secondary amenorrhea. However, in individuals who did not have a history of REDs, secondary amenorrhea did not increase the odds of adverse pregnancy or delivery outcomes. CONCLUSION: A history of REDs, but not secondary amenorrhea, may increase the odds of premature labor and preterm delivery.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".