Mermaid Syndrome: Navigating the Challenges of a Rare Congenital Disorder
Bibliographic record
Abstract
Sirenomelia, or mermaid syndrome, is a rare congenital disorder characterized by the fusion of lower limbs and often associated with multisystem organ dysfunction, resulting in poor survival beyond the neonatal period. We report a case of sirenomelia in a full-term infant born to a 28-year-old primigravida with no significant medical history, gestational diabetes, or teratogenic exposure. The antenatal period was complicated by oligohydramnios, though routine ultrasounds failed to detect the condition. The diagnosis of sirenomelia was only made after delivery by cesarean section, with a compatible-with-life appearance, pulse, grimace, activity, and respiration (APGAR) score. The infant was referred to the pediatric surgical department due to abdominal distension and fused lower limbs, with plans to manage these conditions if the infant survived long-term. During the three-day hospital stay, vomiting was noted, and a babygram confirmed Stocker and Heifetz type IV sirenomelia and distended large bowel. An exploratory laparotomy revealed gross gastrointestinal and genitourinary abnormalities. A sigmoid colostomy was performed to relieve obstruction. Unfortunately, the infant expired shortly after surgery. This case highlights the challenges of prenatal diagnosis and the limited understanding of surgical management in sirenomelia, particularly given the rarity of survival beyond the neonatal period.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".