Case Report: A Very Low Birth Weight Female Infant With Congenital Bilateral Periventricular Leukomalacia, Born to a Mother With Coronavirus Disease 2019
Bibliographic record
Abstract
A 26-year-old primipara woman with COVID-19 performed an emergency Cesarean section due to further hypoxemia at 28 weeks 5/7 days gestation. The female neonate was born weighing 1,347 gram with an Apgar score of four at 1 min, three at 5 min, and eight at 10 min. RT-PCR from nasopharyngeal swabs for COVID-19 were performed at birth, 24 h, and 48 h after birth, all of which were negative. On head ultrasound bilateral cystic lesions were found in the anterior horn of the lateral ventricles at birth. A brain magnetic resonance imaging (MRI) test at 56 days of life (corrected 36 weeks and 6/7 days) revealed cystic lesions with T1 low signal, T2 high signal, and T2 Flair high signal around the anterior horn of the lateral ventricle and We diagnose it as Grade 2 periventricular leukomalacia (PVL). She was discharged on day 64 of life, with no abnormality on exam. While the majority of neonates born to women with COVID-19 during pregnancy have favorable outcome, we report a case of a neonate with Grade 2 periventricular leukomalacia and this should prompt clinicians to monitor fetal cerebral function and structure shortly after birth.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".