Immunological Emergency in Neonate: Case Report and Role of Early Screening
Bibliographic record
Abstract
Healthy looking newborns may have severe combined immunodeficiency (SCID), and neonatologists frequently are the first physicians to encounter these patients. Physicians usually have a high index of suspicion for this condition in presence of certain risk factors (unexplained infants' deaths, consanguinity); however, >80% of infants with SCID have no positive family history. A timely diagnosis of this condition is crucial in decreasing both mortality and morbidity. The only way to detect SCID prior to the onset of infections is newborn screening (NBS). In term infants, NBS has 99.99% sensitivity for SCID, with no false negatives. In preterm infants, screening is less accurate due to a lack of standard T cell receptor excision circle (TREC) values in this age group. We report a case of SCID in term infants born to consanguineous parents who were presented with clinical and laboratory findings of erythroderma, severe infection, failure to thrive, eosinophilia, and elevated immunoglobulin E (IgE) together with immunodeficiency. A timely diagnosis was followed by successful hematopoietic stem cell transplantation (HSCT) therapy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| 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".