Evaluating twins at risk for sepsis: The dilemma of the well-appearing co-twin
Bibliographic record
Abstract
Background: Early-onset sepsis is a significant cause of mortality and morbidity in neonates. Currently, there are no recommendations on how to manage a well-appearing co-twin if one twin meets the criteria for evaluation for sepsis. Objective: Review our experience on management of well-appearing co-twins when one twin (index case) is evaluated for sepsis. Methods: Retrospective review of twins born at ≥36 weeks gestation. Index cases were categorized into two groups: (1) Presence of clinical signs of sepsis and no risk factors (RFs), and (2) presence of clinical signs with RF. All co-twins were well-appearing. Clinical presentation, diagnosis, and management are presented for all twins. Results: The study included 33 twin pairs. Septic workup was performed in index cases due to the presence of clinical signs with no RF (66.7%) or clinical signs with RF (33.3%) and all received antibiotics. Septic workup was performed in 18.2% of co-twins when clinical signs but no RFs were present in the index cases and 36.4% of co-twins when clinical signs and RF were present. No cases of sepsis were identified in either twin. Conclusion: Variation in the management of a well-appearing co-twin exists when the other twin is evaluated due to clinical signs of sepsis with or without the presence of RF. Our small dataset suggests that it may be reasonable to defer a septic workup of the well-appearing co-twin; particularly in the absence of RF. A larger study is required to confirm this suggestion.
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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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".