Subdural hematomas in infants with benign enlargement of the subarachnoid spaces are not pathognomonic for child abuse.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Patients who have benign enlargement of the subarachnoid spaces (BESS) have long been suspected of having an increased propensity for subdural hematomas either spontaneously or as a result of accidental injury. Subdural hematomas in infants are often equated with nonaccidental trauma (NAT). A better understanding of the clinical and imaging characteristics of subdural hematomas that occur either spontaneously or as a result of accidental trauma may help distinguish this group of patients from those who suffer subdural hematomas as a result of NAT. The purpose of this study is to describe the clinical and imaging characteristics of subdural hematomas that occur either spontaneously or as a result of accidental injury in infants with BESS. METHODS: We conducted a retrospective review of all patients with BESS complicated by subdural hematomas evaluated at a single institution from 1998 to 2004. Data concerning the patient's clinical presentation, physical findings, imaging, and management are described. RESULTS: During the study period, 7 patients with BESS complicated by subdural hematoma were identified. Their mean age at identification of the subdural hematoma was 7.4 months of age. In 5 cases, there was no recognized trauma before identification of the subdural hematoma. In 3 cases, baseline CT or MR imaging was available, showing prominent subarachnoid spaces without any evidence of subdural hemorrhage. CONCLUSION: Although suspicious for NAT, subdural hematomas can occur in children either spontaneously or as a result of accidental trauma. Caution must be exercised when investigating for NAT based on the sole presence of subdural hematomas, especially in children who are otherwise well and who have BESS.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".