Recurrent Postnatal Infections Are Associated With Progressive White Matter Injury in Premature Infants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Our objective was to identify clinical predictors of progressive white matter injury. METHODS: We evaluated 133 infants of <34 weeks of gestation at birth from 2 university hospitals. Infants underwent MRI twice, initially when in stable condition for transport and again at term-equivalent age or before transfer or discharge. Two neuroradiologists who were blinded to the clinical course graded MRI white matter injury severity by using a validated scale. Potential risk factors were extracted from medical charts. RESULTS: Twelve neonates (9.0%) had progressive white matter injury. In the unadjusted analysis of 10 newborns without Candida meningoencephalitis, recurrent culture-positive postnatal infection and chronic lung disease were associated with progressive white matter injury. Exposure to multiple episodes of culture-positive infection significantly increased the risk of progressive white matter injury. Of the 11 neonates with >1 infection, 36.4% (4 infants) had progressive injury, compared with 5.0% (6 infants) of those with <or=1 infection. Of the 35 infants with chronic lung disease, 17.1% (6 infants) had progressive injury, compared with 4.3% (4 infants) of those without chronic lung disease. After adjustment for gestational age at birth, the association between infection and white matter injury persisted, whereas chronic lung disease was no longer a statistically significant risk factor. CONCLUSIONS: Recurrent postnatal infection is an important risk factor for progressive white matter injury in premature infants. This is consistent with emerging evidence that white matter injury is attributable to oligodendrocyte precursor susceptibility to inflammation, hypoxia, and ischemia.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it