Prevalence and Characteristics of Intracranial and Extracranial Hemorrhages in Neonates with Hypoxic Ischemic Encephalopathy (HIE)
Bibliographic record
Abstract
Abstract BACKGROUND: Intracranial hemorrhages (ICH) and extracranial hemorrhages(ECH) are not uncommon in neonates with HIE. The risk factors of hemorrhages and their association with HIE severity and other therapeutic interventions are unclear. OBJECTIVES: To examine the prevalence and risk factors associated with ICH and ECH in neonates with HIE. DESIGN/METHODS: A retrospective cohort study of neonates admitted with HIE from September 2011 to October 2015 in a level III NICU. ICH[mainly subdural(SDH), intraventricular (IVH), intraparenchymal (IPH)] and ECH [mainly subgaleal(SGH) and cephalhematoma] were diagnosed by MRI.Perinatal and neonatal characteristics were examined, including mode of delivery, outborn status, HIE staging(using modified Sarnat scoring), therapeutic hypothermia(TH), clinical/EEG seizures, hypo/hypercarbia, inotrope use, thrombocytopenia-mild, moderate, severe(platelet count 100-150, 50-100, 1.8, activated partial thromboplas-tin time(aPTT)>45 sec, fibrinogen RESULTS: Number of HIE patients,n=157; median gestation 40 weeks(IQR 38-40); outborn=104(66%);TH used=103(66%);MRI brain done=138. . Prevalence of SDH,IPH,IVH and SGH were 47,22,9,9 (34%,16%,6.5%,6.5%) respectively. There was no significant increase in hemorrhage with mode of delivery except instrumentation, seizures, hypo/ hypercarbia, severe thrombocytopenia or deranged coagulation. Instrumental delivery significantly increased the prevalence of IPH and SGH. All hemorrhages except cephalhematoma increased with severity of HIE staging, but not with MRI severity. In the logistic regression analysis, use of dopamine was associated with increased risk of IPH(OR 2.94; 95% CI 1.42, 12.08) and trended towards increased risk of IVH (OR 4.49; 95% CI 0.98, 20.6). CONCLUSION: SDH followed by IPH are the common ICH. Despite being frequent, thrombocytopenia and deranged coagulation did not increase the risk of ICH or ECH in HIE; dopamine use associated with significant increase in the risk of IPH.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".