Macrosomia and haemodynamic instability may represent risk factors for subcutaneous fat necrosis in asphyxiated newborns treated with hypothermia
Bibliographic record
Abstract
AIM: To identify additional risk factors other than asphyxia and hypothermia in newborns developing subcutaneous fat necrosis (SCFN). METHODS: We conducted a prospective cohort study of all term asphyxiated newborns treated with hypothermia from 2008 to 2015. The presence and location of SCFN were recorded at the time of discharge or at follow-up visits. To identify the risk factors for developing SCFN, we compared the perinatal characteristics of those newborns who developed SCFN with those who did not. RESULTS: The newborns developing SCFN had significantly higher birthweights compared with those newborns who did not develop SCFN. Among the newborns with a birthweight equal or superior to the 90th percentile, those who developed SCFN had a significantly higher use of inotropic support and higher maximum troponin levels during their initial hospitalisation. CONCLUSION: A higher birthweight represented an independent risk factor for developing SCFN in asphyxiated newborns treated with hypothermia. When macrosomia is present, other risk factors related to haemodynamic instability during the initial hospitalisation may also increase the risk of developing SCFN.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".