Intestinal Crises in the Newborn
Bibliographic record
Abstract
Background: Vascular accidents are generally considered to play a role in the pathogenesis of necrotizing enterocolitis (NEC) and major gastrointestinal disorders such as intestinal atresia/gastroschisis.Using a new non-invasive technique, sidestream darkfield imaging (SDF), the microcirculation in neonates with NEC and the mesenteric circulation during laparotomy in neonates with NEC and intestinal atresia/gastroschisis was evaluated.Methods: This prospective study was subdivided in 2 parts: pre-operative and intraoperative measurements.Pre-operative measurements were performed in the armpit of neonates with NEC.Intra-operative measurements were performed on the mesenteric border of the intestines at standardized places (necrotic and non-affected intestinal tissue).SDF images were analyzed in an automated vascular analysis program (vessel density and blood flow); statistical analysis was performed in SPSS 17.A P value <0.01 was considered statistically significant.Results: 32 patients were included; 15 NEC patients (6 also measured pre-operatively), and 17 patients with gastroschisis (n=8), atresia (n=4), and other (n=5).In the NEC group, pre-operative vessel density and blood flow did not decrease in the days before surgery.During surgery, no significant differences were found in the vessel density and blood flow of affected (necrotic) and non-affected tissue.Vessel density was lower, although not significant, in the non-affected intestinal tissue of the NEC group (4.4 mm/mm 2 ) compared with the gastrointestinal disorders group (7.8 mm/mm 2 ).In gastroschisis no significant differences were found.Atresia patients had a decreased vessel density and blood flow in the atretic part compared with the non-affected tissue.Conclusions: SDF cannot be used to predict which neonates will need surgery for NEC.We did find a difference in the mesenteric perfusion of non-affected intestinal tissue during surgery as a potential new biomarker to determine how much intestinal tissue needs to be resected at laparotomy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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 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".