83: Preoperative Metabolic Acidosis in Infants with Gastroschisis
Bibliographic record
Abstract
It is unclear if infants with gastroschsis develop metabolic acidosis as a result of prolonged intrauterine gut compromise or dehydration secondary to increased fluid loss. There is little literature regarding postnatal preoperative management of these infants. To assess the frequency of preoperative metabolic acidosis in infants with gastroschisis and to investigate whether this acidosis reflects the severity of gut compromise as assessed by time to feeding tolerance. All infants with gastroschisis born between May 2005 and April 2013 in a single tertiary care centre were reviewed. Metabolic acidosis was defined by the presence of pH <7.26 and serum bicarbonate (HCO3) <18.5 or base excess (BE)< −8.5 mmol/L. Infants with birth depression were excluded. Maternal and neonatal data were collected. Frequency of preoperative metabolic acidosis and its correlation with time to first feeding, time to reach full feeds and GPS (Gastroschisis Prognostic Score, Cowan et al 2012) were investigated. Sixty infants were identified, 11 were excluded (birth depression or lack of preoperative blood gases). Twenty infants (41%) had pH <7.26, eight (16%) had serum HCO3 <18.5 mmol/L, and 10 (20%) had BE <−8.5 mmol/L at a median age of 1.2 h. Median preoperative total fluid intake was 130 ml/kg/d and median age at repair was 4 h (Figure). No correlation was found between metabolic acidosis or serum lactate and age at first feed, age at full feeds or Gastroschisis Prognostic Score (Table). By logistic regression analysis, only lower fluid intake (<120 mL/kg/day) was predictive of early first feeding (OR 3.43 [95% CI 1.05 to 11.2]). Preoperative metabolic acidosis was identified in a significant proportion of patients with gastroschisis despite high fluid intake. However, it does not appear to be related to the degree of gut compromise. The practice of providing high fluid to these infants needs more investigation.
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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 | 0.003 |
| 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) | 0.002 | 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".