Clinical Presentation, Prognostic Factors, and Outcome in Neutropenic Enteropathy of Childhood Leukemia
Bibliographic record
Abstract
Leukemia patients are at risk for neutropenic enteropathy (NEP) because of the effects of intensified chemotherapy. Medical records of 18 patients having 20 episodes of NEP were reviewed retrospectively. Primary diagnosis was acute lymphoblastic leukemia in 12 and myeloblastic leukemia in 6 cases. According to prognosis, 3 patients were in the standard-risk group, 6 in the moderate-risk group, and 9 in the high-risk group. Ultrasonography detected increased bowel wall thickness in 6 patients. Abdominal x-ray revealed air-fluid levels (n=8), pneumatosis intestinalis, pneumoperitoneum (n=1), and portal venous gas (n=1). All patients received medical treatment, and 1 with unrelieved hematochezia required resection of the cecum. Two cases with appendicitis and another 1 with pneumoperitoneum responded to antibiotics and recovered without surgery. The mortality rate was 30% and related to sepsis-induced complications. The presence of hypokalemia, hypoalbuminemia, metabolic acidosis, and admission to the intensive care unit were more common in patients with mortality (P=0.01). In conclusion, NEP should be kept in mind as a treatable but potentially lethal complication of childhood leukemia. Radiologic findings should be interpreted in conjunction with clinical picture. A conservative approach should be used in all cases but surgery can be considered in some situations.
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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 | 0.004 |
| 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".