Diabetes During Diarrhea-Associated Hemolytic Uremic Syndrome
Bibliographic record
Abstract
OBJECTIVE: To quantify the incidence of diabetes during the acute phase of diarrhea-associated hemolytic uremic syndrome (D + HUS) and to identify features associated with its development. RESEARCH DESIGN AND METHODS: A systematic review and meta-analysis of articles assessing diabetes during D + HUS was conducted. Relevant citations were identified from Medline, Embase, and Institute for Scientific Information Citation Index databases. Bibliographies of relevant articles were hand searched. All articles were independently reviewed for inclusion and data abstraction by two authors. RESULTS: Twenty-one studies from six countries were included. Only 2 studies reported a standard definition of diabetes; 14 defined diabetes as hyperglycemia requiring insulin. The incidence of diabetes during the acute phase of D + HUS could be quantified in a subset of 1,139 children from 13 studies (1966-1998, age 0.2-16 years) and ranged from 0 to 15%, with a pooled incidence of 3.2% (95% CI 1.3-5.1, random-effects model, significant heterogeneity among studies, P = 0.007). Children who developed diabetes were more likely to have severe disease (e.g., presence of coma or seizures, need for dialysis) and had higher mortality than those without diabetes. Twenty-three percent of those who developed diabetes acutely died, and 38% of survivors required long-term insulin (median follow-up 12 months). Recurrence of diabetes was possible up to 60 months after initial recovery. CONCLUSIONS: Children with D + HUS should be observed for diabetes during their acute illness. Consideration should be given to long-term screening of D + HUS survivors for diabetes.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".