Seizures in children after kidney transplantation: Has the risk changed and can we predict who is at greatest risk?
Bibliographic record
Abstract
Children undergoing kidney transplantation are at increased risk for symptomatic seizures with a previously reported incidence of approximately 20%. Little data exist to help predict which children may be at risk. We retrospectively reviewed all children who underwent kidney transplantation evaluation at our center between October 1993 and August 2007 and identified 41 children who had an EEG prior to transplant. Demographic data as well as the following were collected: immunosuppressive medications, developmental status, history of seizures, family history of seizures, post-transplant seizures and EEG results. EEGs were classified as normal or abnormal. Prior to transplantation, one child had a history of febrile seizures and six experienced afebrile seizures. Nine (22%) children identified had an abnormal EEG prior to transplant. In eight cases the EEG was non-epileptiform and in one case was epileptiform. Abnormal EEGs did not correlate with a family history of seizures. Delayed development was noted in seven children and was not associated with an epileptiform EEG. Following kidney transplantation, no child experienced a seizure. Our single center study suggests that current rates of seizures following kidney transplantation are lower than previously reported and that routine EEG as part of the pretransplant evaluation in these children is of limited use to predict those at risk.
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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 | 0.000 |
| 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".