Safety evaluation of valproate on bone mineral density and bone metabolism in children with epilepsy
Bibliographic record
Abstract
Objective To evaluate the safety of valproate (VPA) on bone mineral density and bone metabolism in children with epilepsy. Methods Retrieve relevant research from online databases (January 1, 1980-March 1, 2018) as PubMed, EBMASE/SCOPUS and Cochrane Library with key words: epilepsy, bone, child. Selection of studies was performed according to pre-designed inclusion and exclusion criteria. Quality of studies was evaluated by using Newcastle-Ottawa Scale (NOS). All data were pooled by RevMan 5.2 software for Meta?analysis. Results The research enrolled 1455 articles, from which 13 studies with NOS score ≥ 6 were chosen after excluding duplicates and those not meeting the inclusion criteria. A total of 683 children with epilepsy using VPA and 436 children in control group were included. Meta-analysis showed that comparing with control group, bone mineral density of lumbar (BMDL) in children treated with VPA has no significant difference (MD = -0.019, 95% CI: -0.044-0.006; P = 0.140), but there was a significant decrease in bone mineral density of femur (BMDF; MD = - 0.037, 95%CI: -0.069- -0.005, P = 0.020). There was no significant change in serum calcium (SMD = -0.284, 95% CI: -0.951-0.382; P = 0.400), phosphorus (SMD = - 0.164, 95%CI: -0.457-0.129; P = 0.270), alkaline phosphatase (ALP; SMD = 0.363, 95%CI: -0.294-1.020, P = 0.280), parathyroid hormone (PTH; SMD = 0.102, 95%CI: -0.291-0.495, P = 0.610) and 25-hydroxy vitamin D [25(OH)D; SMD = -0.104, 95%CI：-0.620-0.413, P = 0.690] in bone metabolic markers. Sensitivity analysis showed Meta-anlaysis of BMDF, serum phosphorus and 25(OH)D was unstable, therefore, it should be cautious when explaining the results. Conclusions VPA has less effect on bone mineral density and bone metabolism, but for children with epilepsy using VPA, their BMDF should be monitored. DOI: 10.3969/j.issn.1672-6731.2018.06.005
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 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".