Effect of methylphenidate on height in pediatric attention-deficit hyperactivity disorder patients: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Abstract Methylphenidate (MPH), a first-line treatment for attention-deficit hyperactivity disorder (ADHD) management, has been the focus of debate for decades regarding its effect on growth. The aim of this PRISMA meta-analysis was to determine the effect of MPH on height in children/adolescents with ADHD, along with factors predictive of this effect. Available full-text articles were systematically reviewed to identify clinical studies of pediatric ADHD patients with height Z-score (HZS) data for monotherapy MPH-treated and non-treated groups. We estimated standardized mean differences (SMDs) of HZS or its changes from baseline (ΔHZS) between groups, then identified associated factors through subgroup analyses and meta-regression. For before-after treatment studies, the paired standard errors of ΔHZS were re-estimated to demonstrate in the forest plot. Risk of bias was analyzed using the Newcastle-Ottawa Scale. Among the 29 eligible studies, 26 before-after studies reported ΔHZS with self-control groups, whereas 11 compared ΔHZS or absolute HZS to other external (healthy/non-medicated) controls. A significant reduction was observed in the post-medicated group compared to the pre-medicated group, with high heterogeneity (SMD = -0.40; 95% confidence interval = [-0.54; -0.27]; I2 = 91%). The study region, ADHD subtype, and stimulant-naïve status of patients at baseline may modify the effect on HZS. Because of the high clinical heterogeneity in observational studies, clinicians should consider the negative effect of MPH on height in ADHD patients by determining whether patients fulfill appropriate high-risk criteria. Further investigations are needed to identify the mechanism and the impact of reduction on the height reached in adulthood.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".