Proposed diagnostic criteria for the diagnosis of hypophosphatasia in children and adolescents: results from the HPP International Working Group
Bibliographic record
Abstract
Hypophosphatasia (HPP) is a rare inborn error of metabolism that presents variably in both age of onset and severity. HPP is caused by pathogenic variants in the ALPL gene, resulting in low activity of tissue nonspecific alkaline phosphatase (TNSALP). Patients with HPP tend have a similar pattern of elevation of natural substrates that can be used to aid in diagnosis. No formal diagnostic guidelines currently exist for the diagnosis of this condition in children, adolescents, or adults. The International HPP Working Group is a comprised of a multidisciplinary team of experts from Europe and North America who have expertise in the diagnosis and management of patients with HPP. This group reviewed 93 papers through a Medline, Medline In-Process, and Embase search for the terms "HPP" and "hypophosphatasia" between 2005 and 2020 and that explicitly address either the diagnosis of HPP in children, clinical manifestations of HPP in children, or both. Two reviewers independently evaluated each full-text publication for eligibility and studies were included if they were narrative reviews or case series/reports that concerned diagnosis of pediatric HPP or included clinical aspects of patients diagnosed with HPP. This review focused on 15 initial clinical manifestations that were selected by a group of clinical experts.The highest agreement in included literature was for pathogenic or likely pathogenic ALPL variant, elevation of natural substrates, and early loss of primary teeth. The highest prevalence was similar, including these same three parameters and including decreased bone mineral density. Additional parameters had less agreement and were less prevalent. These were organized into three major and six minor criteria, with diagnosis of HPP being made when two major or one major and two minor criteria are present.
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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 | 0.033 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.031 | 0.021 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".