HR-pQCT imaging in children, adolescents and young adults: Systematic review and subgroup meta-analysis of normative data
Bibliographic record
Abstract
We aimed to investigate the methodologies on image acquisition of normative data of high-resolution peripheral quantitative computed tomography (HR-pQCT) in children, adolescents and/or young adults (up to 25 years) and to determine their normative data based on available literature. A literature search was conducted in MEDLINE, EMBASE and Web of Science from 1947 to July 2019. Quality of articles was assessed using Standards for Reporting of Diagnostic Accuracy (STARD) scoring system and Modified Newcastle-Ottawa scale (NOS). Articles which fitted the following criteria were combined to meta-analysis: age range (15 to 22.6 years), references at tibia (22.5mm) and/or radius (9.0 to 9.5mm). Eight articles were ultimately included in the systematic review and 4 of them that filled the criteria were summarised in meta-analysis. The results of random effects model of HR-pQCT parameters of the 4 articles were as follows: 1)Radius: bone volume fraction (BT/BV) [estimate 0.17:0.1229(lower)-0.2115 (upper); trabecular number (Tb_N):2.08(2.03-2.12); trabecular thickness (Tb.Th):0.07 (0.07-0.0.08); trabecular separation (Tb.Sp):0.41 (0.38-0.42); cortical thickness (Ct.Th):0.85 (0.76-0.94); cortical porosity (Ct.Po):1.53 (0.63-2.44); total area (Tt.Ar):263.66(-385.3-912.6); total bone density (Tt-vBMD):280.5 (73.1-487.7); Trabecular density (Tb-vBMD):223.6 (47.1-400.09), and cortical density (CT.vBMD):765.9 (389.1-1142.8). 2)Tibia: BT/BV:0.18 (0.17-0.19); Tb_N:2.02 (1.83-2.2); Tb.Th:0.08 (0.80-0.09); Tb.Sp:0.40(0.36-0.44); Ct.Th:1.32(1.26-1.38); Ct.Po:3.15 (1.1-5.2); Tt.Ar:693.1(150.2-1235.8); Tt-vBMD:343.76 (335.5-352.1); Tb-vBMD:223.6 (213.37 (193.5-233.2), and CT.vBMD:894.3 (857.6-931.1). There is overall 'fair' evidence on reporting of results of normative data of HR-pQCT parameters in children, adolescents and/or young adults. However, data are scarce pointing out to the urgent need for standardization of acquisition parameters and guidelines on the use of HR-PQCT in these populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.052 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".