A systematic review and meta-analysis of pediatric normative peripheral quantitative computed tomography data
Bibliographic record
Abstract
BACKGROUND: Peripheral-quantitative computed tomography (pQCT) provides an intriguing diagnostic alternative to dual-energy X-ray absorptiometry (DXA) since it can measure 3D bone geometry and differentiate between the cortical and trabecular bone compartments. OBJECTIVE: To investigate and summarize the methods of pQCT image acquisition of in children, adolescents and/or young adults (up to age 20) and to aggregate the published normative pQCT data. EVIDENCE ACQUISITION: A literature search was conducted in MEDLINE and EMBASE from 1947 to December 2020. Quality of the included articles was assessed using Standards for Reporting of Diagnostic Accuracy (STARD) scoring system and United States Preventative Services Task Force (USPSTF) Study Design Categorization. Seven articles, encompassing a total of 2134 participants, were aggregated in the meta-analysis. Due to dissimilar age groups and scan sites, only seven pQCT parameters of the 4% radius, 4% tibia and 38% tibia were analyzed in this meta-analysis. EVIDENCE SYNTHESIS: in 8 to 9 year-old girls, 210.42 (201.91, 218.93)in 10 to 12 year-old girls, 226.99 (222.45, 231.54) in 12 to 13 year-old girls, 259.97 (254.85, 265.10) in 12 to 13 year-old boys and 171.55 (163.41,179.69) in 16 to 18 year-old girls. 21 of 54 (38.9%) primary papers received a 'good' STARD quality of reporting score (<90 and 70 ≥ %) (mean STARD score of all articles = 69.4%). The primary articles of this review had a 'good' level USPSTF study design categorization. However, most of the normative data in these articles were non-comparable and non-aggregable due to a lack of standardization of reference lines, acquisition parameters and/or age at acquisition. CONCLUSION: There is not sufficient evidence to suggest that pQCT is appropriately suited for use in the pediatric clinical setting. Normative pediatric data must be systematically derived for pQCT should it ever be a modality that is used outside of research. CLINICAL IMPACT: We demonstrate the need for normative pQCT reference data and for clinical guidelines that standardize pediatric acquisition parameters and delineate its use in pediatric settings.
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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 | 0.020 | 0.064 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".