HR-pQCT Measures of Bone Microarchitecture Predict Fracture: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
High-resolution peripheral quantitative computed tomography (HR-pQCT) is a noninvasive imaging modality for assessing volumetric bone mineral density (vBMD) and microarchitecture of cancellous and cortical bone. The objective was to (1) assess fracture-associated differences in HR-pQCT bone parameters; and (2) to determine if HR-pQCT is sufficiently precise to reliably detect these differences in individuals. We systematically identified 40 studies that used HR-pQCT (39/40 used XtremeCT scanners) to assess 1291 to 3253 and 3389 to 10,687 individuals with and without fractures, respectively, ranging in age from 10.9 to 84.7 years with no comorbid conditions. Parameters describing radial and tibial bone density, microarchitecture, and strength were extracted and percentage differences between fracture and control subjects were estimated using a random effects meta-analysis. An additional meta-analysis of short-term in vivo reproducibility of bone parameters assessed by XtremeCT was conducted to determine whether fracture-associated differences exceeded the least significant change (LSC) required to discern measured differences from precision error. Radial and tibial HR-pQCT parameters, including failure load, were significantly altered in fracture subjects, with differences ranging from -2.6% (95% confidence interval [CI] -3.4 to -1.9) in radial cortical vBMD to -12.6% (95% CI -15.0 to -10.3) in radial trabecular vBMD. Fracture-associated differences reported by prospective studies were consistent with those from retrospective studies, indicating that HR-pQCT can predict incident fracture. Assessment of study quality, heterogeneity, and publication biases verified the validity of these findings. Finally, we demonstrated that fracture-associated deficits in total and trabecular vBMD and certain tibial cortical parameters can be reliably discerned from HR-pQCT-related precision error and can be used to detect fracture-associated differences in individual patients. Although differences in other HR-pQCT measures, including failure load, were significantly associated with fracture, improved reproducibility is needed to ensure reliable individual cross-sectional screening and longitudinal monitoring. In conclusion, our study supports the use of HR-pQCT in clinical fracture prediction. © 2019 American Society for Bone and Mineral Research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.018 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".