FP405EVALUATION OF BONE MICROARCHITECTURE BY HIGH-RESOLUTION PERIPHERAL QUANTITATIVE COMPUTED TOMOGRAPHY IN PATIENTS WITH CHRONIC KIDNEY DISEASE: COMPARISON WITH TRANSILIAC BONE BIOPSY
Bibliographic record
Abstract
Introduction and Aims: High-resolution peripheral quantitative computed tomography (HR-pQCT) is a noninvasive imaging technique that assesses trabecular and cortical bone microarchitecture in vivo. The purpose of our study is to evaluate, for the first time, the correlation between HR-pQCT measures and transiliac bone biopsy (Bx) in chronic kidney disease (CKD) patients. Methods: We measured bone mineral desnsity (BMD) by HR-pQCT and dual energy x-ray absorptiometry (DXA) in 31 CKD stage 5D patients. Biopsies were analyzed by 2D quantitative histomorphometry, where both total and mineralized trabecular bone volume (2D BV/TV and 2D Md.V/TV, respectively) were measured. Results: Patients (19 males) were 41 ± 11 years old, with a dialysis vintage of 28 months, BMI of 24 kg/m², serum Ca of 8.4 ± 0.6 mg/dl; P of 3.4±1.5 mg/dl; alkaline phosphatase 93 (71 -145) U/L; PTH 463 ± 343 pg/ml; 25-vitamin D 25 (18 - 32) ng/ml and sclerostin 1.03 (0.51 - 1.83) ng/ml. 2D BV/TV correlated significantly with height; lumbar spine (r = 0.70) and total femur (r = 0.59) DXA; and modestly with HR-pQCT BV/TV at the radius (r = 0.42; p< 0.05) but not at the tibia. 2D Md.V/TV correlated significantly with age; height; lumbar spine (r = 0.67) and total femur (r = 0.63) DXA; and HR-pQCT BV/TV (r = 0.50; p<0.05) only at the radius. Conversely, a strong correlation was found between 2D cortical porosity (Ct.Po) and HR-pQCT cortical bone density (Dcomp) both at radius and tibia (r = -0.60 and -0.64, respectively; p <0.05). We found significant negative correlations between cortical density measured by HR-pQCT, and age, time on dialysis, PTH and alkaline phosphatase in the distal radius and tibia. The trabecular density and BV/TV, as measured by HR-pQCT, correlated with the age at the distal tibia and radius, and sex hormones, only at the radio.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".