Negative Effects of Total Gastrectomy on Bone Tissue Metabolism and Volumetric Bone Mineral Density (vBMD) of Lumbar Spine in 1-Year Study in Men
Bibliographic record
Abstract
Gastrectomy induces severe osteoporosis in humans but its quantitative scale within trabecular and cortical compartments was not estimated. The aim of the study was to determine changes of volumetric bone mineral density (vBMD) in lumbar vertebrae (L1-L4) and biochemical bone metabolism markers in serum of patients 1 year after total gastrectomy. The control group consisted of patients (N = 8) subjected to abdominal surgery due to cardiospasmus. Total gastrectomy was performed in the experimental group (N = 6). Volumetric bone mineral density of trabecular and cortical bone of lumbar spine was measured before (baseline) and 1 year after the gastric surgery using the quantitative computed tomography method. Serum concentrations of insulin, insulin-like growth factor-1, tyroxine, interleukin-6, C-terminal telopeptides of type II collagen and bone formation, and resorption markers were determined at baseline and 1 year later, using ELISA, EIA, and IEMA methods. Total gastrectomy induced significant decrease of vBMD values, up to 16.8% and 10.0%, within the trabecular and cortical bone compartments of lumbar spine (P < 0.05). These negative changes of vBMD were associated with significantly increased serum concentration of bone resorption markers such as deoxypyridinoline, pyridinoline, and C-terminal telopeptides of type I collagen, by 13.5%, 32.2%, and 121.5%, respectively (P < 0.05). Neither vBMD nor biochemical bone turnover markers and hormone concentrations were influenced in the control patients. Dramatic bone loss during the first year in gastrectomized patients has proven dynamic osteoporosis progress indicating an importance of treatment interventions in these patients with emphasis on inhibition of intensive bone resorption processes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".