Lower serum magnesium is associated with vascular calcification in peritoneal dialysis patients: a cross sectional study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Coronary artery calcification (CAC) is highly prevalent among dialysis patients and is associated with increased cardiovascular and all cause mortality. Magnesium (Mg) inhibits vascular calcification in animal and in-vitro studies but whether the same effect occurs in humans is uncertain. A single centre cross-sectional study of 80 prevalent peritoneal dialysis (PD) patients; on PD only for a minimum of 3 months. A radiologist blinded to patient status calculated their abdominal aortic calcification (AAC) scores on lateral lumbar spine radiographs, a validated surrogate for CAC. Eighty patients provided informed consent and underwent lumbar spine radiography. The mean serum Mg was 0.8 mmol/L (standard deviation 0.2) and mean AAC score 8.9 (minimum 0, maximum 24). A higher serum Mg level was associated with a lower AAC score (R 2 = 0.06, unstandardized coefficient [B] = −7.81, p = 0.03), and remained after adjustment for age, serum phosphate, serum parathyroid hormone, low-density lipoprotein cholesterol, smoking history, and diabetes (model adjusted R 2 = 0.36, serum Mg and AAC score B = −11.44, p = 0.00). This translates to a 0.1 mmol/L increase in serum Mg being independently associated with a 1.1-point decrease in AAC score. Our findings suggest that Mg may inhibit vascular calcification. If this association is replicated across larger studies with serial Mg and vascular calcification measurements, interventions that increase serum Mg and their effect on vascular calcification warrant further investigation in the PD population.
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.
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 | 0.000 | 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) | 0.000 | 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 it