Calcium: More Than Bone? Implications for Clinical Practice and Theory
Bibliographic record
Abstract
Serum calcium is routinely screened, but rarely scrutinized in the context of normal, physiologic functioning. This brief review strives to explore the implications of serum calcium, suggests guidelines for its interpretation, and discusses the implications of high, low, and “normocalcemia” in the clinical setting. We find that serum Ca 2+ concentrations are a valuable prognostic indicator in routine metabolic workups and advocate for greater attention, on behalf of the provider, to variations in a patient’s calcemic status. Variations in calcemic status are primarily tied to malignancy, impaired parathyroid hormone (PTH) secretion, defects in vitamin D synthesis, insulin-like growth factor 1 (IGF-1) fluctuation, genetic syndromes (DiGeorge syndrome) and calcium-sensing receptor ( CaSR ) mutation. Prognostic implications for high and low serum Ca 2+ include, but are not limited to, increased thromboembolic and major adverse cardiovascular event (MACE) risk, cardiac remodeling, hypertension, cognitive decline, and insulin resistance. J Clin Med Res. 2021;13(5):253-257 doi: https://doi.org/10.14740/jocmr4505
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.
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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".