Hypercalcemia as a Biomarker of Poor Prognosis in Frail Elderly Patients with COVID-19
Bibliographic record
Abstract
The objective of this cohort study was to determine whether hypercalcemia in early COVID-19 was associated with 3-month mortality in frail elderly patients. Circulating calcium and albumin concentrations at hospital admission and 3-month mortality were assessed in geriatric patients hospitalized for COVID-19 with normal-to-high calcium concentrations. Hypercalcemia was defined as corrected calcium >2.5mmol/L. Covariables were age, sex, functional abilities, malignancies, hypertension, cardiomyopathy, number of acute health issues, use antibiotics and respiratory treatments. In total, 94 participants (mean±SD 88.0±5.5years; 47.9% women; 22.3% hypercalcemia; 0% hypocalcemia) were included. Sixty-five participants who survived at 3months exhibited less often hypercalcemia at baseline than the others (13.9% versus 41.4%, P=0.003). Hypercalcemia was associated with 3-month mortality (fully-adjusted HR=3.03, P=0.009) with specificity=0.86 and sensitivity=0.41. Those with hypercalcemia had shorter survival time than those with normocalcemia (log-rank P=0.002). In conclusion, hypercalcemia was associated with poorer survival in hospitalized frail elderly COVID-19 patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".