A-107 Evaluating the Use of Albumin-Corrected Calcium Measurements in an Acute Care Hospital Network
Bibliographic record
Abstract
Abstract Background Using albumin-corrected calcium remains a conventional practice for determining calcium homeostasis, particularly in patients with hypoalbuminemia. However, studies have demonstrated that relying on albumin-corrected calcium in patients with hypoalbuminemia can overestimate serum calcium levels. We evaluated the correlation between total calcium measurements (with or without albumin correction) and ionized calcium levels in patients with normal and low albumin levels. Our findings were valuable for providing physician education on discontinuing the report of albumin-corrected calcium in our health system. This change aims to improve patient care and optimize laboratory resources. Methods We analyzed six months of patient data for total calcium, with and without albumin correction, obtained across three hospitals (N=56465). The Payne formula [Corrected calcium (mmol/L) = total calcium (mmol/L) + 0.02 [40 - albumin (g/L)] was used to derive the albumin-corrected calcium. We assessed paired ionized calcium specimens, collected within 24 hours apart (N=3123). The linear relationship and clinical correlation were assessed between total calcium, with or without albumin correction, with ionized calcium levels. Results Linear regression showed comparably moderate correlation between uncorrected (R² = 0.75, slope= 1.58) and corrected total calcium (R² = 0.74, slope= 1.55) with ionized calcium levels. In patients with hypoalbuminemia (N=2609), the clinical concordance with ionized calcium was stronger with uncorrected calcium compared to albumin-corrected calcium (72% vs 53%). Moreover, the clinical concordance with low ionized calcium was significantly higher using uncorrected calcium, compared to corrected calcium (88% vs 20%). When the ionized calcium is normal, the concordance was similar between uncorrected and corrected calcium (62% vs 60%). Conclusion Our findings support the literature that relying on the interpretation of albumin-corrected calcium can overestimate calcium status. There is a high risk of missing true hypocalcemia, where the corrected calcium level is in the normal range while the ionized calcium level is low. The uncorrected calcium measurement was more reliable for determining calcium status and agrees better with ionized calcium, in the presence of hypoalbuminemia.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".