Abnormal Calcium Levels During Trauma Resuscitation Are Associated With Increased Mortality, Increased Blood Product Use, and Greater Hospital Resource Consumption: A Pilot Investigation
Bibliographic record
Abstract
BACKGROUND: Admission hypocalcemia predicts both massive transfusion and mortality in severely injured patients. However, the effect of calcium derangements during resuscitation remains unexplored. We hypothesize that any hypocalcemia or hypercalcemia (either primary or from overcorrection) in the first 24 hours after severe injury is associated with increased mortality. METHODS: All patients at our institution with massive transfusion protocol activation from January 2013 through December 2014 were identified. Patients transferred from another hospital, those not transfused, those with no ionized calcium (Ca) measured, and those who expired in the trauma bay were excluded. Hypocalcemia and hypercalcemia were defined as any level outside the normal range of Ca at our institution (1-1.25 mmol/L). Receiver operator curve analysis was also used to further examine significant thresholds for both hypocalcemia and hypercalcemia. Hospital mortality was compared between groups. Secondary outcomes included advanced cardiovascular life support, damage control surgery, ventilator days, and intensive care unit days. RESULTS: The massive transfusion protocol was activated for 77 patients of whom 36 were excluded leaving 41 for analysis. Hypocalcemia occurred in 35 (85%) patients and hypercalcemia occurred in 9 (22%). Mortality was no different in hypocalcemia versus no hypocalcemia (29% vs 0%; P = .13) but was greater in hypercalcemia versus no hypercalcemia (78% vs 9%; P < .01). Receiver operator curve analysis identified inflection points in mortality outside a Ca range of 0.84 to 1.30 mmol/L. Using these extreme values, 15 (37%) had hypocalcemia with a 60% mortality (vs 4%; P < .01) and 9 (22%) had hypercalcemia with a 78% mortality (vs 9%; P < .01). Patients with extreme hypocalcemia and hypercalcemia also received more red blood cells, plasma, platelets, and calcium repletion. CONCLUSIONS: Hypocalcemia and hypercalcemia occur commonly during the initial resuscitation of severely injured patients. Mild hypocalcemia may be tolerable, but more extreme hypocalcemia and any hypercalcemia should be avoided. Further assessment to define best practice for calcium management during resuscitation is warranted.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".