Laboratory Markers of Acidosis and Mortality in Cardiogenic Shock: Developing a Definition of Hemometabolic Shock
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Bibliographic record
Abstract
BACKGROUND: Acidosis and higher lactate predict worse outcomes in cardiogenic shock (CS) patients. We sought to determine whether overall acidosis severity on admission predicted in-hospital mortality in CS patients. METHODS: This retrospective descriptive analysis included CS patients admitted to a single academic tertiary cardiac intensive care unit from 2007 to 2015. Admission arterial pH, base excess, and anion gap values were used to generate a Composite Acidosis Score (range 0-5, with a score ≥2 defining Severe Acidosis). Adjusted in-hospital mortality was analyzed using multivariable logistic regression. RESULTS: We included 1,065 patients with median age of 68.9 (59.0, 77.2) years (36.4% females). Concomitant diagnoses included cardiac arrest in 38.1% and acute coronary syndrome in 59.1%. Severe Acidosis was present in 35.2%, and these patients had worse shock and more organ failure. In-hospital mortality occurred in 34.1% and was higher among patients with Severe Acidosis (54.9% vs. 22.4%, adjusted odds ratio [OR] 2.01, 95% CI 1.43-2.83, P < 0.001). Increasing Composite Acidosis Score was associated with higher in-hospital mortality (adjusted OR 1.25 per point, 95% CI 1.11-1.40, P < 0.001). Severe Acidosis was associated with higher hospital mortality at every level of shock severity and organ failure (all P < 0.05). Admission lactate level had equivalent discrimination for in-hospital mortality as the Composite Acidosis Score (0.69 vs. 0.66; P = 0.32 by De Long test). CONCLUSION: Given its incremental association with higher in-hospital mortality among CS patients beyond shock severity and organ failure, we propose Severe Acidosis as a marker of hemometabolic shock. Lactate levels performed as well as a composite measure of acidosis for predicting mortality.
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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 | 0.001 |
| 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