Association of albumin-corrected anion gap with mortality in ICU patients with heart failure and acute kidney injury: analysis of the MIMIC-IV database
Bibliographic record
Abstract
BACKGROUND: Elevated albumin-corrected anion gap (ACAG) levels have been shown to be associated with increased mortality in various critical illnesses; however, data specifically addressing heart failure (HF) complicated by acute kidney injury (AKI) are lacking. METHOD: Data from ICU patients with HF complicated by AKI between 2008 and 2022 were extracted and analyzed from the MIMIC-IV database. The association between baseline ACAG levels and all-cause mortality was assessed using multiple statistical methods, including variance inflation factor analysis, restricted cubic spline (RCS) modeling, Kaplan-Meier analysis, univariate and multivariate Cox regression, subgroup analysis, mediation analysis, and receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 5425 patients were included in this study. RCS analysis showed a linear relationship between ACAG and mortality (p = 0.075 for nonlinearity). The Kaplan-Meier curve and multivariate Cox regression analysis revealed a positive relationship between ACAG and mortality at both 30 and 365 days post ICU admission. These results were confirmed by subgroup analysis. Mediation analysis showed SAPS II, bicarbonate, BUN, creatinine, hemoglobin, Charlson and ASP III mediated the association between ACAG and all-cause mortality, accounting for 32.34%, - 30.59%, 32.28%, 19.83%, 7.57%, 7.58%, and 25.64% of the mediating effect, respectively (all p values < 0.001). The AUC value for predicting 30-day mortality was 0.643 for ACAG, greater than 0.616 for albumin and 0.604 for AG. For predicting 365-day mortality, the AUC value was 0.641 for ACAG, greater than 0.626 for albumin and 0.597 for AG. CONCLUSION: Elevated ACAG is associated with increased mortality in HF patients with AKI, emphasizing the importance of monitoring metabolic parameters in this population. ACAG may be a valuable prognostic marker for HF and AKI. Further research is warranted to determine whether targeted interventions to correct metabolic acidosis could improve outcomes in this vulnerable patient group.
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How this classification was reachedexpand
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".