Key result
Higher lactate-to-albumin ratio is linked to ~2.6-fold higher in-hospital mortality per 0.1-unit increase post-PCI.
Why the study?
Accurate early risk stratification upon admission is critical for optimizing therapeutic strategies in AMI. Although the lactate-to-albumin ratio is a novel composite biomarker reflecting metabolic stress, tissue hypoperfusion, and systemic inflammation, its prognostic value for predicting in-hospital outcomes in AMI patients undergoing PCI required evaluation.
Does admission lactate-to-albumin ratio (LAR) predict in-hospital all-cause mortality in acute myocardial infarction patients undergoing percutaneous coronary intervention?
Cohort (n=121)
No
Does admission lactate-to-albumin ratio (LAR) predict in-hospital all-cause mortality in acute myocardial infarction patients undergoing percutaneous coronary intervention?
The lactate-to-albumin ratio upon admission is an independent, highly accurate predictor (AUC 0.97) of in-hospital mortality among acute myocardial infarction patients undergoing percutaneous coronary intervention.
Background: Acute myocardial infarction (AMI) remains a leading cause of cardiovascu-lar morbidity and mortality worldwide. Accurate early risk stratification upon admission is critical for optimizing therapeutic strategies. The lactate-to-albumin ratio (LAR) has emerged as a novel composite biomarker reflecting metabolic stress, tissue hypoperfusion, and systemic inflammation. This study aimed to evaluate the prognostic value of LAR in predicting in-hospital outcomes in AMI patients undergoing percutaneous coronary in-tervention (PCI) at Nhan Dan Gia Dinh Hospital. Methods: A prospective cohort study was conducted on 121 AMI patients who underwent PCI between January 2026 and June 2026 at Nhan Dan Gia Dinh Hospital. Clinical base-line characteristics, laboratory parameters (including blood lactate and serum albumin upon admission), and in-hospital clinical outcomes were collected. The predictive per-formance of LAR for in-hospital all-cause mortality was evaluated using Receiver Oper-ating Characteristic (ROC) curve analysis. Multivariate logistic regression was performed to determine the independent prognostic value of LAR. Results: Among the 121 enrolled patients, in-hospital all-cause mortality occurred in 8 pa-tients (6.6%). Median LAR levels were significantly higher in non-survivors compared to survivors (1.22 [IQR: 0.72–2.18] vs 0.41 [IQR: 0.29–0.58], p < 0.001). ROC curve analysis demonstrated that LAR had an excellent accuracy in predicting in-hospital mortality with an Area Under the Curve (AUC) of 0.97 (95% CI: 0.93–1.00, p < 0.001). At the optimal cutoff value of 0.65, LAR yielded 100.0% sensitivity, 88.5% specificity, 38.1% positive predictive value, and 100.0% negative predictive value. In univariate analysis, each 0.1-unit increase in LAR was associated with higher odds of mortality (OR = 2.64, 95% CI: 1.35–5.18, p = 0.005). After adjusting for Killip class III–IV (OR = 2.56, p = 0.008), eGFR (OR = 2.75, p = 0.006), and neutrophil count (OR = 2.87, p = 0.022), elevated LAR remained an independ-ent predictor of in-hospital mortality. Conclusions: LAR is a simple, rapidly accessible, and independent biomarker for predict-ing in-hospital mortality in AMI patients undergoing PCI. Integrating LAR into early clin-ical risk assessment can assist in identifying high-risk patients requiring intensive man-agement.
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Le et al. (2026) conducted a cohort in Acute myocardial infarction undergoing percutaneous coronary intervention (n=121). Admission lactate-to-albumin ratio (LAR) vs. Lower LAR levels / survivors was evaluated on In-hospital all-cause mortality (OR 2.64, 95% CI 1.35-5.18, p=0.005). Lactate-to-albumin ratio independently predicted in-hospital mortality in AMI patients undergoing PCI (AUC 0.97, 95% CI 0.93-1.00; univariate OR 2.64 per 0.1-unit increase, P=0.005).
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