ArticleFrontiers in neurology2024
A prognostic model incorporating the albumin-corrected anion gap in patients with aneurysmal subarachnoid hemorrhage.
Article in Frontiers in neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Association of albumin-corrected anion gap with all-cause and cardiovascular mortality in overactive bladder patients.Scientific reports · 2025Article
- Prediction of postoperative haemorrhage after cerebral tumour surgery using machine learning algorithms.BMC medical informatics and decision making · 2025Article
- Association between albumin-corrected anion gap and delirium in acute pancreatitis: insights from the MIMIC-IV database.BMC gastroenterology · 2025Article
- Association between standard base excess and acute kidney injury in intensive care unit patients: a study based on the medical information mart for intensive care database.BMC nephrology · 2025Article
- The relationship between albumin-corrected anion gap and hyperuricemia and its role in cardiovascular risk assessment: mediation effect analysis of triglycerides and non-high-density lipoproteins.Frontiers in endocrinology · 2025Article
- Association of albumin-corrected anion gap with severe consciousness disorders and outcomes in ischemic stroke: a retrospective MIMIC analysis.Scientific reports · 2024Article
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Abstract
Background: Aneurysmal subarachnoid hemorrhage (aSAH) patients typically have poor prognoses. The anion gap (AG) has been proven to correlate with mortality in various critically ill patients. However, hypoalbuminemia can lead to underestimations of the true anion gap levels. This study was conducted to verify the prognostic value of single AG and albumin-corrected anion gap (ACAG) among aSAH patients. Methods: Significant factors in the univariate logistic regression analysis were included in the multivariate logistic regression analysis to explore the risk factors for mortality in aSAH patients and to confirm the independent relationship between ACAG and mortality. The restricted cubic spline (RCS) was used to visually show the relationship between ACAG level and mortality risk of aSAH patients. The predictive model for mortality was developed by incorporating significant factors into the multivariate logistic regression analysis. The prognostic value of ACAG and the developed model was evaluated by calculating the area under the receiver operating characteristics curve (AUC). Results: Among 710 aSAH patients, a 30-day mortality was observed in 20.3% of the cases. A positive relationship was demonstrated between the ACAG level and mortality in aSAH patients using the RCS curve. The multivariate logistic regression analysis helped discover that only six factors were finally and independently related to mortality of aSAH patients after adjusting for confounding effects, including the Hunt-Hess scale score ( Conclusion: The ACAG is an effective prognostic marker for aSAH patients. A prognostic model incorporating ACAG could help clinicians evaluate the risk of poor outcomes among aSAH patients, thereby facilitating the development of personalized therapeutic strategies.
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