A Prognostic Model Incorporating the Albumin-corrected Anion Gap in Patients with Aneurysmal Subarachnoid Hemorrhage

Overview

Journal Front Neurol

Specialty Neurology

Date 2024 Jul 4

PMID 38962480

Authors

Ruoran Wang

Juan Rong

Jianguo Xu

Min He

Affiliations

Soon will be listed here.

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 ( = 0.006), surgical options ( < 0.001), white blood cell count ( < 0.001), serum chloride levels ( = 0.023), ACAG ( = 0.039), and delayed cerebral ischemia ( < 0.001). The AUC values for the AG, albumin, and ACAG in predicting mortality among aSAH patients were 0.606, 0.536, and 0.617, respectively. A logistic regression model, which includes the Hunt-Hess scale score, surgical options, white blood cell count, serum chloride levels, ACAG, and delayed cerebral ischemia, achieved an AUC of 0.911 for predicting mortality.

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.

Citing Articles

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Chen Y, You M, Chu L Sci Rep. 2024; 14(1):26006.

PMID: 39472602 PMC: 11522283. DOI: 10.1038/s41598-024-76324-x.

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