Serum anion gap at admission predicts all-cause mortality in critically ill patients with cerebral infarction: evidence from the MIMIC-III database

Liu, Xuefang; Feng, Yan; Zhu, Xinyu; Shi, Ying; Lin, Mei-Ju; Song, Xiaoyan; Tu, Jiancheng; Yuan, Enwu

doi:10.1080/1354750x.2020.1842497

Cited by 31 publications

(35 citation statements)

References 30 publications

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“…Data regarding the association between the plasma AG and ischemic stroke are scarce; however, some evidence shows that it is, at least, partially causal [ 9 ]. An increased plasma AG usually indicates an imbalance between acid generation caused by tissue hypoperfusion and acid excretion based on the renal function [ 20 ].…”

Section: Discussionmentioning

confidence: 99%

“…This leads to spreading depolarization with the evolution of ischemic stroke, which might aggravate tissue acidosis and induce cell death [ 22 ]. In a previous cohort study, the plasma AG was independently associated with the risk of mortality [ 9 ]. In this study, we expounded on that finding, revealing that there was a positive linear trend between the plasma AG and the in-hospital mortality.…”

Section: Discussionmentioning

confidence: 99%

“…Thus, they have the potential to be used as predictors of stroke outcomes [ 8 ]. In previous studies by Liu et al, results show that a high AG was associated with an increased risk of all-cause mortality in critically ill patients with cerebral infarction [ 9 ]. However, the anion gap is not often reliable to identify increased concentrations of gap anions.…”

Section: Introductionmentioning

confidence: 99%

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Plasma Anion Gap and Risk of In-Hospital Mortality in Patients with Acute Ischemic Stroke: Analysis from the MIMIC-IV Database

Jhou

Chen

Yang

et al. 2021

JPM

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We aimed to investigate the association between the plasma anion gap (AG) and in-hospital mortality among patients with acute ischemic stroke (AIS). In total, 1236 AIS patients were enrolled using the Medical Information Mart for Intensive Care Database IV. Primary outcome was in-hospital mortality. The patients were divided into four groups according to AG category. The mean age and Charlson comorbidity index increased as the AG category increased. The fourth AG category was most related to the in-hospital mortality (hazards ratio (HR), 95% confidence interval (CI): 2.77, 1.60–4.71), even after adjusting for possible confounding variables (Model 1: HR, 95% CI: 3.37, 1.81–6.09; Model 2: HR, 95% CI: 3.57, 1.91–6.69). Moreover, intensive care unit mortality (p = 0.008) was higher in the highest AG category, but the intracranial hemorrhage (p = 0.071) did not associate with the plasma AG. The plasma AG had a satisfactory predictive ability for in-hospital mortality among AIS patients (areas under the receiver operating characteristic curve: 0.631). The plasma AG is an independent risk factor that can satisfactorily predict the in-hospital mortality among AIS patients.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Plasma Anion Gap and Risk of In-Hospital Mortality in Patients with Acute Ischemic Stroke: Analysis from the MIMIC-IV Database

Jhou

Chen

Yang

et al. 2021

JPM

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“…Currently, bio-markers catch much attention. Higher AG counting was related to increased incidence of all-cause mortality, which guided to monitor cerebral infarction and the formulation of secondary prevention strategies 24 .…”

Section: Discussionmentioning

confidence: 99%

“…The excessive generation of lactate and pyruvate in serum result to common reason for AG cumulation [22][23] . Serum AG count could be applied as a prognostic indicator to have evaluation for patients with CI in a short-term, higher AG on the rst-dayadmission was related to increased risk of all-cause mortality, a few patients who were in ICU had higher AG count 24 . WBC count is an important risk factor and is related with delayed cerebral ischemia 25 .…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Prognostic Nomogram for Cerebral Infarction Patients in Intensive Care Units: a Retrospective Cohort Study

Yu¹,

Xu²,

Zeng³

et al. 2021

Preprint

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OBJECTIVES: Our study aimed to establish a utility risk prediction model for the prognosis of patients with cerebral infarction.BACKGROUND: Despite large number of studies focus on the prognosis risk factors of patients with cerebral infarction, there were still lack of utility and visual risk prediction model for predicting the in-hospital mortality of patients with cerebral infarction.METHODS: The study is a retrospective cohort study. The lasso regression model was used for data dimension reduction and feature selection. Model of hospital mortality of cerebral infarction patients was developed by multivariable logistic regression analysis. Calibration and discrimination were used to assess the performance of the nomogram. Decision curve analysis (DCA) was used to evaluate the clinical utility of the model. RESULTS: Overall, 1,564 patients (1315 survivals and 249 deaths) with cerebral infarction included in our research from MIMIC-IV database. The incident of in-hospital mortality is 15.9%. Lasso regression model verified that age, white blood cell count, anion gap (AG), SOFA score were significantly correlated with hospital mortality. The risk prediction model demonstrated a good discrimination with an AUC of ROC 0.789 (95% CI 0.752–0.826) in training set and 0.829 (95% CI 0.791–0.867) in test set. The calibration plot of risk prediction model showed predicted probabilities against observed death rates indicated excellent concordance. DCA showed that this model has good clinical benefits.Conclusion: We developed a nomogram that predicts hospital mortality in patients with cerebral infarction according to the real world’s data. The nomogram exhibited excellent discrimination and calibration capacity, favoring its clinical utility.

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Associations of continuous anionic gap detection with the mortality in critically ill patients receiving renal replacement therapy

et al. 2023

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Purpose To investigate the associations of anion gap (AG) levels before and 1-day after hemodialysis as well as anion gap changes with the mortality in critically ill patients receiving renal replacement therapy (RRT). Methods Totally, 637 patients from MIMIC-III were included in this cohort study. The associations between AG (T0), AG (T1), or ∆AG [AG (T0) − AG (T1)], and the risk of 30-day or 1-year mortality were examined by Cox restricted cubic spline regression models. Univariate and multivariate Cox proportional-hazards model was applied to assess the associations between AG (T0), AG (T1), ∆AG with 30-day and 1-year mortality, respectively. Results The median follow-up time was 18.60 (8.53, 38.16) days and 263 (41.3%) patients were survived. There was a linear relationship between AG (T0), AG (T1) or ∆AG and the risk of 30-day or 1-year mortality, respectively. The risk of 30-day mortality was higher in AG (T0) > 21 group (HR = 1.723, 95% CI 1.263–2.350), and AG (T1) > 22.3 group (HR = 2.011, 95% CI 1.417–2.853), while lower in AG > 0 group (HR = 0.664, 95% CI 0.486–0.907). The risk of 1-year mortality was increased in AG (T0) > 21 group (HR = 1.666, 95% CI 1.310–2.119), and AG (T1) > 22.3 group (HR = 1.546, 95% CI 1.159–2.064), while decreased in AG > 0 group (HR = 0.765, 95% CI 0.596–0.981). Patients with AG (T0) ≤ 21 had higher 30-day and 1-year survival probability than those with AG (T0) > 21. Conclusion AG before and after dialysis as well as the changes of AG were important factors associated with the risk of 30-day and 1-year mortality in critically ill patients receiving RRT.

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Serum anion gap at admission predicts all-cause mortality in critically ill patients with cerebral infarction: evidence from the MIMIC-III database

Cited by 31 publications

References 30 publications

Plasma Anion Gap and Risk of In-Hospital Mortality in Patients with Acute Ischemic Stroke: Analysis from the MIMIC-IV Database

Plasma Anion Gap and Risk of In-Hospital Mortality in Patients with Acute Ischemic Stroke: Analysis from the MIMIC-IV Database

Development and Validation of a Prognostic Nomogram for Cerebral Infarction Patients in Intensive Care Units: a Retrospective Cohort Study

Associations of continuous anionic gap detection with the mortality in critically ill patients receiving renal replacement therapy

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