Dataset Information

Serum Anion Gap Predicts All-Cause Mortality in Critically Ill Patients with Acute Kidney Injury: Analysis of the MIMIC-III Database.

ABSTRACT: Background:No epidemiological study has investigated the effect of anion gap (AG) on the prognosis of critically ill patients with acute kidney injury (AKI). Therefore, we aimed to determine the association between serum AG and all-cause mortality in these patients. Methods:From MIMIC III, we extracted demographics, vital signs, laboratory tests, comorbidities, and scoring systems from the first 24?h after patient ICU admission. A generalized additive model was used to identify a nonlinear association between anion gap and 30-day all-cause mortality. We also used the Cox proportional hazards models to measure the association between AG levels and 30-day, 90-day, and 365-day mortality in patients with AKI. Results:A total of 11,573 eligible subjects were extracted from the MIMIC-III. The relationship between AG levels and 30-day all-cause mortality in patients with AKI was nonlinear, with a U-shaped curve. In multivariate analysis, after adjusting for potential confounders, higher AG was a significant predictor of 30-day, 90-day, and 365-day all-cause mortality compared with lower AG (HR, 95% CI: 1.54, 1.33-1.75; 1.55, 1.38-1.73; 1.46, 1.31-1.60). Conclusions:The relationship between AG levels and 30-day all-cause mortality described a U-shaped curve. High-AG levels were associated with increased risk 30-day, 90-day, and 365-day all-cause mortality in critically ill patients with AKI.

SUBMITTER: Cheng B

PROVIDER: S-EPMC6995483 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Serum Anion Gap Predicts All-Cause Mortality in Critically Ill Patients with Acute Kidney Injury: Analysis of the MIMIC-III Database.

Cheng Bihuan B Li Diwen D Gong Yuqiang Y Ying Binyu B Wang Benji B

Disease markers 20200121

<h4>Background</h4>No epidemiological study has investigated the effect of anion gap (AG) on the prognosis of critically ill patients with acute kidney injury (AKI). Therefore, we aimed to determine the association between serum AG and all-cause mortality in these patients.<h4>Methods</h4>From MIMIC III, we extracted demographics, vital signs, laboratory tests, comorbidities, and scoring systems from the first 24 h after patient ICU admission. A generalized additive model was used to identify a ...[more]

PMID: 32051697

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Project description:BackgroundThere were controversies over the relationship between Anion gap (AG) and mortality in critically ill patients. Therefore, a large multicenter cohort study was conducted to evaluate the association of AG and mortality in large-scale intensive care units (ICUs) patients.MethodsThis retrospective cohort study included adult ICU patients enrolled from eICU Collaborative Research Database. According to initial serum AG upon ICU admission, patients were divided into three groups: AG < 8 mmol/L, 8 ≤ AG ≤ 16 mmol/L, and AG > 16 mmol/L. Logistic regression models were built to investigate the association between serum AG and ICU and hospital mortalities. Serum AG was added into Acute Physiology and Chronic Health Evaluation (APACHE) IV score and the model discrimination was assessed by the area under the curve (AUC) of receiver operating characteristic curves. The relationship between serum AG and mortalities in patients with different acid-base status and serum lactate were also evaluated. An external validation was performed with the Critical care database comprising patients with infection at Zigong Fourth People's Hospital.ResultsA total of 8520 patients entered the final cohort. There are 42 patients with serum AG < 8 mmol/L, 3238 patients with 8 ≤ AG ≤ 16 mmol/L, and 5240 patients with AG > 16 mmol/L. Serum AG > 16 mmol/L is related with increased ICU mortality (odds ratio [OR], 1.530; 95% confidence interval [CI], 1.305-1.794) and hospital mortality (OR, 1.618; 95% CI, 1.415-1.849), compared with 8 ≤ AG ≤ 16 mmol/L. Adding Serum AG to APACHE IV score could statistically improve the prediction of ICU (0.770 [0.761-0.779] to 0.774 [0.765-0.783], P = 0.001) and hospital mortalities (0.756 [0.747-0.765] to 0.761 [0.751-0.770], P = 0.012). The associations between serum AG and mortalities remain robust in patients with different acid-base statuses and serum lactate. The findings are validated in the external cohort.ConclusionsInitial serum AG > 16 mmol/L after ICU admission is associated with increased mortality in critically ill patients.

Project description:BackgroundHemorrhagic stroke (HS), including non-traumatic intracerebral hemorrhage (ICH) and subarachnoid hemorrhage (SAH), constitutes a substantial proportion of cerebrovascular incidents, accounting for around 30% of stroke cases. The triglyceride-glucose index (TyG-i) represents a precise insulin resistance (IR) indicator, a crucial metabolic disturbance. Existing literature has demonstrated an association between TyG-i and all-cause mortality (ACM) among individuals suffering from ischemic stroke (IS). Yet, the TyG-i prognostic implications for severe HS patients necessitating intensive care unit (ICU) admission are not clearly understood. Considering the notably elevated mortality and morbidity associated with HS relative to IS, investigating this association is warranted. Our primary aim was to investigate TyG-i and ACM association among critically ill HS patients within an ICU context.MethodsHerein, patients with severe HS were identified by accessing the Medical Information Mart for Intensive Care-IV (MIMIC-IV, version 2.2) database, using the International Classification of Diseases (ICD)-9/10 as diagnostic guidelines. Subsequently, we stratified the subjects into quartiles, relying on their TyG-i scores. Moreover, we measured mortality at ICU, in-hospital, 30 days, 90 days, and 1 year as the outcomes. Cox proportional hazards regression analysis and restricted cubic splines (RCS) were deployed for elucidating the relation between the TyG-i and ACM while utilizing the Kaplan-Meier (K-M) method to estimate survival curves. The findings' robustness was assessed by conducting subgroup analysis and interaction tests employing likelihood ratio tests.ResultsThe analysis included 1475 patients, with a male predominance of 54.4%. Observed mortality rates in the ICU, hospital, 30 days, 90 days, and 1 year were 7.3%, 10.9%, 13.8%, 19.7%, and 27.3%, respectively. Multivariate Cox regression analysis results manifested that heightened TyG-i was significantly related to ACM at 30 days (adjusted hazard ratio [aHR]: 1.32; 95% confidence interval [CI]: 1.05-1.67; P = 0.020), 90 days (aHR: 1.27; 95% CI: 1.04-1.55; P = 0.019), and 1 year (aHR: 1.22; 95% CI: 1.03-1.44; P = 0.023). The results of RCS analysis demonstrated a progressive elevation in ACM risk with rising TyG-i levels. Interaction tests found no significant effect modification in this relationship.ConclusionIn summary, TyG-i exhibits a significant correlation with ACM among patients enduring critical illness due to HS. This correlation underscores the probable utility of TyG-i as a prognostic tool for stratifying HS patients according to their risk of mortality. Applying TyG-i in clinical settings could enhance therapeutic decision-making and the management of disease trajectories. Additionally, this investigation augments existing research on the linkage between the TyG-i and IS, elucidating the TyG-i's role in predicting mortality across diverse stroke categories.

Project description:Thyroid dysfunction is common in critical illness and may influence prognosis. However, the value of TSH in patients with severe diseases remains unclear. The aim of this study was to investigate the association between TSH and the clinical prognosis of critically ill patients. Methods: This retrospective study identified patients who were admitted to the ICU in the Medical Information Mart for Intensive Care (MIMIC-IV) database (version 2.2). A total of 6432 patients were divided into four groups based on TSH quartiles (Q1, <0.92 mIU/L; Q2, 0.92-1.07 mIU/L; Q3, 1.07-3.10 mIU/L; Q4, >3.10 mIU/L). The clinical outcomes were defined as all-cause 7-, 30-, and 90-year mortality after ICU admission. Restricted cubic splines (RCSs) for nonlinear associations were generated to visualize the relationship between TSH levels and clinical outcomes. The survival differences among the four groups were also analyzed using Kaplan‒Meier curves and log rank tests. Univariable and multivariable Cox proportional hazards regression were further used to assess the association between TSH levels and clinical outcomes. Results: After multivariate adjustment, a U-shaped relationship was observed between TSH levels and all-cause 7-, 30-, and 90- mortality among patients with severe disease (all P < 0.05 for nonlinearity). The plot showed a risk reduction in the low range of TSH, which reached the lowest risk at approximately 2.9 μIU/mL and then increased thereafter. Compared with patients with Q3 TSH levels, those with Q1, Q2, and Q4 TSH levels had a significantly higher risk of all-cause 30-day mortality (Q1: hazard ratio, 1.28; 95% CI, 1.06-1.54; Q2: hazard ratio, 1.22; 95% CI, 1.01-1.48; Q4: hazard ratio, 1.25; 95% CI, 1.04-1.50). For all-cause 90-day mortality, only the Q4 group had a significantly higher mortality risk than the Q3 group (hazard ratio, 1.24; 95% CI, 1.07-1.44). In subgroup analyses, we found that Q1 TSH levels were associated with higher mortality risk in men and older (≥65 years) patients, while Q4 TSH had a greater risk in men and younger (<65 years) patients. Conclusions: TSH was significantly associated with all-cause 7-, 30-, and 90-day mortality in critically ill patients after admission to the ICU. TSH may serve as a valuable biomarker for risk stratification in critically ill patients.

Dataset Information

Serum Anion Gap Predicts All-Cause Mortality in Critically Ill Patients with Acute Kidney Injury: Analysis of the MIMIC-III Database.

Publications

Serum Anion Gap Predicts All-Cause Mortality in Critically Ill Patients with Acute Kidney Injury: Analysis of the MIMIC-III Database.

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