Anion gap as a prognostic tool for risk stratification in critically ill patients - a systematic review and meta-analysis

The relationship between serum anion gap levels and short-, medium-, and long-term all-cause mortality in ICU patients with congestive heart failure: a retrospective cohort study

BACKGROUND

There hasn't been research done on the connection between serum anion gap (AG) levels and long-, medium-, and short-term all-cause mortality in congestive heart failure (CHF) patients. This study aims to investigate the association between serum anion gap levels and all-cause mortality in CHF patients after adjusting for other covariates.

METHODS

For each patient, we gather demographic information, comorbidities, laboratory results, vital signs, and scoring data using the ICU (Intensive Care Unit) Admission Scoring System from the MIMIC-III database. The connection between baseline AG and long-, medium-, and short-term all-cause mortality in critically ill congestive heart failure patients was investigated using Kaplan-Meier survival curves, subgroup analysis, restricted cubic spline, and Cox proportional risk analysis.

RESULTS

4840 patients with congestive heart failure in total were included in this study. With a mean age of 72.5 years, these patients had a gender split of 2567 males and 2273 females. After adjusting for other covariates, a multiple regression analysis revealed that, in critically ill patients with congestive heart failure, all-cause mortality increased significantly with rising AG levels. In the fully adjusted model, we discovered that AG levels were strongly correlated with 4-year, 365-day, 90-day, and 30-day all-cause mortality in congestive heart failure patients with HRs (95% CI) of 1.06 (1.04, 1.08); 1.08 (1.05, 1.10); and 1.08 (1.05, 1.11) (p-value < 0.05). Our subgroup analysis's findings demonstrated a high level of consistency and reliability. K-M survival curves demonstrate that high serum AG levels are associated with a lower survival probability.

CONCLUSION

Our research showed the association between CHF patients' all-cause mortality and anion gap levels was non-linear. Elevated anion gap levels are associated with an increased risk of long-, medium-, and short-term all-cause death in patients with congestive heart failure. Continuous monitoring of changes in AG levels may have a clinical predictive role.

A prognostic model incorporating the albumin-corrected anion gap in patients with aneurysmal subarachnoid hemorrhage

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 (p = 0.006), surgical options (p < 0.001), white blood cell count (p < 0.001), serum chloride levels (p = 0.023), ACAG (p = 0.039), and delayed cerebral ischemia (p < 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.

Association between Albumin-Corrected Anion Gap and Mortality in Patients with Cardiogenic Shock

Background

Cardiogenic shock (CS) is a critical illness with a high mortality rate in clinical practice. Although some biomarkers have been found to be associated with mortality in patients suffering from CS in previous studies. The albumin-corrected anion gap (ACAG) has not been studied in depth. Our study aimed to explore the relationship between ACAG and mortality in patients with CS.

Methods

All baseline data was extracted from Medical Information Mart for Intensive Care-IV version: 2.0 (MIMIC-IV). According to the prognosis at 30 days of follow-up, they were divided into survivors and non-survivors groups. The survival curves between the two groups were drawn using the Kaplan-Meier method and the log-rank test. Valid factors were selected using the least absolute shrinkage and selection operator (LASSO) logistic analysis model. Analysis was performed to investigate the relationship between mortality and all enrolled patients using restricted cubic spline (RCS) and Cox proportional hazards models. Receiver operating characteristic (ROC) curves were used to assess the predictive ability of ACAG. Evaluation of final result stability using sensitivity analysis.

Results

839 cases were selected to meet the inclusion criteria and categorized into survivors and non-survivors groups in the final analysis. The ACAG value measured for the first time at the time of admission was selected as the research object. Kaplan-Meier (K-M) survival curves showed that cumulative 30- and 90-day survival decreased progressively with elevated ACAG (p < 0.001), and multifactorial Cox regression analyses showed ACAG to be an independent risk factor for increased 30- and 90-day mortality in patients suffering from CS (p < 0.05). RCS curves revealed that all-cause mortality in this group of patients increased with increasing ACAG ( χ 2 = 5.830, p = 0.120). The ROC curve showed that the best cutoff value for ACAG for predicting 30-day mortality in patients with CS was 22.625, with a sensitivity of 44.0% and a specificity of 74.7%. The relationship between ACAG and CS short-term mortality remained stable in all sensitivity analyses (All p < 0.05).

Conclusions

The ACAG is an independent risk factor for 30- and 90-day mortality in CS patients and predicts poor clinical outcomes in CS patients. According to our study, elevated ACAG at admission, especially when ACAG > 20 mmol/L, was an independent predictor of all-cause mortality in CS.

Improving predictions: Enhancing in-hospital mortality forecast for ICU patients with sepsis-induced coagulopathy using a stacking ensemble model

The incidence of sepsis-induced coagulopathy (SIC) is high, leading to increased mortality rates and prolonged hospitalization and intensive care unit (ICU) stays. Early identification of SIC patients at risk of in-hospital mortality can improve patient prognosis. The objective of this study is to develop and validate machine learning (ML) models to dynamically predict in-hospital mortality risk in SIC patients. A ML model is established based on the Medical Information Mart for Intensive Care IV (MIMIC-IV) database to predict in-hospital mortality in SIC patients. Utilizing univariate feature selection for feature screening. The optimal model was determined by calculating the area under the curve (AUC) with a 95% confidence interval (CI). The optimal model was interpreted using Shapley Additive Explanation (SHAP) values. Among the 3112 SIC patients included in MIMIC-IV, a total of 757 (25%) patients experienced mortality during their ICU stay. Univariate feature selection helps us to pick out the 20 most critical variables from the original feature. Among the 10 developed machine learning models, the stacking ensemble model exhibited the highest AUC (0.795, 95% CI: 0.763-0.827). Anion gap and age emerged as the most significant features for predicting the mortality risk in SIC. In this study, an ML model was constructed that exhibited excellent performance in predicting in-hospital mortality risk in SIC patients. Specifically, the stacking ensemble model demonstrated superior predictive ability.

Association Between Serum Anion Gap and Mortality in Critically Ill Patients with COPD in ICU: Data from the MIMIC IV Database

Background

Serum anion gap (AG) has been proven to be associated with prognosis in critically ill patients. However, few studies have investigated the association between AG and all-cause mortality in critically ill patients with chronic obstructive pulmonary disease (COPD).

Objective

We hypothesized that the initial AG level would predict the mortality risk in critically ill patients with COPD.

Methods

This retrospective cohort study was based on the Medical Information Mart for Intensive Care (MIMIC) IV database. We extracted demographics, vital signs, laboratory tests, comorbidity, and scoring systems from the first 24 hours after patient ICU admission. Multivariable logistic regression analysis models were used to explore the association between serum AG levels and mortality. Interaction and stratified analyses were conducted including age, gender and comorbidity.

Results

A total of 5531 critically ill patients with COPD were enrolled, composed of 53.6% male and 46.4% female with a median age of 73 years. The all-cause mortality of these patients during ICU hospitalization was 13.7%. The risk of all-cause mortality increased as the AG level increased in the univariate logistic regression analysis (OR=1.13, 95% CI: 1.11-1.15, p<0.01). After adjusting for all the covariates in multivariate logistic regression analysis, the odds ratio was 1.06 (95% CI: 1.04-1.09, p<0.01). Compared with the lowest AG group Q1 (≤11mmol/L), the adjusted OR value for AG and mortality in Q2 (12-13mmol/L) was 0.89 (95% CI: 0.63-1.25, p=0.502), Q3 (14-15mmol/L) was 0.95 (95% CI: 0.68-1.34, p=0.788), and Q4 (≥16mmol/L) was 1.49 (95% CI: 1.10-2.02, p=0.009) respectively. In addition, the results of the subgroup and stratified analyses were robust.

Conclusion

AG is positively related to all-cause mortality in critically ill patients with COPD.

Association between serum anion gap and risk of in-hospital mortality in patients with acute heart failure

A high serum anion gap (AG) at the time of patient admission can lead to the deterioration or even death; data are lacking for patients who suffer acute heart failure (AHF). The present study aimed at exploring the impact of serum AG (SAG) levels on the in-hospital mortality in AHF patients. The study conducted retrospective analysis on the data from the medical information mart for intensive care (MIMIC-IV) database in severe AHF cases. Serum AG, age, sex, concomitant diseases and laboratory tests were collected from patients at admission. Multivariate Cox proportional hazard regression model together with Kaplan Meier (K-M) survival curve served for analyzing the relationship of serum AG with the hospital all-cause mortality (ACM). In addition, subgroup analysis assisted in assessing the concordance. Data from 2774 AHF patients were collected in the study. The hospital ACM rate was 9.2% (254/2774). After correcting potential confounders, multivariate analysis compared the high serum AG level (≥ 16 mmol/L) and the low serum AG level (< 16 mmol/L) (hazard ratio (HR): 1.89 [95% CI 1.42-2.51]). In a similar way, K-M survival curve indicated that hospital survival was lower in patients with high serum, suggesting that high serum AG level could lead to poor AHF prognosis. In patients with AHF, high serum AG level could increase the hospital ACM.

Machine Learning Algorithms Predict Successful Weaning From Mechanical Ventilation Before Intubation: Retrospective Analysis From the Medical Information Mart for Intensive Care IV Database

BACKGROUND

The prediction of successful weaning from mechanical ventilation (MV) in advance of intubation can facilitate discussions regarding end-of-life care before unnecessary intubation.

OBJECTIVE

We aimed to develop a machine learning-based model that predicts successful weaning from ventilator support based on routine clinical and laboratory data taken before or immediately after intubation.

METHODS

We used the Medical Information Mart for Intensive Care IV database, which is an open-access database covering 524,740 admissions of 382,278 patients in Beth Israel Deaconess Medical Center, United States, from 2008 to 2019. We selected adult patients who underwent MV in the intensive care unit (ICU). Clinical and laboratory variables that are considered relevant to the prognosis of the patient in the ICU were selected. Data collected before or within 24 hours of intubation were used to develop machine learning models that predict the probability of successful weaning within 14 days of ventilator support. Developed models were integrated into an ensemble model. Performance metrics were calculated by 5-fold cross-validation for each model, and a permutation feature importance and Shapley additive explanations analysis was conducted to better understand the impacts of individual variables on outcome prediction.

RESULTS

Of the 23,242 patients, 19,025 (81.9%) patients were successfully weaned from MV within 14 days. Using the preselected 46 clinical and laboratory variables, the area under the receiver operating characteristic curve of CatBoost classifier, random forest classifier, and regularized logistic regression classifier models were 0.860 (95% CI 0.852-0.868), 0.855 (95% CI 0.848-0.863), and 0.823 (95% CI 0.813-0.832), respectively. Using the ensemble voting classifier using the 3 models above, the final model revealed the area under the receiver operating characteristic curve of 0.861 (95% CI 0.853-0.869), which was significantly better than that of Simplified Acute Physiology Score II (0.749, 95% CI 0.742-0.756) and Sequential Organ Failure Assessment (0.588, 95% CI 0.566-0.609). The top features included lactate and anion gap. The model's performance achieved a plateau with approximately the top 21 variables.

CONCLUSIONS

We developed machine learning algorithms that can predict successful weaning from MV in advance to intubation in the ICU. Our models can aid the appropriate management for patients who hesitate to decide on ventilator support or meaningless end-of-life care.

The association between serum anion gap and acute kidney injury after coronary artery bypass grafting in patients with acute coronary syndrome

BACKGROUND

The purpose of this study was to explore the association between serum anion gap (SAG) and acute kidney injury (AKI) after coronary artery bypass grafting (CABG) in patients with acute coronary syndrome (ACS) in the Intensive Care Unit (ICU).

METHODS

We retrospectively analyzed the clinical data of 2,428 ACS patients who underwent CABG in the Medical Information Mart for Intensive Care IV (Mimic-IV) database. The endpoint of this study was AKI after CABG. The baseline data of the two groups (non-AKI group vs. AKI group) was compared, and the restricted cubic spline (RCS) plot, multivariable logistic regression model, and subgroup analysis were used to explore the relationship between SAG and the risk of AKI after CABG.

RESULTS

In the adjusted multivariate logistic regression model, SAG was an independent predictor of AKI after CABG (OR = 1.12, 95% CI: 1.02-1.23, P = 0.015). The RCS revealed that the relationship between SAG levels and risk of AKI was J-shaped. When the SAG was ≥ 11.58 mmol/L, the risk of AKI increased by 26% for each unit increase in SAG. Additionally, we further divided the SAG into quartiles. In the fully adjusted model, compared with the first quartile of SAG, the odds ratios (ORs) and 95% confidence intervals (CIs) for AKI risk across the SAG quartiles were 0.729 (0.311, 1.600), 1.308 (0.688-2.478), and 2.221 (1.072, 4.576).

CONCLUSIONS

The SAG level was associated with the risk of AKI after CABG in a J-shaped curve in the ICU. However, the underlying causes of the problem need to be investigated.

Relationship Between Albumin-Corrected Anion Gap and Mortality in Hospitalized Heart Failure Patients

BACKGROUND

Heart failure (HF) is a disease with high morbidity and mortality. Despite the efforts to reduce mortality rates through medical progress, it is necessary to develop markers to identify critically ill patients. In our study, we aimed to investigate the relationship between albumin-corrected anion gap (ACAG) and mortality in hospitalized patients with HF.

METHODOLOGY

We performed a retrospective study that included patients with HF hospitalized in the Erzurum City Hospital between 2015 and 2022. The basal clinical, hematological, and biochemical findings of the patients were obtained from the electronic medical records. ACAG was calculated. The date and causes of death of the patients were searched and recorded through the Republic of Türkiye Ministry of Health Death Notification System (ÖBYS) and Central Population Administration System (MERNIS). Thus, the relationship between ACAG and mortality in hospitalized patients with HF was evaluated.

RESULTS

A total of 205 patients hospitalized for HF were included in the study. The mean age of all people in this study was 71.8 ± 10.7 years. A total of 104 (50.7%) of the patients included in the study were women. The mean left ventricular ejection fraction was 47.2 ± 13.6%. The mean follow-up period of the entire population was 76.5 ± 18.9 months. The mortality rate was 11.7% (24 patients). Serum anion gap (SAG) and ACAG were significantly higher in the group with death outcomes (p = 0.043 and p = 0.012, respectively). Cox regression analysis showed that ACAG was an independent predictor of HF mortality (p = 0.003). ACAG area under the curve was 0.773 (95% CI 0.634 - 0.914), the cut-off was 13, sensitivity was 75%, and specificity was 75.9% (p = 0.002).

CONCLUSION

Statistical analysis showed a meaningful connection between an increase in ACAG and mortality in hospitalized patients with HF. Consequently, ACAG can be used as an independent predictor of mortality in patients with HF.

Combining the anion gap with the sequential organ failure assessment score to evaluate the short-term prognosis of patients in the cardiac intensive care unit

BACKGROUND

We attempted to determine the predictive ability of the first-day Sequential Organ Failure Assessment (SOFA) score in the cardiac intensive care unit, as well as a new score combining the anion gap (AG) with the SOFA score (SOFA-AG).

METHODS

Information was obtained from the Medical Information Mart for Intensive Care III (MIMIC III 1.4) database. We plotted the relationship between the maximum first-day AG and 90-day mortality after admission to the care unit. Patients were divided into five groups based on the hazard ratio (HR) and assigned scores of 0, 1, 2, 3, or 4 points. We compared the area under the curve (AUC) for the receiver-operating characteristic curve of the SOFA and that of the SOFA-AG.

RESULTS

A total of 1316 patients were identified and divided into the following five groups: AG 8 to <16 mmol/L; AG 16 to <17 mmol/L; AG 17 to <19 mmol/L; AG 19 to <21 mmol/L; and AG ≥ 21 mmol/L. The SOFA-AG score had a greater AUC than the SOFA score at 7 days (0.770 vs. 0.711; P < 0.001), 14 days (0.751 vs. 0.692; P < 0.001), 28 days (0.741 vs. 0.684; P < 0.001), and 90 days (0.727 vs. 0.667; P < 0.001).

CONCLUSIONS

The SOFA score showed moderate predictive value only for 7-day mortality after admission to the cardiac intensive care unit, but the SOFA-AG score had improved predictive ability for up to 90 days after admission.

Relationship of Admission Serum Anion Gap and Prognosis of Critically Ill Patients: A Large Multicenter Cohort Study

Background

There 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.

Methods

This 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.

Results

A 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.

Conclusions

Initial serum AG > 16 mmol/L after ICU admission is associated with increased mortality in critically ill patients.

Plasma anion gap and risk of in-hospital mortality in patients with spontaneous subarachnoid hemorrhage

Background

The association between the serum anion gap (AG) and prognosis of patients with spontaneous subarachnoid hemorrhage (SAH) remains unknown. Thus, this study aimed to explore the association between AG levels and mortality in patients with SAH in the intensive care unit (ICU).

Methods

This was a retrospective analysis of data stored in the Medical Information Mart for Intensive Care–IV and eICU Collaborative Research databases. Critically ill patients diagnosed with spontaneous SAH were included. The primary outcome measure was in-hospital all-cause mortality. A multivariate Cox proportional hazards regression model and a restricted cubic spline were used to evaluate the relationship between AG concentration and outcomes. Kaplan–Meier curves were used to compare cumulative survival among patients with AG levels.

Results

A total of 1,114 patients were enrolled. AG concentration was significantly associated with in-hospital all-cause mortality [hazard ratio ([HR], 1.076 (95% confidence interval (CI), 1.021–1.292; p = 0.006)]. The risk of mortality was higher in the Category 2 group (AG ≥10 mmol/L and <13 mmol/L; HR, 1.961; 95% CI, 1.157–3.324; p = 0.0) and the Category 3 group (AG ≥13 mmol/L; HR, 2.151; 95% CI, 1.198–3.864; p = 0.010) than in the Category 1 group (AG < 10 mmol/L). Cumulative survival rates were significantly lower in patients with higher AG levels (log-rank p < 0.001).

Conclusions

In-hospital and ICU mortalities increase with increasing AG concentration in patients with SAH. An increased serum AG level is an independent, significant, and robust predictor of all-cause mortality. Thus, serum AG levels may be used in the risk stratification of SAH.

Association of Plasma Anion Gap with 28-Day Inhospital Mortality and 1-Year Mortality of Patients with Alcohol Use Disorder at ICU Admission: A Retrospective Cohort Study

Background

Alcohol use disorder (AUD) is common in critically ill patients. Plasma anion gap (AG) was known as a feasible parameter and was associated with outcomes of various diseases. This study is intended to explore whether AG is related to 28-day inhospital mortality and 1-year mortality of critically ill patients with AUD.

Method

We extracted data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The association of plasma AG with 28-day inhospital mortality and 1-year mortality of critically ill AUD patients was assessed using Cox proportional hazard regression models and stratification analyses, allowing AG as a time-varying covariate in the models. To evaluate the accuracy of AG in predicting different endpoints, receiver operator characteristic (ROC) curves were used.

Result

Among the 3993 critically ill patients with AUD, AG was positively associated with 28-day inhospital mortality and 1-year mortality after adjusting confounders (p < 0.001 for all). Compared with lower AG (<12 mmol/L), patients in different groups (12 ≤ AG < 14 mmol/L, 14 ≤ AG < 17 mmol/L, 17 ≤ AG < 20 mmol/L, and AG ≥ 20 mmol/L) had different HRs (95% CIs) for 28-day inhospital mortality (1.105, (0.906, 1.347); 1.171, (0.981, 1.398); 1.320, (1.108, 1.573); and 1.487, (1.254, 1.763), respectively) and 1-year mortality (1.037 (0.898, 1.196); 1.091 (0.955, 1.246); 1.201 (1.052, 1.371); and 1.3093 (1.149, 1.492), respectively).

Conclusion

Increased AG is associated with greater 28-day inhospital mortality and 1-year mortality. The effect of AG on all-cause mortality is linear in critically ill AUD patients.

The value of anion gap for predicting the short-term all-cause mortality of critically ill patients with cardiac diseases, based on MIMIC-III database

BACKGROUND

The association of anion gap (AG) with short-term mortality in the critically ill patients with cardiac diseases is still not well understood.

OBJECTIVE

To evaluate the association of AG with short-term mortality, and the predictive ability of AG for short-term mortality in critically ill patients with cardiac diseases.

METHODS

This retrospective cohort study enrolled 9104 critically ill patients with cardiac diseases from the Medical Information Mart for Intensive Care III (MIMIC III) database. The restricted cubic spline models were used to evaluate the nonlinear relationship between AG and short-term mortality. Cox proportional hazards regression models and subgroup analysis were applied to assess the association of AG with short-term mortality.

RESULTS

The data were divided into three groups by AG tertiles: tertile I (AG <12, n = 2095), tertile II (12 ≤ AG < 15, n = 3195), and tertile III (15 ≤ AG, n = 3814). The restricted cubic spline models revealed continuous AG was non-linearly related to short-term mortality. The elevated AG tertiles were strongly associated with higher in-hospital, 30-day and 90-day mortality (all P for trend < 0.001). After adding AG to traditional severity scores, the area under curves (AUCs) elevated significantly compared to severity scores alone (all DeLong's test: P < 0.001). Subgroup analysis did not indicate significant interaction in most diverse subgroups.

CONCLUSION

AG was an independent risk factor for short-term all-cause mortality in critically ill patients with cardiac diseases. AG improved significantly the mortality predictive abilities of traditional severity scores when AG was added to these scores.

Association Between High Serum Anion Gap and All-Cause Mortality in Non-Traumatic Subarachnoid Hemorrhage: A Retrospective Analysis of the MIMIC-IV Database

Background:

High serum anion gap (AG) on admission is often correlated with poor outcomes in critically ill patients; however, data in patients with non-traumatic subarachnoid hemorrhage (SAH) are lacking. Herein, we aimed to identify the association between serum AG and all-cause mortality in patients with non-traumatic SAH.

Methods

A retrospective analysis of data from the Medical Information Mart for Intensive Care (MIMIC-IV) database was performed on critically ill patients with non-traumatic SAH. Serum AG was collected on Intensive Care Unit (ICU) admission, and ICU and hospital all-cause mortality were analyzed. The multivariate Cox proportional hazard regression model and Kaplan-Meier survival curve analysis were used to analyze the correlation of serum AG with ICU and hospital all-cause mortality. Furthermore, interaction and subgroup analyses were evaluated for the consistency of these correlations.

Results

A total of 893 patients with non-traumatic SAH were included in this study. The all-cause mortality in ICU and hospital were 14.8% (132/893), and 18.9% (169/893), respectively. Multivariate analysis after adjusting for potential confounders indicated that high serum AG levels (≥16 mmol/L) were associated with increased risk of ICU and hospital all-cause mortality as compared to that with low serum AG levels (<16mmol/L), (hazards ratio (HR): 2.31 [95% CI: 1.58–3.38]) and HR: 1.91 [95% CI: 1.36–2.67)], respectively). Similarly, the Kaplan–Meier (K–M) survival curve also showed that patients with high serum AG levels presented with a lower survival rate. Stratified analyses further showed that depending on the variable testes, an association between higher serum AG levels and hospital all-cause mortality in different subgroups was observed.

Conclusion

Among patients with non-traumatic SAH, high serum AG level at ICU admission was associated with increased ICU and hospital all-cause mortality.

Early hyperchloremia and outcomes after acute ischemic stroke

OBJECTIVE

Based on the relationship between hyperchloremia and mortality in critically ill patients, we investigated the effect of early hyperchloremia on 90-day outcomes in acute ischemic stroke patients.

MATERIALS AND METHODS

Acute ischemic stroke patients recruited within 5 h of symptom onset were analyzed. Hyperchloremia (defined as 110 mmol/L or greater) at either baseline, or 24, or 48 h after randomization was identified and classified as one occurrence or two or more occurrences. Logistic regression analyses were performed to determine the effects of hyperchloremia on: favorable outcomes (defined by a National Institutes of Health Stroke Scale and/or modified Rankin scale scores of 0-1) at 90-day, death or disability at 90-day, and death within 90-day after accounting for potential confounders.

RESULTS

Among the total of 1275 patients, one and two or more occurrence of hyperchloremia within 48 h were seen in 191 patients and 108 patients, respectively. Compared with patients without hyperchloremia, patients with two or more occurrences of hyperchloremia at significantly higher odds of lack of favorable outcomes (odds ratio 3.0, 95% confidence interval 1.8-5.1) and death or disability (odds ratio 2.6, 95% confidence interval 1.6-4.1) at 90-day after adjustment for age, National Institutes of Health Stroke Scale score strata (6-9, 10-19, ≥ 20), study intervention, initial SBP, and intra-arterial treatment.

CONCLUSIONS

The independent association between sustained hyperchloremia and lack of favorable outcomes at 90-day suggest that avoidance of hyperchloremia may reduce the rate of lack of favorable outcomes and death or disability in patients with acute ischemic stroke.

Association between delta anion gap and hospital mortality for patients in cardiothoracic surgery recovery unit: a retrospective cohort study

Backgrounds

High level of anion gap (AG) was associated with organic acidosis. This study aimed to explore the relationship between delta AG (ΔAG = AG_max − AG_min) during first 3 days after intensive care unit (ICU) admission and hospital mortality for patients admitted in the cardiothoracic surgery recovery unit (CSRU).

Methods

In this retrospective cohort study, we identified patients from the open access database called Multiparameter Intelligent Monitoring in Intensive Care III (MIMIC III). A logistic regression model was established to predict hospital mortality by adjusting confounding factors using a stepwise backward elimination method. We conducted receiver operating characteristic (ROC) curves to compare the diagnostic performance of acid–base variables. Cox regression model and Kaplan Meier curve were applied to predict patients’ 90-day overall survival (OS).

Results

A total of 2,860 patients were identified. ΔAG was an independent predictive factor of hospital mortality (OR = 1.24 per 1 mEq/L increase, 95% CI: 1.11–1.39, p < 0.001). The area under curve (AUC) values of ΔAG suggested a good diagnostic accuracy (AUC = 0.769). We established the following formula to estimate patients’ hospital mortality: Logit(P) = − 15.69 + 0.21ΔAG + 0.13age-0.21BE + 2.69AKF. After calculating Youden index, patients with ΔAG ≥ 7 was considered at high risk (OR = 4.23, 95% CI: 1.22–14.63, p = 0.023). Kaplan Meier curve demonstrated that patients with ΔAG ≥ 7 had a poorer 90-day OS (Adjusted HR = 3.20, 95% CI: 1.81–5.65, p < 0.001).

Conclusion

ΔAG is a prognostic factor of hospital mortality and 90-day OS. More prospective studies are needed to verify and update our findings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12893-022-01625-9.

Early Hyperchloremia is Independently Associated with Death or Disability in Patients with Intracerebral Hemorrhage

BACKGROUND

On the basis of increased mortality associated with hyperchloremia among critically ill patients, we investigated the effect of occurrence of early hyperchloremia on death or disability at 90 days in patients with intracerebral hemorrhage (ICH).

METHODS

We analyzed the data from Antihypertensive Treatment of Cerebral Hemorrhage 2 trial, which recruited patients with spontaneous ICH within 4.5 h of symptom onset. Patients with increased serum chloride levels (110 mmol/L or greater) at either baseline or 24, 48, or 72 h after randomization were identified. We further graded hyperchloremia into one occurrence or two or more occurrences within the first 72 h. Two logistic regression analyses were performed to determine the effects of hyperchloremia on (1) death within 90 days and (2) death or disability at 90 days after adjustment for potential confounders.

RESULTS

Among the total of 1,000 patients analyzed, hyperchloremia within 72 h was seen in 114 patients with one occurrence and in 154 patients with two or more occurrences. Patients with one occurrence of hyperchloremia (odds ratio [OR] 2.5, 95% confidence interval [CI] 1.1-5.5) and those with two or more occurrences (OR 2.6, 95% CI 1.3-5.0) had significantly higher odds of death within 90 days after adjustment for age, race and ethnicity, National Institutes of Health Stroke Scale score strata, hematoma volume, presence or absence of intraventricular hemorrhage, cigarette smoking, previous stroke, and maximum hourly dose of nicardipine. Patients with two or more occurrences of hyperchloremia (OR 3.4, 95% CI 2.1-5.6) had significantly higher odds of death or disability at 90 days compared with patients without hyperchloremia after adjustment for the abovementioned potential confounders.

CONCLUSIONS

The independent association between hyperchloremia and death or disability at 90 days suggests that avoidance of hyperchloremia may reduce the observed death or disability in patients with ICH.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov: NCT01176565.

Laboratory Markers of Acidosis and Mortality in Cardiogenic Shock: Developing a Definition of Hemometabolic Shock

BACKGROUND

Acidosis and higher lactate predict worse outcomes in cardiogenic shock (CS) patients. We sought to determine whether overall acidosis severity on admission predicted in-hospital mortality in CS patients.

METHODS

This retrospective descriptive analysis included CS patients admitted to a single academic tertiary cardiac intensive care unit from 2007 to 2015. Admission arterial pH, base excess, and anion gap values were used to generate a Composite Acidosis Score (range 0-5, with a score ≥2 defining Severe Acidosis). Adjusted in-hospital mortality was analyzed using multivariable logistic regression.

RESULTS

We included 1,065 patients with median age of 68.9 (59.0, 77.2) years (36.4% females). Concomitant diagnoses included cardiac arrest in 38.1% and acute coronary syndrome in 59.1%. Severe Acidosis was present in 35.2%, and these patients had worse shock and more organ failure. In-hospital mortality occurred in 34.1% and was higher among patients with Severe Acidosis (54.9% vs. 22.4%, adjusted odds ratio [OR] 2.01, 95% CI 1.43-2.83, P < 0.001). Increasing Composite Acidosis Score was associated with higher in-hospital mortality (adjusted OR 1.25 per point, 95% CI 1.11-1.40, P < 0.001). Severe Acidosis was associated with higher hospital mortality at every level of shock severity and organ failure (all P < 0.05). Admission lactate level had equivalent discrimination for in-hospital mortality as the Composite Acidosis Score (0.69 vs. 0.66; P = 0.32 by De Long test).

CONCLUSION

Given its incremental association with higher in-hospital mortality among CS patients beyond shock severity and organ failure, we propose Severe Acidosis as a marker of hemometabolic shock. Lactate levels performed as well as a composite measure of acidosis for predicting mortality.

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

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.

Association Between Anion Gap and Mortality in Critically Ill Patients with Cardiogenic Shock

Background

No epidemiological study has determined the association between the anion gap (AG) and all-cause mortality in critically ill patients with cardiogenic shock (CS). This study was conducted to clarify the relationship between the AG and mortality in CS.

Methods

We extracted clinical data from the public database, MIMIC-III V1.4, by using a generalized additive model to identify the nonlinear relationship between the AG and the 30-day mortality in 1248 intensive care unit patients. Cox proportional hazard models were used to assess the association between the AG and the 30-day, 90-day, and 365-day mortality in CS.

Results

The AG and 30-day all-cause mortality showed a nonlinear relationship, indicated by a J-shaped curve. In the multivariate analysis, after adjusting for potential confounders, a high AG was associated with an increased risk of 30-day, 90-day, and 365-day all-cause mortality in patients with CS compared with patients who had low AG (hazard ratio [95% confidence interval] 1.62 [1.14-2.30]; 1.35 [1.04-1.84]; and 1.38 [1.03-1.84], respectively). Similar results were shown in Model I (adjusted for age, sex and ethnicity) and in Model II (fully adjusting for age, ethnicity, sex, acute kidney injury stage, CHF, renal disease, stroke, malignancy, respiratory failure, pneumonia, sodium, potassium, chloride, BUN, PT, WBC, pH, creatinine, albumin, glucose, bicarbonate, vasopressor use, diastolic blood pressure, respiration rate, temperature, the Elixhauser Comorbidity Index, SOFA score and SAPSII score).

Conclusion

The relationship between the AG and 30-day all-cause mortality followed a J-shaped curve. Higher AG was associated with an increased risk of 30-day, 90-day, and 365-day all-cause mortality in critically ill patients with CS.

The Association Between Serum Anion Gap and All-Cause Mortality in Disseminated Intravascular Coagulation Patients: A Retrospective Analysis

Purpose

Studies regarding death risk factors of disseminated intravascular coagulation (DIC) patients were limited. Therefore, we conducted this study to investigate whether the serum anion gap (AG) was independently related to all-cause mortality of DIC patients.

Methods

We used the data from Medical Information Mart for Intensive Care III version 1.4 (MIMIC-III v1.4). A total of 2,654 DIC patients were included. The main outcomes were in-hospital, 30-day, and 90-day all-cause mortality. The AG was measured upon ICU admission and its association with mortality was evaluated using the Cox proportional-hazards regression model. The generalized additive model and the smooth curve fitting were introduced to examine the non-linear association.

Results

After adjusting for potential covariates, the in-hospital, 30-day, and 90-day all-cause mortality were positively correlated with AG. The hazard ratio (HR), confidence intervals (CI), and P were 1.05 (1.04–1.07) <0.0001, 1.06 (1.04–1.07) <0.0001, and 1.05 (1.03–1.07) <0.0001, respectively. We did not find an obvious non-linear relationship between AG and in-hospital, 30-day, and 90-day mortality, which indicated that the association between AG and all-cause mortality of DIC patients was nearly linear.

Conclusion

Serum AG is positively related with all-cause mortality in DIC patients.

Elevated Venous to Arterial Carbon Dioxide Gap and Anion Gap Are Associated with Poor Outcome in Cardiogenic Shock Requiring Extracorporeal Membrane Oxygenation Support

Optimal management of cardiogenic shock requiring extracorporeal membrane oxygenation (ECMO) is still an evolving area in which assessment and optimization of the microcirculation may be critically important. We hypothesized that the venous arterial carbon dioxide gap (P(v-a)CO2 gap); the ratio of this gap to arterio-venous oxygen content (P(v-a)CO2/C(a-v)O2 ratio) and the anion gap would be early indicators of microcirculatory status and useful parameters for outcome prediction during ECMO support. We retrospectively reviewed 31 cardiogenic shock patients requiring veno-arterial ECMO, calculating P(v-a)CO2 gap and P(v-a)CO2/C(a-v)O2 ratios in the first 36 hours and the final 24 hours of ECMO support. Sixteen patients (52%) survived and 15 (48%) died. After 24 hours of ECMO support, the P(v-a)CO2 gap (4.9 ± 1.5 vs. 6.8 ± 1.9 mm Hg; p = 0.004) and anion gap (5.2 ± 1.8 vs. 8.7 ± 2.7 mmol/L; p < 0.001) were significantly higher in non-survivors. In the final 24 hours of ECMO support, the P(v-a)CO2 gap (3.5 ± 1.6 vs. 10.5 ± 3.2 mm Hg; p < 0.001), P(v-a)CO2/C(a-v)O2 ratio (1.1 ± 0.5 vs. 2.7 ± 1.0; p < 0.001), anion gap (5.1 ± 3.0 vs. 9.3 ± 5.9 mmol/L; p = 0.02), and lactate (median 1.0 [interquartile range {IQR}: 0.7-1.5] vs. 2.8 [IQR: 1.7-7.7] mmol/L; p = <0.001) were all significantly lower in survivors. Increasing P(v-a)CO2 gap and increasing anion gap were significantly associated with increased risk of mortality. Optimum cut-points for prediction of mortality were 6 mm Hg for P(v-a)CO2 gap in combination with an anion gap above 6 mmol/L in the first 24 hours of ECMO in patients with cardiogenic shock requiring ECMO.

A Higher Serum Anion Gap Is Associated with the Risk of Progressing to Impaired Fasting Glucose and Diabetes

Impaired fasting glucose (IFG) is a reversible intermediate hyperglycemia stage with an increasing risk of diabetes and related complications. Our study was designed to identify the relationship between the serum anion gap and the risk of progressing to impaired fasting glucose and diabetes. Here, we performed a prospective, population-based study among 1191 Chinese individuals aged 22-87 years who took health examinations annually between 2006 and 2012 including clinical features and plasma metabolites. All of the participants had no history of diabetes or related chronic complications. Logistic regression analysis was designed to examine the associations between clinical and metabolomic factors and the risk of developing IFG or diabetes. Among them, 58 subjects whose fasting glucose were between 6.1 and 7 mmol/L were diagnosed as IFG or diabetes. After adjusting for age, sex, body mass index (BMI), high-density lipoprotein (HDL), low-density lipoprotein (LDL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), systolic blood pressure (SBP), diastolic blood pressure (DBP), potassium, and albumin at baseline, the participants in the upper tertiles of serum anion gap (SAG) had higher odds of progressing to IFG or diabetes than those in the lower tertiles. A receiver operating characteristic (ROC) curve was analyzed, and the optimal cutoff level for the anion gap to predict incident IFG or diabetes was 13.76 mmol/L, and the area under the ROC curve (AUC) was 0.623. Our data demonstrate that a higher serum anion gap is associated with the risk of developing IFG or diabetes.

Serum Anion Gap Is Associated with All-Cause Mortality among Critically Ill Patients with Congestive Heart Failure

Background

Congestive heart failure (CHF) is a complex clinical syndrome, with high morbidity and mortality. Serum anion gap (SAG) is associated with the severity of various cardiovascular diseases. However, the role of SAG indicators in CHF is unclear.

Methods and Results

A retrospective analysis of data from Multiparameter Intelligent Monitoring in Intensive Care III version 1.4 was conducted in critically ill patients with CHF. The clinical information of each patient, including demographic data, comorbidities, vital signs, scores, and laboratory indicators, were successfully obtained. Cox proportional hazards models were used to determine the relationship between SAG and mortality in patients with CHF, the consistency of which was further verified by subgroup analysis.

Results

A total of 7426 subjects met the inclusion criteria. Multivariate analysis showed that after adjusting for age, gender, ethnicity, and other potential confounders, increased SAG was significantly related to an increase in 30- and 90-day all-cause mortalities of critically ill patients with CHF compared with decreased SAG (tertile 3 versus tertile 1: adjusted hazard ratio, 95% confidence interval: 1.74, 1.46–2.08; 1.53, 1.32–1.77). Subgroup analysis indicated that the association between SAG and all-cause mortality presented similarities in most strata.

Conclusion

SAG at admission could be a promising predictor of all-cause mortality in critically ill patients with CHF.

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

BACKGROUND

Recent studies reported that serum anion gap could be regarded as a prognostic biomarker for patients admitted to intensive care units. However, the association between AG and mortality in cerebral infarction patients remained largely unknown.

METHODS

Relevant clinical data were collected from Medical Information Mart for Intensive Care III. Patients were divided into three groups according to tertiles of AG. Kaplan-Meier curve and Cox proportional hazards models were used to evaluate the association between AG levels and all-cause mortality. Subgroup analyses were performed to verify the predictive role of AG on mortality.

RESULTS

Kaplan-Meier analysis showed that patients with higher AG had shorter survival time. Cox regression model indicated high AG as an independent risk factor of 30-day, 60-day and 180-day all-cause mortality (30-day: HR = 2.45, 95% CI = 1.21-4.97, 60-day: HR = 2.04, 95% CI = 1.07-3.89, and 180-day: HR = 1.85, 95% CI = 1.02-3.36). However, no significance was observed between AG and 365-day all-cause mortality (HR = 1.56, 95% CI = 0.87-2.78).

CONCLUSIONS

High AG was associated with increased risk of all-cause mortality, and AG could be an independent short-term prognostic factor for cerebral infarction.

Anion Gap Was Associated with Inhospital Mortality and Adverse Clinical Outcomes of Coronary Care Unit Patients

Background

Anion gap (AG) has been proved to be associated with prognosis of many cardiovascular diseases. This study is aimed at exploring the association of AG with inhospital all-cause mortality and adverse clinical outcomes in coronary care unit (CCU) patients.

Method

All data of this study was extracted from Medical Information Mart for Intensive Care III (MIMIC-III, version 1.4) database. All patients were divided into four groups according to AG quartiles. Primary outcome was inhospital all-cause mortality. Lowess smoothing curve was drawn to describe the overall trend of inhospital mortality. Binary logistic regression analysis was performed to determine the independent effect of AG on inhospital mortality.

Result

A total of 3593 patients were enrolled in this study. In unadjusted model, as AG quartiles increased, inhospital mortality increased significantly, OR increased stepwise from quartile 2 (OR, 95% CI: 1.01, 0.74-1.38, P = 0.958) to quartile 4 (OR, 95% CI: 2.72, 2.08-3.55, P < 0.001). After adjusting for possible confounding variables, this association was attenuated, but still remained statistically significant (quartile 1 vs. quartile 4: OR, 95% CI: 1.02, 0.72-1.45 vs. 1.49, 1.07-2.09, P = 0.019). Moreover, CCU mortality (P < 0.001) and rate of acute kidney injury (P < 0.001) were proved to be higher in the highest AG quartiles. Length of CCU (P < 0.001) and hospital stay (P < 0.001) prolonged significantly in higher AG quartiles. Maximum sequential organ failure assessment score (SOFA) (P < 0.001) and simplified acute physiology score II (SAPSII) (P < 0.001) increased significantly as AG quartiles increased. Moderate predictive ability of AG on inhospital (AUC: 0.6291), CCU mortality (AUC: 0.6355), and acute kidney injury (AUC: 0.6096) was confirmed. The interactions were proved to be significant in hypercholesterolemia, congestive heart failure, chronic lung disease, respiratory failure, oral anticoagulants, Beta-blocks, angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor blocker (ARB), and vasopressin treatment subgroups.

Conclusion

AG was an independent risk factor of inhospital all-cause mortality and was associated with adverse clinical outcomes in CCU patients.

Anion gap reference intervals show instrument dependence and weak correlation with albumin levels

BACKGROUND

Anion gap (AG) aids the differential diagnosis of acid-base disorders. Its value has decreased, because of new analytical methods. Our goal was to compare AG reference intervals for different instruments and Southeast Asian populations.

METHODS

We studied AG at three hospitals. One used the cobas 8000; two others, the Architect c16000. We included consecutive adults ≥18 years whose samples were sent for electrolytes and creatinine. We assessed AG for all patients and patients with normal electrolytes.

RESULTS

AG means differed significantly (P < 0.001) between the three hospitals for all patients and the normal electrolyte subgroup. AG reference intervals from all patients were 9-19, 5-15, and 5-15 mmol/L, and for the normal electrolyte subgroup, 10-17, 6-14, and 5-12 mmol/L, respectively. Compared to the normal albumin group, hypoalbuminemia patients showed lower AG in two hospitals (P < 0.001, P = 0.03), whereas patients with hyperalbuminemia demonstrated higher AG in all three hospitals (P < 0.001).

CONCLUSIONS

Different instruments produce different AGs. There is a weak correlation between albumin levels and AG. Laboratorians should verify reference intervals used when detecting laboratory errors and assisting clinicians in the differential diagnosis of acid base disorders and other medical conditions.

Derivation and Validation of a Novel Cardiac Intensive Care Unit Admission Risk Score for Mortality

Background

There are no risk scores designed specifically for mortality risk prediction in unselected cardiac intensive care unit (CICU) patients. We sought to develop a novel CICU‐specific risk score for prediction of hospital mortality using variables available at the time of CICU admission.

Methods and Results

A database of CICU patients admitted from January 1, 2007 to April 30, 2018 was divided into derivation and validation cohorts. The top 7 predictors of hospital mortality were identified using stepwise backward regression, then used to develop the Mayo CICU Admission Risk Score (M‐CARS), with integer scores ranging from 0 to 10. Discrimination was assessed using area under the receiver‐operator curve analysis. Calibration was assessed using the Hosmer–Lemeshow statistic. The derivation cohort included 10 004 patients and the validation cohort included 2634 patients (mean age 67.6 years, 37.7% females). Hospital mortality was 9.2%. Predictor variables included in the M‐CARS were cardiac arrest, shock, respiratory failure, Braden skin score, blood urea nitrogen, anion gap and red blood cell distribution width at the time of CICU admission. The M‐CARS showed a graded relationship with hospital mortality (odds ratio 1.84 for each 1‐point increase in M‐CARS, 95% CI 1.78–1.89). In the validation cohort, the M‐CARS had an area under the receiver‐operator curve of 0.86 for hospital mortality, with good calibration (P=0.21). The 47.1% of patients with M‐CARS <2 had hospital mortality of 0.8%, and the 5.2% of patients with M‐CARS >6 had hospital mortality of 51.6%.

Conclusions

Using 7 variables available at the time of CICU admission, the M‐CARS can predict hospital mortality in unselected CICU patients with excellent discrimination.

Serum anion gap on admission predicts intensive care unit mortality in patients with aortic aneurysm

It has been widely reported that the serum anion gap is significantly associated with mortality in intensive care unit (ICU); however, it remains unknown whether the association is present in aortic aneurysm (AA) patients. The present study aimed to investigate the association between the admission serum anion gap and ICU mortality in AA patients. Data extracted from a publicly accessible clinical database using a modifiable data mining technique were analyzed retrospectively, mainly by employing multivariable logistic regression analysis. The primary study outcome was ICU mortality. A total of 273 patient records were analyzed. The ICU mortality was 8.79% (24/273). The median serum anion gap was significantly higher in non-survivors [17.50 mEq/l, interquartile range (IQR) 15.75-22.50 mEq/l] compared with survivors [13.00 mEq/l, IQR 11.00-15.00 mEq/l, P<0.001]. Multivariate analysis resulted in identification of a clear association between admission serum anion gap and ICU mortality in AA patients [odds ratio (OR) 1.38 per 1 mEq/l increase, 95% confidence interval (CI) 1.08-1.76]. The area under the receiver operating characteristic curve showed an outstanding discrimination ability in predicting ICU mortality (area under curve 0.8513, 95% CI 0.7698-0.9328). In conclusion, admission serum anion gap may serve as a strong predictor of ICU mortality for AA patients.

Can base excess and anion gap predict lactate level in diagnosis of septic shock?

Background

Lactate measurement is the key component in septic shock identification and resuscitation. However, point-of-care lactate testing is not widely used due to the lack of access to nearby test equipment. Biomarkers such as serum lactate, anion gap (AG), and base excess (BE) are used in determining shock in patients with seemingly normal vital signs.

Purpose

We aimed to determine if these biomarkers can be used interchangeably in patients with septic shock in the emergency setting.

Patients and methods

A prospective observational cohort study was undertaken at a tertiary hospital in southern Thailand. Baseline point-of-care BE, AG, and serum lactate were recorded in all patients presenting with septic shock at the emergency department. Overall correlations including area under the receiver operating characteristic curve (AUROC) for both BE and AG to predict serum lactate level were calculated.

Results

One hundred and fifteen patients were enrolled. Pearson correlation of serum lactate to BE was −0.59 (r² = 0.35; 95% confidence interval [CI], −0.69 to −0.44; P < 0.001) and BE to AG was −0.67 (r² = 0.49; 95% CI, −0.76 to −0.55; P < 0.001), and serum lactate to AG was 0.64 (r² = 0.41; 95% CI, 0.52 to 0.74; P < 0.001). A cut-off point of 15.8 for AG identified a lactate level ≥2 mmol/L (sensitivity, 71.4%; specificity, 80.7%; and AUROC, 0.76), and the best cut-off value to predict a lactate level ≥4 mmol/L was 18.5 (sensitivity, 64.2%; specificity, 85.5%; and AUROC 0.78).

Conclusion

In patients with septic shock, lactate and AG showed a strong correlation with each other, whereas lactate and BE showed a moderate correlation with each other. Thus, these biomarkers can be used interchangeably to help determine septic shock earlier in patients.

A systematic review and diagnostic test accuracy meta-analysis of the validity of anion gap as a screening tool for hyperlactatemia

Objective

This systematic review and meta-analysis seeks to determine the validity of the anion gap to screen for hyperlactatemia in critically ill patients. We have previously shown that the anion gap does not predict 31-day and in-hospital mortality in critically ill patients. The present review aims to add confirmatory evidence to identify whether the anion gap is a suitable tool for risk stratification in low-resource countries.

Results

Nine studies reporting on 4504 samples from 2111 patients were included. The anion gap failed to detect hyperlactatemia defined as lactate above 2.5 mmol/l but showed good discriminatory ability for the detection of severe hyperlactatemia defined as lactate over 4 mmol/l. At the 2.5 mmol/l threshold, the anion gap had high specificity but low sensitivity for the detection of hyperlactatemia. A meta-analysis of correlation coefficients yielded high statistical heterogeneity. Therefore, in keeping with our previous findings, the use of the anion gap for risk stratification as an alternative to lactate cannot be recommended. However, the strength of the evidence we have synthesised is adversely affected by the small number of studies included, inconsistency of effect measures and positivity thresholds reported, and selection bias within individual studies. PROSPERO Registration Number: CRD42015016470 (registered on the 4th February 2015).

Electronic supplementary material

The online version of this article (10.1186/s13104-017-2853-9) contains supplementary material, which is available to authorized users.