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

Albumin corrected anion gap for predicting in-hospital death among patients with acute myocardial infarction: A retrospective cohort study

OBJECTIVE

To explore the relationship between Anion Gap (AG), Albumin Corrected AG (ACAG), and in-hospital mortality of Acute Myocardial Infarction (AMI) patients and develop a prediction model for predicting the mortality in AMI patients.

METHODS

This was a retrospective cohort study based on the Medical Information Mart for Intensive Care (MIMIC)-Ⅲ, MIMIC-IV, and eICU Collaborative Study Database (eICU). A total of 9767 AMI patients who were admitted to the intensive care unit were included. The authors employed univariate and multivariable cox proportional hazards analyses to investigate the association between AG, ACAG, and in-hospital mortality; p < 0.05 was considered statistically significant. A nomogram incorporating ACAG and clinical indicators was developed and validated for predicting mortality among AMI patients.

RESULTS

Both ACAG and AG exhibited a significant association with an elevated risk of in-hospital mortality in AMI patients. The C-index of ACAG (C-index = 0.606) was significantly higher than AG (C-index = 0.589). A nomogram (ACAG combined model) was developed to predict the in-hospital mortality for AMI patients. The nomogram demonstrated a good predictive performance by Area Under the Curve (AUC) of 0.763 in the training set, 0.744 and 0.681 in the external validation cohort. The C-index of the nomogram was 0.759 in the training set, 0.756 and 0.762 in the validation cohorts. Additionally, the C-index of the nomogram was obviously higher than the ACAG and age shock index in three databases.

CONCLUSION

ACAG was related to in-hospital mortality among AMI patients. The authors developed a nomogram incorporating ACAG and clinical indicators, demonstrating good performance for predicting in-hospital mortality of AMI patients.

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.

Dynamics of serum anion gaps with in-hospital mortality: Analysis of the multi-open databases

BACKGROUND

Few studies have investigated the relationship between the anion gap, including the corrected anion gap, and patient mortality in intensive care units (ICUs) without restricting the analysis to specific diseases or medical specialties. Our primary objective was to investigate the association between the anion gap and ICU mortality using multiple open-access databases.

METHODS

We identified 4229 subjects from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, whose entries were from between 2008 and 2019. For each patient, the anion gap and corrected anion gap were calculated, and the study sample was divided into tertile groups (T) according to these levels. The association between the anion gap and in-hospital mortality was assessed using hazard ratios (HRs) and 95% confidence intervals (CIs) derived from a multivariable-adjusted Cox proportional hazards model. Besides MIMIC-IV, we also incorporated study samples from two other databases (MIMIC-III and electronic ICU) to calculate summary HRs using a random-effects meta-analysis.

RESULTS

Within MIMIC-IV, 1015 patients (24%) died during an average follow-up period of 15.5 days. The fully adjusted HRs and 95% CIs for T2 and T3, relative to T1, were 1.31 (95% CI 1.08-1.58) and 1.54 (95% CI 1.24-1.90), respectively. When grouped by corrected anion gap, the results remained statistically significant. In the meta-analysis, the summary HRs and 95% CIs for T2 and T3 were 1.24 (95% CI 1.08-1.43) and 1.55 (95% CI 1.33-1.82), respectively.

CONCLUSIONS

Both the anion gap and corrected anion gap were associated with in-hospital mortality regardless of specific diseases or medical specialties.

The correlation between albumin-corrected anion gap and prognosis in patients with acute myocardial infarction

AIMS

Acute myocardial infarction (AMI) is a cardiovascular disease with high morbidity and mortality. We collected patients with AMI from the Medical Information Mart for Intensive Care IV (v2.0) database and explored the association between serum albumin-corrected anion gap (ACAG) level and mortality in patients with AMI.

METHODS AND RESULTS

Data of adult patients with AMI were collected. According to the 360 day prognosis, patients were divided into survival and non-survival groups. Based on the ACAG level, patients were then divided into normal and high ACAG groups. Cox hazard proportional models and restricted cubic splines (RCSs) were used to investigate the correlation between ACAG and mortality. Kaplan-Meier curves were created to compare the cumulative survival rates between the high and normal ACAG groups. The receiver operating characteristic (ROC) curve was used to analyse the predictive value of ACAG for the prognosis of patients with AMI. Sensitivity and subgroup analyses were conducted to revalidate the results. Finally, 1783 patients were included. Elevated ACAG (>20 mmol/L) was significantly associated with 30 and 360 day mortality (P < 0.001). Adjusted for multiple confounding factors, the Cox proportional hazard analysis showed that elevated ACAG (>20 mmol/L) was an independent risk factor of increased all-cause mortality in patients with AMI (hazard ratio 1.423, 95% confidence interval 1.206-1.678, P < 0.001). RCS analysis further showed that there was a non-linear trend relationship between ACAG and the risk of all-cause mortality at 30 and 360 days (χ2 = 10.750, P = 0.013; χ2 = 13.960, P = 0.003). Kaplan-Meier survival curves showed that the 30 and 360 day cumulative survival rates of patients with AMI were significantly lower (log-rank test, χ2 = 98.880, P < 0.001; χ2 = 105.440, P < 0.001) in the high ACAG group. ROC curve analysis showed that the area under the curve (AUC) of ACAG was 0.651, while the AUC of anion gap (AG) was 0.609, indicating that ACAG had a higher predictive value for 360 day mortality than AG. When combined with Sequential Organ Failure Assessment score, the predictive performance of ACAG for 360 day mortality was better, with an AUC of 0.699. Sensitivity and subgroup analyses were conducted suggesting the stability of our results.

CONCLUSIONS

Elevated serum ACAG (≥20 mmol/L) is an independent risk factor for short-term and long-term mortality in critically ill patients with AMI, and it may assist clinicians and nurses identifying high-risk patients.

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.

Identifying prognostic factors for pulmonary embolism patients with hemodynamic decompensation admitted to the intensive care unit

We aimed to determine prognostic indicators of PE patients with hemodynamic decompensation admitted to the ICU. PE patients with hemodynamic decompensation at ICU admission from Medical Information Mart for Intensive Care IV database were included. Least absolute shrinkage and selection operator with 2 specific lambdas were performed to reduce the dimension of variables after univariate analysis. Then we conducted multivariate logistic regression analysis and 2 models were built. A total of 548 patients were included, among whom 187 died. Lactate, creatine-kinase MB, troponin-T were significantly higher in death group. Eight common factors were screened out from first model statistically mostly in consistent with second model: older age, decreased hemoglobin, elevated anion gap, elevated International Standard Ratio (INR), elevated respiratory rate, decreased temperature, decreased blood oxygen saturation (SpO2) and the onset of cardiac arrest were significantly risk factors for in-Hospital mortality. The nonlinear relationships between these indicators and mortality were showed by the restricted cubic spline and cutoff values were determined. Our study demonstrated that age, hemoglobin levels, anion gap levels, INR, respiratory rate, temperature, SpO2 levels, the onset of cardiac arrest could be applied to predict mortality of PE patients with hemodynamic decompensation at ICU admission.

The relationship between albumin corrected anion gap levels and mortality in patients with asthma in the ICU

Although previous studies have suggested that albumin-corrected anion gap (ACAG) may be a predictor of mortality in critically ill patients in intensive care unit (ICU), its utility in the context of asthma has not been definitively established. In this study, baseline data, albumin concentration, anion gap (AG) and 30-d mortality data were retrieved from the Medical Information Mart for Intensive Care IV database (MIMIC-IV) for patients with asthma in the intensive care unit. Receiver operating characteristic (ROC) curves were constructed to analyze the predictive ability of ACAG and AG. The risk of 30-day mortality among patients with ACAG and asthma was analyzed using a restricted cubic spline (RCS) plot. Decision curve analysis (DCA) was used to evaluate the clinical usefulness of ACAG as a prognostic factor for 30-day mortality. Subsequently, subgroup analysis was conducted to explore potential variations in the relationship between ACAG and 30-day mortality based on factors such as sex, age, whether the asthma was acute, and other co-morbidities. Our study reveals that ACAG is a significant independent predictor of 30-day mortality in asthmatic patients receiving intensive care. The area under the AUC curve for ACAG was found to be 0.703, which is higher than that of AG, indicating that ACAG has a better predictive ability for 30-day mortality in this population. Furthermore, higher levels of ACAG were found to be associated with increased risk of 30-day mortality in asthmatic patients. In addition, decision curve analysis (DCA) demonstrated that the net benefit of ACAG was greater than that of AG. These findings suggest that ACAG may be a valuable prognostic factor for predicting 30-day mortality in asthmatic patients in the ICU. Our study provides evidence that ACAG is associated with an increased risk of 30-d mortality and has better predictive value in patients with combined asthma who are admitted to the ICU than AG.

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.

Association of serum anion gap and risk of long-term mortality in patients following coronary artery bypass grafting: A propensity score matching study

BACKGROUND

The present study aimed to explore the relationship between serum anion gap (AG) and long-term mortality in patients undergoing coronary artery bypass grafting (CABG).

METHODS

Clinical variables were extracted among patients undergoing CABG from Medical Information Mart for Intensive Care III (MIMIC III) database. The primary outcome was 4-year mortality following CABG. An optimal cut-off value of AG was determined by the receiver operating characteristic (ROC) curve. The Kaplan-Meier (K-M) analysis and multivariate Cox hazard analysis were performed to investigate the prognostic value of AG in long-term mortality after CABG. To eliminate the bias between different groups, propensity score matching (PSM) was conducted to validate the findings.

RESULTS

The optimal cut-off value of AG was 17.00 mmol/L. Then a total of 3162 eligible patients enrolled in this study were divided into a high AG group (≥17.00, n = 1022) and a low AG group (<17.00, n = 2,140). A lower survival rate was identified in the high AG group based on the K-M curve (p < .001). Compared with patients in the low AG group, patients in the high AG group had an increased risk of long-term mortality [1-year mortality: hazard ratio, HR: 2.309, 95% CI (1.672-3.187), p < .001; 2-year mortality: HR: 1.813, 95% CI (1.401-2.346), p < .001; 3- year mortality: HR: 1.667, 95% CI (1.341-2.097), p < .001; 4-year mortality: HR: 1.710, 95% CI (1.401-2.087), p < .001] according to multivariate Cox hazard analysis. And further validation of above results was consistent in the matched cohort after PSM.

CONCLUSIONS

The AG is an independent predictive factor for long-term all-cause mortality in patients following CABG, where a high AG value is associated with an increased mortality.

Predictive value of the serum anion gap for 28-day in-hospital all-cause mortality in sepsis patients with acute kidney injury: a retrospective analysis of the MIMIC-IV database

Background

The kidney is one of the most vulnerable organs in sepsis patients, which mainly manifests as sepsis-associated acute kidney injury (SA-AKI). The case fatality rate of SA-AKI is high, and thus, predicting the risk of SA-AKI-related death is hugely significant. Anion gap (AG) is an important indicator in critical illness patients. The present study aimed to analyze the predictive value of the AG for the short-term prognosis of SA-AKI patients.

Methods

SA-AKI patient data from the Medical Information Mart for Intensive Care (MIMIC-IV) database were collected retrospectively. Hospitalized septic patients who meet the inclusion criteria were included in the final analysis. All laboratory test parameters only included the data generated within the first 24 hours after the patient entered the intensive care unit (ICU) and the extreme value. Univariate and multivariate logistic regression analyses were performed to analyze the risk factors related to the death of SA-AKI patients within 28 days during hospitalization in the ICU.

Results

A total of 3,684 SA-AKI patients were included, including 3,305 patients with low AG (<18 mmol/L) and 379 patients with high AG (≥18 mmol/L). Among these patients, 497 cases (13.5%) died during hospitalization, including 376 cases (11.4%) in the low AG group and 121 cases (31.9%) in the high AG group. Multivariate logistic regression analysis showed that elevated AG increased the risk of death in SA-AKI patients within 28 days during hospitalization in the ICU (odds ratio =1.2, 95% confidence interval: 1.2-1.3). Further analysis showed that the risk of death of SA-AKI patients within 28 days during hospitalization in the ICU was increased when AG ≥14 mmol/L. The relationship between AG level and the risk of death of SA-AKI patients during hospitalization was S-shaped.

Conclusions

In clinical practice, AG levels can serve as a valuable predictor of the death risk of SA-AKI patients during hospitalization.

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 Anion Gap and Mortality in Critically Ill Patients with Hip Fractures

Objectives

Epidemiological evidence suggests that anion gap (AG) has been reported to serve as an independent predictor for mortality in different diseases. We studied the effect of AG on both short and long-term mortalities in critically ill patients with hip fracture.

Methods

A large clinical database was utilized to perform retrospective cohort analysis. AG was subdivided into three groups. The Cox proportional hazards regression model was employed to approximate the hazard ratio (HR) with a confidence interval (CI) of 95% for the link between AG and mortality. 30-day mortality is the primary outcome, while 90-day and 1-year mortalities represented our secondary outcomes for this study.

Results

The participants in this study were that who provided essential data on AG and the number of patients with hip fractures was 395, and they were all aged ≥16 years. The participants comprised 199 (50.4%) females as well as 196 (49.6%) males with an average age of 71.9 ± 19.4 years, and a mean AG of 12.4 ± 3.3 gmEq/L. According to an unadjusted model for 30-day all-cause mortality, the HR (95% CI) of AG ≥ 12.5 gmEq/L was 1.82 (1.11, 2.99), correspondingly, compared to the reference group (AG < 12.5 gmEq/L). This correlation was still remarkable after adjustment for r age, sex, race, SBP, DBP, WBC, heart failure, and serum chloride (HR = 1.70, 95% CI: 1.02–2.02; 2.82). For 90-day all-cause mortality, a similar correlation was observed.

Conclusions

We noted that AG was an independent indicator of both short and long-term mortalities among hip fractures individuals in this retrospective single-center cohort study. AG is a simple, readily available, and inexpensive laboratory variable that can serve as a possible risk stratification tool for hip fracture.

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.

The Association between Serum Anion Gap and All-Cause Mortality in Cerebral Infarction Patients after Treatment with rtPA: A Retrospective Analysis

Background

No epidemiological study has determined the association between the anion gap (AG) and all-cause mortality in cerebral infarction patients after treatment with rtPA. This study is aimed at using AG levels as a prognostic factor for evaluating cerebral infarction patients after receiving rtPA treatment and to help the resident physicians accurately evaluate the therapeutic plan of rtPA.

Methods

We extracted clinical data from the public database (MIMIC-IV database V1.0) and used the Kaplan-Meier curve to estimate the survival probabilities of cerebral infarction patients after rtPA treatment for the one-year, four-year, and whole period by log-rank test in 948 intensive care unit patients. Cox proportional hazard models were used to assess the association between AG and one-year, four-year, and whole period mortality in cerebral infarction patients after treatment with rtPA.

Results

Kaplan-Meier survival curve indicated a higher AG value is significantly associated with an increased risk of one-year, four-year, and whole-period all-cause mortality in cerebral infarction patients after treatment with rtPA. Model I adjusted for ethnicity, age, gender, and skin tone. Model II adjusted for ethnicity, age, gender, skin tone, hypertension, diabetes, coronary atherosclerosis, congestive heart failure, peripheral vascular, hyperlipidemia, acute myocardial infarction (AMI), respiratory failure, and end-stage renal diseaseesrd (ESRD). On the basis of model II, model III adjusted for WBC, BUN, creatinine, platelet, MCH, MCHC, MCV, RBC, and RDW. In addition, there was better predictive ability between higher AG levels and mortality in certain subgroups, such as patients with platelet ≤ 247, RBC > 3.11.

Conclusion

Serum AG is positively related to all-cause mortality in cerebral infarction patients after treatment with rtPA.

Machine Learning for Prediction of Outcomes in Cardiogenic Shock

Objective

The management of cardiogenic shock (CS) in the elderly remains a major clinical challenge. Existing clinical prediction models have not performed well in assessing the prognosis of elderly patients with CS. This study aims to build a predictive model, which could better predict the 30-day mortality of elderly patients with CS.

Methods

We extracted data from the Medical Information Mart for Intensive Care III version 1.4 (MIMIC-III) as the training set and the data of validation sets were collected from the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University. Three models, including the cox regression model, the Least Absolute Shrinkage and Selection Operator (LASSO) regression model, and the CoxBoost model, were established using the training set. Through the comparison of area under the receiver operating characteristic (ROC) curve (AUC), C index, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and median improvement in risk score, the best model was selected. Then for external validation, compared the best model with the simplified acute physiology score II (SAPSII) and the CardShock risk score.

Results

A total of 919 patients were included in the study, of which 804 patients were in the training set and 115 patients were in the verification set. Using the training set, we built three models: the cox regression model including 6 predictors, the LASSO regression model including 4 predictors, and the CoxBoost model including 16 predictors. Among them, the CoxBoost model had good discrimination [AUC: 0.730; C index: 0.6958 (0.6657, 0.7259)]. Compared with the CoxBoost model, the NRI, IDI, and median improvement in risk score of other models were all<0. In the validation set, the CoxBoost model was also well-discriminated [AUC: 0.770; C index: 0.7713 (0.6751, 0.8675)]. Compared with the CoxBoost model, the NRI, IDI, and median improvement in risk score of SAPS II and the CardShock risk score were all < 0. And we constructed a dynamic nomogram to visually display the model.

Conclusion

In conclusion, this study showed that in predicting the 30-day mortality of elderly CS patients, the CoxBoost model was superior to the Cox regression model, LASSO regression model, SAPS II, and the CardShock risk score.