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

Combined effect of anion gap and red cell distribution width on the risk of acute kidney injury after cardiac surgery

BACKGROUND

This study was to analyze the roles of red blood cell distribution width (RDW), anion gap (AG) levels and their combined effects on the risk of acute kidney injury (AKI) following cardiac surgery.

METHODS

This cohort study extracted the data of 1951 participants aged ≥ 18 years with the assessment of AKI after cardiac surgery during ICU stay from MIMIC-IV database between 2008 and 2019. Receiver operator characteristic (ROC) curve was used to determine the optimal cut-off value AG and RDW. The associations between AG, RDW, and the combined effects of AG and effects were evaluated via univariable and multivariable Logistic models. Odds ratio (OR) with 95% confidence interval (CI) were imputed.

RESULTS

Among all the participants, 831 participants had AKI, and 1120 did not have AKI. ROC curves revealed that the optimum cut of points of AG and RDW were 12.75 mmol/L, and 13.65%, respectively. Increased risk of AKI was found in patients after cardiac surgery with AG > 12.75 mmol/L (OR = 1.44, 95%CI 1.15-1.80) or RDW > 13.65% group (OR = 1.23, 95%CI 1.01-1.50). In comparison to subjects with AG ≤ 12.75 mmol/L and RDW ≤ 13.65%, AG > 12.75 mmol/L and RDW ≤ 13.65% (OR = 1.42, 95%CI 1.07-1.89), and AG > 12.75 mmol/L and RDW > 13.65% (OR = 1.75, 95%CI 1.24-2.47) were associated with increased odds of AKI in patients after cardiac surgery.

CONCLUSIONS

AG and RDW had combined effects on risk of AKI in patients after cardiac surgery, which might offer an insight for the management of patients after cardiac surgery.

The association between anion gap and length of stay in patients undergoing hip fracture surgery: data from the MIMIC-IV database

OBJECTIVE

To explore the relationship between anion gap (AG) and length of stay (LOS) in patients undergoing hip fracture surgery.

METHODS

Clinical data of patients diagnosed with hip fracture and undergoing surgery were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Logistic regression analysis by adjusting different covariables and threshold effect analysis were used to analyze the relationship between AG and LOS. Subgroup analysis and interaction test were also performed to detect their relationship. Receiver Operating Characteristic (ROC) analysis was performed to identify the prediction performance and cutoff value of AG.Kaplan-Meier (KM) survival analysis was used to explore the influence of AG on overall survival.

RESULTS

A total of 1508 patients were enrolled and the median LOS was 4.9 days. The correlation between AG and LOS > 7 days was observed among 3 regression models when regarding AG as continuous variables (all OR > 1, all P < 0.05). After stratifying samples with AG quartiles, their relationship was only presented in the Q4 group both in model 1 and model 2 (all P < 0.001). The risk of LOS > 7 days gradually increased with increasing AG quartiles (all P for trend < 0.05). Further, threshold effect analysis found that their association was mainly observed when AG ≥ 14 mEq/L (OR = 1.122, P < 0.001). Subgroup analysis showed that their correlation was not influenced by sex, age, BMI, ethnicity, classification of fracture, therapeutic method, CHD, hypertension, osteoporosis, diabetes and admitted to the ICU (all P for interaction > 0.05). ROC analysis identified 14.5 as the cutoff value of AG for predicted LOS > 7 days. Survival analysis found that patients in the AG < 14.5 group had better overall survival.

CONCLUSION

In patients undergoing hip fracture surgery, the AG was positively correlated with LOS, and 14.5 mEq/L AG was the cutoff value for predicting LOS > 7 days. The cutoff value can favorably distinguish the survival difference of patients.

The preventative effects of Lactococcus Lactis metabolites against LPS-induced sepsis

Introduction

Sepsis is a syndrome of organ dysfunction caused by a dysregulated host response to infection and septic shock. Currently, antibiotic therapy is the standard treatment for sepsis, but it can lead to drug resistance. The disturbance of the gut microbiota which is affected by sepsis could lead to the development of organ failure. It is reported that probiotics could shape the gut microbiota, potentially controlling a variety of intestinal diseases and promoting whole-body health.

Methods

In this study, we evaluated the preventive effects of intra- and extracellular products of probiotics on sepsis. The extracellular products of Lactococcus lactis (L. lactis) were identified through the in vivo cell experiments. The preventive effect and mechanism of L. lactis extracellular products on mouse sepsis were further explored through HE staining, mouse survival rate measurement, chip analysis, etc.

Results

L. lactis extracellular products increase cell survival and significantly reduce inflammatory factors secreted in a cellular sepsis model. In in vivo experiments in mice, our samples attenuated sepsis-induced pulmonary edema and inflammatory infiltrates in the lungs of mice, and reduced mortality and inflammatory factor levels within the serum of mice. Finally, the mechanism of sepsis prevention by lactic acid bacteria is suggested. Extracellular products of L. lactis could effectively prevent sepsis episodes.

Discussion

In animal experiments, we reported that extracellular products of L. lactis can effectively prevent sepsis, and preliminarily discussed the pathological mechanism, which provides more ideas for the prevention of sepsis. In the future, probiotics may be considered a new way to prevent sepsis.

Association between albumin-corrected anion gap level and the risk of acute kidney injury in intensive care unit

PURPOSE

This study was to investigate the association between albumin-corrected anion gap (AG) (ACAG) levels and the risk of acute kidney injury (AKI) in intensive care unit (ICU) patients.

METHODS

The ICU patients of this retrospective cohort study were collected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database between 2008 and 2019. ACAG = AG + {4.4 - [albumin (g/dl)]} × 2.5. The incidence of AKI was determined using the Kidney Disease: Improving Global Outcomes (KDIGO) definition. The logistic regression model was used to evaluate the association between ACAG levels and the risk of AKI. Subgroup analyses were applied based on age, gender, mechanical ventilation, vasopressors, the Charlson comorbidity index (CCI), and the Simplified Acute Physiology Score II (SAPS II).

RESULTS

Totally, 5586 patients were enrolled, of which 1929 patients (34.53%) occurred AKI. The higher levels of ACAG were associated with the risk of AKI in ICU patients, with the odds ratio (OR) value being 1.23 [95% confidence interval (CI): 1.22-1.24, P = 0.005] in ACAG level between 16.5 and 19.5, and OR value being 1.20 (95% CI 1.16-1.24, P = 0.016) in ACAG level > 19.5. A higher ACAG level was associated with a higher risk of AKI in ICU patients aged < 65 years, in ICU patients of female gender, in ICU patients who used mechanical ventilation, in ICU patients who did not use vasopressors, in patients without cardiogenic shock, and in ICU patients with CCI ≥ 2, and SAPS II > 31 (all P < 0.05).

CONCLUSION

There is an association between ACAG level and the risk of AKI in ICU patients. A higher ACAG value in ICU patients should therefore receive more attention.

Association Between Albumin-Corrected Anion Gap and In-Hospital Mortality and Sepsis-Associated Acute Kidney Injury

BACKGROUND This study aimed to investigate the association between albumin-corrected anion gap (ACAG) and in-hospital mortality in sepsis-associated acute kidney injury (S-AKI). MATERIAL AND METHODS We conducted this retrospective study based on data from the Medical Information Mart for Intensive Care IV database, and assessed the prognostic capabilities of ACAG in comparison with albumin (ALB) and anion gap (AG) to predict in-hospital mortality of patients with S-AKI. Binomial logistic regression analysis was performed to identify whether ACAG was an independent risk factor for in-hospital mortality for the patients, and receiver operating characteristic (ROC) curves were plotted to clarify its efficacy in predicting in-hospital mortality. We also performed a decision curve analysis (DCA) to determine whether there were net clinical benefits for patients when ACAG was used to predict in-hospital mortality. RESULTS Binary logistic regression analysis showed that ACAG was an independent risk factor for in-hospital mortality in patients with S-AKI, with an area under the ROC (AUC) curve of 0.675 (moderate predictive value) for the prediction of in-hospital mortality, higher than that of ALB or AG alone, with the highest Youden's index (0.2675). The DCA substantiated the superiority of ACAG in net clinical benefits at various threshold probability, enhancing its clinical applicability. CONCLUSIONS The research emphasizes the potential of ACAG as a valuable predictive tool for in-hospital mortality in S-AKI patients, which is better than albumin and AG, encouraging its consideration in clinical practice.

Effect of sodium bicarbonate infusion on hospital mortality in acute kidney injury patients with metabolic acidosis

Background

Physicians usually consider that sodium bicarbonate (SB) infusion can be used for metabolic acidosis; however, there is little evidence available to assess its effect on hospital mortality in large AKI cohorts. Here, we investigated the effect of SB infusion in patients with AKI complicated by metabolic acidosis.

Method

Patients with AKI complicated by metabolic acidosis were screened from the MIMIC-IV database. A propensity score analysis (PSA) was used to decrease baseline differences in the probability of receiving SB. The marginal structural Cox model (MSCM) was employed to adjust for both baseline and time-varying confounding factors.

Results

A total of 1853 patients with AKI complicated with metabolic acidosis were included in our study. A total of 390 pairs of patients were divided into an SB infusion group and a non-SB infusion group. The SB infusion group had more serious and worse laboratory indicators, including lower pH [7.19 (0.11) vs. 7.26 (0.07)] and bicarbonate concentration (BC) [12.36 (4.26) vs. 15.96 (3.25) mmol/l]. While there was no significant effect on overall hospital mortality in AKI patients complicated with metabolic acidosis (p = 0.056), SB infusion was observed to have beneficial correlation on hospital mortality in patients with high AG acidosis (AG > 18 mmol/L) (p = 0.012). Similar results were replicated with the MSCM.

Conclusion

We found that SB infusion in AKI patients with metabolic acidosis is not beneficial for hospital mortality. However, SB infusion for AKI patients and high AG metabolic acidosis significantly improved hospital mortality. Further larger randomized controlled trials are needed to confirm these results.

The predictive values of admission characteristics for 28-day all-cause mortality in septic patients with diabetes mellitus: a study from the MIMIC database

Background

Septic patients with diabetes mellitus (DM) are more venerable to subsequent complications and the resultant increase in associated mortality. Therefore, it is important to make tailored clinical decisions for this subpopulation at admission.

Method

Data from large-scale real-world databases named the Medical Information Mart for Intensive Care Database (MIMIC) were reviewed. The least absolute selection and shrinkage operator (LASSO) was performed with 10 times cross-validation methods to select the optimal prognostic factors. Multivariate COX regression analysis was conducted to identify the independent prognostic factors and nomogram construction. The nomogram was internally validated via the bootstrapping method and externally validated by the MIMIC III database with receiver operating characteristic (ROC), calibration curves, decision curve analysis (DCA), and Kaplan-Meier curves for robustness check.

Results

A total of 3,291 septic patients with DM were included in this study, 2,227 in the MIMIC IV database and 1,064 in the MIMIC III database, respectively. In the training cohort, the 28-day all-cause mortality rate is 23.9% septic patients with DM. The multivariate Cox regression analysis reveals age (hazard ratio (HR)=1.023, 95%CI: 1.016-1.031, p<0.001), respiratory failure (HR=1.872, 95%CI: 1.554-2.254, p<0.001), Sequential Organ Failure Assessment score (HR=1.056, 95%CI: 1.018-1.094, p=0.004); base excess (HR=0.980, 95%CI: 0.967-0.992, p=0.002), anion gap (HR=1.100, 95%CI: 1.080-1.120, p<0.001), albumin (HR=0.679, 95%CI: 0.574-0.802, p<0.001), international normalized ratio (HR=1.087, 95%CI: 1.027-1.150, p=0.004), red cell distribution width (HR=1.056, 95%CI: 1.021-1.092, p=0.001), temperature (HR=0.857, 95%CI: 0.789-0.932, p<0.001), and glycosylated hemoglobin (HR=1.358, 95%CI: 1.320-1.401, p<0.001) at admission are independent prognostic factors for 28-day all-cause mortality of septic patients with DM. The established nomogram shows satisfied accuracy and clinical utility with AUCs of 0.870 in the internal validation and 0.830 in the external validation cohort as well as 0.820 in the septic shock subpopulation, which is superior to the predictive value of the single SOFA score.

Conclusion

Our results suggest that admission characteristics show an optimal prediction value for short-term mortality in septic patients with DM. The established model can support intensive care unit physicians in making better initial clinical decisions for this subpopulation.