Impact of diabetes mellitus on outcomes of patients with sepsis: an updated systematic review and meta-analysis

Dipeptidyl peptidase-4 inhibitors and the risk of infection: A systematic review and meta-analysis of cardiovascular outcome trials

BACKGROUND

Since adverse events during treatment affect adherence and subsequent glycemic control, understanding the safety profile of oral anti-diabetic drugs is imperative for type 2 diabetes mellitus (T2DM) therapy.

AIM

To evaluate the risk of infection in patients with T2DM treated with dipeptidyl-peptidase 4 (DPP-4) inhibitors.

METHODS

Electronic databases were searched. The selection criteria included randomized controlled trials focused on cardiovascular outcomes. In these studies, the effects of DPP-4 inhibitors were directly compared to those of either other active anti-diabetic treatments or placebo. Six trials involving 53616 patients were deemed eligible. We calculated aggregate relative risks employing both random-effects and fixed-effects approaches, contingent upon the context.

RESULTS

The application of DPP-4 inhibitors showed no significant link to the overall infection risk [0.98 (0.95, 1.02)] or the risk of serious infections [0.96 (0.85, 1.08)], additionally, no significant associations were found with opportunistic infections [0.69 (0.46, 1.04)], site-specific infections [respiratory infection 0.99 (0.96, 1.03), urinary tract infections 1.02 (0.95, 1.10), abdominal and gastrointestinal infections 1.02 (0.83, 1.25), skin structure and soft tissue infections 0.81 (0.60, 1.09), bone infections 0.96 (0.68, 1.36), and bloodstream infections 0.97 (0.80, 1.18)].

CONCLUSION

This meta-analysis of data from cardiovascular outcome trials revealed no heightened infection risk in patients undergoing DPP-4 inhibitor therapy compared to control cohorts.

Preexisting Diabetes Mellitus and All-Cause Mortality in Adult Patients With Sepsis: A Population-Based Cohort Study

OBJECTIVES

We assessed the association of preexisting diabetes mellitus with all-cause mortality and organ support receipt in adult patients with sepsis.

DESIGN

Population-based cohort study.

SETTING

Ontario, Canada (2008-2019).

POPULATION

Adult patients (18 yr old or older) with a first sepsis-related hospitalization episode.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The main exposure of interest was preexisting diabetes (either type 1 or 2). The primary outcome was all-cause mortality by 90 days; secondary outcomes included receipt of invasive mechanical ventilation and new renal replacement therapy. We report adjusted (for baseline characteristics using standardization) risk ratios (RRs) alongside 95% CIs. A main secondary analysis evaluated the potential mediation by prior metformin use of the association between preexisting diabetes and all-cause mortality following sepsis. Overall, 503,455 adults with a first sepsis-related hospitalization episode were included; 36% had preexisting diabetes. Mean age was 73 years, and 54% of the cohort were females. Preexisting diabetes was associated with a lower adjusted risk of all-cause mortality at 90 days (RR, 0.81; 95% CI, 0.80-0.82). Preexisting diabetes was associated with an increased risk of new renal replacement therapy (RR, 1.53; 95% CI, 1.46-1.60) but not invasive mechanical ventilation (RR, 1.03; 95% CI, 1.00-1.05). Overall, 21% (95% CI, 19-28) of the association between preexisting diabetes and reduced risk of all-cause mortality was mediated by prior metformin use.

CONCLUSIONS

Preexisting diabetes is associated with a lower risk of all-cause mortality and higher risk of new renal replacement therapy among adult patients with sepsis. Future studies should evaluate the underlying mechanisms of these associations.

Poor treatment outcome and associated factors of hyperglycemic emergencies among diabetic patients in Ethiopia: A systematic review and meta-analysis

Background

Despite the fact that hyperglycemic crisis poses a significant threat to the health care systems of developing countries like Ethiopia, there is a dearth of reliable data regarding the poor treatment outcome and associated factors among hyperglycemic emergencies in Ethiopia. Therefore, this review aimed to assess poor treatment outcome and associated factors of hyperglycemic emergencies among diabetic patients in Ethiopia.

Methods

Published articles regarding poor treatment outcome and associated factors of hyperglycemic emergencies among diabetic patients in Ethiopia were extensively searched from PubMed, Google Scholar, Cochrane library, and African journal online. After extraction, data were exported to Stata software version 11 (Stata Corp LLC, TX, USA) for analysis. Statistically, the Cochrane Q-test and I2 statistics were used to determine the presence or absence of heterogeneity.

Results

3650 duplicates were eliminated from the 4291 papers (PubMed [18], Google scholar (1170), African journal online [21], and Cochrane library (3082)). The pooled estimate of poor treatment outcome among hyperglycemic emergencies in Ethiopia is found to be 16.21% (95% CI: 11.01, 21.41, P < 0.001). Creatinine level >1.2 mg/dl, stroke, sepsis and comorbidity were associated factors of poor treatment outcome.

Conclusion

Poor treatment outcome from hyperglycemic emergencies among diabetic patients was found to be high. Poor treatment outcome was predicted for those patients who had creatinine level >1.2 mg/dl, stroke, sepsis and comorbidity. As a result, we recommend healthcare providers to monitor thoroughly and have close follow-ups for patients with the identified predictors to improve poor treatment outcome from hyperglycemic crises.

Steatotic Liver Disease and Sepsis Outcomes-A Prospective Cohort Study (SepsisFAT)

Background: While it has been shown that steatotic liver disease (SLD) is associated with systemic changes in immune response, the impact of SLD on sepsis outcomes has not yet been established. The aim of this study was to investigate the association between SLD and sepsis severity and outcomes. Methods: A prospective observational study included consecutively hospitalized adult patients with community-acquired sepsis during a 16-month period. Results: Of the 378 included patients (49.5% male, median age of 69, IQR 57-78 years), 174 (46%) were diagnosed with SLD. Patients with SLD were older and more frequently fulfilled the criteria for metabolic syndrome. There were no differences in the source and etiology of sepsis between the groups. Patients with SLD exhibited a higher incidence of acute kidney injury (29.3% vs. 17.6%), the need for renal replacement therapy (16.1% vs. 8.8%), and more frequent use of invasive mechanical ventilation (29.3% vs. 18.1%). In-hospital mortality was significantly higher in the SLD group (18.39% vs. 9.8%). The multivariable analysis indicated that SLD was associated with mortality (HR 2.82, 95% CI 1.40-5.71) irrespective of the other elements within metabolic syndrome. Conclusions: SLD might be associated with higher sepsis in-hospital mortality, and more frequent development of acute kidney and respiratory insufficiency requiring more critical care support.

An early warning model to predict acute kidney injury in sepsis patients with prior hypertension

Background

In the context of sepsis patients, hypertension has a significant impact on the likelihood of developing sepsis-associated acute kidney injury (S-AKI), leading to a considerable burden. Moreover, sepsis is responsible for over 50 % of cases of acute kidney injuries (AKI) and is linked to an increased likelihood of death during hospitalization. The objective of this research is to develop a dependable and strong nomogram framework, utilizing the variables accessible within the first 24 h of admission, for the anticipation of S-AKI in sepsis patients who have hypertension.

Methods

In this study that looked back, a total of 462 patients with sepsis and high blood pressure were identified from Nanfang Hospital. These patients were then split into a training set (consisting of 347 patients) and a validation set (consisting of 115 patients). A multivariate logistic regression analysis and a univariate logistic regression analysis were performed to identify the factors that independently predict S-AKI. Based on these independent predictors, the model was constructed. To evaluate the efficacy of the designed nomogram, several analyses were conducted, including calibration curves, receiver operating characteristics curves, and decision curve analysis.

Results

The findings of this research indicated that diabetes, prothrombin time activity (PTA), thrombin time (TT), cystatin C, creatinine (Cr), and procalcitonin (PCT) were autonomous prognosticators for S-AKI in sepsis individuals with hypertension. The nomogram model, built using these predictors, demonstrated satisfactory discrimination in both the training (AUC = 0.823) and validation (AUC = 0.929) groups. The S-AKI nomogram demonstrated superior predictive ability in assessing S-AKI within the hypertension grade I (AUC = 0.901) set, surpassing the hypertension grade II (AUC = 0.816) and III (AUC = 0.810) sets. The nomogram exhibited satisfactory calibration and clinical utility based on the calibration curve and decision curve analysis.

Conclusion

In patients with sepsis and high blood pressure, the nomogram that was created offers a dependable and strong evaluation for predicting S-AKI. This evaluation provides valuable insights to enhance individualized treatment, ultimately resulting in improved clinical outcomes.

Mesenchymal stem cells-derived exosomes ameliorate high glucose and lipopolysaccharide-induced HPMECs injury through the Nrf2/HO-1 pathway

Mesenchymal stem cells-derived exosomes (MSC-Exo) are considered to have great potential in the treatment of human diseases. However, the role of MSC-Exo in the process of diabetes with sepsis and the underlying molecular mechanism remain unclear. Human pulmonary microvascular endothelial cells (HPMECs) were treated with high glucose (HG) and lipopolysaccharide (LPS). Cell viability, migration, angiogenesis were analyzed by cell counting kit 8 assay, transwell assay and tube formation assay. Transmembrane electrical resistance (TER) detection and FITC-dextran assay were performed to evaluate cell barrier function. The protein levels of cell permeability-related markers, ferroptosis-related markers, exosomes-related markers, Nrf2 and HO-1 were examined using western bolt (WB) analysis. Besides, the levels of inflammation factors were tested by ELISA, and the levels of ferroptosis-related indicators were examined using corresponding assay kits. Flow cytometry was employed to analyze stem cell markers. The identification of MSC-Exo was performed using transmission electron microscopy, nanoparticle tracking analysis and WB analysis. DIO staining was used to examine the uptake of MSC-Exo by HPMECs. HG treatment suppressed HPMECs viability, migration, angiogenesis and TER, while promoted permeability, inflammation and ferroptosis. LPS treatment aggravated HG-induced HPMECs dysfunction, inflammation and ferroptosis. After HPMECs were co-cultured with MSC-Exo, cell injury induced by HG + LPS could be relieved. Moreover, MSC-Exo treatment enhanced the activity of Nrf2/HO-1 pathway in HG + LPS-induced HPMECs, and Nrf2-silenced MSC-Exo could promote HG + LPS-induced HPMECs injury. MSC-Exo alleviated HG + LPS-induced HPMECs injury via activating Nrf2/HO-1 pathway, confirming that it might be used for the treatment of diabetes with sepsis.

Prevalent diabetes and long-term cardiovascular outcomes in adult sepsis survivors: a population-based cohort study

BACKGROUND

Sepsis survivors are at elevated risk for cardiovascular disease during long-term follow-up. Whether diabetes influences cardiovascular risk after sepsis survival remains unknown. We sought to describe the association of diabetes with long-term cardiovascular outcomes in adult sepsis survivors.

METHODS

Population-based cohort study in the province of Ontario, Canada (2008-2017). Adult survivors of a first sepsis-associated hospitalization, without pre-existing cardiovascular disease, were included. Main exposure was pre-existing diabetes (any type). The primary outcome was the composite of myocardial infarction, stroke, and cardiovascular death. Patients were followed up to 5 years from discharge date until outcome occurrence or end of study period (March 2018). We used propensity score matching (i.e., 1:1 to patients with sepsis but no pre-existing diabetes) to adjust for measured confounding at baseline. Cause-specific Cox proportional hazards models with robust standard errors were used to estimate hazard ratios (HR) alongside 95% confidence intervals (CI). A main secondary analysis evaluated the modification of the association between sepsis and cardiovascular disease by pre-existing diabetes.

RESULTS

78,638 patients with pre-existing diabetes who had a sepsis-associated hospitalization were matched to patients hospitalized for sepsis but without diabetes. Mean age of patients was 71 years, and 55% were female. Median duration from diabetes diagnosis was 9.8 years; mean HbA1c was 7.1%. Adult sepsis survivors with pre-existing diabetes experienced a higher hazard of major cardiovascular disease (HR 1.25; 95% CI 1.22-1.29)-including myocardial infarction (HR 1.40; 95% CI 1.34-1.47) and stroke (HR 1.24; 95% CI 1.18-1.29)-during long-term follow-up compared to sepsis survivors without diabetes. Pre-existing diabetes modified the association between sepsis and cardiovascular disease (risk difference: 2.3%; 95% CI 2.0-2.6 and risk difference: 1.8%; 95% CI 1.6-2.0 for the effect of sepsis-compared to no sepsis-among patients with and without diabetes, respectively).

CONCLUSIONS

Sepsis survivors with pre-existing diabetes experience a higher long-term hazard of major cardiovascular events when compared to sepsis survivors without diabetes. Compared to patients without sepsis, the absolute risk increase of cardiovascular events after sepsis is higher in patients with diabetes (i.e., diabetes intensified the higher cardiovascular risk induced by sepsis).

Causal relationship between type 1 diabetes mellitus and six high-frequency infectious diseases: A two-sample mendelian randomization study

Purpose

Type 1 diabetes mellitus (T1DM) is associated with different types of infections; however, studies on the causal relationship between T1DM and infectious diseases are lacking. Therefore, our study aimed to explore the causalities between T1DM and six high-frequency infections using a Mendelian randomization (MR) approach.

Methods

Two-sample MR studies were conducted to explore the causalities between T1DM and six high-frequency infections: sepsis, acute lower respiratory infections (ALRIs), intestinal infections (IIs), infections of the genitourinary tract (GUTIs) in pregnancy, infections of the skin and subcutaneous tissues (SSTIs), and urinary tract infections (UTIs). Data on summary statistics for T1DM and infections were obtained from the European Bioinformatics Institute database, the United Kingdom Biobank, FinnGen biobank, and Medical Research Council Integrative Epidemiology Unit. All data obtained for summary statistics were from European countries. The inverse-variance weighted (IVW) method was employed as the main analysis. Considering the multiple comparisons, statistical significance was set at p< 0.008. If univariate MR analyses found a significant causal association, multivariable MR (MVMR) analyses were performed to adjust body mass index (BMI) and glycated hemoglobin (HbA1c). MVMR-IVW was performed as the primary analysis, and the least absolute shrinkage and selection operator (LASSO) regression and MVMR-Robust were performed as complementary analyses.

Results

MR analysis showed that susceptibility to IIs increased in patients with T1DM by 6.09% using the IVW-fixed method [odds ratio (OR)=1.0609; 95% confidence interval (CI): 1.0281-1.0947, p=0.0002]. Results were still significant after multiple testing. Sensitivity analyses did not show any significant horizontal pleiotropy or heterogeneity. After adjusting for BMI and HbA1c, MVMR-IVW (OR=1.0942; 95% CI: 1.0666-1.1224, p<0.0001) showed significant outcomes that were consistent with those of LASSO regression and MVMR-Robust. However, no significant causal relationship was found between T1DM and sepsis susceptibility, ALRI susceptibility, GUTI susceptibility in pregnancy, SSTI susceptibility, and UTI susceptibility.

Conclusions

Our MR analysis genetically predicted increased susceptibility to IIs in T1DM. However, no causality between T1DM and sepsis, ALRIs, GUTIs in pregnancy, SSTIs, or UTIs was found. Larger epidemiological and metagenomic studies are required to further investigate the observed associations between the susceptibility of certain infectious diseases with T1DM.

Insight on Infections in Diabetic Setting

The correlation between diabetes mellitus and infectious diseases is widely recognized. DM patients are characterized by the impaired function of the immune system. This translates into the occurrence of a variety of infections, including urinary tract, skin and surgical site infections, pneumonia, tuberculosis, and, more recently, SARS-CoV-2. Hyperglycemia has been identified as a relevant factor contributing to unfavorable outcomes in hospitalized patients including SARS-CoV-2 patients. Several studies have been performed proving that to maintain the proper and stringent monitoring of glycemia, a balanced diet and physical activity is mandatory to reduce the risk of infections and their associated complications. This review is focused on the mechanisms accounting for the increased susceptibility of DM patients to infections, with particular attention to the impact of newly introduced hypoglycemic drugs in sepsis management.

Predictors of outcomes in emergency department patients with suspected infections and without fulfillment of the sepsis criteria

BACKGROUND

Data on patient characteristics and determinants of serious outcomes for acutely admitted patients with infections who do not fulfill the sepsis criteria are sparse. The study aimed to characterize acutely admitted emergency department (ED) patients with infections and a composite outcome of in-hospital mortality or transfer to the intensive care unit without fulfilling the criteria for sepsis and to examine predictors of the composite outcome.

METHODS

This was a secondary analysis of data from a prospective observational study of patients with suspected bacterial infection admitted to the ED between October 1, 2017 and March 31, 2018. A National Early Warning Score 2 (NEWS2) ≥ 5 within the first 4 h in the ED was assumed to represent a sepsis-like condition with a high risk for the composite endpoint. Patients who achieved the composite outcome were grouped according to fulfillment of the NEWS2 ≥ 5 criteria. We used logistic regression analysis to estimate the unadjusted and adjusted odds ratio (OR) for the composite endpoint among patients with either NEWS2  < 5 (NEWS2-) or NEWS2  ≥ 5 (NEWS2+).

RESULTS

A total of 2055 patients with a median age of 73 years were included. Of these, 198 (9.6%) achieved the composite endpoint, including 59 (29.8%) NEWS2- and 139 (70.2%) NEWS2+ patients, respectively. Diabetes (OR 2.23;1.23-4.0), a Sequential Organ Failure Assessment (SOFA) score ≥ 2 (OR 2.57;1.37-4.79), and a Do-not-attempt-cardiopulmonary-resuscitation order (DNACPR) on admission (OR 3.70;1.75-7.79) were independent predictive variables for the composite endpoint in NEWS2- patients (goodness-of-fit test P = 0.291; area under the receiver operating characteristic curve for the model (AUROC) = 0.72). The regression model for NEWS2+ patients revealed that a SOFA score ≥ 2 (OR 2.79; 1.59-4.91), hypothermia (OR 2.48;1.30-4.75), and DNACPR order on admission were predictive variables for the composite endpoint (goodness-of-fit test P = 0.62; AUROC for the model = 0.70).

CONCLUSION

Approximately one-third of the patients with infections and serious outcomes during hospitalization did not meet the NEWS2 threshold for likely sepsis. Our study identified factors with independent predictive values for the development of serious outcomes that should be tested in future prediction models.

Association between type II diabetes mellitus and 90-day mortality in a large multicenter prospectively collected cohort. A FROG ICU post-hoc study

PURPOSE

Factors associated with adverse outcomes in ICU patients with type II (T2DM) are poorly defined. The main goal of this study is to determine the impact of pre-existing T2DM on 90-day mortality post ICU admission.

MATERIAL

Post-hoc analysis from the FROG-ICU cohort. All patients admitted to ICU who were ventilated and/or treated by a vasoactive agent for >24 h were included. Association between T2DM and 90-day mortality was analyzed in unmatched, and populations matched by propensity score (PS) method to balance confounders recorded before ICU admission. Analysis was performed in non-imputed and imputed datasets.

RESULTS

2002 patients were included, and 16% had a history of T2DM. The latter were at inclusion more severely ill (SAPSII score 51(39-67) vs 48(35-61), p < 0.0001; Charlson score 2(1-3) vs 0(0-2), p < 0.0001). In the unmatched cohort, T2DM patients had a higher 90-day risk of death compared to no-DM patients (HR 1.35(1.1-1.65)). The 90-day risk of death was not significantly different T2DM and no T2DM patients after PS matching (HR: 0.81 (0.56-1.18). Results were similar with the analysis performed on imputed datasets (pooled HR: 0.95 (0.69-1.30)).

CONCLUSIONS

In the present study, T2DM was not associated with 90-day mortality post ICU admission.

Is compromised intestinal barrier integrity responsible for the poor prognosis in critically ill patients with pre-existing hyperglycemia?

BACKGROUND

Compromised intestinal barrier integrity can be independently driven by hyperglycemia, and both hyperglycemia and intestinal barrier injury are associated with poor prognosis in critical illness. This study investigated the intestinal barrier biomarkers in critically ill patients, to explore the role of compromised intestinal barrier integrity on the prognosis of critically ill patients with pre-existing hyperglycemia.

METHODS

This was a retrospective observational study. The relationships between intestinal barrier biomarkers and glycated hemoglobin A1c (HbA1c), fasting blood glucose (FBG), indicators of clinical characteristics, disease severity, and prognosis in critically ill patients were investigated. Then the metrics mentioned above were compared between survivors and non-survivors, the risk factors of 90-day mortality were investigated by logistic regression analysis. Further, patients were divided into HbA1c < 6.5% Group and HbA1c ≥ 6.5% Group, metrics mentioned above were compared between these two groups.

RESULTS

A total of 109 patients with critical illness were included in the study. D-lactate and lipopolysaccharide (LPS) were associated with sequential organ failure assessment (SOFA) score and 90-day mortality. LPS was an independent risk factor of 90-day mortality. DAO, NEU (neutrophil) proportion, temperature, lactate were lower in HbA1c ≥ 6.5% Group while D-lactate, LPS, indicators of disease severity and prognosis showed no statistical difference between HbA1c < 6.5% Group and HbA1c ≥ 6.5% Group.

CONCLUSIONS

Intestinal barrier integrity is associated with the disease severity and prognosis in critical illness. Compromised intestinal barrier integrity might be responsible for the poor prognosis in critically ill patients with pre-existing hyperglycemia.

Association between glucose-to-lymphocyte ratio and in-hospital mortality in intensive care patients with sepsis: A retrospective observational study based on Medical Information Mart for Intensive Care IV

Background

This study aimed to evaluate the association between the glucose-to-lymphocyte ratio (GLR) and in-hospital mortality in intensive care unit (ICUs) patients with sepsis.

Methods

This is a retrospective cohort study. Patients with sepsis from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database had their baseline data and in-hospital prognosis retrieved. Multivariable Cox regression analyses were applied to calculate adjusted hazard ratios (HR) with 95% confidence intervals (CI). Survival curves were plotted, and subgroup analyses were stratified by relevant covariates. To address the non-linearity relationship, curve fitting and a threshold effect analysis were performed.

Results

Of the 23,901 patients, 10,118 patients with sepsis were included. The overall in-hospital mortality rate was 17.1% (1,726/10,118). Adjusted for confounding factors in the multivariable Cox regression analysis models, when GLR was used as a categorical variable, patients in the highest GLR quartile had increased in-hospital mortality compared to patients in the lowest GLR quartile (HR = 1.26, 95% CI: 1.15–1.38). When GLR was used as a continuous variable, each unit increase in GLR was associated with a 2% increase in the prevalence of in-hospital mortality (adjusted HR = 1.02, 95% CI: 1.01–1.03, p = 0.001). Stratified analyses indicated that the correlation between the GLR and in-hospital mortality was stable. The non-linear relationship between GLR and in-hospital mortality was explored in a dose-dependent manner. In-hospital mortality increased by 67% (aHR = 1.67, 95% CI: 1.45–1.92) for every unit GLR increase. When GLR was beyond 1.68, in-hospital mortality did not significantly change (aHR: 1.04, 95% CI: 0.92–1.18).

Conclusion

There is a non-linear relationship between GLR and in-hospital mortality in intensive care patients with sepsis. A higher GLR in ICU patients is associated with in-hospital mortality in the United States. However, further research is needed to confirm the findings.

Predictive nomogram model for major adverse kidney events within 30 days in sepsis patients with type 2 diabetes mellitus

BACKGROUND

In sepsis patients, Type 2 Diabetes Mellitus (T2DM) was associated with an increased risk of kidney injury. Furthermore, kidney damage is among the dangerous complications, with a high mortality rate in sepsis patients. However, the underlying predictive model on the prediction of major adverse kidney events within 30 days (MAKE30) in sepsis patients with T2DM has not been reported by any study.

METHODS

A total of 406 sepsis patients with T2DM were retrospectively enrolled and divided into a non-MAKE30 group (261 cases) and a MAKE30 group (145 cases). In sepsis patients with T2DM, univariate and multivariate logistic regression analyses were conducted to identify independent predictors of MAKE30. Based on the findings of multivariate logistic regression analysis, the corresponding nomogram was constructed. The nomogram was evaluated using the calibration curve, Receiver Operating Characteristic (ROC) curve, and decision curve analysis. A composite of death, new Renal Replacement Therapy (RRT), or Persistent Renal Dysfunction (PRD) comprised MAKE30. Finally, subgroup analyses of the nomogram for 30-day mortality, new RRT, and PRD were performed.

RESULTS

In sepsis patients with T2DM, Mean Arterial Pressure (MAP), Platelet (PLT), cystatin C, High-Density Lipoprotein (HDL), and apolipoprotein E (apoE) were independent predictors for MAKE30. According to the ROC curve, calibration curve, and decision curve analysis, the nomogram model based on those predictors had satisfactory discrimination (AUC = 0.916), good calibration, and clinical application. Additionally, in sepsis patients with T2DM, the nomogram model exhibited a high ability to predict the occurrence of 30-day mortality (AUC = 0.822), new RRT (AUC = 0.874), and PRD (AUC = 0.801).

CONCLUSION

The nomogram model, which is available within 24 hours after admission, had a robust and accurate assessment for the MAKE30 occurrence, and it provided information to better manage sepsis patients with T2DM.