Prognostic impact of elevated lactate levels on mortality in critically ill patients with and without preadmission metformin treatment: a Danish registry-based cohort study

Metformin exposure and the incidence of lactic acidosis in critically ill patients with T2DM: A retrospective cohort study

OBJECTIVE

The objective of this study was to investigate the correlation between metformin exposure and the incidence of lactic acidosis in critically ill patients.

METHODS

The patients with type 2 diabetes mellitus (T2DM) were included from Medical Information Mart for Intensive Care IV database (MIMIC-IV). The primary outcome was the incidence of lactic acidosis. The secondary outcomes were lactate level and in-hospital mortality. Propensity score matching (PSM) method was adopted to reduce bias of the confounders. The multivariate logistic regression was used to explore the correlation between metformin exposure and the incidence of lactic acidosis. Subgroup analysis and sensitivity analysis were used to test the stability of the conclusion.

RESULTS

We included 4939 patients. There were 2070 patients in the metformin group, and 2869 patients in the nonmetformin group. The frequency of lactic acidosis was 5.7% (118/2070) in the metformin group and it was 4.3% (122/2869) in the nonmetformin group. There was a statistically significant difference between the two groups (P < 0.05). The lactate level in the metformin group was higher than in the nonmetformin group (2.78 ± 2.23 vs. 2.45 ± 2.24, P < 0.001). After PSM, the frequency of lactic acidosis (6.3% vs. 3.7%, P < 0.001) and lactate level (2.85 ± 2.38 vs. 2.40 ± 2.14, P < 0.001) were significantly higher in the metformin group compared with the nonmetformin group. In multivariate logistic models, the frequency of lactic acidosis was obviously increased in metformin group, and the adjusted odds ratio (OR) of metformin exposure was 1.852 (95% confidence interval (CI) = 1.298-2.643, P < 0.001). The results were consistent with subgroup analysis except for respiratory failure subgroup. Metformin exposure increased lactate level but did not affect the frequency of lactic acidosis in patients of respiratory failure with hypercapnia. However, the in-hospital mortality between metformin and nonmetformin group had no obvious difference (P = 0.215). In sensitivity analysis, metformin exposure showed similar effect as the original cohort.

CONCLUSIONS

In critically ill patients with T2DM, metformin exposure elevated the incidence of lactic acidosis except for patients of respiratory failure with hypercapnia, but did not affect the in-hospital mortality.

Metformin for sepsis-associated AKI: a protocol for the Randomized Clinical Trial of the Safety and FeasibiLity of Metformin as a Treatment for sepsis-associated AKI (LiMiT AKI)

INTRODUCTION

Acute kidney injury (AKI) is a common complication of sepsis associated with increased risk of death. Preclinical data and observational human studies suggest that activation of AMP-activated protein kinase, an ubiquitous master regulator of energy that can limit mitochondrial injury, with metformin may protect against sepsis-associated AKI (SA-AKI) and mortality. The Randomized Clinical Trial of the Safety and FeasibiLity of Metformin as a Treatment for sepsis-associated AKI (LiMiT AKI) aims to evaluate the safety and feasibility of enteral metformin in patients with sepsis at risk of developing SA-AKI.

METHODS AND ANALYSIS

Blind, randomised, placebo-controlled clinical trial in a single-centre, quaternary teaching hospital in the USA. We will enrol adult patients (18 years of age or older) within 48 hours of meeting Sepsis-3 criteria, admitted to intensive care unit, with oral or enteral access. Patients will be randomised 1:1:1 to low-dose metformin (500 mg two times per day), high-dose metformin (1000 mg two times per day) or placebo for 5 days. Primary safety outcome will be the proportion of metformin-associated serious adverse events. Feasibility assessment will be based on acceptability by patients and clinicians, and by enrolment rate.

ETHICS AND DISSEMINATION

This study has been approved by the Institutional Review Board. All patients or surrogates will provide written consent prior to enrolment and any study intervention. Metformin is a widely available, inexpensive medication with a long track record for safety, which if effective would be accessible and easy to deploy. We describe the study methods using the Standard Protocol Items for Randomized Trials framework and discuss key design features and methodological decisions. LiMiT AKI will investigate the feasibility and safety of metformin in critically ill patients with sepsis at risk of SA-AKI, in preparation for a future large-scale efficacy study. Main results will be published as soon as available after final analysis.

TRIAL REGISTRATION NUMBER

NCT05900284.

Early prediction of mortality at sepsis diagnosis time in critically ill patients by using interpretable machine learning

This study applied machine learning for the early prediction of 30-day mortality at sepsis diagnosis time in critically ill patients. Retrospective study using data collected from the Medical Information Mart for Intensive Care IV database. The data of the patient cohort was divided on the basis of the year of hospitalization, into training (2008-2013), validation (2014-2016), and testing (2017-2019) datasets. 24,377 patients with the sepsis diagnosis time < 24 h after intensive care unit (ICU) admission were included. A gradient boosting tree-based algorithm (XGBoost) was used for training the machine learning model to predict 30-day mortality at sepsis diagnosis time in critically ill patients. Model performance was measured in both discrimination and calibration aspects. The model was interpreted using the SHapley Additive exPlanations (SHAP) module. The 30-day mortality rate of the testing dataset was 17.9%, and 39 features were selected for the machine learning model. Model performance on the testing dataset achieved an area under the receiver operating characteristic curve (AUROC) of 0.853 (95% CI 0.837-0.868) and an area under the precision-recall curves of 0.581 (95% CI 0.541-0.619). The calibration plot for the model revealed a slope of 1.03 (95% CI 0.94-1.12) and intercept of 0.14 (95% CI 0.04-0.25). The SHAP revealed the top three most significant features, namely age, increased red blood cell distribution width, and respiratory rate. Our study demonstrated the feasibility of using the interpretable machine learning model to predict mortality at sepsis diagnosis time.

Identifying molecular phenotypes in sepsis: an analysis of two prospective observational cohorts and secondary analysis of two randomised controlled trials

BACKGROUND

In sepsis and acute respiratory distress syndrome (ARDS), heterogeneity has contributed to difficulty identifying effective pharmacotherapies. In ARDS, two molecular phenotypes (hypoinflammatory and hyperinflammatory) have consistently been identified, with divergent outcomes and treatment responses. In this study, we sought to derive molecular phenotypes in critically ill adults with sepsis, determine their overlap with previous ARDS phenotypes, and evaluate whether they respond differently to treatment in completed sepsis trials.

METHODS

We used clinical data and plasma biomarkers from two prospective sepsis cohorts, the Validating Acute Lung Injury biomarkers for Diagnosis (VALID) study (N=1140) and the Early Assessment of Renal and Lung Injury (EARLI) study (N=818), in latent class analysis (LCA) to identify the optimal number of classes in each cohort independently. We used validated models trained to classify ARDS phenotypes to evaluate concordance of sepsis and ARDS phenotypes. We applied these models retrospectively to the previously published Prospective Recombinant Human Activated Protein C Worldwide Evaluation in Severe Sepsis and Septic Shock (PROWESS-SHOCK) trial and Vasopressin and Septic Shock Trial (VASST) to assign phenotypes and evaluate heterogeneity of treatment effect.

FINDINGS

A two-class model best fit both VALID and EARLI (p<0·0001). In VALID, 804 (70·5%) of the 1140 patients were classified as hypoinflammatory and 336 (29·5%) as hyperinflammatory; in EARLI, 530 (64·8%) of 818 were hypoinflammatory and 288 (35·2%) hyperinflammatory. We observed higher plasma pro-inflammatory cytokines, more vasopressor use, more bacteraemia, lower protein C, and higher mortality in the hyperinflammatory than in the hypoinflammatory phenotype (p<0·0001 for all). Classifier models indicated strong concordance between sepsis phenotypes and previously identified ARDS phenotypes (area under the curve 0·87-0·96, depending on the model). Findings were similar excluding participants with both sepsis and ARDS. In PROWESS-SHOCK, 1142 (68·0%) of 1680 patients had the hypoinflammatory phenotype and 538 (32·0%) had the hyperinflammatory phenotype, and response to activated protein C differed by phenotype (p=0·0043). In VASST, phenotype proportions were similar to other cohorts; however, no treatment interaction with the type of vasopressor was observed (p=0·72).

INTERPRETATION

Molecular phenotypes previously identified in ARDS are also identifiable in multiple sepsis cohorts and respond differently to activated protein C. Molecular phenotypes could represent a treatable trait in critical illness beyond the patient's syndromic diagnosis.

FUNDING

US National Institutes of Health.

New potential for an old kid on the block: Impact of premorbid metformin use on lactate kinetics, kidney injury and mortality in sepsis and septic shock, an observational study

INTRODUCTION

Sepsis and septic shock cause significant mortality worldwide, with no targeted molecular therapies available. Metformin has pleomorphic effects that may be beneficial in sepsis, but at present, the impact of metformin exposure on sepsis remains controversial. Metformin might alter lactate metabolism, but little is known about its influence on lactate kinetics. We therefore investigated the impact of preadmission metformin use on lactate kinetics, acute kidney injury (AKI) and mortality in sepsis.

MATERIALS AND METHODS

We retrospectively analysed all ICU admissions with sepsis and septic shock between January 2013 and September 2020, identifying 77 users and 390 nonusers (subdivided in diabetics, n = 48 and nondiabetics, n = 342).

RESULTS

(Sub)groups did not differ in illness severity or sepsis aetiology. Admission lactate levels were similar, but evolution in lactate over the first 24 h showed a larger decrease in users vs nonusers (median - 53% vs. -36%, p = .010). No difference in AKI or renal replacement therapy was found. Mortality was lower in users vs nonusers in case of septic shock (21.9% (n = 7) vs. 42.7% (n = 61) for 90d mortality, p = .029, OR 0.38 [95% CI: 0.15-0.93]), but showed no significant differences in the combined sepsis and septic shock population.

CONCLUSIONS

In our data, preadmission metformin use is associated with a significantly larger decrease in lactate after admission with sepsis or septic shock and with reduced mortality in septic shock. This underscores the need for further studies investigating the interplay between metformin, lactate and sepsis, thereby exploring the potential use of metformin or its pathways in sepsis.

Quality and Characteristics of 4241 Case Reports of Lactic Acidosis in Metformin Users Reported to a Large Pharmacovigilance Database

Objective

Metformin-associated lactic acidosis (MaLA) occurs rarely and is thus difficult to study. We analysed 4241 individual case safety reports of lactic acidosis (LA) that implicated metformin as a suspected drug reported to the pharmacovigilance database of Merck KGaA, Darmstadt, Germany. The primary objective was to review reports for quality and completeness of data to support diagnoses of MaLA. We also explored the correlations between reported biomarkers, and associations between biomarkers and outcomes.

Research Design and Methods

Records were analysed for completeness in supporting diagnoses of LA or metformin-associated LA (MaLA), against commonly used diagnostic criteria. Correlations between indices of exposure to metformin and biomarkers of LA and mortality were investigated.

Results

Missing data was common, especially for plasma metformin. Clinical/biomarker evidence supported a diagnosis of LA in only 33% of cases (LA subpopulation) and of MaLA in only 9% (MaLA subpopulation). The metformin plasma level correlated weakly with plasma lactate (positive) and pH (negative). About one-fifth (21.9%) of cases reported a fatal outcome. Metformin exposure (plasma level or dose) was not associated with increased mortality risk (there was a suggestion of decreased risk at higher levels of exposure to metformin). Plasma lactate was the only variable associated with increased risk of mortality. Examination of concomitant risk factors for MaLA identified renal dysfunction (including of iatrogenic origin) as a potential driver of mortality in this population.

Conclusion

Despite the high frequency of missing data, this is the largest analysis of cases of MaLA supported by measurements of circulating metformin, and lactate, and pH, to date. Plasma lactate, and not metformin dose or plasma level, appeared to be the main driver of mortality in the setting of LA or MaLA. Further research with more complete case reports is required.

Association of Metformin Use During Hospitalization and Mortality in Critically Ill Adults With Type 2 Diabetes Mellitus and Sepsis

OBJECTIVES

Whether metformin exposure is associated with improved outcomes in patients with type 2 diabetes mellitus and sepsis.

DESIGN

Retrospective cohort study.

SETTING

Patients admitted to ICUs in 16 hospitals in Pennsylvania from October 2008 to December 2014.

PATIENTS

Adult critical ill patients with type 2 diabetes mellitus and sepsis.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We conducted a retrospective cohort study to compare 90-day mortality in diabetic patients with sepsis with and without exposure to metformin during hospitalization. Data were obtained from the electronic health record of a large healthcare system in Pennsylvania from October 2008 to December 2014, on patients admitted to the ICU at any of the 16 hospitals within the system. The primary outcome was mortality at 90 days. The absolute and adjusted odds ratio (OR) with 95% CI were calculated in a propensity score-matched cohort. Among 14,847 patients with type 2 diabetes mellitus and sepsis, 682 patients (4.6%) were exposed to metformin during hospitalization and 14,165 (95.4%) were not. Within a total of 2,691 patients subjected to propensity score-matching at a 1:4 ratio, exposure to metformin (n = 599) was associated with decreased 90-day mortality (71/599, 11.9% vs 475/2,092, 22.7%; OR, 0.46; 95% CI, 0.35-0.60), reduced severe acute kidney injury (50% vs 57%; OR, 0.75; 95% CI, 0.62-0.90), less Major Adverse Kidney Events at 1 year (OR, 0.27; 95% CI, 0.22-0.68), and increased renal recovery (95% vs 86%; OR, 6.43; 95% CI, 3.42-12.1).

CONCLUSIONS

Metformin exposure during hospitalization is associated with a decrease in 90-day mortality in patients with type 2 diabetes mellitus and sepsis.

Blood lactate levels in sepsis: in 8 questions

PURPOSE OF REVIEW

Blood lactate concentrations are frequently measured in critically ill patients and have important prognostic value. Here, we review some key questions related to their clinical use in sepsis.

RECENT FINDINGS

Despite the metabolic hurdles, measuring lactate concentrations remains very informative in clinical practice. Although blood lactate levels change too slowly to represent the only guide to resuscitation, serial lactate levels can help to define the patient's trajectory and encourage a review of the therapeutic strategy if they remain stable or increase over time.

SUMMARY

Lactate concentrations respond too slowly to be used to guide acute changes in therapy, but can help evaluate overall response. Hyperlactatemia should not be considered as a problem in itself, but as a warning of altered cell function.