Association between admission lactate levels and mortality in patients with acute coronary syndrome: a retrospective cohort study

Preadmission metformin use increased the incidence of hyperlactatemia at admission and 30-day in-hospital mortality among T2D patients with heart disease at high risk of hypoxia

BACKGROUND

Surprisingly, despite the high prevalence of metformin use in type 2 diabetes (T2D) patients with heart disease, limited safety data is available regarding metformin use in patients with acute and critical heart disease.

METHODS

In this single-center retrospective study, patients admitted to the cardiology department for heart failure (HF) or acute coronary syndrome (ACS) between December 2013 and December 2021 and who underwent arterial blood gas analysis at admission with an estimated glomerular clearance rate of ≥45 ml/min/1.73 m2 were identified. The incidences of hyperlactatemia, acidosis, and 30-day in-hospital mortality were compared between preadmission metformin users and nonusers.

RESULTS

Of 526 admissions, 193/193 metformin users/nonusers were selected in a propensity score-matched model. Metformin users had greater lactate levels (2.55 ± 2.07 mmol/l vs. 2.00 ± 1.80 mmol/l P < 0.01), a greater incidence of hyperlactatemia [odds ratio (OR) = 2.55; 95% confidence interval (CI), 1.63-3.98; P < 0.01] and acidosis (OR = 1.78; 95% CI, 1.00-3.16; P < 0.05) at admission and a greater incidence of in-hospital mortality (OR = 3.83; 95% CI, 1.05-13.94; P < 0.05), especially those with HF/acute myocardial infarction, elderly age, or without preadmission insulin use.

CONCLUSIONS

Our results suggest that, compared to metformin nonusers, preadmission use of metformin may be associated with a greater incidence of hyperlactatemia and acidosis at admission and greater 30-day in-hospital mortality among T2D patients with HF or ACS at high risk of hypoxia, particularly those without preadmission insulin use. The safety of metformin in this population needs to be confirmed in prospective controlled trials.

Association between normalized lactate load and in-hospital mortality in patients with acute myocardial infarction

BACKGROUND

Lactate was a prognostic indicator for acute myocardial infarction (AMI) patients. However, the association between normalized lactate load, representing hypoxic burden over time, and in-hospital mortality remained uncertain.

METHODS

The data for this study was obtained from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.1) database. The normalized lactate load, describing the average intensity of hyperlactatemia, was calculated as the area under the curve (AUC) of lactate divided by time. 5882 AMI patients enrolled in this study were divided into survivor (n = 5015), and non-survivor group (n = 867). The primary endpoint was in-hospital mortality. Receiver operating characteristic (ROC) curves were generated to assess the predictive efficacy of normalized lactate load for in-hospital mortality, and areas under the curves of different parameters were compared using DeLong test. Multivariate binary logistic regression analysis was employed to explore the association between normalized lactate load and in-hospital mortality. The adjusting variables included age, gender, ethnicity, heart rate, systolic blood pressure, congestive heart failure, shock, dyslipidemia, cardiac arrest, cerebrovascular disease, neutrophil, lymphocyte, creatinine, blood nitrogen urea, clopidogrel, beta-blockers, angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor blocker (ARB), statins, dialysis, extracorporeal membrane oxygenation (ECMO), the Sequential Organ Failure Assessment (SOFA) score and Simplified Acute Physiology Score II (SAPS II). Restricted cubic spline (RCS) was conducted to evaluate nonlinear associations of normalized lactate load with in-hospital mortality.

RESULTS

The overall in-hospital mortality rate was 14.7%. After adjusting for confounding variables, normalized lactate load was independently associated with increased risk of in-hospital mortality (Normalized lactate load≥2.6 vs Normalized lactate load<2.6: OR, 95% CI: 1.56, 1.27-1.93). The RCS demonstrated a positive linear relationship between normalized lactate load and in-hospital mortality (non-linear p = 0.725). ROC curves showed that normalized lactate load was better than first lactate, maximum lactate, and mean lactate in predicting in-hospital mortality, but lower than SOFA and SAPS II. Among participants with at least nine lactate measures, normalized lactate load showed predictive performance comparable to SOFA and SAPS II.

CONCLUSION

Normalized lactate load can be used to predict the prognosis of in-hospital mortality in AMI patients, and its prediction performance increases with the increase of lactate measurement.

Prognostic value of arterial lactate index in ST-elevation myocardial infarction treated with primary percutaneous coronary intervention: a prospective cohort study

Aim: Limited knowledge exists on the pathophysiological cascade beyond serum lactate's association with myocardial injury. Method: Assessed the prognostic value of lactate index on periprocedural variables and its impact on 30-day major adverse cardiovascular events (MACE) in 300 prospective ST-elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention (pPCI). Results: Significant correlations were observed between admission lactate and Killip class, periprocedural time intervals, postprocedure thrombolysis in myocardial infarction (TIMI) flow and myocardial blush grade (MBG; p < 0.01). Lactate levels correlated with diminished ST-deviation resolution, cardiac enzymes (CK-MB, troponin; p < 0.001; 0.004), and lower ejection fraction (p < 0.001). This relationship impacted 30-day MACE (p < 0.001). Conclusion: Hyperlactatemia in STEMI patients undergoing pPCI is associated with worse Killip class, unsatisfactory TIMI flow, MBG, larger infarct size and higher 30-day MACE. Serum lactate aids risk stratification in pPCI for STEMI patients.

A simple APACHE IV risk dynamic nomogram that incorporates early admitted lactate for the initial assessment of 28-day mortality in critically ill patients with acute myocardial infarction

BACKGROUND

Early risk stratification is important for patients with acute myocardial infarction (AMI). We aimed to develop a simple APACHE IV dynamic nomogram, combined with easily available clinical parameters within 24 h of admission, thus improving its predictive power to assess the risk of mortality at 28 days.

METHODS

Clinical information on AMI patients was extracted from the eICU database v2.0. A preliminary XGBoost examination of the degree of association between all variables in the database and 28-day mortality was conducted. Univariate and multivariate logistic regression analysis were used to perform screening of variables. Based on the multifactorial analysis, a dynamic nomogram predicting 28-day mortality in these patients was developed. To cope with missing data in records with missing variables, we applied the multiple imputation method. Predictive models are evaluated in three main areas, namely discrimination, calibration, and clinical validity. The discrimination is mainly represented by the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Calibration is represented by the calibration plot. Clinical validity is represented by the decision curve analysis (DCA) curve.

RESULTS

A total of 504 people were included in the study. All 504 people were used to build the predictive model, and the internal validation model used a 500-bootstrap method. Multivariate analysis showed that four variables, APACHE IV, the first sample of admission lactate, prior atrial fibrillation (AF), and gender, were included in the nomogram as independent predictors of 28-day mortality in AMI. The prediction model had an AUC of 0.819 (95%CI 0.770-0.868) whereas the internal validation model had an AUC of 0.814 (95%CI 0.765-0.860). Calibration and DCA curves indicated that the dynamic nomogram in this study were reflective of real-world conditions and could be applied clinically. The predictive model composed of these four variables outperformed a single APACHE IV in terms of NRI and IDI. The NRI was 16.4% (95% CI: 6.1-26.8%; p = 0.0019) and the IDI was 16.4% (95% CI: 6.0-26.8%; p = 0.0020). Lactate accounted for nearly half of the total NRI, which showed that lactate was the most important of the other three variables.

CONCLUSION

The prediction model constructed by APACHE IV in combination with the first sample of admission lactate, prior AF, and gender outperformed the APACHE IV scoring system alone in predicting 28-day mortality in AMI. The prediction dynamic nomogram model was published via a website app, allowing clinicians to improve the predictive efficacy of the APACHE IV score by 16.4% in less than 1 min.

Lactate level and lactate clearance for acute kidney injury prediction among patients admitted with ST-segment elevation myocardial infarction: A retrospective cohort study

Background

Hyperlactatemia is a prognostic marker among patients with ST-segment elevation acute myocardial infarction (STEMI). However, the predictive value of lactate and the dynamic change associated with acute kidney injury (AKI) among patients with STEMI, remain poorly understood. We aimed to compare single lactate values at admission (Lacadm) and 12 h after admission (Lac12h) with lactate clearance (LC) 12 h after admission for AKI prediction in patients with STEMI.

Methods

A total of 1,784 patients with STEMI were included. The study endpoint was AKI occurrence during hospitalization. The predictive value of lactate levels measured at admission and 12 h after admission and LC for AKI prediction was determined using multivariate logistic regression analyses and compared with receiver operator characteristic (ROC) curve analysis.

Results

Overall, AKI was observed in 353 (19.8%) patients. In multivariate logistic regression analyses, Lacadm ≥ 4.3 mmol/L (OR: 1.53; 95% CI: 1.01-2.30), Lac12h ≥ 2.1 mmol/L (OR: 1.81; 95% CI: 1.36-2.42), and LC ≥ -7.5% (OR: 0.40; 95% CI: 0.30-0.53) were the independent predictive factors for AKI after adjusting for confounders. ROC curve analysis results revealed that Lac12h (0.639; 95% CI: 0.616-0.661) exhibited a significantly higher area under the curve (AUC) than those of Lacadm (0.551; 95% CI: 0.527-0.574) and LC (0.593; 95% CI: 0.570-0.616) in the prediction of AKI. LC (△AUC = 0.037, p < 0.001) and Lac12h (△AUC = 0.017, p = 0.029) enhanced the discrimination capacity of Mehran Risk Score (MRS) for AKI among patients undergoing emergency coronary angiography.

Conclusion

Lac12h is more effective for AKI prediction among patients with STEMI than Lacadm and LC. Furthermore, Lac12h and LC enhance the prediction capacity of MRS for AKI among patients after emergency coronary angiography.

Outcomes of hyperlactatemia on admission in critically ill patients with acute myocardial infarction: A retrospective study from MIMIC-IV

BACKGROUND

It has not been verified whether there is a correlation between admission hyperlactatemia and outcomes in critically ill patients with acute myocardial infarction (AMI), especially in large data studies, which we aimed to do in this study.

METHODS

For this retrospective study, we extracted analysis data from a famous online intensive care unit database, the Medical Information Mart for Intensive Care (MIMIC)-IV. Included patients were divided into four groups according to the serum lactate level on admission. Hospital mortality and mortality over time were the main outcomes. To explore the relationship between admission hyperlactatemia and outcomes in critically ill patients with AMI, logistic regression, Cox regression, Kaplan-Meier curves, and subgroup analyses were used.

RESULTS

2171 patients matching the selection criteria were enrolled in this study. After adjusting for potential confounding factors, hyperlactatemia on admission contributed to increased short-term mortality in critically ill patients with AMI. The adjusted odds ratio for hospital mortality were 1.62, 3.46 and 5.28 in the mild, moderate, and severe hyperlactatemia groups (95% CI: 1.20-2.18, 2.15-5.58, and 2.20-12.70, respectively). The adjusted hazard ratio for 7-day and 30-day mortality were 1.99 and 1.35 (95% CI: 1.45-2.73 and 1.09-1.67) in the mild hyperlactatemia group, 3.33 and 2.31 (95% CI: 2.22-4.99 and 1.72-3.10) in the moderate hyperlactatemia group, 4.81 and 2.91 (95% CI: 2.86-8.08 and 1.88-4.50) in the severe hyperlactatemia group. The adjusted hazard ratio for 1-year and 5-year mortality were 2.03 and 1.93 (95% CI: 1.58-2.62 and 1.52-2.47) in the moderate hyperlactatemia group, 1.92 and 1.74 (95% CI: 1.28-2.89 and 1.17-2.59) in the severe hyperlactatemia group. Subgroup analyses indicated that the positive correlation between serum lactate level on admission and short-term mortality of critically ill patients with AMI was similar in the subgroups of cardiogenic shock and acute heart failure (P for interaction > 0.05).

CONCLUSION

Hyperlactatemia, especially moderate and severe hyperlactatemia, on admission is closely related to higher short-term mortality incidence in critically ill patients with AMI. The relationship between serum lactate level on admission and short-term mortality of critical AMI patients is stable in subgroups of cardiogenic shock and acute heart failure.

Association of lymphocyte-to-monocyte ratio with the long-term outcome after hospital discharge in patients with ST-elevation myocardial infarction: a retrospective cohort study

OBJECTIVE

Lymphocyte-to-monocyte ratio (LMR), a novel systemic inflammatory factor, correlates with adverse outcomes in patients with cardiovascular disease. However, data are limited regarding the prognostic value of LMR in patients with ST-elevation myocardial infarction (STEMI) after hospital discharge. Therefore, the aim of our study was to evaluate the prognostic impact of admission LMR in hospital survivors of STEMI.

METHODS

This retrospective observational study enrolled 1369 STEMI patients between 2014 and 2017. The study population was divided into three groups according to tertiles (T) of LMR (T1: ≥2.84; T2: 1.85-2.83; T3: <1.85). The primary outcomes were long-term outcomes after discharge including major adverse cardiac events (MACE) and all-cause mortality. The associations between LMR and long-term outcomes were assessed using Cox regression analysis.

RESULTS

The median follow-up period was 556 days (interquartile range, 342-864 days). Independent correlations were observed between LMR and both long-term MACE and all-cause mortality. For long-term MACE, the T3 (adjusted hazard ratio [HR], 1.74; 95% confidence interval [CI]: 1.12-2.70; P = 0.013) and T2 groups (adjusted HR, 1.65; CI: 1.07-2.54; P = 0.024) showed significantly higher risk of MACE than did the T1 group. For long-term all-cause mortality, the adjusted HR was 3.07 (CI: 1.10-8.54; P = 0.032) in the T3 group and 2.35 (CI: 0.82-6.76; P = 0.112) in the T2 group compared with that of the T1 group.

CONCLUSION

Decreased admission LMR was independently associated with long-term all-cause mortality and MACE after discharge in patients with STEMI.

A prognostic nomogram for long-term major adverse cardiovascular events in patients with acute coronary syndrome after percutaneous coronary intervention

BACKGROUND

Accurate prediction of major adverse cardiovascular events (MACEs) is very important for the management of acute coronary syndrome (ACS) patients. We aimed to construct an effective prognostic nomogram for individualized risk estimates of MACEs for patients with ACS after percutaneous coronary intervention (PCI).

METHODS

This was a prospective study of patients with ACS after PCI from January 2013 to July 2019 (n = 2465). After removing patients with incomplete clinical information, a total of 1986 patients were randomly divided into evaluation (n = 1324) and validation (n = 662) groups. Predictors included in the nomogram were determined by a multivariate Cox proportional hazards regression model based on the training set. Receiver operating characteristic (ROC) curves and calibration curves were used to assess the discrimination and predictive accuracy of the nomogram, which were then compared with those of the classic models. The clinical utility of the nomogram was assessed by X-tile analysis and Kaplan-Meier curve analysis.

RESULTS

Independent prognostic factors, including lactate level, age, left anterior descending branch stenosis, right coronary artery stenosis, brain natriuretic peptide level, and left ventricular ejection fraction, were determined and contained in the nomogram. The nomogram achieved good areas under the ROC curve of 0.712-0.762 in the training set and 0.724-0.818 in the validation set and well-fitted calibration curves. In addition, participants could be divided into two risk groups (low and high) according to this model.

CONCLUSIONS

A simple-to-use nomogram incorporating lactate level effectively predicted 6-month, 1-year, and 4-year MACE incidence among patients with ACS after PCI.

The Effect of High Lactate Level on Mortality in Acute Heart Failure Patients With Reduced Ejection Fraction Without Cardiogenic Shock

BACKGROUND

We aimed to determine the effect of blood lactate levels on cardiovascular (CV) death and hospitalization for heart failure (HF) in acute HF patients with reduced left ventricular ejection fraction (EF).

METHODS

Eighty-five acute HF patients with reduced ejection fraction were divided into two groups according to admission blood lactate levels. 48 of them had low blood lactate levels (< 2 mmol/l) and 37 of them had high blood lactate levels (≥ 2 mmol/l). Patients with acute coronary syndrome, cardiogenic shock, sepsis and low blood pressure at admission were excluded from the study. Primary endpoint is the composite of cardiovascular (CV) death and hospitalization for heart failure (HHF) in 6-month follow-up. Secondary endpoint is the change in NT-proBNP levels from admission to 72 h.

RESULTS

Baseline characteristics of patients were similar in two groups. On baseline echocardiographic evaluation; patients with high lactate revealed a higher mitral E/A ratio (2.34 [0.43-3.31], p = 0.008) and a lower TAPSE ratio (14 [10-27], p = 0.008) than patients with low lactate levels. Over a median follow-up period of 6 months, the primary end point occurred in 28 (75.7%) of 37 patients assigned to high lactate group and in 20 (41.7%) of 48 patients assigned to low lactate group (p = 0.006). High lactate levels significantly increased the risk of CV death and HHF at 6 months by nearly 5.35-fold in acute HF patients with reduced EF. The change in NT-proBNP levels at 72nd hour after admission were similar between two groups.

CONCLUSION

Higher lactate levels at admission related with higher HHF at 6 months and may be related with higher risk of CV death in acute HF patients with reduced EF.

Association of Different Lactate Indices with 30-Day and 180-Day Mortality in Patients with ST-Segment Elevation Myocardial Infarction Treated with Primary Percutaneous Coronary Intervention: A Retrospective Cohort Study

Background

Admission lactate level has been reported as a useful marker of mortality. In this study, we compared the relative value of different lactate indices to predict survival in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI).

Methods

This was a retrospective observational study including consecutive patients with STEMI undergoing primary PCI who admitted to the Coronary Care Unit of the First Affiliated Hospital of Wenzhou Medical University between 2014 and 2017. The predictive value of lactate indices for mortality was compared using receiver operator characteristic (ROC) analysis, and DeLong’s test was used to compare the AUC. We compared the AUC between GRACE score and GRACE score + lactate index.

Results

A total of 1080 patients were included. Fifty-nine died in 30 days and 68 died in 180 days. Most lactate indices (Lac_adm, Lac_24max, Lac_24min and Lac_24tw) were significantly lower in survivors (all P<0.001). In Cox proportional hazards model, each lactate index showed as an independent factor of 30-day and 180-day mortality except Lac_Δ. Kaplan–Meier curves demonstrated that the patients of higher lactate indices group had higher rates of mortality (all P<0.0001, except Lac_Δ P=0.0485). In receiver operator characteristic analysis, Lac_24max was significantly larger than Lac_adm(P<0.001) while the AUC value for Lac_adm was similar to Lac_24min and Lac_24tw. Lac_24tw improved the predictive probability of 30-day mortality (P=0.0415). Lac_24max improved the predictive probability of GRACE score for both 30-day and 180-day mortality (P<0.05).

Conclusion

In patients with STEMI undergoing primary PCI, most lactate indices are all associated with 30-day and 180-day mortality except LacΔ. In prediction of both 30-day and 180-day mortality, Lac_24max is superior to Lac_adm and significantly enhances the ability of risk stratification and prognostic evaluation when adding Lac_24max to the GRACE score.

The association between the initial lactate level and need for massive transfusion in severe trauma patients with and without traumatic brain injury

Background

Exsanguination is a major cause of death in severe trauma patients. The purpose of this study was to analyze the prognostic impact of the initial lactate level for massive transfusion (MT) in severe trauma. We divided patients according to subgroups of traumatic brain injury (TBI) and non-TBI.

Methods

This single-institution retrospective study was conducted on patients who were admitted to hospital for severe trauma between January 2016 and December 2017. TBI was defined by a head Abbreviated Injury Scale ≥3. Receiver operating characteristic analysis was used to analyze the prognostic impact of the lactate level. Multivariate analyses were performed to evaluate the relationship between the MT and lactate level. The primary outcome was MT.

Results

Of the 553 patients, MT was performed in 62 patients (11.2%). The area under the curve (AUC) for the lactate level for predicting MT was 0.779 (95% confidence interval [CI], 0.742 to 0.813). The AUCs for lactate level in the TBI and non-TBI patients were 0.690 (95% CI, 0.627 to 0.747) and 0.842 (95% CI, 0.796 to 0.881), respectively. In multivariate analyses, the lactate level was independently associated with the MT (odds ratio [OR], 1.179; 95% CI, 1.070 to 1.299). The lactate level was independently associated with MT in non-TBI patients (OR, 1.469; 95% CI, 1.262 to 1.710), but not in TBI patients.

Conclusions

The initial lactate level may be a possible prognostic factor for MT in severe trauma. In TBI patients, however, the initial lactate level was not suitable for predicting MT.