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31 January 2025: Clinical Research  

Leukoglycemic Index and Its Prognostic Implications in Diabetic and Nondiabetic Patients with Acute Pulmonary Embolism

Nuray Aslan ORCID logo1ABCDEF*, Fatih Güneysu ORCID logo2ADEF, Yusuf Yürümez ORCID logo2ADF, Necip Gökhan Güner ORCID logo2BCD, Sacit Akdeniz ORCID logo1BF, Muharrem Kaner ORCID logo2BF

DOI: 10.12659/MSM.947156

Med Sci Monit 2025; 31:e947156

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Abstract

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BACKGROUND: The leuko-glycemic index (LGI) combines the white blood cell count and blood glucose levels and is calculated by multiplying the 2 values and dividing them by 1000. This study aimed to compare the prognostic value of the LGI in 199 patients with acute pulmonary embolism (APE) with and without diabetes mellitus.

MATERIAL AND METHODS: This study was conducted retrospectively on 199 patients who were admitted to the Emergency Department of Sakarya Training and Research Hospital between January 1, 2019, and December 31, 2022, and received a diagnosis of APE by pulmonary angiography. The patients were divided into 2 groups, diabetic and nondiabetic, based on their medical history. The groups were compared in terms of mortality according to the optimal cut-off value of LGI.

RESULTS: Of the 199 patients with APE included in the study, 61% were women and 39% were men. Mortality was higher in the diabetic group, and a simplified Pulmonary Embolism Severity Index score ≥1 was an independent predictor of all-cause mortality during the 30-day follow-up in the nondiabetic group (P=0.024). Multivariate logistic regression analysis showed that LGI was not an independent predictor of all-cause mortality during the first 30 days of follow-up in either group (P>0.05).

CONCLUSIONS: Mortality was higher in patients with diabetes and APE. However, the LGI was not an independent predictor of mortality in patients with or without diabetes. Since there are not enough studies on this subject, this result needs to be supported by additional research.

Keywords: Emergency Medicine, Pulmonary Embolism

Introduction

Cardiovascular disease is the leading cause of death and premature death worldwide [1]. The third most common cause of cardiovascular disease-related deaths is acute pulmonary embolism (APE), with an annual incidence of 39 to 115 per 100 000, and a mortality rate of approximately 300 000 per year. Approximately 70% of deaths occur within days [2].

A thorough examination of the literature showed that the tendency toward hypercoagulability in developing thrombus during APE is influenced by venous stasis, vascular endothelial damage, and the triggering effects of specific inflammatory cytokines and immune cells [3–5]. A similar situation is discussed in thrombus formation in acute coronary syndromes, with an alleged involvement of inflammatory cytokines and immune cells in thrombus formation [6]. Another factor that triggers thrombus formation is diabetes. In diabetes, impaired glucose balance initiates a transition to a hypercoagulable state and triggers thrombus formation [7]. Especially in stressful situations, the release of inflammatory mediators affects glucose metabolism, leading to hyperglycemia [4]. Hyperglycemia triggers the release of procoagulant and proinflammatory molecules, resulting in vascular complications and prothrombotic conditions [8,9]. The blood glucose level, serving as a key inflammatory marker in leukocytes, is noteworthy because, unlike other markers not readily accessible in practical applications, it is included in routine tests [4].

Considering these data, the leuko-glycemic index (LGI), which combines 2 accessible parameters, leukocyte count and blood glucose level, has become a researched topic. In previous studies, LGI has been identified as an independent determinant of post-acute myocardial infarction (AMI) mortality and a predictor of acute cardiac and non-cardiac complications [3,10,11]. Furthermore, it has been demonstrated that the LGI predicts in-hospital mortality in diabetic and nondiabetic patients with AMI [12]. However, although AMI has similar pathophysiological mechanisms to APE, our literature search did not reveal any studies on the use of the LGI in patients with APE. Therefore, this study aimed to compare the prognostic value of the LGI in 199 patients with APE, with and without diabetes mellitus.

Material and Methods

ETHICS:

This study was approved by the local ethics committee in our institution (IRB No: 71522473/050.01.04-309477-364), and the Declaration of Helsinki was complied with during the study process. Since our study was designed retrospectively, informed consent was not obtained from the patients.

STUDY DESIGN AND POPULATION:

This study was conducted retrospectively on 199 patients who were admitted to the Emergency Department of Sakarya Training and Research Hospital between January 1, 2019, and December 31, 2022, and received a diagnosis of APE by pulmonary angiography. The patients were divided into 2 groups, diabetic and nondiabetic, based on their medical history.

The inclusion criteria were age >18 years and diagnosis of APE. The exclusion criteria were age <18 years, incomplete data, and conditions such as pregnancy, hemolytic disease, acquired immunodeficiency, acquired immunodeficiency, rheumatic disease, chronic renal failure, chronic liver disease, and malignancy.

DATA COLLECTION:

Demographic characteristics, including sex and age, comorbidities, APE symptoms, vital signs, laboratory parameters, including hematological, biochemical, and serological, hemodynamic instability status, including inotrope administration, respiratory support, arrest, and simplified Pulmonary Embolism Severity Index (sPESI) scores ≥1, clinical results, including discharge, referral, or hospitalization, and 30-day mortality status of both groups were recorded. The white blood cell count was expressed as cells per mm3, and blood glucose level was expressed as mg/dL. The LGI is calculated by multiplying the 2 values and dividing by 1000, and is reported as mg/dL·mm3 [10]. Then, the same parameters were compared according to the optimum cut-off value of LGI determined for predicting in-hospital mortality for both groups, and the prognostic value of LGI was investigated.

STATISTICAL ANALYSIS:

The conformity of measurable data to a normal distribution was evaluated with the Shapiro-Wilk test. Median and 25th and 75th percentile values of continuous variables are given. The Mann-Whitney U test was used to compare continuous variables. Percentage values are given for categorical variables. Groups containing categorical variables were analyzed with the chi-square test. Univariate and multivariate logistic regression analysis evaluated relationships between variables and death within the first 30 days. The optimal cutoff value of the LGI for predicting in-hospital mortality was determined using the Youden index in the receiver operating characteristic (ROC) curve. All tests were performed with a 2-sided significance of 5%. For each endpoint, absolute and relative effects and their corresponding 95% confidence intervals were calculated according to Altman et al [13]. All analyses were performed using IBM SPSS version 21.

Optimum threshold values for both study groups were determined according to the Youden index. ROC curves determined that the optimal critical values of LGI were 1472 mg/dL·mm3 (area under the ROC curve [AUC]: 0.474; 95% CI: 0.354–0.595; sensitivity, 52%; specificity, 50%) and 1934 mg/dL·mm3 (AUC: 0.632; 95% CI: 0.502–0.761; sensitivity; 57%, specificity, 57%) to predict mortality within the first 30 days in the diabetic and nondiabetic groups, respectively. The 2 groups were divided into high- and low-LGI subgroups (Figures 1, 2).

ENDPOINT AND FOLLOW-UP:

The endpoint was defined as all-cause mortality occurring in the hospital or during follow-up. The follow-up period was determined as 30 days after discharge. Information about in-hospital death was obtained from hospital records, and information about death that occurred during follow-up was obtained by calling the patients’ relatives.

Results

BASELINE CHARACTERISTICS:

A total of 199 patients with APE were included in the study, with 61% (121/199) women and 39% (78/199) men. Baseline characteristics and clinical conditions are listed in Table 1. The prevalence of hypertension (P<0.001) and coronary artery disease (P=0.007) was higher in the medical history of the diabetic group. In the diabetic group, the patients’ blood glucose (P<0.001), creatinine (P=0.008), and potassium (P=0.006) values were higher, and their glomerular filtration rate (P=0.041) values were lower. It was also observed that mortality was higher in the diabetic group than in the nondiabetic group (P=0.034). The 2 groups had no statistically significant difference regarding symptoms, vital signs, clinical status, and emergency department outcomes (P>0.05).

CHARACTERISTICS OF PATIENTS ACCORDING TO LGI SUBGROUPS:

For the nondiabetic group, there were 63 patients in the high-LGI subgroup, with LGI ≥1472 mg/dL·mm3, and 59 patients in the low-LGI subgroup, with LGI <1472 mg/dL·mm3. For the diabetic group, there were 37 patients in the high-LGI subgroup, with LGI ≥1934 mg/dL·mm3, and 40 patients in the low-LGI group, with LGI <1934 mg/dL·mm3 (Table 2).

In the nondiabetic group, compared with the diabetic group, the prevalence of coronary artery disease was higher, urea, creatinine, troponin, and hemoglobin levels were higher, and glomerular filtration rate was lower. Also, sPESI ≥1 was more common in the high-LGI subgroup (P<0.05). In the diabetic group, compared with the nondiabetic group, C-reactive protein and ferritin levels were higher in the high-LGI subgroup (P<0.05). However, blood glucose, lactate, neutrophil, leukocyte, and platelet levels were statistically significantly higher in the high-LGI subgroups of both groups (P<0.05).

CLINICAL OUTCOMES AT FOLLOW-UP:

A total of 61 patients died within 30 days. Multivariate logistic regression analysis was performed by prioritizing statistically significant parameters and clinical experiences in the analyses performed between the low- and high-LGI subgroups of the nondiabetic and diabetic groups according to mortality outcome. Multivariate logistic regression analysis showed that LGI was not an independent predictor of all-cause mortality during the first 30 days of follow-up in both the diabetic and nondiabetic groups (P>0.05; Table 3). In the nondiabetic group, at the first 30-day follow-up, sPESI ≥1 was an independent predictor of all-cause mortality (P<0.05; Table 3).

Discussion

In this study, we found that mortality was higher in patients with diabetes, and sPESI ≥1 was an independent predictor of all-cause mortality during the 30-day follow-up in patients without diabetes. However, multivariate logistic regression analysis revealed that the LGI was not an independent predictor of all-cause mortality during the 30-day follow-up in either group.

In the literature, there is a search for optimal risk assessment in APE. The main reason for this search is to quickly identify patients with predicted death, implement appropriate treatment options promptly, and prevent early mortality due to APE [14–17]. Studies have been conducted on many biomarkers and laboratory parameters, based on the fact that complex interactions between inflammatory and coagulation factors play a role in the pathophysiology of APE in terms of early mortality prediction [14–16,18].

Diabetes is one of the main cardiovascular risk factors that increases the tendency to hypercoagulation by affecting many organ systems, including the coagulation system. It is known that diabetes creates a predisposing situation for atrial fibrillation, kidney disease, peripheral artery disease, and hypertension [9]. Additionally, many studies in the literature show that diabetes is an independent determinant of mortality in patients with APE [8,9,19]. Therefore, the changes in history and laboratory parameters and the increase in mortality rates in the diabetic group in our study are compatible with the literature, and this result is not surprising.

In a study on rats with APE, Watts et al found neutrophil and macrophage infiltration, especially in the pulmonary artery wall and right ventricle [20]. Other studies on this subject have also reported that the acute inflammatory response causes platelet activation and neutrophil release and is associated with poor prognosis and early mortality in patients [9,14,15,17,18]. Additionally, increases in lactate level (>3.3 mmol/L), deterioration in renal function, and increases in troponin levels have been shown to have increased sensitivity and specificity in predicting adverse outcomes and mortality [17,19–21]. In this regard, it is also seen that the use of troponins and the sPESI score, which has been proven as a prognostic predictor for mortality, is recommended [16]. Our study results showed that contrary to expectations, whether patients had diabetes or not made no difference in terms of inflammatory markers, troponin levels, and sPESI scores in patients with APE. However, clinicians should consider that there are differences in other inflammatory markers, especially troponin, in the evaluation based on LGI elevation. In the evaluation made considering the LGI in our study, the fact that sPESI ≥1 predicted mortality in the first 30 days in the nondiabetic patient group supports this recommendation.

When we looked at the current literature, studies on prognosis prediction of LGI came to the fore [3,10,12,22]. A systematic meta-analysis by Sadeghi et al, which included 10 studies, reported that the LGI had an acceptable prognostic value in predicting major cardiac complications after AMI [12]. Similarly, it has been reported that the LGI predicts in-hospital complications and mortality in patients with AMI and is even a good predictor of 1-year all-cause mortality [10,12]. Qi et al examined patients with AMI by dividing them into 2 groups: diabetic and nondiabetic. They reported that the LGI was an independent determinant for short- and long-term prognosis in patients with AMI, according to different cutoff values [4]. Our study showed that the LGI we examined did not make any additional contribution to mortality in patients with APE, whether they had diabetes or not. This result suggests that there may be mechanisms in AMI that differ from those of APE. However, there are not sufficient studies in the literature to shed light on this issue.

This study had some limitations. It was a retrospective study, and the sample size was relatively small, due to the number of patients for whom the investigated parameters were available. Additionally, the predictive value of the LGI shown in other cardiovascular diseases with similar pathogenesis must be compared with further prognostic scores for its place in APE.

Conclusions

Mortality was higher in patients with diabetes and APE. However, the LGI was not an independent predictor of mortality in either the diabetic or nondiabetic groups. Since there are not enough studies on this subject, this result needs to be supported by additional research.

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