The Novel Predictive Biomarkers for Type 2 Diabetes Mellitus in Active Pulmonary Tuberculosis Patients

A Novel Inflammatory Indicator for Tuberculosis-Associated Obstructive Pulmonary Disease (TOPD): The Systemic Inflammatory Response Index (SIRI)

Background

The development of chronic obstructive pulmonary disease (COPD) following tuberculosis (TB) is known as tuberculosis-associated obstructive pulmonary disease (TOPD). This study aimed to explore the predictive value of inflammatory indicators for TOPD in TB patients.

Methods

Data for this cross-sectional study were collected between January 2014 and January 2022 at Wuhan Jinyintan Hospital. The ratio of inflammatory indicators, including Systemic Inflammatory Response Index (SIRI), C-reactive protein-to-lymphocyte ratio (CLR), eosinophil count-to-lymphocyte count ratio (ELR), were calculated. Univariate and multivariate logistic regression analyses were conducted to explore the association between the ratio of inflammatory indicators and TOPD. Furthermore, the relationship between the ratio of inflammatory indicators and TOPD was investigated using propensity score matching (PSM) and receiver operating characteristic (ROC) curve analysis was performed to evaluate their predictive value for TOPD.

Results

The present study included a total of 737 patients, of whom 83 participants (11.26%) had TOPD. Sixty-nine TOPD patients and 69 non-TOPD (NTOPD) patients were successfully matched. Univariate and multivariable logistics regression analysis, conducted before and after PSM, revealed that SIRI was independently significantly associated with an increased risk of TOPD. The area under curve (AUC) of SIRI were 0.702 and 0.668 before and after PSM, respectively. Additionally, patients were stratified into four different groups based on SIRI quartiles for further analysis. The prevalence of TOPD in TB patients showed an increase with higher SIRI values, both before and after PSM.

Conclusion

Levels of inflammatory indicators were higher in TOPD patients when compared to NTOPD patients. SIRI may be a simple and useful inflammatory index for assessing TOPD, and TB patients with higher values of SIRI are more likely to be high-risk group for TOPD.

Complete blood count inflammation derived indexes as predictors of metabolic syndrome in type 2 diabetes mellitus

BACKGROUND

Metabolic syndrome (MetS) is a group of comorbidities related to regulating hyperglycemia and acute cardiovascular incidents and complications. With the increasing prevalence in individuals with type 2 diabetes mellitus (T2DM), MetS represents an increasing public health problem and clinical challenge, and early diagnosis is necessary to avoid the accelerated development of diabetic complications.

OBJECTIVE

To investigate the role of Complete Blood Count-derived Inflammation Indexes (CBCIIs) in predicting MetS in T2DM individuals.

METHODS

The study was designed as a two-year prospective study and included 80 T2DM individuals divided into MetS and non-MetS groups based on MetS development over two years. The sera samples were analyzed for complete blood count parameters and C-reactive protein (CRP). Based on the laboratory test results, 13 CBCIIs were calculated and analyzed. The receiver operating characteristic (ROC) curve and their corresponding areas under the curve (AUC) were used to determine prognostic accuracy.

RESULTS

There were significant differences between T2DM participants with Mets and those without MetS concerning Neutrophil to Platelet Ratio (NPR) values (p< 0.001), Neutrophil to Lymphocyte and Platelet Ratio (NLPR) (p< 0.001), Platelet to Lymphocyte Ratio (PLR) (p< 0.001), Lymphocyte to C-reactive protein Ratio (LCR) (p< 0.001), C-reactive protein to Lymphocyte Ratio (CRP/Ly) (p< 0.001), Systemic immune inflammation index (SII) (< 0.001), and Aggregate Index of Systemic Inflammation (AISI) (p= 0.005). The results of ROC curve analysis have shown that the LCR (AUC of 0.907), CRP/Ly (AUC of 0.907) can serve as excellent predictors, but NPR (AUC of 0.734), NLRP (AUC of 0.755), PLR (AUC of 0.823), SII (AUC of 0.745), and AISI (AUC of 0.688) as good predictors of MetS in T2 DM individuals.

CONCLUSION

This study confirms the reliability of the CBCIIs as novel, simple, low cost and valuable predictors of MetS developing in T2DM.

The survival analysis of rifampicin/multidrug-resistant tuberculosis patients based on the levels of inflammatory biomarkers: a retrospective cohort study

Purpose

The development of tuberculosis and inflammatory status are closely related. The aim of this study was to investigate the prognostic value of inflammatory biomarkers in patients with rifampicin/multidrug-resistant tuberculosis (RR/MDR-TB).

Patients and methods

This study recruited 504 patients with RR/MDR-TB from Wuhan Jinyintan Hospital. A total of 348 RR/MDR patients from January 2017 to December 2019 were defined as training set, the rest of patients as validation set. The patients were divided into three-risk degrees according to the levels of inflammatory biomarkers (median, 85th percentile). Kaplan-Meier curve and log-rank test were used to assess survival differences among the groups. Cox proportion risk regression was used to identify risk factors for RR/MDR-TB mortality.

Results

In training set, cox proportion risk regression analysis showed that high age (≥60 years) [OR (95%CI):1.053(1.03188-1.077)], smoking [OR (95%CI):2.206(1.191-4.085)], and bronchiectasia [OR (95%CI):2.867(1.548-5.311)] were prognostic factors for RR/MDR-TB patients. In addition, lower survival rates were observed in high CAR group [OR (95%CI):1.464(1.275-1.681)], high CPR group[OR (95%CI):1.268(1.101-1.459)], high CLR group[OR (95%CI):1.004(1.002-1.005)], high NLR group[OR (95%CI):1.103(1.069-1.139)], high PLR group[OR (95%CI):1.003(1.002-1.004)], and high MLR group[OR (95%CI):3.471(2.188-5.508)].Furthermore, AUCs of age, smoking, bronchiectasia, CAR, CPR, CLR, NLR, PLR, and MLR for predicting mortality in RR/MDR-TB patients were 0.697(95%CI:0.618-0.775), 0.603(95%CI:0.512-0.695), 0.629(95%CI:0.538-0.721), 0.748(95%CI:0.675-0.821, P<0.05), 0.754(95%CI:0.683-0.824, P<0.05), 0.759(95%CI:0.689-0.828, P<0.05), 0.789(95%CI:0.731-0.846, P<0.05), 0.740(95%CI:0.669-0.812, P<0.05), and 0.752(95%CI:0.685-0.819, P<0.05), respectively. Importantly, the AUC of predicting mortality of combination of six inflammatory biomarkers [0.823 (95%CI:0.769-0.876)] is higher than any single inflammatory biomarkers. Additionally, the similar results are also obtained in the validation set.

Conclusion

Inflammatory biomarkers could predict the survival status of RR/MDR-TB patients. Therefore, more attention should be paid to the level of inflammatory biomarkers in clinical practice.

Combination model of neutrophil to high-density lipoprotein ratio and system inflammation response index is more valuable for predicting peripheral arterial disease in type 2 diabetic patients: A cross-sectional study

BACKGROUND

Neutrophil/high-density lipoprotein (HDL) ratio (NHR), monocyte/HDL ratio (MHR), lymphocyte/HDL ratio (LHR), platelet/HDL ratio (PHR), systemic immune-inflammation index (SII), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) have been recently investigated as novel inflammatory markers. Herein, the correlation was investigated between these inflammatory biomarkers and peripheral arterial disease (PAD) in type 2 diabetes mellitus (T2DM) patients.

METHODS

In this retrospective observational study, the hematological parameter data of 216 T2DM patients without PAD (T2DM-WPAD) and 218 T2DM patients with PAD (T2DM-PAD) at Fontaine stages II, III or IV stage had been collected. Differences in NHR, MHR, LHR, PHR, SII, SIRI, and AISI were analyzed, and receiver operating characteristic (ROC) curves were used to analyze the diagnostic potential of these parameters.

RESULTS

The levels of NHR, MHR, PHR, SII, SIRI and AISI in T2DM-PAD patients were significantly higher than in T2DM-WPAD patients (P < 0.001). They were correlated with disease severity. Further, multifactorial logistic regression analyses showed that higher NHR, MHR, PHR, SII, SIRI, and AISI might be independent risk factors for T2DM-PAD (P < 0.001). The areas under the curve (AUCs) of the NHR, MHR, PHR, SII, SIRI, and AISI for T2DM-PAD patients was 0.703, 0.685, 0.606, 0.648, 0.711, and 0.670, respectively. The AUC of the NHR and SIRI combined model was 0.733.

CONCLUSION

The levels of NHR, MHR, PHR, SII, SIRI, and AISI were higher in T2DM-PAD patients, and they were independently linked with its clinical severity. The combination model of NHR and SIRI was most valuable for predicting T2DM - PAD.