Usefulness of Complete Blood Count (CBC) to Assess Cardiovascular and Metabolic Diseases in Clinical Settings: A Comprehensive Literature Review

Association of high-sensitivity C-reactive protein and hematologic-inflammatory indices with risk of cardiovascular diseases: a population-based study with partial least squares structural equation modeling approach

Partial least squares structural equation modeling is a simple approach that may be used to determine the factors associated with diseases. In the current study, we aimed to explore the most associated high-sensitivity C-reactive protein (hs-CRP) as well as hematologic-inflammatory indices for the risk of cardiovascular disease (CVD). A total of 7362 healthy (non-CVD) participants aged 35-65 years old from baseline investigation were evaluated in the Phase 2 follow-up. Of these, 1022 individuals were found to have CVDs in the second phase (10-year follow-up) of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) cohort study. We used partial least squares structural equation modeling to develop a prediction model for association of CVD risk factors and hs-CRP as well as hematologic-inflammatory indices in the study population. According to the study, age had the most significant impact on the presence of CVD. Increasing in age by one unit raises the risk of CVD by 0.166. Also, serum hs-CRP was found to have the second-highest impact on CVD; increasing in age by one unit raises the risk of CVD by 0.042. The study also discovered a strong and significant correlation between red cell distribution width (RDW) and CVD. Moreover, the study found that several factors such as hemoglobin (HGB), neutrophil (NEUT), neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and platelet-to-lymphocyte ratio (PLR) have indirect effects on CVD that are mediated by hs-CRP while controlling for age, sex and social-economic factors. Generally, the results showed that age, hs-CRP, and RDW were the most important risk factors on CVD.

Predictive biosignatures for hospitalization in patients with virologically confirmed COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, presents with varying severity among individuals. Both viral and host factors can influence the severity of acute and chronic COVID-19, with chronic COVID-19 commonly referred to as long COVID. SARS-CoV-2 infection can be properly diagnosed by performing real-time reverse transcription polymerase chain reaction analysis of nasal swab samples. Pulse oximetry, chest X-ray, and complete blood count (CBC) analysis can be used to assess the condition of the patient to ensure that the appropriate medical care is delivered. This study aimed to develop biosignatures that can be used to distinguish between patients who are likely to develop severe disease and require hospitalization from patients who can be safely monitored in less intensive settings.

METHODS

A retrospective investigation was conducted on 7897 adult patients with virologically confirmed SARS-CoV-2 infection between January 26, 2020, and November 30, 2023; all patients underwent comprehensive CBC testing at Taipei Veterans General Hospital. Among them, 1867 patients were independently recruited for a population study involving genome-wide genotyping of approximately 424 000 genomic variants. Therefore, the participants were divided into two patient cohorts, one with genomic data (n = 1867) and one without (n = 6030) for model validation and training, respectively.

RESULTS

We constructed and validated a biosignature model by using a combination of CBC measurements to predict subsequent hospitalization events (hazard ratio = 3.38, 95% confidence interval: 3.07-3.73 for the training cohort and 3.03 [2.46-3.73] for the validation cohort; both p < 10 -8 ). The obtained scores were used to identify the top quartile of patients, who formed the "very high risk" group with a significantly higher cumulative incidence of hospitalization (log-rank p < 10 -8 in both the training and validation cohorts). The "very high risk" group exhibited a cumulative hospitalization rate of >60%, whereas the rate for the other patients was approximately 30% over a 1.5-year period, providing a binary classification of patients with distinct hospitalization risks. To investigate the genetic factors mediating this risk, we conducted a genome-wide association study. Specific regions in chromosomes 7 and 10 and the mitochondrial chromosome (M), harboring IKAROS family zinc finger 1 ( IKZF1 ), actin binding LIM protein 1 ( ABLIM1 ), and mitochondrially encoded NADH:ubiquinone oxidoreductase core subunit 3 ( MT-ND3 ), exhibited prominent associations with binary risk classification. The identified exonic variants of IKZF1 are linked to several autoimmune diseases. Notably, people with different genotypes of the leading variants (rs4132601, rs141492519, and Affx-120744614) exhibited varying cumulative hospitalization rates after infection.

CONCLUSION

We successfully developed and validated a biosignature model of COVID-19 severe disease in virologically confirmed patients. The identified genomic variants provide new insights for infectious disease research and medical care.

Exploring the causal association between circulating leukocyte count and IgA nephropathy based on two-sample Mendelian randomization: possible role of transitional B cells

BACKGROUND

To examine the causal association between genetically predicted circulating leukocyte counts and IgA nephropathy.

METHODS

A two-sample Mendelian randomization (MR) design was used. The exposures were the neutrophil, lymphocyte (with subsequent analyses for memory B-cell %lymphocyte, IgD- CD38br %lymphocyte, IgD+ CD38br %lymphocyte, CD24+ CD27+ %lymphocyte, Sw mem %lymphocyte, transitional %lymphocyte, and naïve-mature B-cell %lymphocyte), monocyte, basophil, and eosinophil counts. The outcome was IgA nephropathy. Analysis was conducted using the inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode. The Cochran's Q-test and MR-Egger regression were used to assess heterogeneity and horizontal pleiotropy, respectively. The robustness of the results was tested using MR-PRESSO and leave-one-out analyses.

RESULTS

The genetic prediction results showed causal associations between the neutrophil counts and IgA nephropathy (OR = 2.62, 95%CI 2.47-2.77, P < 0.001) and between the lymphocyte counts and IgA nephropathy (OR = 0.76, 95%CI 0.58-0.99, P = 0.04). Monocyte, basophil, and eosinophil counts showed no causal associations with IgA nephropathy. The supplementary genetic prediction analyses showed a causal association between transitional %lymphocytes and IgA nephropathy (OR = 0.58, 95%CI 0.39-0.87, P = 0.008). Cochran's Q test revealed heterogeneity for the neutrophil, lymphocyte, monocyte, eosinophil, transitional %lymphocytes, and count analyses (all P < 0.05), but the MR-Egger test revealed no pleiotropy. After removing the outliers, the associations remained the same.

CONCLUSION

Causal associations were observed between neutrophil and lymphocyte counts as exposures and IgA nephropathy as outcome. Among lymphocytes, transitional B cells could be involved in the pathogenesis of IgA nephropathy. Attention should be paid to neutrophil and lymphocyte counts in future studies on IgA nephropathy.

Left atrial appendage velocity, association with inflammatory indices in non-valvular atrial fibrillation patients

INTRODUCTION

Decreased left atrial appendage emptying velocity (LAAV) is a marker for thrombus formation. This study evaluates the association between LAAV and inflammatory indices in non-valvular atrial fibrillation (AF) patients.

METHODS

The study population was 1428 patients with AF, 875 of whom enrolled. Based on the LAAV, patients were divided into three groups of 262 patients with a velocity of <25 cm/s, 360 patients with a velocity of 25 to 55 cm/s, and 253 patients with a velocity of >55 cm/s to assess and compare in terms of inflammatory indices, including the platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, systemic immune inflammation index, neutrophil - to - platelet ratio and white blood cell-to-platelet ratio (WPR).

RESULTS

There was no statistical difference in the level of inflammatory indices between the three groups, and none of them were related to LAAV (p > .05) except WPR with a weak negative correlation (p = 0.01, r = -0.10). Patients with lower LAAV were found to have a higher age (p = 0.001), decreased left ventricular ejection fraction (p = 0.001) and greater left atrial volume index (p = 0.001).

CONCLUSION

This study did not show any association between inflammatory indices and LAAV in non-valvular AF patients except for the WPR.

Relationship Between Systemic Inflammatory Response Exponents, Levels of ADAM10, ADAM17 Proteins and Selected Clinical Parameters in Patients with Colorectal Cancer: Original Research Study

Chronic inflammation is a confirmed risk factor for colorectal cancer (CRC). Indicators of systemic inflammatory response (SIR), such as neutrophil-to-lymphocyte ratio (NLR) or platelet-to-lymphocyte ratio (PLR), are easily accessible indicators of the generalized inflammatory response. At the molecular level, inflammation-related carcinogenesis involves proteins from the adamalysin family: ADAM10 and ADAM17. The aim of the study was to assess NLR and PLR and their relationship with selected clinical parameters in CRC patients, as well as the correlation between ADAM10 and ADAM17 in tumor tissue and matched surgical margins with NLR and PLR values. Tumor tissue material matched surgical margins, and blood was collected from 66 patients who underwent surgery because of CRC. The concentrations of ADAM10 and ADAM17 in the collected material were tested using the enzyme-linked immunosorbent assay (ELISA) method. SIR parameters (NLR, PLR) were also determined. The results were statistically analyzed and compared with selected clinical parameters. Results: The study showed that PLR was lower in patients with comorbid cardiovascular diseases (CVD). In patients who underwent preoperative treatment, both the NLR and PLR values were higher than in patients who underwent primary surgery. There was also a negative correlation between ADAM17 concentrations in the surgical margin and PLR values. In conclusion, the presence of additional diseases such as CVD or diabetes mellitus type 2 (DMT2) or the use of preoperative treatment should be taken into account when assessing SIR parameters in CRC patients. Moreover, no clear correlations have been found between ADAM10 and ADAM17 and SIR parameters.

Association of Premature Ventricular Contraction (PVC) with hematological parameters: a data mining approach

Premature ventricular contraction (PVC) is characterized by early repolarization of the myocardium originating from Purkinje fibers. PVC may occur in individuals who are otherwise healthy. However, it may be associated with some pathological conditions. In this research the association between hematological factors and PVC was studied. In this study, 9,035 participants were enrolled in the Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort study. The association of hematological factors with PVC was evaluated using different machine learning (ML) algorithms, including logistic regression (LR), C5.0, and boosting decision tree (DT). The dataset was divided into training and test, and each model's performance was appraised on the test dataset. All data analyses used SPSS version 26 and SPSS Modeler 10. The results show that the Boosting DT was the most effective algorithm. Boosting DT had an accuracy of 98.13% and 96.92% for males and females respectively. According to the models, RDW and PLT were the most significant hematological factors for both males and females. WBC, PDW, and HCT for males and RBC, MCV, and MXD for females were also important. Some hematological factors associated with PVC were found using ML models. Further studies are needed to confirm these results in other populations, considering the novelty of the exploration of the relationship between hematological parameters and PVC.

The complete blood count and cardiovascular disease: analyses across six cohorts of 23,370 adults

Background

The complete blood count (CBC) is one of the most performed laboratory studies. However, the CBC and its components are not commonly used to understand and quantify cardiovascular disease (CVD) risk.

Objective

We sought to define the relationships between the CBC, traditional CVD risk factors, and common CVD biomarkers and their joint association with all-cause mortality and CVD.

Methods

We examined the relationships between the CBC, traditional CVD risk factors, and mortality in NHANES (n=7843). We validated and extended these findings to more refined CVD endpoints in five additional cohorts (n=15,527).

Results

We first examined the variance accounted for by common laboratory studies (lipid panel, HbA1c, hs-CRP, and basic metabolic panel) by traditional risk factors in NHANES. Except for hemoglobin (Hb) components, we found that traditional risk factors accounted for less than 20% of the variance in the CBC, suggesting that the CBC provides unique information beyond traditional risk factors and CVD biomarkers. Additionally, the CBC was strongly associated with all-cause mortality (p<0.0001), even more than traditional CVD biomarkers (lipid panel, HbA1c, and CRP). We validated and extended these findings across five additional cohorts with a mean follow-up of 16 years and more refined CVD endpoints. In the fully adjusted analyses, several CBC components, including the white blood cell (WBC) count, neutrophil (PMN) count, Hb level, and an integrated immune cell score, were associated with individual CVD endpoints (incident stroke, MI, or revascularization) and a composite CV endpoint (MACE3) with standardized hazard ratios of 1.13 (p=0.002), 1.15 (p=0.0006), 0.82 (p<0.0001), and 2.16 (p<0.0001) respectively.

Conclusion

This study represents the first systematic examination of the relationship between the CBC, all-cause mortality, and CVD in a diverse cohort of 23,370 adults. These findings underscore the added value of the CBC over traditional risk factors and common CVD biomarkers for CVD risk assessment. Future studies should explore the integration of CBC parameters into predictive models to enhance our understanding, early identification, and prevention strategies for CVD.

Development and validation of a mortality predictive model for ICU patients with primary pulmonary hypertension

There is a lack of an effective prognostic model for predicting outcomes in patients with primary pulmonary hypertension (PPH). A retrospective analysis was conducted on PPH patients from MIMIC and eICU databases. A predictive model was developed to assess mortality risk. The Consistency Index (C-index) and Receiver Operating Characteristic (ROC) curve were utilized to assess the overall performance of the model and its discriminatory capacity. The model's calibration and clinical applicability were assessed through calibration curve and decision curve analysis (DCA). The nomogram was employed for visual representation of the model. The study included 420 patients, 260 in the development group, 104 in the internal validation group and 56 in the external validation group. The predictive model's risk factors included age, respiratory rate, red blood cell distribution width, glucose, and SAPS II. The model demonstrated C-indexes of 0.736 and 0.696 in the development and internal validation groups, respectively. The ROC curves for the development, internal validation and external validation groups demonstrated robust discriminatory capabilities. The calibration curves indicated a slope close to 1, suggesting good calibration of the model. Additionally, DCA analysis revealed the model offered significant clinical benefits across a wide range of thresholds. The model showed good discrimination ability, accuracy and clinical application value in predicting the prognosis of patients with PPH.

Assessing the impact of severe acute respiratory syndrome coronavirus 2 infection on hematological parameters

BACKGROUND

The current study is a retrospective study designed to evaluate changes in complete blood count and coagulation parameters in adult coronavirus disease 2019 (COVID-19) patients at a prominent Saudi tertiary center to predict disease severity and mortality.

METHODS

The cohort consisted of 74 800 adult patients divided into four groups based on a COVID-19 test and the patient's sex: 35 985 in the female negative COVID-19 group, 23 278 in the male negative COVID-19 group, 8846 in the female positive COVID-19 group and 6691 in the male positive COVID-19 group.

RESULTS

Patients with COVID-19 demonstrated decreased white blood cell counts and increased red blood cell counts. Also, COVID-19-positive participants exhibited more prolonged partial thromboplastin time and lower D-dimer levels than those of COVID-19-negative subjects (p<0.05). The study also revealed gender-dependent impacts on platelet counts, implying a possible relationship with the greater infection mortality rate in men than in women (p<0.001). In addition, the study found a link between changes in coagulation test results and death in COVID-19 patients (p<0.001). The evidence regarding the effects of COVID-19 on blood cell counts and coagulation, on the other hand, is conflicting, most likely due to variances in study populations and the timing of testing postinfection.

CONCLUSIONS

According to the findings, COVID-19-related alterations in blood cell count and clotting ability may be risk factors for death.

Key differences between chronic inducible and spontaneous urticaria

Introduction

The latest international EAACI/GA²LEN/EuroGuiDerm/APAAACI guideline for urticaria recommends limited laboratory testing for chronic spontaneous urticaria (CSU) and selective testing for only certain chronic inducible urticaria (CIndU) subtypes, though the rationale for these recommendations is poorly explained. This study aimed to improve the understanding of CIndU subtypes by comprehensively comparing their demographic, clinical, and laboratory characteristics with those of the better-characterized CSU.

Methods

We conducted a retrospective analysis of 567 patients (median age 41 years, 67% female) diagnosed with CSU, symptomatic dermographism (SD), cold urticaria (ColdU), cholinergic urticaria (CholU), and delayed pressure urticaria (DPU).

Results

Our findings revealed that patients with SD, ColdU, and CholU had lower levels of C-reactive protein (CRP), higher total serum immunoglobulin E (IgE) levels, and higher basophil counts compared to CSU patients. These subtypes also had distinct demographic and clinical features, such as a younger age of onset and a longer disease duration. In contrast, patients with DPU had significantly higher CRP levels and neutrophil counts compared to those with CSU.

Discussion

These findings highlight the heterogeneity among chronic urticaria subtypes, suggesting that a tailored approach to laboratory testing may be more effective. The distinct immunological and clinical features observed in CIndU subtypes suggest a need for subtype-specific diagnostic and therapeutic guidelines.

DNA Methylation Age Mediates Effect of Metabolic Profile on Cardiovascular and General Aging

BACKGROUND

Alterations in lipid metabolism and DNA methylation are 2 hallmarks of aging. Connecting metabolomic, epigenomic, and aging outcomes help unravel the complex mechanisms underlying aging. We aimed to assess whether DNA methylation clocks mediate the association of circulating metabolites with incident atherosclerotic cardiovascular disease (ASCVD) and frailty.

METHODS

The China Kadoorie Biobank is a prospective cohort study with a baseline survey from 2004 to 2008 and a follow-up period until December 31, 2018. We used the Infinium Methylation EPIC BeadChip to measure the methylation levels of 988 participants' baseline blood leukocyte DNA. Metabolite profiles, including lipoprotein particles, lipid constituents, and various circulating metabolites, were measured using quantitative nuclear magnetic resonance. The pace of DNA methylation age acceleration (AA) was calculated using 5 widely used epigenetic clocks (the first generation: Horvath, Hannum, and Li; the second generation: Grim and Pheno). Incident ASCVD was ascertained through linkage with local death and disease registries and national health insurance databases, supplemented by active follow-up. The frailty index was constructed using medical conditions, symptoms, signs, and physical measurements collected at baseline.

RESULTS

A total of 508 incident cases of ASCVD were documented during a median follow-up of 9.5 years. The first generation of epigenetic clocks was associated with the risk of ASCVD (P<0.05). For each SD increment in LiAA, HorvathAA, and HannumAA, the corresponding hazard ratios for ASCVD risk were 1.16 (1.05-1.28), 1.10 (1.00-1.22), and 1.17 (1.04-1.31), respectively. Only LiAA mediated the association of various metabolites (lipids, fatty acids, histidine, and inflammatory biomarkers) with ASCVD, with the mediating proportion reaching up to 15% for the diameter of low-density lipoprotein (P=1.2×10-2). Regarding general aging, a 1-SD increase in GrimAA was associated with an average increase of 0.10 in the frailty index (P=2.0×10-3), and a 33% and 63% increased risk of prefrailty and frailty at baseline (P=1.5×10-2 and 5.8×10-2), respectively; this association was not observed with other clocks. GrimAA mediated the effect of various lipids, fatty acids, glucose, lactate, and inflammatory biomarkers on the frailty index, with the mediating proportion reaching up to 22% for triglycerides in very small-sized very low-density lipoprotein (P=6.0×10-3).

CONCLUSIONS

These findings suggest that epigenomic mechanisms may play a role in the associations between circulating metabolites and the aging process. Different mechanisms underlie the first and second generations of DNA methylation age in cardiovascular and general aging.

The Role of Paraclinical Investigations in Detecting Inflammation in Children and Adolescents with Obesity and Metabolic Syndrome

Obesity is linked to the increasing prevalence of metabolic syndrome (MetS), even among the pediatric population. Some inflammatory and cardioembolic indexes derived from routine laboratory tests have captivated the attention of the medical community.

OBJECTIVES

The aim of our study was to evaluate whether these markers are effective in distinguishing varying degrees of obesity and MetS in children and adolescents.

METHODS

We conducted a retrospective study. A total of 71 children and adolescents, aged between 6 and 16, were included in the study. Among them, 5 were overweight, 35 had obesity, and 31 had severe obesity. According to the NCEP ATP III criteria, 32 individuals had Metabolic Syndrome (MetS), while 39 did not have MetS.

RESULTS

The MetS positive group had higher values of TG/HDL-C (p < 0.001), TC/HDL-C (p < 0.001), MHR (p = 0.015), LHR (p = 0.001), NHR (p = 0.001), atherogenic index of plasma (p < 0.001), and PHR (p < 0.001). ESR, NLR, PLR, and SII did not progressively increase with the number of MetS criteria. The ROC curve analysis demonstrated that markers such as TG/HDL-C, the atherogenic index of plasma, TC/HDL-C, LHR, NHR, and PHR were effective in identifying MetS in children and adolescents with obesity.

CONCLUSIONS

In conclusion, we determined that some novel inflammatory and cardioembolic indexes are useful in assessing MetS and obesity in children and adolescents.

Assessing red blood cell distribution width in Vietnamese heart failure patients: A cross-sectional study

BACKGROUND

Heart failure (HF) is becoming a growing public health concern. Diagnostic tests for determining the severity of HF often come with high costs and require specialized expertise, which makes it difficult to assess HF severity, especially in low-income countries or at primary healthcare facilities. Recently, red blood cell distribution width (RDW) has emerged as a promising, easily accessible marker associated with HF severity. The study aimed to assess changes in RDW levels in HF patients and the diagnostic value of RDW in detecting acute heart failure (AHF) among HF patients.

METHODS

We conducted a cross-sectional examination involving 351 participants divided into HF and non-HF cohorts. HF was defined and categorized according to the diagnostic and treatment guidelines for AHF and chronic heart failure (CHF) set forth by the European Society of Cardiology (2021). Univariate and multivariate analysis of factors associated with AHF was performed.

RESULTS

The study revealed that HF patients displayed higher median RDW levels (14.90% [13.70-17.00]) compared to non-HF individuals (13.00% [12.23-13.78]). RDW was notably elevated in HF patients with left ventricular ejection fraction < 50% compared to those with left ventricular ejection fraction ≥ 50%. ROC curve analysis of RDW for AHF detection identified a cutoff value of 13.85%, with a sensitivity of 86.05% and specificity of 47.18%, statistically significant at p < 0.001. RDW > 13.85% was identified as an independent risk factor for AHF in patients with HF, with odds ratios of 2.644 (95% CI, 1.190-5.875; p = 0.017).

CONCLUSION

The study revealed significant RDW variations in patients with CHF and AHF compared to the control group. These findings suggest that RDW could be a biomarker for detecting HF severity.

Prediction of Osteoporotic Hip Fracture Outcome: Comparative Accuracy of 27 Immune-Inflammatory-Metabolic Markers and Related Conceptual Issues

Objectives: This study, based on the concept of immuno-inflammatory-metabolic (IIM) dysregulation, investigated and compared the prognostic impact of 27 indices at admission for prediction of postoperative myocardial injury (PMI) and/or hospital death in hip fracture (HF) patients. Methods: In consecutive HF patient (n = 1273, mean age 82.9 ± 8.7 years, 73.5% females) demographics, medical history, laboratory parameters, and outcomes were recorded prospectively. Multiple logistic regression and receiver-operating characteristic analyses (the area under the curve, AUC) were used to establish the predictive role for each biomarker. Results: Among 27 IIM biomarkers, 10 indices were significantly associated with development of PMI and 16 were indicative of a fatal outcome; in the subset of patients aged >80 years with ischaemic heart disease (IHD, the highest risk group: 90.2% of all deaths), the corresponding figures were 26 and 20. In the latter group, the five strongest preoperative predictors for PMI were anaemia (AUC 0.7879), monocyte/eosinophil ratio > 13.0 (AUC 0.7814), neutrophil/lymphocyte ratio > 7.5 (AUC 0.7784), eosinophil count < 1.1 × 109/L (AUC 0.7780), and neutrophil/albumin × 10 > 2.4 (AUC 0.7732); additionally, sensitivity was 83.1-75.4% and specificity was 82.1-75.0%. The highest predictors of in-hospital death were platelet/lymphocyte ratio > 280.0 (AUC 0.8390), lymphocyte/monocyte ratio < 1.1 (AUC 0.8375), albumin < 33 g/L (AUC 0.7889), red cell distribution width > 14.5% (AUC 0.7739), and anaemia (AUC 0.7604), sensitivity 88.2% and above, and specificity 85.1-79.3%. Internal validation confirmed the predictive value of the models. Conclusions: Comparison of 27 IIM indices in HF patients identified several simple, widely available, and inexpensive parameters highly predictive for PMI and/or in-hospital death. The applicability of IIM biomarkers to diagnose and predict risks for chronic diseases, including OP/OF, in the preclinical stages is discussed.

1 Million Segmented Red Blood Cells With 240 K Classified in 9 Shapes and 47 K Patches of 25 Manual Blood Smears

Around 20% of complete blood count samples necessitate visual review using light microscopes or digital pathology scanners. There is currently no technological alternative to the visual examination of red blood cells (RBCs) morphology/shapes. True/non-artifact teardrop-shaped RBCs and schistocytes/fragmented RBCs are commonly associated with serious medical conditions that could be fatal, increased ovalocytes are associated with almost all types of anemias. 25 distinct blood smears, each from a different patient, were manually prepared, stained, and then sorted into four groups. Each group underwent imaging using different cameras integrated into light microscopes with 40X microscopic lenses resulting in total 47 K + field images/patches. Two hematologists processed cell-by-cell to provide one million + segmented RBCs with their XYWH coordinates and classified 240 K + RBCs into nine shapes. This dataset (Elsafty_RBCs_for_AI) enables the development/testing of deep learning-based (DL) automation of RBCs morphology/shapes examination, including specific normalization of blood smear stains (different from histopathology stains), detection/counting, segmentation, and classification. Two codes are provided (Elsafty_Codes_for_AI), one for semi-automated image processing and another for training/testing of a DL-based image classifier.

A deep dive into burn-mediated ARDS severity assessment: a retrospective study on hematological markers

Acute Respiratory Distress Syndrome (ARDS) is a critical form of Acute Lung Injury (ALI), challenging clinical diagnosis and severity assessment. This study evaluates the potential utility of various hematological markers in burn-mediated ARDS, including Neutrophil-to-Lymphocyte Ratio (NLR), Mean Platelet Volume (MPV), MPV-to-Lymphocyte Ratio (MPVLR), Platelet count, and Platelet Distribution Width (PDW). Employing a retrospective analysis of data collected over 12 years, this study focuses on the relationship between these hematological markers and ARDS diagnosis and severity in hospitalized patients. The study establishes NLR as a reliable systemic inflammation marker associated with ARDS severity. Elevated MPV and MPVLR also emerged as significant markers correlating with adverse outcomes. These findings suggest these economical, routinely measured markers can enhance traditional clinical criteria, offering a more objective approach to ARDS diagnosis and severity assessment. Hematological markers such as NLR, MPV, MPVLR, Platelet count, and PDW could be invaluable in clinical settings for diagnosing and assessing ARDS severity. They offer a cost-effective, accessible means to improve diagnostic accuracy and patient stratification in ARDS. However, further prospective studies are necessary to confirm these findings and investigate their integration with other diagnostic tools in diverse clinical settings.

Serum albumin and white matter hyperintensities

People living with HIV and those diagnosed with alcohol use disorders (AUD) relative to healthy individuals commonly have low levels of serum albumin, substantiated as an independent predictor of cardiovascular events. White matter hyperintensities (WMH)-a neuroimaging feature of cerebral small vessel disease-are also related to cardiovascular disease. Despite consensus regarding associations between high levels of urine albumin and WMH prevalence, and low serum albumin levels and impaired cognitive functioning, relations between serum albumin and WMH burdens have rarely been evaluated. Here, a sample including 160 individuals with AUD, 142 living with HIV, and 102 healthy controls was used to test the hypothesis that serum albumin would be inversely related to WMH volumes and directly related to cognitive performance in the two diagnostic groups. Although serum albumin and periventricular WMH volumes showed an inverse relationship in both AUD and HIV groups, this relationship persisted only in the HIV group after consideration of traditional cardiovascular (i.e., age, sex, body mass index (BMI), nicotine use, hypertension, diabetes), study-relevant (i.e., race, socioeconomic status, hepatitis C virus status), and disease-specific (i.e., CD4 nadir, HIV viral load, HIV duration) factors. Further, serum albumin contributed more significantly than periventricular WMH volume to variance in performance on a verbal learning and memory composite score in the HIV group only. Relations in both HIV and AUD groups between albumin and hematological red blood cell markers (e.g., hemoglobin, hematocrit) suggest that in this sample, serum albumin reflects hematological abnormalities. Albumin, a simple serum biomarker available in most clinical settings, may therefore help identify periventricular WMH burden and performance levels in specific cognitive domains in people living with HIV. Whether serum albumin contributes mechanistically to periventricular WMH in HIV will require additional investigation.

Associations of CBC-Derived inflammatory indicators with sarcopenia and mortality in adults: evidence from Nhanes 1999 ∼ 2006

BACKGROUND

It has been proposed that inflammation plays a role in the development of sarcopenia. This study aimed to investigate the links of complete blood cell count (CBC) parameters and CBC-derived inflammatory indicators with sarcopenia and mortality.

METHODS

Data pertaining to sarcopenia were extracted from the 1999-2006 National Health and Nutrition Examination Survey (NHANES), and mortality events were ascertained through the National Death Index up to December 31, 2019. The CBC-derived inflammatory indicators assessed in this study included the neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), monocyte-to-lymphocyte ratio (MLR), neutrophil-monocyte to lymphocyte ratio (NMLR), systemic inflammatory response index (SIRI), and systemic immune-inflammation index (SII). The prognostic significance of these CBC-derived inflammatory indicators was evaluated using the random survival forests (RSF) analysis.

RESULTS

The study encompassed a cohort of 12,689 individuals, among whom 1,725 were diagnosed with sarcopenia. Among individuals with sarcopenia, 782 experienced all-cause mortality, and 195 succumbed to cardiovascular causes. Following adjustment for confounding variables, it was observed that elevated levels of NLR, dNLR, NMLR, SIRI, and SII were associated with an increased prevalence of sarcopenia. Among participants with sarcopenia, those in the highest quartile of NLR (HR = 1.336 [1.095-1.631]), dNLR (HR = 1.274 [1.046-1.550]), MLR (HR = 1.619 [1.290-2.032]), NMLR (HR = 1.390 [1.132-1.707]), and SIRI (HR = 1.501 [1.210-1.862]) exhibited an elevated risk of all-cause mortality compared to those in the lowest quartile of these inflammation-derived indicators. These associations were similarly observed in cardiovascular mortality (HR = 1.874 [1.169-3.003] for MLR, HR = 1.838 [1.175-2.878] for SIRI). The RSF analysis indicated that MLR exhibited the highest predictive power for both all-cause and cardiovascular mortality among individuals with sarcopenia.

CONCLUSIONS

Our findings underscore the association between CBC-derived inflammatory indicators and mortality in adults with sarcopenia. Of note, MLR emerged as the most robust predictor of all-cause and cardiovascular mortality in this population.

Optimizing Dual Antiplatelet Therapy in the Perioperative Period for Spine Surgery After Recent Percutaneous Coronary Intervention: A Comprehensive Review, Synthesis, and Catalyst for Protocol Formulation

The increased incidence of spine surgery within the past decade has highlighted the importance of robust perioperative management to improve patient outcomes overall. Coronary artery disease is a common medical comorbidity present in the population of individuals who receive surgery for spinal pathology that is often treated with dual antiplatelet therapy (DAPT) after percutaneous coronary intervention. Discontinuation of DAPT before surgical intervention is typically indicated; however, contradictory evidence exists in the literature regarding the timing of DAPT use and discontinuation in the perioperative period. We review the most recent cardiac and spine literature on the intricacies of percutaneous coronary intervention and its associated risks in the postoperative period. We further propose protocols for DAPT use after both elective and urgent spine surgery to optimize perioperative care.

Biology and functions of fish thrombocytes: A review

This comprehensive review examines the role of fish thrombocytes, cells considered functionally analogous to platelets in terms of coagulation, but which differ in their origin and morphology. Despite the evolutionary distance between teleosts and mammals, genomic studies reveal conserved patterns in blood coagulation, although there are exceptions such as the absence of factors belonging to the contact system. Beyond coagulation, fish thrombocytes have important immunological functions. These cells express both proinflammatory genes and genes involved in antigen presentation, suggesting a role in both innate and adaptive immune responses. Moreover, having demonstrated their phagocytic abilities, crucial in the fight against pathogenic microorganisms, underscores their multifaceted involvement in immunity. Finally, the need for further research on the functions of these cells is highlighted, in order to better understand their involvement in maintaining the health of aquaculture fish. The use of standardized and automated methods for the analysis of these activities is advocated, emphaiszing their potential to facilitate the early detection of stress or infection, thus minimizing the economic losses that these adverse situations can generate in the field of aquaculture.

A prediction model of elderly hip fracture mortality including preoperative red cell distribution width constructed based on the random survival forest (RSF) and Cox risk ratio regression

An independent correlation between pre-RDW and 1-year mortality after surgery in elderly hip fracture can be used to predict mortality in elderly hip fracture patients and has predictive significance in anemia patients. With further research, a treatment algorithm can be developed to potentially identify patients at high risk of preoperative mortality.

INTRODUCTION

Red blood cell distribution width (RDW) is an independent predictor of various disease states in elderly individuals, but its association with the prognosis of elderly hip fracture patients is controversial. This study aimed to evaluate the prognostic value of RDW in such patients, construct a prediction model containing RDW using random survival forest (RSF) and Cox regression analysis, and compare RDW in patients with and without anemia.

METHODS

We retrospectively analyzed the data of elderly patients who underwent hip fracture surgery, selected the best variables using RSF, stratified the independent variables by Cox regression analysis, constructed a 1-year mortality prediction model of elderly hip fracture with RDW, and conducted internal validation and external validation.

RESULTS

Two thousand one hundred six patients were included in this study. The RSF algorithm selects 12 important influencing factors, and Cox regression analysis showed that eight variables including preoperative RDW (pre-RDW) were independent risk factors for death within 1-year after hip fracture surgery in elderly patients. Stratified analysis showed that pre-RDW was still independently associated with 1-year mortality in the non-anemia group and not in the anemia group. The nomogram prediction model had high differentiation and fit, and the prediction model constructed by the total cohort of patients was also used for validation of patients in the anemia patients and obtained good clinical benefits.

CONCLUSION

An independent correlation between pre-RDW and 1-year mortality after surgery in elderly hip fracture can be used to predict mortality in elderly hip fracture patients and has predictive significance in anemia patients.

Association Between Red Blood Cell Distribution Width and Coronary Calcification in Patients Referred for Invasive Coronary Angiography

This study aimed to determine whether red cell distribution width (RDW) is associated with coronary calcification. A total of 4796 patients who underwent coronary computed tomography angiography and subsequent invasive coronary angiography were consecutively enrolled. Coronary artery calcium score (CACS), demographic, clinical, and laboratory data were collected from electronic medical records. RDW were expressed in two forms, as a coefficient of variation (CV) or as a standard deviation (SD). Multivariable ordinal logistic regression was used to investigate the association of RDW with CACS grades (CACS 0-99, 100-399, 400-999, and >1000). A significant association was found between elevated RDW-SD and higher CACS grades after full adjustment (adjusted OR per 1-SD increase: 1.11, 95% CI: 1.05-1.18; P < .001), while no significant association was found between RDW-CV and CACS grades. When RDW-SD was analyzed as a categorical variable, it was primarily the 4th quartile of RDW-SD that was associated with elevated CACS grades compared with the 1st quartile (adjusted OR: 1.25, 95% CI: 1.07-1.46; P = .006), while the 2nd and 3rd quartiles showed no significantly higher risk. RDW-SD is a more robust biomarker for coronary calcification compared with RDW-CV.

Association between biomarkers of inflammation and dyslipidemia in drug resistant tuberculosis in Uganda

BACKGROUND

Active tuberculosis (TB) significantly increases the risk of cardiovascular disease, but the underlying mechanisms remain unclear. This study aimed to investigate the association between inflammation biomarkers and dyslipidemia in patients with drug-resistant TB (DR-TB).

METHODS

This was a secondary analysis of data from a cross-sectional multi-center study in Uganda conducted 2021. Participants underwent anthropometric measurements and laboratory tests included a lipid profile, full haemogram and serology for HIV infection. Dyslipidemia was defined as total cholesterol > 5.0 mmol/l and/or low-density lipoprotein cholesterol > 4.14 mmol/l, and/or triglycerides (TG) ≥ 1.7 mmol/l, and/or high density lipoprotein cholesterol (HDL-c) < 1.03 mmol/l for men and < 1.29 mmol/l for women. Biomarkers of inflammation were leukocyte, neutrophil, lymphocyte, monocyte, and platelet counts, as well as neutrophil/lymphocyte (NLR), platelet/lymphocyte, and lymphocyte/monocyte (LMR) ratios, mean corpuscular volume (MCV), and the systemic immune inflammation index (SII) (neutrophil × platelet/lymphocyte). Modified Poisson Regression analysis was used for determining the association of the biomarkers and dyslipidemia.

RESULTS

Of 171 participants, 118 (69.0%) were co-infected with HIV. The prevalence of dyslipidemia was 70.2% (120/171) with low HDL-c (40.4%, 69/171) and hypertriglyceridemia (22.5%, 38/169) being the most common components. Patients with dyslipidemia had significantly higher lymphocyte (P = 0.008), monocyte (P < 0.001), and platelet counts (P = 0.014) in addition to a lower MCV (P < 0.001) than those without dyslipidemia. Further, patients with dyslipidemia had lower leucocyte (P < 0.001) and neutrophil (P = 0.001) counts, NLR (P = 0.008), LMR (P = 0.006), and SII (P = 0.049). The MCV was inversely associated with low HDL-C (adjusted prevalence ratio (aPR) = 0.97, 95% CI 0.94-0.99, P = 0.023) but was positively associated with hypertriglyceridemia (aPR = 1.04, 95% CI 1.00-1.08, P = 0.052).

CONCLUSIONS

Individuals with dyslipidemia exhibited elevated lymphocyte, monocyte, and platelet counts compared to those without. However, only MCV demonstrated an independent association with specific components of dyslipidemia. There is need for further scientific inquiry into the potential impact of dyslipidemia on red cell morphology and a pro-thrombotic state among patients with TB.

Classification and Explanation of Iron Deficiency Anemia from Complete Blood Count Data Using Machine Learning

Background: Currently, discriminating Iron Deficiency Anemia (IDA) from other anemia requires an expensive test (serum ferritin). Complete Blood Count (CBC) tests are less costly and more widely available. Machine learning models have not yet been applied to discriminating IDA but do well for similar tasks. Methods: We constructed multiple machine learning methods to classify IDA from CBC data using a US NHANES dataset of over 19,000 instances, calculating accuracy, precision, recall, and precision AUC (PR AUC). We validated the results using an unseen dataset from Kenya, using the same model. We calculated ranked feature importance to explain the global behavior of the model. Results: Our model classifies IDA with a PR AUC of 0.87 and recall/sensitivity of 0.98 and 0.89 for the original dataset and an unseen Kenya dataset, respectively. The explanations indicate that low blood level of hemoglobin, higher age, and higher Red Blood Cell distribution width were most critical. We also found that optimization made only minor changes to the explanations and that the features used remained consistent with professional practice. Conclusions: The overall high performance and consistency of the results suggest that the approach would be acceptable to health professionals and would support enhancements to current automated CBC analyzers.

Effect of Neutrophil-to-Lymphocyte Ratio on Post-TAVR Mortality and Periprocedural Pulmonary Hypertension

Aims

To evaluate the impact of neutrophil-to-lymphocyte ratio (NLR) on periprocedural pulmonary hypertension (PH) and 3-month all-cause mortality in patients with aortic stenosis (AS) who underwent transcatheter aortic valve replacement (TAVR) and to develop a nomogram for predicting the mortality for these patients.

Methods and Results

124 patients undergoing TAVR were categorized into three groups according to systolic pulmonary artery pressure (sPAP): Group I (no PH, n = 61) consisted of patients with no pre- and post-TAVR PH; Group II (improved PH, n = 35) consisted of patients with post-TAVR systolic pulmonary artery pressure (sPAP) decreased by more than 10 mmHg compared to pre-TAVR levels; and Group III (persistent PH, n = 28) consisted of patients with post-TAVR sPAP no decrease or less than 10 mmHg, or new-onset PH after the TAVR procedure. The risk of all-cause mortality within 3 months tended to be higher in Group II (11.4%) and Group III (14.3%) compared to Group I (3.3%) (P=0.057). The multinomial logistic regression analysis demonstrated a positive correlation between NLR and both improved PH (OR: 1.182, 95% CI: 1.036-1.350, P=0.013) and persistent PH (OR: 1.181, 95% CI: 1.032-1.352, P=0.016). Kaplan-Meier analysis revealed a significant association between higher NLR and increased 3-month all-cause mortality (16.1% vs. 3.1% in lower NLR group, P=0.021). The multivariable Cox regression analysis confirmed that NLR was an independent predictor for all-cause mortality within 3 months, even after adjusting for clinical confounders. A nomogram incorporating five factors (BNP, heart rate, serum total bilirubin, NLR, and comorbidity with coronary heart disease) was developed. ROC analysis was performed to discriminate the ability of the nomogram, and the AUC was 0.926 (95% CI: 0.850-1.000, P < 0.001).

Conclusions

Patients with higher baseline NLR were found to be at an increased risk of periprocedural PH and all-cause mortality within 3 months after TAVR.

Serum albumin and white matter hyperintensities

Urine albumin, high in kidney disease, predicts cardiovascular incidents and CNS white matter hyperintensity (WMH) burdens. Serum albumin - a more general biomarker which can be low in several disorders - including kidney and liver disease, malnutrition, and inflammation - also predicts cardiovascular events and is associated with cognitive impairment in several clinical populations; relations between serum albumin and WMH prevalence, however, have rarely been evaluated. In a sample of 160 individuals with alcohol use disorder (AUD), 142 infected with HIV, and 102 healthy controls, the hypothesis was tested that lower serum albumin levels would predict larger WMH volumes and worse cognitive performance irrespective of diagnosis. After considering traditional cardiovascular risk factors (e.g., age, sex, body mass index (BMI), nicotine use, hypertension, diabetes) and study-relevant variables (i.e., primary diagnoses, race, socioeconomic status, hepatitis C virus status), serum albumin survived false discovery rate (FDR)-correction in contributing variance to larger periventricular but not deep WMH volumes. This relationship was salient in the AUD and HIV groups, but not the control group. In secondary analyses, serum albumin and periventricular WMH along with age, sex, diagnoses, BMI, and hypertension were considered for hierarchical contribution to variance in performance in 4 cognitive domains. Albumin survived FDR-correction for significantly contributing to visual and verbal learning and memory performance after accounting for diagnosis. Relations between albumin and markers of liver integrity [e.g., aspartate transaminase (AST)] and blood status (e.g., hemoglobin, red blood cell count, red cell distribution width) suggest that in this sample, albumin reflects both liver dysfunction and hematological abnormalities. The current results suggest that albumin, a simple serum biomarker available in most clinical settings, can predict variance in periventricular WMH volumes and performance in visual and verbal learning and memory cognitive domains. Whether serum albumin contributes mechanistically to periventricular WMH prevalence will require additional investigation.

Association of Leukocyte, Erythrocyte, and Platelet Counts with Metabolic Syndrome and Its Components in Young Individuals without Overt Signs of Inflammation: A Cross-Sectional Study

The presence of metabolic syndrome (MetS) increases the risk of developing type 2 diabetes, cardiovascular diseases, and mortality. MetS is associated with increased leukocyte or erythrocyte counts. In 16- to 20-year-old males (n = 1188) and females (n = 1231) without signs of overt inflammation, we studied whether the presence of MetS and its components results in elevated blood cell counts. The leukocyte, erythrocyte, and thrombocyte counts significantly but weakly correlated with the continuous MetS score, MetS components, uric acid, and C-reactive protein levels both in males (r = -0.09 to 0.2; p < 0.01) and females (r = -0.08 to 0.2; p < 0.05). Subjects with MetS had higher leukocyte (males: 6.2 ± 1.3 vs. 6.9 ± 1.2 × 109/L; females 6.6 ± 1.5 vs. 7.5 ± 1.6 × 109/L; p < 0.001), erythrocyte (males: 5.1 ± 0.3 vs. 5.3 ± 0.3 × 1012/L; females: 4.5 ± 0.3 vs. 4.8 ± 0.3 × 1012/L; p < 0.001), and platelet counts (males: 245 ± 48 vs. 261 ± 47 × 109/L; females: 274 ± 56 vs. 288 ± 74 × 109/L; p < 0.05) than those without MetS. With the exception of platelet counts in females, the blood counts increased with the number of manifested MetS components. Phenotypes with the highest average leukocyte, erythrocyte, or platelet counts differed between sexes, and their prevalence was low (males: 0.3% to 3.9%; females: 1.2% to 2.7%). Whether functional changes in blood elements accompany MetS and whether the increase in blood counts within the reference ranges represents a risk for future manifestation of cardiometabolic diseases remain unanswered.

A COMPREHENSIVE EVALUATION OF HEMOGRAM-DERIVED INFLAMMATORY INDICES IN HASHIMOTO THYROIDITIS AND NON-IMMUNOGENIC HYPOTHYROIDISM

OBJECTIVES

The objective of this study was to evaluate the Systemic Inflammation Index (SII), Platelet to Lymphocyte Ratio (PLR), and Neutrophil to Lymphocyte Ratio (NLR) in HT and NIH, as well as their diagnostic value to predict the presence of inflammation.

SUBJECTS AND METHODS

The study included 505 patients, including 190 healthy controls, 166 euthyroid Hashimoto's thyroiditis (HT), 91 hypothyroid HT, and 58 non- immunogenic hypothyroidism (NIH) patients. The records of the patients in each group were reviewed retrospectively.

RESULTS

In terms of SII, there was a significant difference between the control and patient groups (p<0.001). PLR and NLR values were also found to be significantly higher in the patient group (p<0.001 and p=0.007, respectively). When euthyroid HT, hypothyroid HT, and NIH subgroups were compared to the control group, there was a significant difference in SII, PLR (for all p<0.001), but not in NLR (p=0.059). SII, PLR, and NLR were not different between the subgroups (p=0.595, p=0.861, and p=0.777, respectively).

CONCLUSIONS

It was found that the PLR, NLR, and SII indices were higher in Hashimoto's thyroiditis and non-immunogenic hypothyroidism. Of these indices, SII was the most powerful marker to predict the presence of inflammation.

Relapsing polychondritis: focus on cardiac involvement

Background

Relapsing polychondritis (RP) with cardiac involvement may present with acute cardiovascular events, and may be associated with a negative prognosis. Herein, we analyzed the clinical characteristics of RP patients with cardiac involvement.

Method

RP patients, hospitalized from December 2005 to December 2021 at Peking Union Medical College Hospital (PUMCH), were screened. Univariate and multivariate logistic regression analyses were used to statistically analyze the clinical characteristics of these patients.

Results

The incidence of cardiac involvement in inpatients with RP was 24.1%. Univariate logistic regression analysis revealed age, central nervous system (CNS) involvement, neutrophil-to-lymphocyte ratio (NLR) > 6.41, and disease duration > 4 years as risk factors for cardiac involvement in RP. Conversely, the incidence of tracheobronchial and chest wall involvement was significantly lower in the group with cardiac involvement. Multivariate logistic regression confirmed that age, CNS involvement, NLR > 6.41, and disease duration > 4 years were independent factors for cardiac involvement. Subsequently, we identified five well-defined clinical patterns of RP, based on the involvement of different organs in our patients, and found that the heart-brain model was significantly mutually exclusive with the airway model.

Conclusion

Occurrence of cardiac involvement in RP is associated with age, CNS involvement, NLR, and disease duration. It is mutually exclusive with airway-related involvement. Regular echocardiography and electrocardiography are necessary for patients with RP.

The Role Played by Novel Inflammatory Markers in Assessment of Peripheral Artery Disease

Background and Objectives: Atherosclerosis is a multifactorial process in which inflammatory markers have both therapeutic and prognostic roles. Recent studies bring into question the importance of assessing new inflammatory markers in relation to the severity of peripheral artery disease (PAD), such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-C-reactive protein ratio (LCR). Materials and Methods: We conducted a retrospective and descriptive study including 652 patients with PAD, who were divided into two groups according to the severity of the ankle-brachial index value: mild and moderate obstruction (257 patients) and severe obstruction (395 patients). We evaluated demographics, anthropometric data and clinical and paraclinical parameters in relation to the novel inflammatory biomarkers mentioned above. Results: Weight (p = 0.048), smoking (p = 0.033), the number of cardiovascular risk factors (p = 0.041), NLR (p = 0.037), LCR (p = 0.041) and PLR (p = 0.019), the presence of gangrene (p = 0.001) and the number of lesions detected via peripheral angiography (p < 0.001) were statistically significant parameters in our study. For the group of patients with severe obstruction, all three inflammatory biomarkers were statistically significantly correlated with a serum low-density lipoprotein-cholesterol level, the number of cardiovascular risk factors, rest pain, gangrene and a risk of amputation. In addition, directly proportional relationships were found between NLR, PLR and the number of stenotic lesions (p = 0.018, p = 0.016). Also, NLR (area under the curve = 0.682, p = 0.010) and PLR (AUC = 0.692, p = 0.006) were predictors associated with a high risk of amputation in patients with an ABI < 0.5. Conclusions: in our study, we demonstrated the importance of assessing inflammatory markers in relation to the presence of cardiovascular risk factors through the therapeutic and prognostic value demonstrated in PAD.

Incorporating inflammatory biomarkers into a prognostic risk score in patients with non-ischemic heart failure: a machine learning approach

Objectives

Inflammation is involved in the mechanisms of non-ischemic heart failure (NIHF). We aimed to investigate the prognostic value of 21 inflammatory biomarkers and construct a biomarker risk score to improve risk prediction for patients with NIHF.

Methods

Patients diagnosed with NIHF without infection during hospitalization were included. The primary outcome was defined as all-cause mortality and heart transplantations. We used elastic net Cox regression with cross-validation to select inflammatory biomarkers and construct the best biomarker risk score model. Discrimination, calibration, and reclassification were evaluated to assess the predictive value of the biomarker risk score.

Results

Of 1,250 patients included (median age, 53 years, 31.9% women), 436 patients (34.9%) experienced the primary outcome during a median of 2.8 years of follow-up. The final biomarker risk score included high-sensitivity C-reactive protein-to-albumin ratio (CAR) and red blood cell distribution width-standard deviation (RDW-SD), both of which were 100% selected in 1,000 times cross-validation folds. Incorporating the biomarker risk score into the best basic model improved the discrimination (ΔC-index = 0.012, 95% CI 0.003-0.018) and reclassification (IDI, 2.3%, 95% CI 0.7%-4.9%; NRI, 17.3% 95% CI 6.4%-32.3%) in risk identification. In the cross-validation sets, the mean time-dependent AUC ranged from 0.670 to 0.724 for the biomarker risk score and 0.705 to 0.804 for the basic model with a biomarker risk score, from 1 to 8 years. In multivariable Cox regression, the biomarker risk score was independently associated with the outcome in patients with NIHF (HR 1.76, 95% CI 1.49-2.08, p < 0.001, per 1 score increase).

Conclusions

An inflammatory biomarker-derived risk score significantly improved prognosis prediction and risk stratification, providing potential individualized therapeutic targets for NIHF patients.

Predictive association of gut microbiome and NLR in anemic low middle-income population of Odisha- a cross-sectional study

Background

Iron is abundant on earth but not readily available for colonizing bacteria due to its low solubility in the human body. Hosts and microbiota compete fiercely for iron. <15% Supplemented Iron is absorbed in the small bowel, and the remaining iron is a source of dysbiosis. The gut microbiome signatures to the level of predicting anemia among low-middle-income populations are unknown. The present study was conducted to identify gut microbiome signatures that have predictive potential in association with Neutrophil to lymphocytes ratio (NLR) and Mean corpuscular volume (MCV) in anemia.

Methods

One hundred and four participants between 10 and 70 years were recruited from Odisha's Low Middle-Income (LMI) rural population. Hematological parameters such as Hemoglobin (HGB), NLR, and MCV were measured, and NLR was categorized using percentiles. The microbiome signatures were analyzed from 61 anemic and 43 non-anemic participants using 16 s rRNA sequencing, followed by the Bioinformatics analysis performed to identify the diversity, correlations, and indicator species. The Multi-Layered Perceptron Neural Network (MLPNN) model were applied to predict anemia.

Results

Significant microbiome diversity among anemic participants was observed between the lower, middle, and upper Quartile NLR groups. For anemic participants with NLR in the lower quartile, alpha indices indicated bacterial overgrowth, and consistently, we identified R. faecis and B. uniformis were predominating. Using ROC analysis, R. faecis had better distinction (AUC = 0.803) to predict anemia with lower NLR. In contrast, E. biforme and H. parainfluenzae were indicators of the NLR in the middle and upper quartile, respectively. While in Non-anemic participants with low MCV, the bacterial alteration was inversely related to gender. Furthermore, our Multi-Layered Perceptron Neural Network (MLPNN) models also provided 89% accuracy in predicting Anemic or Non-Anemic from the top 20 OTUs, HGB level, NLR, MCV, and indicator species.

Conclusion

These findings strongly associate anemic hematological parameters and microbiome. Such predictive association between the gut microbiome and NLR could be further evaluated and utilized to design precision nutrition models and to predict Iron supplementation and dietary intervention responses in both community and clinical settings.

Association of inflammation indices with left atrial thrombus in patients with valvular atrial fibrillation

BACKGROUND

Inflammation has been implicated in the progressive exacerbation of valvular atrial fibrillation (VAF) and thrombogenesis. This study aimed to analyze the association of systemic inflammation as measured by six indices with left atrial thrombus (LAT) in patients with VAF.

METHODS

This comparative cross-sectional analytical study included 434 patients with VAF. Logistic regression analysis was used to assess the predictive value of LAT using six inflammation indices: neutrophil-to-lymphocyte ratio, monocyte-to-lymphocyte ratio (MLR), white blood cell-to-mean platelet volume ratio, neutrophil-to-mean platelet volume ratio, systemic immune inflammation index, and systemic inflammation response index. Receiver operating characteristic curves were plotted, and the area under these curves (AUC) were calculated to evaluate the discriminative ability of the indices.

RESULTS

Transesophageal echocardiography revealed LAT in 143 (32.9%) patients. All six indices reflected a positive correlation with C-reactive protein levels. Multivariate logistic analysis revealed that these indices were independent predictors of LAT, and MLR appeared to perform best (odds ratio 12.006 [95% confidence interval (CI) 3.404-42.347]; P < 0.001; AUC 0.639 [95% CI 0.583-0.694]; P < 0.001).

CONCLUSIONS

Selected inflammatory indices were significantly and independently associated with LAT among patients with VAF.

The Value of Peripheral Blood Cell Ratios in Primary Membranous Nephropathy: A Single Center Retrospective Study

Background

Primary membranous nephropathy (PMN) is a common cause of nephrotic syndrome in adults. Forty percent of the patients continue to progress and eventually develop into chronic renal failure. Although phospholipase A2 receptor (PLA2R) is the major antigen of PMN, the clinical features do not often parallel with the antibody titers. Therefore, it is significant to find relative credible markers to predict the treatment response.

Methods

One hundred and eighteen PMN patients were recruited. The response to treatment was defined as ALB≥30g/L at 6 months and complete remission (CR) or not at the end of the follow-up. Renal outcome endpoint was defined as 50% or more Cr increase at the end.

Results

The patients with poor treatment effects had numerically higher platelet-lymphocytes ratio (PLR). For patients with CR or not, the difference was near to statistic significant (P=0.095). When analyzing CR or not, the fitting of the binary logistic regression model including both PLA2R Ab titer and PLR (Hosmer-Lemeshow test: χ ²=8.328, P = 0.402; OR (PLA2R Ab titer) = 1.002 (95% CI 1.000-1.004, P = 0.042); OR (PLR) = 1.006 (95% CI 0.999-1.013, P = 0.098)) was markedly better than that with only PLA2R Ab titer (Hosmer-Lemeshow test: χ ²=13.885, P = 0.016). The patients with renal function deterioration showed significantly higher monocyte-lymphocyte ratio (MLR) (0.26 (0.22-0.31) vs 0.18 (0.13-0.22), P = 0.012).

Conclusion

PMN patients with poor treatment response tended to have higher PLR at the time of renal biopsy, and a higher MLR was associated with poor renal outcomes. Our findings suggested that PLR and MLR might be used to predict treatment efficacy and prognosis for PMN patients, respectively.

Correlation of White Blood Cell, Neutrophils, and Hemoglobin with Metabolic Syndrome and Its Components

Background

Metabolic syndrome (MetS) is a global health problem. White blood cell (WBC), neutrophils and neutrophil-to-lymphocyte ratio (NLR) are valid indicators involved in acute and chronic inflammation. The aims of our study were to analyze the correlation and severity of these indicators with MetS and its components, and explore the diagnostic value of their combined tests for MetS.

Methods

A total of 7726 subjects were recruited, and laboratory biomarkers were collected. The differences of indicators between MetS group and non-MetS group were analyzed. The linear trend between each indicator and the increasing number of metabolic disorders was analyzed using trend variance test. The correlation between each indicator and MetS with its components was analyzed by logistic regression.

Results

The levels of WBC, neutrophil, and hemoglobin grew significantly in the MetS group compared to non-MetS group, and gradually increased with the increased number of MetS disorders. Logistic regression analysis indicated significant correlations between WBC, neutrophils, and hemoglobin with MetS and its components. ROC curve analysis showed WBC, neutrophils, and hemoglobin served as good predictors for MetS, especially in adults aged under 40.

Conclusion

Our study indicated that WBC, neutrophils, and hemoglobin are efficient indicators for predicting MetS and evaluate its severity.