Red Cell Distribution Width Research Articles

Integration of clinical and blood parameters in risk prognostication for patients receiving immunochemotherapy for extensive stage small cell lung cancer: real-world data from two centers

BackgroundImmune checkpoint inhibitors (ICIs) had modest advances in the treatment of extensive-stage small cell lung cancer (ES-SCLC) in clinical trials, but there is a lack of biomarkers for prognosis in clinical practice.MethodsWe retrospectively collected data from ES-SCLC patients who received ICIs combined chemotherapy from two centers in China, integrated clinical and blood parameters, and constructed risk prognostication for immunochemotherapy. The population was divided into high- and low-risk groups, and the performance of the model was assessed separately in the training and validation cohorts.ResultsTwo hundred and twenty and 43 patients were included in the training and validation groups, respectively. The important predictors were screened including body mass index, liver metastases, coefficient variation of red blood cell distribution width, lactate dehydrogenase, albumin, and C-reactive protein. Predicting 1-year overall survival (OS), the AUC values under ROC for the model under training, internal validation, and external validation were 0.760, 0.732, and 0.722, respectively, and the calibration curve and clinical decision curve performed well. Applied the model to divide patients into low-risk and high-risk groups, and the median OS was 23.7 months and 9.1 months, and the median progression-free survival was 8.2 months and 4.8 months, respectively; furthermore, this ability to discriminate survival was also observed in the validation cohort.ConclusionsWe constructed a novel prognostic model for ES-SCLC to predict survival employing baseline tumor burden, nutritional and inflammatory parameters, it is easily measured to screen high-risk patient populations.

The long-term impact of increased red blood cell distribution width detected during hospitalization for heart failure.

Aim: We determined the long-term role of increased RDW (red blood cell distribution width) detected during cardiac decompensation.Methods: We followed 3697 patients [mean age 71.4years (±SD 10.1), 59.1% males] hospitalized for acute heart failure (HF) and assessed the five-year all-cause mortality risk associated with tertiles of RDW.Results: Patients with RDW in the top tertile showed roughly twofold higher 5-year mortality risk than those in the bottom tertile. The association remained significant not only after adjustments for potential covariates but even if we excluded patients who deceased during the first year of follow-up [HRR 1.76 (95% CIs:1.42-2.18), p<0.0001].Conclusion: The high degree of anisocytosis represents an independent predictor of poor prognosis in HF patients, even long-term after an acute manifestation.

Hematologic Indices and Chronic Subdural Hematoma: A Single-Center Cohort Study

Abstract Objective Chronic subdural hematoma (cSDH) is common, predominantly affects the elderly, often recurs after treatment, and can have serious complications, including death. Inflammation plays an important role in cSDH and it has been previously shown that some laboratory indices are useful as prognostic markers. The aim was to research the role of hematologic and inflammatory markers in cSDH. Materials and Methods A single-center archival database review to retrieve data on cSDH cases operated on between 2018 and 2020, including: (1) sociodemography (age, gender), (2) clinics (Glasgow Coma Score [GCS], anticoagulants, chronic conditions), (3) laboratory (leukocyte, neutrophil, platelet, C-reactive protein, hemoglobin, red cell distribution width [RDW], neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio [PLR], systemic immune-inflammatory index [SII]), (4) cSDH (size, location, midline shift), and (5) treatment (craniotomy/craniostomy, drainage). Primary outcome was Glasgow Outcome Score (GOS) at discharge and at 1 year, and secondary outcomes were 1 year mortality, resurgery, and recurrence. Hematological and inflammatory indices were compared across two cSDH thickness groups. Results Seventy-two patients were included, 25 women and 47 men, median age 77 years. Seventeen (23.6%) patients had chronic anticoagulant treatment. The majority had a chronic comorbidity: 19 (26.4%) diabetes, 48 (66.7%) hypertension, and 56 (77.8%) other chronic diseases. Median preoperative GCS was 15. Median cSDH thickness was 22.9 mm, sidedness was equally distributed, and midline shift occurred in 60 (83.3 %) patients, with median midline shift of 8.4 mm. The majority of patients underwent a single craniostomy (n = 44, 61.1%), and in all patients a subdural drainage was placed. Median GOS at discharge and at 1 year postoperatively was 5. Mortality was 11.1%, and 16.7% of patients were lost to follow-up. Within the 1-year follow-up, 27.8% of patients had disease recurrence, 25% underwent a repeat surgery. In the “above” versus “below” 15 mm cSDH thickness group there were significant differences in P count (211.5 vs. 279.5 × 109/L, p = 0.009), RDW (13.3 vs. 12.6, p = 0.031), SII (1782 vs. 2653, p = 0.025), and PLR (26.2 vs. 36.7, p = 0.042). Conclusion Hematological indices bear a diagnostic and prognostic potential in cSDH management.

A stacked machine learning-based classification model for endometriosis and adenomyosis: a retrospective cohort study utilizing peripheral blood and coagulation markers.

Endometriosis (EMs) and adenomyosis (AD) are common gynecological diseases that impact women's health, and they share symptoms such as dysmenorrhea, chronic pain, and infertility, which adversely affect women's quality of life. Current diagnostic approaches for EMs and AD involve invasive surgical procedures, and thus, methods of noninvasive differentiation between EMs and AD are needed. This retrospective cohort study introduces a novel, noninvasive classification methodology employing a stacked ensemble machine learning (ML) model that utilizes peripheral blood and coagulation markers to distinguish between EMs and AD. The study included a total of 558 patients (329 with EMs and 229 with AD), in whom key hematological and coagulation markers were analyzed to identify distinctive profiles. Feature selection was conducted through ML (logistic regression, support vector machine, and K-nearest neighbors) to determine significant hematological markers. Red cell distribution width, mean corpuscular hemoglobin concentration, activated partial thromboplastin time, international normalized ratio, and antithrombin III were proved to be the key distinguishing indexes for disease differentiation. Among all the ML classification models developed, the stacked ensemble model demonstrated superior performance (area under the curve = 0.803, 95% credibility interval = 0.701-0.904). Our findings demonstrate the effectiveness of the stacked ensemble ML model for classifying EMs and AD. Integrating biomarkers into this multi-algorithm framework offers a novel approach to noninvasive diagnosis. These results advocate for the application of stacked ensemble ML utilizing cost-effective and readily available peripheral blood and coagulation indicators for the early, rapid, and noninvasive differential diagnosis of EMs and AD, offering a potentially transformative approach for clinical decision-making and personalized treatment strategies.

Development and validation of nomograms for predicting cardiovascular disease risk in patients with prediabetes and diabetes

This study aimed to develop and validate distinct nomogram models for assessing CVD risk in individuals with prediabetes and diabetes. In a cross-sectional study design, we examined data from 2294 prediabetes and 1037 diabetics who participated in the National Health and Nutrition Examination Survey, which was conducted in the United States of America between 2007 and 2018. The dataset was randomly divided into training and validation cohorts at a ratio of 0.75–0.25. The Boruta feature selection method was used in the training cohort to identify optimal predictors for CVD diagnosis. A web-based dynamic nomogram was developed using the selected features, which were validated in the validation cohort. The Hosmer–Lemeshow test was performed to assess the nomogram's stability and performance. Receiver operating characteristics and calibration curves were used to assess the effectiveness of the nomogram. The clinical applicability of the nomogram was evaluated using decision curve analysis and clinical impact curves. In the prediabetes cohort, the CVD risk prediction nomogram included nine risk factors: age, smoking status, platelet/lymphocyte ratio, platelet count, white blood cell count, red cell distribution width, lactate dehydrogenase level, sleep disorder, and hypertension. In the diabetes cohort, the CVD risk prediction nomogram included eleven risk factors: age, material status, smoking status, systemic inflammatory response index, neutrophil-to-lymphocyte ratio, red cell distribution width, lactate dehydrogenase, high-density lipoprotein cholesterol, sleep disorder, hypertension, and physical activity. The nomogram models developed in this study have good predictive and discriminant utility for predicting CVD risk in patients with prediabetes and diabetes.

A nomogram for predicting short-term mortality in ICU patients with coexisting chronic obstructive pulmonary disease and congestive heart failure

ObjectiveThis study aimed to develop and validate a nomogram for predicting 28-day and 90-day mortality in intensive care unit (ICU) patients who have chronic obstructive pulmonary disease (COPD) coexisting with congestive heart failure (CHF). MethodsAn extensive analysis was conducted on clinical data from the Medical Information Mart for Intensive Care IV database, covering patients over 18 years old with both COPD and CHF, who were were first-time ICU admissions between 2008 and 2019. The least absolute shrinkage and selection operator (LASSO) regression method was employed to screen clinical features, with the final model being optimized using backward stepwise regression guided by the Akaike Information Criterion (AIC) to construct the nomogram. The predictive model's discrimination and clinical applicability were evaluated via receiver operating characteristic (ROC) curves, calibration curves, the C-index, and decision curve analysi s (DCA). ResultsThis analysis was comprised of a total of 1948 patients. Patients were separated into developing and validation cohorts in a 7:3 ratio, with similar baseline characteristics between the two groups. The ICU mortality rates for the developing and verification cohorts were 20.8 % and 19.5 % at 28 days, respectively, and 29.4 % and 28.3 % at 90 days, respectively. The clinical characteristics retained by the backward stepwise regression include age, weight, systolic blood pressure (SBP), respiratory rate (RR), oxygen saturation (SpO2), red blood cell distribution width (RDW), lactate, partial thrombosis time (PTT), race, marital status, type 2 diabetes mellitus (T2DM), malignant cancer, acute kidney failure (AKF), pneumonia, immunosuppressive drugs, antiplatelet agents, vasoactive agents, acute physiology score III (APS III), Oxford acute severity of illness score (OASIS), and Charlson comorbidity index (CCI). We developed two separate models by assigning weighted scores to each independent risk factor: nomogram A excludes CCI but includes age, T2DM, and malignant cancer, while nomogram B includes only CCI, without age, T2DM, and malignant cancer. Based on the results of the AUC and C-index, this study selected nomogram A, which demonstrated better predictive performance, for subsequent validation. The calibration curve, C-index, and DCA results indicate that nomogram A has good accuracy in predicting short-term mortality and demonstrates better discriminative ability than commonly used clinical scoring systems, making it more suitable for clinical application. ConclusionThe nomogram developed in this study offers an effective assessment of short-term mortality risk for ICU patients with COPD and CHF, proving to be a superior tool for predicting their short-term prognosis.

EVALUATION OF HEMATOLOGICAL PARAMETERS AND DIAGNOSTIC SIGNIFICANCE IN H. PYLORI INFECTION: A COMPARATIVE STUDY

Helicobacter pylori (H. pylori) infection is globally recognized for its role in various gastrointestinal diseases and extra gastric conditions, including hematological anomalies. Understanding the correlation between H. pylori infection and hematological parameters could provide insights into its broader health impacts. Objective: This study evaluated the correlation between H. pylori infection and various demographic, socioeconomic, and hematological parameters. Methods: A cross-sectional study enrolled patients diagnosed with H. pylori and a matched control group without the infection. Blood samples were collected and analyzed for hematological parameters, including white blood cell count, red blood cell count, hemoglobin (HGB), hematocrit (HCT), platelet count, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and red cell distribution width (RDW). Statistical analyses were performed using t-tests and chi-square tests where appropriate, with significance set at p &lt; 0.05. Results: The study included patients with statistically significant differences in hematological parameters between the H. pylori-infected and healthy groups. Notably, the infected group showed lower mean HGB (12.41±1.38 g/dl vs. 14.32±1.46 g/dl), RBC count (4.12±0.62x10^6/µL vs. 4.87±0.53x10^6/µL), and HCT (39.17±3.87% vs. 44.52±4.51%), and higher RDW (13.51±2.10% vs. 13.87±1.32%) compared to the control group (all p &lt; 0.05). Conclusion: The findings indicate significant hematological changes associated with H. pylori infection, suggesting a potential impact on the overall health status of affected individuals. These results highlight the importance of considering H. pylori infection in the differential diagnosis of hematological abnormalities and underscore the need for further research to explore the underlying mechanisms and potential therapeutic interventions.

Value of the red blood cell distribution width (RDW) and neutrophil lymphocyte ratio (NLR) in the prediction of functional recovery and 3-month mortality following endovascular treatment for acute anterior circulation ischemic stroke

ObjectivesThe red blood cell distribution width (RDW) and neutrophil to lymphocyte ratio (NLR) have been linked to poor prognosis in patients with ischaemic stroke. However, no study has yet evaluated the prognostic role of RDW and NLR, or their combined effect on reperfusion in patients with endovascularly-treated acute ischaemic stroke. This study therefore aimed to analyse the impact of RDW and NLR on poor functional outcomes and failed reperfusion following endovascular treatment in patients with acute anterior circulation ischaemic stroke. MethodsA total of 275 patients with acute anterior circulation ischaemic stroke treated endovascularly between 2015 and 2018 were enrolled in this study. The relationships between RDW, NLR, and poor outcomes were analysed using univariate and multivariate logistic regression models and receiver operating characteristic (ROC) curve analysis. The Youden Index was applied to determine the cut-off value. ResultsMultivariate logistic regression analysis identified RDW (p = 0.015) and NLR (p = 0.015) as independent predictors of mortality at the 3rd month. ROC curve analysis of RDW revealed a cutoff value of 14.25 (p = 0.009) for poor clinical outcomes (modified Rankin scale [mRS] 3–6). Similarly, a cutoff value of 14.25 was found for mortality prediction (p = 0.003). The cutoff value for poor clinical outcome (mRS 3–6) in the NLR was determined as 5.93 (p = 0.003), whereas the cutoff value for mortality was set at 5.17 (p = 0.028). RDW also predicted failed reperfusion, with a cutoff value of 17.75 (p = 0.048). ConclusionsHigh RDW and NLR upon admission were identified as independent indicators of mortality in endovascularly treated acute anterior circulation ischemic stroke patients. Furthermore, the RDW could potentially predict failed reperfusion.

Red blood cell distribution width as a surrogate biomarker of damage and disease activity in patients with systemic lupus erythematosus.

Red blood cell distribution width (RDW) is a measure of variability in mean corpuscular volume. Alterations in RDW can be observed in a variety of human disorders, including inflammatory, cardiovascular, and hepatic or renal diseases. Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that can affect virtually any organ in the body. In this work, our objective was to analyse how a complete characterisation of disease characteristics in a large series of patients with SLE is related to RDW values. 284 patients with SLE and 181 age- and sex-matched healthy controls were recruited. Complete blood count including RDW was assessed. Multivariable analysis was performed to analyse the relationship between RDW and SLE disease characteristics, including composite scores of disease activity and damage. After multivariable adjustment, RDW was higher in patients with SLE compared to controls (beta coefficient 0.8 [95% confidence interval: 0.3-1] %, p=0.003). Several disease characteristics, such as the presence of extractable nuclear antibodies and antiphospholipid syndrome, and the use of prednisone and azathioprine, were significantly associated with higher levels of RDW after adjustment for confounders. Of note, cumulative disease damage and disease activity scores were associated with higher RDW values after controlling for covariates. RDW may serve as a surrogate biomarker of accrual disease damage and activity in patients with SLE.

Association Between Red Cell Distribution Width and Liver Injury after Cardiac and Aortic Aneurysm Surgery with Cardiopulmonary Bypass

This study aimed to investigate the association between preoperative red blood cell distribution width (RDW) levels and liver injury (LI) after cardiac surgery, to highlight RDW's usefulness in the early identification and intervention for patients at high risk of LI. A retrospective observational study. A university-affiliated teaching hospital and tertiary referral center. Adult patients who underwent cardiac and aortic aneurysm surgery at Changhai Hospital in 2021. Postoperative LI was defined by increased liver enzyme levels and/or hyperbilirubinemia, noted from the time of surgery to discharge. Logistic regression analyses were conducted to examine the RDW-LI relationship, with stratified analyses based on age, gender, and anemia. Survival within 30 days was assessed using the Kaplan-Meier method, with survival curve differences analyzed via the log-rank test. The study included 3 sets of sensitivity analyses. Postoperative LI was observed in 75 patients (10%). Multivariate regression analysis showed a significant association between high RDW levels and postoperative LI (adjusted odds ratio, 3.25; p = 0.033; 95% confidence intefal, 1.10-9.63), even after adjusting for all covariates. This association remained consistent across 3 sets of sensitivity analyses. Subgroup analysis showed men had a higher correlation with LI (p for interaction = 0.041). Kaplan-Meier analysis indicated a significantly lower survival rate in the LI group (76%) compared with the non-LI group (99.6%; p < 0.001). Preoperative RDW levels are significantly associated with postoperative LI. RDW could serve as a significant useful marker for early detection and intervention in patients at high risk of LI, thereby potentially improving patient outcomes.

Optimizing the Diagnosis of Microcytic Hypochromic Anemia: A Comparative Evaluation of Erythrocyte and Reticulocyte Parameters.

Background Anemia is a widespread, worldwide hematological disorder, with iron deficiency anemia (IDA) and thalassemia trait (TT) being two frequently encountered forms. For effective management, it is vital to distinguish between these two conditions. Existing diagnostic methods have some limitations due to their inaccessibility and high cost. This study aims to evaluate novel hematological indices for distinguishing IDA from TT, offering potential improvements in diagnostic accuracy and patient care. Objective To compare the efficacy of novel hematological indices in differentiating IDA from TT, and to assess their sensitivity and specificity in clinical practice. Methods This cross-sectional observational study included 80 anemia patients (40 diagnosed cases of IDA and 40 of TT each). Hematological parameters were measured using the Sysmex XN-1000 analyzer (Sysmex Corporation, Kobe, Japan), and statistical analysis was conducted using the Mann-Whitney test, Pearson correlation coefficient (r), and correlation matrix. Results Significant differences were observed between IDA and TT patients in the indices studied. The Green and King Index demonstrated high diagnostic accuracy, with a sensitivity of 90% and specificity of 82%. The red cell distribution width (RDW) Index exhibited similar diagnostic performance, with a sensitivity of 90% and specificity of 77%. The England and Fraser Index showed a sensitivity of 85% and specificity of 80%, with a large effect size (r = -0.60). The correlation matrix revealed strong associations between key parameters, including a negative correlation between hemoglobin and RDWIndex (r = -0.61) and a positive correlation between mean corpuscular volume (MCV) and Shine and Lal Index (r = 0.82). On the other hand, our study found that indices like Shine and Lal and Srivastava had limited diagnostic value, with smaller effect sizes (r = 0.28 and r = -0.005, respectively). Conclusion Hematological indices, such as the Green and King, RDW, and England and Fraser indices, show strong potential for differentiating IDA from TT, with high sensitivity, specificity, and large effect sizes. The correlation matrix further supports the diagnostic utility of these indices. These tools can enhance diagnostic precision in resource-limited settings and improve patient outcomes.

Red cell distribution width/albumin ratio and mortality risk in rheumatoid arthritis patients: Insights from a NHANES study.

Despite the established negative regulatory effects observed in various diseases like cardiovascular disease and diabetes, the distinct impact of red cell distribution width (RDW) to albumin ratio (RAR) on mortality within the realm of rheumatoid arthritis (RA) remains obscure. This study sought to explore the relationship between RAR and mortality in RA patients. A cohort of 2151 adults with RA from the National Health and Nutrition Examination Survey (NHANES) spanning 2003-2016 was analyzed for RAR levels derived from red cell distribution width and albumin concentrations. Utilizing Cox regression analysis, Kaplan-Meier curves, and Restricted Cubic Spline (RCS) models, we assessed the association between RAR levels and RA mortality while adjusting for potential confounding variables. Participants with higher RAR had a twofold to threefold increased risk of all-cause (HR = 3.10, 95% CI: 2.26-4.24) and cardiovascular mortality (HR = 2.46, 95%CI: 1.26-4.79) versus lower RAR. Kaplan-Meier analysis revealed that the higher RAR group had a significantly lower survival rate compared to the lower RAR group for both all-cause and cardiovascular mortality (both p < .0001), with a more pronounced effect observed for all-cause mortality. Furthermore, the RCS-fitted Cox regression model illustrated a nonlinear positive correlation between RAR levels and RA mortality. Overall, a higher RAR was associated with an increased risk mortality in RA patients. These findings underscore the potential of RAR as a prognostic biomarker in predicting outcomes in RA.

Determination of the Relationship between Red Cell Distribution Width, NT-proBNP and cTnT in Acute Myocardial Infarction Patients

Determination of the Relationship between Red Cell Distribution Width, NT-proBNP and cTnT in Acute Myocardial Infarction Patients

A Predictive Nomogram of In-Hospital Mortality After 48 h for Atrial Fibrillation Patients in the Coronary Care Unit.

Patients with atrial fibrillation (AF) suffer a higher risk of death, and it is necessary to develop prediction tools for mortality risk in critically ill patients with AF. This study aimed to develop a novel predictive nomogram of in-hospital mortality after 48 h in the coronary care unit (CCU) for patients with AF. We collected information on CCU patients with AF from the "Medical Information Mart for Intensive Care-III" database and developed a nomogram model for predicting the all-cause mortality risk after 48 h in the hospital. Key variables were selected by univariate logistic and least absolute shrinkage and selection operator regression. The independent predictors with p < 0.05 were screened out by multivariate logistic regression. A predictive nomogram was constructed using these independent predictors, and the model calibration and discrimination were evaluated. This study finally enrolled 1248 CCU patients with AF, and the in-hospital mortality was 17% (209/1248). The predictive nomogram was constructed by 13 selected independent predictors, including age, smoking status, acute kidney injury, chronic obstructive pulmonary disease, ventricular arrhythmia, shock, urea, red cell distribution width, leucocytosis, continuous renal replacement therapy, continuous positive airway pressure, anticoagulation, and heart rate. The area under the curve of the nomogram was 0.803 (95% confidence interval 0.771-0.835). The nomogram was verified to have good accuracy and calibration. This study developed a novel nomogram containing age, acute kidney injury, and heart rate that can be a good predictor of potential in-hospital mortality after 48 h in CCU patients with AF.

Analysis of clinical characteristics of patients with pulmonary hypertension in Chaya County, Chamdo, Tibet.

Pulmonary hypertension (PH) is a critical health issue marked by high blood pressure in the pulmonary arteries, with limited data on its clinical characteristics in the Tibetan population. The objective of this study was to examine the clinical characteristics of PH patients among Tibetan population residing in Chaya County, Changdu, Tibet. This was a retrospective cross-sectional study. A total of 94 PH patients diagnosed via echocardiography at the Internal Medicine Department of Chaya County People's Hospital in Changdu (Tibet, China) between March 2019 and October 2020 were included. Additionally, 52 non-PH inpatients were selected as the control group. Patient medical records were reviewed for demographic and clinical data, lab results, and echocardiographic findings. Student's t-test/chi-squared test between PH and control group, one-way analysis of variance (ANOVA) among control and PH subgroups, Pearson's and Spearman's correlation coefficient were used to analysis the results. Out of 1,689 inpatients in the Internal Medicine Department, 94 were identified as PH patients for analysis. The average hemoglobin level among PH patients (150.64±21.67 g/L) was similar to that observed in the normal population (146.65±17.51 g/L) at high altitude (P=0.28). Abnormal liver function indexes were observed, with 51.06% of PH patients exhibiting hyperuricemia (P<0.001 compared to control's 15.38%). The PH group demonstrated significantly elevated red blood cell distribution width (RDW)-standard deviation (50.59±6.49 vs. 43.67±3.40 fL, P<0.001) and RDW-coefficient of variation of (16.18%±3.04% vs. 13.52%±1.32%, P<0.001), along with a decreased platelet level compared to the control group [(202.55±73.67) vs. (256.63±72.85) ×109/L]. Furthermore, echocardiographic indicators related to right heart function showed correlations with red blood cell count, bilirubin, albumin, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol (multiple significant correlation coefficient r, magnitude from 0.22 to 0.54). Chronic pulmonary disease and left heart disease were identified as common etiologies of PH among Tibetan patients residing in high-altitude regions. The Tibetan population residing in high-altitude regions and diagnosed with PH displayed abnormal changes in numerous liver functional and metabolic indices, which were correlated with the morphological indices observed via cardiac ultrasound.

Machine Learning Models for Predicting Mortality in Patients with Cirrhosis and Acute Upper Gastrointestinal Bleeding at an Emergency Department: A Retrospective Cohort Study.

Cirrhosis is a major global cause of mortality, and upper gastrointestinal (GI) bleeding significantly increases the mortality risk in these patients. Although scoring systems such as the Child-Pugh score and the Model for End-stage Liver Disease evaluate the severity of cirrhosis, none of these systems specifically target the risk of mortality in patients with upper GI bleeding. In this study, we constructed machine learning (ML) models for predicting mortality in patients with cirrhosis and upper GI bleeding, particularly in emergency settings, to achieve early intervention and improve outcomes. In this retrospective study, we analyzed the electronic health records of adult patients with cirrhosis who presented at an emergency department (ED) with GI bleeding between 2001 and 2019. Data were divided into training and testing sets at a ratio of 90:10. The ability of three ML models-a linear regression model, an XGBoost (XGB) model, and a three-layer neural network model-to predict mortality in the patients was evaluated. A total of 16,025 patients with cirrhosis and 32,826 ED visits for upper GI bleeding were included in the study. The in-hospital and ED mortality rates were 11.2% and 2.2%, respectively. The XGB model exhibited the highest performance in predicting both in-hospital and ED mortality (area under the receiver operating characteristic curve: 0.866 and 0.861, respectively). International normalized ratio, renal function, red blood cell distribution width, age, and white blood cell count were the strongest predictors in all the ML models. The median ED length of stay for the ED mortality group was 17.54 h (7.16-40.01 h). ML models can be used to predict mortality in patients with cirrhosis and upper GI bleeding. Of the three models, the XGB model exhibits the highest performance. Further research is required to determine the actual efficacy of our ML models in clinical settings.

A Study on relationship between Red Cell Distribution Width and HighDensity Lipoprotein-Cholesterol in patients with Acute coronary syndrome in a tertiary care hospital

Introduction: Acute coronary syndrome is a spectrum of disease consisting of ST segment elevated myocardial infarction (STEMI), non-ST segment elevated myocardial infarction (NSTEMI) and unstable angina where the blood flow to the heart is decreased. According to WHO, India contributes to one-fifth of the world's deaths due to cardiovascular disease. In recent times, the RDW has been used as a helpful marker in the diagnosis and prognosis of patients with acute coronary syndrome. However, the relationship between RDW, HDL-C, and ACS has yet to be identified properly. Aim: To evaluate the association between HDL-C levels and the RDW among patients with ACS and to find its association with the various socio-demographic factors of the patient. Methods: This hospital-based cross-sectional study was conducted in a tertiary care hospital in Puducherry between October 2023 and February 2024. Patients aged more than 18 with a diagnosis of acute coronary syndrome were included in the study. All the patients were subjected to a complete history followed by laboratory investigations, including the RDW, HDL-C, and troponin-I. Results: A total of 62 patients participated in the study. The mean age of the patients with ACS was found to be 55.6 + 3.4 years. The study didn’t show any association between the age (p=0.753), gender (p=0.897), residence (p=0.517), Type-2 DM (p=-.924), hypertension (p=0.615), dyslipidemia (p=0.302), smoking (p=0.565), alcohol (p=0.593), ACS type (p=0.714), Troponin-I (p=0.916), HDL-C (p=0.517) and RBS (p=0.078) with the level of the RDW. However, the study showed a significant association between BMI and RDW levels (p&lt;0.001), and there is a significant and negative correlation was noted between the RDW and HDL-C levels (p=0.038). Conclusion: The study showed a significant and negative correlation between the HDL-C and the RDW among patients with acute coronary syndrome. The study recommends that the RDW be used as an additional marker in predicting the risk of ACS and diagnosing patients with ACS. Keywords: acute coronary syndrome, RDW, HDL-C, demographic factors.

The relationship between hemoglobin to red cell distribution width (RDW) ratio (HRR) and prognosis in patients with acute coronary syndrome

Aims: The use of hematological parameters in the prognostic assessment of acute coronary syndrome (ACS) has become common in recent years. Thus, our study aimed to evaluate the relationship between hemoglobin to red cell distribution width (RDW) ratio (HRR) and prognosis of these patients. Methods: A retrospective evaluation was conducted on patients who presented to the emergency department between 01.09.2023 and 01.04.2024 and received a diagnosis of ACS. HRR was determined by dividing the hemoglobin concentration by the red cell distribution width (RDW). The patients were categorized into two groups based on their HRR values: high HRR patients and low HRR patients, using a specified HRR cut-off value. Statistical comparisons were conducted on all parameters between the two patient groups. The variables potentially linked to mortality were analyzed using receiver operating characteristic (ROC) analysis. Results: The in-hospital mortality rate, vasopressor needs, and MV support requirements were significantly higher in the low HRR (≤0.828) group than in the high HRR (&gt;0.828) group (p

Analysis of ultrasound coronary parameters and blood red cell distribution width and N-terminal pro-brain natriuretic peptide concentrations following coronary lesions in children with Kawasaki disease.

Aims/Background Kawasaki disease is an acute inflammatory condition primarily affecting the young children. It can lead to coronary artery abnormalities, which can worsen the prognosis. Early diagnosis of coronary disease is crucial for the effective treatment and the prognosis evaluation. To explore the clinical significance of ultrasound examination characteristics, peripheral blood red cell distribution width, and changes in N-terminal pro-brain natriuretic peptide levels for the early detect coronary artery abnormality in children with Kawasaki disease. Methods The case-control study was conducted. 85 Kawasaki disease patients diagnosed in our hospital from January 2020 to December 2023 were selected as the Kawasaki disease group. 100 healthy children who received physical examination in the Department of Child Healthcare during the same period were selected as control group. The cardiac ultrasound indicators, erythrocyte sedimentation rate, C-reactive protein, white blood cell, neutrophil percentage, platelet count, D-dimer, red cell distribution width, N-terminal pro-brain natriuretic peptide of two groups were compared. The Kawasaki disease group was further divided into the coronary artery lesion group and the non-coronary artery lesion group based on whether coronary artery lesions occurred in the Kawasaki disease patients. The differences of above indicators were compared. Results The left main coronary artery, left anterior descending branch, and right coronary artery Z-scores of the Kawasaki disease group were all higher than those of the control group (p < 0.05). There was no significant difference in left ventricular ejection fraction between Kawasaki disease group and control group (p > 0.05). The erythrocyte sedimentation rate, C-reactive protein, neutrophil percentage, platelet count, D-dimer, red cell distribution width, and N-terminal pro-brain natriuretic peptide of Kawasaki disease group were all higher than those of control group (p < 0.05). The left main coronary artery, left anterior descending branch, and right coronary artery Z-scores of Kawasaki disease patients with coronary artery lesions were all higher than those of Kawasaki disease patients without coronary artery lesions (p < 0.05). The left ventricular ejection fraction of Kawasaki disease patients with coronary artery lesions was lower than that of Kawasaki disease patients without coronary artery lesions (p < 0.05). The erythrocyte sedimentation rate, C-reactive protein, white blood cell, neutrophil percentage, platelet count, D-dimer, red cell distribution width, and N-terminal pro-brain natriuretic peptide of Kawasaki disease patients with coronary artery lesions were all higher than those of Kawasaki disease patients without coronary artery lesions, and the differences were statistically significant (p < 0.05). After treatment, the left main coronary artery, left anterior descending branch, and right coronary artery Z-scores of Kawasaki disease patients with coronary artery lesions significantly decreased (p < 0.05), and the left ventricular ejection fraction significantly increased (p < 0.05). The erythrocyte sedimentation rate, C-reactive protein, white blood cell, neutrophil percentage, platelet count, D-dimer, red cell distribution width, and N-terminal pro-brain natriuretic peptide of Kawasaki disease patients with or without coronary artery lesions significantly decreased after treatment compared with before treatment in the same group (p < 0.05). Conclusion Kawasaki disease patients with coronary artery lesions exhibit significantly increased coronary artery vessel diameter, as well as elevated red cell distribution width and N-terminal pro-brain natriuretic peptide concentration. The combined use of ultrasound combined with red cell distribution width and N-terminal pro-brain natriuretic peptide examination can assist in determining whether Kawasaki disease patients have coronary artery lesions and assessing the clinical treatment effect.

Prognostic value of hemoglobin to red blood cell distribution width ratio in pancreatic ductal adenocarcinoma: a retrospective study

BackgroundPrevious studies have identified the hemoglobin (Hb) to red blood cell distribution width (RDW) ratio (HRR) is associated with the prognosis of a variety of malignant tumors. However, the relationship between HRR and pancreatic ductal adenocarcinoma (PDAC) prognosis remains unexplored. This study aims to ascertain the prognostic significance of HRR in PDAC patients.MethodsIn a retrospective analysis, 128 PDAC patients undergoing initial surgical resection at Ningbo Medical Center Lihuili Hospital between January 2016 and September 2021 were included. Based on receiver operating characteristic curve-derived cut-off values, participants were categorized into low and high HRR groups. The correlation between HRR and patient prognosis was subsequently examined.ResultsSignificant disparities in age, Hb levels, RDW, tumor locality, surgical intervention, and postoperative chemotherapy were observed between the two groups (P < 0.05). Notably, the low HRR cohort exhibited inferior disease-free survival (DFS) and overall survival (OS) rates (P = 0.002 for both). Univariate analysis indicated that male gender, adjacent tissue invasion, TNM stages III/IV, non-O blood types, low HRR, and lack of postoperative chemotherapy were linked to adverse DFS and OS outcomes (P < 0.05). Multivariate analysis further delineated low HRR as an independent predictor of poor DFS and OS outcomes (HR: 1.520, 95% CI: 1.028–2.247, P = 0.036; HR: 1.537, 95% CI: 1.034–2.284, P = 0.034, respectively).ConclusionOur findings suggest that a lower HRR is indicative of poorer DFS and OS in PDAC patients, underscoring its potential utility as a prognostic biomarker for this population.