Higher Red Blood Cell Distribution Research Articles

Accounting for Red Cell Distribution Width Improves Risk Stratification by Commonly Used Mortality/Deterioration Risk Scores in Adult Patients Hospitalized Due to COVID-19.

Higher red blood cell distribution width (RDW) levels have gained attention in the prognostication of many chronic metabolic and malignant diseases, as well as coronavirus disease 2019 (COVID-19). We aimed to evaluate whether accounting for RDW might contribute to risk stratification when added to commonly used risk scoring systems in adult COVID-19 patients. We retrospectively analyzed a cohort of 3212 non-critical COVID-19 patients hospitalized in a tertiary-level institution from March 2020 to June 2021. Admission RDW values were considered normal if they were ≤14.5% in males or ≤16.1% in females. The Modified Early Warning Score (MEWS), International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium score (ISARIC 4C), and Veterans Health Administration COVID-19 (VACO) index were evaluated as prognostic scores. RDW exceeded the upper limit in 628 (19.6%) of the patients. When RDW was accounted for, risks of the predicted outcomes were considerably different within the same MEWS, 4C score, and VACO index levels. The same patterns applied equally to patients who started, and those who did not start, remdesivir before deterioration. RDW may be a useful tool for stratifying risk when considered on top of commonly used prognostic scores in non-critical COVID-19 patients.

Prognostic value of red blood cell distribution width to albumin ratio for predicting mortality in adult patients meeting sepsis-3 criteria in intensive care units

BackgroundPatients with sepsis with low albumin levels and high red blood cell distribution width levels have poor prognoses. Red blood cell distribution width to albumin ratio (RAR) has recently attracted attention as an innovative inflammation biomarker. We aimed to explore the association between RAR and the prognosis of patients with sepsis.MethodsThis retrospective observational study included 402 patients meeting the sepsis-3 standards admitted to Yantai Yuhuangding Hospital’s intensive care units (ICUs) between January 2020 and December 2022. The relationship between RAR and mortality in patients with sepsis was examined using regression analysis, Kaplan–Meier analyses, and a receiver operating characteristic curve. Subgroup and sensitivity analyses were conducted to assess the results’ robustness.ResultsRAR, when considered as a continuous variable, was a significant independent in-hospital mortality risk factor (adjusted odds ratio [OR]: 1.383; 95% confidence interval [CI]: 1.164–1.645; P < 0.001). When considering RAR as a categorical variable, the ORs (95% CIs) of hospital mortality for quartile 2 (Q2), Q3, and Q4 compared with Q1 were 1.027 (0.413–2.551), 3.632 (1.579–8.354), and 4.175 (1.625–10.729), respectively, P < 0.001. Similar outcomes were observed for 28- and 90-day mortalities.ConclusionsRAR may indicate clinical prognosis for patients with sepsis in the ICU, potentially providing a low-cost, easily repeatable, and accessible biomarker for risk categorization for these patients.

A positive association between RDW and coronary heart disease in the rheumatoid arthritis population: A cross-sectional study from NHANES.

Previous research has indicated that higher red blood cell distribution width (RDW) increases the risk of coronary heart disease. However, no studies have established a link between RDW and coronary heart disease in the rheumatoid arthritis population. This research aims to explore the association between RDW and coronary heart disease among individuals with rheumatoid arthritis. We selected demographic data, laboratory data, lifestyle, and medical history from the National Health and Nutrition Examination Survey (NHANES), specifically including age, gender, poverty, RDW, race, BMI, diabetes, education, coronary heart disease, hypertension, cholesterol, smoking, and drinking. RDW and coronary heart disease were found to have a positive association in the rheumatoid arthritis population (OR = 1.145, 95%CI: 1.036-1.266, P = .0098), even after adjusting for factors such as age, gender, race, education level, smoking, and drinking. Subgroup analysis showed a stronger positive association, particularly in individuals aged 55-66 years, males, and the Hispanic White population with diabetes or hypercholesterolemia. There is a significant correlation between RDW and coronary heart disease among individuals with rheumatoid arthritis.

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.

Is Red Cell Distribution Width Correlated with Mortality in Geriatric Patients Undergoing Hip Fracture Surgery: A Prospective Observational Study

Introduction: Our study aimed to determine the impact of preoperative red blood cell distribution width on length of intensive care unit and hospital stays, and short- and long-term mortality in elderly patients undergoing hip fracture surgery. Materials and Method: This prospective cohort study included 414 patients aged 65 and older who presented with hip fractures between November 2021 and November 2022. Patients’ demographic characteristics, American Society of Anesthesiologists score, Revised Cardiac Risk Index, comorbidities, and preoperative complete blood counts (hemoglobin, red blood cell distribution width, platelet count, etc.) were recorded at the preoperative visit. Length of intensive care unit and hospital stays were documented postoperatively. Patients were followed for one year after surgery in terms of mortality. Results: Patients with high red blood cell distribution width levels (≥14.25%) were older, had more comorbidities, and had higher American Society of Anesthesiologists score and Revised Cardiac Risk Index scores (p&lt;0.001). In the high red blood cell distribution width group, length of hospital stays was longer (p&lt;0.001). There was no significant difference between red blood cell distribution width groups in terms of intensive care unit stay duration and readmissions (p=0.304 and p=0.664, respectively). According to the multivariate logistic regression analysis, an red blood cell distribution width of ≥14.25 was found to increase the risk of 30-day mortality by 4.7 times and 1-year mortality by 2.74 times. Conclusion: Red blood cell distribution width is a useful, practical, and cost-effective indicator of short- and long-term mortality in elderly patients undergoing hip fracture surgery. Keywords: Aged; Anemia; Hip fracture; Mortality.

High red blood cell distribution width attenuates the effectiveness of Immune checkpoint inhibitor therapy: An exploratory study using a clinical data warehouse.

Immune checkpoint inhibitors (ICIs) have improved outcomes in cancer treatment but are also associated with adverse events and financial burdens. Identifying accurate biomarkers is crucial for determining which patients are likely to benefit from ICIs. Current markers, such as PD-L1 expression and tumor mutation burden, exhibit limited predictive accuracy. This study utilizes a Clinical Data Warehouse (CDW) to explore the prognostic significance of novel blood-based factors, such as the neutrophil-to-lymphocyte ratio and red cell distribution width (RDW), to enhance the prediction of ICI therapy benefit. This retrospective study utilized an exploratory cohort from the CDW that included a variety of cancers to explore factors associated with pembrolizumab treatment duration, validated in a non-small cell lung cancer (NSCLC) patient cohort from electronic medical records (EMR) and CDW. The CDW contained anonymized data on demographics, diagnoses, medications, and tests for cancer patients treated with ICIs between 2017-2022. Logistic regression identified factors predicting ≤2 or ≥5 pembrolizumab doses as proxies for progression-free survival (PFS), and Receiver Operating Characteristic analysis was used to examine their predictive ability. These factors were validated by correlating doses with PFS in the EMR cohort and re-testing their significance in the CDW cohort with other ICIs. This dual approach utilized the CDW for discovery and EMR/CDW cohorts for validating prognostic biomarkers before ICI treatment. A total of 609 cases (428 in the exploratory cohort and 181 in the validation cohort) from CDW and 44 cases from EMR were selected for study. CDW analysis revealed that elevated red cell distribution width (RDW) correlated with receiving ≤2 pembrolizumab doses (p = 0.0008), with an AUC of 0.60 for predicting treatment duration. RDW's correlation with PFS (r = 0.80, p<0.0001) and its weak association with RDW (r = -0.30, p = 0.049) were confirmed in the EMR cohort. RDW also remained significant in predicting short treatment duration across various ICIs (p = 0.0081). This dual methodology verified pretreatment RDW elevation as a prognostic biomarker for shortened ICI therapy. This study suggests the utility of CDWs in identifying prognostic biomarkers for ICI therapy in cancer treatment. Elevated RDW before treatment initiation emerged as a potential biomarker of shorter therapy duration.

Dual nature of ferritin for hematologic, liver functional, and metabolic parameters in older diabetic patients

This study explored the association between ferritin with hematologic, liver functional, and metabolic parameters in older diabetic patients. A total of 210 diabetic patients aged 65 or older were classified into four groups according to the reference range of serum ferritin. Demographic variables and health-related lifestyle factors were obtained through the utilization of a standardized questionnaire. Anthropometric measures, blood pressure, hematology test, and biochemical assessment were also performed. Among all patients, 29.5% had anemia. The percentage of anemia in groups low ferritin (< 40 μg/L), lower side within the reference range (40–120 μg/L), higher side within the reference range (121–200 μg/L), and high ferritin levels (> 200 μg/L) were 50.0, 27.7, 20.5, and 24.2% (P = 0.025), respectively. Low ferritin levels had a higher risk of anemia and a high red blood cell distribution width (RDW). High ferritin levels were associated with a higher risk of high glutamate pyruvate transaminase, obesity, high fasting blood glucose (FBG), and high postprandial blood glucose. The higher side within the reference range of ferritin also showed a higher risk of high FBG and high glycated hemoglobin. Nevertheless, there was no significant association between ferritin and inflammation marker, serum lipids or blood pressure. Overall, ferritin demonstrates a dual nature in older diabetic patients: low ferritin levels are linked to anemia or elevated RDW, while high levels are linked to obesity, increased liver enzymes, and worse glycemia control.

Survival and prognosis analysis of systemic lupus erythematosus patients with pulmonary hypertension: A systematic review and meta-analysis.

The study aimed to evaluate survival rates and prognosis in systemic lupus erythematosus (SLE) patients with pulmonary hypertension (PH) using meta-analysis. PubMed, EMBASE, Cochrane central register of controlled trials, China National Knowledge Infrastructure, China Science and Technology Journal Database, Wan-Fang Database, and Chinese biomedical database were searched. Information and data were screened and extracted by 2 researchers. The obtained data were analyzed using the R software meta package. Quality assessment was conducted using Newcastle-Ottawa Scale. The causes of heterogeneity were analyzed using subgroup analysis and sensitivity analysis. Publication bias was evaluated using Begger funnel plots and Egger test. The search strategy yielded a total of 21 studies involving 875 patients included in the final analysis. The pooled 1-, 3- and 5-year survival rates of patients with SLE-PH were 0.9020 (95%CI: 0.8576; 0.9397), 0.8363 (96%CI: 0.7813; 0.8852), 0.7301 (95%CI: 0.6327; 0.8181). The 1-, 3- and 5-year survival rates of echocardiography subgroup were 0.9000 (95%CI: 0.8480; 0.9551), 0.8435 (95%CI: 0.7744; 0.9187), 0.6795 (95%CI: 0.5746; 0.8035), respectively; and there were 0.9174 (95%CI: 0.8951; 0.9402), 0.8529 (95%CI: 0.8255; 0.8812), 0.7757 (95%CI: 0.7409; 0.8121) at right heart catheterization subgroup in the meantime. Multivariate analysis for predicting mortality in SLE-PH patients revealed that diminishing left ventricular ejection fraction, New York Heart Association classification, lupus nephritis, lower cardiac index, and higher red blood cell distribution width level were significantly associated with a higher mortality rate. Treatment with huge doses of cyclophosphamide, tricuspid annular plane systolic excursion/pulmonary artery systolic pressure, and Raynaud phenomenon signaled favorable outcomes. The 1-, 3-, and 5-year survival rates of SLE-PH patients in recent years (0.9020, 0.8363, 0.7301) were estimated in this study. SLE-PH patients diagnosed by echocardiography have a worse long-term prognosis than those diagnosed by right heart catheterization. Studies after 2015 have shown significantly better survival than earlier studies.

In-hospital changes in the red blood cell distribution width and mortality in critically ill patients with heart failure.

A high red blood cell distribution width (RDW) at admission or discharge is associated with a worse prognosis in hospitalized patients with heart failure (HF), and the prognostic value of the in-hospital change in RDW (∆RDW) remains debatable. We included 5514 patients with critical illness and HF from the MIMIC-IV database. The ΔRDW was calculated by the RDW at discharge minus that at admission. Clinical outcomes included all-cause mortality at 90day, 180day, and 1year after discharge. The median age of the patients was 73.91years, and 46.37% were women. Kaplan-Meier curve and Cox regression analyses were used to examine the association between the ΔRDW and all-cause mortality at different time points. A multivariable Cox proportional hazard model showed that the ΔRDW (per 1% increase) was independently associated with all-cause mortality at 90day, 180day, and 1year after adjusting for confounding factors (hazard ratio [HR]=1.17, 95% confidence interval [CI]=1.13-1.21, P<0.001; HR=1.17, 95% CI=1.14-1.20, P<0.001; and HR=1.18, 95% CI=1.15-1.20, P<0.001, respectively). Restricted cubic splines showed a non-linear relationship between the ΔRDW and the risk of clinical outcomes. High ΔRDW was associated with a high risk of mortality at different time points. A subgroup analysis showed that this positive association remained consistent in pre-specified subgroups. Our study suggests that an increased RDW during hospitalization is independently associated with short- or long-term all-cause mortality in critical-ill patients with HF.

The predictive value of hematological inflammatory markers for acute kidney injury and mortality in adults with hemophagocytic Lymphohistiocytosis: A retrospective analysis of 585 patients.

Hemophagocytic lymphohistiocytosis (HLH) is a rare immunological hyperactivation-related disease with a high mortality rate. The purpose of this study was to examine the relationship between complete blood count parameters and the occurrence of acute kidney injury (AKI) and mortality in patients with HLH. We included 585 adult patients with HLH. Logistic regression models for AKI and 28-day mortality were developed. Multivariate logistic regression models revealed that hemoglobin (HB)≤7.3g/dl (adjusted OR, 1.651; 95% CI, 1.044-2.612), hemoglobin-to-red blood cell distribution width ratio (HRR)<0.49 (adjusted OR, 1.692), neutrophil-to-lymphocyte ratio (NLR)≥3.15 (adjusted OR, 1.697), and neutrophil-to-lymphocyte-platelet ratio (NLPR)≥11.0 (adjusted OR, 1.608) were independent risk factors for the development of AKI. Moreover, lower platelet levels (31×109/L<platelets<84×109/L, adjusted OR, 2.133; platelets≤31×109/L, adjusted OR, 3.545) and higher red blood cell distribution width-to-platelet ratio (RPR) levels (0.20<RPR<0.54, adjusted OR, 2.595; RPR≥0.54, adjusted OR, 4.307), lymphocytes≤0.34×109/L (adjusted OR, 1.793), NLPR≥11.0 (adjusted OR, 2.898), and the aggregate index of systemic inflammation (AISI)≤7 (adjusted OR,1.778) were also independent risk factors for 28-day mortality. Furthermore, patients with AKI had a worse prognosis than those without AKI (P<0.05). In patients with HLH, hematological parameters are of great value for the early identification of patients at high risk of AKI and 28-day mortality.

Identification of distinct clinical phenotypes of cardiogenic shock using machine learning consensus clustering approach

BackgroundCardiogenic shock (CS) is a complex state with many underlying causes and associated outcomes. It is still difficult to differentiate between various CS phenotypes. We investigated if the CS phenotypes with distinctive clinical profiles and prognoses might be found using the machine learning (ML) consensus clustering approach.MethodsThe current study included patients who were diagnosed with CS at the time of admission from the electronic ICU (eICU) Collaborative Research Database. Among 21,925 patients with CS, an unsupervised ML consensus clustering analysis was conducted. The optimal number of clusters was identified by means of the consensus matrix (CM) heat map, cumulative distribution function (CDF), cluster-consensus plots, and the proportion of ambiguously clustered pairs (PAC) analysis. We calculated the standardized mean difference (SMD) of each variable and used the cutoff of ± 0.3 to identify each cluster’s key features. We examined the relationship between the phenotypes and several clinical endpoints utilizing logistic regression (LR) analysis.ResultsThe consensus cluster analysis identified two clusters (Cluster 1: n = 9,848; Cluster 2: n = 12,077). The key features of patients in Cluster 1, compared with Cluster 2, included: lower blood pressure, lower eGFR (estimated glomerular filtration rate), higher BUN (blood urea nitrogen), higher creatinine, lower albumin, higher potassium, lower bicarbonate, lower red blood cell (RBC), higher red blood cell distribution width (RDW), higher SOFA score, higher APS III score, and higher APACHE IV score on admission. The results of LR analysis showed that the Cluster 2 was associated with lower in-hospital mortality (odds ratio [OR]: 0.374; 95% confidence interval [CI]: 0.347–0.402; P < 0.001), ICU mortality (OR: 0.349; 95% CI: 0.318–0.382; P < 0.001), and the incidence of acute kidney injury (AKI) after admission (OR: 0.478; 95% CI: 0.452–0.505; P < 0.001).ConclusionsML consensus clustering analysis synthesized the pattern of clinical and laboratory data to reveal distinct CS phenotypes with different clinical outcomes.

Association between red blood cell distribution width and ischemic stroke recurrence in patients with acute ischemic stroke: a 10-years retrospective cohort analysis

Numerous studies have reported that a higher red blood cell distribution width (RDW) level was associated with adverse outcomes in patients with the first stroke. However, no studies have examined the association between RDW and recurrent ischemic stroke. We performed a population-based cohort data analysis from 2007 to 2017. Baseline RDW was measured in 6402 first ischemic stroke participants, who were followed for about five years on average. During 62 months of median follow-up, 205 participants (3.20%) reported a recurrence (self-reported). RDW showed a nonlinear relationship with the risk of ischemic stroke recurrence. When RDW was assessed as quartiles (quartile 1, RDW<12.4; quartile 2, 12.4 to 12.8; quartile 3,12.8 to 13.3, quartile4, RDW>13.3), compared with the reference group (quartile 1), the hazard ratios (HRs) of ischemic stroke recurrence were 1.372 (95% confidence interval [CI]=0.671-2.805, P=0.386) in quartile 2, 1.835 (95% CI=1.222-2.755, P=0.003) in quartile 3, and 1.732 (95% CI=1.114-2.561, P<0.001) in quartile 4. The trend test was significant (P<0.001). When quartiles 3 and 4 were combined, the adjusted HR of ischemic stroke recurrence was 1.439 (95% CI=1.330-1.556, P<0.001) compared with the combined quartiles 1 and 2 subgroups. This study demonstrated that elevated RDW levels were positively associated with an increased risk of recurrent ischemic stroke. RDW can provide a new perspective for initial risk assessment and identify high-risk patients early. Further research is required to confirm our results.

Identification of predictors for the comprehensive clinical risk and severity of coronary lesions of acute coronary syndrome.

Acute coronary syndrome (ACS) is the most common cause of death in patients with coronary artery disease. The aim of the study was to identify the predictors of both comprehensive clinical risk and severity of coronary lesions by comprehensive use of GRACE and SYNTAX scores in patients with ACS. Clinical data of 225 ACS patients who underwent coronary angiography between 2015 and 2016 were collected. Multiple logistic regression analysis (stepwise) was used to identify the predictors. The predictive ability of predictors and the model were determined using receiver operating characteristics analyses. Multivariable logistic regression analyses showed that high aspartate aminotransferase (AST) predicted the comprehensive clinical risk with odds ratios (ORs) and 95% confidence intervals (CIs) of 1.011 (1.002-1.021). High total cholesterol (TC) and red blood cell distribution width (RDW) predicted the severity of coronary lesions with ORs and 95% CIs of 1.517 (1.148-2.004) and 1.556 (1.195-2.028), respectively. Low prealbumin predicted both severity of coronary lesions and comprehensive clinical risk of ACS patients with ORs and 95% CIs of 0.743 (0.672-0.821) and 0.836 (0.769-0.909), respectively. The model with a combination of prealbumin and AST had the highest predictive efficacy for comprehensive clinical risk, and the combination of prealbumin, TC, and RDW had the highest predictive efficacy for the severity of coronary lesions. The sensitivity and specificity, and the optimal cut-off values of these four indexes were determined. Four predictors for the comprehensive clinical risk and severity of coronary lesions of ACS were identified, which provided important information for the early diagnosis and appropriate treatment of ACS.

Using red blood cell distribution width to predict death after abdominal aortic aneurysm rupture

BackgroundAn abdominal aortic aneurysm is a life-threatening enlargement in the major vessel at the abdomen level. This study investigated the associations between different levels of red blood cell distribution width and all-cause mortality among patients with abdominal aortic aneurysm rupture. It developed predictive models for all-cause mortality risk.MethodsThis was a retrospective cohort study using 2001 to 2012 MIMIC-III dataset. The study sample included 392 U.S. adults with abdominal aortic aneurysms who were admitted to ICU after the aneurysm rupture. Then we used two single-factor and four multivariable logistic regression models to examine the associations between different levels of red blood cell distribution and all-cause mortality (30 days and 90 days), controlling for demographics, comorbidities, vital signs, and other laboratory measurements. The receiver operator characteristic curves were calculated, and the areas under the curves were recorded.ResultsThere were 140 (35.7%) patients with an abdominal aortic aneurysm in the red blood cell distribution width range between 11.7 and 13.8%, 117 (29.8%) patients in the range between 13.9 and 14.9%, and 135 (34.5%) patients in the range between 15.0 and 21.6%. Patients with higher red blood cell distribution width level (> 13.8%) tended to have a higher mortality rate (both 30 days and 90 days), congestive heart failure, renal failure, coagulation disorders, lower hemoglobin, hematocrit, MCV, red blood cell count, higher levels of chloride, creatinine, sodium, and BUN (All P < 0.05). Results of multivariate logistic regression models indicated that patients with higher red blood cell distribution width levels (> 13.8%) had the highest statistically significant odd ratios of 30 days and 90 days of all-cause mortality than lower red blood cell distribution width levels. The area under the RDW curve was lower (P = 0.0009) than that of SAPSII scores.ConclusionsOur study found that patients with abdominal aortic aneurysm rupture with a higher blood cell distribution had the highest risk of all-cause mortality. Using the blood cell distribution width level in patients with abdominal aortic aneurysm rupture to predict mortality should be considered in future clinical practice.

Higher Preoperative Red Blood Cell Distribution Width Increases the Risk of Myocardial Injury After Noncardiac Surgery in Advanced-Age Patients: A Retrospective Cohort Study.

Myocardial injury after noncardiac surgery (MINS) has been associated with worse outcomes. The aim of our study was to investigate the relationship between higher red blood cell distribution width (RDW) and postoperative 30-day MINS among advanced-age patients. This was a retrospective observational study including advanced-age patients (≥65 years old) who underwent noncardiac surgery between January 2017 and August 2019 at the First Medical Center of the Chinese People's Liberation Army General Hospital. Patients were divided into two groups according to the cutoff value identified the lowest risk using Restricted Cubic Splines (RCS) model. The primary outcome was the incidence of MINS within 30 days after surgery. The relationship between RDW and MINS was investigated by univariable and multi-variable logistic regression analysis. Propensity score (PS) analysis, including propensity score matching (PSM) and inverse probability treatment weighting (IPTW), as well as subgroup analysis were also conducted to identify the effect of RDW. The result of the RCS analysis showed that the risk of MINS in advanced-age patients increases when the baseline RDW is >12.8%. In the univariate analysis, baseline RDW >12.8% was a risk factor for postoperative MINS [odds ratio (OR)=2.11; 95% confidence interval (CI): 1.83-2.44; p<0.001]. After adjustment for all possible components, there was also a high risk of MINS for patients with elevated RDW [Adjusted OR (aOR)=1.43; 95% CI: 1.27-1.61; p<0.001). The relationship remained after PS analysis (aOR=1.24; 95% CI: 1.04-1.47; p=0.016 in PSM; aOR=1.23; 95% CI: 1.05-1.44; p=0.012 in IPTW, respectively). Significant differences between two groups were established in the incidence rate of postoperative cardiac complications and mortality. Elevated preoperative RDW is significantly associated with an increased risk of MINS within postoperative 30 days.

High Red Blood Cell Distribution Width to Platelet Ratio is an Independent Poor Prognostic Factor in Patients with Newly Diagnosed Multiple Myeloma.

The red blood cell distribution width to platelet ratio (RPR) is an inflammatory marker that is a convenient and reliable prognostic indicator for several solid malignancies. However, the correlation between RPR and myeloma prognosis has not been reported. Therefore, this study aims to explore the correlation between RPR level and the prognosis of multiple myeloma (MM) patients. We retrospectively analyzed 145 newly diagnosed patients with MM. The receiver operating characteristic curve (ROC) method was used to determine the RPR cut-off value. In addition, we studied the correlation between pre-treatment RPR levels and clinical characteristics, immunophenotype, cytogenetics, and its impact on the disease prognosis. The optimal cut-off value for RPR was 0.12 and was divided into high RPR and low RPR groups. Patients in the high RPR group are more likely to have anemia, thrombocytopenia, high β2-macroglobulinemia, a high percentage of bone marrow plasma cells, late-stage status by Dury-Salmon (DS) and international staging system (ISS) (p < 0.05). More notably, between the high RPR and low RPR groups, the incidence rates of CD56-positive, D13S319-positive, RB1-positive, and 1q21 amplification were statistically significant (p < 0.05). Additionally, survival analysis revealed that compared with patients in the low RPR group, the median progression-free survival (PFS) and overall survival (OS) of patients in the high RPR group were substantially shortened (p < 0.05). Multivariate analysis confirmed that RPR ≥0.12, D13S319-positive, and 1q21 amplification were independent risk factors for poor PFS and OS. RPR is a practical and effective prognostic marker in newly diagnosed patients with MM, and a high RPR is an independent poor prognostic factor.

Dose-Response Relationship between Red Blood Cell Distribution Width and In-Hospital Mortality in Oldest Old Patients with Acute Ischemic Stroke

Introduction: It is crucial to identify predictors of mortality in the early stage of acute ischemic stroke for the oldest old (aged ≥80 years) because of their poor overall survival outcomes. However, limited data are available as the oldest old have often been excluded from previous clinical studies. Hence, we aimed to assess the predictive effect of red blood cell distribution width on in-hospital mortality and the dose-response relationship between the red blood cell distribution width and in-hospital mortality in oldest old with acute ischemic stroke. Methods: A retrospective cohort study was performed in two tertiary hospitals. Patients aged ≥80 years admitted due to acute ischemic stroke from January 1, 2014, to January 31, 2020, were included in the study. We divided the eligible patients into 3 groups with tertiles of red blood cell distribution width. Restrictive cubic spline and robust locally weighted regression analysis were performed to test the dose-response relationship between red blood cell distribution width and the in-hospital mortality risk. All-cause in-hospital mortality was the main study outcome. Results: Overall, 606 patients were included in the final analysis. Red blood cell distribution width was categorized into 3 groups (T1: <13.7%, T2: 13.8–15.7%, and T3: >15.7%). The rationality of this categorization was then validated with restricted cubic spline and robust locally regression smoothing scatterplot, respectively. After adjusting for demographic and clinical features, a higher red blood cell distribution width was independently associated with in-hospital mortality and the hazard ratio (HR) was 3.31 (95% CI 2.47–4.45, p < 0.001). There was a positive dose-response relationship between red blood cell distribution width and mortality risk. Sensitivity analysis identified no conspicuous change in the HR. Conclusions: Red blood cell distribution width may be a valuable and simple measure for predicting in-hospital mortality in oldest old patients with acute ischemic stroke.

The Relation Between Red Blood Cell Distribution Width and Coronary Atherosclerotic Plaque Vulnerability Detected by Intracoronary Optical Coherence Tomography.

A higher red blood cell distribution width (RDW) predicts major adverse cardiac events in patients with coronary artery disease (CAD). However, there are only a few studies regarding the relationship between RDW and vulnerable plaques. Thus, the purpose of the present study is to retrospectively explore the predictive value of the association between RDW and plaque vulnerability assessed by optical coherence tomography (OCT) in patients with cardiovascular (CV) diseases. This study included 35 patients with stable angina pectoris (SAP) and 70 patients with the acute coronary syndrome (ACS). We documented clinical features as well as peripheral RDW. Plaque vulnerability was determined by OCT. We defined thin-cap fibroatheroma (TCFA) as a lipid-rich plaque (fibrous cap <65 μm thick). Plaque rupture was detected more frequently in patients with ACS compared with patients with SAP (62.9 vs. 2.9%, p<0.001, and the corresponding TCFA were 50.69±15.68 vs. 80.03±21.60 μm, p<0.001, respectively). A higher RDW was found in patients with ACS than in patients with SAP (p<0.001). A cut-off value of RDW >13.85% could detect ruptured plaque with a sensitivity of 72.3% and a specificity of 62%. TCFA and plaque rupture were detected more frequently in patients with ACS compared with SAP. Elevated RDW was positively the predictive value of the association between plaque vulnerability.

High red blood cell distribution width is associated with the mortality of critically ill cancer patients: A propensity-matching study.

The red blood cell distribution width (RDW) is related to the mortality of patients with malignant tumors, but the relationship between RDW and the prognosis of cancer patients in the intensive care unit (ICU) has not been fully clarified. To investigate the role of RDW in predicting the prognosis of critically ill cancer patients. A propensity score matching (PSM) study was conducted using data from adult patients with cancer, admitted to the ICU from the Intensive Care Medical Information Market IV (MIMIC-IV, v. 1.4) database. The correlation between RDW and ICU all-cause mortality was evaluated using a logistic regression model; stratification factors were considered. Additionally, a receiver operating characteristic (ROC) curve analysis was performed to compare the prognostic values of various blood biomarkers. Overall, 4836 cancer patients were included. The optimal critical RDW value was 15%. The RDW levels were independently correlated with ICU mortality in critically ill cancer patients, with odds ratios (ORs) of 1.56 (1.12-2.18) in the original cohort, 1.64 (1.27-2.12) in the imputation cohort, 1.65 (1.22-2.24) in the matched cohort, and 1.55 (1.19-2.03) in the weighted cohort. The forecasted performance of RDW is better than other blood biomarkers with an area under the ROC curve (AUC) of 0.637 (0.591-0.683). The RDW has a prognostic value in critically ill cancer patients and a high RDW is independently associated with high mortality.

High red blood cell distribution width is associated with the mortality of critically ill cancer patients: a propsensity matching study

High red blood cell distribution width is associated with the mortality of critically ill cancer patients: a propsensity matching study