Diagnostic value of RDW for the prediction of mortality in adult sepsis patients: A systematic review and meta-analysis

Wu, Hongsheng; Liao, Biling; Cao, Tiansheng; Ji, Tengfei; Huang, Jianbin; Ma, Keqiang

doi:10.3389/fimmu.2022.997853

Cited by 20 publications

(11 citation statements)

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“…Previous studies have also reported a close association between early elevation of WBC and adverse prognosis, suggesting that WBC may serve as a prognostic factor, as confirmed by the present study [ 5 , 10 , 17 ]. The RDW has recently been found to have a strong predictive capacity for the risk of death and adverse outcomes of other infectious and serious diseases, such as COVID-19 [ 18 ], acute respiratory obstruction syndrome [ 19 ], and sepsis [ 20 ]. Studies of ICU patients have shown that the RDW is an independent risk factor for death and is significantly and independently related to mortality [ 21 ].…”

Section: Discussionmentioning

confidence: 99%

Construction of a mortality risk prediction model for patients with acute diquat poisoning based on clinically accessible data

Lv,

2024

J Occup Med Toxicol

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Background To examine the risk factors associated with mortality in individuals suffering from acute diquat poisoning and to develop an effective prediction model using clinical data. Methods A retrospective review was conducted on the clinical records of 107 individuals who were hospitalized for acute diquat poisoning at a tertiary hospital in Sichuan Province between January 2017 and September 30, 2023, and further categorized into survivor and nonsurvivor groups based on their mortality status within 30 days of poisoning. The patient’s demographic information, symptoms within 24 h of admission, and details of the initial clinical ancillary examination, as well as the APACHE II score, were documented. The model was developed using backward stepwise logistic regression, and its performance was assessed using receiver operating characteristic curves, calibration curves, Brier scores, decision curve analysis curves, and bootstrap replicates for internal validation. Results Multifactorial logistic regression analysis revealed that blood pressure (hypertension, OR 19.73, 95% CI 5.71–68.16; hypotension, OR 61.38, 95% CI 7.40–509.51), white blood count (OR 1.35, 95% CI 1.20–1.52), red cell distribution width-standard deviation (OR 1.22, 95% CI 1.08–1.38), and glomerular filtration rate (OR 0.96, 95% CI 0.94–0.97) were identified as independent risk factors for mortality in patients with diquat. Subsequently, a nomogram with an area under the curve of 0.97 (95% CI: 0.93–1) was developed. Internal bootstrap resampling (1000 repetitions) confirmed the model’s adequate discriminatory power, with an area under the curve of 0.97. Decision curve analysis demonstrated greater net gains for the nomogram, while the clinical impact curves indicated greater predictive validity. Conclusion The nomogram model developed in this study using available clinical data enhances the prediction of risk for DQ patients and has the potential to provide valuable clinical insights to guide patient treatment decisions.

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Section: Discussionmentioning

confidence: 99%

Construction of a mortality risk prediction model for patients with acute diquat poisoning based on clinically accessible data

Lv,

2024

J Occup Med Toxicol

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“…Beyond merely serving as a prognostic marker for mortality in conditions such as heart disease, kidney disease, and cancer, the significance of RDW extends further. It encompasses the assessment of inflammation levels in conditions like sepsis and autoimmune diseases and the evaluation of infection severity, and it may also offer insights into the presence of neurological or liver disorders [ 15 , 17 , 19 , 20 , 43 , 44 , 45 , 46 ].…”

Section: Discussionmentioning

confidence: 99%

The Association between Red Blood Cell Distribution Width and Mortality Risk after Hip Fracture: A Meta-Analysis

Nguyen,

Tran,

Nguyen

et al. 2024

Medicina

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Background and Objectives: Hip fractures in the elderly pose a considerable health risk and cause concern. Red blood cell distribution width (RDW) is a valuable marker for identifying patients at high risk of age-related mortality and various disorders and diseases. However, its association with poor patient outcomes following hip fractures has yet to be fully established. Hence, the purpose of this meta-analysis was to investigate and gain a better understanding of the relationship between RDW levels and the risk of mortality after hip fractures. Materials and Methods: PubMed, Embase, Web of Science, and other databases were comprehensively searched until April 2023 to identify relevant studies. The meta-analysis included observational studies finding the association between RDW at admission or preoperation and short-term and long-term mortality rates following hip fractures. The results were presented in terms of odds ratios (ORs) or hazard ratios (HRs) with corresponding 95% confidence intervals (CIs). Results: This meta-analysis included 10 studies involving 5834 patients with hip fractures. Patients with preoperative RDW of over 14.5% had higher risks of 1-year (OR: 5.40, 95% CI: 1.89–15.48, p = 0.002) and 3-month (OR: 2.91, 95% CI: 1.42–5.95, p = 0.004) mortality. Higher admission or preoperative RDW was significantly associated with an 11% higher mortality risk after 1 year (HR: 1.11, 95% CI: 1.06–1.17, p < 0.00001). Patients with higher preoperative RDW had a significantly higher risk of 6-month mortality, which was three times that of those with lower preoperative RDW (OR: 3.00, 95% CI: 1.60–5.61, p = 0.0006). Higher preoperative RDW was correlated to a higher 30-day mortality risk (OR: 6.44, 95% CI: 3.32–12.47, p < 0.00001). Conclusions: Greater RDW values at admission or before surgery were associated with a higher risk of short-term and long-term mortality following hip fractures. Because RDW can be easily measured using a routine blood test at a low cost, this parameter is promising as an indicator of mortality in elderly patients with hip fractures.

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“… 36 RDW, whether used alone or in combination with other clinical and laboratory parameters, has demonstrated prognostic value in predicting clinical outcomes in sepsis. 37 However, there are limited studies utilizing the coefficient of variation (RDW-CV) of RDW to predict clinical outcomes in sepsis. On the other hand, sepsis often leads to significant coagulation dysfunction.…”

Section: Discussionmentioning

confidence: 99%

LASSO-Based Identification of Risk Factors and Development of a Prediction Model for Sepsis Patients

Hong,

Xiong,

Xia

et al. 2024

TCRM

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Objective The objective of this study was to utilize LASSO regression (Least Absolute Shrinkage and Selection Operator Regression) to identify key variables in septic patients and develop a predictive model for intensive care unit (ICU) mortality. Methods We conducted a cohort consisting of septic patients admitted to the ICU between December 2016 and July 2019. The disease severity and laboratory index were analyzed using LASSO regression. The selected variables were then used to develop a model for predicting ICU mortality. AUCs of ROCs were applied to assess the prediction model, and the accuracy, sensitivity and specificity were calculated. Calibration were also used to assess the actual and predicted values of the predictive model. Results A total of 1733 septic patients were included, among of whom 382 (22%) died during ICU stay. Ten variables, namely mechanical ventilation (MV) requirement, hemofiltration (HF) requirement, norepinephrine (NE) requirement, septicemia, multiple drug-resistance infection (MDR), thrombocytopenia, hematocrit, red-cell deviation width coefficient of variation (RDW-CV), C-reactive protein (CRP), and antithrombin (AT) III, showed the strongest association with sepsis-related mortality according to LASSO regression. When these variables were combined into a predictive model, the area under the curve (AUC) was found to be 0.801. The AUC of the validation group was 0.791. The specificity of the model was as high as 0.953. Within the probability range of 0.25 to 0.90, the predictive performance of the model surpassed that of individual predictors within the cohort. Conclusion Our findings suggest that a predictive model incorporating the variables of MV requirement, HF requirement, NE requirement, septicemia, MDR, thrombocytopenia, HCT, RDW-CV, CRP, and AT III exhibiting an 80% likelihood of predicting ICU mortality in sepsis and demonstrates high accuracy.

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Diagnostic value of RDW for the prediction of mortality in adult sepsis patients: A systematic review and meta-analysis

Cited by 20 publications

References 50 publications

Construction of a mortality risk prediction model for patients with acute diquat poisoning based on clinically accessible data

Construction of a mortality risk prediction model for patients with acute diquat poisoning based on clinically accessible data

The Association between Red Blood Cell Distribution Width and Mortality Risk after Hip Fracture: A Meta-Analysis

LASSO-Based Identification of Risk Factors and Development of a Prediction Model for Sepsis Patients

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