Monocyte distribution width adds prognostic value in detection of COVID‐19 respiratory failure

Hossain, Rubayet; Ayub, Salman; Tarabichi, Yasir

doi:10.1111/ijlh.13712

Cited by 12 publications

(7 citation statements)

References 10 publications

(13 reference statements)

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“…It is important to note that the MDW was helpful for risk stratification. Our data support Hossain et al, who found that there is a meaningful difference in MDW in patients with hypoxic respiratory failure [15]. Our data utilized the International Classification of Diseases (ICD) codes in the determination of hypoxia and respiratory failure, and we were able to demonstrate that patients with respiratory problems had a significantly higher MDW of 24.9 compared to those without respiratory failure (24.9 vs. 21.9; p < 0.01).…”

Section: Mdw Is Able To Detect Hypoxia and Respiratory Failuresupporting

confidence: 86%

Monocyte Distribution Width Predicts Sepsis, Respiratory Failure, and Death in COVID-19

Frugoli,

Ong,

Meyer

et al. 2023

Cureus

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IntroductionSepsis is the leading cause of hospital mortality nationwide. Early recognition has been shown to improve outcomes. This research investigates the use of monocyte distribution width's (MDW) ability to detect sepsis and clinically correlate to outcomes in COVID-19 infection. MethodsThis is a retrospective, single-center cohort study of adult patients with confirmed COVID-19 requiring hospital admission over a 14-month period (September 2020 to November 2021). MDW was evaluated as a cytomarker to predict disease severity, mortality, and determination of sepsis in patients with COVID-19. Additionally, MDW was compared to existing inflammatory markers, including procalcitonin, D-dimer, ferritin, and lactic acid. ResultsMDW was able to predict sepsis in patients with COVID-19. The average MDW was found to be significantly higher in the detection of sepsis (25.50 ± 5.93) vs. patients without (23.13 ± 4.46) (p < 0.01). MDW was able to correlate with clinical outcomes or respiratory failure/hypoxia and death. An MDW value of 24.9 was shown to be the best cut-off value in determining fatal outcomes; receiver operating characteristic curve analysis revealed an area under the curve value of 0.69 (95% CI: 0.55-0.71) with a sensitivity of 83% and specificity of 71%. A chi-square test was performed, which detected a significant association between MDW values and the final clinical outcome of COVID-19 (OR = 3.52, 95% CI: 1.78-7.11, p < 0.001). Additionally, the mean MDW of patients with hypoxia or respiratory failure was significantly higher (22 vs. 25, p < 0.1). MDW did not correlate with any of the existing inflammatory markers. ConclusionMDW is a novel and reliable cytomarker for identifying sepsis in patients with COVID-19 infection. High MDW values are associated with clinical outcomes of respiratory failure and death with a mortality rate or absolute risk of 25%. MDW is easily obtained from routine laboratory evaluation in the emergency room and has the potential to be a useful tool in the triage of COVID-19 patients.

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Section: Mdw Is Able To Detect Hypoxia and Respiratory Failuresupporting

confidence: 86%

Monocyte Distribution Width Predicts Sepsis, Respiratory Failure, and Death in COVID-19

Frugoli,

Ong,

Meyer

et al. 2023

Cureus

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“…They observed that a ΔMDW value less than one indicated an unfavorable prognosis [ 11 ]. Hossain et al encountered a median MDW of 26.0 (interquartile range: 23.0–28.0) in patients with respiratory failure and proposed to evaluate MDW and NLR together for better prognostication of COVID-19 patients [ 16 ]. Lin et al utilized MDW and neutrophil–lymphocyte ratio (NLR) to distinguish COVID-19 and common upper respiratory tract infections with MDW ≥ 20 and NLR < 3.2, efficiently identifying COVID-19 patients [ 17 ].…”

Section: Discussionmentioning

confidence: 99%

Monocyte Distribution Width (MDW) in Patients with COVID-19: An Indicator of Disease Severity

Sharma

Naseem

Varma

et al. 2023

Indian J Hematol Blood Transfus

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Identifying patients with Coronavirus disease-2019 (COVID-19) who may have a severe illness is essential for timely intervention and decreasing the fatality rate. In the present study, we evaluated the performance of Monocyte Distribution Width (MDW) as a prognostic marker for identifying disease severity in COVID-19 patients. We included 145 patients with PCR-confirmed COVID-19 infection in the study. The performance of MDW was evaluated by calculating the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, negative predictive value, and positive predictive value. Further analysis was conducted for the disease outcome, comparing COVID-19 patients discharged ( n = 135) to deceased COVID-19 patients ( n = 10). As a marker of disease severity, MDW demonstrated an AUC of 0.702 (95% CI 0.620–0.775) in ROC analysis. If MDW is considered a marker of patient outcome, AUC was 0.916 (95% CI 0.862–0.953), comparing deceased COVID-19 patients vs. those who survived. At a cut-off of > 25.4 on admission, MDW correlates well with poor disease outcomes in COVID-19 patients. MDW can be considered a helpful parameter in predicting the severity of COVID-19 disease and patient outcomes. Its role and incorporation in the standard diagnostic algorithm and management of COVID-19 patients need further validation. Supplementary Information The online version contains supplementary material available at 10.1007/s12288-023-01665-y.

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“…An elevated MDW value of 20 or higher in adult patients as measured by a proprietary cellular analysis system developed by Beckman Coulter, Inc. (Brea, CA, USA) has been associated with an increased risk of developing sepsis within 12 hours of hospital admission [17, 18]. Recent studies have also explored the role of MDW as a prognostic marker in patients with SARS-CoV-2-associated disease (COVID-19) infection [19, 20].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Interpretability Methods to Characterize the Importance of Hematologic Biomarkers in Prognosticating Patients with Suspected Infection

Upadhyaya

Tarabichi

Prantzalos

et al. 2023

Preprint

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Background Early detection of sepsis in patients admitted to the emergency department (ED) is an important clinical objective to help reduce morbidity and mortality. We aimed to use data from Electronic Health Records (EHR) system to characterize the relative importance of a new biomarker called Monocyte Distribution Width (MDW) that has been recently approved by the US Food and Drug Administration (FDA) for sepsis screening in the presence of routinely available hematologic parameters and vital signs measures. Methods In this retrospective cohort study, we included ED patients admitted to the MetroHealth hospital (a large regional safety-net hospital in Cleveland, OH, USA) with suspected infection who later developed severe sepsis. All adult patients presenting to the ED were eligible for inclusion and encounters that did not have complete blood count with differential data or vital signs data were excluded. We developed seven data models and an ensemble of four high accuracy machine learning (ML) algorithms using the Sepsis-3 diagnostic criteria for validation. Using the results generated by the high accuracy ML models, we applied the Local Interpretable Model- Agnostic Explanation (LIME) and Shapley Additive Value (SHAP) post-hoc ML interpretability methods to characterize the contributions of individual hematologic parameters, including MDW, vital signs measures in screening for severe sepsis. Findings We evaluated 7071 adult patients from 303,339 adult ED visits occurring between May 1st, 2020 and August 26th, 2022. Implementation of the seven data models reflected the ED clinical workflow with incremental addition of standard complete blood count (CBC), CBC with differential, with MDW, and finally vital signs measures. Random forest and deep neural network model reported classification area under the receiver operating characteristic curve (AUC) value of up to 93% (CI 92 : 94) and 90% (CI 88 : 91) over data model with hematologic parameters and vital signs measures. We applied the LIME and SHAP ML interpretability methods on these high accuracy ML models. Both the interpretability methods were consistent in their findings that the value of MDW is grossly attenuated (low feature importance scores of 0.015 (SHAP) and 0.0004 (LIME)) in the presence of other routinely reported hematologic parameters and vital signs measures for severe sepsis detection. Interpretation Using ML interpretability methods applied to EHR data, we show that MDW can be replaced with routinely reported CBC with differential together with vital signs measures for severe sepsis screening. MDW requires specialized laboratory equipment and modification of existing care protocols; therefore, these results could guide decisions about allocation of limited resources in cost constrained care settings. Additionally, the analysis shows the practical application of ML interpretability methods in clinical decision making.

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Monocyte distribution width adds prognostic value in detection of COVID‐19 respiratory failure

Cited by 12 publications

References 10 publications

Monocyte Distribution Width Predicts Sepsis, Respiratory Failure, and Death in COVID-19

Monocyte Distribution Width Predicts Sepsis, Respiratory Failure, and Death in COVID-19

Monocyte Distribution Width (MDW) in Patients with COVID-19: An Indicator of Disease Severity

Machine Learning Interpretability Methods to Characterize the Importance of Hematologic Biomarkers in Prognosticating Patients with Suspected Infection

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