Monocyte distribution width (MDW) as a screening tool for early detecting sepsis: a systematic review and meta-analysis

Introduction

Sepsis represents an important health burden worldwide. Early recognition is fundamental for promptly starting the appropriate treatment in order to improve the patient’s outcome and to reduce mortality. However, the diagnosis of sepsis, which relies on the integration of clinical and laboratory findings, is still challenging. Indeed, sepsis is characterised by no specific signs and symptoms. Additionally, blood culture, which represents the gold standard for sepsis diagnosis, has several drawbacks, including a long turnaround time and a high rate of false-negative findings (up to 70%) [1]. Thus, many efforts are ongoing for identifying a reliable biomarker to early recognize patients at high risk of sepsis.

Recently, the monocyte distribution width (MDW) emerged as a valuable biomarker, allowing to identifying patients at risk of sepsis admitted to acute settings, such as the Emergency Department (ED) and Intensive Care Unit (ICU). MDW is a cell population data (CPD) parameter, which is rapidly and automatically calculated by last-generation DxH haematology analysers (Beckman Coulter, Inc.), along with routine complete blood cell (CBC) count. It reflects the heterogeneity in the size of circulating monocytes, which have a key role in the pathogenesis of sepsis since very early stages [2]. Indeed, monocytes represent the first-line defence against infection. After infectious stimuli, monocytes undergo activation leading to functional and morphological changes. Thus, during the early stages of infection and sepsis, the monocyte population is characterised by high heterogeneity, which can be detected by MDW [3]. Several Authors showed that an increased MDW is associated with an increased risk of sepsis. Additionally, the reference intervals and decisional values, two fundamental steps in the clinical validation process of a biomarker, have been established [2, 4]. Among all biomarkers of sepsis [5], [6], [7], MDW has a great potential to be introduced in clinical practice.

We performed a systematic review and comprehensive meta-analysis to evaluate the accuracy of MDW as a biomarker of sepsis.

Materials and methods

We followed the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines 2020 [8]. All studies investigating the diagnostic efficacy of MDW for sepsis were searched for inclusion.

Results

Study selection

The process of study selection is schematically presented in the PRISMA flow diagram (Figure 1). A total of 570 articles (20 from PubMed and 550 from Google Scholar) were obtained. After the removal of 20 duplicates, 550 studies were retrieved. After screening the title and abstracts, 536 studies were excluded because they were literature review, case reports, abstracts, experimental studies on animals, website product information, they were performed only on paediatric population, they did not measure MDW, they did not evaluate the diagnostic accuracy of MDW for sepsis. The full text of 14 studies was further evaluated. Finally, a total of 10 studies, performed in different settings (Intensive Care Unit, Emergency Department or Infectious Diseases Unit) were included.

Figure 1:

PRISMA 2020 study selection flow diagram.

Study characteristics and quality assessment

Sepsis-2 or sepsis-3 criteria were applied, respectively, in 4 and in 6 studies. The ten studies correspond to nine independent published works, since in the work by Hausfater [15] the same 1,517 patients investigated were classified using sepsis-2 [16] or sepsis-3 criteria [17]. The main characteristics and diagnostic performances of the studies are reported in Table 1. The sample size of the studies included was between 82 and 2,215. For studies applying sepsis-2 criteria (n=4), the cut-off ranged from 20.5 to 23.5, with sensitivity and specificity ranging, respectively, from 0.645 to 0.920 and from 0.604 to 0.929 (Table 1). For studies applying sepsis-3 criteria (n=6), the cut-off ranged from 19.2 to 24.6, with sensitivity and specificity ranging, respectively, from 0.669 to 0.957 and from 0.499 to 0.797 (Table 1). The forest plots and the crosshair plots for sensitivity and specificity across the studies, classified according to sepsis-2 or sepsis-3 criteria, are reported in Figures 2 and 3. The plots suggest high variability for both sensitivity and specificity. No publication bias was detected by inspection of funnel plot and formal Deeks’s test.

Table 1:

Characteristics of the studies included in the meta-analysis.

Study	Study design	Clinical setting	Sepsis criteria	Study population		Anticoag	MDW cut-off value	AUC	SE	Sens	Spec	PPV, %	NPV, %	LR+	LR−
				Total	Sepsis
Crouser et al., 2017 [18]	Prospective	ED	Sepsis-2	1,320	98	K2	20.5	0.790	0.03	0.77	0.73	NA	NA	NA	NA
Guo et al., 2019 [19]	Retrospective	ICU	Sepsis-3	249	54	NA	19.2	0.767	0.03	0.759	0.760	63.1	85.4	NA	NA
Polilli et al., 2020 [20]	Prospective	Inf. Dis. Unit	Sepsis-3	260	105	K3	21.9	0.870	0.025	0.943	0.697	67.8	94.7	NA	NA
Agnello et al., 2021 [21]	Retrospective	ED	Sepsis-2	2,215	88	K3	23.5	0.964	0.01	0.920	0.929	30	99.6	NA	NA
Agnello et al., 2021 [22]	Retrospective	ICU	Sepsis-3	82	23	K3	23.9	0.937	0.03	0.957	0.787	54	98	NA	NA
Hausfater et al., 2021 [15]	Prospective	ED	Sepsis-2	1,517	260	K3	21.5	0.810	0.02	0.750	0.730	36	93	2.76	0.34
Hausfater et al., 2021 [15]	Prospective	ED	Sepsis-3	1,517	144	K3	21.5	0.820	0.015	0.810	0.690	22	97	2.63	0.28
Hou et al., 2021 [23]	Retrospective	ED	Sepsis-2	1,480	296	NA	22.1	0.625	0.02	0.645	0.604	NA	NA	NA	NA
Piva et al. 2021 [24]	Prospective	ICU	Sepsis-3	506	112	K2	24.6	0.785	0.01	0.669	0.778	NA	NA	3.01	0.43
Woo et al., 2021 [25]	Prospective	ED	Sepsis-3	549	188	K2	19.8	0.710	0.02	0.830	0.499	34.2	84.9	1.65	0.34

1. Total: total sample size, sepsis: sample size of patients with sepsis; anticoag., anticoagulant; AUC: area under the curve; SE, standard error; Sens, sensitivity; Spec, specificity; PPV, positive predictive value; NPV, negative predictive value; LR+, positive likelihood ratio; LR−, negative likelihood ratio; NA, information not available; ED, Emergency Department; ICU, Intensive Care Unit; Inf. Dis. Unit, Infectious Disease Unit.

Figure 2:

Forest plots of sensitivity (left column) and specificity (right column) of the studies investigated divided by the use of sepsis-2 (above) or sepsis-3 (below) criteria.Studies were ordered following date of publication.

Figure 3:

Crosshair plots of the sensitivity and specificity across the studies investigated divided by the use of sepsis-2 (left) or sepsis-3 (right) criteria. Studies were ordered following date of publication.

Discussion

In this systematic review and meta-analysis, we evaluated the accuracy of MDW as a biomarker of sepsis by analysing results from ten studies, including a total of 9,475 individuals, of whom 1,370 had sepsis, 742 diagnosed according to Sepsis-2 criteria and 628 according to Sepsis-3 criteria. We included only studies performed on adult individuals, who were admitted to different clinical settings, including ED (n=7), ICU (n=2), and Unit of Infectious Diseases (n=1). We excluded paediatric individuals and patients with COVID-19 in order to avoid bias. Indeed, although some Authors showed that COVID-19 patients have increased levels of MDW [26, 27], such disease is characterised by a high heterogeneity both a clinical and clinical-biochemistry point of view. Additionally, COVID-19 patients show significant differences among the epidemiological waves. Thus, in order to avoid to further increasing the heterogeneity already found among studies, we considered it appropriate to exclude COVID-19 patients.

Finally, since sepsis-2 and sepsis-3 criteria identify patients with sepsis by using different parameters, we considered it appropriate to distinguish studies according to these criteria.

In all studies, MDW showed good diagnostic accuracy for early detecting patients with sepsis, with an AUC ranging from 0.625 to 0.964. Due to different cut-offs reported in the published studies, we did not calculate weighted estimates of sensitivity and specificity for MDW at a common threshold, using sensitivity and specificity data at the different cut-offs. Instead, we estimated pooled summaries using a bivariate binomial approach. Specifically, we found pooled sensitivity and specificity of 0.789 and 0.777, respectively, for sepsis-2 criteria, and 0.838 and 0.704, respectively, for sepsis-3 criteria. DORs were, respectively, 13.032 and 12.312. Forest plot analysis showed significant heterogeneity among the included studies. However, we did not apply additional statistical methods to further investigate this heterogeneity due to the small number of studies. Thus, neither the meta-regression nor a subgroup analysis was performed. We can hypothesize that the main sources of heterogeneity could be the anticoagulant used for collecting blood samples (K₃-EDTA vs. K₂-EDTA), the clinical wards where the studies were performed, the cut-off used and the characteristics of the study population. Specifically, the manufacturer has described the influence of the anticoagulant, with a 1.5 unit offset between K₂- and K₃ - EDTA (https://www.beckmancoulter.com/download/file/wsr-262828/C21894AC?type=pdf).

To the best of our knowledge, this is the first meta-analysis to assess the value of MDW as a biomarker of sepsis. Our findings show that MDW has high accuracy for detecting patients at risk of sepsis in different clinical wards. The introduction of MDW in clinical practice is very attractive because it has the great advantage of being a parameter belonging to the CBC. Thus, its evaluation is fast, easy, low-cost, and it does not require an additional blood sample, as for the measurement of other biomarkers of sepsis. CBC is the most common laboratory test required in all patients admitted in any clinical ward, from ED to ICU [28]. Thus, it could be available to any clinicians in every moment of the patient’s care path, also when there is no suspect of sepsis. On the contrary, the most commonly used biomarkers of sepsis, such as C-reactive protein and procalcitonin, are ordered by clinicians in an advanced stage, when there is the clinical suspicion of sepsis.

An altered MDW value should be interpreted as a “red flag” for sepsis and the clinicians should monitor the patient and further investigate to confirm the suspect of sepsis. Noteworthy, several Authors reported that MDW has a high negative predictive value [15, 20], [21], [22]. Thus, a value of MDW below the cut-off should exclude with high reliability sepsis.

Conclusions

This meta-analysis showed that MDW has high accuracy in early detecting patients with sepsis. Thus, it could represent a reliable tool for guiding clinicians in the appropriate management of patients, also when sepsis is not suspected.