A new tool for sepsis screening in the Emergency Department

Machine learning interpretability methods to characterize the importance of hematologic biomarkers in prognosticating patients with suspected infection

OBJECTIVE

To evaluate the effectiveness of Monocyte Distribution Width (MDW) in predicting sepsis outcomes in emergency department (ED) patients compared to other hematologic parameters and vital signs, and to determine whether routine parameters could substitute MDW in machine learning models.

METHODS

We conducted a retrospective analysis of data from 10,229 ED patients admitted to a large regional safety-net hospital in Cleveland, Ohio who had suspected infections and developed sepsis-associated poor outcomes. We developed a new analytical framework consisting of seven data models and an ensemble of high accuracy machine learning (ML) algorithms (accuracy values ranging from 0.83 to 0.90) to predict sepsis-associated poor outcomes (3-day intensive care unit stay or death). Local Interpretable Model-Agnostic Explanation (LIME) and Shapley Additive Value (SHAP) interpretability methods were utilized to assess the contributions of individual hematologic parameters.

RESULTS

The ML interpretability analysis indicated that the predictive value of MDW is significantly reduced when other hematological parameters and vital signs are considered. The results suggest that complete blood count with differential (CBD-DIFF) alongside vital signs can effectively replace MDW in high accuracy machine learning algorithms for screening poor outcome associated with sepsis.

CONCLUSION

MDW, although a newly approved biomarker for sepsis, does not significantly enhance prediction models when combined with routinely available parameters and vital signs. Hospitals, especially those with resource constraints, can rely on existing parameters with high accuracy machine learning models to predict sepsis outcomes effectively, thereby reducing the need for specialized tests like MDW.

Monocyte distribution width (MDW) kinetic for monitoring sepsis in intensive care unit

OBJECTIVES

Monocyte distribution width (MDW) is a measure of monocyte anisocytosis. In this study, we assessed the role of MDW, in comparison to C-reactive protein (CRP), procalcitonin (PCT), and lactate, as a screening and prognostic biomarker of sepsis in intensive care unit (ICU) by longitudinally measuring it in the first 5 days of hospital stay.

METHODS

We considered all consecutive patients admitted to the ICU. At admission, patients were classified as septic or not according to Sepsis-3 criteria. MDW, CRP, PCT, and lactate were measured daily in the first 5 days of hospitalization. ICU mortality was also recorded.

RESULTS

We included 193 patients, 62 with sepsis and 131 without sepsis (controls). 58% and 26 % of the patients, with and without sepsis respectively, died during ICU stay. MDW showed the highest accuracy for sepsis detection, superior to CRP, PCT, and lactate (AUC of 0.840, 0.755, 0.708, 0.622, respectively). At admission, no biomarker predicts ICU mortality in patients with sepsis. The kinetic of all biomarkers during the first 5 days of hospitalization was associated with ICU mortality. Noteworthy, above all, the kinetic of MDW showed the best accuracy. Specifically, an increase or decrease in MDW from day 1-4 and 5 was significantly associated with mortality or survival, respectively.

CONCLUSIONS

MDW is a reliable diagnostic and prognostic sepsis biomarker, better than traditional biomarkers.

Clinical impact of the implementation of monocyte distribution width (MDW) measurement on time to anti-infective administration in sepsis patients in the emergency department: a before/after cohort study

BACKGROUND

Timely recognition of sepsis in emergency department (ED) is challenging. We evaluated the impact of implementing the biomarker monocyte distribution width (MDW) at bedside, on the time to anti-infective administration.

METHODS

We conducted a before-and-after cohort study in the ED of an academic hospital in Paris, to compare sepsis patients care and outcomes, before and after the implementation of point of care (POC) MDW measurement in the ED. During post-implementation period (period-2), MDW was measured with complete blood count by ED nurses with results given in 2 min: if above 21.5 units, ED physicians were asked to consider sepsis and to start an anti-infectious as soon as possible. Primary endpoint was time to anti-infectious administration (TTA) from ED arrival, and secondary endpoints were TTA from sepsis onset (TTAS), length of stay, mortality, and hospitalization rates.

RESULTS

In total, 255 patients (period-1) and 180 patients (period-2) with sepsis were included. The TTA was 5.4 h (3.5-7.7) period-1 and 4.9 h (IQR 2.5-7.1) in period-2 (p = 0.06). MDW implementation significantly reduced the median TTAS from to 3.7 h (IQR 1.5-5.8) in period-1, to 2.2 h (IQR 0.5-4.5) in period-2 (p < 0.001). Mortality rates remained similar between the two periods (18% vs. 16% respectively, p = 0.4), as did hospitalization rates (93% vs. 91%, p = 0.4) and ED length of stay (7.2 h (5.3-9.8) vs 7.0 (5.4-9.4), p = 0.7).

CONCLUSION

Implementing POC MDW measurement in the ED protocols enhances the timeliness of anti-infective administration from sepsis onset, meeting current sepsis management guidelines.

Clinical usefulness of presepsin and monocyte distribution width (MDW) kinetic for predicting mortality in critically ill patients in intensive care unit

Background

In this study, we explored the accuracy of two new sepsis biomarkers, monocyte distribution width (MDW) and presepsin (PSP), compared to traditional ones, C-reactive protein (CRP) and Procalcitonin (PCT), to identify sepsis and predict intra-hospital mortality by analyzing their kinetic at different time points during hospitalization stay.

Methods

We enrolled 104 patients admitted to the intensive care unit (ICU) of University Hospital "Paolo Giaccone", Palermo. Among these, 30 (29%) had a clinical diagnosis of sepsis. MDW, PCT, CRP, and PSP were evaluated at admission (T0), after 24 h (T24), 48 h (T48), 72 h (T72), at day 5 (T5), and at discharge (TD).

Results

Patients with sepsis displayed higher levels of PCT and PSP than patients without sepsis at each timepoint; differently, CRP displayed statistically significant differences only at T0, while MDW only at T0 and T24. Patients with increasing levels of PSP displayed lower median survival time than patients with decreasing levels; differences reached statistical significance only at 48 h (20 vs. 29 days, log rank test, p = 0.046). Interestingly, PSP was an independent predictor of ICU mortality at 48 and 72 h after hospital admission. Also, the kinetic of PSP had prognostic value, with increased values at 48 h after admission being associated with reduced survival.

Conclusion

Our findings support the role of PSP and its kinetic as a predictor of ICU mortality.

A new hematological parameter model for the diagnosis and prognosis of sepsis in emergency department: A single-center retrospective study

INTRODUCTION

Sepsis, a syndrome of organ dysfunction caused by an unregulated host response to infection. This study aimed to develop a novel sepsis diagnostic model of hematological parameters and evaluate its effectiveness in the early identification and prognosis of sepsis in emergency departments.

METHODS

A retrospective study was conducted in Emergency Department. Cell population data parameters related to monocytes and neutrophils were obtained using the Mindary BC-6800 plus hematology analyzer. Receiver operating characteristic (ROC) curve analysis, logistic regression analysis was performed to assess the performance of the parameters and establish a diagnostic and prognostic model of sepsis, which was then verified with a validation cohort.

RESULTS

Mon_XW exhibited the best diagnostic performance (area under the ROC curve [AUC] = 0.848, 95% confidence interval [CI]: 0.810-0.885, p < 0.001), followed by Neu_Y and Neu_YW (AUC = 0.777 95% CI: 0.730-0.824, p < 0.001). Logistic regression analysis identified Mon_XW and Neu_Y as independent predictors, which were used to establish a diagnostic model named hematological parameter for sepsis (HPS). HPS demonstrated the best diagnostic performance with an AUC of 0.862 (95% CI: 0.826-0.898, p < 0.001), sensitivity of 70.0%, and specificity of 87.1%, compared to C-reactive protein (CRP) and procalcitonin (PCT). The validation cohort also found that the positive predictive value of HPS was 70.4% and the negative predictive value was 92.2%.

CONCLUSION

The developed HPS model showed promising diagnostic efficacy for sepsis in the emergency department, which outperformed CRP and PCT in terms of sensitivity and specificity. By enabling early identification and prognosis of sepsis, that contributes to reducing sepsis-related mortality.

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

Early detection of sepsis in patients admitted to the emergency department (ED) is an important clinical objective as early identification and treatment can help reduce morbidity and mortality rate of 20% or higher. Hematologic changes during sepsis-associated organ dysfunction are well established and a new biomarker called Monocyte Distribution Width (MDW) has been recently approved by the US Food and Drug Administration for sepsis. However, MDW, which quantifies monocyte activation in sepsis patients, is not a routinely reported parameter and it requires specialized proprietary laboratory equipment. Further, the relative importance of MDW as compared to other routinely available hematologic parameters and vital signs has not been studied, which makes it difficult for resource constrained hospital systems to make informed decisions in this regard. To address this issue, we analyzed data from a cohort of ED patients (n=10,229) admitted to a large regional safety-net hospital in Cleveland, Ohio with suspected infection who later developed poor outcomes associated with sepsis. We developed a new analytical framework consisting of seven data models and an ensemble of high accuracy machine learning (ML) algorithms (accuracy values ranging from 0.83 to 0.90) for the prediction of outcomes more common in sepsis than uncomplicated infection (3-day intensive care unit stay or death). To characterize the contributions of individual hematologic parameters, we applied the Local Interpretable Model-Agnostic Explanation (LIME) and Shapley Additive Value (SHAP) interpretability methods to the high accuracy ML algorithms. The ML interpretability results were consistent in their findings that the value of MDW is grossly attenuated in the presence of other routinely reported hematologic parameters and vital signs data. Further, this study for the first time shows that complete blood count with differential (CBC-DIFF) together with vital signs data can be used as a substitute for MDW in high accuracy ML algorithms to screen for poor outcomes associated with sepsis.

Developing an early warning system for detecting sepsis in patients with trauma

The purpose of this study was to analyse the risk factors for sepsis in patients with trauma and develop a new scoring system for predicting sepsis in patients with trauma based on these risk factors. This will provide a simple and effective early warning method for the rapid and accurate detection and evaluation of the probability of sepsis in patients with trauma to assist in planning timely clinical interventions. We undertook a retrospective analysis of the clinical data of 216 patients with trauma who were admitted to the emergency intensive care unit of the emergency medicine department of the Hebei Medical University Third Hospital, China, between November 2017 and October 2022. We conducted a preliminary screening of the relevant factors using univariate logistic regression analysis and included those factors with a p value of <0.075 in the multivariate logistic regression analysis, from which the risk factors were screened and assigned, and obtained a total score, which was the sepsis early warning score. The incidence of sepsis in patients in the intensive care unit with trauma was 36.9%, and the mortality rate due to sepsis was 19.4%. We found statistically significant differences in several factors for patients with sepsis. The risk factors for sepsis in patients with trauma were the activated partial thromboplastin time, the New Injury Severity Score, growth differentiation factor-15 levels, shock, mechanical ventilation and the Acute Physiology and Chronic Health Evaluation II score. The area under the receiver operating characteristic curve of the sepsis early warning score for predicting sepsis in patients with trauma was 0.725. When the cutoff value of the early warning score was set at 5.0 points, the sensitivity was 69.9% and the specificity was 60.3%. The incidence of sepsis in patients with trauma can be reduced by closely monitoring patients' hemodynamics, implementing adequate fluid resuscitation promptly and by early removal of the catheter to minimize the duration of unnecessary invasive mechanical ventilation. In this study, we found that the use of the sepsis early warning score helped in a more accurate and effective evaluation of the prognosis of patients with trauma.

Uncovering hub genes in sepsis through bioinformatics analysis

In-depth studies on the mechanisms of pathogenesis of sepsis and diagnostic biomarkers in the early stages may be the key to developing individualized and effective treatment strategies. This study aimed to identify sepsis-related hub genes and evaluate their diagnostic reliability. The gene expression profiles of GSE4607 and GSE131761 were obtained from the Gene Expression Omnibus. Differentially co-expressed genes between the sepsis and control groups were screened. Single-sample gene set enrichment analysis and gene set variation analysis were performed to investigate the biological functions of the hub genes. A receiver operating characteristic curve was used to evaluate diagnostic value. Datasets GSE154918 and GSE185263 were used as external validation datasets to verify the reliability of the hub genes. Four differentially co-expressed genes, FAM89A, FFAR3, G0S2, and FGF13, were extracted using a weighted gene co-expression network analysis and differential gene expression analysis methods. These 4 genes were upregulated in the sepsis group and were distinct from those in the controls. Moreover, the receiver operating characteristic curves of the 4 genes exhibited considerable diagnostic value in discriminating septic blood samples from those of the non-septic control group. The reliability and consistency of these 4 genes were externally validated. Single-sample gene set enrichment analysis and gene set variation analysis analyses indicated that the 4 hub genes were significantly correlated with the regulation of immunity and metabolism in sepsis. The identified FAM89A, FFAR3, G0S2, and FGF13 genes may help elucidate the molecular mechanisms underlying sepsis and drive the introduction of new biomarkers to advance diagnosis and treatment.

A low-cost, label-free microfluidic scanning flow cytometer for high-accuracy quantification of size and refractive index of particles

Flow cytometers and fluorescence activated cells sorters (FCM/FACS) represent the gold standard for high-throughput single-cell analysis, but their usefulness for label-free applications is limited by the unreliability of forward and side scatter measurements. Scanning flow cytometers represent an appealing alternative, as they exploit measurements of the angle-resolved scattered light to provide accurate and quantitative estimates of cellular properties, but the requirements of current setups are unsuitable for integration with other lab-on-chip technologies or for point-of-care applications. Here we present the first microfluidic scanning flow cytometer (μSFC), able to achieve accurate angle-resolved scattering measurements within a standard polydimethylsiloxane microfluidic chip. The system exploits a low cost linearly variable optical density (OD) filter to reduce the dynamic range of the signal and to increase its signal-to-noise ratio. We present a performance comparison between the μSFC and commercial machines for the label free characterization of polymeric beads with different diameters and refractive indices. In contrast to FCM and FACS, the μSFC yields size estimates linearly correlated with nominal particle sizes (R² = 0.99) and quantitative estimates of particle refractive indices. The feasibility of using the μSFC for the characterization of biological samples is demonstrated by analyzing a population of monocytes identified based on the morphology of a peripheral blood mononuclear cells sample, which yields values in agreement with the literature. The proposed μSFC combines low setup requirements with high performance, and has great potential for integration within other lab-on-chip systems for multi-parametric cell analysis and for next-generation point-of-care diagnostic applications.

Monocyte Distribution Width (MDW) as a biomarker of sepsis: An evidenced-based laboratory medicine approach

Monocyte Distribution Width (MDW) is a new generation cell blood count parameter providing a measure of monocyte anisocytosis. In the last decades, it has emerged as a reliable biomarker of sepsis in the acute setting, especially emergency department, and intensive care unit. MDW has several advantages over commonly used sepsis biomarkers, including low-cost, ease and speed of measurement. The clinical usefulness of MDW has been established in several studies and some clinical laboratory medicines have already implemented it in their routine. In this article, we describe the analytical and clinical features of MDW to guide its appropriate use in clinical practice by integrating the research evidence with real-world laboratory experience. The proper use of a biomarker is critical for improving patients' care and outcome as well as ensuring healthcare quality.

Biomarkers of Sepsis

Sepsis is a highly complex disease caused by a deregulated host's response to infection [...].

Deciphering the role of monocyte and monocyte distribution width (MDW) in COVID-19: an updated systematic review and meta-analysis

The SARS-CoV-2 infection is characterized by both systemic and organ hyper-thromboinflammation, with a clinical course ranging from mild up-to critical systemic dysfunction and death. In patients with coronavirus disease 2019 (COVID-19) the monocyte/macrophage population is deeply involved as both trigger and target, assuming the value of useful diagnostic/prognostic marker of innate cellular immunity. Several studies correlated morphological and immunophenotypic alterations of circulating monocytes with clinical outcomes in COVID-19 patients, concluding that monocyte distribution width (MDW) may retain clinical value in stratifying the risk of disease worsening. Through an electronic search in Medline and Scopus we performed an updated literature review and meta-analysis aimed to explore the association between increased MDW levels and illness severity in COVID-19 patients, deciphering role(s) and function(s) of monocytes in the harmful network underlining SARS-CoV-2 infection. We found that significantly elevated MDW values were frequently present in COVID-19 patients who developed unfavorable clinical outcomes, compounded by a significant association between monocyte anisocytosis and SARS-CoV-2 outcomes. These findings suggest that blood MDW index and its scatter plot could represent useful routine laboratory tools for early identification of patients at higher risk of unfavorable COVID-19 and for monitoring the progression of viral infection, clinical outcomes, and therapeutic efficacy throughout hospitalization. According to this evidence, therapeutic decisions in patients with SARS-CoV-2 infection could benefit from monitoring MDW value, with administration of drugs limiting thrombo-inflammation due to monocyte hyper-activation in patients with severe/critical COVID-19 disease.

Recent advances in laboratory hematology reflected by a decade of CCLM publications

On the occasion of the 60th anniversary of Clinical Chemistry and Laboratory Medicine (CCLM) we present a review of recent developments in the discipline of laboratory hematology as these are reflected by papers published in CCLM in the period 2012–2022. Since data on CCLM publications from 1963 to 2012 are also available, we were able to make a comparison between the two periods. This interestingly revealed that the share of laboratory hematology papers has steadily increased and reached now 16% of all papers published in CCLM. It also became evident that blood coagulation and fibrinolysis, erythrocytes, platelets and instrument and method evaluation constituted the ‘hottest’ topics with regard to number of publications. Some traditional, characteristic CCLM categories like reference intervals, standardization and harmonization, were more stable and probably will remain so in the future. With the advent of important newer topics, like new coagulation assays and drugs and cell population data generated by hematology analyzers, laboratory hematology is anticipated to remain a significant discipline in CCLM publications.

Monocyte Distribution Width (MDW) as an Early Investigational Marker for the Diagnosis of Sepsis in an Emergency Department of a Tertiary Care Hospital in North India

Background Sepsis is an emergency state in response to an infectious process ultimately leading to multiorgan dysfunction and death. There is an urgent need for sepsis detection methods, especially in emergency settings. To fill this gap, monocyte distribution width (MDW) was studied as an early indicator of sepsis. Aim To evaluate MDW as an early marker of sepsis. Material and methods This was a prospective observational study including critically ill adult patients who presented to the emergency department. MDW was measured using a DxH 900 Hematology Analyser (Beckman Coulter Inc., Miami, FL). Abnormal MDW (>20.0) was considered a predictor of sepsis. Results A total of 148 patients were included and categorized according to the Sepsis-2 and Sepsis-3 criteria, as having sepsis (25.6%), sepsis with shock (21.6%), and non-sepsis (52.8%). In patients with sepsis with and without shock, MDW was 28.28 ± 9.20 and 28.02 ± 9.01, respectively, significantly higher than in patients without sepsis (p < 0.001). The diagnostic accuracy value of MDW testing for early sepsis detection was highly significant (0.74, p < 0.000). Conclusion MDW can be used as a marker for the early prediction of sepsis.

Reliability of predictive models to support early decision making in the emergency department for patients with confirmed diagnosis of COVID-19: the Pescara Covid Hospital score

Background

The hospital management of patients diagnosed with COVID-19 can be hampered by heterogeneous characteristics at entry into the emergency department. We aimed to identify demographic, clinical and laboratory parameters associated with higher risks of hospitalisation, oxygen support, admission to intensive care and death, to build a risk score for clinical decision making at presentation to the emergency department.

Methods

We carried out a retrospective study using linked administrative data and laboratory parameters available in the initial phase of the pandemic at the emergency department of the regional reference hospital of Pescara, Abruzzo, Italy, March–June 2020. Logistic regression and Cox modelling were used to identify independent predictors for risk stratification. Validation was carried out collecting data from an extended timeframe covering other variants of concern, including Alpha (December 2020–January 2021) and Delta/Omicron (January–March 2022).

Results

Several clinical and laboratory parameters were significantly associated to the outcomes of interest, independently from age and gender. The strongest predictors were: for hospitalisation, monocyte distribution width ≥ 22 (4.09; 2.21–7.72) and diabetes (OR = 3.04; 1.09–9.84); for oxygen support: saturation < 95% (OR = 11.01; 3.75–41.14), lactate dehydrogenase≥237 U/L (OR = 5.93; 2.40–15.39) and lymphocytes< 1.2 × 10³/μL (OR = 4.49; 1.84–11.53); for intensive care, end stage renal disease (OR = 59.42; 2.43–2230.60), lactate dehydrogenase≥334 U/L (OR = 5.59; 2.46–13.84), D-dimer≥2.37 mg/L (OR = 5.18; 1.14–26.36), monocyte distribution width ≥ 25 (OR = 3.32; 1.39–8.50); for death, procalcitonin≥0.2 ng/mL (HR = 2.86; 1.95–4.19) and saturation < 96% (HR = 2.74; 1.76–4.28). Risk scores derived from predictive models using optimal thresholds achieved values of the area under the curve between 81 and 91%. Validation of the scoring algorithm for the evolving virus achieved accuracy between 65 and 84%.

Conclusions

A set of parameters that are normally available at emergency departments of any hospital can be used to stratify patients with COVID-19 at risk of severe conditions. The method shall be calibrated to support timely clinical decision during the first hours of admission with different variants of concern.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08421-4.

Diagnostic and Prognostic Value of Monocyte Distribution Width in Sepsis

Monocyte distribution width (MDW) is a blood monocyte morphological parameter that can be easily detected by an automated hemocyte analyzer and can provide clinicians with important information about cell volume variability in peripheral blood monocyte populations. The United States' Food and Drug Administration and Conformite Europeenne have both been cleared for their clinical application in the detection of sepsis and developing sepsis in adult patients in the emergency department (ED). Recently, MDW has been found to have an early diagnosis and predictive value for sepsis in neonates and COVID-19 patients. Here, we summarize the findings of the studies investigating the clinical application of MDW in sepsis. Under different stimuli, especially in infectious diseases, the activation of innate immunity is the host's first defense mechanism, and the change in monocyte volume is considered an early indicator reflecting the state of activation of innate immunity. Pivotal study data from a large multicenter patient cohort showed that abnormal MDW at presentation increases the odds of sepsis, considering the combination of MDW and White Blood Cell Count (WBC) as part of a standard sepsis assessment protocol for ED, which may increase the sensitivity and specificity of sepsis diagnosis. Meanwhile, MDW shares a diagnostic performance comparable to that of conventional biomarkers (C-reactive protein and procalcitonin) in sepsis. In addition, some evidence suggests that increased MDW, both in adults and neonates, may be associated with unfavorable short- and long-term outcomes, which indicates its prognostic value in sepsis. Taken together, MDW is a parameter of increased morphological variability of monocytes in response to infection, and numerous studies have shown that MDW could be used as a valuable diagnostic and prognostic index in patients with sepsis or suspected sepsis.

Monocyte distribution width and the fighting action to neutralize sepsis (FANS) score for sepsis prediction in emergency department

BACKGROUND AND AIMS

The aim of this study was to evaluate the diagnostic accuracy of sepsis markers and to develop a multiparametric score, using demographic and clinical variables as well as laboratory parameters to predict sepsis in patients admitted in the ED with suspected symptoms.

MATERIALS AND METHODS

Patients with clinical presentation of suspected sepsis were enrolled in the ED of San Donato Hospital in Arezzo between September 2019 and May 2020. Anagraphic, anamnestic, clinical and laboratory data were collected for all subjects. PCT, MDW, WBC, MPV and BT were utilised to formulate FANS score.

RESULTS

The AUC of the FANS score, PCT, MDW and CRP was 0.87, 0.80, 0.77 and 0.71, respectively, when used to predict sepsis in all 308 subjects. Instead, the AUC of the FANS (Fighting Action To Neutralize Sepsis) score, PCT, MDW and CRP was 0.93, 0.84, 0.83 and 0.77, respectively, when used to predict sepsis excluding subjects with infection (clinically classified as the Infections group).

CONCLUSIONS

The results obtained with PCT, PCR and MDW confirm the results of these markers for the identification of sepsis obtained from other studies. The multiparametric approach, obtained from the statistical study of the parameters using binary logistic regression, identified those PCT, WBC, MPV, BT and MDW as the most significant and effective clinical classifiers for diagnosing sepsis.

The Value of a Complete Blood Count (CBC) for Sepsis Diagnosis and Prognosis

Sepsis represents an important global health burden due to its high mortality and morbidity. The rapid detection of sepsis is crucial in order to prevent adverse outcomes and reduce mortality. However, the diagnosis of sepsis is still challenging and many efforts have been made to identify reliable biomarkers. Unfortunately, many investigated biomarkers have several limitations that do not support their introduction in clinical practice, such as moderate diagnostic and prognostic accuracy, long turn-around time, and high-costs. Complete blood count represents instead a precious test that provides a wealth of information on individual health status. It can guide clinicians to early-identify patients at high risk of developing sepsis and to predict adverse outcomes. It has several advantages, being cheap, easy-to-perform, and available in all wards, from the emergency department to the intensive care unit. Noteworthy, it represents a first-level test and an alteration of its parameters must always be considered within the clinical context, and the eventual suspect of sepsis must be confirmed by more specific investigations. In this review, we describe the usefulness of basic and new complete blood count parameters as diagnostic and prognostic biomarkers of sepsis.

Independent Validation of Sepsis Index for Sepsis Screening in the Emergency Department

(1) Background: The early detection of sepsis is still challenging, and there is an urgent need for biomarkers that could identify patients at a high risk of developing it. We recently developed an index, namely the Sepsis Index (SI), based on the combination of two CBC parameters: monocyte distribution width (MDW) and mean monocyte volume (MMV). In this study, we sought to independently validate the performance of SI as a tool for the early detection of patients at a high risk of sepsis in the Emergency Department (ED). (2) Methods: We enrolled all consecutive patients attending the ED with a request of the CBC. MDW and MMV were measured on samples collected in K3-EDTA tubes on the UniCel DxH 900 haematology analyser. SI was calculated based on the MDW and MMV. (3) Results: We enrolled a total of 703 patients stratified into four subgroups according to the Sepsis-2 criteria: control (498), infection (105), SIRS (52) and sepsis (48). The sepsis subgroup displayed the highest MDW (median 27.5, IQR 24.6–32.9) and SI (median 1.15, IQR 1.05–1.29) values. The ROC curve analysis for the prediction of sepsis showed a good and comparable diagnostic accuracy of the MDW and SI. However, the SI displayed an increased specificity, positive predictive value and positive likelihood ratio in comparison to MDW alone. (4) Conclusions: SI improves the diagnostic accuracy of MDW for sepsis screening.