Cytomorphometric Neutrophil and Monocyte Markers May Strengthen the Diagnosis of Sepsis

Development and validation of a machine learning-based interpretable model for predicting sepsis by complete blood cell parameters

Background

Sepsis, a severe infectious disease, carries a high mortality rate. Early detection and prompt treatment are crucial for reducing mortality and improving prognosis. The aim of this research is to develop a clinical prediction model using machine learning algorithms, leveraging complete blood cell (CBC) parameters, to detect sepsis at an early stage.

Methods

The study involved 572 patients admitted to West China Hospital of Sichuan University between July 2020 and September 2021. Among them, 215 were diagnosed with sepsis, while 357 had local infections. Demographic information was collected, and 57 CBC parameters were analyzed to identify potential predictors using techniques such as the Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost). The prediction model was built using Logistic Regression and evaluated for diagnostic specificity, discrimination, and clinical applicability including metrics such as the area under the curve (AUC), calibration curve, clinical impact curve, and clinical decision curve. Additionally, the model's diagnostic performance was assessed on a separate validation cohort. Shapley's additive explanations (SHAP), and breakdown (BD) profiles were used to explain the contribution of each variable in predicting the outcome.

Results

Among all the machine learning methods' prediction models, the LASSO-based model (λ = min) demonstrated the highest diagnostic performance in both the discovery cohort (AUC = 0.9446, P < 0.001) and the validation cohort (AUC = 0.9001, P < 0.001). Furthermore, upon local analysis and interpretation of the model, we demonstrated that LY-Z, MO-Z, and PLT-I had the most significant impact on the outcome.

Conclusions

The predictive model based on CBC parameters can be utilized as an effective approach for the early detection of sepsis.

The Role of New Morphological Parameters Provided by the BC 6800 Plus Analyzer in the Early Diagnosis of Sepsis

BACKGROUND

Late diagnosis of sepsis is associated with adverse consequences and high mortality rate. The aim of this study was to evaluate the diagnostic value of hematologic research parameters, that reflect the cell morphology of blood cells, available on the BC 6800 plus automated analyzer (Mindray) for the early detection of sepsis.

MATERIALS AND METHODS

A complete blood count (CBC) was performed by Mindray BC 6800 Plus Analyzer in 327 patients (223 with a confirmed diagnosis of sepsis following sepsis-3 criteria, 104 without sepsis), admitted at the Intensive Care Unit of the Novara's Hospital (Italy) and in 56 patients with localized infection.

RESULTS

In univariate logistic regression, age, Hb, RDW, MO#, NMR, NeuX, NeuY, NeuZ, LymX, MonX, MonY, MonZ were associated with sepsis (p < 0.005). In multivariate analysis, only RDW, NeuX, NeuY, NeuZ, MonX and MonZ were found to be independent predictors of sepsis (p < 0.005). Morphological research parameters are confirmed to be predictors of sepsis even when analyzing the group with localized infection.

CONCLUSIONS

In addition to already established biomarkers and basic CBC parameters, new morphological cell parameters can be a valuable aid in the early diagnosis of sepsis at no additional cost.

Leucocyte volume, conductivity, and scatter at presentation in COVID-19 patients

Background

In COVID-19 patients, besides changes in leucocyte count, morphological abnormalities of circulating blood cells have been reported.

Aim

This study aims to investigate the relationship between the morphological and functional properties of leucocytes and the severity of the disease in COVID-19 patients.

Materials and Methods

Blood samples were collected from COVID-19 patients (n = 130) at the time of admission. The patients were stratified according to the comorbidity, age, LDH, lymhocyte count score as mild, moderate, and severe. Complete blood count and the cell population data were analyzed by the Volume, conductivity, scatter (VCS) technology on Beckman Coulter LH-780 hematology analyzer. Kruskal-Wal'lis test was used to assess the differences between the groups with subsequent Bonferroni correction.

Results

Neutrophil count was increased, and lymphocyte count was decreased in severe patients compared to mild patients. The increase in the percent of neutrophils and the neutrophil/lymphocyte ratio in the severe patient group was significant in comparison to both the moderate and the mild group. The dispersion of the neutrophil volume and conductivity showed significant changes depending on the severity of the disease. The lymphocyte volume, lymphocyte-volume-SD and lymphocyte-conductivity as well as the monocyte-volume and monocyte-volume-SD were significantly increased in severe patients in comparison to mild patients. The increase of lymphocyte and monocyte volume in severe patients was also significant in comparison to moderate patients.

Conclusions

COVID-19 infection leads to important changes in cell population data of leucocytes. The volumetric changes in lymphocytes and monocytes are related to the severity of the disease.

Evaluation of the Diagnostic Value of Cell Population Data in Sepsis in Comparison to Localized Infection, Chronic Inflammation, and Noninfectious Inflammation Cases

INTRODUCTION

Sepsis, defined as an increase of 2 points or more in the sequential organ failure assessment score, is a life-threatening organ dysfunction caused by the dysregulated host response to infection. Volume-conductivity-scatter (VCS) parameters of cell counters which are known as cell population data (CPD) have been suggested to be beneficial in diagnosing sepsis. We aimed to evaluate the diagnostic value of CPD parameters in sepsis in comparison to nonsystemic infection cases (NSI) and non-infectious acute and chronic inflammatory conditions.

MATERIALS AND METHODS

We prospectively included four groups of patients" data: sepsis (n = 66), localized infection (pneumonia, n = 59), chronic inflammation (rheumatoid arthritis, n = 92) and noninfectious inflammation (coronary artery bypass graft operation, n = 56) groups, according to their clinical status and laboratory results. Samples for cell counting and serum markers were collected on the same day of culture collection. VCS parameters were measured by Unicel DxH800 Coulter Cellular Analyzer (Beckman Coulter, USA).

RESULTS

Mean neutrophil volume (MN-V-NE), was highest in the sepsis group [155(149-168)] compared to the localized infection [148(140-158)], chronic inflammation [144.5(142-149)] and noninfectious inflammation [149(145.2-153.7)] (P = 0.001, P < 0.001, P < 0.001, respectively). Neutrophil volume SD (SD-V-NE) was higher in the sepsis [21(18.8-23.7)], significantly differentiating sepsis from other groups. The area under curves of procalcitonin and hs-C-reactive protein were 0.846 and 0.837, respectively, in the receiver-operating characteristic curves (ROC) . CPD combinations, (SD-V NE + SD-V LY + SD-V MO), (SD-V NE + SD-V MO), and (MN-V NE + SD-V NE + SD-C LY + SD-V MO) had greater AUC values than procalcitonin's.

CONCLUSION

VCS parameters might be promising for differentiating sepsis and non-sepsis cases. Additionally, obtaining these data routinely makes their prospects promising without any additional cost and time.

Application of Digital Holographic Microscopy to Analyze Changes in T-Cell Morphology in Response to Bacterial Challenge

Quantitative phase imaging (QPI) is a non-invasive, label-free technique used to detect aberrant cell morphologies caused by disease, thus providing a useful diagnostic approach. Here, we evaluated the potential of QPI to differentiate specific morphological changes in human primary T-cells exposed to various bacterial species and strains. Cells were challenged with sterile bacterial determinants, i.e., membrane vesicles or culture supernatants, derived from different Gram-positive and Gram-negative bacteria. Timelapse QPI by digital holographic microscopy (DHM) was applied to capture changes in T-cell morphology over time. After numerical reconstruction and image segmentation, we calculated single cell area, circularity and mean phase contrast. Upon bacterial challenge, T-cells underwent rapid morphological changes such as cell shrinkage, alterations of mean phase contrast and loss of cell integrity. Time course and intensity of this response varied between both different species and strains. The strongest effect was observed for treatment with S. aureus-derived culture supernatants that led to complete lysis of the cells. Furthermore, cell shrinkage and loss of circular shape was stronger in Gram-negative than in Gram-positive bacteria. Additionally, T-cell response to bacterial virulence factors was concentration-dependent, as decreases in cellular area and circularity were enhanced with increasing concentrations of bacterial determinants. Our findings clearly indicate that T-cell response to bacterial stress depends on the causative pathogen, and specific morphological alterations can be detected using DHM.

Monocyte distribution width as part of a broad pragmatic sepsis screen in the emergency department

STUDY OBJECTIVE

Enhancement of a routine complete blood count (CBC) for detection of sepsis in the emergency department (ED) has pragmatic utility for early management. This study evaluated the performance of monocyte distribution width (MDW) alone and in combination with other routine CBC parameters as a screen for sepsis and septic shock in ED patients.

METHODS

A prospective cohort analysis of adult patients with a CBC collected at an urban ED from January 2020 through July 2021. The performance of MDW, white blood count (WBC) count, and neutrophil-to-lymphocyte-ratio (NLR) to detect sepsis and septic shock (Sepsis-3 Criteria) was evaluated using diagnostic performance measures.

RESULTS

The cohort included 7952 ED patients, with 180 meeting criteria for sepsis; 43 with septic shock and 137 without shock. MDW was highest for patients with septic shock (median 24.8 U, interquartile range [IQR] 22.0-28.1) and trended downward for patients with sepsis without shock (23.9 U, IQR 20.2-26.8), infection (20.4 U, IQR 18.2-23.3), then controls (18.6 U, IQR 17.1-20.4). In isolation, MDW detected sepsis and septic shock with an area under the receiver operator characteristic curve (AUC) of 0.80 (95% confidence interval [CI] 0.77-0.84) and 0.85 (95% CI 0.80-0 .91), respectively. Optimal performance was achieved in combination with WBC count and NLR for detection of sepsis (AUC 0.86, 95% CI 0.83-0.89) and septic shock (0.86, 95% CI 0.80-0.92).

CONCLUSION

A CBC differential panel that includes MDW demonstrated strong performance characteristics in a broad ED population suggesting pragmatic value as a rapid screen for sepsis and septic shock.

Investigating Morphological Changes of T-lymphocytes after Exposure with Bacterial Determinants for Early Detection of Septic Conditions

Sepsis is a leading cause of morbidity and mortality, annually affecting millions of people worldwide. Immediate treatment initiation is crucial to improve the outcome but despite great progress, early identification of septic patients remains a challenge. Recently, white blood cell morphology was proposed as a new biomarker for sepsis diagnosis. In this proof-of-concept study, we aimed to investigate the effect of different bacteria and their determinants on T-lymphocytes by digital holographic microscopy (DHM). We hypothesize that species- and strain-specific morphological changes occur, which may offer a new approach for early sepsis diagnosis and identification of the causative agent. Jurkat cells as a model system were exposed to different S. aureus or E. coli strains either using sterile determinants or living bacteria. Time-lapse DHM was applied to analyze cellular morphological changes. There were not only living bacteria but also membrane vesicles and sterile culture supernatant-induced changes of cell area, circularity, and mean phase contrast. Interestingly, different cellular responses occurred depending on both the species and strain of the causative bacteria. Our findings suggest that investigation of T-lymphocyte morphology might provide a promising tool for the early identification of bacterial infections and possibly discrimination between different causative agents. Distinguishing gram-positive from gram-negative infection would already offer a great benefit for the proper administration of antibiotics.

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.

Reviewing the value of leukocytes cell population data (CPD) in the management of sepsis

Sepsis is a medical emergency that describes the body's systemic immune response to an infection and can lead to end-stage organic dysfunction and death. Despite the advances in understanding the pathophysiology of this syndrome and therapies, sepsis remains one of the leading causes of morbidity and mortality in critically ill patients. Early diagnosis and rapid intervention are essential to improve outcomes, which inspired the concept "golden hour," during which the correction of shock and organic dysfunction can improve the patients' outcomes. But the initial presentation of sepsis is often nonspecific and its severity is difficult to assess. Anomalies in temperature, heart and respiratory rates and leukocyte counts are manifestations of systemic inflammatory response syndrome (SIRS). Diagnosis, management and follow-up of patients with sepsis remains a challenge, and diverse biomarkers have been proposed for the timely diagnosis and prognosis of septic patients: lactic acid, procalcitonin (PCT), C-reactive protein, immature granulocytes. The host's initial response to infection is a humoral, cellular and neuroendocrine reaction to infection, and leukocytes interact with endothelial cells. The new generation of hematological analyzers incorporates technological innovations allowing to expand the information derived from the complete blood count: new leukocyte derived parameters are emerging as potentially useful markers in different clinical situations. Additional research parameters cell population data (CPD), characterizing different leukocyte populations have become available, and preliminary observations suggest their utility in the diagnosis of sepsis. This review emphasizes the value of CPD, reported by modern cellular counters for early recognition of sepsis, and therefore the potential improvement in patient outcomes.