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

Construction of the prediction model for multiple myeloma based on machine learning

INTRODUCTION

The global burden of multiple myeloma (MM) is increasing every year. Here, we have developed machine learning models to provide a reference for the early detection of MM.

METHODS

A total of 465 patients and 150 healthy controls were enrolled in this retrospective study. Based on the variable screening strategy of least absolute shrinkage and selection operator (LASSO), three prediction models, logistic regression (LR), support vector machine (SVM), and random forest (RF), were established combining complete blood count (CBC) and cell population data (CPD) parameters in the training set (210 cases), and were verified in the validation set (90 cases) and test set (165 cases). The performance of each model was analyzed using receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis (DCA). Accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the ROC curve (AUC) were applied to evaluate the models. Delong test was used to compare the AUC of the models.

RESULTS

Six parameters including RBC (1012/L), RDW-CV (%), IG (%), NE-WZ, LY-WX, and LY-WZ were screened out by LASSO to construct the model. Among the three models, the AUC of RF model in the training set, validation set, and test set were 0.956, 0.892, and 0.875, which were higher than those of LR model (0.901, 0.849, and 0.858) and SVM model (0.929, 0.868, and 0.846). Delong test showed that there were significant differences among the models in the training set, no significant differences in the validation set, and significant differences only between SVM and RF models in the test set. The calibration curve and DCA showed that the three models had good validity and feasibility, and the RF model performed best.

CONCLUSION

The proposed RF model may be a useful auxiliary tool for rapid screening of MM patients.

Detection of blasts using flags and cell population data rules on Beckman Coulter DxH 900 hematology analyzer in patients with hematologic diseases

OBJECTIVES

White blood cell (WBC)-related flags are essential for detecting abnormal cells including blasts in automated hematology analyzers (AHAs). Cell population data (CPD) may characterize each WBC population, and customized CPD rules can be also useful for detecting blasts. We evaluated the performance of WBC-related flags, customized CPD rules, and their combination for detecting blasts on the Beckman Coulter DxH 900 AHA (DxH 900, Beckman Coulter, Miami, Florida, USA).

METHODS

In a total of 239 samples from patients with hematologic diseases, complete blood count on DxH 900 and manual slide review (MSR) were conducted. The sensitivity, specificity, and efficiency of the five WBC-related flags, nine customized CPD rules, and their combination were evaluated for detecting blasts, in comparison with MSR.

RESULTS

Blasts were detected by MSR in 40 out of 239 (16.7 %) samples. The combination of flags and CPD rules showed the highest sensitivity compared with each of flags and CPD rules for detecting blasts (97.5 vs. 72.5 % vs. 92.5 %). Compared with any flag, the combination of flags and CPD rules significantly reduced false-negative samples from 11 to one for detecting blasts (27.5 vs. 2.5 %, p=0.002).

CONCLUSIONS

This is the first study that evaluated the performance of both flags and CPD rules on DxH 900. The customized CPD rules as well as the combination of flags and CPD rules outperformed WBC-related flags for detecting blasts on DxH 900. The customized CPD rules can play a complementary role for improving the capability of blast detection on DxH 900.

Time-dependent changes in cell population data obtained using Sysmex XN-series hematology analyzer in bacterial infections

BACKGROUND

Time-dependent changes in cell populations during acute bacterial infections remain unclear. We assessed time-dependent changes in fluorescent light intensity of the neutrophil area (NE-SFL) and fluorescent light distribution width index of the neutrophil area (NE-WY) and their association with sepsis and bacteremia.

METHODS

Patients with acute bacterial infections were enrolled in this prospective, observational cohort study. Blood samples were collected from all patients at the onset of bacterial infections (day 0) and on days 1 and 3. Microbiological evaluation included the examination of blood bacterial load using PCR. Cell population data were assessed using an automated hematology analyzer (Sysmex series XN-2000).

RESULTS

Forty-three participants with acute bacterial infections were enrolled in the study. Twenty-five participants developed definite sepsis. All the participants improved after the onset of infection. NE-WY levels showed significant time-dependent changes in participants with sepsis, peaking on day 0 and significantly decreasing until day 3, whereas these changes were not statistically significant for NE-SFL. A significant correlation with the Sequential Organ Failure Assessment score was observed with NE-WY and NE-SFL in the entire cohort on days 0 and 1. However, only NE-WY showed a significant correlation with blood bacterial load on days 0 and 1.

CONCLUSION

This study demonstrated that NE-WY elevation in sepsis peaked earlier than NE-SFL, which may partly reflect the early bacterial invasion into circulation. These findings advocate caution in interpreting cell population data values as sepsis biomarkers and propose the potential of NE-WY as a therapeutic indicator.

Exploring the Relationship between Plasma Adiponectin, Gender, and Underlying Diseases in Severe Illness

Adiponectin is low in obesity, plays a crucial role in metabolic health, and, moreover, possesses immunoregulatory properties. However, studies examining its levels in patients with systemic inflammatory response syndrome (SIRS) or sepsis have yielded conflicting results. While females typically have higher systemic adiponectin levels than males, research on sex-specific associations in this context is limited. In this study of 156 SIRS/sepsis patients, including those with liver cirrhosis, we aimed to explore the relationship between plasma adiponectin, body mass index (BMI), gender, disease severity, and underlying etiological conditions. Our findings revealed that patients with liver cirrhosis, who are susceptible to infections, exhibited elevated circulating adiponectin levels, irrespective of sex. When excluding cirrhosis patients, plasma adiponectin levels were similar between male SIRS/sepsis patients and controls but lower in female patients compared to female controls. Plasma adiponectin was inversely related to BMI in female but not male patients. Further analysis within the non-cirrhosis subgroup demonstrated no significant differences in adiponectin levels between sexes among SIRS, sepsis, and septic shock patients. Ventilation, dialysis, and vasopressor therapy had no discernible impact on adiponectin levels in either sex. A negative correlation between adiponectin and C-reactive protein (CRP) existed in males only. Notably, patients with pancreatitis showed the lowest plasma adiponectin concentrations, although sex-specific differences were not significant. Infection with Gram-negative or Gram-positive bacteria had minimal effects on plasma adiponectin levels in both sexes. However, infection with the severe acute respiratory syndrome coronavirus type 2 led to decreased adiponectin levels in females exclusively. Multivariate analysis considering all factors affecting plasma adiponectin levels in males or females identified BMI in females and CRP levels in males to predict plasma adiponectin levels in SIRS/sepsis patients. Additionally, our study observed a trend where the 25 patients who did not survive had higher plasma adiponectin levels, particularly among males. In summary, our investigation highlights the influence of underlying diseases and sex on plasma adiponectin levels in SIRS/sepsis patients, shedding light on potential implications for disease management and prognosis.

It's in the blood: a review of the hematological system in SARS-CoV-2-associated COVID-19

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an unprecedented global healthcare crisis. While SARS-CoV-2-associated COVID-19 affects primarily the respiratory system, patients with COVID-19 frequently develop extrapulmonary manifestations. Notably, changes in the hematological system, including lymphocytopenia, neutrophilia and significant abnormalities of hemostatic markers, were observed early in the pandemic. Hematological manifestations have since been recognized as important parameters in the pathophysiology of SARS-CoV-2 and in the management of patients with COVID-19. In this narrative review, we summarize the state-of-the-art regarding the hematological and hemostatic abnormalities observed in patients with SARS-CoV-2-associated COVID-19, as well as the current understanding of the hematological system in the pathophysiology of acute and chronic SARS-CoV-2-associated COVID-19.

The Clinical Performance of Cell Population Data for Diagnosis of Bloodstream Infection in Cancer Patients

Background Bloodstream infection (BSI) induces a change in the number and morphology of blood cells. In this study, we compared cell population data (CPD) parameters between cancer patients with or without BSI to determine whether these parameters could serve as biomarkers of BSI. Methods Between April and June 2021, 43 BSI-negative and 22 BSI-positive cancer patients were enrolled in this study. We compared 18 CPD parameters and biomarkers between cancer patients with BSI-positive and BSI-negative. Results There were significant differences in the levels of several CPD parameters, including MO-WZ (p=0.040), MO-X (p<0.01), MO-Y (p=0.012), NE-SFL (p<0.01), and NE-WX (p=0.037), but not C-reactive protein (p=0.347) and procalcitonin (p=0.237) between BSI-positive and BSI-negative patients. The areas under the receiver-operating characteristic curves (AUCs) were above 0.7 for MO-X (0.762; 95% confidence intervals (CI): 0.624-0.901), NE-SFL (0.766; 95% CI: 0.625-0.880). And LY-WY (p=0.024) showed a significant difference between gram-negative and gram-positive BSI patients with high AUC (0.883; 95% CI: 0.703-1). Conclusion CPD parameters (MO-X and NE-SFL) provide additional information for discriminating between BSI-negative and BSI-positive BSI. And LY-WY provides useful information for discriminating between cancer patients with gram-negative BSI and gram-positive BSI.

Beyond the routine CBC: machine learning and statistical analyses identify research CBC parameter associations with myelodysplastic syndromes and specific underlying pathogenic variants

AIMS

Given the time, expense and clinical expertise required for a myelodysplastic syndrome (MDS) diagnosis, there is a clear need for a cost-effective screening laboratory test that can rapidly and accurately distinguish patients with cytopenias related to MDS from other causes.

METHODS

We measured conventional and research use only complete blood cell (CBC) parameters using the Sysmex XN-series haematology analyser in 102 MDS patients (70 patients with active MDS and 32 patients in remission), 43 patients with cytopenia without morphological evidence of MDS and 484 age-adjusted controls. A variety of algorithms, including random forest machine learning, were used to construct parameter-based models to predict the presence of MDS using both CBC and molecular data or CBC data alone and correlated individual pathogenic variants/genetic pathways with CBC parameters changes.

RESULTS

Using the CBC parameters alone, our predictive model for active MDS showed a 0.86 receiver operating characteristic curve (ROC)/area under the ROC curve (AUC), with 0.87 sensitivity and 0.72 specificity; with the addition of the molecular and demographic status, the ROC/AUC improved to 0.93, sensitivity to 0.89 and specificity to 0.84. The most discriminatory MDS parameters were reflective of dysplastic neutrophil morphology, red cell count fragmentation and degree of platelet immaturity. Specific patterns of parameters were associated with individual gene pathogenic variants or affected pathways.

CONCLUSIONS

CBC research parameters can be used as an adjunct to the haematological workup of cytopenia(s) to help screen for patients with high likelihood of MDS.

Machine learning pipeline for blood culture outcome prediction using Sysmex XN-2000 blood sample results in Western Australia

BACKGROUND

Bloodstream infections (BSIs) are a significant burden on the global population and represent a key area of focus in the hospital environment. Blood culture (BC) testing is the standard diagnostic test utilised to confirm the presence of a BSI. However, current BC testing practices result in low positive yields and overuse of the diagnostic test. Diagnostic stewardship research regarding BC testing is increasing, and becoming more important to reduce unnecessary resource expenditure and antimicrobial use, especially as antimicrobial resistance continues to rise. This study aims to establish a machine learning (ML) pipeline for BC outcome prediction using data obtained from routinely analysed blood samples, including complete blood count (CBC), white blood cell differential (DIFF), and cell population data (CPD) produced by Sysmex XN-2000 analysers.

METHODS

ML models were trained using retrospective data produced between 2018 and 2019, from patients at Sir Charles Gairdner hospital, Nedlands, Western Australia, and processed at Pathwest Laboratory Medicine, Nedlands. Trained ML models were evaluated using stratified 10-fold cross validation.

RESULTS

Two ML models, an XGBoost model using CBC/DIFF/CPD features with boruta feature selection (BFS) , and a random forest model trained using CBC/DIFF features with BFS were selected for further validation after obtaining AUC scores of [Formula: see text] and [Formula: see text] respectively using stratified 10-fold cross validation. The XGBoost model obtained an AUC score of 0.76 on a internal validation set. The random forest model obtained AUC scores of 0.82 and 0.76 on internal and external validation datasets respectively.

CONCLUSIONS

We have demonstrated the utility of using an ML pipeline combined with CBC/DIFF, and CBC/DIFF/CPD feature spaces for BC outcome prediction. This builds on the growing body of research in the area of BC outcome prediction, and provides opportunity for further research.

Blood Biomarkers of Neonatal Sepsis with Special Emphasis on the Monocyte Distribution Width Value as an Early Sepsis Index

Background and Objectives: Early detection of neonatal sepsis is critical because it is potentially fatal. Therefore, sepsis biomarkers of sufficient sensitivity and specificity are needed. This study aimed to evaluate the utility of peripheral blood parameters as neonatal sepsis biomarkers and the diagnostic performance of the monocyte distribution width (MDW) in sepsis in a neonatal intensive care unit. Materials and Methods: A cross-sectional study was conducted from September 2019 to August 2020 at the King Saud University Medical City in Riyadh, Saudi Arabia. Samples were collected and organised as follows: 77 study cases were subdivided into two subgroups (other health complication (49) and sepsis (28)), and there were 70 controls. The causative microorganisms of neonatal sepsis were isolated. Peripheral blood samples were collected from each neonate in an ethylenediaminetetraacetic acid tube for a complete blood count and a leukocyte differential count. Moreover, the receiver operating characteristic (ROC) curve analysis was used to measure the diagnostic performance of the MDW. Results: The haematological parameters and neonatal sepsis cases had a considerable correlation. The MDW was the most significant haematological parameter. The ROC analysis of the MDW demonstrated that the area under the curve was 0.89 (95% confidence interval: 0.867 to 0.998) with a sensitivity of 89.3%, a specificity of 88.2%, and a negative predictive value of 97.2% at the cut-off point of 23. Conclusions: The use of haematological parameters is feasible and can be performed rapidly. Neonatal sepsis showed a strong correlation with leukopenia, anaemia, thrombocytopenia, and an elevated MDW value. Moreover, the ROC curve analysis confirmed the high diagnostic ability of the MDW in neonatal sepsis prediction.

Machine learning of cell population data, complete blood count, and differential count parameters for early prediction of bacteremia among adult patients with suspected bacterial infections and blood culture sampling in emergency departments

BACKGROUND

Bacteremia is a life-threatening complication of infectious diseases. Bacteremia can be predicted using machine learning (ML) models, but these models have not utilized cell population data (CPD).

METHODS

The derivation cohort from emergency department (ED) of China Medical University Hospital (CMUH) was used to develop the model and was prospectively validated in the same hospital. External validation was performed using cohorts from ED of Wei-Gong Memorial Hospital (WMH) and Tainan Municipal An-Nan Hospital (ANH). Adult patients who underwent complete blood count (CBC), differential count (DC), and blood culture tests were enrolled in the present study. The ML model was developed using CBC, DC, and CPD to predict bacteremia from positive blood cultures obtained within 4 h before or after the acquisition of CBC/DC blood samples.

RESULTS

This study included 20,636 patients from CMUH, 664 from WMH, and 1622 patients from ANH. Another 3143 patients were included in the prospective validation cohort of CMUH. The CatBoost model achieved an area under the receiver operating characteristic curve of 0.844 in the derivation cross-validation, 0.812 in the prospective validation, 0.844 in the WMH external validation, and 0.847 in the ANH external validation. The most valuable predictors of bacteremia in the CatBoost model were the mean conductivity of lymphocytes, nucleated red blood cell count, mean conductivity of monocytes, and neutrophil-to-lymphocyte ratio.

CONCLUSIONS

ML model that incorporated CBC, DC, and CPD showed excellent performance in predicting bacteremia among adult patients with suspected bacterial infections and blood culture sampling in emergency departments.

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.

Morphological changes in white blood cells in systemic inflammatory response syndrome (SIRS) with and without sepsis: An observational study

Background

This is an observational study which aims to research morphological changes of white blood cells in patients with Systemic Inflammatory Response Syndrome (SIRS) with and without sepsis and evaluate morphological changes in white blood cells as predictors of sepsis.

Methods

Patients aged 18 years or more with SIRS with sepsis and SIRS without sepsis were included and those with haematological disorders or pregnant patients were excluded. A total of 52 patients with SIRS with sepsis and 32 patients of SIRS without sepsis were included. Peripheral blood smear was prepared from the venous blood sample drawn. The presence of toxic granules, cytoplasmic vacuoles, and Dohle bodies in both cases of SIRS with sepsis without sepsis were assessed and it was compared with culture-positive sepsis and shock.

Results

The difference in the presence of toxic granules (55.8% vs. 12.5%; p <0.001), cytoplasmic vacuoles (30.8% vs. 6.3%; p -0.012), and Dohle bodies (17.3% vs. 0%; p = 0.012) was significantly higher in the SIRS with sepsis group, compared to the SIRS without sepsis group. In the subgroup analysis of patients in the sepsis group, it was observed that patients with positive blood culture (9%) had a significantly higher proportion of toxic granules (100% vs. 51.1%; p=0.059), cytoplasmic vacuoles (40% vs. 29.8%; p=0.637) and Dohle bodies (40% vs. 14.9%; p=0.202). However, these differences were not statistically significant.

Conclusion

Toxic granules and cytoplasmic vacuoles in the neutrophils of patients with SIRS with sepsis were found more frequently, compared to patients of SIRS without sepsis. Dohle bodies were found only in patients with sepsis and not in those with SIRS without sepsis.

Predictive value of cell population data with Sysmex XN-series hematology analyzer for culture-proven bacteremia

Background

Cell population data (CPD) parameters related to neutrophils, such as fluorescent light intensity (NE-SFL) and fluorescent light distribution width index (NE-WY), have emerged as potential biomarkers for sepsis. However, the diagnostic implication in acute bacterial infection remains unclear. This study assessed the diagnostic value of NE-WY and NE-SFL for bacteremia in patients with acute bacterial infections, and those associations with other sepsis biomarkers.

Methods

Patients with acute bacterial infections were enrolled in this prospective observational cohort study. For all patients, a blood sample, with at least two sets of blood cultures, were collected at the onset of infection. Microbiological evaluation included examination of the blood bacterial load using PCR. CPD was assessed using Automated Hematology analyzer Sysmex series XN-2000. Serum levels of procalcitonin (PCT), interleukin-6 (IL-6), presepsin, and CRP were also assessed.

Results

Of 93 patients with acute bacterial infection, 24 developed culture-proven bacteremia and 69 did not. NE-SFL and NE-WY were significantly higher in patients with bacteremia than in those without bacteremia (p < 0.005, respectively), and were significantly correlated with the bacterial load determined by PCR (r = 0.384 and r = 0.374, p < 0.005, respectively). To assess the diagnostic value for bacteremia, receiver operating characteristic curve analysis was used. NE-SFL and NE-WY showed an area under the curve of 0.685 and 0.708, respectively, while those of PCT, IL-6, presepsin, and CRP were 0.744, 0.778, 0.685, and 0.528, respectively. Correlation analysis showed that the levels of NE-WY and NE-SFL were strongly correlated with PCT and IL-6 levels.

Conclusion

This study demonstrated that NE-WY and NE-SFL could predict bacteremia in a manner that may be different from that of other indicators. These findings suggest there are potential benefits of NE-WY/NE-SFL in predicting severe bacterial infections.

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.

Prognostic Role of Monocyte Distribution Width, CRP, Procalcitonin and Lactate as Sepsis Biomarkers in Critically Ill COVID-19 Patients

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic and one group of patients has developed a severe form of COVID-19 pneumonia with an urgent need for hospitalization and intensive care unit (ICU) admission. The aim of our study was to evaluate the prognostic role of MDW, CRP, procalcitonin (PCT), and lactate in critically ill COVID-19 patients. The primary outcome of interest is the 28 day mortality of ICU patients with confirmed SARS-CoV-2 infection and sepsis (according to Sepsis 3 criteria with acute change in SOFA score ≥ 2 points). Patients were divided into two groups according to survival on the 28th day after admission to the ICU. Every group was divided into two subgroups (women and men). Nonparametric tests (Mann-Whitney) for variables age, PCT, lactate, and MDW were lower than alpha p < 0.05, so there was a significant difference between survived and deceased patients. The Chi-square test confirmed statistically significant higher values of MDW and lactate in the non-survivor group. We found a significant association between MDW, lactate, procalcitonin, and fatal outcome, higher values were reported in the deceased group.

Monocyte Distribution Width, a Novel Biomarker for Early Sepsis Screening and Comparison with Procalcitonin and C-Reactive Protein

Objectives Monocyte distribution width (MDW) can be used for the early recognition of sepsis. The study compared the diagnostic accuracy of the MDW with two well-known sepsis biomarkers, procalcitonin (PCT) and C-reactive protein (CRP).

Materials and Methods A study was conducted from July 2021 to October 2021, on 111 patients admitted to the Indus Hospital and Health Network. Patients from the ages of 1 to 90 years were enrolled if hospitalized for more than 24 hours for suspected sepsis to avoid inclusion of patients who had short-term stay in the emergency department. According to the Sequential Organ Failure Assessment score, the clinical team did the characterization of cases as with sepsis or without sepsis. SPSS version 24 was used, and the diagnostic accuracy of MDW was assessed and compared using the area under the curves (AUCs) acquired from receiver operating characteristic curves. Pearson's chi-square/Fisher's exact test (as per need) was applied to determine the association. A p-value of less than 0.05 was considered significant.

Results Among 111 patients, 81 (73%) patients were labeled with sepsis and 30 (27%) were without sepsis. We have reported significantly higher MDW, PCT, and CRP levels in septic patients (p < 0.001). The AUC of MDW was comparable with PCT (0.794). Significant cutoff value for the MDW was greater than 20.24 U with 86% sensitivity and 73% specificity.

Conclusion MDW may have a predictive ability similar to PCT and CRP in terms of sepsis and, thus, can be used as a standard parameter for the timely diagnosis of sepsis.

The Value of Peripheral Blood Leukocyte Parameters in the Early Diagnosis and Clinical Prognosis of Sepsis

Background

Early diagnosis of sepsis is the key to timely, targeted treatment. Cell population data (CPD) has been widely used in many diseases, but its predictive value for early diagnosis and the clinical outcome of sepsis remains unclear. Therefore, this paper discusses whether peripheral blood leukocyte parameters can be used as predictive indicators for early diagnosis and the clinical outcome of sepsis.

Methods

A retrospective study of 45 patients with sepsis, 53 patients with nonseptic infections, and 86 healthy check-ups admitted to Gansu Provincial Hospital from January 2021 to June 2022 was done using a hematology analyzer.

Results

The results of LYMPH#, HFLC#, IG#, NE-WX, LY-WX, LY-WY, and MO-WX showed better diagnostic efficiency in the sepsis group and nonseptic infection group. When the seven differential leukocyte parameters were used to establish diagnostic models, the sensitivity and specificity were 82.20% and 77.40%, respectively. Correlation analysis showed that LYMPH# and HFLC# were positively correlated with PCT (P < 0.05). The clinical outcome of sepsis showed that the leukocyte parameters of discharged WBC and LY-X had better predictive efficacy. When the two differential leukocyte parameters were used to establish diagnostic models, the sensitivity and specificity were 90.90% and 100.00%. Cox regression analysis showed that leukocyte parameters of discharged WBC and LY-X were independent predictors of clinical outcomes (P < 0.05).

Conclusion

Leucocyte parameters HFLC#, IG#, NE-WX, LY-WX, LY-WY, and MO-WX had a certain auxiliary effect on the early diagnosis of sepsis leukocyte parameters of discharged WBC and LY-X were independent predictors of clinical outcomes in patients with sepsis. Therefore, peripheral blood leukocyte parameters may have predictive value for early diagnosis and the clinical outcome of sepsis, but large-scale retrospective studies are still needed to prove our preliminary results.

Hematology and Machine Learning

BACKGROUND

Substantial improvements in computational power and machine learning (ML) algorithm development have vastly increased the limits of what autonomous machines are capable of. Since its beginnings in the 19th century, laboratory hematology has absorbed waves of progress yielding improvements in both of accuracy and efficiency. The next wave of change in laboratory hematology will be the result of the ML revolution that has already touched many corners of healthcare and society at large.

CONTENT

This review will describe the manifestations of ML and artificial intelligence (AI) already utilized in the clinical hematology laboratory. This will be followed by a topical summary of the innovative and investigational applications of this technology in each of the major subdomains within laboratory hematology.

SUMMARY

Application of this technology to laboratory hematology will increase standardization and efficiency by reducing laboratory staff involvement in automatable activities. This will unleash time and resources for focus on more meaningful activities such as the complexities of patient care, research and development, and process improvement.

Utility of Differential White Cell Count and Cell Population Data for Ruling Out COVID-19 Infection in Patients With Community-Acquired Pneumonia

INTRODUCTION

The main aim of this study was to assess the utility of differential white cell count and cell population data (CPD) for the detection of COVID-19 in patients admitted for community-acquired pneumonia (CAP) of different etiologies.

METHODS

This was a multicenter, observational, prospective study of adults aged ≥18 years admitted to three teaching hospitals in Spain from November 2019 to November 2021 with a diagnosis of CAP. At baseline, a Sysmex XN-20 analyzer was used to obtain detailed information related to the activation status and functional activity of white cells.

RESULTS

The sample was split into derivation and validation cohorts of 1065 and 717 patients, respectively. In the derivation cohort, COVID-19 was confirmed in 791 patients and ruled out in 274 patients, with mean ages of 62.13 (14.37) and 65.42 (16.62) years, respectively (p<0.001). There were significant differences in all CPD parameters except MO-Y. The multivariate prediction model showed that lower NE-X, NE-WY, LY-Z, LY-WY, MO-WX, MO-WY, and MO-Z values and neutrophil-to-lymphocyte ratio were related to COVID-19 etiology with an AUC of 0.819 (0.790, 0.846). No significant differences were found comparing this model to another including biomarkers (p=0.18).

CONCLUSIONS

Abnormalities in white blood cell morphology based on a few cell population data values as well as NLR were able to accurately identify COVID-19 etiology. Moreover, systemic inflammation biomarkers currently used were unable to improve the predictive ability. We conclude that new peripheral blood biomarkers can help determine the etiology of CAP fast and inexpensively.

High generation of reactive oxygen species from neutrophils in patients with severe COVID-19

Neutrophilia and an elevated neutrophil:lymphocyte ratio are both characteristic features of severe COVID-19 infection. However, functional neutrophil responses have been poorly investigated in this setting. We utilised a novel PMA-based stimulation assay to determine neutrophil-derived reactive oxygen species (ROS) generation in patients with severe COVID-19 infection, non-COVID related sepsis and healthy study participants. ROS production was markedly elevated in COVID-19 patients with median values ninefold higher than in healthy controls and was particularly high in patients on mechanical ventilation. ROS generation correlated strongly with neutrophil count and elevated levels were also seen in patients with non-COVID related sepsis. Relative values, adjusted for neutrophil count, were high in both groups but extreme low or high values were seen in two patients who died shortly after testing, potentially indicating a predictive value for neutrophil function. Our results show that the high levels of neutrophils observed in patients with COVID-19 and sepsis exhibit functional capacity for ROS generation. This may contribute to the clinical features of acute disease and represents a potential novel target for therapeutic intervention.

Role of the triad of procalcitonin, C-reactive protein, and white blood cell count in the prediction of anastomotic leak following colorectal resections

Purpose

The enhanced recovery after surgery (ERAS) program expedites patient recovery after major surgery. This study aimed to investigate the role of the triad of procalcitonin (PCT), C-reactive protein (CRP), and white blood cells (WBC) trajectories as a predictive biomarker for the anastomotic leak (AL) after colorectal surgery.

Method

Patients who had colorectal anastomosis were prospectively included. Postoperative clinical and laboratory parameters and outcomes were collected and analyzed. The 5-day trajectories of PCT, CRP, and WBC were evaluated. Based on the trajectory of the three biomarkers, we compared patients with and without AL as detected during the first 30 days after surgery using the area under receiver operator characteristic curves (AUC) for logistic estimation.

Results

This study included 205 patients, of whom 56% were men and 43.9% were women with a mean age of 56.4 ± 13.1 years. Twenty-two patients (10.7%) had AL; 77.3% underwent surgery, and 22.7% were treated with drainage and antibiotics. Procalcitonin was the best predictor for AL compared to CRP and WBC at three days postoperatively (AUC: 0.84, 0.76, 0.66, respectively). On day 5, a cutoff value of 4.93 ng/mL for PCT had the highest sensitivity, specificity, and negative predictive value. The predictive power of PCT was substantially improved when combined with either CRP or WBC, or both (AUC: 0.92, 0.92, 0.93, respectively).

Conclusion

The 5-day trajectories of combined CRP, PCT, and WBC had a better predictive power for AL than the isolated daily measurements. Combining the three parameters may be a reliable predictor of early patient discharge, which would be highly beneficial to ERAS programs.

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.

Monocyte distribution width (MDW) as a new tool for the prediction of sepsis in critically ill patients: a preliminary investigation in an intensive care unit

Background

Monocyte Distribution Width (MDW), a simple proxy marker of innate monocyte activation, can be used for the early recognition of sepsis along with Procalcitonin. This study explored the added value of MDW as an early predictor of ensuing sepsis in patients hospitalised in an Intensive Care Unit.

Methods

We performed an observational prospective monocentric study to estimate the analytical performance of MDW in detecting ensuing sepsis in a sample of consecutive patients assisted in an Intensive Care Unit for > 48 h for any reason. Demographic and clinical characteristics, past medical history and other laboratory measurements were included as potential predictors of confirmed sepsis in multivariate logistic regression.

Results

A total of 211 patients were observed, 129 of whom were included in the final sample due to the suspect of ensuing sepsis; of these, 74 (57%) had a confirmed diagnosis of sepsis, which was best predicted with the combination of MDW > 23.0 and PCT > 0.5 ng/mL (Positive Predictive Value, PPV: 92.6, 95% CI: 82.1–97.9). The best MDW cut-off to rule out sepsis was ≤20.0 (Negative Predictive Value, NPV: 86.4, 95% CI: 65.1–97.1). Multivariate analyses using both MDW and PCT found a significant association for MDW > 23 only (OR:17.64, 95% CI: 5.53–67.91).

Conclusion

We found that values of MDW > 23 were associated with a high PPV for sepsis, whereas values of MDW ≤ 20 were associated with a high NPV. Our findings suggest that MDW may help clinicians to monitor ICU patients at risk of sepsis, with minimal additional efforts over standard of care.

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.

Reticulocyte and Erythrocyte Hemoglobin Parameters for Iron Deficiency and Anemia Diagnostics in Patient Blood Management. A Narrative Review

Anemia, iron deficiency and other hematinic deficiencies are a major cause of perioperative transfusion needs and are associated with increased morbidity and mortality. Anemia can be caused either by decreased production of hemoglobin or red blood cells or by increased consumption and blood loss. Decreased production can involve anything from erythropoietin or vitamin B12 insufficiency to absolute or functional lack of iron. Thus, to achieve the goal of patient blood management, anemia must be addressed by addressing its causes. The traditional parameters to diagnose anemia, despite offering elaborate options, are not ideally suited to giving a simple overview of the causes of anemia, e.g., iron status for erythropoiesis, especially during the acute phase of inflammation, acute blood loss or iron deficiency. Reticulocyte hemoglobin can thus help to uncover the cause of the anemia and to identify the main factors inhibiting erythropoiesis. Regardless of the cause of anemia, reticulocyte hemoglobin can also quickly track the success of therapy and, together with the regular full blood count it is measured alongside, help in clearing the patient for surgery.

Neutrophil Maturation, Reactivity and Granularity Research Parameters to Characterize and Differentiate Convalescent Patients from Active SARS-CoV-2 Infection

Studying the dynamics changes of neutrophils during innate immune response in coronavirus 2019 (COVID-19) can help understand the pathogenesis of this disease. The aim of the study was to assess the usefulness of new neutrophil activation parameters: Immature Granulocyte (IG), Neutrophil Reactivity Intensity (NEUT-RI), Neutrophil Granularity Intensity (NEUT-GI), and data relating to granularity, activity, and neutrophil volume (NE-WX, NE-WY, NE-WZ) available in hematology analyzers to distinguish convalescent patients from patients with active SARS-CoV-2 infection and healthy controls (HC). The study group consisted of 79 patients with a confirmed positive RT-PCR test for SARS-CoV2 infection, 71 convalescent patients, and 20 HC. We observed leukopenia with neutrophilia in patients with active infection compared to convalescents and HC. The IG median absolute count was higher in convalescent patients than in COVID-19 and HC (respectively, 0.08 vs. 0.03 vs. 0.02, p < 0.0001). The value of the NEUT-RI parameter was the highest in HC and the lowest in convalescents (48.3 vs. 43.7, p < 0.0001). We observed the highest proportion of NE-WX, NE-WY, and NE-WZ parameters in HC, without differences between the COVID-19 and convalescent groups. New neutrophil parameters can be useful tools to assess neutrophils’ activity and functionalities in the immune response during infection and recovery from COVID-19 disease.

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.

Leukocyte cell population data from the blood cell analyzer as a predictive marker for severity of acute pancreatitis

BACKGROUND

The prediction for severe acute pancreatitis (SAP) is the key to give timely targeted treatment. Leukocyte cell population data (CPD) have been widely applied in early prediction and diagnosis of many diseases, but their predictive ability for SAP remains unexplored. We aim to testify whether CPD could be an indicator of AP severity in the early stage of the disease.

METHODS

The prospective observational study was conducted in the emergency department ward of a territory hospital in Shanghai. The enrolled AP patients should meet 2012 Atlanta guideline.

RESULTS

Totally, 103 AP patients and 62 healthy controls were enrolled and patients were classified into mild AP (n = 30), moderate SAP (n = 42), and SAP (n = 31). Forty-two CPD parameters were examined in first 3 days of admission. Four CPD parameters were highest in SAP on admission and were constantly different among 3 groups during first 3 days of hospital stay. Eighteen CPD parameters were found correlated with the occurrence of SAP. Stepwise multivariate logistic regression analysis identified a scoring system of 4 parameters (SD_LALS_NE, MN_LALS_LY, SD_LMALS_MO, and SD_AL2_MO) with a sensitivity of 96.8%, specificity of 65.3%, and AUC of 0.87 for diagnostic accuracy on early identification of SAP. AUC of this scoring system was comparable with MCTSI, SOFA, APACHE II, MMS, BISAP, or biomarkers as CRP, PCT, and WBC in prediction of SAP and ICU transfer or death.

CONCLUSIONS

Several leukocyte CPD parameters have been identified different among MAP, MSAP, and SAP. They might be ultimately incorporated into a predictive system marker for severity of AP.

Cell Population Data (CPD) for Early Recognition of Sepsis and Septic Shock in Children: A Pilot Study

Objectives: Innovative Cell Population Data (CPD) have been used as early biomarkers for diagnosing sepsis in adults. We assessed the usefulness of CPD in pediatric patients with sepsis/septic shock, in terms of early recognition and outcome prediction. We revised 54 patients (0-15 y) admitted to our Pediatric Intensive Care Unit (PICU) for sepsis/septic shock during a 4-year period. Twenty-eight patients were excluded, 26 septic patients were enrolled (G1). Forty children admitted for elective surgery served as controls (G2). Data on five selected CPD parameters, namely neutrophils fluorescence intensity (NE-SFL), monocytes cells complexity (MO-X), monocytes fluorescence intensity (MO-Y), monocytes complexity and width of dispersion of events measured (MO-WX), and monocytes cells size and width dispersion (MO-WZ), were obtained at time of PICU admission (t0) by a hematological analyzer (Sysmex XN 9000®). As the primary outcome we evaluated the relevance of CPD for diagnosing sepsis/septic shock on PICU admission. Furthermore, we investigated if CPD at t0 were correlated with C-reactive protein (CRP), patient survival, or complicated sepsis course. Results: On PICU admission (t0), NE-SFL, MO-WX, and MO-Y were higher in sepsis/septic shock patients compared to controls. NE-SFL values were correlated with CRP values in G1 patients (r = 0.83). None of the five CPD parameters was correlated with survival or complicated sepsis course. Conclusion: We found higher values of NE-SFL, MO-WX, and MO-Y in children with sepsis/septic shock upon PICU admission. These parameters may be a promising adjunct for early sepsis diagnosis in pediatric populations. Larger, prospective studies are needed to confirm our preliminary observations.

The superiority of 72 h leukocyte descent over CRP for mortality prediction in patients with sepsis

BACKGROUND

Detection of an eventful course in the early days of sepsis treatment is clinically relevant. The white blood cell count (WBCC) and C-reactive protein (CRP) are used in daily practice to monitor the intensity of the inflammatory response associated with sepsis. It is not entirely clear which of the two might better discriminate the outcomes of patients with sepsis.

METHODS

30-day mortality was assessed in a cohort of patients who were hospitalized with sepsis in the departments of Internal Medicine in a tertiary medical center. Admission and 72-hour time points were analyzed to discriminate between patients with increased versus decreased 30 days mortality risk.

RESULTS

The study included 195 patients. Higher 72 h CRP, WBCC, neutrophil counts and neutrophils to lymphocyte ratio were associated with increased mortality (p < 0.02). Baseline WBCC and CRP failed to discriminate between patients who died and those who survived (AUC = 0.551, 0.479). In multivariate analysis of the 72 h tests, higher WBCC count (OR = 1.12, 95%CI 1.05-1.20, p = 0.001), was associated with increased mortality whereas CRP was not (OR = 1.004, 95%CI 0.998-1.01, p = 0.146).

CONCLUSION

Patients who presented a 72-hour leukocyte descent had a better outcome and in this regard, WBCC was superior to 72-hour CRP in predicting 30 days mortality.