Complete blood count as a biomarker for preeclampsia with severe features diagnosis: a machine learning approach.

OBJECTIVE: This study introduces the complete blood count (CBC), a standard prenatal screening test, as a biomarker for diagnosing preeclampsia with severe features (sPE), employing machine learning models. METHODS: We used a boosting machine learning model fed with synthetic data generated through a new methodology called DAS (Data Augmentation and Smoothing). Using data from a Brazilian study including 132 pregnant women, we generated 3,552 synthetic samples for model training. To improve interpretability, we also provided a ridge regression model. RESULTS: Our boosting model obtained an AUROC of 0.90±0.10, sensitivity of 0.95, and specificity of 0.79 to differentiate sPE and non-PE pregnant women, using CBC parameters of neutrophils count, mean corpuscular hemoglobin (MCH), and the aggregate index of systemic inflammation (AISI). In addition, we provided a ridge regression equation using the same three CBC parameters, which is fully interpretable and achieved an AUROC of 0.79±0.10 to differentiate the both groups. Moreover, we also showed that a monocyte count lower than 490 / m m 3 yielded a sensitivity of 0.71 and specificity of 0.72. CONCLUSION: Our study showed that ML-powered CBC could be used as a biomarker for sPE diagnosis support. In addition, we showed that a low monocyte count alone could be an indicator of sPE. SIGNIFICANCE: Although preeclampsia has been extensively studied, no laboratory biomarker with favorable cost-effectiveness has been proposed. Using artificial intelligence, we proposed to use the CBC, a low-cost, fast, and well-spread blood test, as a biomarker for sPE.

Complete Blood Count-Based Biomarkers as Predictors of Clinical Outcomes in Advanced Non-Small Cell Lung Cancer Patients with PD-L1 < 50% Treated with First-Line Chemoimmunotherapy.

Background: The aim of the study was to investigate a series of complete blood cell count-based biomarkers of systemic inflammation as predictors of clinical outcomes in patients who underwent first-line chemoimmunotherapy for advanced NSCLC. Methods: Consecutive patients with pathologically diagnosed stage III/IV NSCLC and PD-L1 < 50% who underwent first-line chemoimmunotherapy were retrospectively enrolled. The clinical outcomes used for biomarker evaluation were Objective Response Rate (ORR) and Overall Survival (OS). Results: Non-responders had significantly higher values of neutrophil to lymphocyte ratio (NLR, median: 5.36; IQR: 2.78-10.82 vs. 3.31; IQR: 2.15-4.12, p = 0.019), neutrophil to monocyte ratio (NMR, median: 14.00; IQR: 8.82-21.20 vs. 9.20; IQR: 7.45-11.20, p = 0.013), and systemic inflammation index (SII, median: 1395; IQR: 929-3334 vs. 945; IQR: 552-1373, p = 0.025), but only NLR and NMR remained independently associated with clinical response in multivariate logistic regression. In the univariate analysis, white blood cells (OR:1.2202; 95% CI: 1.0339-1.4400, p = 0.019), neutrophils (OR:1.2916; 95% CI: 1.0692-1.5604, p = 0.008), NLR (OR:1.3601: 95% CI: 1.0949-1.6896, p = 0.005) and NMR (OR:1.2159; 95% CI: 1.00396-1.4221, p = 0.015) were significantly associated with survival; Cox regression models confirmed that neutrophils, NLR, and MLR were independently associated with survival; NLR, at a cut-off value of 4.0, showed the better AUC (0.749) in predicting OS. Conclusions: Baseline complete blood cell count biomarkers, especially the NLR, can predict clinical outcomes in patients with advanced NSCLC treated with first-line chemoimmunotherapy.

The accuracy and precision of plain CT chest for diagnosis of anaemia.

OBJECTIVE: To determine the accuracy and precision of anaemia diagnosis with plain computed tomography of chest by keeping complete blood count as the gold standard. METHODS: The cohort study was conducted from January 1 to December 31, 2020, at Dow University of Health Sciences, Karachi, and comprised patients attending the hospital regardless of gender or age. The subjects underwent complete blood count and high-resolution computed tomography scan of chest with 7-day interval. On the basis of haematology, the subjects were divided into anaemic group A and control group B. Blood attenuation measurements and visual perception of the inter-ventricular septum was done blinded to haemoglobin values. Region of interest attenuation cursor was placed within the right ventricular chamber and left ventricular chamber. Quantitative diagnosis of anaemia on computed tomography was done with Hounsfield unit <35 in a chamber. Qualitative computed tomography diagnosis of anaemia was equivalent to inter-ventricular septum visualisation. Accuracy and precision was calculated. Data was analysed using SPSS 17. RESULTS: Of the 124 subjects, 62(50%) were males and 62(50%) were females. The overall mean age was 51.45±17.3 years (range: 8-96 years). On the basis of haematology, 74(59.6%) subjects were in group A and 50(40.3%) were in group B. The sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of chest computed tomography for quantitative diagnosis of anaemia were 48.6%, 76.5%, 76.5%, 50.6% and 60.5% respectively. The corresponding values for qualitative diagnosis of anaemia were 55.4%, 88.0%, 87.2%, 57.1%, and 68.5%. CONCLUSIONS: There was a high positive predictive value for quantitative diagnosis of anaemia on chest computed tomography with low diagnostic accuracy and moderate reliability.

Biochemical Markers in the Prediction of Pregnancy Outcome in Gestational Diabetes Mellitus.

Background and Objectives: Gestational diabetes mellitus (GDM) may impact both maternal and fetal/neonatal health. The identification of prognostic indicators for GDM may improve risk assessment and selection of patient for intensive monitoring. The aim of this study was to find potential predictors of adverse pregnancy outcome in GDM and normoglycemic patients by comparing the levels of different biochemical parameters and the values of blood cell count (BCC) between GDM and normoglycemic patients and between patients with adverse and good outcome. Materials and Methods: Prospective clinical study included 49 patients with GDM (study group) and 44 healthy pregnant women (control group) who underwent oral glucose tolerance test (OGTT) at gestational age of 24-28 weeks. At the time of OGTT peripheral blood was taken for the determination of glucose levels, insulin, glycated hemoglobin, lipid status, homeostatic model assessment, BCC, iron and zinc metabolism, liver function, kidney function and inflammatory status. Each group was divided into two subgroups-normal and poor pregnancy outcome. Results: Higher RBC, hemoglobin concentration, hematocrit value, fasting glucose, uric acid and fibrinogen were found in GDM patients compared to control group. In GDM patients with poor pregnancy outcome values of fibrinogen, ALT, sedimentation rate, granulocyte and total leukocyte counts were elevated, while the serum level of zinc was significantly lower. Higher level of fibrinogen was found in normoglycemic patients with adverse pregnancy outcomes. ROC curve was constructed in order to assess fibrinogen's biomarker potential. The established AUC value for diagnostic ROC was 0.816 (p < 0.001, 95% CI 0.691-0.941), while the AUC value for assessing fibrinogen's potential to predict poor pregnancy outcome in GDM was 0.751 (p = 0.0096, 95% CI 0.561-0.941). Conclusions: The results of our study demonstrated that the best prognostic potential in GDM showed inflammation related parameters, identifying fibrinogen as a parameter with both diagnostic and prognostic ability.

Rapid complete blood count and C-reactive protein determination with the Horiba Microsemi analyzer: the experience in neonatal intensive care unit of Careggi University Hospital.

Microsystems represent an alternative but proficient approach of analysis outside the laboratory, and their use could help in reducing the impact of pre-analytical errors, in particular in challenging newborn samples. The study purpose is to compare the Horiba Microsemi CRP LC-767G system for rapid 3-part complete blood count (CBC) and C-reactive protein (CRP) determination with the laboratory reference systems (respectively Sysmex XN-9100™ and Roche Cobas® c702) in samples of adult patients and newborns hospitalized in the neonatal intensive care unit (NICU) samples. The comparison between the analyzers was performed through Passing-Bablok regression analysis and Bland-Altman plot. One hundred eighty-three blood samples were analyzed. The regression analysis results, performed in the newborn (n = 70) and in adult (n = 113) populations, showed a good agreement between the instruments. The evaluation of the Bland-Altman plots showed comparable values of bias < 10% for most of the parameters, but not for MPV, lymphocyte, and monocyte count. CONCLUSION: The comparison between the Microsemi CRP LC-767G system and the laboratory instrumentations demonstrated comparable results. The Microsemi CRP LC-767G system provides reliable analytical data and faster turnaround time, particularly useful in NICU. WHAT IS KNOWN: • Microsystems for point-of-care testing (POCT) represent an alternative but proficient approach of analysis outside the laboratory, in order to perform a rapid, safe, and exhaustive evaluation for critical patients' management, acting as a valid support for treatment in acute care. WHAT IS NEW: • The Microsemi CRP LC-767G system can represent an alternative but effective testing approach outside the laboratory, particularly in NICU, to reduce the impact of pre-analytical errors on newborn samples.

Clinical value of complete blood count ratio in benign and malignant thyroid diseases.

OBJECTIVE: To investigate the clinical value of blood routine derivative biomarkers and thyroid function biomarkers in differentiating different thyroid diseases. METHODS: The differences of blood routine derived indexes neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), platelet-large cell rate (P-LCR) and thyroid function indexes between benign and malignant thyroid diseases were compared, and the differences of each index between different benign thyroid diseases were further compared. Univariate regression analysis model was used to analyze the clinical value of various indexes. Receiver operating characteristic curve (ROC) was used to calculate the area under the curve (AUC). RESULTS: There were statistically significant differences in PLR, NLR and P-LCR between patients with benign and malignant thyroid diseases (P < 0.05 for each). The results of univariate logistic regression analysis showed that P < 0.05 for all indicators except LMR, when PLR and NLR value increased by 1, the risk of thyroid malignancy decreased by 1 % and 21 %, when P-LCR value increased by 1, the risk of thyroid malignancy increased by 4 %. CONCLUSIONS: PLR, NLR and P-LCR are helpful to distinguish different benign thyroid diseases and to diagnose benign and malignant thyroid diseases.

Complete blood count-based inflammation indexes and symptom severity in people with schizophrenia spectrum disorders: An analysis based on structural equation modelling.

INTRODUCTION: Schizophrenia spectrum disorders (SSDs) are associated with immune-inflammatory activation. Recently, complete blood count (CBC)-based inflammation indexes such as the neutrophil-to-lymphocyte ratio (NLR), the monocyte-to-lymphocyte ratio (MLR), and the platelet-to-lymphocyte ratio (PLR) have emerged as reproducible and cost-effective inflammation markers in mental disorders. In this study, we aimed at investigating the relationship of NLR, MLR, and PLR with symptom severity in people with SSDs, testing interactions with relevant clinical variables. METHODS: We included inpatients with SSDs aged 18-65 consecutively hospitalized from May 2020 to March 2024. Socio-demographic and clinical data were recorded. CBC-based ratios were estimated from routinely collected blood samples. Structural equation modelling (SEM) was performed to test relationships involving symptom severity constructs and CBC-based ratios, accounting for substance use disorder, antipsychotic treatment, and obesity. RESULTS: Two hundred sixty-six participants met inclusion criteria. The SEM analysis uncovered a significant relationship of MLR with positive (coeff.: 0.19, p=0.048) and negative (coeff.: 0.27, p=0.004) symptoms, also showing a significant link of substance use disorder and antipsychotic treatment with symptom severity as well as of antipsychotic treatment with obesity. CONCLUSIONS: Notwithstanding the cross-sectional design and the somewhat limited sample representativeness, this study showed a significant relationship between the MLR - but not the NLR or the PLR - and the severity of both positive and negative symptoms, testing at the same time the interactions with other clinical variables. Considering the insufficiency and inconsistency of data in this field, further research is needed to validate our findings and elucidate the underlying mechanisms driving the observed relationships between the MLR and SSD symptoms.

Consistency analysis of two fingertip capillary blood sampling methods for complete blood count.

This study was performed to analyze fingertip capillary blood sampling in pediatric patients using microcapillary blood collection tubes and microhematocrit tubes and to compare the blood cell analysis results obtained via these two blood collection methods. Finger capillary blood was collected from 110 outpatients using microcapillary blood collection tubes and microhematocrit tubes and complete blood count analysis was performed with a Sysmex XS-900i hematology analyzer and manual microscopy for blood cell morphology. Paired data was evaluated for agreement and bias using the microhematocrit samples as the reference group and the samples from the microcapillary blood collection tubes as the observation group. The two blood collection methods demonstrated good agreement for measuring red blood cell (RBC) parameters (i.e., RBC, Hb, Hct, MCV, MCH and MCHC), wherein the relative bias was > allowable total error (TEa) in 0.91%, 1.82%, 11.82%, 1.82%, 0.91% and 8.18% of the parameter measures, respectively. According to industry requirements, the proportion of samples meeting the acceptable bias level should be > 80%. Additionally, the estimated biases at each medical decision level were within clinically acceptable levels for RBC, Hb, Hct, and MCV. However, the proportion of WBC and PLT counts with relative bias > TEa was 25.45% and 35.45%, respectively. Furthermore, the relative bias of the WBC count at the medical decision level of 0.5 × 109/L and that of the PLT counts at the medical decision levels of 10 × 109/L and 50 × 109/L were clinically significant. Bland-Altman analysis further showed a mean bias of 0.66 × 109/L (95% LoA, - 0.79 to 2.11) for the WBC count and 39 × 109/L (95% LoA, - 46 to 124) for the PLT count from the blood samples collected in the microcapillary blood collection tubes compared with the counts of those collected in the microhematocrit tubes. Neutrophil, monocyte, lymphocyte, eosinophil, and PLT counts increased significantly in the microcapillary blood collection tubes compared with those in the microhematocrit tubes, along with an elevated number of instrument false alarms (P < 0.05). The two capillary blood collection devices exhibit performance differences. Therefore, clinicians should pay attention to the variation in results caused by different blood collection methods.

Comparison of peripheral blood automated hematopoietic progenitor cell count and flow cytometric CD34+ cell count.

BACKGROUND: Stem cell apheresis in the context of autologous stem cell transplantation requires an accurate cluster of differentiantion 34 (CD34+) count determined by flow cytometry as the current gold standard. Since flow cytometry is a personnel and time-intensive diagnostic tool, automated stem cell enumeration may provide a promising alternative. Hence, this study aimed to compare automated hematopoietic progenitor enumeration carried out on a Sysmex XN-20 module compared with conventional flow cytometric measurements. METHODS: One hundred forty-three blood samples from 41 patients were included in this study. Correlation between the two methods was calculated over all samples, depending on leukocyte count and diagnosis. RESULTS: Overall, we found a high degree of correlation (r = 0.884). Furthermore, correlation was not impaired by elevated leukocyte counts (>10 000/µL, r = 0.860 vs <10 000/µL, r = 0.849; >20 000/µL, r = 0.843 vs <20 000/µL, r = 0.875). However, correlation was significantly impaired in patients with multiple myeloma (multiple myeloma r = 0.840 vs nonmyeloma r = 0.934). SUMMARY: Stem cell measurement carried out on the Sysmex XN-20 module provides a significant correlation with flow cytometry and might be implemented in clinical practice. In clinical decision-making, there was discrepancy of under 15% of cases. In multiple myeloma patients, XN-20 should be used with caution.

Short Prewarming at 41°C to Correct the Interference in Samples with the Presence of Cold Agglutination.

BACKGROUND: Cold agglutinins (CAs) in blood samples can cause a reversible agglutination of red blood cell (RBC) which result in an incorrect complete blood count (CBC). So, it is important to explore new simple and feasible treatment conditions for clinical work. METHODS: The CAs group included 32 samples with CAs. The parameters of CBC at room temperature or after prewarming at 37°C or 41°C for different time periods were compared. The consistency and correlation of those parameters were analyzed. The morphology of erythrocytes in the CAs group was observed manually. The control group included 45 samples without CAs and prewarmed at 37°C or 41°C for different time periods. The differences were also analyzed. RESULTS: CAs have a significant effect on CBC. After prewarming at 37°C or 41°C the interferences are all corrected. Consider prewarming at 37°C for 120 minutes as the standard procedure. The consistency and correlation analysis showed there was no statistical difference between the results of each subgroup and standard group, except the MCHC of group 41°C 10 minutes. The correlation of parameters between all subgroups and the standard group is satisfied. Microscopic examination showed no RBC aggregation or fragmentation after prewarming at 41°C or 37°C. According to the maximum bias requirements for expert performance in Validation, Verification, and Quality Assurance of Automated Hematology Analyzers, 2nd Edition (CLSI H26-A2), the differences in overall results in control group are negligible. CONCLUSIONS: The 41°C 2 minutes prewarming method is a rapid and effective way for treating samples with CAs. It is an efficient way to obtain more reliable CBC results, without specific instruments.

Associations of CBC-Derived inflammatory indicators with sarcopenia and mortality in adults: evidence from Nhanes 1999 ∼ 2006.

BACKGROUND: It has been proposed that inflammation plays a role in the development of sarcopenia. This study aimed to investigate the links of complete blood cell count (CBC) parameters and CBC-derived inflammatory indicators with sarcopenia and mortality. METHODS: Data pertaining to sarcopenia were extracted from the 1999-2006 National Health and Nutrition Examination Survey (NHANES), and mortality events were ascertained through the National Death Index up to December 31, 2019. The CBC-derived inflammatory indicators assessed in this study included the neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), monocyte-to-lymphocyte ratio (MLR), neutrophil-monocyte to lymphocyte ratio (NMLR), systemic inflammatory response index (SIRI), and systemic immune-inflammation index (SII). The prognostic significance of these CBC-derived inflammatory indicators was evaluated using the random survival forests (RSF) analysis. RESULTS: The study encompassed a cohort of 12,689 individuals, among whom 1,725 were diagnosed with sarcopenia. Among individuals with sarcopenia, 782 experienced all-cause mortality, and 195 succumbed to cardiovascular causes. Following adjustment for confounding variables, it was observed that elevated levels of NLR, dNLR, NMLR, SIRI, and SII were associated with an increased prevalence of sarcopenia. Among participants with sarcopenia, those in the highest quartile of NLR (HR = 1.336 [1.095-1.631]), dNLR (HR = 1.274 [1.046-1.550]), MLR (HR = 1.619 [1.290-2.032]), NMLR (HR = 1.390 [1.132-1.707]), and SIRI (HR = 1.501 [1.210-1.862]) exhibited an elevated risk of all-cause mortality compared to those in the lowest quartile of these inflammation-derived indicators. These associations were similarly observed in cardiovascular mortality (HR = 1.874 [1.169-3.003] for MLR, HR = 1.838 [1.175-2.878] for SIRI). The RSF analysis indicated that MLR exhibited the highest predictive power for both all-cause and cardiovascular mortality among individuals with sarcopenia. CONCLUSIONS: Our findings underscore the association between CBC-derived inflammatory indicators and mortality in adults with sarcopenia. Of note, MLR emerged as the most robust predictor of all-cause and cardiovascular mortality in this population.

Unlocking the complete blood count as a risk stratification tool for breast cancer using machine learning: a large scale retrospective study.

Optimizing early breast cancer (BC) detection requires effective risk assessment tools. This retrospective study from Brazil showcases the efficacy of machine learning in discerning complex patterns within routine blood tests, presenting a globally accessible and cost-effective approach for risk evaluation. We analyzed complete blood count (CBC) tests from 396,848 women aged 40-70, who underwent breast imaging or biopsies within six months after their CBC test. Of these, 2861 (0.72%) were identified as cases: 1882 with BC confirmed by anatomopathological tests, and 979 with highly suspicious imaging (BI-RADS 5). The remaining 393,987 participants (99.28%), with BI-RADS 1 or 2 results, were classified as controls. The database was divided into modeling (including training and validation) and testing sets based on diagnostic certainty. The testing set comprised cases confirmed by anatomopathology and controls cancer-free for 4.5-6.5 years post-CBC. Our ridge regression model, incorporating neutrophil-lymphocyte ratio, red blood cells, and age, achieved an AUC of 0.64 (95% CI 0.64-0.65). We also demonstrate that these results are slightly better than those from a boosting machine learning model, LightGBM, plus having the benefit of being fully interpretable. Using the probabilistic output from this model, we divided the study population into four risk groups: high, moderate, average, and low risk, which obtained relative ratios of BC of 1.99, 1.32, 1.02, and 0.42, respectively. The aim of this stratification was to streamline prioritization, potentially improving the early detection of breast cancer, particularly in resource-limited environments. As a risk stratification tool, this model offers the potential for personalized breast cancer screening by prioritizing women based on their individual risk, thereby indicating a shift from a broad population strategy.

A comparative study of blood cell count in four automated hematology analyzers: An evaluation of the impact of preanalytical factors.

Differential white blood cell counts are frequently used in diagnosis, patient stratification, and treatment selection to optimize therapy responses. Referral laboratories are often used but challenged with use of different hematology platforms, variable blood shipping times and storage conditions, and the different sensitivities of specific cell types. To extend the scientific literature and knowledge on the temporal commutability of blood samples between hematology analyzers, we performed a comparative ex-vivo study using four of the most utilized commercial platforms, focusing on the assessment of eosinophils given its importance in asthma management. Whole blood from healthy volunteers with and without atopy (n = 6+6) and participants with eosinophilic asthma (n = 6) were stored under different conditions (at 4, 20, 30, and 37°C, with or without agitation) and analyzed at different time points (3, 6, 24, 48 and 72h post-sampling) in parallel on the Abbott CELL-DYN Sapphire, Beckman Coulter DxH900, Siemens ADVIA 2120i and Sysmex XN-1000V. In the same blood samples, eosinophil-derived neurotoxin (EDN), eosinophil activation and death markers were analyzed. All platforms gave comparable measurements of cell differentials on fresh blood within the same day of sampling. However, by 24 hours, significant temporal and temperature-dependent differences were observed, most markedly for eosinophils. None of the platforms performed perfectly across all temperatures tested during the 72 hours, showing that handling conditions should be optimized depending on the cell type of interest and the hematology analyzer. Neither disease status (healthy vs. asthma) nor agitation of the sample affected the cell quantification result or EDN release. The eosinophil activation markers measured by flow cytometry increased with time, were influenced by temperature, and were higher in those with asthma versus healthy participants. In conclusion, hematology analyzer, time window from sampling until analysis, and temperature conditions must be considered when analyzing blood cell differentials, particularly for eosinophils, via central labs to obtain counts comparable to the values obtained in freshly sampled blood.

An Introduction to the Complete Blood Count for Clinical Chemists: Red Blood Cells.

BACKGROUND: The most frequently ordered laboratory test worldwide is the complete blood count (CBC). CONTENT: In this primer, the red blood cell test components of the CBC are introduced, followed by a discussion of the laboratory evaluation of anemia and polycythemia. SUMMARY: As clinical chemists are increasingly tasked to direct laboratories outside of the traditional clinical chemistry sections such as hematology, expertise must be developed. This review article is a dedication to that effort.

Predicting community acquired bloodstream infection in infants using full blood count parameters and C-reactive protein; a machine learning study.

Early recognition of bloodstream infection (BSI) in infants can be difficult, as symptoms may be non-specific, and culture can take up to 48 h. As a result, many infants receive unneeded antibiotic treatment while awaiting the culture results. In this study, we aimed to develop a model that can reliably identify infants who do not have positive blood cultures (and, by extension, BSI) based on the full blood count (FBC) and C-reactive protein (CRP) values. Several models (i.e. multivariable logistic regression, linear discriminant analysis, K nearest neighbors, support vector machine, random forest model and decision tree) were trained using FBC and CRP values of 2693 infants aged 7 to 60 days with suspected BSI between 2005 and 2022 in a tertiary paediatric hospital in Dublin, Ireland. All models tested showed similar sensitivities (range 47% - 62%) and specificities (range 85%-95%). A trained decision tree and random forest model were applied to the full dataset and to a dataset containing infants with suspected BSI in 2023 and showed good segregation of a low-risk and high-risk group. Negative predictive values for these two models were high for the full dataset (> 99%) and for the 2023 dataset (> 97%), while positive predictive values were low in both dataset (4%-20%).   Conclusion: We identified several models that can predict positive blood cultures in infants with suspected BSI aged 7 to 60 days. Application of these models could prevent administration of antimicrobial treatment and burdensome diagnostics in infants who do not need them. What is Known: • Bloodstream infection (BSI) in infants cause non-specific symptoms and may be difficult to diagnose. • Results of blood cultures can take up to 48 hours. What is New: • Machine learning models can contribute to clinical decision making on BSI in infants while blood culture results are not yet known.

Umbilical Cord Blood as an Alternative to Neonatal Blood for Complete Blood Count: A Comparison Study.

OBJECTIVE: To assess concordance between umbilical cord blood (UCB) and neonatal blood (NB) laboratory test results at birth. STUDY DESIGN: This retrospective study considered very preterm neonates (<32 weeks' gestational age) admitted to a tertiary neonatal intensive care unit from 2012 to 2023. Inclusion criteria required neonates with a complete blood count measured in both UCB and NB drawn within 2 hours after birth. Median hemoglobin (Hb) and hematocrit (Hct) concentrations were compared between UCB (venous samples) and NB (venous, arterial, or capillary samples). RESULTS: A total of 432 neonates with paired UCB and NB values were included in the study. Hb concentration in UCB was 14.7 g/dL (IQR 13.5-16.1 g/dL) compared with 14.8 g/dL (IQR 12.6-19.3 g/dL) in venous NB samples, 13.9 g/dL (IQR 12.9-15.3 g/dL) in arterial NB and 18.7 g/dL (IQR 16.6-20.8 g/dL) in capillary NB. The regression equation showed a correction factor of 1.08 for converting Hb values from UCB to venous NB. Median Hct concentration in UCB was 0.45 L/L (IQR: 0.41-0.49 L/L) compared with 0.48 L/L (IQR 0.43-0.54 L/L) in venous NB, 0.42 L/L (IQR 0.38-0.45 L/L) in arterial NB and 0.57 L/L, (IQR 0.51-0.63 L/L) in capillary NB. CONCLUSIONS: Hb and Hct concentrations measured in UCB are similar to those measured in venous blood in very preterm infants and are valid alternatives for NB tests at birth. Hb and Hct concentrations in arterial and capillary NB are respectively lower and higher compared with UCB measurements.

An Introduction to the Complete Blood Count for Clinical Chemists: Platelets.

BACKGROUND: The most ordered laboratory test worldwide is the complete blood count (CBC). CONTENT: In this primer, an introduction to platelet testing in the context of the CBC is provided with a discussion of the laboratory evaluation of platelet abnormalities including thrombocytopenia and thrombocytosis. SUMMARY: As clinical chemists continue to be tasked to direct laboratories outside of the traditional clinical chemistry sections such as hematology, expertise must be developed. This primer is dedicated to that effort.

Verification of a Benchtop Hematology Analyzer with a 5-Part Differential Count: There is Nothing Wrong with Being Small.

BACKGROUND: The benchtop ADVIA 560 AL hematology analyzer (Siemens Healthineers Tarrytown, NY, USA) offers a small footprint and ease of operation making it suitable for satellite laboratories and intensive care units. A verification study of this analyzer was performed. METHODS: Between- and intra-run precision, carry-over, linearity, and throughput were evaluated on the ADVIA 560 AL. Accuracy was assessed on 94 patient samples by comparing the results obtained on the ADVIA 560 AL to the results on the reference Sysmex XN1000 analyzer (Sysmex Corporation, Kobe, Japan). RESULTS: The ADVIA 560 AL showed acceptable imprecision on control material and minimal bias in comparison to the XN 1000 on patient samples with a throughput of 60 samples per hour. The percentage carryover was not significant and the linearity was within acceptable limits. CONCLUSIONS: The ADVIA 560 AL bench-top analyzer is suitable for acute care centers and satellite laboratories owing to its small footprint, ease of use, and reproducible and accurate results.

Evaluation of the Sysmex XQ-320 three-part differential haematology analyser and its flagging capabilities.

BACKGROUND: Three-part differential (3PD) haematology analysers offer a quick, easy-to-use and economical way to acquire important information about a patient's physiology. In this study, we evaluated a new 3PD analyser, the Sysmex XQ-320, investigated its comparability with its predecessor (Sysmex XP-300) and the five-part differential analyser Sysmex XN-9000, and explored its flagging potential. METHODS: Analytical performance studies were conducted for repeatability, within-laboratory precision, between-day precision, carry-over and linearity with fresh blood and QC material. Method comparison was performed in 493 samples comparing XQ-320 with XP-300, using the XN-9000 as the gold standard. RESULTS: The XQ-320 excelled manufacturer's specifications in the analytical performance studies, except for MXD in within-laboratory and between-day precisions using the QC material level 1. The XQ-320 showed correlation values greater than 0.94 with XN-9000 for the majority of the 20 reportable parameters (MXD# 0.891, MXD% 0.898 and MCHC 0.849). Improvements over the XP-300 were observed in WBC in the leucocytopenic range (bias -0.038 vs. -0.097) and PLT (bias 2.568 vs. -7.877, intercept 3.880 vs. -8.845). Concordance between XQ-320 and XP-300 was 91.9% for the WBC histogram abnormal distribution flag and 95.3% for the PLT flag. Patterns of increased neutrophils and decreased mixed cells on the XQ-320 were observed in samples that raised a flag on XN-9000. CONCLUSION: The XQ-320 showed excellent analytical performance, and very good to excellent correlation with XN-9000 with improvements over XP-300. Flagging combined with parameter patterns identified additional suspected abnormal samples, thus making the XQ-320 an excellent solution for laboratories utilising 3PD analysers.

Validation of the Sysmex XN analyser and Blood Bank mode for the quality and safety of donor blood and transfusion products.

OBJECTIVES: Our objective was to compare the measurement of residual white blood cell (rWBC) and residual red blood cell (rRBC) counts in blood products using the XN Blood Bank mode and the laboratory standard operating procedures for manual counts. In addition, to compare the whole blood complete blood count (CBC) values of blood donors and the quality of blood products using the Sysmex XN analyser versus the XS-1000i analyser. MATERIALS AND METHODS: For blood donors, 190 samples from blood or apheresis donors were analysed on both the Sysmex XS-1000i and XN-1000 analysers and the mean values of six CBC parameters were compared: the white blood cell count (WBC), the red blood cell count (RBC), haemoglobin (HGB), haematocrit (HCT), the mean corpuscular volume (MCV), the platelet count (PLT). For blood products, 164 samples were collected: 13 Plasma products - whole blood, 9 Plasma products - apheresis, 36 RBC concentrates - whole blood, 30 PLT concentrates - buffy coats, 36 PLT concentrates - buffy coats - pooled and 55 PLT concentrates - apheresis. RESULTS: All CBC parameters of the blood donors tested showed similar performance, with excellent correlation coefficients (r) ranging from 0.821 to 0.995. The majority of the blood products did not have a quantifiable number of residual cells, meaning the number of rWBC and rRBC, if present, was below the limit of quantitation (LoQ) of the different methods. rWBC were detected by Blood Bank mode in Plasma products - whole blood with a mean rWBC of 0.012 × 109 /L and in PLT concentrates - buffy coats with a mean rWBC of 0.19 × 109 /L. The correlation coefficient in both analysers for all three parameters (HGB, HCT, RBC) in RBC concentrates - whole blood was excellent, ranging from 0.95 to 0.99. For platelet count, r ranged from 0.98 to 0.99. CONCLUSION: The XN-Series analyser, equipped with a Blood Bank mode, demonstrated reliable performance when used for blood donor evaluation, rWBC enumeration and measurement of end blood products.