Hemolysis After Medication Exposure in Pediatric Patients With G6PD Deficiency.

Hemolysis in glucose-6-phosphate dehydrogenase (G6PD) deficiency varies by mutation status and the oxidative stressor. Although classified by percent of enzymatic deficiency, variability in normal G6PD values clouds assessment of hemolysis risk by level. This was a retrospective, single institution, cohort study assessing risk of postexposure medication-induced hemolysis in G6PD deficient patients. Exposures occurred in 87 of 1415 deficient patients. Only 2 of 87 medication-exposed patients had hemolytic episodes and both had very low enzymatic activity. No hemolytic events occurred with G6PD levels >7 units/g hemoglobin. Correlation of levels with mutation may improve predictive capacity for hemolysis in G6PD deficiency.

Persistence of long-lived plasma cells and humoral immunity in individuals responding to CD19-directed CAR T-cell therapy.

The mechanisms underlying the maintenance of long-lasting humoral immunity are not well understood. Studies in mice indicate that plasma cells (PCs) can survive up to a lifetime, even in the absence of regeneration by B cells, implying the presence of long-lived PCs as a mechanism for long-lasting immunity. Evidence from humans treated with anti-CD20, which depletes circulating B cells, also suggests B-cell-independent long-term survival of some PCs. On the other hand, antibody responses may be sustained solely by short-lived PCs with repopulation from clonally related memory B cells. To explore PC longevity and humoral immunity in humans, we investigated the fate of PCs and their antibodies in adult and pediatric patients who received chimeric antigen receptor-based adoptive T-cell immunotherapy targeting CD19 to treat B-cell lineage malignancies (CTL019). Treatment with CTL019 is frequently associated with B-cell aplasia that can persist for years. Serum antibody titers to vaccine-related antigens were measured, and quantitative assessment of B cells and PCs in blood and bone marrow was performed at various time points before and after CTL019 therapy. While total serum immunoglobulin concentrations decline following CTL019-induced B-cell aplasia, several vaccine/pathogen-specific serum immunoglobulin G and A (IgG and IgA) titers remain relatively stable for at least 6 and 12 months posttreatment, respectively. Analysis of bone marrow biopsies after CTL019 revealed 8 patients with persistence of antibody-secreting PCs at least 25 months post-CTL019 infusion despite absence of CD19(+)CD20(+) B cells. These results provide strong evidence for the existence of memory B-cell-independent, long-lived PCs in humans that contribute to long-lasting humoral immunity.

Gain of CD26 expression on the malignant T-cells in relapsed erythrodermic leukemic mycosis fungoides.

Loss of CD26 surface expression on the circulating malignant T-cell is the most widely accepted diagnostic marker in patients with leukemic cutaneous T-cell lymphoma (CTCL). CTCL cases with reemergence of CD7 and/or CD26 surface expression are unusual and of uncertain prognosis. We report the case of an erythrodermic leukemic mycosis fungoides patient who had achieved temporary remission after several months on multimodality immunotherapy and extracorporeal photopheresis, but who relapsed with aggressive disease phenotypically characterized by CD4+ T-cells with high CD26 expression. Polymerase chain reaction studies and high-throughput sequencing analyses from peripheral blood mononuclear cells at presentation and relapse consistently showed an identical clonal T-cell receptor suggesting evolution of her original malignant clone which lacked CD26 expression. Interestingly, quantitative expression of the sialomucin, CD164, mirrored her clinical picture, thus favoring its reliability as a novel biomarker in CTCL.

Report of the International Council for Standardization in Haematology working group for standardization of reticulocyte parameters.

INTRODUCTION: The International Council for Standardization in Haematology convened a working group to assess and propose improvements upon the state of standardization and harmonization of reticulocyte parameters among commercial hematology analyzers. METHODS: An international group of laboratory hematologists prospectively collected and analyzed clinical samples using locally available IVD commercial hematology analyzers. Eight hundred and fifty-five total samples were collected at 6 sites using 9 distinct analyzer types. Samples were assessed for reticulocyte percent (RET%), immature reticulocyte fraction (IRF), and reticulocyte hemoglobin content (RHC). Method comparison and regression statistics were calculated. These analyses were used to determine whether statistical recalibration offered a potential avenue for increasing comparability between these methods. RESULTS: While methods producing reticulocyte percent were the most comparable in this study, the state of harmonization for the IRF and RHC was reduced with pearson correlation coefficients ranging from 0.955 to 0.77 and 0.927 and 0.680, respectively. Nevertheless, use of parameters from the Passing Bablok regression substantially improved the comparability of the results. In addition, precision data was derived which also demonstrated substantial differences between analyzer systems. CONCLUSION: While reticulocyte counting is correlated between the automated methods evaluated in this study, the current state of harmonization of other reticulocyte parameters is not as strong. A major challenge in moving this field forward is the need for commutable materials to facilitate comparisons between analyzers not co-located. A potential alternate approach to improve the current state would be instrument re-calibration. However, this is challenging both technically and due to national regulatory frameworks.

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.

Digital image analysis of erythroblastic islands in myelodysplastic syndromes.

INTRODUCTION: Myelodysplastic syndromes (MDS) encompass a diverse group of myeloid neoplasms for which the diagnosis of low-grade subtypes remains challenging. Erythroblastic islands (EBIs) are highly organized units of erythroid proliferation, differentiation, and enucleation. EBI disruption is frequently observed and is believed to be one of the early changes in MDS. METHODS: In this study, we digitally analyzed bone marrow biopsies dual stained with alpha-hemoglobin stabilizing protein (AHSP) and CD163 to quantitatively study features of EBIs in MDS, among MDS subtypes, as well as those in normal marrows and marrows with other causes of anemia. RESULTS: EBIs in MDS specimens were smaller in size and higher in density compared to both normal and non-MDS anemia specimens. Increased CD163 expression within the EBIs is observed in both MDS and other causes of anemia. A combination of increased EBI density and CD163 expression is seen in association with MDS with high-risk cytogenetics and multiple adverse mutations. CONCLUSION: As a proof-of-concept study, we show that EBI features can be relatively easily quantified with AHSP/CD163 dual immunohistochemistry and open-source imaging analysis software, highlighting those that are unique to MDS, and which may be prognostically relevant. Further studies of the measurable EBI features may provide valuable and novel tools to aid MDS diagnosis and prognostication in the era of digital pathology.

Proceedings of the Association for Pathology Informatics Bootcamp 2022.

The Pathology Informatics Bootcamp, held annually at the Pathology Informatics Summit, provides pathology trainees with essential knowledge in the rapidly evolving field of Pathology Informatics. With a focus on data analytics, data science, and data management in 2022, the bootcamp addressed the growing importance of data analysis in pathology and laboratory medicine practice. The expansion of data-related subjects in Pathology Informatics Essentials for Residents (PIER) and the Clinical Informatics fellowship examinations highlights the increasing significance of these skills in pathology practice in particular and medicine in general. The curriculum included lectures on databases, programming, analytics, machine learning basics, and specialized topics like anatomic pathology data analysis and dashboarding.

Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

INTRODUCTION: Early diagnosis and antibiotic administration are essential for reducing sepsis morbidity and mortality; however, diagnosis remains difficult due to complex pathogenesis and presentation. We created a machine learning model for bacterial sepsis identification in the neonatal intensive care unit (NICU) using hematological analyzer data. METHODS: Hematological analyzer data were gathered from NICU patients up to 48 hours prior to clinical evaluation for bacterial sepsis. Five models, Support Vector Machine, K-nearest-neighbors, Logistic Regression, Random Forest (RF), and Extreme Gradient boosting (XGBoost), were trained on 60 hematological and nine clinical variables for 2357 cases (1692 control, 665 septic). Clinical feature only models (nine variables) were additionally trained and compared with models including hematological variables. Feature importance was used to assess relative contributions of parameters to performance. RESULTS: The three best performing models were RF, Logistic Regression, and XGBoost. RF achieved an average accuracy of 0.74, AUC-ROC of 0.73, Sensitivity of 0.38, and Specificity of 0.88. Logistic Regression achieved an average accuracy of 0.70, AUC-ROC of 0.74, Sensitivity of 0.62, and Specificity of 0.73. XGBoost achieved an average accuracy of 0.72, AUC-ROC of 0.71, Sensitivity of 0.40, and Specificity of 0.85. All models with hematological variables had significantly stronger performance than models trained on only clinical features. Neutrophil parameters had the highest average feature importance. CONCLUSIONS: Machine learning models using hematological analyzer data can classify NICU patients as sepsis positive or negative with stronger performance compared to clinical feature only models. Hematological analyzer variables could augment current sepsis classification machine learning algorithms.

Facilitating Test Status Information Communication in the Time of COVID-19.

The Coronavirus 2019 pandemic has strained nearly every aspect of pathology practice, including preanalytic, analytic, and postanalytic processes. Much of the challenges result from high demand for limited severe acute respiratory syndrome coronavirus 2 testing capacity, a resource required to facilitate patient flow throughout the hospital system and society at large. At our institution, this led to unprecedented increases in inquiries from providers to laboratory staff relating to the expected time to result for their patients. The demand was great enough to require redeployment of staff to handle the laboratory call volume. Although these data are available in our laboratory information system, the data do not interface to our electronic health record system. We developed systems using the R statistical programming language that abstract the necessary data regarding severe acute respiratory syndrome coronavirus 2 polymerase chain reaction testing from our lab system in real time, store it, and present it to clinicians for on demand querying. These data have been accessed over 2500 times by over 100 distinct users. Median length of each user session is approximately 4.9 minutes. Because our lab information system does not persistently store tracking information while our system does, we have been able to iteratively recalculate time to result values for each tracking stop as workflows have changed over time. Facility with informatics and programming concepts coupled with clinical understanding have allowed us to swiftly develop and iterate on applications which provide efficiency gains, allowing laboratory resources to focus on generating test results for our patients.

Implementation of an Extraction-Free COVID Real-Time PCR Workflow in a Pediatric Hospital Setting.

BACKGROUND: This study outlines the development, implementation, and impact of a laboratory-developed, extraction-free real-time PCR assay as the primary diagnostic test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a pediatric hospital. METHODS: Clinical specimens from both upper and lower respiratory tract sources were validated, including nasopharyngeal aspirates, nasopharyngeal swabs, anterior nares swabs, and tracheal aspirates (n = 333 clinical samples). Testing volumes and laboratory turnaround times were then compared before and after implementation to investigate effects of the workflow changes. RESULTS: Compared to magnetic-bead extraction platforms, extraction-free real-time PCR demonstrated ≥95% positive agreement and ≥97% negative agreement across all tested sources. Implementation of this workflow reduced laboratory turnaround time from an average of 8.8 (+/-5.5) h to 3.6 (+/-1.3) h despite increasing testing volumes (from 1515 to 4884 tests per week over the reported period of testing). CONCLUSIONS: The extraction-free workflow reduced extraction reagent cost for SARS-CoV-2 testing by 97%, shortened sample handling time, and significantly alleviated supply chain scarcities due to the elimination of specialized extraction reagents for routine testing. Overall, this assay is a viable option for laboratories to increase efficiency and navigate reagent shortages for SARS-CoV-2 diagnostic testing.

Utility of repeat testing in the evaluation for von Willebrand disease in pediatric patients.

BACKGROUND: Von Willebrand disease (VWD) is the most common inherited bleeding disorder and is caused by quantitative and qualitative defects in von Willebrand factor (VWF). The laboratory diagnosis of VWD in pediatric patients is complicated by VWF interassay and intra-assay variability, stress-induced elevations in VWF levels, and a lack of significant bleeding history with which to correlate test results. OBJECTIVE: Guidelines recommend repeat testing in patients with a high suspicion of VWD and unclear laboratory assay results; however, no studies have evaluated the utility of repeat VWF testing in pediatric patients. METHODS: This retrospective single-center cohort study aimed to determine clinical variables associated with requiring more than one test to diagnose VWD and to establish a cutoff VWF value above which further testing is not informative. RESULTS: Of 811 patients evaluated for a suspected bleeding disorder, 22.2% were diagnosed with VWD, with ~70% diagnosed on the first test. Patients with VWD were younger (5.8 vs. 8.5 years, P = .002) and more likely to have a family history of VWD (38% vs. 22%, P < .001) than those without VWD. Univariate analysis failed to identify any clinical variables that correlated with needing multiple tests for a VWD diagnosis. A cutoff of 100 IU/dL for VWF antigen or activity on the first test yielded negative predictive values >95%. CONCLUSIONS: We demonstrate that the majority of pediatric patients had diagnostic VWF values on the first set of testing. Pediatric patients without a family history of VWD and VWF levels >100 IU/dL may not need further testing to rule out the diagnosis of VWD.

Surgical Pathology Resident Rotation Restructuring at a Tertiary Care Academic Center.

Changes in the field of pathology and resident education necessitate ongoing evaluation of residency training. Evolutionary change is particularly important for surgical pathology rotations, which form the core of anatomic pathology training programs. In the past, we organized this rotation based on subjective insight. When faced with the recent need to restructure the rotation, we strove for a more evidence-based process. Our approach involved 2 primary sources of data. We quantified the number of cases and blocks submitted per case type to estimate workload and surveyed residents about the time required to gross specimens in all organ systems. A multidisciplinary committee including faculty, residents, and staff evaluated the results and used the data to model how various changes to the rotation would affect resident workload, turnaround time, and other variables. Finally, we identified rotation structures that equally distributed work and created a point-based system that capped grossing time for residents of different experience. Following implementation, we retrospectively compared turnaround time and duty hour violations before and after these changes and surveyed residents about their experiences with both systems. We evaluated the accuracy of the point-based system by examining grossing times and comparing them to the assigned point values. We found overall improvement in the rotation following the implementation. As there is essentially no literature on the subject of surgical pathology rotation organization, we hope that our experience will provide a road map to improve pathology resident education at other institutions.

C-C chemokine receptor 2 (CCR2) regulates the hepatic recruitment of myeloid cells that promote obesity-induced hepatic steatosis.

OBJECTIVE: Obesity induces a program of systemic inflammation that is implicated in the development of many of its clinical sequelae. Hepatic inflammation is a feature of obesity-induced liver disease, and our previous studies demonstrated reduced hepatic steatosis in obese mice deficient in the C-C chemokine receptor 2 (CCR2) that regulates myeloid cell recruitment. This suggests that a myeloid cell population is recruited to the liver in obesity and contributes to nonalcoholic fatty liver disease. RESEARCH DESIGN AND METHODS: We used fluorescence-activated cell sorting to measure hepatic leukocyte populations in genetic and diet forms of murine obesity. We characterized in vivo models that increase and decrease an obesity-regulated CCR2-expressing population of hepatic leukocytes. Finally, using an in vitro co-culture system, we measured the ability of these cells to modulate a hepatocyte program of lipid metabolism. RESULTS: We demonstrate that obesity activates hepatocyte expression of C-C chemokine ligand 2 (CCL2/MCP-1) leading to hepatic recruitment of CCR2(+) myeloid cells that promote hepatosteatosis. The quantity of these cells correlates with body mass and in obese mice represents the second largest immune cell population in the liver. Hepatic expression of CCL2 increases their recruitment and in the presence of dietary fat induces hepatosteatosis. These cells activate hepatic transcription of genes responsible for fatty acid esterification and steatosis. CONCLUSIONS: Obesity induces hepatic recruitment of a myeloid cell population that promotes hepatocyte lipid storage. These findings demonstrate that recruitment of myeloid cells to metabolic tissues is a common feature of obesity, not limited to adipose tissue.

Roles of the proline-rich domain in SLP-76 subcellular localization and T cell function.

The adaptor protein Src homology (SH)2 domain-containing and leukocyte-specific phosphoprotein of 76 kDa (SLP-76) is critical for signal transduction in multiple hematopoietic lineages. It links proximal and distal T cell receptor signaling events through its function as a molecular scaffold in the assembly of multimolecular signaling complexes. Here we studied the functional roles of sub-domains within the SLP-76 proline-rich region, specifically the Gads binding domain and the recently defined P1 domain. To gain a further understanding of the functions mediated by this region, we used three complementary approaches as follows: reconstitution of SLP-76-deficient cells with functional domain deletion mutants, blocking molecular associations through the expression of a dominant negative protein fragment, and directed localization of SLP-76 to assess the role of the domains in SLP-76 recruitment. We find the Gads binding domain and the P1 domain are both necessary for optimal SLP-76 function, and in the absence of these two regions, SLP-76 is functionally inert. Furthermore, we provide direct evidence that SLP-76 localization and, in turn, function are dependent upon association with Gads.