Detection of dysplasia in peripheral blood: Proposal of an algorithm to detect myelodysplastic syndromes and chronic myelomonocytic leukemias on a high-speed technical platform using the Sysmex XN™ analyser.

INTRODUCTION: Chronic Myelomonocytic Leukemia (CMML) and Myelodysplastic Syndromes (MDS) are increasingly represented in the general population. We propose a screening strategy based on algorithms calculated from quantitative and analytical data from the XN analyser. MATERIALS AND METHODS: We tested the performance of previously published MDS and CMML scores on an evaluation cohort of 749 individual eligible patients over 50 years of age. These patients were classified into 3 groups as follows: 713 patients without MDS or CMML, 18 patients with MDS, and finally 18 patients with CMML. In a second step, a routine cohort of 37 828 samples was studied to evaluate the impact of this approach. RESULTS: The concordance rate between cytology and the two scores is 92.1%. The sensitivity and specificity of the CMML score are 100% and 96.2%, respectively. For the MDS score, they are 83.3% and 89.6% respectively. The ratio of platelets measured by fluorescence on board (PLT-F) as reflex tests generated is 1.5% after 6 months. The additional smear ratio for suspected MDS is calculated at 0.6%. CONCLUSION: We propose a flowchart using embedded artificial intelligence to help the cytologist in an optimized smear review and thus improve guidance to the clinician and the patients in the diagnosis process. This strategy permits a more comprehensive approach to MDS and CMML detection fitting with the new definition of CMML according to the recommendations of the World Health Organization (WHO) published in 2022.

Towards Addressing the Body Electrolyte Environment via Sweat Analysis:Pilocarpine Iontophoresis Supports Assessment of Plasma Potassium Concentration.

Electrolyte concentration in sweat depends on environmental context and physical condition but also on the pathophysiological status. Sweat analyzers may be therefore the future way for biological survey although how sweat electrolyte composition can reflect plasma composition remains unclear. We recruited 10 healthy subjects and 6 patients to have a broad range of plasma electrolyte concentrations (chloride, potassium and sodium) and pH. These variables were compared to those found in sweat produced following cycling exercise or pilocarpine iontophoresis, a condition compatible with operating a wearable device. We found no correlation between plasma and sweat parameters when exercise-induced sweat was analyzed, and we could identify a correlation only between plasma and sweat potassium concentration (R = 0.78, p < 0.01) when sweat was induced using pilocarpine iontophoresis. We tested measurement repeatability in sweat at 24hr-interval for 3 days in 4 subjects and found a great intra-individual variability regarding all parameters in exercise-induced sweat whereas similar electrolyte levels were measured in pilocarpine-induced sweat. Thus, electrolyte concentration in sweat sampled following physical activity does not reflect concentration in plasma while pilocarpine iontophoresis appears to be promising to reproducibly address sweat electrolytes, and to make an indirect evaluation of plasma potassium concentration in chronic kidney disease and arrhythmia.