10.6084/m9.figshare.7617155.v1 Evashin Pillay Evashin Pillay Shanaz Khodaiji Shanaz Khodaiji Belinda Bezuidenhout Belinda Bezuidenhout Monwabisi Litshie Monwabisi Litshie Thérèsa Coetzer Thérèsa Coetzer MOESM1 of Evaluation of automated malaria diagnosis using the Sysmex XN-30 analyser in a clinical setting Springer Nature 2019 Plasmodium falciparum Automated diagnosis Sysmex XN-30 analyser 2019-01-22 05:00:00 Dataset https://springernature.figshare.com/articles/dataset/MOESM1_of_Evaluation_of_automated_malaria_diagnosis_using_the_Sysmex_XN-30_analyser_in_a_clinical_setting/7617155 Additional file 1: Fig. S1. XN-30 software improvements. a. In the prototype software, the M scattergram plot area was divided into 3 regions classifying signals as WBCs (cluster a), non-infected RBCs, platelets and debris (cluster b) and MI-RBCs (cluster c). In brief, the gating strategy sequence was to first identify cluster a and then cluster b. In the prototype, all remaining signals were then assigned to cluster c. Upon further investigation, it was identified that the specified MI-RBC area (cluster c) was too broad, giving rise to false positive MI-RBC results. b. The software was subsequently improved for the XN-30 by narrowing the MI-RBC area (cluster c) and incorporating the recognition of one or more distinct clusters (ring forms, gametocytes, trophozoites/schizonts) within an appropriate shape and position as a prerequisite for generating an MI-RBC result. Fig. S2. XN-30 malaria classification algorithm. The left side illustrates the algorithm flow if a malaria cluster is not recognized. In such cases, if the MI-RBC# is < LoQ, the sample is reported as malaria negative (MI-RBC green box). However, if the MI-RBC# is ≥ LoQ but signals are detected in the absence of appropriate clustering, or an incorrect cluster shape is generated within the MI-RBC area, then the result is suppressed and an MI-RBC abnormal scattergram flag is generated. An indeterminate result is reported (MI-RBC grey box). An example is presented in M scattergram (a). The right side illustrates the algorithm flow if a malaria cluster is recognized. In such cases, if the MI-RBC# is < LoQ, the sample is reported as malaria negative (MI-RBC green box). However, if the MI-RBC# is ≥ LoQ the sample is reported as malaria positive (MI-RBC red box). An example is presented in M scattergram (b). Fig. S3. XN-30 M scattergrams, MI-RBC values and the species RBC flags for patient samples infected with a P. falciparum (P. f) and b P. ovale (others). Measurements were performed in WB mode. P. ovale parasites were confirmed microscopically. SFL: side fluorescence light; FSC: forward scattered light; blue dots: non-infected RBCs, platelets and debris; red dots: MI-RBCs; green and orange dots: different P. ovale life cycle forms; turquoise dots: white blood cells. Fig. S4. Correlation between P. falciparum parasitaemia obtained from the XN-30 (MI-RBC%) and expert microscopy. Samples were analysed in a LM mode and b PD mode. R2 indicates the coefficient of determination. The diagonal lines represent the regression lines. Fig. S5. XN-30 M scattergrams of malaria-negative patient samples with a thalassaemia, b sickle cell disease and c reticulocytosis of 13.86%. The grey area within the large blue cluster reflects the region where MI-RBCs scatter, but the software correctly triggered an “abnormal MI-RBC scattergram”. Measurements were performed in WB mode. SFL: side fluorescence light; FSC: forward scattered light; blue dots: non-infected RBCs, platelets and debris; turquoise dots: white blood cells. Fig. S6. Stability of MI-RBC parameters (MI-RBC#) at 4–8 °C measured in WB mode on the XN-30. Four samples with P. falciparum parasitaemia ranging from a high (21–107 × 103/µL), to b low (3–4.5 × 103/µL), were stored at 4–8 °C and analysed at various time intervals. The first measurement was performed within 24 h of sample collection from the patient and thus the initial point is different for each sample.