Abstract:Hematology analyzers capable of performing complete blood count (CBC) have lagged in their prevalence at the point-of-care. Sight OLO (Sight Diagnostics, Israel) is a novel hematological platform which provides a 19-parameter, five-part differential CBC, and is designed to address the limitations in current point-of-care hematology analyzers using recent advances in artificial intelligence (AI) and computer vision.Accuracy, repeatability, and flagging capabilities of OLO were compared with the Sysmex XN-Series… Show more
“…We selected FBC due to the approval of a point-of-care haematology analyser with a time-to-result of 10 min (OLO) and explainability analyses showing that FBC components were most informative (eg, basophil, eosinophil, and neutrophil counts). 5 , 28 The timeline of model development, evaluation, and deployment is shown in figure 1A . Figure 1 Overview of study design Overview shows the timeline of model development, evaluation, and deployment (A); successive elimination of less informative predictors from CURIAL-1.0 to optimise for generalisability (CURIAL-Lab) and result-time (CURIAL-Rapide; B); and a proposed novel rapid screening pathway for COVID-19 in emergency departments, which combines lateral flow device testing with artificial intelligence screening (C).…”
Section: Methodsmentioning
confidence: 99%
“…To prospectively assess the operational and predictive performance of CURIAL-Rapide in a laboratory-free setting, we deployed two OLO rapid haematology analysers in the John Radcliffe Hospital's Emergency Department (Oxford), as part of an OUH-approved service evaluation (Ulysses ID 6907). 28 We simultaneously aimed to improve routine clinical care by reducing the turnaround time for routine blood test results in the emergency department. The analysis plan and data requirements were determined prospectively and registered with the Trust service evaluation database.…”
Section: Methodsmentioning
confidence: 99%
“…25,26 A 2021 editorial highlighted the promise of CURIAL-1.0 to support patients with COVID-19, discussing the need for further evaluation to show benefits over standard of care in a real-world clinical setting. 27 Moreover, recent advances in point-of-care testing include the availability of rapid haematology analysers, which offer results within 10 min, 28 and their role within artificial intelligence-driven COVID-19 screening remains unexplored.…”
Section: Implications Of All the Available Evidencementioning
confidence: 99%
“…We selected FBC due to the approval of a point-of-care haematology analyser with a time-to-result of 10 min (OLO) and explainability analyses showing that FBC components were most informative (eg, basophil, eosinophil, and neutrophil counts). 5,28 The time line of model development, evaluation, and deploy ment is shown in figure 1A.…”
Section: Diagnostic Models To Identify Patients Presenting With Covid-19mentioning
“…We selected FBC due to the approval of a point-of-care haematology analyser with a time-to-result of 10 min (OLO) and explainability analyses showing that FBC components were most informative (eg, basophil, eosinophil, and neutrophil counts). 5 , 28 The timeline of model development, evaluation, and deployment is shown in figure 1A . Figure 1 Overview of study design Overview shows the timeline of model development, evaluation, and deployment (A); successive elimination of less informative predictors from CURIAL-1.0 to optimise for generalisability (CURIAL-Lab) and result-time (CURIAL-Rapide; B); and a proposed novel rapid screening pathway for COVID-19 in emergency departments, which combines lateral flow device testing with artificial intelligence screening (C).…”
Section: Methodsmentioning
confidence: 99%
“…To prospectively assess the operational and predictive performance of CURIAL-Rapide in a laboratory-free setting, we deployed two OLO rapid haematology analysers in the John Radcliffe Hospital's Emergency Department (Oxford), as part of an OUH-approved service evaluation (Ulysses ID 6907). 28 We simultaneously aimed to improve routine clinical care by reducing the turnaround time for routine blood test results in the emergency department. The analysis plan and data requirements were determined prospectively and registered with the Trust service evaluation database.…”
Section: Methodsmentioning
confidence: 99%
“…25,26 A 2021 editorial highlighted the promise of CURIAL-1.0 to support patients with COVID-19, discussing the need for further evaluation to show benefits over standard of care in a real-world clinical setting. 27 Moreover, recent advances in point-of-care testing include the availability of rapid haematology analysers, which offer results within 10 min, 28 and their role within artificial intelligence-driven COVID-19 screening remains unexplored.…”
Section: Implications Of All the Available Evidencementioning
confidence: 99%
“…We selected FBC due to the approval of a point-of-care haematology analyser with a time-to-result of 10 min (OLO) and explainability analyses showing that FBC components were most informative (eg, basophil, eosinophil, and neutrophil counts). 5,28 The time line of model development, evaluation, and deploy ment is shown in figure 1A.…”
Section: Diagnostic Models To Identify Patients Presenting With Covid-19mentioning
“…Even considering that the gold standard method for cell identification is manual microscopy, mainly CBCs are realized in hematological analyzers, which use flow cytometry or resistivity-impedance methodologies 4 . However, these require frequent maintenance and are large and expensive devices, restricted to hospitals and central laboratories of considerable size.…”
The complete blood count (CBC) is one of the most requested tests by physicians. CBC tests, most realized in conventional hematological analyzers, are restricted to centralized laboratories due to frequent maintenance, large devices, and expensive costs required. On the other hand, most handheld CBC devices commercially available show high prices and are not liable to calibration or control procedures, which results in poor quality compared to standard hematology instruments. The Hilab system is a small-handed hematological platform that uses microscopy and chromatography techniques for blood cells and hematimetric parameters analysis through artificial intelligence, machine learning, and deep learning techniques. For clinical evaluation of the handheld CBC device, 450 blood samples were analyzed. The samples encompassed normal (82%) and pathological conditions (18%), such as thalassemias (2.2%), anemias (6.6%), and infections (9.2%). For all analytes, accuracy, precision, method comparison, and flagging capabilities of the Hilab System, were compared with the Sysmex XE-2100 (Sysmex, Japan) results. The sample source (venous and capillary) influences were also evaluated. Pearson correlation, Student t test, bias, and the Bland–Altman plot of each blood count analyte were calculated and shown. The significance level was set at p ≤ 0.05. For clinical evaluation, Hilab System and the Sysmex XE-2100 showed a strong correlation (r ≥ 0.9) for most evaluated parameters. In the precision study, analytes showed CV inside the limits established according to European Federation of Clinical Chemistry and Laboratory Medicine guidelines. The flagging capabilities of the Hilab system, compared to the manual microscopy technique, presented high sensibility, specificity, and accuracy. Venous and capillary samples (p > 0.05) do not differ statistically. Considering the need for point-of-care CBCs, the study indicated that the Hilab system provides fast, accurate, low cost, and robust analysis for reliable clinical use.
Hematology analyzers capable of performing complete blood count (CBC) have lagged in their prevalence at the point-of-care. Sight OLO (Sight Diagnostics, Israel) is a novel hematological platform which provides a 19-parameter, five-part differential CBC, and is designed to address the limitations in current point-of-care hematology analyzers using recent advances in artificial intelligence (AI) and computer vision.Accuracy, repeatability, and flagging capabilities of OLO were compared with the Sysmex XN-Series System (Sysmex, Japan). Matrix studies compared performance using venous, capillary and direct-from-fingerprick blood samples. Regression analysis shows strong concordance between OLO and the Sysmex XN, demonstrating that OLO performs with high accuracy for all CBC parameters. High repeatability and reproducibility were demonstrated for most of the testing parameters. The analytical performance of the OLO hematology analyzer was validated in a multicenter clinical laboratory setting, demonstrating its accuracy and comparability to clinical laboratory-based hematology analyzers. Furthermore, the study demonstrated the validity of CBC analysis of samples collected directly from fingerpricks.
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