Common laboratory tests, values, and interpretations

Identification of Pulmonary Hypertension Animal Models Using a New Evolutionary Machine Learning Framework Based on Blood Routine Indicators

Pulmonary Hypertension (PH) is a global health problem that affects about 1% of the global population. Animal models of PH play a vital role in unraveling the pathophysiological mechanisms of the disease. The present study proposes a Kernel Extreme Learning Machine (KELM) model based on an improved Whale Optimization Algorithm (WOA) for predicting PH mouse models. The experimental results showed that the selected blood indicators, including Haemoglobin (HGB), Hematocrit (HCT), Mean, Platelet Volume (MPV), Platelet distribution width (PDW), and Platelet-Large Cell Ratio (P-LCR), were essential for identifying PH mouse models using the feature selection method proposed in this paper. Remarkably, the method achieved 100.0% accuracy and 100.0% specificity in classification, demonstrating that our method has great potential to be used for evaluating and identifying mouse PH models.

Acoustofluidic hematocrit determination

Hematocrit (HCT) measurements of blood from patients, blood donors and athletes are routinely performed on a daily basis. These measurements are often performed in centralized hospital labs by whole blood analyzers, which leads to long time-to-result. On site measurements, based on centrifugation can be done, but these assays require manual handling, are slow and can just measure HCT in contrast to the central lab whole blood analyzers. In this work, we present a microfluidic based method to measure HCT in blood samples by acoustic separation of whole blood into discrete regions of plasma and red blood cells. Comparison of the areas of the red blood cell and plasma regions gives an accurate HCT value, with a linear correlation to the centrifugation-based reference method. A readout can be performed within 2 s of acoustic actuation providing a readout accuracy of approximately 3% points (pp) HCT. Additional accuracy can be achieved by extending the acoustic actuation to 20 s, yielding an error of less than 1 pp HCT. This acoustic tool is optimal for integration into a lab-on-a-chip device with in-line measurements of different clinical parameters.

Electrochemical hematocrit determination in a direct current microfluidic device

Hematocrit (HCT) tests are widely performed to screen blood donors and to diagnose medical conditions. Current HCT test methods include conventional microhematocrit, Coulter counter, CuSO4 specific gravity, and conductivity-based point-of-care (POC) HCT devices, which can be either expensive, environmentally inadvisable, or complicated. In the present work, we introduce a new and simple microfluidic system for a POC HCT determination. HCT was determined by measuring current responses of blood under 100 V DC for 1 min in a microfluidic device containing a single microchannel with dimensions of 180 μm by 70 μm and 10 mm long. Current responses of red blood cell (RBC) suspensions in PBS or separately plasma at HCT concentrations of 10, 20, 25, 30, 35, 40, 45, 50, 55, 60, and 70 vol% were measured to show feasibility of the microfluidic system for HCT determination. Key parameters affecting current responses included electrolysis bubbles and irreversible RBC adsorption; parameters were optimized via addition of nonionic surfactant Triton X-100 into sample solution and carbonizing electrode surfaces. The linear trend line of current responses over a range of RBC concentrations were obtained in both PBS and plasma. This work suggested that a simple microfluidic device could be a promising platform for a new POC HCT device.