8 results about "Leukocyte Counts" patented technology

Provided is a subject measurement device capable of efficiently performing a subject inspection service including an inspection of malaria infection. A subject measurement device for measuring a subject collected from a subject includes: a measurement unit for preparing a measurement sample from the subject and a reagent and detecting at least an optical signal corresponding to cells in the measurement sample; and an analysis means for analyzing the cells on the basis of the measurement of the subject by the measurement means. The measurement unit is capable of selectively performing a plurality of measurement operations on a subject. The plurality of measurement operations include: a first measurement operation in which a subject is measured using a first reagent containing a first fluorescent dye for staining white blood cells for classification of white blood cells, and a second measurement operation in which the subject is measured using a second reagent containing a second fluorescent dye for staining white blood cells for classification of white blood cells; a second measurement operation in which the subject is measured using a second reagent containing a second fluorescent dye that stains cells suspected of being infected with malaria; and a third measurement operation in which the subject is measured using the first reagent and the second reagent.

The invention relates to a method for constructing a preeclampsia prediction model by using clinical laboratory data and a related application thereof. Specifically, the preeclampsia risk prediction model is constructed based on a plurality of clinical indexes of pregnant women, a plurality of clinical laboratory data and insulin growth binding factor binding protein 1 and / or placental growth factors. The clinical laboratory data comprises leukocyte count and / or urine protein, and further comprises any one or combination of platelet count, monocyte proportion, glutamic-straw / glutamic-pyruvic transaminase ratio, glutamyltranspeptidase, uric acid and high-density lipoprotein. The constructed preeclampsia risk prediction model can provide a reliable implementation means for early prevention and early treatment of preeclampsia. Meanwhile, the sensitivity of the prediction model is 88.0% when the specificity of early eclampsia is 85.04% and the sensitivity of the prediction model is 62.5% when the specificity of late eclampsia is 85.04% in a complete independent verification set, and the detection performance of the prediction model is higher than that of the current detection performance.

The invention provides a model for predicting the risk of allergic reaction of a Wilson disease patient during copper expelling treatment, and belongs to the crossing field of clinical medicine and biological information technology. The risk prediction model comprises: an input module receiving patient parameter indexes composed of a sodium dimercaptopropanesulfonate injection dosage, a severe adverse drug reaction, a drug allergy history, a neutrophil count, a lymphocyte count, a ratio of neutrophil to lymphocyte, a ratio of platelets to lymphocyte, a leukocyte count, a urine copper level and a platelet count; the processing module is connected with the input module and is used for calculating the score and prediction probability of the allergic reaction during copper expelling treatment based on the parameter indexes of the patient; and the output module is connected with the processing module, and outputs the allergic reaction risk probability obtained by the risk prediction model during the copper expelling treatment of the Wilson disease patient. The risk prediction model can be conveniently used for early recognition and risk prediction of anaphylaxis of a Wilson disease patient during copper expelling treatment.

The present invention relates to an isolated targeted delivery system comprising a CD45+ leukocyte cell comprising within said cell a complex of one or more iron binding proteins and a pharmaceutically active substance, label or pharmaceutically active substance and label, for use in a method of treatment or diagnosis of glioma.

The invention discloses an application of alpha-ketoglutaric acid in diagnosis and treatment of acute pancreatitis, diagnosis of acute pancreatitis is realized by detecting the concentration of alpha-ketoglutaric acid in serum or plasma of a detected person, and the invention also provides an application of alpha-ketoglutaric acid in preparation of a diagnostic reagent for monitoring the condition of acute pancreatitis. By dynamically detecting the concentration change of alpha-ketoglutaric acid in serum or plasma of a patient, the real-time monitoring of the illness state is realized. The invention discloses the specific accumulation of the endogenous alpha-ketoglutaric acid level in the serum of a patient with acute pancreatitis for the first time, and the endogenous alpha-ketoglutaric acid level is remarkably positively correlated with disease severity indexes (such as amylase and leukocyte count); the invention provides a simple, convenient and effective serological biomarker for early and accurate diagnosis and illness monitoring of acute pancreatitis, and provides a novel treatment strategy with strong targeting property.

The invention relates to the field of hepatobiliary postoperative infection risk grading early warning, in particular to a hepatobiliary postoperative infection risk grading early warning method based on clinical parameters. The method comprises the steps that original clinical parameters are collected and preprocessed, and preprocessed standardized clinical parameters are obtained; a clinical basic weight is introduced, and based on the preprocessed standardized clinical parameters, an infection risk score is obtained through calculation by applying a multi-dimensional distribution mapping algorithm; and risk grades are divided based on infection risk scores, a dynamic weighting mechanism emphasizing effective updating is introduced, and clinical basic weights are dynamically updated. The problems that a traditional hepatobiliary postoperative infection risk assessment method neglects complex high-order interaction and non-linear correlation among indexes such as body temperature, leukocyte count, procalcitonin and C-reactive protein, cannot adjust parameter weights in real time according to dynamic changes of postoperative illness states of patients, lacks a clear risk grading rule and is poor in risk assessment accuracy are solved. And the engineering application value is limited.

The invention relates to the technical field of leukocyte counting, in particular to a leukocyte classified counting device and method for acute respiratory infection patients. The method comprises the following steps: screening leukocytes according to manifestation of cell membrane fluorescence and manifestation component types to obtain leukocytes in a single-cell suspension sample; dividing a plurality of periodic groups according to the similarity degree of the fluorescence intensity of the interleukin nuclear DNA; further analyzing scattered light characteristics of cells in a single cell population in a same-period state, and dividing cell subpopulations; performing corresponding one-to-one combination on the cell subgroups of every two cycle groups according to differences among different components to obtain leukocyte classification of the single-cell suspension sample; according to the cell number distribution of the classification results of the multiple single-cell suspension samples, final classification counting is achieved. According to the method, classification division and combination of the white blood cells in different growth states are combined, so that the accuracy of classification division of the white blood cells is improved, and a more accurate white blood cell classification counting result for acute respiratory infection patients is obtained.

This invention discloses a method and system for early warning of pediatric sepsis risk based on leukocyte dynamic trajectory. The method includes: acquiring time-series leukocyte count data of a target pediatric patient for N consecutive days after admission or diagnosis of sepsis, forming a raw data sequence; preprocessing the raw data sequence to eliminate baseline differences between individuals; inputting the preprocessed data sequence into a pre-trained leukocyte dynamic trajectory classification model to output the probability of the target pediatric patient belonging to each category, and determining the category with the highest probability as the current trajectory category of the target pediatric patient; mapping the current trajectory category to the corresponding sepsis risk level according to a preset trajectory category-risk level mapping rule; and determining whether to generate early warning information based on the sepsis risk level. This invention can automatically analyze continuous leukocyte count data after patient admission, identify its characteristic dynamic change trajectory, automatically determine the risk level based on the trajectory pattern, and issue timely early warnings.