6 results about "Laboratory quality control" patented technology

The application belongs to the technical field of biological detection, and discloses a cardiovascular marker control article and a preparation method thereof. The cardiovascular marker control article comprises a serum matrix, antigens, a preservative and a stabilizer. The antigens include cardiac troponin I antigens, creatine kinase isoenzyme antigens, myoglobin antigens, amino-terminal brain natriuretic peptide precursor antigens, brain natriuretic peptide antigens, D-dimer antigens, heart-type fatty acid-binding protein antigens, myeloperoxidase antigens and lipoprotein phospholipase A2 antigens. The stabilizer includes at least one of D-trehalose, sucrose, glycine, inositol and polyethylene glycol. The cardiovascular marker control article can cover various cardiovascular disease markers, including heart failure, pulmonary embolism, vasculitis and atherosclerosis, myocardial injury, myocardial infarction and the like. The control article can be used as a third-party control article for indoor and inter-laboratory quality control of a cardiovascular disease screening and auxiliary diagnosis measurement system.

The invention belongs to the technical field of detection, and particularly discloses a measurement uncertainty evaluation method for measuring immune factors in serum by an ELISA (enzyme-linked immuno sorbent assay) method. According to the method, ELISA detection is carried out on immune factors (such as IL-1beta) in serum of an experimental animal in contact with a medical instrument according to standards such as GB / T16886.20-2015, system analysis comprises nine types of uncertainty sources such as repeated detection, standard substance preparation and sample dilution, the standard uncertainty of each component is calculated through mathematical methods such as rectangular distribution and a least square method, and the standard uncertainty of each component is calculated according to the standard uncertainty. And synthesizing the standard uncertainty and calculating the expansion uncertainty, and finally outputting a standard detection result. The method comprehensively covers the uncertainty source, is rigorous in computational logic and clear in key quality control factors, provides a scientific and complete uncertainty evaluation scheme for medical instrument immunogenicity evaluation and immune factor determination in other experimental scenes, is beneficial to laboratory quality control and detection result optimization, and has wide practicability.

The invention relates to the field of intelligent medical treatment, in particular to a construction method and equipment of a laboratory quality control model and a program product. The method includes: acquiring a laboratory detection sample data set; constructing a first-grade quality control grade of laboratory quality, wherein each grade corresponds to different scores; performing index quantification on the score of any one first-level quality control grade to obtain L second-level quantitative indexes; calculating L secondary quantitative index scores of the laboratory sample data, and constructing a weight matrix; calculating and obtaining a quality control score based on the secondary quantitative index score and the weight matrix; based on the quality control score, positioning a second-level quantitative index of the last three digits of contribution degree sorting, and marking the second-level quantitative index as a core optimization factor; and decomposing the core optimization factor into a standard variable and a non-standard variable, optimizing the non-standard variable, and repeating the steps until the quality control score of the laboratory sample reaches a preset quality control score, thereby obtaining the quality control model of the medical examination laboratory. The application has good clinical value.

This invention provides a vibration testing capability verification sample and method based on the test resonant frequency, belonging to the field of capability verification technology. The method includes: participating laboratories fixing the obtained verification sample on the table surface of a vibration testing rig; installing control sensors and monitoring sensors according to pre-compiled capability verification guidelines; wherein, the control sensors are used to detect the test frequency, and the monitoring sensors are used to monitor the resonant frequency; starting the vibration testing rig and conducting the test according to the vibration test conditions, and measuring the resonant frequency through the monitoring sensors; evaluating the resonant frequency measured by each participating laboratory according to pre-established evaluation criteria, thereby verifying the vibration testing capability of each laboratory. Using the verification sample and verification method provided by this invention, a comprehensive examination of the human, machine, material, method, environment, and measurement factors during the vibration testing process in participating laboratories can be conducted, while simultaneously identifying differences between laboratories, promoting the improvement of laboratory vibration testing technology, and enhancing the laboratory quality control level.

The invention discloses a laboratory quality control data management method, and relates to the technical field of big data management, and the method comprises the steps: obtaining laboratory quality control data, and carrying out the classification according to the food category, and obtaining a plurality of quality control data sets; performing trend consistency analysis on a plurality of pieces of detection category data in the quality control data sequence to obtain category credibility; performing category integrity analysis on the quality control data sequence to obtain integrity credibility; screening to obtain quality control data sequences of a plurality of same storage places, and performing transverse trend consistency analysis to obtain transverse credibility; and performing weighted calculation on the category credibility, the integrity credibility and the transverse credibility to obtain comprehensive credibility, performing credibility grading on the quality control data sequence, performing hierarchical storage, and performing laboratory quality control data management. The technical problem of poor quality control data management effect in the prior art is solved.