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Zou Z, Tang H, Xiao E, Zhou Y, Yin X, Hu Z, Cai Y, Han Q, Wang L. Ensuring Clinical Excellence: The Mindray SAL9000 Biochemical Immunoassay System. Cell Biochem Biophys 2024:10.1007/s12013-024-01568-3. [PMID: 39419930 DOI: 10.1007/s12013-024-01568-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/17/2024] [Indexed: 10/19/2024]
Abstract
This study aimed to evaluate the performance and clinical laboratory adaptability of the Mindray SAL9000 biochemical immunoassay automation system, ensuring compliance with ISO 15189 standards and relevant national requirements. We conducted comprehensive performance verification tests on 21 biochemical analytes and 15 immunoassays, including precision, accuracy, linear bias, measurement range assessments, interference testing, reference range validation, inter-instrument comparison, and carryover verification. The Mindray SAL9000 demonstrated high performance across various parameters, with all analytes showing good linearity and minimal bias. While specific interfering substances affected some analytes, the system showed excellent resistance to common interferences such as hemolysis, ascorbic acid, and jaundice. The inter-instrument comparison with the BS2000M and Roche 702 indicated a good correlation, with most parameters showing biases of less than 10%, although exceptions were noted for ALT and AST. In conclusion, the Mindray SAL9000 meets clinical requirements through its high precision, excellent accuracy, and broad measurement range, making it a reliable and adaptable choice for clinical outpatient and emergency laboratories.
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Affiliation(s)
- Zhenzhen Zou
- Center of Clinical Laboratory, The Fourth Affiliated of Soochow University, Suzhou, Jiangsu, 215000, China
| | - Honghui Tang
- Center of Clinical Laboratory, The Fourth Affiliated of Soochow University, Suzhou, Jiangsu, 215000, China
| | - Erya Xiao
- Center of Clinical Laboratory, The Fourth Affiliated of Soochow University, Suzhou, Jiangsu, 215000, China
| | - Yu Zhou
- Suzhou Affiliated Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, 215000, China
| | - Xuebei Yin
- Center of Clinical Laboratory, The Fourth Affiliated of Soochow University, Suzhou, Jiangsu, 215000, China
| | - Zhen Hu
- Center of Clinical Laboratory, The Fourth Affiliated of Soochow University, Suzhou, Jiangsu, 215000, China
| | - Yang Cai
- Center of Clinical Laboratory, The Fourth Affiliated of Soochow University, Suzhou, Jiangsu, 215000, China
| | - Qingzhen Han
- Center of Clinical Laboratory, The Fourth Affiliated of Soochow University, Suzhou, Jiangsu, 215000, China
| | - Lin Wang
- Center of Clinical Laboratory, The Fourth Affiliated of Soochow University, Suzhou, Jiangsu, 215000, China.
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Nijman J, Zoodsma RS, Koomen E. A Strategy for Artificial Intelligence With Clinical Impact-Eyes on the Prize. JAMA Pediatr 2024; 178:219-220. [PMID: 38285473 DOI: 10.1001/jamapediatrics.2023.6259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
This Viewpoint describes a strategy for addressing major challenges in artificial intelligence in pediatrics to maximize clinical impact.
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Affiliation(s)
- Joppe Nijman
- Department of Pediatric Intensive Care, University Medical Center Utrecht, Utrecht, the Netherlands
- Data Science Working Group, European Society of Pediatric and Neonatal Intensive Care, Geneva, Switzerland
| | - Ruben S Zoodsma
- Department of Pediatric Intensive Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Erik Koomen
- Department of Pediatric Intensive Care, University Medical Center Utrecht, Utrecht, the Netherlands
- Data Science Working Group, European Society of Pediatric and Neonatal Intensive Care, Geneva, Switzerland
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