1.Clinical value of automated EasyNAT system for the diagnosis of tuberculosis in paraffin-embedded tissues.
Jialu CHE ; Zichen LIU ; Kun LI ; Chen ZHANG ; Nanying CHE
Journal of Peking University(Health Sciences) 2024;56(6):1047-1051
OBJECTIVE:
Assessing the accuracy of automated EasyNAT system for rapidly detecting paraffin-embedded tissue for the diagnosis of tuberculosis.
METHODS:
A retrospective analysis was conducted on 134 patients, comprising 101 with confirmed tuberculosis and 33 without tuberculosis, treated at Beijing Chest Hospital, Capital Medical University, between 2018 and 2022.The clinical diagnostic results served as the standard for assessing the diagnostic performance of the EasyNAT system in comparison to quantitative real-time polymerase chain reaction (qPCR) for tuberculosis detection in paraffin-embedded tissues.The evaluation criteria included sensitivity, specificity, positive predictive value, negative predictive value, and accuracy rate.
RESULTS:
Based on the clinical diagnostic results, the EasyNAT assay demonstrated a sensitivity of 87.1%(88/101, 95%CI: 79.2%-92.3%)and a specificity of 100.0%(33/33, 95%CI: 89.6%-100.0%).The positive predictive value, negative predictive value, and accuracy rate were 100% (88/88, 95%CI: 95.8%-100.0%), 71.7%(33/46, 95%CI: 57.5%-82.7%), and 90.3%(121/134, 95%CI: 84.1%-94.2%), respectively.In comparison, the qPCR assay exhibited a sensitivity of 96.0%(90.3%-98.5%)and a specificity of 100.0%(89.6%-100.0%).The positive predictive value, negative predictive value, and accuracy rate for qPCR were 100.0%(96.2%-100.0%), 89.2%(75.3%- 95.7%), and 97.0%(92.6%-98.8%).The Cohen's kappa value of 0.84 indicated substantial agreement between EasyNAT and qPCR.The detection rate of tuberculosis using this method was 86.4%(38/44, 95%CI: 73.3%-93.6%), while the detection rate for extrapulmonary tuberculosis was 87.7%(50/57, 95%CI: 76.8%-93.9%).In comparison, qPCR showed a detection rate of 97.7%(88.2%- 99.6%) for pulmonary tuberculosis and 94.7%(85.6%-98.6%)for extrapulmonary tuberculosis.There was no statistically significant difference in the detection results between the method and qPCR for both pulmonary and extrapulmonary tuberculosis(P>0.05).Importantly, the EasyNAT detection combined nucleic acid extraction, amplification, and analysis into one process.Compared with traditional qPCR methods, manual operation time was reduced by 2 hours, leading to an overall reduction in total testing time by 3 hours.
CONCLUSION
The EasyNAT nucleic acid rapid detection system can quickly, conveniently, and accurately detect Mycobacterium tuberculosis DNA in paraffin-embedded tissues, demonstrating significant clinical utility in the pathological diagnosis of tuberculosis.
Humans
;
Retrospective Studies
;
Paraffin Embedding
;
Sensitivity and Specificity
;
Tuberculosis/microbiology*
;
Real-Time Polymerase Chain Reaction
;
Mycobacterium tuberculosis/genetics*
;
Predictive Value of Tests
;
Nucleic Acid Amplification Techniques/methods*
;
Female
;
Male
2.Medical Institution's Multiple Role in the Collaborative Innovation Transformation Mode of "Industry-University-Research-Medicine" on Domestic Surgical Robots.
Zhiqun SHU ; Jialu QU ; Shuxian ZHANG ; Yirou TIE ; Yuan CHE ; Junting LI ; Letong JIANG ; Huiqing SHEN
Chinese Journal of Medical Instrumentation 2023;47(5):582-586
In recent years, with the rapid development of Chinese domestic surgical robot technology and the expansion of the application market, the "industry-university-research-medicine" collaborative innovation transformation mode has gradually developed and formed. Medical institutions play an important role in multi-party cooperation with enterprises, universities, and research institutes, as well as in product planning, technology research and development, achievement transformation, and personnel training. On the basis of reviewing the current situation of the development of the "industry-university-research-medicine" collaborative innovation transformation mode of domestic surgical robots, this study explores the multiple roles played by medical institutions in this mode and challenges, further putting forward corresponding recommendations.
Humans
;
Robotics
;
Universities
;
Medicine
;
Industry
;
Technology

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