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Integrating serum microRNAs and electronic health records improved the diagnosis of tuberculosis.
Gao, Shu-Hui; Chen, Chun-Guang; Zhuang, Chun-Bo; Zeng, Yu-Ling; Zeng, Zhen-Zhen; Wen, Pei-Hao; Yu, Yong-Min; Ming, Liang; Zhao, Jun-Wei.
  • Gao SH; Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Chen CG; Department of Clinical Laboratory, Henan Provincial Infectious Disease Hospital, Zhengzhou, 450000, China.
  • Zhuang CB; Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Zeng YL; Department of Clinical Laboratory, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Zeng ZZ; Department of Nuclear Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Wen PH; Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Yu YM; Department of Clinical Laboratory, Henan Provincial Infectious Disease Hospital, Zhengzhou, 450000, China.
  • Ming L; Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Zhao JW; Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
J Clin Lab Anal ; 35(8): e23871, 2021 Aug.
Article en En | MEDLINE | ID: mdl-34106501
BACKGROUND: To verify the differential expression of miR-30c and miR-142-3p between tuberculosis patients and healthy controls and to investigate the performance of microRNA (miRNA) and subsequently models for the diagnosis of tuberculosis (TB). METHODS: We followed up 460 subjects suspected of TB, and finally enrolled 132 patients, including 60 TB patients, 24 non-TB disease controls (TB-DCs), and 48 healthy controls (HCs). The differential expression of miR-30c and miR-142-3p in serum samples of the TB patients, TB-DCs, and HCs were identified by reverse transcription-quantitative real-time PCR. Diagnostic models were developed by analyzing the characteristics of miRNA and electronic health records (EHRs). These models evaluated by the area under the curves (AUC) and calibration curves were presented as nomograms. RESULTS: There were differential expression of miR-30c and miR-142-3p between TB patients and HCs (p < 0.05). Individual miRNA has a limited diagnostic value for TB. However, diagnostic performance has been both significantly improved when we integrated miR-142-3p and ordinary EHRs to develop two models for the diagnosis of tuberculosis. The AUC of the model for distinguishing tuberculosis patients from healthy controls has increased from 0.75 (95% CI: 0.66-0.84) to 0.96 (95% CI: 0.92-0.99) and the model for distinguishing tuberculosis patients from non-TB disease controls has increased from 0.67 (95% CI: 0.55-0.79) to 0.94 (95% CI: 0.89-0.99). CONCLUSIONS: Integrating serum miR-142-3p and EHRs is a good strategy for improving TB diagnosis.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Tuberculosis / MicroARNs / Nomogramas / Registros Electrónicos de Salud Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Tuberculosis / MicroARNs / Nomogramas / Registros Electrónicos de Salud Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Año: 2021 Tipo del documento: Article