Construction of a thoracic surgery database system and platform for regional information interactions on pulmonary tuberculosis_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

SONG Yijie ¹ , XU Xiuyuan ² , WANG Ning ^1,3 , JIA Shuang ¹ , YUAN Ye ¹ , JIANG Liangshuang ¹ ,  YAO Xiaojun ^1,3

1. Department of Thoracic Surgery, Public Health Clinical Center of Chengdu, Chengdu, 610061, P. R. China;
2. College of Computer Science, Sichuan University, Chengdu, 610065, P. R. China;
3. School of Public Health, Chengdu Medical College, Chengdu, 610500, P. R. China;

Corresponding author：

YAO Xiaojun, Email: flyingyao@163.com

Keywords：

Database; pulmonary tuberculosis; thoracic surgery; information share

DOI：

10.7507/1007-4848.202307005

Video：

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Objective To collect and store all interactions relating to medical information between our center and allied specialized hospitals by constructing a database system for thoracic surgery and pulmonary tuberculosis. Methods We collected all related medical records of patients who had been clinically diagnosed with pulmonary tuberculosis and tuberculous empyema using the CouchBase Database, including outpatient and inpatient system of the Department of Thoracic Surgery at the Public Health Clinical Center of Chengdu between January 2017 to June 2023. Then, we integrated all medical records derived from the radiology information system, hospital information system, image archiving and communication systems, and the laboratory information management system. Finally, we used artificial intelligence to generate a database system for the application of thoracic surgery on pulmonary tuberculosis, which stored structured medical data from different hospitals along with data collected from patients via WeChat users. The new database could share medical data between our center and allied hospitals by using a front-end processor. Results We finally included 124 patients with 86 males and 38 females aged 43 (26, 56) years. A structured database for the application of thoracic surgery on patients with pulmonary tuberculosis was successfully constructed. A follow-up list created by the database can help outpatient doctors to complete follow-up tasks on time. All structured data can be downloaded in the form of Microsoft Excel files to meet the needs of different clinical researchers. Conclusion Our new database allows medical data to be structured, stored and shared between our center and allied hospitals. The database represents a powerful platform for interactions relating to regional information concerning pulmonary tuberculosis.

Citation： SONG Yijie, XU Xiuyuan, WANG Ning, JIA Shuang, YUAN Ye, JIANG Liangshuang, YAO Xiaojun. Construction of a thoracic surgery database system and platform for regional information interactions on pulmonary tuberculosis. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2023, 30(12): 1749-1756. doi: 10.7507/1007-4848.202307005 Copy

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2.	Borisov SE, D'Ambrosio L, Centis R, et al. Outcomes of patients with drug-resistant-tuberculosis treated with bedaquiline-containing regimens and undergoing adjunctive surgery. J Infect, 2019, 78(1): 35-39.
3.	Vashakidze SA, Gogishvili SG, Nikolaishvili KG, et al. Adjunctive surgery versus medical treatment among patients with cavitary multidrug-resistant tuberculosis. Eur J Cardiothorac Surg, 2021, 60(6): 1279-1285.
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7.	宋言峥, 朱益军, 陈辉, 等. 肺结核外科的微创伤疗法(附39例报告). 中华胸部外科电子杂志, 2020, 7(2): 71-75.
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10.	常炜, 车勇, 关小军. 单中心肺结核外科数据库的建立与应用. 结核病与肺部健康杂志, 2017, 6(1): 77-81.
11.	Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform, 2009, 42(2): 377-381.
12.	Allie T, Jackson A, Ambler J, et al. TBDBT: A TB database template for collection of harmonized TB clinical research data in REDCap, facilitating data standardization for inter-study comparison and meta-analyses. PLoS One, 2021, 16(3): e0249165.
13.	Willers C, Lynch T, Chand V, et al. A versatile, secure, and sustainable all-in-one biobank-registry data solution: The A3BC REDCap Model. Biopreserv Biobank, 2022, 20(3): 244-259.
14.	Pellison FC, Rijo R, Lima VC, et al. Data integration in the brazilian public health system for tuberculosis: Use of the semantic web to establish interoperability. JMIR Med Inform, 2020, 8(7): e17176.
15.	World Health Organization. Global tuberculosis report 2022. URL: https://www.who.int/teams/global-tuberculosis-programme/tb-reports/global-tuberculosis-report-2022. Accessed on 2023-06-28.
16.	陈留萍. 慢性病患者生命质量测定量表体系之肺结核患者生命质量测定量表QLICD-PT研制与应用. 昆明医科大学, 2012.
17.	戴维, 王雅琴, 魏星, 等. 无纸化临床研究数据采集平台构建. 医学信息学杂志, 2021, 42(4): 75-78.
18.	Ahmad N, Ahuja SD, Akkerman OW, et al. Treatment correlates of successful outcomes in pulmonary multidrug-resistant tuberculosis: An individual patient data meta-analysis. Lancet, 2018, 392(10150): 821-834.
19.	闫银锁, 陶荔莹, 张红伟, 等. 基于Power Pivot构建新病原学阳性肺结核患者耐药筛查辅助监测系统. 结核病与肺部健康杂志, 2019, 8(4): 294-298.

1. Mirzayev F, Viney K, Linh NN, et al. World Health Organization recommendations on the treatment of drug-resistant tuberculosis, 2020 update. Eur Respir J, 2021, 57(6): 2003300.
2. Borisov SE, D'Ambrosio L, Centis R, et al. Outcomes of patients with drug-resistant-tuberculosis treated with bedaquiline-containing regimens and undergoing adjunctive surgery. J Infect, 2019, 78(1): 35-39.
3. Vashakidze SA, Gogishvili SG, Nikolaishvili KG, et al. Adjunctive surgery versus medical treatment among patients with cavitary multidrug-resistant tuberculosis. Eur J Cardiothorac Surg, 2021, 60(6): 1279-1285.
4. Fox GJ, Mitnick CD, Benedetti A, et al. Surgery as an adjunctive treatment for multidrug-resistant tuberculosis: An individual patient data metaanalysis. Clin Infect Dis, 2016, 62(7): 887-895.
5. 贾霜, 宋毅杰, 吴邦贵, 等. 胸腔镜胸膜剥脱术在治疗Ⅲ期结核性脓胸中的临床应用. 中华结核和呼吸杂志, 2023, 46(5): 474-479.
6. Tang J, Tang Z, Feng C, et al. Efficacy and safety of video-assisted thoracoscopic surgery for pulmonary TB. Int J Tuberc Lung Dis, 2023, 27(5): 387-394.
7. 宋言峥, 朱益军, 陈辉, 等. 肺结核外科的微创伤疗法(附39例报告). 中华胸部外科电子杂志, 2020, 7(2): 71-75.
8. 蒋钰辉, 申磊, 戴希勇. 单向式肺叶切除术在复杂肺结核手术中应用的回顾性队列研究. 中国胸心血管外科临床杂志, 2022, 29(12): 1607-1611.
9. Shaffer JG, Doumbia SO, Ndiaye D, et al. Development of a data collection and management system in West Africa: Challenges and sustainability. Infect Dis Poverty, 2018, 7(1): 125 .
10. 常炜, 车勇, 关小军. 单中心肺结核外科数据库的建立与应用. 结核病与肺部健康杂志, 2017, 6(1): 77-81.
11. Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform, 2009, 42(2): 377-381.
12. Allie T, Jackson A, Ambler J, et al. TBDBT: A TB database template for collection of harmonized TB clinical research data in REDCap, facilitating data standardization for inter-study comparison and meta-analyses. PLoS One, 2021, 16(3): e0249165.
13. Willers C, Lynch T, Chand V, et al. A versatile, secure, and sustainable all-in-one biobank-registry data solution: The A3BC REDCap Model. Biopreserv Biobank, 2022, 20(3): 244-259.
14. Pellison FC, Rijo R, Lima VC, et al. Data integration in the brazilian public health system for tuberculosis: Use of the semantic web to establish interoperability. JMIR Med Inform, 2020, 8(7): e17176.
15. World Health Organization. Global tuberculosis report 2022. URL: https://www.who.int/teams/global-tuberculosis-programme/tb-reports/global-tuberculosis-report-2022. Accessed on 2023-06-28.
16. 陈留萍. 慢性病患者生命质量测定量表体系之肺结核患者生命质量测定量表QLICD-PT研制与应用. 昆明医科大学, 2012.
17. 戴维, 王雅琴, 魏星, 等. 无纸化临床研究数据采集平台构建. 医学信息学杂志, 2021, 42(4): 75-78.
18. Ahmad N, Ahuja SD, Akkerman OW, et al. Treatment correlates of successful outcomes in pulmonary multidrug-resistant tuberculosis: An individual patient data meta-analysis. Lancet, 2018, 392(10150): 821-834.
19. 闫银锁, 陶荔莹, 张红伟, 等. 基于Power Pivot构建新病原学阳性肺结核患者耐药筛查辅助监测系统. 结核病与肺部健康杂志, 2019, 8(4): 294-298.

Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Construction of a thoracic surgery database system and platform for regional information interactions on pulmonary tuberculosis

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