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Generating evidence on screening, diagnosis and management of non-communicable diseases during pregnancy; a scoping review of current gap and practice in India with a comparison of Asian context. PLoS One 2021; 16:e0244136. [PMID: 33524025 PMCID: PMC7850625 DOI: 10.1371/journal.pone.0244136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Accepted: 12/03/2020] [Indexed: 11/19/2022] Open
Abstract
Background Children born to high-risk pregnancies are more likely to experience adverse health outcomes later in life. As estimated, 15% of all pregnancies are at risk of various life-threatening conditions leading to adverse maternal and foetal outcomes. Millennium Development Goal resulted in the global reduction of maternal death from 390,000 to 275000 in 1990–2015). Similarly, to keep this momentum, the current United Nations Sustainable Development Goal (SDG: 3.1) aims at reducing the global maternal mortality ratio to less than 70 per 100,000 live births by 2030, and this can be achieved by addressing high-risk pregnancy contributing to significant mortality and morbidity. In India, gestational diabetes, gestational hypertension, and gestational hypothyroidism were identified as factors contributing to the high-risk pregnancy. This review summarises the commonly used approach for screening, diagnosis, and management of these conditions in the Asian population. It draws a comparison with the current protocols and guidelines in the Indian setting. Methods Electronic search in PubMed and Google Scholar, reference snowballing, and review of current guidelines and protocols were done between January 2010 to October 2019. Published studies reporting Screening, diagnosis, and management of these conditions were included. Articles selected were then screened, appraised for quality, extract relevant data, and synthesised. Results Screening, diagnosis, and management of these three conditions vary and no single universally accepted criteria for diagnosis and management exist to date. In India, national guidelines available have not been evaluated for feasibility of implementation at the community level. There are no national guidelines for PIH diagnosis and management despite the increasing burden and contribution to maternal and perinatal morbidity and mortality. Criteria for diagnosis and management of gestational diabetes, gestational hypertension, and gestational hypothyroidism varies but overall early screening for predicting risk, as reported from majority of the articles, were effective in minimizing maternal and foetal outcome. Conclusion Existing National guidelines for Screening, Diagnosis, and Management of Gestational Diabetes Mellitus (2018) and Gestational Hypothyroidism (2014) need to be contextualized and modified based on the need of the local population for effective treatment. Findings from this review show that early screening for predicting risk to be an effective preventive strategy. However, reports related to a definitive diagnosis and medical management were heterogeneous.
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Yang L, Sun G, Wang A, Jiang H, Zhang S, Yang Y, Li X, Hao D, Xu M, Shao J. Predictive models of hypertensive disorders in pregnancy based on support vector machine algorithm. Technol Health Care 2020; 28:181-186. [PMID: 32364150 PMCID: PMC7369093 DOI: 10.3233/thc-209018] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The risk factors of hypertensive disorders in pregnancy (HDP) could be summarized into three categories: clinical epidemiological factors, hemodynamic factors and biochemical factors. OBJECTIVE To establish models for early prediction and intervention of HDP. METHODS This study used the three types of risk factors and support vector machine (SVM) to establish prediction models of HDP at different gestational weeks. RESULTS The average accuracy of the model was gradually increased when the pregnancy progressed, especially in the late pregnancy 28-34 weeks and ⩾ 35 weeks, it reached more than 92%. CONCLUSION Multi-risk factors combined with dynamic gestational weeks' prediction of HDP based on machine learning was superior to static and single-class conventional prediction methods. Multiple continuous tests could be performed from early pregnancy to late pregnancy.
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Affiliation(s)
- Lin Yang
- College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China.,College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China
| | - Ge Sun
- College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China.,College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China
| | - Anran Wang
- Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing, 100020, China.,College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China
| | - Hongqing Jiang
- Haidian Maternal and Children Health Hospital, Beijing, 100080, China.,College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China
| | - Song Zhang
- College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China
| | - Yimin Yang
- College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China
| | - Xuwen Li
- College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China
| | - Dongmei Hao
- College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China
| | - Mingzhou Xu
- Beijing Aerospace ChangFeng Co. Ltd., Beijing, 100071, China
| | - Jing Shao
- Beijing Yes Medical Devices Co. Ltd., Beijing, 100152, China
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Mei Z, Huang B, Qian X, Zhang Y, Teng B. Gastrodin improves preeclampsia-induced cell apoptosis by regulation of TLR4/NF-κB in rats. Food Sci Nutr 2020; 8:820-829. [PMID: 32148791 PMCID: PMC7020309 DOI: 10.1002/fsn3.1342] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 10/23/2019] [Accepted: 11/17/2019] [Indexed: 12/25/2022] Open
Abstract
To explain gastrodin improved cell apoptosis induced by preeclampsia in vivo and in vitro study. The PE and normal rats were injected with normal saline (Model), low-dose gastrodin (Gas-L), medium-dose gastrodin (Gas-M), and high-dose gastrodin (Gas-H) groups at 50, 100, or 200 mg/kg per day. The rat blood pressure and 24-hr urine protein level were measured at pregnant days 10, 16, and 20. Evaluating pathology by H&E staining, the cell apoptosis by TUNEL, and MyD88 and NF-κB (p65) proteins by IHC assay using H/R to simulate PE cell model. Measuring cell proliferation, apoptosis, and MyD88 and NF-κB (p65) protein expression by MTT, flow cytometry, and WB assay. The SBP, DBP, and 24-hr urine protein levels were significantly different in PE rats (p < .05). The SBP, DBP, and 24-hr urine protein levels were significantly improved (p < .05) in vivo and in vitro. The positive apoptosis cells and apoptosis rate were significantly increased with MyD88 and NF-κB (p65) proteins upregulation (p < .05). The positive apoptosis cells and apoptosis rate were significantly decreased with MyD88 and NF-κB (p65) proteins depressing in gastrodin-treated groups with dose-dependent (p < .05). Gastrodin improves PE-induced cell apoptosis and pathology changed via MyD88/NF-κB pathway in vitro and in vivo study.
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Affiliation(s)
- Zhixiong Mei
- Department of ObstetricsThe Third Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - Baoqin Huang
- Department of ObstetricsThe Third Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - Xialiu Qian
- Department of ObstetricsThe Third Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - Yuan Zhang
- Department of ObstetricsThe Third Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - Benqi Teng
- Department of ObstetricsThe Third Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
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Tang B, Zhong Z, Qiu Z, Wu HP, Hu JY, Ma JP, Wu JP. Serum soluble TWEAK levels in severe traumatic brain injury and its prognostic significance. Clin Chim Acta 2019; 495:227-232. [PMID: 31009601 DOI: 10.1016/j.cca.2019.04.070] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 04/13/2019] [Accepted: 04/17/2019] [Indexed: 01/03/2023]
Abstract
BACKGROUND Severe traumatic brain injury (sTBI) is characterized by a high mortality. Tumor necrosis factor-like weak inducer of apoptosis (TWEAK) participates in inflammation. We determined serum soluble TWEAK (sTWEAK) levels with respect to its prognostic ability. METHODS This was a single-center prospective, observational study that was performed from December 2014 to December 2017. A total of 114 sTBI patients who met the inclusion criteria and 114 randomly selected healthy controls were included in the study. Serum sTWEAK levels were gauged. Patients were followed-up until death or completion of 6 months. Poor outcome was referred to as Glasgow outcome scale score of 1-3. RESULTS In comparison with controls, patients displayed predominantly higher serum sTWEAK levels. Serum sTWEAK levels were strongly correlated with Glasgow coma scale scores and serum C-reactive protein levels. 32 patients (28.1%) died and 60 patients (52.6%) suffered from a poor outcome. Receiver operating characteristic curve analysis clearly showed that serum sTWEAK levels had substantially high predictive performance for 6-month mortality and poor outcome. Serum sTWEAK emerged as an independent predictor for 6-month mortality, overall survival and poor outcome. CONCLUSIONS Raised serum sTWEAK levels are closely related to increasing inflammatory response, elevated trauma severity and worse clinical outcome after sTBI.
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Affiliation(s)
- Bei Tang
- Department of Critical Care Medicine, The First People's Hospital of Jiande City, 599 Yanzhou Main Road, Jiande 311600, China
| | - Ze Zhong
- Department of Critical Care Medicine, The First People's Hospital of Jiande City, 599 Yanzhou Main Road, Jiande 311600, China.
| | - Zheng Qiu
- Department of Neurosurgery, The First People's Hospital of Jiande City, 599 Yanzhou Main Road, Jiande 311600, China
| | - Hui-Ping Wu
- Department of Critical Care Medicine, The First People's Hospital of Jiande City, 599 Yanzhou Main Road, Jiande 311600, China
| | - Jia-Yuan Hu
- Department of Critical Care Medicine, The First People's Hospital of Jiande City, 599 Yanzhou Main Road, Jiande 311600, China
| | - Jian-Ping Ma
- Department of Critical Care Medicine, The First People's Hospital of Jiande City, 599 Yanzhou Main Road, Jiande 311600, China
| | - Jin-Ping Wu
- Department of Critical Care Medicine, The First People's Hospital of Jiande City, 599 Yanzhou Main Road, Jiande 311600, China
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