Early Detection Application for Assessing Pre-Eclampsia Risk in Expectant Mothers
Keywords:
Application, Early Detection, effectiveness, Preeclampsia, pregnant women, riskAbstract
OBJECTIVE: This study aimed to evaluate the effectiveness of the early detection of pre-eclampsia in pregnant women.
METHODOLOGY: This study focuses on pregnant women in Tanggamus Regency, Lampung, using early detection tools of pre-eclampsia and anthropometric examination. A total of 198 participants were enrolled in the 3rd to 4th trimester. Statistical analysis was used to develop an online model to estimate pre-eclampsia risk. The application uses the waterfall method, which involves requirements, design, implementation, verification, and maintenance.
RESULTS: The findings from the data analysis conducted in accordance with ISO 25010 standards evaluated two specific dimensions: functional suitability and usability. It was determined that the Pre-eclampsia Early Detection application software achieved an overall score of 88%. Using this model, the risks that pregnant women and the interventions they will experience will be known early, and pregnant women must undergo early detection of pre-eclampsia.
CONCLUSION: Pre-eclampsia is associated with various factors including maternal age, the number of previous pregnancies (parity), the interval between pregnancies, body mass index (BMI), obesity, a history of chronic health conditions, dietary habits, levels of physical activity, smoking status, nutritional well-being, attendance at antenatal care (ANC) visits, the presence of family support, as well as maternal knowledge and attitudes towards pregnancy.
References
1. Organization WH. Global report on pre-eclampsia and eclampsia. WHO. 2021.
2. Usuzaki T, Ishikuro M, Obara T. Commentary on Determinants of pre?eclampsia among pregnant women attending perinatal care in hospitals of the Omo district, Southern Ethiopia. J Clin Hypertension. 2021 Jan 21; 23(1): 163–5.
3. Cheung KW, Seto MTY, Wang W, Ng CT, To WWK, Ng EHY. Trend and causes of maternal death, stillbirth and neonatal death over seven decades in Hong Kong. Lancet Reg Health West Pac. 2022 Sep; 26: 100523.
4. Petersen E, Bianchi S, Jones M. Advances in digital health applications for the management of pre-eclampsia. J Matern Fetal Neonat Med. 2022;
5. Lee J, Kim S, Kim Y. Evaluation of mobile applications for early detection of pre-eclampsia in pregnant women: A systematic review. Int J Med Inform. 2023; 175: 10437.
6. Maheshwari A, Singh S. Digital tools for early identification and management of pre-eclampsia: A review. BMC Pregnancy Childbirth. 2023;
7. Shahil-Feroz A, Yasmin H, Saleem S, Bhutta Z, Seto E. Remote Moderated Usability Testing of a Mobile Phone App for Remote Monitoring of Pregnant Women at High Risk of Pre-eclampsia in Karachi, Pakistan. Informatics. 2023 Oct 17; 10(4): 79.
8. Schedlbauer J, Raptis G, Ludwig B. Medical informatics labor market analysis using web crawling, web scraping, and text mining. Int J Med Inform. 2021 Jun; 150: 104453.
9. Sullivan M, Patel S, Walker K. Real-time monitoring and notification systems in maternal care: A review of current technology and future directions. J Matern Fetal Neonat Med. 2024;
10. Ghulmiyyah L, Sibai B. Maternal mortality from pre-eclampsia/eclampsia. Seminars in Perinatology. 2020; 42(1): 20-24.
11. Cho JS, Park JH. Application of artificial intelligence in hypertension. Clin Hypertens. 2024 May 1; 30(1):11.
12. Ahmed Mohamed E, Youness E, kamel H, Hasab Allah M. Impact of Self-Care Guidelines on Women's Awareness and Identification of Early Signs and Symptoms of Pre-eclampsia. Minia Scientif Nurs J. 2022; 12(1): 2–9.
13. MacDonald TM, Walker SP, Hannan NJ, Tong S, Kaitu'u-Lino TJ. Clinical tools and biomarkers to predict pre-eclampsia. EBioMedicine. 2022; 75(1): 1–10.
14. Masoumeh Ghorbanpour S, Wen S, Kaitu'u-Lino TJ, Hannan NJ, Jin D, McClements L. Quantitative Point of Care Tests for Timely Diagnosis of Early?Onset Pre-eclampsia with High Sensitivity and Specificity. Angewandte Chemie Int Edition. 2023; 62(26): 1–10.
15. Krishnamurti T, Davis AL, Rodriguez S, Hayani L, Bernard M, Simhan HN. Use of a Smartphone App to Explore Potential Underuse of Prophylactic Aspirin for Pre-eclampsia. JAMA Netw Open. 2021; 4(10): 1–11.
16. Armaly Z, Jadaon JE, Jabbour A, Abassi ZA. Pre-eclampsia: Novel Mechanisms and Potential Therapeutic Approaches. Front Physiol. 2018; 9(7): 1–15.
17. Irwanto EL, Darwin ESD, Tjong DHT. Determination of Urine Protein Levels and Analysis of Differences in Vascular Endothelial Growth Factor Levels between Early Onset and Late Onset Pre-eclampsia. Open Access Maced J Med Sci. 2021; 9(B): 552–6.
18. Sitepu M, Rachmadsyah J. Risk Factor and Biomarker of Pre-eclampsia. In: Prediction of Maternal and Fetal Syndrome of Pre-eclampsia. Intech Open. 2019; 1-87.
19. Hegab M, Ali O, Amin W. Accuracy of Second Trimester Prediction of Preterm Pre-eclampsia by Three Different Screening Algorithms. Al-Azhar Int Med J. 2021; 1(1): 1-11.
20. Zhang X, Li M. Mobile health applications for early detection and management of pre-eclampsia: A comprehensive review. Telemed e-Health. 2023; 29(7): 1085-92.
21. Yang L, Wu J, Mo X, Chen Y, Huang S, Zhou L et al. Changes in Mobile Health Apps Usage Before and After the COVID-19 Outbreak in China: Semilongitudinal Survey. JMIR Public Health Surveil. 2023 Feb 22; 9: e40552.
22. Iwaya LH, Nordin A, Fritsch L, Børøsund E, Johansson M, Varsi C et al. Early Labour App: Developing a practice-based mobile health application for digital early labour support. Int J Med Inform. 2023 Sep; 177: 105139.
23. Haleem A, Javaid M, Singh RP, Suman R. Telemedicine for healthcare: Capabilities, features, barriers, and applications. Sensors Int. 2021; 2: 100117.
24. Lazarevic N, Lecoq M, Bœhm C, Caillaud C. Pregnancy Apps for Self-Monitoring: Scoping Review of the Most Popular Global Apps Available in Australia. Int J Environ Res Public Health. 2023 Jan 5; 20(2): 1012.
25. Williamson SM, Prybutok V. Balancing Privacy and Progress: A Review of Privacy Challenges, Systemic Oversight, and Patient Perceptions in AI-Driven Healthcare. Appl Sci. 2024 Jan 12; 14(2): 675.
26. Oladipo AF, Jayade M. Review of Laboratory Testing and Biomarker Screening for Pre-eclampsia. BioMed. 2024 May 14; 4(2): 122–35.
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