Effects of Abnormal Glucose Metabolism during Pregnancy on Pregnancy Complications and Maternal and Fetal Outcomes
DOI: 10.23977/medsc.2023.040304 | Downloads: 9 | Views: 361
Author(s)
Huan Li 1, Ting Lv 1
Affiliation(s)
1 Maternal and Child Health Hospital of Hubei Province, Wuhan, Hubei, China
Corresponding Author
Huan LiABSTRACT
Abnormal glucose metabolism during pregnancy is one of the important factors that affect the delivery rate and health level of pregnant women, and it is also a disease that needs to be properly treated and treated when pregnant women face serious complications or death risks. In order to reduce or avoid the impact of diabetes in pregnancy on pregnant women and fetuses, it is necessary to study the relationship between diabetes and pregnancy complications and fetuses. Deeply understand this knowledge and reduce unnecessary injuries. This paper mainly uses the survey method, data comparison and repeated analysis of variance to obtain relevant data. The survey results show that more than 50% of people generally know little about the serious consequences of abnormal glucose metabolism during pregnancy. Therefore, it is necessary to popularize relevant knowledge to avoid complications as much as possible.
KEYWORDS
Abnormal Glucose Metabolism, Pregnancy Complications, Maternal and Fetal Outcomes, Prospective ComparisonCITE THIS PAPER
Huan Li, Ting Lv, Effects of Abnormal Glucose Metabolism during Pregnancy on Pregnancy Complications and Maternal and Fetal Outcomes. MEDS Clinical Medicine (2023) Vol. 4: 27-34. DOI: http://dx.doi.org/10.23977/medsc.2023.040304.
REFERENCES
[1] A. Sumathi, S. Meganathan. (2022) Ensemble Classifier Technique to Predict Gestational Diabetes Mellitus (GDM). Comput. Syst. Sci. Eng. 40(1): 313-325
[2] Mikko Kytö, Lisbeth Strömberg, Heli Tuomonen, Antti Ruonala, Saila Koivusalo, Giulio Jacucci. (2022) Behavior Change Apps for Gestational Diabetes Management: Exploring Desirable Features. Int. J. Hum. Comput. Interact. 38(12): 1095-1112
[3] Nora El-Rashidy, Nesma E. ElSayed, Amir El-Ghamry, Fatma M. Talaat. (2022) Prediction of Gestational Diabetes Based on Explainable Deep Learning and Fog Computing. Soft Comput. 26(21): 11435-11450
[4] K. Deeba, R. A. K. Saravanaguru. (2021) Context Reasoning for Predicting Gestational Diabetes Mellitus Using CA-RETE Algorithm. Int. J. e Collab. 17(4): 41-59
[5] Shiva Shankar Reddy, Nilambar Sethi, R. Rajender. (2021) Rigorous Assessment of Data Mining Algorithms in Gestational Diabetes Mellitus Prediction. Int. J. Knowl. Based Intell. Eng. Syst. 25(4): 369-383
[6] Cristina Tassone, Karim Keshavjee, Alessia Paglialonga, Nimia Moreira, Jennifer Pinto, Yuri Quintana. (2020) Evaluation of Mobile Apps for Treatment of Patients at Risk of Developing Gestational Diabetes. Health Informatics J. 26(3): 1983-1994
[7] Priya Shirley Muller, M. Nirmala. (2019) Logistic Regression Model as Classifier for Early Detection of Gestational Diabetes Mellitus. Int. J. Comput. Aided Eng. Technol. 11(2): 174-183
[8] Saeed Rouhani, Maryam MirSharif. (2018) Data Mining Approach for the Early Risk Assessment of Gestational Diabetes Mellitus. Int. J. Knowl. Discov. Bioinform. 8(1): 1-11
[9] Claudia Carissoli, Deborah Gasparri, Giuseppe Riva, Daniela Villani. (2022) Mobile Well-Being in Pregnancy: Suggestions from a Quasi-Experimental Controlled Study. Behav. Inf. Technol. 41(8): 1639-1651
[10] Nikolay Alexeyevich Korenevskiy, Seregin Stanislav Petrovich, Riad Taha Al-Kasasbeh, Ayman Ahmad Alqaralleh, Gennadij Vjacheslavovich Siplivyj, Mahdi Salman Alshamasin, Sofia Nikolaevna Rodionova, Ivan Mikhailovich Kholimenko, Maxim Yurievich Ilyash. (2023) Managing Infectious and inflammatory Complications in Closed Kidney Injuries on the Basis of Fuzzy Models. Int. J. Medical Eng. Informatics 15(1): 33-44
[11] Evgeny Zherebtsov, Igor Kozlov, Viktor Dremin, Alexander Bykov, Andrey Dunaev, Igor V. Meglinski. (2023) Diagnosis of Skin Vascular Complications Revealed by Time-Frequency Analysis and Laser Doppler Spectrum Decomposition. IEEE Trans. Biomed. Eng. 70(1): 3-14
[12] Breanna P. Swan, Maria E. Mayorga, Julie S. Ivy. (2022) The SMART Framework: Selection of Machine Learning Algorithms with ReplicaTions-A Case Study on the Microvascular Complications of Diabetes. IEEE J. Biomed. Health Informatics 26(2): 809-817
[13] Michael F. Gorman. (2021) Contextual Complications in Analytical Modeling: When the Problem is Not the Problem. INFORMS J. Appl. Anal. 51(4): 245-261
[14] Fereshteh Jeyafzam, Babak Vaziri, Mohsen Yaghoubi Suraki, Ali Asghar Rahmani Hosseinabadi, Adam Slowik. (2021) Improvement of Grey Wolf Optimizer with Adaptive Middle Filter to Adjust Support Vector Machine Parameters to Predict Diabetes Complications. Neural Comput. Appl. 33(22): 15205-15228
[15] Tama K H. Tree-based classifier ensembles for early detection method of diabetes: an exploratory study. Artificial Intelligence Review: An International Science and Engineering Journal, 2019, 51(3)
Downloads: | 4576 |
---|---|
Visits: | 198302 |
Sponsors, Associates, and Links
-
Journal of Neurobiology and Genetics
-
Medical Imaging and Nuclear Medicine
-
Bacterial Genetics and Ecology
-
Transactions on Cancer
-
Journal of Biophysics and Ecology
-
Journal of Animal Science and Veterinary
-
Academic Journal of Biochemistry and Molecular Biology
-
Transactions on Cell and Developmental Biology
-
Rehabilitation Engineering & Assistive Technology
-
Orthopaedics and Sports Medicine
-
Hematology and Stem Cell
-
Journal of Intelligent Informatics and Biomedical Engineering
-
MEDS Basic Medicine
-
MEDS Stomatology
-
MEDS Public Health and Preventive Medicine
-
MEDS Chinese Medicine
-
Journal of Enzyme Engineering
-
Advances in Industrial Pharmacy and Pharmaceutical Sciences
-
Bacteriology and Microbiology
-
Advances in Physiology and Pathophysiology
-
Journal of Vision and Ophthalmology
-
Frontiers of Obstetrics and Gynecology
-
Digestive Disease and Diabetes
-
Advances in Immunology and Vaccines
-
Nanomedicine and Drug Delivery
-
Cardiology and Vascular System
-
Pediatrics and Child Health
-
Journal of Reproductive Medicine and Contraception
-
Journal of Respiratory and Lung Disease
-
Journal of Bioinformatics and Biomedicine