Giriş: Demir eksikliği anemisi, dünya çapında aneminin en yaygın nedenidir ve hamilelik sırasında artan demir gereksinimi anemi riskini artırır. Gebelikte anemi, düşük doğum ağırlığı, preterm ve intrauterin gelişme geriliği gibi olumsuz gebelik sonuçları ile ilişkilidir. Bu çalışma, gebelik sırasında demir eksikliği anemisi üzerindeki sosyo-demografik, beslenme, antenatal bakım ve obstetrik faktörleri tahmin etmek için Kural Tabanlı Akıllı Sınıflandırma Modelleri kullanmıştır.
Yöntem: Bu retrospektif çalışma, Türkiye'nin doğusundaki Elazığ ilinde Ocak ve Haziran 2019 tarihleri arasında yürütülen toplum temelli kesitsel bir çalışmanın ikincil bir analiziydi. Çalışmaya 495 gebenin verileri dahil edildi. Demir eksikliği anemisi hemoglobin < 11,0 g/dl ve ferritin <30,0 µg/L olarak tanımlandı. Hamilelik sırasında anemi ile ilişkili faktörleri tahmin etmek için kural tabanlı makine öğrenimi yöntemleri kullanıldı.
Bulgular: 495 gebenin yaş ortalaması 30,06 ± 5,15 yıldı. Çalışma popülasyonunda anemi prevalansı %27,9 idi. Anne yaşı, eğitim durumu, meslek, beslenme eğitimi durumu, beslenme özelliği, gravida ve parite anemi ile anlamlı şekilde ilişkiliydi. Jrip, OneR ve PART algoritmaları anemi ile ilişkili faktörleri sırasıyla %96,36, %85,45 ve %97,98 doğrulukla tahmin etti.
Sonuç: Kural tabanlı makine öğrenimi algoritması, hamilelik sırasında demir eksikliği anemisi için risk faktörlerine yeni bir yaklaşım sunabilir. Bu model ile gebelik öncesi ve gebelik anında anemi riski tahmin edilebilir ve önleyici girişimler yapılabilir.
The current study protocol was approved by Firat University's non-interventional research ethics committee (date: 08.04.2021, IRB number: 2021/05/05). Written consent of the participants was not required as it was a retrospective study. Necessary permissions were obtained from the corresponding author for the reanalysis of the data of the study entitled "Prevalence of Anemia and Associated Risk Factors among Pregnant Women, What is the Role of Antenatal Care in Prevention? A Cross-sectional Study".
We thank all authors for allowing us to use the data of the study "Prevalence of Anemia and Associated Risk Factors among Pregnant Women, What is the Role of Antenatal Care in Prevention? A Cross-sectional Study".
Introduction: Iron deficiency anemia is the most common cause of anemia worldwide, and increased iron requirement during pregnancy increases the risk of anemia. Anemia in pregnancy is associated with adverse pregnancy outcomes such as low birth weight, preterm and intrauterine growth restriction. This study used a Rule-based Intelligent Classification Models to predict socio-demographic, nutritional, antenatal care and obstetric factors on iron deficiency anemia during pregnancy
Methods: This retrospective study was a secondary analysis of a community-based cross-sectional study conducted between January and June 2019 in the province of Elazig in eastern Turkey. Data of 495 pregnant women were included in the study iron deficiency anemia was defined as hemoglobin < 11 g/dl, and ferritin < 30 µg/L. Rule-based machine learning methods were used to predict factors associated with anemia during pregnancy.
Results: The mean age of 495 pregnant women were 30.06 ± 5.15 years. The prevalence of anemia was 27.9% in study population. Maternal age, educational status, occupation, nutrition education status, nutritional property, gravida, and parity were significantly related to anemia. Jrip, OneR, and PART algorithms estimated factors associated with anemia with 96.36%, 85.45%, and 97.98% accuracy, respectively.
Conclusion: Rule-based machine learning algorithm may offer a new approach to risk factors for iron deficiency anemia during pregnancy. With the use of this model, it is possible to predict the risk of anemia both before and during pregnancy and to take preventative measures.
Pregnancy Iron-Deficiency Anemia Algorithms Machine learning
The current study protocol was approved by Firat University's non-interventional research ethics committee (date: 08.04.2021, IRB number: 2021/05/05). Written consent of the participants was not required as it was a retrospective study. Necessary permissions were obtained from the corresponding author for the reanalysis of the data of the study entitled "Prevalence of Anemia and Associated Risk Factors among Pregnant Women, What is the Role of Antenatal Care in Prevention? A Cross-sectional Study".
We thank all authors for allowing us to use the data of the study "Prevalence of Anemia and Associated Risk Factors among Pregnant Women, What is the Role of Antenatal Care in Prevention? A Cross-sectional Study".
Birincil Dil | İngilizce |
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Konular | Aile Hekimliği |
Bölüm | Araştırma Makalesi (Original Article) |
Yazarlar | |
Yayımlanma Tarihi | 28 Aralık 2023 |
Gönderilme Tarihi | 22 Ağustos 2023 |
Kabul Tarihi | 13 Aralık 2023 |
Yayımlandığı Sayı | Yıl 2023Cilt: 8 Sayı: 6 |