Evidence map›Paper›PMID 38989387›Full record

ArticleCureus2024

Factors Affecting Elective and Non-elective Cesarean Sections: A Multinomial Regression Analysis Using Robson's Classification in a Southeast European Country.

Arjan Shylla, Daniela Teferici, Aldo Shpuza, Xhesika Xhetani, Enver Roshi

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Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Arjan ShyllaDepartment of Obstetrics and Gynecology, University Hospital of Obstetrics and Gynecology "Koco Gliozheni", Tirane, ALB.
Daniela TefericiDepartment of Cardiology and Cardiac Surgery, University Hospital Center "Mother Theresa", Tirane, ALB.
Aldo ShpuzaDepartment of Public Health, University of Medicine, Tirane, ALB.
Xhesika XhetaniDepartment of Radiology, Korca Region Hospital, Korce, ALB.
Enver RoshiDepartment of Public Health, University of Medicine, Tirane, ALB.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlbania, a middle-income Southeast European country, is experiencing an increase in cesarean section rates. This study aims to analyze cesarean section practices in Albania using the Robson classification to identify patterns and provide insights into elective and non-elective cesarean trends.

methodsThis retrospective cohort study was conducted at the University Hospital of Obstetrics and Gynecology "Koco Gliozheni" in Albania, a leading tertiary hospital, from January to May 2023, involving 5,315 consecutive women who delivered during this period, including both live births and stillbirths, with a gestational age minimum of 28 weeks to align with standards of viability. We defined a function to systematically evaluate each case based on multiple criteria: parity, fetal presentation, onset of labor, previous deliveries, number of fetuses, and gestational age according to the Robson classification. Multinomial multiple regression was used to estimate the relationship between each of the above-mentioned variables and the likelihood of each type of cesarean delivery compared to normal births.

resultsThe participants' mean age was 28.2 years (59.6% <30 years vs. 40.4% ≥30 years), while gestational age varied (12.1% before 37 weeks, the majority (72.3%) between 37 and 40 weeks, and 15.6% > 40 weeks). In elective cesarean sections, maternal age (odds ratio (OR) = 1.06) and gestational age (OR = 1.13) were associated with increased odds, with women with previous cesarean deliveries showing significantly higher odds (OR = 20.6), breech position (OR = 15.7), and multiple pregnancies elevating odds (OR = 7.3), whereas in non-elective cesarean sections, similar associations were observed with slightly different odds ratios which were maternal age (OR = 1.07), gestational age (OR = 1.16), previous cesarean delivery (OR = 6.3), breech position (OR = 8.5), and multiple pregnancies (OR = 5.1). Significant disparities in cesarean section rates were observed across various groups, with rates ranging from as low as 0.74% in Group 1 to as high as 89.24% in Group 5, and notable contributions from Group 2 with a rate of 69.95% and Group 6 with a rate of 81.29%.

conclusionIn conclusion, this study emphasizes the significance of factors such as maternal age, gestational age, previous cesarean deliveries, fetal presentation, number of fetuses, and multiple pregnancies in impacting the rates of elective, non-elective, and overall cesarean sections in Albania, highlighting the need for targeted strategies to improve maternal and fetal health outcomes.

Indexed as

albaniacesarean sectionselectivemultinomial regressionrobson classification

Identifiers

PMID38989387
PMCPMC11234161

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.