Is the Robson’s classification system burdened by obstetric pathologies, maternal characteristics and assistential levels in comparing hospitals cesarean rates? A regional analysis of class 1 and 3

Sandro Gerli, Alessandro Favilli, David Franchini, Marcello De Giorgi, Paola Casucci, Fabio Parazzini

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Abstract

Objective: To assess if maternal risk profile and Hospital assistential levels were able to influence the inter-Hospitals comparison in the class 1 and 3 of the “The Ten Group Classification System” (TGCS). Methods: A population-based analysis using data from Institutional data-base of an Italian Region was carried out. The 11 maternity wards were divided into two categories: second-level hospitals (SLH), and first-level hospitals (FLH). The recorded deliveries were classified according to the TGCS. To analyze if different maternal characteristics and the hospitals assistential level could influence the cesarean section (CS) risk, a multivariate analysis was done considering separately women in the TGCS class 1 and 3. Results: From January 2011 to December 2013 were recorded 19,987 deliveries. Of those 7,693 were in the TGCS class 1 and 4,919 in the class 3. The CS rates were 20.8% and 14.7% in class 1 (p < 0.0001) and 6.9% and 5.3% (p < 0.0230) in class 3, respectively in the FLH and SLH. The multivariate logistic regression showed that the FLH, older maternal age and gestational diabetes were independent risk factors for CS in groups 1 and 3. Obesity and gestational hypertension were also independent risk factors for group 1. Conclusions: TGCS is a useful tool to analyze the incidence of CS in a single center but in comparing different Hospitals, maternal characteristics and different assistential levels should be considered as potential bias.

Original languageEnglish
Pages (from-to)173-177
Number of pages8
JournalJournal of Maternal-Fetal and Neonatal Medicine
Volume31
Issue number2
DOIs
Publication statusPublished - 2018

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Obstetrics
Mothers
Pathology
Cesarean Section
Pregnancy Induced Hypertension
Gestational Diabetes
Maternal Age
Multivariate Analysis
Obesity
Logistic Models
Databases
Incidence
Population

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Obstetrics and Gynaecology

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Is the Robson’s classification system burdened by obstetric pathologies, maternal characteristics and assistential levels in comparing hospitals cesarean rates? A regional analysis of class 1 and 3. / Gerli, Sandro; Favilli, Alessandro; Franchini, David; De Giorgi, Marcello; Casucci, Paola; Parazzini, Fabio.

In: Journal of Maternal-Fetal and Neonatal Medicine, Vol. 31, No. 2, 2018, p. 173-177.

Research output: Contribution to journalArticle

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abstract = "Objective: To assess if maternal risk profile and Hospital assistential levels were able to influence the inter-Hospitals comparison in the class 1 and 3 of the “The Ten Group Classification System” (TGCS). Methods: A population-based analysis using data from Institutional data-base of an Italian Region was carried out. The 11 maternity wards were divided into two categories: second-level hospitals (SLH), and first-level hospitals (FLH). The recorded deliveries were classified according to the TGCS. To analyze if different maternal characteristics and the hospitals assistential level could influence the cesarean section (CS) risk, a multivariate analysis was done considering separately women in the TGCS class 1 and 3. Results: From January 2011 to December 2013 were recorded 19,987 deliveries. Of those 7,693 were in the TGCS class 1 and 4,919 in the class 3. The CS rates were 20.8{\%} and 14.7{\%} in class 1 (p < 0.0001) and 6.9{\%} and 5.3{\%} (p < 0.0230) in class 3, respectively in the FLH and SLH. The multivariate logistic regression showed that the FLH, older maternal age and gestational diabetes were independent risk factors for CS in groups 1 and 3. Obesity and gestational hypertension were also independent risk factors for group 1. Conclusions: TGCS is a useful tool to analyze the incidence of CS in a single center but in comparing different Hospitals, maternal characteristics and different assistential levels should be considered as potential bias.",
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