T A Nippita1,2,3, A Z Khambalia1,2, S K Seeho2, J A Trevena1, J A Patterson1,2, J B Ford1,2, J M Morris1,2, C L Roberts1,2. 1. Clinical Population and Perinatal Health Research, Kolling Institute, Northern Sydney Local Health District, St Leonards, NSW, Australia. 2. Sydney Medical School Northern, University of Sydney, St Leonards, NSW, Australia. 3. Department of Obstetrics and Gynaecology, Royal North Shore Hospital, Northern Sydney Local Health District, St Leonards, NSW, Australia.
Abstract
BACKGROUND: A lack of reproducible methods for classifying women having an induction of labour (IOL) has led to controversies regarding IOL and related maternal and perinatal health outcomes. OBJECTIVES: To evaluate articles that classify IOL and to develop a novel IOL classification system. SEARCH STRATEGY: Electronic searches using CINAHL, EMBASE, WEB of KNOWLEDGE, and reference lists. SELECTION CRITERIA: Two reviewers independently assessed studies that classified women having an IOL. DATA COLLECTION AND ANALYSIS: For the systematic review, data were extracted on study characteristics, quality, and results. Pre-specified criteria were used for evaluation. A multidisciplinary collaboration developed a new classification system using a clinically logical model and stakeholder feedback, demonstrating applicability in a population cohort of 909 702 maternities in New South Wales, Australia, over the period 2002-2011. MAIN RESULTS: All seven studies included in the systematic review categorised women according to the presence or absence of varying medical indications for IOL. Evaluation identified uncertainties or deficiencies across all studies, related to the criteria of total inclusivity, reproducibility, clinical utility, implementability, and data availability. A classification system of ten groups was developed based on parity, previous caesarean, gestational age, number, and presentation of the fetus. Nulliparous and parous women at full term were the largest groups (21.2 and 24.5%, respectively), and accounted for the highest proportion of all IOL (20.7 and 21.5%, respectively). AUTHOR'S CONCLUSIONS: Current methods of classifying women undertaking IOL based on medical indications are inadequate. We propose a classification system that has the attributes of simplicity and clarity, uses information that is readily and reliably collected, and enables the standard characterisation of populations of women having an IOL across and within jurisdictions.
BACKGROUND: A lack of reproducible methods for classifying women having an induction of labour (IOL) has led to controversies regarding IOL and related maternal and perinatal health outcomes. OBJECTIVES: To evaluate articles that classify IOL and to develop a novel IOL classification system. SEARCH STRATEGY: Electronic searches using CINAHL, EMBASE, WEB of KNOWLEDGE, and reference lists. SELECTION CRITERIA: Two reviewers independently assessed studies that classified women having an IOL. DATA COLLECTION AND ANALYSIS: For the systematic review, data were extracted on study characteristics, quality, and results. Pre-specified criteria were used for evaluation. A multidisciplinary collaboration developed a new classification system using a clinically logical model and stakeholder feedback, demonstrating applicability in a population cohort of 909 702 maternities in New South Wales, Australia, over the period 2002-2011. MAIN RESULTS: All seven studies included in the systematic review categorised women according to the presence or absence of varying medical indications for IOL. Evaluation identified uncertainties or deficiencies across all studies, related to the criteria of total inclusivity, reproducibility, clinical utility, implementability, and data availability. A classification system of ten groups was developed based on parity, previous caesarean, gestational age, number, and presentation of the fetus. Nulliparous and parous women at full term were the largest groups (21.2 and 24.5%, respectively), and accounted for the highest proportion of all IOL (20.7 and 21.5%, respectively). AUTHOR'S CONCLUSIONS: Current methods of classifying women undertaking IOL based on medical indications are inadequate. We propose a classification system that has the attributes of simplicity and clarity, uses information that is readily and reliably collected, and enables the standard characterisation of populations of women having an IOL across and within jurisdictions.
Authors: Sahar Hassan; Katariina Laine; Erik Fosse; Niveen Me Abu-Rmeileh; Hadil Y Ali-Masri; Mohammed Zimmo; Kaled Zimmo; Åse Vikanes; Khaled M Ismail Journal: Int J Womens Health Date: 2019-11-07
Authors: Tanya A Nippita; Judy A Trevena; Jillian A Patterson; Jane B Ford; Jonathan M Morris; Christine L Roberts Journal: BMJ Open Date: 2015-09-02 Impact factor: 2.692