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He X, Zeng X, Troendle J, Ahlberg M, Tilden EL, Souza JP, Bernitz S, Duan T, Oladapo OT, Fraser W, Zhang J. New insights on labor progression: a systematic review. Am J Obstet Gynecol 2023; 228:S1063-S1094. [PMID: 37164489 DOI: 10.1016/j.ajog.2022.11.1299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 11/26/2022] [Accepted: 11/28/2022] [Indexed: 03/18/2023]
Abstract
The past 20 years witnessed an invigoration of research on labor progression and a change of thinking regarding normal labor. New evidence is emerging, and more advanced statistical methods are applied to labor progression analyses. Given the wide variations in the onset of active labor and the pattern of labor progression, there is an emerging consensus that the definition of abnormal labor may not be related to an idealized or average labor curve. Alternative approaches to guide labor management have been proposed; for example, using an upper limit of a distribution of labor duration to define abnormally slow labor. Nonetheless, the methods of labor assessment are still primitive and subject to error; more objective measures and more advanced instruments are needed to identify the onset of active labor, monitor labor progression, and define when labor duration is associated with maternal/child risk. Cervical dilation alone may be insufficient to define active labor, and incorporating more physical and biochemical measures may improve accuracy of diagnosing active labor onset and progression. Because the association between duration of labor and perinatal outcomes is rather complex and influenced by various underlying and iatrogenic conditions, future research must carefully explore how to integrate statistical cut-points with clinical outcomes to reach a practical definition of labor abnormalities. Finally, research regarding the complex labor process may benefit from new approaches, such as machine learning technologies and artificial intelligence to improve the predictability of successful vaginal delivery with normal perinatal outcomes.
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Affiliation(s)
- Xiaoqing He
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China; Ministry of Education -Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaojing Zeng
- Ministry of Education -Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - James Troendle
- Office of Biostatistics Research, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Maria Ahlberg
- Clinical Epidemiology Division, Department of Medicine, Solna, Karolinska Institute, Stockholm, Sweden
| | - Ellen L Tilden
- Department of Obstetrics and Gynecology, School of Medicine, Department of Nurse-Midwifery, School of Nursing, Oregon Health & Science University, Portland, OR
| | - João Paulo Souza
- Department of Social Medicine, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - Stine Bernitz
- Department of Obstetrics and Gynaecology, Østfold Hospital Trust, Grålum, Norway; Department of Health Promotion, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway
| | - Tao Duan
- Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China
| | - Olufemi T Oladapo
- United Nations Development Programme/United Nations Population Fund/ United Nations Children's Fund/World Health Organization/World Bank Special Programme of Research, Development and Research Training in Human Reproduction, Department of Reproductive Health and Research, World Health Organization, Geneva, Switzerland
| | - William Fraser
- Department of Obstetrics and Gynecology, Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Canada
| | - Jun Zhang
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China; Ministry of Education -Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Ghulaxe Y, Tayade S, Huse S, Chavada J. Advancement in Partograph: WHO's Labor Care Guide. Cureus 2022; 14:e30238. [PMID: 36381845 PMCID: PMC9652267 DOI: 10.7759/cureus.30238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 10/12/2022] [Indexed: 06/16/2023] Open
Abstract
Worldwide, the partograph, also known as a partogram, is used as a labor monitoring tool to detect difficulties early, allowing for referral, intervention, or closer observations to follow. Despite widespread support from health experts, there are worries that the partograph has not yet fully realized its potential for enhancing therapeutic results. As a result, the instrument has undergone several changes, and numerous studies have been conducted to examine the obstacles and enablers to its use. Nevertheless, the partograph was widely embraced and has been a component of evaluating labor progress. Earlier it was also used as a standard method for monitoring labor progress. Even though it is widely used, there have been reports of usage and accurate execution rates. The WHO Labor Care Guide (LCG) was created so that medical professionals could keep an eye on the health of pregnant women and their unborn children during labor by conducting routine evaluations to spot any abnormalities. The tool intends to enhance women-centered care and encourage collaborative decision-making between women and healthcare professionals. The LCG is designed to be a tool for ensuring high-quality research centered on health, reducing pointless measures, and offering comfort measures.
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Affiliation(s)
- Yash Ghulaxe
- Medical Student, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND
| | - Surekha Tayade
- Department of Obstetrics and Gynaecology, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND
| | - Shreyash Huse
- Medical Student, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND
| | - Jay Chavada
- Medical Student, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND
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Shazly SA, Shawki AA, Ahmed MM, Monib FA, Radwan AA, Sedik AS, Said AE, Ali SS, Abouzeid MH, Sayed EG, Nassr AA, Eltaweel NA, Hortu I, Hassan RM, Abdelbadie AS. Middle-East OBGYN graduate education (MOGGE) foundation practice guidelines: use of labor charts in management of labor. Practice guideline no. 04-O-21. J Matern Fetal Neonatal Med 2021; 35:7280-7289. [PMID: 34470117 DOI: 10.1080/14767058.2021.1946787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Since the 50 s of the last century, labor charts have been proposed and appraised as a tool to diagnose labor abnormalities and guide decision-making. The partogram, the most widely adopted form of labor charts, has been endorsed by the world health organization (WHO) since 1994. Nevertheless, recent studies and systematic reviews did not support clinical significance of application of the WHO partogram. These results have led to further studies that investigate modifications to the structure of the partogram, or more recently, to reconstruct new labor charts to improve their clinical efficacy. This guideline appraises current evidence on use of labor charts in management of labor specially in low-resource settings.
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Affiliation(s)
- Sherif A Shazly
- Department of Obstetrics and Gynecology, Assiut School of Medicine, Assiut, Egypt
| | - Abdelrahman A Shawki
- Department of Obstetrics and Gynecology, Assiut School of Medicine, Assiut, Egypt
| | - Manar M Ahmed
- Department of Obstetrics and Gynecology, Assiut School of Medicine, Assiut, Egypt
| | - Fatma A Monib
- Department of Obstetrics and Gynecology, Assiut School of Medicine, Assiut, Egypt
| | - Ahmad A Radwan
- Department of Obstetrics and Gynecology, Assiut School of Medicine, Assiut, Egypt
| | - Ahmed S Sedik
- Department of Obstetrics and Gynecology, Assiut School of Medicine, Assiut, Egypt
| | - Aliaa E Said
- Department of Obstetrics and Gynecology, Assiut School of Medicine, Assiut, Egypt
| | - Shimaa S Ali
- Department of Obstetrics and Gynecology, Assiut School of Medicine, Assiut, Egypt
| | - Mostafa H Abouzeid
- Department of Obstetrics and Gynecology, Assiut School of Medicine, Assiut, Egypt
| | - Esraa G Sayed
- Department of Obstetrics and Gynecology, Assiut School of Medicine, Assiut, Egypt
| | - Ahmed A Nassr
- Department of Obstetrics and Gynecology, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA
| | - Nashwa A Eltaweel
- Department of Obstetrics and Gynecology, University hospitals of Coventry and Warwickshire, UK
| | - Ismet Hortu
- Department of Obstetrics and Gynecology, Ege University School of Medicine, Izmir, Turkey
| | - Rana M Hassan
- Department of Obstetrics and Gynecology, Maternity Hospital, Alexandria, Egypt
| | - Amr S Abdelbadie
- Department of Obstetrics and Gynecology, Aswan University, Aswan, Egypt
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