| Literature DB >> 34006288 |
Elise Farrington1,2, Mairead Connolly3,4, Laura Phung3,4, Alyce N Wilson3, Liz Comrie-Thomson3, Meghan A Bohren5, Caroline S E Homer3, Joshua P Vogel3,6.
Abstract
BACKGROUND: Uterine fundal pressure involves a birth attendant pushing on the woman's uterine fundus to assist vaginal birth. It is used in some clinical settings, though guidelines recommend against it. This systematic review aimed to determine the prevalence of uterine fundal pressure during the second stage of labour for women giving birth vaginally at health facilities.Entities:
Keywords: Fundal pressure; Intrapartum care; Kristeller maneuver; Labour and childbirth; Mistreatment during childbirth; Quality of care
Mesh:
Year: 2021 PMID: 34006288 PMCID: PMC8132352 DOI: 10.1186/s12978-021-01148-1
Source DB: PubMed Journal: Reprod Health ISSN: 1742-4755 Impact factor: 3.223
Fig. 1PRISMA flow chart demonstrating inclusion and exclusion of studies
Characteristics of the 80 datasets from 76 included studies
| Author Year | Study design | Country | Income level (2020 World Bank) | Method of measuring use of fundal pressure | Last year of data collection | Study population (denominator) | Fundal pressure (numerator) | % | Risk of bias |
|---|---|---|---|---|---|---|---|---|---|
| Abasian Kasegari 2019 [ | Randomised controlled trial | Iran | Upper-middle | Direct observation | 2019 | 152 | 54 | 35.5 | Moderate |
| Abedadeh-Kalahroudi 2019 [ | Cross-sectional | Iran | Upper-middle | Direct observation | 2015 | 3239 | 473 | 14.6 | Low |
| Ahlberg 2016 [ | Cross-sectional | Sweden | High | Medical records | 2013 | 596 | 68 | 11.4 | Moderate |
| Andrade 2016 [ | Cross-sectional | Brazil | Upper-middle | Medical records | 2014 | 603 | 52 | 9.0 | Low |
| Ashouri 2019 [ | Cross-sectional | Iran | Upper-middle | Self-reported | 2017 | 600 | 125 | 20.8 | Low |
| Banks 2017 [ | Cross-sectional | Ethiopia | Low | Direct observation | 2013 | 193 | 22 | 11.4 | Low |
| Becerra-Chauca 2019 [ | Cross-sectional | Peru | Upper-middle | Self-reported | 2016 | 250 | 116 | 46.4 | Low |
| Biguzzi 2012 [ | Prospective cohort | Italy | High | Direct observation | 2009 | 6011 | 1632 | 27.2 | Low |
| Bohren 2019 [ | Cross-sectional | Guinea, Myanmar, Ghana and Nigeria | Lower-middle and low | Direct observation | 2018 | 2016 | 63 | 3.1 | Low |
| Brandao 2018 [ | Cross-sectional | Ecuador | Upper middle | Self-reported | 2017 | 252 | 49 | 19.4 | Low |
| Burns 2007 [ | Randomised controlled trial | Italy | High | Direct observation | 2003 | 513 | 21 | 4.1 | Low |
| Calik 2018 [ | Descriptive | Turkey | Upper-middle | Direct observation | 2015 | 351 | 152 | 43.3 | Low |
| Chalmers 2009 [ | Descriptive | Canada | High | Self-reported | 2006 | 5368 | 805 | 15.0 | Low |
| Ciriello 2012a [ | Cross-sectional | Italy | High | Medical records | 1996 | 8112 | 219 | 2.7 | Low |
| Ciriello 2012b [ | Cross-sectional | Italy | High | Medical records | 2006 | 8237 | 47 | 0.6 | Low |
| Comas 2017 [ | Prospective cohort | Spain | High | Direct observation | 2013 | 279 | 48 | 17.2 | Low |
| Cortes 2018 [ | Quasi-experimental before-and-after | Brazil | Upper-middle | Self-reported | 2015 | 140 | 29 | 20.7 | Low |
| Cromi 2014 [ | Cross-sectional | Italy | High | Medical records | Not specified | 736 | 103 | 14.0 | Low |
| Cuerva 2015 [ | Prospective cohort | Spain | High | Direct observation | 2013 | 52 | 36 | 69.2 | Low |
| da Gama 2016 [ | Descriptive | Brazil | Upper-middle | Self-reported | 2012 | 11,499 | 4232 | 36.8 | Low |
| da Silva Carvalho 2019 [ | Cross-sectional | Brazil | Upper-middle | Self-reported | 2014 | 314 | 70 | 22.3 | Low |
| de Oliveira Peripolli 2019 [ | Descriptive | Brazil | Upper-middle | Medical records | 2015 | 3078 | 141 | 4.5 | Low |
| Dey 2017 [ | Cross-sectional | India | Lower-middle | Direct observation | 2016 | 875 | 100 | 11.4 | Low |
| Dulfe 2016 [ | Cross-sectional | Brazil | Upper-middle | Self-reported | 2014 | 42 | 26 | 61.9 | Moderate |
| Edqvist 2017 [ | Prospective cohort | Sweden | High | Direct observation | 2015 | 704 | 16 | 2.3 | Low |
| Ejegard 2008 [ | Case–control | Sweden | High | Self-reported | 1999 | 206 | 39 | 18.9 | Moderate |
| Fernandes 2017 [ | Case–control | Brazil | Upper-middle | Medical records | 2013 | 369 | 12 | 3.3 | Low |
| Furrer 2015 [ | Retrospective cohort | Switzerland | High | Medical records | 2013 | 9743 | 919 | 9.4 | Low |
| Garcia Cachafeiro 2017 [ | Cross-sectional | Spain | High | Direct observation | 2015 | 312 | 49 | 15.7 | Moderate |
| Hasegawa 2014 [ | Cross-sectional | Japan | High | Medical records | 2012 | 347,771 | 38,973 | 11.2 | Moderate |
| Hasegawa 2020 [ | Cross-sectional | Japan | High | Medical records | 2017 | 404,444 | 38,205 | 9.5 | Moderate |
| Haslinger 2015 [ | Retrospective cohort | Switzerland | High | Medical records | 2011 | 7832 | 556 | 7.1 | Low |
| Hayata 2019 [ | Cross-sectional | Japan | High | Medical records | 2017 | 1928 | 265 | 13.7 | Low |
| Inagaki 2019 [ | Cross-sectional | Brazil | Upper-middle | Medical records | 2016 | 373 | 129 | 34.6 | Low |
| Indraccolo 2016 [ | Prospective cohort | Italy | High | Direct observation | 2015 | 92 | 25 | 27.2 | Moderate |
| Indraccolo 2017 [ | Prospective cohort | Italy | High | Direct observation | 2014 | 158 | 41 | 25.9 | Moderate |
| Iyengar 2009 [ | Cross-sectional | India | Lower-middle | Self-reported | 2006 | 632 | 422 | 67.0 | Moderate |
| Karaçam 2012 [ | Randomised controlled trial | Turkey | Upper-middle | Direct observation | 2009 | 396 | 167 | 42.2 | Low |
| Karacam 2017 [ | Cross-sectional | Turkey | Upper-middle | Direct observation | 2014 | 303 | 83 | 27.4 | Low |
| Kawasoe 2019 [ | Case–control | Japan | High | Medical records | 2016 | 462 | 48 | 10.4 | Low |
| Lazzerini 2018 [ | Cross-sectional | Italy | High | Self-reported | 2018 | 807 | 106 | 13.1 | Low |
| Leal 2019a [ | Cross-sectional | Brazil | Upper-middle | Not specified | 2017 | 5998 | 954 | 15.9 | Moderate |
| Leal 2019b [ | Cross-sectional | Brazil | Upper-middle | Not specified | 2017 | 1096 | 235 | 21.4 | Moderate |
| Lemos 2011 [ | Cross-sectional | Brazil | Upper-middle | Direct observation | Not specified | 33 | 12 | 36.4 | Moderate |
| Leombroni 2019 [ | Cross-sectional | Italy | High | Direct observation | 2016 | 104 | 31 | 29.8 | Moderate |
| Lima 2018 [ | Cross-sectional | Brazil | Upper-middle | Not specified | 2014 | 460 | 71 | 15.5 | Low |
| Lopes 2019a [ | Cross-sectional | Brazil | Upper-middle | Not specified | 2012 | 293 | 25 | 8.5 | Moderate |
| Lopes 2019b [ | Cross-sectional | Brazil | Upper-middle | Not specified | 2016 | 499 | 61 | 13.6 | Moderate |
| Martins Franco Motta 2016 [ | Cross-sectional | Brazil | Upper-middle | Not specified | 2013 | 51 | 32 | 62.7 | Moderate |
| Masuda 2020 [ | Cross-sectional | Philippines | Lower-middle | Direct observation | 2018 | 170 | 53 | 31.2 | Low |
| Matsuo 2009 [ | Cross-sectional | Japan | High | Medical records | 2006 | 661 | 39 | 5.9 | Low |
| Maves 2020 [ | Descriptive | India | Lower-middle | Direct observation | 2019 | 16 | 11 | 69.0 | Moderate |
| Mohamed 2017 [ | Cross-sectional | Egypt | Lower-middle | Direct observation | 2017 | 672 | 428 | 63.1 | Low |
| Moiety 2014 [ | Cross-sectional | Egypt | Lower-middle | Direct observation | 2011 | 8097 | 1974 | 24.4 | Low |
| Mollberg 2005 [ | Cross-sectional | Sweden | High | Medical records | 1997 | 13,716 | 5236 | 38.2 | Low |
| Mollberg 2007 [ | Case–control | Sweden | High | Direct observation | 2001 | 557 | 90 | 16.2 | Low |
| Monguilhott 2018 [ | Cross-sectional | Brazil | Upper-middle | Self-reported | 2011 | 2070 | 571 | 27.6 | Low |
| Okumus 2017 [ | Descriptive | Turkey | Upper-middle | Medical records | 2016 | 240 | 138 | 57.5 | Moderate |
| Pazandeh 2015a [ | Cross-sectional | Iran | Upper-middle | Direct observation | 2012 | 24 | 16 | 66.7 | Low |
| Pazandeh 2015b [ | Cross-sectional | Iran | Upper-middle | Self-reported | 2012 | 100 | 59 | 59.0 | Low |
| Pifarotti 2014 [ | Case–control | Italy | High | Medical records | 2010 | 405 | 39 | 9.6 | Low |
| Pinar 2018 [ | Cross-sectional | Turkey | Upper-middle | Direct observation | 2014 | 350 | 107 | 30.6 | Low |
| Prado 2017 [ | Cross-sectional | Brazil | Upper-middle | Self-reported | 2016 | 456 | 145 | 31.7 | Low |
| Raj 2017 [ | Cross-sectional | India | Lower-middle | Self-reported | 2015 | 2639 | 211 | 8.0 | Low |
| Ratcliffe 2016 [ | Cross-sectional | Tanzania | Low | Direct observation | 2014 | 208 | 7 | 3.4 | Moderate |
| Rathfisch 2011 [ | Descriptive | Turkey | Upper-middle | Direct observation | Not specified | 537 | 245 | 45.6 | Low |
| Rohde 2016 [ | Cross-sectional | Portugal | High | Self-reported | 2015 | 468 | 165 | 35.0 | Moderate |
| Ruiz de Vinaspre Hernandez 2013 [ | Retrospective cohort | Spain | High | Medical records | 2010 | 212 | 71 | 33.5 | Low |
| Sandin-Bojo 2006 [ | Cross-sectional | Sweden | High | Medical records | 1999 | 192 | 25 | 13.0 | Low |
| Santos 2016 [ | Quasi-experimental before-and-after | Brazil | Upper-middle | Self-reported | 2016 | 35 | 2 | 5.7 | Moderate |
| Sehhati 2013 [ | Descriptive | Iran | Upper-middle | Not specified | 2012 | 499 | 153 | 30.7 | Low |
| Sharma 2019 [ | Cross-sectional | India | Lower-middle | Direct observation | 2015 | 275 | 79 | 29.0 | Low |
| Shimada 2013 [ | Case–control | Japan | High | Medical records | 2012 | 6317 | 634 | 10.0 | Low |
| Skrablin 2011 [ | Cross-sectional | Croatia | High | Direct observation | 2010 | 205 | 35 | 17.1 | Low |
| Sonoda 2012 [ | Cross-sectional | Japan | High | Medical records | 2009 | 761 | 68 | 8.9 | Low |
| Sousa 2016 [ | Cross-sectional | Brazil | Upper-middle | Not specified | 2012 | 237 | 22 | 9.3 | Low |
| Sturzenegger 2017 [ | Retrospective cohort | Switzerland | High | Medical records | 2013 | 17,957 | 1447 | 8.1 | Low |
| Suzuki 2014 [ | Cross-sectional | Japan | High | Medical records | 2012 | 64 | 15 | 24.0 | Low |
| Ukke 2019 [ | Cross-sectional | Ethiopia | Low | Self-reported | 2017 | 214 | 35 | 16.4 | Low |
| Vora 2018 [ | Cross-sectional | India | Lower-middle | Self-reported | 2014 | 1616 | 259 | 16.0 | Moderate |
Countries where included studies gathered primary data, income levels per the 2020 World Bank Classification [25]
| Country | Number of studies | Number of women included | Income level [ |
|---|---|---|---|
| Egypt | 2 | 8769 | Lower-middle |
| Ethiopia | 2 | 407 | Low |
| Tanzania | 1 | 208 | Low |
| India | 6 | 6053 | Lower-middle |
| Iran | 6 | 4614 | Upper-middle |
| Japan | 8 | 762,408 | High |
| Philippines | 1 | 170 | Lower-middle |
| Turkey | 6 | 2177 | Upper-middle |
| Croatia | 1 | 205 | High |
| Italy | 10 | 25,175 | High |
| Portugal | 1 | 468 | High |
| Spain | 4 | 855 | High |
| Sweden | 6 | 15,971 | High |
| Switzerland | 3 | 35,532 | High |
| Canada | 1 | 5368 | High |
| Brazil | 19 | 27,596 | Upper-middle |
| Ecuador | 1 | 252 | Upper-middle |
| Peru | 1 | 250 | Upper-middle |
| Guinea, Myanmar, Ghana and Nigeria | 1 | 2016 | 3 lower-middle, 1 low |
Of the 80 data sets three were from low income countries, nine from lower-middle income countries, 33 from upper-middle income countries, 34 from high income countries and one included four countries of various income levels
Summary of characteristics of included studies
| Study characteristic | Number of studies | % |
|---|---|---|
| Case–control | 6 | 7.5 |
| Cross-sectional | 51 | 63.8 |
| Descriptive | 8 | 10.0 |
| Prospective cohort | 6 | 7.5 |
| Retrospective cohort | 4 | 5.0 |
| Quasi-experimental before and after | 2 | 2.5 |
| Randomised controlled trial | 3 | 3.8 |
| Women’s self-report | 19 | 23.6 |
| Direct observation | 29 | 36.3 |
| Medical records | 24 | 30.0 |
| Not specified | 8 | 10.0 |
| During labour and childbirth care | 54 | 67.5 |
| Postpartum within 6 weeks | 17 | 21.3 |
| Postpartum ranging outside 6 weeks | 6 | 7.5 |
| Not specified | 3 | 3.8 |
Characteristics of women in the included studies
| Characteristics of women | Number of studies | % |
|---|---|---|
| Women giving birth vaginally or women in labour | 76 | 95.0 |
| Women undergoing vacuum extraction | 2 | 2.5 |
| Women undergoing induction of labour | 1 | 1.3 |
| Women with prolonged second stage of labour | 1 | 1.3 |
| Singleton only | 29 | 36.3 |
| Twins only | 1 | 1.3 |
| Singletons and multiples | 6 | 7.5 |
| Not specified | 44 | 55.0 |
| Nulliparous women only | 11 | 13.8 |
| Any parity | 39 | 48.8 |
| Any parity except grandmultiparas | 1 | 1.3 |
| Not specified | 29 | 36.3 |
Fig. 2Forest plot of pooled meta-analysis of prevalence of uterine fundal pressure
Results of sensitivity analyses
| Population | Number of studies | Pooled estimate of prevalence (%, 95% CI) | Heterogeneity (%) |
|---|---|---|---|
| High quality studies only | 57 | 21.5 (17.3–25.7) | 99.90 |
| Studies with > 500 women only | 36 | 17.1 (12.0–22.2) | 99.98 |
| Study population generalizable to the target population | 76 | 22.6 (18.8–26.4) | 99.97 |
Results of subgroup analyses
| Number of studiesa | Pooled estimate of prevalence (%, 95% CI) | ||
|---|---|---|---|
| < 0.001* | |||
| High | 33 | 16.4 (12.3–20.5) | |
| Upper-middle | 33 | 29.0 (23.1–35.0) | |
| Lower-middle | 10 | 34.7 (19.0–50.4) | |
| Low | 3 | 10.2 (2.6–17.7) | |
| 0.705 | |||
| 1991–2000 | 4 | 18.2 (3.4–33.0) | |
| 2001–2010 | 12 | 20.5 (9.7–31.4) | |
| 2011–2020 | 61 | 23.7 (19.3–28.1) | |
| 0.098 | |||
| Nulliparous | 22 | 27.3 (18.6–36.0) | |
| Multiparous | 11 | 15.6 (4.8–26.4) | |
| 0.001* | |||
| Direct observation | 29 | 28.0 (21.3–34.8) | |
| Medical records | 24 | 14.4 (9.1–19.7) | |
| Women’s self-report | 19 | 29.8 (21.5–38.0) |
aOne study reporting data from multiple countries of mixed income levels was excluded from the income level subgroup analysis. Studies that did not specify decade of data collection (n = 3) or method of assessing fundal pressure use (n = 8) were not included in subgroup analyses. Twenty-two studies included in subgroup analysis of parity—eleven of these provided data on both nulliparous and multiparous women, and eleven provided data on nulliparous women only