# Factors associated with severe postpartum haemorrhage: systematic review using Bradford Hill's causality framework

Tatiana Stachetti, Michel Spodenkiewicz, Arnaud Winer, Malik Boukerrou, Julie Jesson, Patrick Gérardin

► To cite this version:

Tatiana Stachetti, Michel Spodenkiewicz, Arnaud Winer, Malik Boukerrou, Julie Jesson, et al. Factors associated with severe postpartum haemorrhage: systematic review using Bradford Hill's causality framework. Journal of Global Health Reports, 2019, 3, 10.29392/joghr.3.e2019085. hal-04832076

HAL Id: hal-04832076

https://ut3-toulouseinp.hal.science/hal-04832076v1

Submitted on 11 Dec 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
Research Article

# Factors associated with severe postpartum haemorrhage: systematic review using Bradford Hill's causality framework

Tatiana Stachetti<fnref n="1" />, Michel Spodenkiewicz<fnref n="1" />, Arnaud Winer², Malik Boukerrou³, Julie Jesson⁴, Patrick Gérardin<fnref n="1" />

Keywords: maternal mortality, post partum hemorrhage, global health

https://doi.org/10.29392/joghr.3.e2019085

Journal of Global Health Reports

Vol. 3, 2019

## Background

Severe postpartum haemorrhage (S-PPH) is the leading cause of maternal death worldwide. We aimed to provide an up-to-date summary about S-PPH determinants.

## Methods

We performed a systematic review following the Preferred Reporting Items for Systematic reviews and Meta-analysis (PRISMA) guidelines. We searched the terms “risk factor”, “determinant”, “post-partum haemorrhage” and “severe”, within Web of Science, Scopus, Science Direct, Medline, Cochrane, and Clinical Trials.gov databases. The primary endpoint was S-PPH, defined as a blood loss ≥1,000 mL a second-line treatment, a PPH-related blood transfusion, a peripartum decrease in haemoglobin level or a PPH-related maternal death. All interventional and observational studies about risks factors for S-PPH published in English or French between January 1, 2004 and August 31, 2018 were eligible. Because studies used very different definitions of S-PPH, meta-analysis was ruled out and we gauged the risk factors using the Bradford Hill's criteria causality framework.

## Results

Amongst 1,193 identified abstracts, we selected fourteen studies that collected information on 9,271,519 parturient women (35,825 with S-PPH). Key established determinants of S-PPH were previous PPH, previous caesarean, multiple pregnancy, abnormal placentation, preeclampsia, labour induction, prolonged labour, placental retention, uterine rupture, uterine atony, uterine fibroids, macrosomia, birth canal injuries, instrumental vaginal and caesarean deliveries. Most of associated factors of uncertain significance belonged to socio-environmental characteristics. Biological parameters were all classified as indicators of risk.

## Conclusions

The key established determinants of S-PPH are of primarily obstetrical nature. New avenues of research, including contextual studies, are needed to improve the management of severe obstetrical morbidity.

Despite global effort to reduce maternal mortality, post-partum haemorrhage (PPH) is the leading cause of maternal death worldwide. PPH accounts for a large majority of obstetrical haemorrhages and severe obstetrical morbidity.<fnref n="1" />

PPH is usually defined as blood loss of at least 500 mL, 700 mL, or 1,000 ml, according to its different guidelines.<fnref n="1" />⁻³ At population level, the incidence of PPH is estimated about 5% of total live births—this number varying greatly between regions and obstetric centres. Severe PPH (S-PPH), currently defined as blood loss of more than 1,000 mL accounts for about 1% of total deliveries (~20% of all parturient women).<fnref n="1" />⁻³

Several individual risk factors for PPH and S-PPH have been reported in the literature, including non-obstetrical and obstetrical determinants.⁴,⁵ Thus, greater attention has been paid during the last decade to the medical management of S-PPH, as it may lead to further improvements with an important impact on the disease burden.

In accordance, studies have been conducted to establish recommendations for clinical practice in managing child-birth. Nevertheless, most of these studies have focused on the period of labour and did not fully account, either for non-obstetrical individual or antepartum obstetrical individual risk factors.⁶,⁷ Furthermore, the quality of care in

<footnote n="1">¹ INSERM CIC1410 Clinical Epidemiology, Centre Hospitalier Universitaire (CHU) Réunion, Saint Pierre, Réunion, France, ² CEPOI-EA7388, Pôle des Disciplines de l'Urgence, Réanimation, CHU de la Réunion, Saint Pierre, Réunion, France, ³ CEPOI-EA7388, Pôle Femme Mère Enfant, Gynécologie-Obstétrique, CHU de la Réunion, Saint Pierre, Réunion, France, ⁴ Bordeaux Population Health Research Center, INSERM U1219, Bordeaux, France</footnote>
obstetrics is a major global health concern that requires
continuous improvements. In this sense, conducting regu-
lar updates of the literature on the determinants of S-PPH
can help to account for the evolution of knowledge and
practices, quality emergency obstetric care (EmOC) while
in turn it may also contribute to mitigating maternal risks
through improving the triage and treatment of parturient
women.

In this framework, we provided an up-to-date summary
about the determinants for S-PPH. Our first hypothesis was
that certain maternal conditions (age at first parity, grand
multiparity, obesity, stress, depression, etc.) which are in-
creasing in western countries and are classically associated
with some PPH determinants (pre-eclampsia, caesarean
section, instrumental extractions) could contribute to an
increase in the incidence of PPH. Our second hypothesis
was that the lack of identification, upstream of organiza-
tional measures aimed at preventing PPH, pushed to focus
efforts on individual obstetrical care, which could be ham-
pered by the deterioration of socio-economic conditions
and access to prevention, thus facilitating the risk of S-PPH
at presentation. We deduced from the above the possibil-
ity that determinants of PPH upstream of childbirth could
emerge, with a strong probability that those which are not
very dependent on obstetrical care, could be also associated
with progression from PPH to S-PPH. Our primary objective
was to identify and classify the determinants of S-PPH for
decision-making purposes.

METHODS

SEARCH STRATEGY AND STUDY SELECTION

This systematic review was developed following the Pre-
ferred Reporting Items for Systematic Reviews and Meta-
Analysis (PRISMA) guidelines (Appendix S1 in the **Online**
**Supplementary Document**).⁸

Using the terms “risk factor”, OR “determinant”, AND “post-partum haemorrhage” AND “severe”, we searched Web of Science, Scopus, Science Direct, Medline, Cochrane (Pregnancy and Childbirth Group’s Register), [ClinicalTrials.gov](https://ClinicalTrials.gov) databases, for both interventional and observational studies (randomized controlled trials; either cross-sectional, case-control or cohort studies, respectively) published in English language, between January 1, 2004 and August 31, 2018.

The full search strategy is detailed in the protocol pro-
vided in Appendix S2 of the **Online Supplementary Docu-**
**ment.**

Abstracts of identified articles were screened indepen-
dently by two reviewers (TS, PG) to verify whether they
matched the selection criteria. Inter-observer discrepancies
were resolved by arbitration of a third reviewer (MS).
Searches were complemented by consulting with experts in
the field.

Study eligibility criteria targeted women who planned for
a vaginal delivery or those who underwent an unplanned,
emergency caesarean. All interventional and observational
studies were deemed eligible.

Our primary endpoint was S-PPH, defined as a composite
of blood loss of at least 1,000 mL, or a second-line treat-

ment (uterine suture, pelvic vessel ligation, arterial em-
bolization, hysterectomy), PPH-related blood transfusion,
peripartum decrease in haemoglobin level, PPH-related
maternal death. This outcome definition was selected be-
cause it was consistent with the WHO definition of S-PPH.¹

QUALITY ASSESSMENT AND DATA EXTRACTION

The quality of studies was assessed using both the STROBE and CONSORT checklists, as appropriate for observational studies and RCTs.⁹,¹⁰

Data extraction was performed in duplicate using a stan-
dardized form by two independent researchers (TS and PG).
Inter-observer discrepancies were again resolved by arbitra-
tion of the same third reviewer (MS).

DATA ANALYSIS

BIAS ASSESSMENT

Bias analysis was adapted from both interventional and ob-
servational study designs. It was conducted with reference
to the classic biases identified in the Cochrane Handbook or
in Jean Bouyer's epidemiology textbook (selection, perfor-
mance, detection, attrition, classification, evaluation, and
confusion biases).<sup>11,12</sup> We rated biases in each study as "ab-
sent" (-), "possible" (+), "probable" (++), "highly probable"
(+++), or "not applicable" (N/A).

EVALUATION OF RISK FACTORS FOR S-PPH

Risk factors for S-PPH were gauged using odds ratios (OR)
and their 95% confidence interval (CI). Strength was defined
for OR>2.0. They were classified as “key established” or of
“uncertain significance” determinants using the Bradford
Hill criteria’s framework for causal inference, under a prag-
matic approach devised to comply with modern-day is-
sues.<sup>13,14</sup> Concretely, each of the factors identified through
data extraction was gauged using the Bradford Hill criteria
(strength, consistency, specificity, temporality, biological
gradient, plausibility, coherence, experiment, and analogy)
causality framework to determine the causative nature of
the pathway between exposure to this factor and S-PPH.
Causation and mediation were investigated using directed
acyclic graphs, as done routinely in epidemiological prac-
tice.

Factors matching at least three of the abovementioned
criteria, or two criteria while being linked to a known cause
of bleeding (well-known aetiology of PPH, inherited or ac-
quired haemorrhagic disease) were considered as “key es-
tablished” determinants (involving the probability of a
“causal pathway”, based on this abovementioned composite
definition).

Factors matching one or two criteria without being
linked to a known cause of bleeding were classified as of
“associated uncertain status” and recommended for being
explored in further study.

Factors accompanying development or progression of S-
PPH, without matching any of the abovementioned criteria,
nor being linked to a known cause of bleeding, were consid-
ered as indicators (or markers) of risk. By this, we mean fac-
<figure><img src="image_2.png" /><figcaption>**Figure 1. PRISMA flowchart.**</figcaption></figure>

Summarizes the selection of the articles included in this literature review.

tors indicating a risk of PPH without necessarily interven-
ing in the causal chain between exposure and event.

RESULTS

The selection process of the articles fulfilling the eligibility
criteria for our systematic review is presented in Figure 1.

SELECTED STUDIES

We identified 1,193 potentially relevant, non-duplicate
studies. After reviewing the full text of these publications,
we found a total of eleven articles that met our inclusion
criteria.
## CHARACTERISTICS OF SELECTED STUDIES

The descriptive characteristics of the retrieved studies<sup>15-28</sup> including the period, location, study design, duration of enrolment, and the monocentric or multi-centric organisation of the fourteen selected studies, as well as the statistical method used for classifying risk factors in each of them, are summarized in Table 1.

The selected studies belonged to several study designs, as follows: cohort study (n=10), case-control study (n=3), and cluster randomized clinical trial (n=1). Inclusion periods ranged from ten months to nine years.

The total study population was composed of 9,271,519 parturient women (including 146,781 participants of the Pithagore-6 cluster randomized clinical trial). The number of cases of S-PPH was of 35,825 representing 3.9% of all childbirths.

In studies for which the proportion of S-PPH among all cases of PPH could be measured, the average proportion of S-PPH was of 25%. This figure differs slightly from the usually accepted ratio of one S-PPH for five PPH (20%).

The primary endpoint of each study fulfilled the outcome measure previously established in our review protocol. However, the definition of S-PPH varied across studies according to whether the selected outcome was single or composite.

## RISK OF BIAS IN SELECTED STUDIES

Biases were independently evaluated for each study. Their analysis is summarized in Table 2.

For example, the study by Briley *et al.* was deemed to be potentially prone to a moderate selection bias given the small representativeness of this bicentric study and the use of secondary subsampling withdrawing the majority of PPH cases.¹⁷ Together with a 14% error rate in estimated blood loss, we considered it was also affected by a highly probable classification bias, while other biases were considered negligible.

## FACTORS ASSOCIATED WITH S-PPH

The full assessment of risk factors using Bradford Hill's criteria is displayed in Appendix S3 of the **Online Supplementary Document**.

### INDIVIDUAL RISK FACTORS

#### AGE

Six studies showed that maternal age of 35 years or above were associated with PPH in a significant, consistent, and coherent manner.<sup>15,17,24-27</sup> In addition, Kramer *et al.* also showed a significant association between PPH and maternal age less than 19 years and the role of first pregnancy at older age on risk of S-HPP was highlighted.<sup>27</sup> Indeed, the risk of S-PPH appears to be U-shaped, being higher before 19 and after 35 years.

#### BODY MASS INDEX

In the study by Briley *et al.*, the body Mass Index (BMI) was associated with a linear increase of the S-PPH risk (OR 1.04,

95% CI=1.01-1.06, per one-unit increase).<sup>17</sup> In the study by Nyfløt *et al.*, obese women (BMI>30) were slightly more at risk of S-PPH (OR 1.29, 95% CI=1.02-1.63),<sup>16</sup> while in turn, Paglia *et al.* found a higher risk of S-PPH when the parturient had a BMI less than 30 kg/m<sup>2</sup>.<sup>20</sup>

These seemingly contradictory results do not allow us to conclude about the risk's direction between BMI and S-PPH.

#### ETHNICITY

The risk of S-PPH was lower among patients from the Middle East (OR 0.60, 95% CI=0.45-0.81) but was higher among patients from Southeast Asia (OR 1.77, 95% CI=1.48-2.12) than it was among European patients.<sup>15</sup> Another study found a strong risk (OR>2.0) of PPH in Hispanic populations (OR 3.14, 95% CI=1.23-9.32), as compared with Caucasians.<sup>20</sup>

#### SOCIAL CONTEXT

The study by Briley *et al.* was the only to focus on the impact of patients' neighbourhood, income level, and educational skills (these variables feeding an "index of multiple deprivation") on PPH.<sup>17</sup> Importantly, it showed that a disadvantaged neighbourhood was associated with an increased risk of severe PPH (OR 1.82, 95% CI=1.10-3.00).

## OBSTETRICAL HISTORY

### PREVIOUS CAESAREAN

The studies by Al Zirqi *et al.* (OR 1.46, 95% CI=1.02-2.20), Helman *et al.* (OR 2.75, 95% CI=1.42-5.33), and Kramer *et al.* (OR 1.3, 95% CI=1.2-1.3) found an association between a history of caesarean and S-PPH.<sup>15,18,27</sup>

These results are consistent, plausible, and coherent. They also met the criterion of temporality, according to which exposure precedes the effect. In agreement, a history of previous caesarean section was deemed a key established determinant of S-PPH.

### PREVIOUS PPH

The strength of the association between a history of previous PPH and subsequent postpartum bleeding was consistent.<sup>16,17,22,24</sup> Ditto, the criterion of temporality was met. In agreement, a history of previous PPH was deemed a key established determinant of S-PPH.

#### PARITY

Al Zirqi *et al.* (OR 1.10, 95% CI=1.02-1.19), Driessen *et al.* (OR 1.88, 95% CI=1.51-2.33) and Dupont *et al.* (OR 1.71, 95% CI=1.43-2.05), reported an association between primiparity and S-PPH.<sup>15,22,24</sup> It was less clear for multiparity. Given these discrepancies through parity, we concluded that regarding S-PPH, parity was a factor of uncertain significance.

## COURSE OF PREGNANCY

### MULTIPLE PREGNANCY

Eight studies showed a strong association between multiple pregnancy and severe bleeding.<sup>15-18,22-25</sup> These results
<table><caption>Table 1. Descriptive characteristics of selected studies</caption><thead><tr><th>Authors</th><th>Study location, period</th><th>Study design</th><th>Inclusion (months)</th><th>Population (inclusion criteria)</th><th>Outcome measure</th><th>Analysis</th></tr></thead><tbody><tr><td>Al Zirqi et al, Sep. 2008<sup>15</sup></td><td>Norway, 1999 - 2004</td><td>Multicentric retrospective cohort study</td><td>48</td><td>Cohort n= 307,415 (SPPH n=3,501)<br>"Medical Birth Registry of Norway"</td><td>1: SPPH: >1,500 mL or blood transfusion</td><td>Multivariate logistic regression</td></tr><tr><td>Briley et al, Feb. 2014<sup>17</sup></td><td>United Kingdom, 08/2008 - 07/2009</td><td>Bicentric prospective Cohort study</td><td>12</td><td>Cohort n=10,213- 9,937 (PPH n=3,349; SPPH n=936)</td><td>1: PPH: >500 mL<br>2: SPPH: >1,500 mL (measure not specified)</td><td>Multivariate logistic regression</td></tr><tr><td>Deneux-Tharaux et al. Jun. 2010<sup>21</sup></td><td>France 09/ 2004 - 11/ 2005, 09/ 2005 - 11/ 2006</td><td>Multicentric cluster randomized controlled trial</td><td>27</td><td>Trial population n=146,781 (SPPH n=2,414)<br>Pithagore</td><td>1: SPPH: blood transfusion, second-line treatment, decrease in Hb≥4 g/dL, ICU transfer, death<br>2: Ratio of SPPH to total number of deliveries</td><td>Multivariate logistic regression (random intercept mixed model)</td></tr><tr><td>Driessen et al, Jan. 2011<sup>22</sup></td><td>France, 12/ 2004 - 11/ 2006</td><td>Multicentric prospective cohort study</td><td>24</td><td>PPH from uterine atony n=4,550<br>Including SPPH n=952<br>Pithagore 6</td><td>SPPH: decrease in Hb ≥ 4g/dL</td><td>Multivariate random-intercept hierarchical logistic regression</td></tr><tr><td>Dupont et al, May 2014<sup>24</sup></td><td>France, 12/ 2005 - 11/ 2006</td><td>Multicentric Prospective cohort study</td><td>27</td><td>Cohort n=146,781 (PPH n=9,364; SPPH n=2,494)<br>Pithagore 6</td><td>1: PPH: >500mL, decrease in Hb ≥2g/dL,<br>2: SPPH: >1,000mL, decrease in Hb ≥4g/dL, uterine embolization, uterine surgery, blood transfusion, ICU transfer, death (measure not standardized)</td><td>Multivariate logistic regression</td></tr><tr><td>Gayat et al, Jul. 2011<sup>23</sup></td><td>France, 01/ 2004 -12/ 2005</td><td>Monocentric retrospective cohort study</td><td>24</td><td>PPH n=257 including SPPH n=110<br>Cohort Lariboisière</td><td>SPPH: uterine embolization, balloon tamponade, pelvic vessel ligation and/or hysterectomy</td><td>Multivariate logistic regression</td></tr><tr><td>Marocchini et al, May 2017<sup>25</sup></td><td>France, 2006-2014</td><td>Multicentric rétrospective Cohort</td><td></td><td>Cohort n=156047 including SPPH n=1136</td><td>Blood transfusion</td><td>Multivariate logistic regression</td></tr><tr><td>Helman et al, Apr. 2015<sup>18</sup></td><td>Israel, 07/ 2005- 02/ 2014</td><td>Monocentric case-control (1/4) study</td><td>24</td><td>n=113,342 (SPPH n=122)<br>"Medical DataBase"</td><td>SPPH: blood transfusion (5 RBCs)</td><td>Multivariate logistic regression</td></tr><tr><td>Karlsson et al, Jul. 2015<sup>19</sup></td><td>Sweden, 06/ 2013 - 03/ 2014</td><td>Multicentric prospective cohort study</td><td>10</td><td>n=1,951 (SPPH n=250)</td><td>SPPH: >1,000mL (measure not specified)</td><td>Multivariate logistic regression</td></tr><tr><td>Kramer et</td><td>Canada,</td><td>Multicentric</td><td>108</td><td>PPH n=240,472, SPPH n=25,906</td><td>SPPH: -PPH + blood transfusion, -PPH + hysterectomy and/</td><td>Multivariate</td></tr></tbody></table>
<table><thead><tr><th>Authors</th><th>Study location, period</th><th>Study design</th><th>Inclusion (months)</th><th>Population (inclusion criteria)</th><th>Outcome measure</th><th>Analysis</th></tr></thead><tbody><tr><td>al, Jul. 2013<sup>27</sup></td><td>Montreal, USA, Atlanta, 1999 - 2008</td><td>retrospective cohort study</td><td></td><td>"NIS Database"</td><td>or blood transfusion and/or uterine surgery, - PPH + uterine surgery w/o hysterectomy and/or blood transfusion</td><td>logistic regression</td></tr><tr><td>Nyflot et al, Jan. 2017<sup>16</sup></td><td>Norway, 2008-2011</td><td>Bicentric retrospective, Case control</td><td>48</td><td>Population n=43105,SPPH=1064</td><td>SPPH: >1,500 mL or blood transfusion</td><td>Multivariate logistic regression</td></tr><tr><td>Paglia et al, 2012<sup>20</sup></td><td>USA, Durham, 2000 - 2004</td><td>Monocentric case-control study</td><td>60</td><td>n=218 deliveries in the case-control group (12,476 in the source population), PPH n=671 including SPPH n=109<br>"Duke University Medical Center, ICD 9"</td><td>SPPH: PPH + blood transfusion</td><td>Multivariate logistic regression</td></tr><tr><td>Sosa et al, Jun. 2009<sup>28</sup></td><td>Uruguay, Argentina, 12/10/2003 -12/0/2005</td><td>Multicentric prospective cohort<br>Secondary analysis</td><td>24</td><td>Cohort n=11,323 (PPH n=1,221; SPPH n=209)</td><td>PPH: >500 mL<br>SPPH: >1,000 mL + blood transfusion (measure not specified)</td><td>Multivariate cluster logistic regression</td></tr><tr><td>Tort et al, Nov. 2016<sup>26</sup></td><td>Benin Mali, 2013-2014</td><td>Multicentric prospective cohort</td><td>17</td><td>Cohort:22666,PPH:223,SPPH:88</td><td>SPPH:PPH+surgery or blood transfusion or death</td><td>Multivariate logistic regression</td></tr></tbody></table>

SPPH – severe postpartum haemorrhage, PPH – postpartum haemorrhage
<table><caption>Table 2. Evaluation of study quality with bias analysis</caption><thead><tr><td>Study/bias</td><td>Selection</td><td>Performance</td><td>Detection</td><td>Attrition</td><td>Classification</td><td>Evaluation</td><td>Confounding</td></tr></thead><tbody><tr><td>Al Zirqi et al.<sup>15</sup></td><td>+</td><td>N/A</td><td>N/A</td><td>-</td><td>+</td><td>++</td><td>+</td></tr><tr><td>Briley et al.<sup>17</sup></td><td>++</td><td>N/A</td><td>N/A</td><td>-</td><td>++</td><td>+++</td><td>+</td></tr><tr><td>Deneux-Tharaux et al.<sup>21</sup></td><td>-</td><td>++</td><td>+</td><td>-</td><td>N/A</td><td>+</td><td>+</td></tr><tr><td>Driessen et al.<sup>22</sup></td><td>+</td><td>N/A</td><td>N/A</td><td>-</td><td>+</td><td>+</td><td>++</td></tr><tr><td>Dupont et al.<sup>24</sup></td><td>++</td><td>N/A</td><td>N/A</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>Gayat et al.<sup>23</sup></td><td>+++</td><td>N/A</td><td>N/A</td><td>+</td><td>++</td><td>++</td><td>+++</td></tr><tr><td>Marocchini et al.<sup>25</sup></td><td>++</td><td>N/A</td><td>N/A</td><td>+</td><td>++</td><td>+++</td><td>+++</td></tr><tr><td>Helman et al.<sup>18</sup></td><td>+++</td><td>N/A</td><td>N/A</td><td>-</td><td>++</td><td>+++</td><td>+++</td></tr><tr><td>Karlsson et al.<sup>19</sup></td><td>+++</td><td>N/A</td><td>N/A</td><td>+</td><td>++</td><td>+++</td><td>+++</td></tr><tr><td>Kramer et al.<sup>27</sup></td><td>++</td><td>N/A</td><td>N/A</td><td>-</td><td>++</td><td>++</td><td>++</td></tr><tr><td>Nyflot et al.<sup>16</sup></td><td>++</td><td>N/A</td><td>N/A</td><td>-</td><td>+</td><td>++</td><td>+</td></tr><tr><td>Paglia et al.<sup>20</sup></td><td>++</td><td>N/A</td><td>N/A</td><td>-</td><td>++</td><td>+++</td><td>+++</td></tr><tr><td>Sosa et al.<sup>28</sup></td><td>+</td><td>N/A</td><td>N/A</td><td>-</td><td>+</td><td>++</td><td>++</td></tr><tr><td>Tort et al.<sup>26</sup></td><td>+</td><td>N/A</td><td>N/A</td><td>-</td><td>++</td><td>+++</td><td>++</td></tr></tbody></table>

no bias (-), possible bias (+), probable bias (++), highly probable bias (+++), N/A – not applicable
met the criteria of strength, consistency, plausibility, and
coherence. Multiple pregnancy was considered as a key es-
tablished determinant of S-PPH.

EMBRYONIC ANNEXES (PLACENTA, AMNIOTIC MEMBRANES, UMBILICAL CORD)

Abnormal placentation led to S-PPH (OR 7.05, 95% CI=2.26-22.03).²³ Kramer *et al*. confirmed this association with placenta praevia and placenta abruption (OR 7.00, 95% CI=6.60-7.30),²⁷ though Marocchini *et al*. found a very strong association between placenta praevia and S-PPH (OR 22.00).²⁵ In addition, Briley *et al*. specified that the risk of S-PPH was the higher with anterior placental presentation (OR 5.55, 95% CI=1.29-23.90).¹⁷ Kramer *et al*. showed a significant increase in the risk of PPH in the presence of polyhydramnios and chorioamnionitis.²⁷

Given the strength, consistency, and plausibility of these
results, we considered abnormal placentation as a key es-
tablished determinant for S-PPH.

PREGNANCY-INDUCED HYPERTENSIVE DISORDERS

Although no association was found between preeclampsia and PPH, the strength and the dose-response relationship between pregnancy-induced hypertensive disorders and S-PPH found consistently in the literature support a causal as- sociation.¹⁷,²⁰ Moreover, eclampsia complicated by a HELLP Syndrome (Haemolysis, Elevated Liver enzyme levels, Low Platelet count) was strongly and consistently associated with life-threatening haemorrhages.¹⁵,²⁵

Given the coherence of these results, we classified
preeclampsia as a key established determinant for S-PPH
and low platelet counts as a key established indicator.

UTERINE FIBROIDS

Uterine fibroids increased the risk of PPH in the study by Nyfløt *et al*. (OR 2.51, 95% CI=1.36-4.64)¹⁶ and in the study by Kramer *et al*. (OR 2.00, 95% CI=1.80-2.20).²⁷ Given uter- ine fibroids are known to cause bleeding in other circum- stances (eg, menstruations), this association was found co- herent, strong, and in accordance, uterine fibroids were considered as a key established obstetrical determinant of S-PPH.

ASSISTED REPRODUCTION

In vitro fertilization (IVF) or intra-cytoplasmic sperm injec-
tion (ICSI) increased the risk of S-PPH in the study by Nyfløt
*et al*. (OR 2.72, 95% CI=1.93-3.85). ¹⁶

MEDICATIONS

Two studies assessed the impact of medications taken dur-
ing pregnancy on S-PPH.<sup>17,20</sup>

The use of corticosteroids for foetal lung maturation was associated with an increased risk of S-PPH (OR 2.0, 95% CI=1.2-3.4).¹⁷ Magnesium injection, as used for alleviating preeclampsia, was also associated with S-PPH (OR 5.4, 95% CI=1.8-20.1).²⁰ Both were deemed as indicators (markers of risk) of S-PPH.

GESTATIONAL AGE

An increased risk of S-PPH was shown for deliveries oc-
curring before 37 weeks gestation (OR 5.0) (²⁵), or after
41 weeks gestation (OR 1.30, 95% CI=1.08-1.56).²⁴ Women
whose infant was very small-for-gestational age (< 3rd per-
centile) were more likely to be transfused for S-PPH.²⁵
These two studies did not allow us to draw a firm conclusion
and this factor was classified as of uncertain significance.

ACTIVE PHASE OF LABOUR

OXYTOCIC DRUGS

Eight studies assessed the role of oxytocic drugs, used for labour induction, in S-PPH.15–18,20,24,27,28 Two was incon- clusive,¹⁷,²⁰ four of these showed a weak association (OR between 1.1 and 1.7),¹⁵,¹⁶,²⁴,²⁷ whereas two found a strong association (OR>2.0).¹⁸,²⁸

The consistency, the coherence with current knowledge
and temporality led us to consider labour induction as a key
established determinant of S-PPH.

LABOUR DURATION

Prolonged active phase of labour, known to alter muscle
contractility, was associated with an increased risk of S-
PPH.15,16,22,24 In addition, Dupont et al. emphasised that
bleeding risk was higher when the active phase of labour ex-
ceeded six hours (OR 1.70, 95% CI=1.143-2.01).24

Given the consistency and plausibility of these results,
we concluded that prolonged labour is a key established de-
tMINANT for S-PPH, without further confirming the six-
hour time limit.

UTERINE RUPTURE

Uterine rupture, a complication that occurs mostly during the active phase of labour, has been recognised as cause of obstetric haemorrhage. The study by Kramer *et al*. confirmed a very strong association between uterine rupture and S-PPH (OR 11.6, 95% CI=9.7-13.8).²⁷

CHILDBIRTH

MODE OF DELIVERY

Eight studies found that instrumental vaginal delivery and emergency caesarean were both associated with S-PPH.<sup>15-19,24,25,27</sup>

Given consistency and coherence of these results, we concluded that instrumental vaginal delivery and caesarean were key established determinants of S-PPH.

FOETAL PRESENTATION

Kramer *et al*. showed that breech presentation increased the risk of S-PPH (OR 1.2, 95% CI=1.1-1.2).²⁷ However, this single study did not allow us to draw a firm conclusion conducting this factor to be considered as of uncertain significance.
## DELIVERY COMPLICATIONS

Sosa *et al.* found a strong association between placenta retention and S-PPH (OR 16.0, 95% CI=7.1-36.0).²⁸ Karlsson *et al.* highlighted a strong association between uterine exploration (usually an indicator of placenta retention) and risk of S-PPH (OR 23.0, 95% CI=14.3-37.1).¹⁹ These findings are highly coherent with current knowledge and recommendations.

## LESIONS IN THE BIRTH CANAL

Cervical laceration was shown strongly associated with bleeding risk (OR 94.0, 95% CI=87.3-101.2).²⁷

Together with the plausibility and coherence of these results, this strong association led us to conclude that if such a birth canal injury (cervical or vaginal laceration, episiotomy) was not sutured in the shortest time possible, blood loss would be substantial. In agreement, cervical injury was considered as a key established determinant of S-PPH.

## BIRTHWEIGHT

Five studies an association between foetal macrosomia and the risk of S-PPH.¹⁵,¹⁶,²⁴,²⁷,²⁸

The consistency and the coherence of these results with current knowledge led us to propose foetal macrosomia as a key established determinant of S-PPH, even though it may not be causal, this increasing the risk of other contributors on the causal pathway to S-PPH like, for instance, the lesions of birth canal.

## BIOLOGICAL PARAMETERS

Low pre-pregnancy or low prepartum haemoglobin levels (<9 g/dL), prothrombin time (PT) below 50%, fibrinogen level below 2 g/L, and detectable level of Troponin-I before delivery, were considered as indicators of S-PPH.¹⁵,¹⁶,²³

## EPIDURAL ANALGESIA

Several studies examined the relationships between epidural analgesia during labour and S-PPH.¹⁷,²²,²⁴ Only two of these showed a weakly protective role (0.5<OR<1.0) of analgesia against S-PPH. Further studies are needed to draw a firm conclusion.

## MANAGEMENT OF SEVERE PPH

Only four studies reported the impact of the medical management of labour on the incidence and prevalence of S-PPH.²¹,²²,²⁴,²⁶

Importantly, Deneux-Tharaux *et al.* found no risk reduction in women exposed to a multifaceted intervention for reducing the incidence of S-PPH.²¹ In the Pithagore-6 cluster RCT similar incidence rates of S-PPH were observed in both the intervention arm (discussion of recommendations, reminders, audit) and the control group (passive diffusion of information). With respect to oxytocin injected during labour, one study found a protective effect when injected within 10 minutes.²⁶ By contrast, Dupont *et al.* found an overall increased risk of S-PPH (OR 1.26, 95%

CI=1.06-1.50),²⁴ while the study by Driessen *et al.*, within the same Pithagore-6-trial framework, established that this risk was actual when given beyond 20 minutes after birth (OR 1.49, 95% CI=1.14-1.94).²² Given this inconsistency, oxytocin during labour was deemed as a factor of S-PPH of uncertain significance.

## SUMMARY OF FINDINGS

We distinguished the factors associated with S-PPH into key established determinants, associated factors of uncertain significance, and indicators to guide the obstetrical decision. This classification is summarized in Table 3.

## DISCUSSION

Based on a critical and pragmatic analysis of the literature, we propose that the key established determinants of S-PPH be identified, as follows: previous caesarean, previous PPH, multiple pregnancy, abnormal placentation, pregnancy-induced hypertensive disorders, labour induction, prolonged labour, uterine rupture, uterine fibroids, instrumental vaginal delivery and caesarean, uterine atony, placental retention, macrosomia and birth canal injuries. In addition, we require further studies to confirm the relevance of reproductive assistance technics (IVF/ICSI), epidural analgesia, gestational age, as well as social factors.

Together with the heterogeneity in the outcome measure definition, the very different study designs, population sizes, and definitions of exposure factors, prevented us to use meta-analysis for providing quantitative estimates of the associations between the candidate determinants and S-PPH.

Despite these limitations, we believe that the pragmatic approach that we used ensures internal validity of our results while minimising publication bias.

We confirm the primarily obstetrical nature of the key determinants of S-PPH. This observation fits current knowledge on the pathogenesis of postpartum bleeding.⁴,²⁹ Among these, we distinguish causes and risk factors according to whether there are no or not mediators on the causal pathway linking exposure to severe bleeding. In agreement, uterine fibroids, abnormal placentation, preeclampsia, uterine rupture, uterus atony, placental retention, and birth canal injuries, are likely causes of PPH by different pathomechanisms *(*fibrinolysis and consumption of clotting factors) and should prompt active management to prevent evolution into S-PPH. By contrast, history of previous caesarean, history of previous PPH, multiple pregnancy, labour induction, prolonged labour, instrumental vaginal delivery and caesarean, require intermediate factors (abnormal placentation or uterus atony) are favouring conditions to severe bleeding in the third stage of labour or after delivery, which motivates additional explorations and interventions (e.g., timely reinjection of oxytocin,³⁰ sublingual misoprostol,³¹ sulprostone,³² or early tranxenamic acid³³) to contain blood losses.

Along with uncertain significance of their predictive value, the non-modifiable character of most socio-demographic factors does not support them for guiding obstetrical decisions.
<table><caption>Table 3. Summary of determinants of severe postpartum haemorrhage</caption><thead><tr><th>S- PPH determinants</th><th>Socio-demographic</th><th>Obstetrical</th><th>Delivery</th><th>Indicators (biological, medical statements)</th></tr></thead><tbody><tr><td rowspan="8">Key established</td><td rowspan="8"></td><td>Previous caesarean, or PPH,</td><td>Instrumental vaginal delivery,</td><td>Hb&lt;9g/dL,</td></tr><tr><td>Multiple pregnancy,</td><td>Caesarean,</td><td>Low platelets,</td></tr><tr><td>Abnormal placentation</td><td>Placental retention,</td><td>PT&lt;50%,</td></tr><tr><td>Preeclampsia, eclampsia,</td><td>Uterine exploration,</td><td>Fibrinogen&lt;2g/dL,</td></tr><tr><td>Cervical maturation,</td><td>Cervical injury,</td><td>Troponin I (detectable)</td></tr><tr><td>Labour induction,</td><td>Macrosomia.</td><td></td></tr><tr><td>Prolonged duration of labour,</td><td></td><td></td></tr><tr><td>Uterine fibroids,</td><td></td><td></td></tr><tr><td>Uterine rupture.</td><td></td><td></td></tr><tr><td rowspan="5">Uncertain significance</td><td>Age</td><td>Parity</td><td>Breech presentation</td><td>Corticosteroid</td></tr><tr><td>BMI</td><td>IVF</td><td>Epidural analgesia*</td><td>Magnesium intake</td></tr><tr><td>Etnicity</td><td>Gestational age</td><td></td><td></td></tr><tr><td>Socio-educational level</td><td>Oxytocin infusion during labour</td><td></td><td></td></tr><tr><td>Maternal education</td><td></td><td></td><td></td></tr></tbody></table>

PPH - postpartum haemorrhage, Hb - Haemoglobin level, TP - Prothrombin time, BMI - Body Mass Index, IVF - In vitro Fertilization

*Protective factor.

However, the U-shaped curves of S-PPH risk observed both for maternal age and parity, should prompt caregiver's awareness to young nulliparae and elderly grand multiparae at the top of the risk of S-PPH, while women with one single of these factors could be considered at an intermediate risk. Interestingly, these U-shaped curves are coherent with those observed in several other perinatal outcomes, such as preterm birth and small-for-gestational age for maternal age, but also with all-cause mortality later in life for parity.³⁴

It is recognised that severely obese women with a pre-pregnancy BMI> 35 kg/m² face multiple perinatal risks.³⁵ Briley et al. have confirmed the existence of a positive association between maternal weight and S-PPH in a large prospective cohort.¹⁷ The evidence of a biological gradient between an increasing BMI and a higher risk of S-PPH likely supports causality. Actually, the finding suggest that maternal obesity has a modest effect on haemorrhage risk: the direction of the association may differ by delivery mode.³⁶

The role of ethnicity in S-PPH is less clear and may differ according to both socio-environmental context and genetic factors. Briley et al. have suggested that Black African women were more likely to have PPH.¹⁷ In other studies, Southeast Asian¹⁵ and Hispanic²⁰ women were the more at-risk of S-PPH, while Middle Eastern women seemed protected.¹⁵ Importantly, these ethnic groups at-risk have been confirmed recently in a large hospital-based study conducted in the US, in comparison to Non-Hispanic White, the lower-risk group, independently of confounding factors, including insurance status.³⁷ Interestingly, among seven can-

didate genes, promoter polymorphism of the tissue factor gene (F3-603A>G) showed a significant association with PPH after adjustment for known risk factors, fuelling the idea of a genetic background that supports role of ethnicity in S-PPH.³⁸ However, this hypothesis is challenged by another observation in low-income American women of increased risks of PPH with antidepressants uptake, independently of numerous confounders including race.³⁹

During the last decade, the growing interest in reviews of clinical practices and the commitment to identifying sub-optimal care has led to investigate the factors related to the management of PPH, both collectively and individually.

At maternity level, despite the inconclusive Pithagore-6 cluster RCT,²¹ community-based multifaceted interventions, aimed at improving the translation into clinical practices of the guidelines for PPH management, have gained attention in recent years and even proved effectiveness in low-middle income countries.⁴⁰

At individual level, oxytocin infusion is mandatory for the prevention of third-stage labour and postpartum bleeding risks. In the presence of PPH, re-administration of oxytocin should be prompt, as it was shown ineffective when performed more than 20 min after onset of PPH to avoid progression towards S-PPH.²² In addition, caution should be the rule as treatment with oxytocin was associated with a harmful dose-response in a population-based nested case-control study (i.e., the higher the dose, the more severe the bleeding), which emphasises the need for more evidence-based indications and the minimal useful regimens.⁴¹
Epidural analgesia was found protective for the risk of S-PPH in two studies.²²,²⁴ This practice ensures comfort to parturient women and allows effective and rapid intervention in life-threatening obstetric emergencies. However, its benefits must be weighed against a potential decrease in uterine contractility, and hence against increased duration of labour, with expected difficulties in foetus expulsion.

We found four biological parameters, Troponin-I, haemoglobin, PT, and fibrinogen that seemed mere indicators of S-PPH as they are not clearly located on the causal pathway between exposure and disease. Among these, given that fibrinolysis may be important in S-PPH pathogenesis,²² only fibrinogen has paid attention so far, and multicenter trials testing the effectiveness of fibrinogen concentrates are currently underway.

Our systematic review has strengths and limitations. The attachment to the PRISMA statement throughout the different steps of this systematic review adds scientific rigour in the reporting of the results.

In the absence of consensual definition, we defined S-PPH as primary endpoint using the WHO definition. As a consequence, we excluded from our systematic review studies that used the former definition of S-PPH, such as Canadian and Italian studies.⁴²,⁴³

Our systematic review covers a wide range of geographic areas including North and South America,²⁰,²⁷,²⁸ Southern and Northern Europe,¹⁵⁻¹⁷,¹⁹,²¹⁻²⁵ West Africa²⁶ and Israel.¹⁸ It gathers a very large population, which provides external validity and ensures extrapolations.

In a global context in which S-PPH remains the leading cause of maternal mortality, we rigorously gauged factors associated with S-PPH and distinguished key established determinants, as well as associated factors (especially contextual factors) and indicators that warrant further studies. We highlight socio-environmental factors and propose new studies to specify the impact of emerging factors on PPH, to take into account the context in which the disease occurs, and organise emergency obstetric care distribution and accessibility. In the field of obstetrical care, in which practices move faster than the pace of new publications, we endorse the concept of “living” systematic reviews and encourage regular updates of the current knowledge on S-PPH determinants combining rigour with timeliness.⁴⁴

## ACKNOWLEDGEMENTS

This work results of an internship of Master degree in clinical epidemiology. Tatiana Stachetti thanks the team of the CIC1410 for its warm welcoming during her internship, as well as Prof Laetitia Huiart, Head of the CIC, for her supervision. The authors are indebted to Monsieur Jacques Gonthier, documentalist, to ease access to bibliography. Tatiana Stachetti also thanks Dr Marie Devred, gynaecologist-obstetrician, for her clinical expertise, guidance and proof-reading. Patrick Gérardin thanks Dr Philippe Guillermin, gynaecologist-obstetrician, for furthering clinical research on PPH within the CIC. They also thank the teachers of the Master at the Institute of Public Health, Epidemiology and Development (ISPED), Bordeaux, especially Prof Rachid Salmi, Prof Rodolphe Thiébaut and Dr Karen Leffondre, for their precious advices as well as their colleagues for dedicated care to women's health.

## FUNDING

None.

## COMPETING INTERESTS

The author completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf (available upon request from the corresponding author), and declare no conflicts of interest.

## CORRESPONDENCE TO:

Madame Tatiana Stachetti
INSERM CIC1410
Clinical Epidemiology, Pôle Anesthésie
Centre Hospitalier Universitaire (CHU) Réunion
BP 350, 97448 Saint Pierre Cedex
Réunion
tatiana.stachetti@chu-reunion.fr

Dr Patrick Gérardin
INSERM CIC1410
Clinical Epidemiology
CHU de la Réunion
Groupe Hospitalier Sud Réunion
BP 350, 97448 Saint Pierre Cedex
Réunion
patrick.gerardin@chu-reunion.fr

<figure><img src="image_3.png" /></figure>

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CCBY-4.0). View this license's legal deed at http://creativecommons.org/licenses/by/4.0 and legal code at http://creativecommons.org/licenses/by/4.0/legalcode for more information.
REFERENCES

1. WHO Recommendations for the Prevention and Treatment of Postpartum Haemorrhage. https://www.ncbi.nlm.nih.gov/pubmed/23586122

2. HPP_rapport.pdf - Haute Autorité Santé. Accessed June 7, 2018. https://www.has-sante.fr/portail/uploadd/docs/application/pdf/HPP_rapport.pdf

3. Royal College of Obstetricians and Gynaecologists. Postpartum hemorrhage: prevention and management. Postpartum Haemorrhage, Prevention and Management (Green-top Guideline No. 52). Published 2011. Accessed June 6, 2018. https://www.rcog.org.uk/en/guidelines-research-services/guidelines/gtg52/

4. Sentilhes L, Merlot B, Madar H, Sztark F, Brun S, Deneux-Tharaux C. Postpartum haemorrhage: prevention and treatment. Expert Rev Hematol. 2016;9(11):1043-1061. doi:10.1080/17474086.2016.1245135

5. Bonnet MP. Postpartum Hemorrhage : epidemiological profile and assessment of anesthesia and intensive care practices in France. Published online 2014. Accessed March 7, 2016. https://tel.archives-ouvertes.fr/tel-00978795

6. Tessier V, Pierre F, Collège National des Gynécologues et Obstétriciens Français, Agence Nationale d'Accréditation et d'Evaluation en Santé. Risk factors of postpartum hemorrhage during labor and clinical and pharmacological prevention. J Gynecol Obstet Biol Reprod (Paris). 2004;33(8 Suppl):4S29-24S56.

7. Goffinet F, Mercier F, Teyssier V, et al. Postpartum haemorrhage: recommendations for clinical practice by the CNGOF (December 2004). Gynécol Obstét Fertil. 2005;33(4):268-274. doi:10.1016/j.gyobfe.2005.03.016

8. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097. doi:10.1371/journal.pmed.1000097

9. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453-1457. doi:10.1016/s0140-6736(07)61602-x

10. Moher D, Hopewell S, Schulz KF, et al. CONSORT 2010 Explanation and elaboration: updated guidelines for reporting parallel group randomised trials. J Clin Epidemiol. 2010;63(8):e1-e37. doi:10.1016/j.jclinepi.2010.03.004

11. Cochrane Handbook for Systematic Reviews of Interventions. Accessed September 7, 2018. https://training.cochrane.org

12. Bouyer J, Hémon D, Cordier S, Derriennic F, Stücker I, Stengel B, et al. Librairie Lavoisier. Accessed June 6, 2018. https://www.lavoisier.fr/livre/medecine/epidemiologie/bouyer/descriptif-9782743011673

13. Hill AB. The environment and disease: Association or causation? Proc R Soc Med. 1965;58(5):295-300. doi:10.1177/003591576505800503

14. Fedak KM, Bernal A, Capshaw ZA, Gross S. Applying the Bradford Hill criteria in the 21st century: how data integration has changed causal inference in molecular epidemiology. Emerg Themes Epidemiol. 2015;12(1):14. doi:10.1186/s12982-015-0037-4

15. Al-Zirqi I, Vangen S, Forsen L, Stray-Pedersen B. Prevalence and risk factors of severe obstetric haemorrhage. BJOG. 2008;115(10):1265-1272. doi:10.1111/j.1471-0528.2008.01859.x

16. Nyfløt LT, Sandven I, Stray-Pedersen B, et al. Risk factors for severe postpartum hemorrhage: a case-control study. BMC Pregnancy Childbirth. 2017;17(1):17. doi:10.1186/s12884-016-1217-0

17. Briley A, Seed PT, Tydeman G, et al. Reporting errors, incidence and risk factors for postpartum haemorrhage and progression to severe PPH: a prospective observational study. BJOG. 2014;121(7):876-888. doi:10.1111/1471-0528.12588

18. Helman S, Drukker L, Fruchtman H, et al. Revisit of risk factors for major obstetric hemorrhage: insights from a large medical center. Arch Gynecol Obstet. 2015;292(4):819-828. doi:10.1007/s00404-015-3725-y

19. Karlsson O, Jeppsson A, Thornemo M, Lafrenz H, Rådström M, Hellgren M. Fibrinogen plasma concentration before delivery is not associated with postpartum haemorrhage: a prospective observational study. Br J Anaesth. 2015;115(1):99-104. doi:10.1093/bja/aev039
20. Paglia MJ, Grotegut CA, Johnson LNC, Thames B, James AH. Body mass index and severe postpartum hemorrhage. *Gynecol Obstet Invest.* 2012;73(1):70-74.
doi:10.1159/000329335

21. Deneux-Tharaux C, Dupont C, Colin C, Rabilloud M, Touzet S, Lansac J. Multifaceted intervention to decrease the rate of severe postpartum haemorrhage: the pithagore6 clster-randomised controlled trial. *J Matern Fetal Neonatal Med.* 2010;15(609):23-24. doi:10.1111/j.1471-0528.2010.02648.x

22. Driessen M, Bouvier-Colle MH, Dupont C, Khoshnood B, Rudigoz RC, Deneux-Tharaux C. Postpartum hemorrhage resulting from uterine atony after vaginal delivery: factors associated with severity. *Obstet Gynecol.* 2011;117(1):21-31. doi:10.1097/aog.0b013e318202c845

23. Gayat E, Resche-Rigon M, Morel O, et al. Predictive factors of advanced interventional procedures in a multicentre severe postpartum haemorrhage study. *Intensive Care Med.* 2011;37(11):1816-1825. doi:10.1007/s00134-011-2315-0

24. Dupont C, Rudigoz RC, Cortet M, et al. Frequency, causes and risk factors of postpartum haemorrhage: a population-based study in 106 French maternity units. *J Gynecol Obstet Biol Reprod (Paris).* 2014;43(3):244-253. doi:10.1016/j.jgyn.2013.05.003

25. Marocchini M, Lauféron J, Quantin C, Sagot P. Postpartum hemorrhage with transfusion: Trends, near misses, risk factors and management at the scale of a perinatal network. *J Gynecol Obstet Hum Reprod.* 2017;46(5):455-460. doi:10.1016/j.jogoh.2017.03.011

26. Tort J, Traoré M, Hounkpatin B, Bodin C, Rozenberg P, Dumont A. Initial management of postpartum hemorrhage: A cohort study in Benin and Mali. *Int J Gynaecol Obstet.* 2016;135(S1):S84-S88. doi:10.1016/j.ijgo.2016.08.016

27. Kramer MS, Berg C, Abenhaim H, et al. Incidence, risk factors, and temporal trends in severe postpartum hemorrhage. *Am J Obstet Gynecol.* 2013;209(5):449.e1-7. doi:10.1016/j.ajog.2013.07.007

28. Sosa CG, Althabe F, Belizán JM, Buekens P. Risk factors for postpartum hemorrhage in vaginal deliveries in a Latin-American population. *Obstet Gynecol.* 2009;113(6):1313-1319. doi:10.1097/aog.0b013e3181a66b05

29. Bonnet MP, Benhamou D. Management of postpartum haemorrhage. *F1000Res.* 2016;5:1514. doi:10.12688/f1000research.7836.1

30. Gülmezoglu AM, Villar J, Ngoc NTN, et al. WHO multicentre randomised trial of misoprostol in the management of the third stage of labour. *Lancet.* 2001;358(9283):689-695. doi:10.1016/s0140-6736(01)05835-4

31. Atukunda EC, Siedner MJ, Obua C, Mugyenyi GR, Twagirumukiza M, Agaba AG. Sublingual misoprostol versus intramuscular oxytocin for prevention of postpartum hemorrhage in Uganda: A double-blind randomized non-inferiority trial. *PLoS Med.* 2014;11(11):e1001752. doi:10.1371/journal.pmed.1001752

32. Poeschmann RP, Doesburg WH, Eskes TKAB. A randomized comparison of oxytocin, sulprostone and placebo in the management of the third stage of labour. *Br J Obstet Gynaecol.* 1991;98(6):528-530. doi:10.1111/j.1471-0528.1991.tb10364.x

33. WOMAN Trial Collaborators. Effect of early tranexamic acid administration on mortality, hysterectomy, and other morbidities in women with post-partum haemorrhage (WOMAN): an international, randomised, double-blind, placebo-controlled trial. *Lancet.* 2017;389:2105-2116. doi:10.1016/S0140-6736(17)30638-428456509

34. Dior UP, Hochner H, Friedlander Y, et al. Association between number of children and mortality of mothers: results of a 37-year follow-up study. *Ann Epidemiol.* 2013;23(1):13-18. doi:10.1016/j.annepidem.2012.10.005

35. Liu L, Hong Z, Zhang L. Associations of prepregnancy body mass index and gestational weight gain with pregnancy outcomes in nulliparous women delivering single live babies. *Sci Rep.* 2015;5(1):12863. doi:10.1038/srep12863

36. Butwick AJ, Abreo A, Bateman BT, et al. Effect of Maternal Body Mass Index on Postpartum Hemorrhage. *Anesthesiology.* 2018;128(4):774-783. doi:10.1097/aln.00000000000002082

37. Grobman WA, Bailit JL, Rice MM, et al. Racial and ethnic disparities in maternal morbidity and obstetric care. *Obstet Gynecol.* 2015;125(6):1460-1467. doi:10.1097/aog.0000000000000735

38. Biguzzi E, Franchi F, Acaia B, et al. Genetic background and risk of postpartum haemorrhage: results from an Italian cohort of 3219 women. *Haemophilia.* 2014;20(6):e377-e383. doi:10.1111/hae.12514

39. Palmsten K, Hernandez-Diaz S, Huybrechts KF, et al. Use of antidepressants near delivery and risk of postpartum hemorrhage: cohort study of low income women in the United States. *BMJ.* 2013;347(aug212):f4877. doi:10.1136/bmj.f4877
40. Liabsuetrakul T, Palanukunwong K, Chinduereh A, Oumudee N. Evaluation of a multifaceted postpartum hemorrhage-management intervention in community hospitals in Southern Thailand. *Int J Gynecol Obstet*. 2017;139(1):39-44. doi:10.1002/ijgo.12253

41. Belghiti J, Kayem G, Dupont C, Rudigoz RC, Bouvier-Colle MH, Deneux-Tharaux C. Oxytocin during labour and risk of severe postpartum haemorrhage: a population-based, cohort-nested case-control study. *BMJ Open*. 2011;1(2):e000514. doi:10.1136/bmjopen-2011-000514

42. Mehrabadi A, Liu S, Bartholomew S, et al. Temporal trends in postpartum hemorrhage and severe postpartum hemorrhage in Canada from 2003 to 2010. *J Obstet Gynaecol Can*. 2014;36(1):21-33. doi:10.1016/s1701-2163(15)30680-0

43. Biguzzi E, Franchi F, Ambrogi F, et al. Risk factors for postpartum hemorrhage in a cohort of 6011 Italian women. *Thromb Res*. 2012;129(4):e1-e7. doi:10.1016/j.thromres.2011.09.010

44. Elliott JH, Turner T, Clavisi O, et al. Living systematic reviews: an emerging opportunity to narrow the evidence-practice gap. *PLoS Med*. 2014;11(2):e1001603. doi:10.1371/journal.pmed.1001603