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  • Research article
  • Open Access
  • Open Peer Review

Applicability of the WHO maternal near miss tool in sub-Saharan Africa: a systematic review

BMC Pregnancy and Childbirth201919:79

https://doi.org/10.1186/s12884-019-2225-7

  • Received: 25 September 2018
  • Accepted: 19 February 2019
  • Published:
Open Peer Review reports

Abstract

Background

Applicability of the World Health Organization (WHO) maternal near miss criteria in low-income settings is not systematically addressed in the literature. The objective of this review was to determine the applicability of the WHO maternal near miss tool in sub-Saharan Africa.

Methods

We searched PubMed, Embase, Popline, CINAHL, AJOL, and Google scholar using key words for maternal near miss and sub-Saharan Africa. Studies which applied the WHO maternal near miss criteria, containing clear definitions, and published between January 1st, 2009 and December 31st, 2017 were included. Two authors independently extracted data. Quantitative analysis and narrative synthesis were conducted, and medians with interquartile range (IQR) were calculated for summarizing the findings. Methodological quality of the studies was assessed using the Estabrook’s quality assessment and validity tool.

Results

Fifteen studies from nine countries comprising 227,077 participants were included. Median maternal near miss ratio was 24.2 (IQR: 12.4–35.8) per 1000 live births ranging from 4.4 in a population-based study in South Africa to 198 in a rural private hospital in Nigeria. Eight studies reported challenges in implementing the WHO maternal near miss tool, especially related to the threshold for blood transfusion, and availability of several laboratory-based criteria. In three studies, local adaptations were made.

Conclusion

This review showed that the WHO maternal near miss tool is not uniformly applied in sub-Saharan Africa. Therefore, a common adaptation for the region is required to increase its applicability.

Keywords

  • Systematic review
  • Severe acute maternal morbidity
  • Maternal near miss
  • Severe maternal outcomes
  • Sub-Saharan Africa

Background

With the decline of maternal deaths, studying maternal near misses (MNM) has been used as a proxy to measure quality of obstetric care [1, 2]. MNM refers to a very ill pregnant or delivered woman who nearly died but survived a complication during pregnancy, childbirth or within 42 days of termination of pregnancy [3]. Studying MNM has additional advantages to studying maternal deaths since it occurs more often, shares similar characteristics with deaths and is less ‘threatening’ to report by health providers and managers, possibly reducing underreporting [1, 4, 5]. In addition, audit of MNM brings the possibility to include opinions and perceptions of the women themselves, who may be interviewed after the event [6, 7].

A WHO maternal morbidity-working group developed MNM criteria in 2009 mainly focusing on presence of organ dysfunction [3]. The WHO near-miss approach was published in 2011 to serve as a manual for conducting MNM studies [6]. The manual provides guidelines to implement MNM studies (including definition of terms and expected results), calculations of MNM indicators, a data collection tool, and dummy tables, as well as guidance for interpretation. The MNM identification criteria consist of 25 parameters grouped into clinical, laboratory, and management-based criteria mainly focusing on presence of organ dysfunction—cardiac, respiratory, renal, coagulation/ hematological, hepatic, neurologic, and uterine dysfunctions (Table 1). Although the WHO MNM tool has been widely used, including in low-income settings, the tool turned out to be rather difficult to apply because of limited applicability especially the laboratory- and management-based criteria in low-income settings [810]. Therefore, several authors suggested local adaptations [9, 11], noted the need for practical MNM criteria for use in low-resource settings [8].
Table 1

World health organization maternal near miss criteria [3]

Clinical criteria

 Acute cyanosis

Loss of consciousness lasting > 12 h

 Gasping

Loss of consciousness and absence of pulse/heart beat

 Respiratory rate > 40 or < 6/min

Stroke

 Shock

Uncontrollable fit/total paralysis

 Oliguria non-responsive to fluids or diuretics

Jaundice in the presence of pre-eclampsia

 Clotting failure

 

Laboratory-based criteria

 Oxygen saturation < 90% for > 60 min

pH < 7.1

 PaO2/FiO2 < 200 mmHg

Lactate > 5

 Creatinine > 300 mmol/l or > 3.5 mg/dl

Acute thrombocytopenia (< 50,000 platelets)

 Bilirubin > 100 mmol/l or > 6.0 mg/dl

Loss of consciousness and the presence of glucose and ketoacids in urine

Management-based criteria

 Use of continuous vasoactive drugs

Intubation and ventilation for > 60 min not related to anesthesia

 Hysterectomy following infection or hemorrhage

Dialysis for acute renal failure

 Transfusion of u5 units red cell transfusion

Cardio-pulmonary resuscitation (CPR)

Systematic reviews have indicated that the use of different sets of criteria was one of the major limitations in estimating the burden of MNM, hampering comparisons between settings and countries [1214]. Despite WHO’s recommendation to use a uniform set of clinical, laboratory-, and management- based criteria for MNM identification [3], classifications based on only disease-based criteria are still being applied in several studies [15]. Any recommendations to apply either the WHO MNM criteria or resorting to adaptations for low-resource settings should be based on knowledge of performance of available criteria and pay attention to challenges that may occur during their implementation. Aim of this review was to assess applicability and challenges related to use of the WHO MNM tool in sub-Saharan Africa.

Methods

The review was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guideline [16]. The review protocol was registered in PROSPERO (CRD42015023883). PubMed, Embase, Popline, CINHAL, and AJOL databases were searched using key terms developed in consultation with a medical information specialist librarian of the University Medical Centre Groningen. We used the key terms ‘near miss’, ‘severe acute maternal morbidity’, ‘severe maternal morbidity’ in combination with terms used to describe sub-Saharan African region (Additional file 1). Open grey sources and references of identified articles were also searched for additional publications. The search was updated on December 28, 2018.

All identified articles were exported to Refworks reference manager and duplicates removed. Two reviewers (AKT and TLT) independently screened titles and abstracts of the studies. All potentially relevant articles and articles that could not clearly be excluded on the basis of the abstract only were retained for full text review. Differences between assessors to include articles in full text review were resolved by a senior reviewer (JS). Abstract and full text screening were conducted online using Covidence (www.covidence.org) [17]. Studies were included in the review if conducted in sub-Saharan Africa; provided a clear definition of MNM and used the WHO MNM criteria (or adaptations); were published between January 1, 2009 and December 31, 2017; used defined denominators (live births or deliveries); and contained data on frequency of MNM. Also included were studies that contained qualitative data of relevance to assessing the use of the tool, in line with the objective of this review. Studies that did not apply the WHO MNM criteria or that provided no primary data i.e. conference abstracts, reviews, and case reports were excluded. Qualitative studies were excluded since their main focus is mainly on description of the MNM experience: quality of life, risk of complications after MNM, social or economic impacts or experience of women regarding their treatment or complications [1824]. The year 2009 was chosen as the initial year of inclusion, since this was the year of publication of the 2009 WHO MNM tool and 2017 was the most recent year at the time our search was conducted. AKT and TLT collected data on study design, study settings, data collection period, denominators, number of participants, MNM, maternal deaths, and qualitative data related to applicability or adaptation of the criteria. Data were extracted online using a systematic review data repository (srdr.ahrq.gov) platform [25]. Conflicts during data collection were resolved by discussion until unanimity was reached.

One author (AKT) assessed the methodological quality of all studies using Estabrook’s quality assessment and validity tool for cross sectional studies [26, 27]. Estabrook’s quality assessment and validity tool, developed based on the Cochrane collaboration guidelines, has been widely used for assessing methodological quality of cross-sectional studies [26, 27]. The tool contains a maximum of 16 points and comprises three core areas: sampling, measurement, and statistical analysis. Each item contains a one-point score (0 or 1) except two items (representativeness and matching) containing scores from 0 to 2. A final score for each study was derived using the scoring system developed by de Vet et al [28] by dividing the total score obtained by total points possible after subtracting total number of not applicable (16-not applicable), resulting in a final score between 0 and 1. Each study was then classified as weak (< 0.5), moderately-weak (0.51–0.65), moderately-strong (0.66–0.79), or strong (> 0.80).

Reported challenges related to the use of the WHO MNM tool and qualitative remarks about the applicability of the tool were synthesized using texts and tables. Medians with interquartile range were used to present MNM ratio, maternal mortality ratio (MMR) and mortality index (MI). We calculated MNM ratio (MNM cases per 1000 live births), MMR (maternal deaths per 100,000 live births) and mortality index (maternal deaths divided by the sum of maternal deaths and MNM). These MNM indicators are essential components of MNM studies and give an indication of the performance of the MNM tool and the quality of care in a particular context [6].

Results

General description of studies

A total of 710 citations were identified through our initial search. After removal of duplicates and screening of titles and abstracts, 82 articles were retained for full text review, of which 67 were excluded. Main reasons for exclusion were that the studies did not contain data on MNM (18), did not report any relevant data (16), did not apply the WHO MNM criteria (12) or were duplicate publications from the same database (8) (Fig. 1).
Fig. 1
Fig. 1

PRISMA flow chart of the overall phases of the systematic review [16]

Methodological quality of the remaining 15 studies is shown in Table 2. Matching in design and appropriate handling of missing data were not applied in all studies. Overall, four studies were rated as strong [2932], three as moderately-strong [3335] and eight as moderately-weak [11, 3642].
Table 2

Methodological Quality of included cross sectional studies

Author, year

Sample

Measurement

Statistical Analysis

Total Points

Score

Quality

 

Probabilistic sample used

Representative

Sample size appropriate for power

Sample drawn > 1 site

Matching design

Statistically adjusted

Response rate > 50%

DV measurement

DV reliability

DV validity

Appropriate tests used

p values reported

CI values reported

Missing data managed appropriately

   

Ayele, 2014

0

1

1

0

NA

0

1

1

1

1

1

0

0

NA

7/13

0.54

Mod weak

Litorp,2014

0

2

1

1

NA

1

1

1

1

1

1

0

1

NA

11/13

0.85

Strong

Nelissen, 2013

0

1

1

0

NA

0

1

1

1

1

1

1

0

NA

8/13

0.62

Mod weak

Oladapo, 2015

1

2

1

1

NA

0

1

1

1

1

1

1

0

NA

11/13

0.85

Strong

Rulisa, 2015

0

1

1

0

NA

0

1

1

1

1

1

0

0

NA

7/13

0.54

Mod weak

Soma-Pillay, 2015

0

2

1

1

NA

0

1

1

1

1

1

0

0

NA

9/13

0.69

Mod strong

Tunçalp, 2013

0

1

1

0

NA

0

1

1

1

1

1

0

0

NA

7/13

0.54

Mod weak

Herklots, 2017

0

1

1

0

NA

0

1

1

1

1

1

1

0

NA

8/13

0.62

Mod weak

Kiruja, 2017

0

1

1

0

NA

0

1

1

1

1

1

1

0

NA

8/13

0.62

Mod weak

Kalisa, 2016

0

1

1

0

NA

0

1

1

1

1

1

0

1

NA

8/13

0.62

Mod weak

Nakimuli, 2016

0

2

1

1

NA

0

1

1

1

1

1

1

1

NA

11/13

0.85

Strong

Liyew, 2017

0

2

1

1

NA

0

1

1

1

1

1

0

1

NA

10/13

0.77

Mod Strong

Sayinzoga, 2017

0

2

1

1

NA

0

1

1

1

1

1

1

1

NA

11/13

0.85

Mod Strong

Mbachu, 2017

0

1

1

0

NA

0

1

1

1

1

1

1

0

NA

8/13

0.62

Mod weak

Peprah, 2015

1

2

1

1

NA

0

1

1

1

1

1

1

1

NA

12/13

0.92

Strong

Total Points = 13 total points possible; DV = Dependent Variable; CI = Confidence Interval; Weak (≤0.50), Moderate-weak (0.51 to 0.65), Moderate-Strong (0.66 to 0.79), or Strong (≥0.80)

All studies were cross sectional in design, although sometimes reported as being prospective or retrospective cohort studies. The median MNM ratio was 24.2 per 1000 live births and ranged from 4.4 in a population-based study from South Africa to 198 per 1000 live births in a private rural referral hospital in Nigeria. For each maternal death, 6.2 MNM cases were reported ranging from 1.3 in Zanzibar to 15.4 in Rwanda (IQR 2.6–6.8). Mortality index ranged from 6% in Rwanda to 43% in Zanzibar with a median of 14 (IQR 12.9–27.7). The maternal mortality ratio ranged from 71 in South Africa to 2875 per 100,000 live births in Rwanda (Table 3).
Table 3

Characteristics of included studies (n = 15)

Author, year

Country

Study setting

# Sample

# MNM

# MD

MNMr

MMR

MNM:MD

MI(%)

Ayele, 2014

Ethiopia

District hospital

8509

206

23

24.2

270

9

10

Herklots, 2017

Zanzibar

Tertiary

4125

37

28

9*

679

1.3

43

Kalisa, 2016

Rwanda

Rural referral

3994

86

13

21.5

326

6.6

13.1

Kiruja, 2017

Somaliland

Referral

1355

120

18

88.6

1328

6.7

13

Litorp, 2014

Tanzania

tertiary & regional

13,121

467

77

35.6

587

6.1

13.9

Liyew, 2017

Ethiopia

Tertiary and secondary

29,697

238

8

Mbachu, 2017

Nigeria

Private referral

262

52

5

198.5

1908

10.4

8.8

Nakimuli, 2016

Uganda

Tertiary and regional

25,840

695

130

26.9

503

5.3

15.8

Nelissen, 2013

Tanzania

District hospital

9136

216

32

23.6

350

6.8

12.9

Oladapo, 2015

Nigeria

tertiary (nationwide)

91,724

1451

998

15.8

1088

1.5

40.8

Peprah, 2015

Ghana

Tertiary and reg

2178

15

7

6.9

321

2.1

31.8

Rulisa, 2015

Rwanda

tertiary

1739

142

50

81.7

2875

2.8

26

Sayinzoga, 2017

Rwanda

District hospitals

5577

201

13

36

233

15.4

6

Soma-Pillay, 2015

South Africa

population based

26,614

117

19

4.4

71

6.2

14.0

Tunçalp, 2013

Ghana

Tertiary

3206

94

37

29.3

1154

2.5

28.2

Median (IQR)

  

5577 (2692, 19,480.5)

142 (90,227)

25.5 (14.3,46.8)

24.2 (12.4,35.8)

545 (322,1138)

6.2 (2.6,6.8)

14 (12.9,27.7)

Total

  

227,077

4137

1450

6.4

639

2.9

26

IQR Interquartile Range, MNM maternal near miss, MD maternal death, MNMr maternal near miss ratio, MI mortality index

Applicability of the WHO MNM criteria

Eight studies discussed challenges related to using the WHO MNM criteria [11, 29, 34, 3640]. A thorough discussion and adaptation was done in one study (Haydom near miss criteria) [37], and another study utilized these adapted criteria [34]. The Haydom criteria adapted the WHO MNM tool to a local hospital in Tanzania, Haydom Hospital. These criteria comprised of all the WHO clinical-based (n = 11), two out of eight laboratory-based criteria, and three out of six management-based criteria of the 2009 WHO MNM criteria. Additional criteria (admission to intensive care unit, eclampsia, sepsis/severe systemic infection, and uterine rupture), which were not part of the 2009 WHO criteria, were added and the threshold for the number of units of blood transfusion was lowered from five or more units of blood to one or more [9]. A study by Kalisa et al. reported another adaptation applied in Rwanda (the Ruhengeri Hospital criteria). In this adaptation they included all the WHO clinical criteria (n = 11), four out of eight laboratory-based criteria, and five out of six management-based criteria from the 2009 WHO MNM criteria. Additionally, admission to an intensive care unit, eclampsia, sepsis/severe systemic infection, and uterine rupture [11] were included. The remaining studies reported limitations with the use of some management-based (dialysis for acute renal failure, use of continuous vaso-active drugs) and a majority of the laboratory- based criteria (measuring pH, lactate, bilirubin, creatinine, arterial blood gas PaO2/FiO2) [29, 36, 3840] (Table 4). Seven studies did not describe limitations with regard to the use of the WHO MNM tool [3033, 35, 41, 42]. In general, suggested changes in near miss inclusion criteria included lowering the threshold of units of blood given for transfusion from five or more units to one or more [34, 37], four or more [32] or five or more units ordered but not transfused due to shortage [40]. Criteria that were suggested to be included were additional clinical criteria (eclampsia, uterine rupture, and sepsis or severe systemic infections) [11, 34, 37, 38]; and including admission to an intensive care unit as additional management-based criterion [11, 32, 34, 37, 38]. One study compared the WHO criteria with the Sequential Organ Failure Assessment (SOFA) score [43] and reported better utility of the WHO criteria in obstetrics [32]. SOFA is used to quantify organ dysfunction and predict prognosis of severely ill patients [44, 45]. Utility of SOFA score in women with MNM or admitted to intensive care unit was previously validated [43, 46, 47]. Details of reported limitations and suggested adaptations are summarized in Table 4.
Table 4

Applicability of the WHO MNM criteria and suggested adaptations

Study

Hospital type

Reported challenges or removed criteria

Adaptations made

Ayele, 2014, Ethiopia

District

Not all WHO near miss criteria were available

Reported as possible limitation only. No adaptation made or suggested

Litorp, 2014, Tanzania

Tertiary and secondary

Due to limited resources, some laboratory- and management-based criteria were not applicable (not specified)

None. But it was reported as a limitation for possible under-estimation especially at the regional hospital

Nelissen, 2013, Tanzania

District

Removed: PaO2/FiO2 < 200 mmHg; creatinine > 300 μmol/l or > 3.5 mg/dl; bilirubin > 100 μmol.l or > 6.0 mg/dl; pH < 7.1; lactate > 5 mEq/ml; loss of consciousness and ketoacids in urine; use of continuous vasoactive drugs; dialysis for acute renal failure

Included additionally eclampsia, uterine rupture, sepsis or severe systemic infection, admission to intensive care unit, reducing threshold of blood for transfusion from > 5 units to > 1 (Haydom Hospital criteria)

Rulisa, 2015, Rwanda

Tertiary

In most cases, it was impossible to meet the full WHO criteria because most of the laboratory tests used to define those events, were not performed at the hospital

Patients were include if they had severe maternal complications (not specified) or admitted to intensive care unit

Tuncalp 2013, Ghana

Tertiary

Although laboratory testing was available, often the markers were not requested on time or at all owing to the urgency of the management of these women.

No adaptation was made

Herklots 2017, Zanzibar

Tertiary

Some of the markers were not applicable to the setting especially laboratory criteria

Lowered threshold of blood transfusion from > 5 units to > 5 units transfused or ordered but not entirely given

Kalisa, 2016, Rwanda

District

Reported as not available: PaO2 /FiO2 < 200 mmHg; pH < 7.1; lactate > 5 mEq/ml; ketoacids in urine; dialysis for acute renal failure

Additionally included: eclampsia, uterine rupture, sepsis or severe systemic infection; admission to intensive care unit (Ruhengeri hospital criteria)

Sayinzoga, 2017, Rwanda

District

The WHO criteria adapted in the Haydom study was used

Used Haydom Hospital criteria

Discussion

This review was conducted to assess the applicability of the WHO MNM criteria and related methodological challenges in sub-Saharan Africa. Eight of the 15 studies indicated presence of challenges in using the WHO MNM criteria: especially related to laboratory- and management-based criteria. Such limitations resulted in adapting and using ‘locally applicable’ criteria [9, 11, 34] by some while others are opting to use the original criteria [29].

Using the WHO MNM criteria without adaptation is preferred by those who aimed for comparing findings with other studies [29], but fear of underestimation lead others to adapt to broader criteria, hampering comparisons but possibly leading to more genuine estimation of MNM prevalence [9]. Unless standard criteria for using the WHO MNM approach in low-resource settings is developed [48], adaptations by some, while others opt not to adapt, will result in confusion on the outcome of studies and their comparability. Although adaptation to a local context is required for improving obstetric care and for producing genuine MNM estimates [6], several adaptations may further complicate MNM studies. On the other hand, one of the main reasons for using the standard WHO criteria—comparability—should consider issues of under-reporting and feasibility especially in low-income settings [8]. Therefore, there should be MNM criteria which can be uniformly applied and at the same time applicable to create a balanced trade-off [49].

Compared to studies using disease-based criteria, a high mortality index was reported in our review. This shows that the WHO criteria only picked the most severe MNM cases. For example, the studies from Zanzibar (mortality index, 43%) and Nigeria (mortality index, 40.8%) reported only 1.3 and 1.5 near misses per maternal death respectively [30, 40]. Other studies conducted during the same period using disease-specific criteria, reported much higher MNM ratios and lower mortality indices [5052]. Although most MNM could be identified by clinical or management-based criteria [39], the WHO MNM criteria failed to identify nearly two-thirds of sustained severe acute maternal morbidity and one-third of maternal deaths even in high-income settings [53].

Some notable challenges should be considered in using the WHO MNM criteria in low-income settings: lack of blood for transfusion [5456] and absence of infrastructure and ability to make an appropriate diagnosis [57, 58]. Transfusion of five or more units of blood, and diagnosis of MNM based on the majority of the WHO laboratory-based criteria are unlikely in most sub-Saharan Africa settings. As the ultimate goal of studying MNM is to improve quality of obstetric care [2, 6], this aim should not be compromised by the need to compare findings across studies.

To our knowledge, this is the first review to systematically synthesize the applicability of the WHO MNM criteria in sub-Saharan Africa. The use of WHO MNM criteria in sub-Saharan Africa is compounded by the need for having uniform criteria and limitations to apply some parameters related to laboratory- and management- based criteria. These considerations are affecting the use of the original criteria or making local adaptations based on the researchers’ judgement [29]—which may result in several different adaptations.

Locally adapted criteria may enable researchers to get a better estimate of the prevalence of MNM [59], but such findings could not be compared with other studies which used different criteria [12]. Similarly, using the WHO criteria is essential for having comparable findings across studies. But this may underestimate the true burden of cases as it only picks the most severe cases [53, 60].

Conclusion

This review showed that the WHO MNM tool is not uniformly applied in sub-Saharan Africa. In eight studies challenges for using the WHO MNM tool were reported. Limited supply of blood and lack of infrastructure for performing some of the WHO laboratory-based criteria were the major challenges reported. There is a need to have a common tool for use in sub-Saharan Africa to avoid different adaptations because of the limited applicability of the WHO MNM tool.

Abbreviations

IQR: 

Interquartile range

MD: 

Maternal Death

MI: 

Mortality Index

MMR: 

Maternal Mortality Ratio

MNM: 

Maternal Near Miss

SRDR: 

Systematic Review Data Repository

WHO: 

World Health Organization

Declarations

Acknowledgements

We want to thank University Medical Centre Groningen librarian who helped us in the development of the search strategy. We also want to thank the Dutch organization for internationalization in education for funding this study.

Funding

AKT received a stipend from the Dutch organization for internationalization in education (Nuffic) in the form of a PhD study. The funders have no role in the design, data collection, analysis or the decision to publish.

Availability of data and materials

All data underlying the findings in the study are included in the manuscript. Additional data are available from the corresponding author on reasonable request.

Authors’ contributions

AKT, SS, JZ, TvdA, JvR and JS conceived the review. AKT and TLT screened articles and extracted data. AKT drafted the manuscript, which was revised by TLT, JZ, SS, JvR, TvdA, and JS. All authors approved the final version for submission.

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Competing interests

JvR is section editor while TvDA and JS are associate editors in BMC Pregnancy and Childbirth. All other authors have no competing interests.

Publisher’s Note

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Authors’ Affiliations

(1)
School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Dire Dawa, Ethiopia
(2)
Department of Obstetrics and Gynecology, University Medical Centre Groningen, University of Groningen, Hanzeplein 1, 9700 RB, P.O.B, 30 001 Groningen, The Netherlands
(3)
Department of Obstetrics and Gynecology, Leeuwarden Medical Center, Leeuwarden, The Netherlands
(4)
Department of Obstetrics and Gynaecology, Leiden University Medical Center, Leiden, the Netherlands
(5)
Athena Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
(6)
Department of Obstetrics and Gynecology, Deventer Ziekenhuis, Deventer, The Netherlands
(7)
Department of Health Sciences, Global Health, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands

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