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Towards a consensus definition of maternal sepsis: results of a systematic review and expert consultation
review-article
Author(s):
Mercedes Bonet
1
,
,
Vicky Nogueira Pileggi
2 ,
Marcus J Rijken
3 ,
Arri Coomarasamy
4
,
5 ,
David Lissauer
6 ,
João Paulo Souza
1 ,
Ahmet Metin Gülmezoglu
1
Publication date (Electronic):
30 May 2017
Journal:
Reproductive Health
Publisher:
BioMed Central
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Abstract
Background
There is a need for a clear and actionable definition of maternal sepsis, in order to better assess the burden of this condition, trigger timely and effective treatment and allow comparisons across facilities and countries. The objective of this study was to review maternal sepsis definitions and identification criteria and to report on the results of an expert consultation to develop a new international definition of maternal sepsis.
Methods
All original and review articles and WHO documents, as well as clinical guidelines providing definitions and/or identification criteria of maternal sepsis were included. A multidisciplinary international panel of experts was surveyed through an online consultation in March-April 2016 on their opinion on the existing sepsis definitions, including new definition of sepsis proposed for the adult population (2016 Third International Consensus Definitions for Sepsis and Septic Shock) and importance of different criteria for identification of maternal sepsis. The definition was agreed using an iterative process in an expert face-to-face consensus development meeting convened by WHO and Jhpiego.
Results
Standardizing the definition of maternal sepsis and aligning it with the current understanding of sepsis in the adult population was considered a mandatory step to improve the assessment of the burden of maternal sepsis by the expert panel. The literature review and expert consultation resulted in a new WHO consensus definition “Maternal sepsis is a life-threatening condition defined as organ dysfunction resulting from infection during pregnancy, child-birth, post-abortion, or post-partum period”. Plans are in progress to validate the new WHO definition of maternal sepsis in a large international population.
Conclusion
The operationalization of the new maternal sepsis definition requires generation of a set of practical criteria to identify women with sepsis. These criteria should enable clinicians to focus on the timely initiation of actionable elements of care (administration of antimicrobials and fluids, support of vital organ functions, and referral) and improve maternal outcomes.
Related collections
Most cited references33
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Maternal near miss--towards a standard tool for monitoring quality of maternal health care.
Lale Say, João Souza, Robert C Pattinson … (2009)
Maternal mortality is still among the worst performing health indicators in resource-poor settings. For deaths occurring in health facilities, it is crucial to understand the processes of obstetric care in order to address any identified weakness or failure within the system and take corrective action. However, although a significant public health problem, maternal deaths are rare in absolute numbers especially within an individual facility. Studying cases of women who nearly died but survived a complication during pregnancy, childbirth or postpartum (maternal near miss or severe acute maternal morbidity) are increasingly recognized as useful means to examine quality of obstetric care. Nevertheless, routine implementation and wider application of this concept in reviewing clinical care has been limited due to the lack of a standard definition and uniform case-identification criteria. WHO has initiated a process in agreeing on a definition and developing a uniform set of identification criteria for maternal near miss cases aiming to facilitate the reviews of these cases for monitoring and improving quality of obstetric care. A list of identification criteria was proposed together with one single definition. This article presents the proposed definition and the identification criteria of maternal near miss cases. It also suggests procedures to make maternal near miss audits operational in monitoring/evaluating quality of obstetric care. The practical implementation of maternal near miss concept should provide an important contribution to improving quality of obstetric care to reduce maternal deaths and improve maternal health.
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Risk of Early-Onset Neonatal Infection with Maternal Infection or Colonization: A Global Systematic Review and Meta-Analysis
Grace Chan, Anne Lee, Abdullah Baqui … (2013)
Introduction In the last two decades, mortality among children under 5 years old has declined significantly; however, neonatal mortality has not declined as quickly. An estimated 3.1–3.3 million newborns die each year, accounting for 40.3% of under-five mortality [1],[2]. The neonatal mortality rate, the number of newborns dying in the first 28 d of life per 1,000 live births, is estimated globally to be approximately 23.9. In low-middle income African, Eastern Mediterranean, and southeast Asian countries, the neonatal mortality rate ranges from 30.7–35.9, which is substantially greater than in high-income countries where it is estimated to be 3.6 [2]. Neonatal infections, defined as bacteremia/sepsis, pneumonia, and meningitis, cause approximately 23.4% of neonatal deaths worldwide each year [1]. Approximately half of the deaths caused by sepsis or pneumonia occur during the first week of life [3]. Over the last decade, there has been no measurable reduction in early neonatal mortality [4]. To develop research priorities and develop strategies for prevention, the mechanisms by which newborns are acquiring infection need to be better understood. The shared relationship between mothers and their newborns leads to common risk factors and etiologies of infectious diseases. Newborns may acquire early-onset neonatal infection “vertically” (mother-to-newborn during birth) from endogenous bacteria in the mother's reproductive tract (hereafter referred to as maternal colonization), which may or may not cause disease in the mother but can cause disease in the newborn. These bacteria, often common colonizers in the maternal vaginal tract, may be transmitted to newborns during the delivery process when newborns come into direct contact with bacterial flora. Ascending infections from the mother to the fetus may occur before or during labour when colonized bacteria from the maternal perineum spread through the vaginal canal, amniotic sac, and into the once-sterile amniotic fluid [5],[6]. Amniotic fluid infection, or chorioamnionitis, and bacteremia are additional sources of bacterial transmission from the mother to fetus in utero. In resource-rich settings, interventions such as risk-based antibiotic prophylaxis during labour (based on microbiological screening or risk factors in pregnancy), early diagnosis of sepsis, and neonatal antibiotic treatment have been highly effective in reducing mortality from early-onset neonatal bacterial sepsis [7]. As a result, in regions with low neonatal mortality levels (less than 15 per 1,000 births), such as the Americas, Europe, and western Pacific, sepsis accounts for 9.1%–15.3% of neonatal deaths [1]. Most of these cases are related to nosocomial infections or prematurity. In contrast, in resource-poor settings where neonatal mortality levels are high (more than 27 per 1,000 births), sepsis accounts for 22.5%–27.2% of neonatal deaths [1]. Interventions such as risk-based prophylaxis are rare or absent, and consequently there is a disproportionately large number of neonatal deaths from sepsis in countries like India, Nigeria, the Democratic Republic of the Congo, Pakistan, and China [1]. Newborns in very high-mortality settings are twice as likely to die from infectious diseases as in low-mortality settings. Despite the heavy burden of disease in high-mortality settings, the risk factors and modes of transmission for neonatal infections have not been well studied in these settings [8]. Several reviews have evaluated the effect of antibiotics on maternal Group B streptococcus (GBS) colonization and maternal risk factors of infection on neonatal sepsis [9]–[11]. These reviews are limited to randomized controlled trials, predominantly represented high income settings, and focused on specific maternal factors (GBS colonization, prelabour rupture of membranes [PROM], preterm prelabour rupture of membranes [PPROM]). Antibiotics given to women with PROM reduced the risk of neonatal infection (relative risk [RR] = 0.67, 95% CI 0.52–0.85) [10]. Similarly, among women with PPROM, antibiotics reduced the risk of neonatal infection (RR = 0.61, CI = 0.48–0.77) [9]. The evidence for antibiotics given during labour to prevent GBS early-onset neonatal sepsis was inconclusive [11]. This systematic review and meta-analysis estimates the risk of early-onset neonatal infection among newborns of mothers with bacterial infection or colonization compared to newborns of mothers without infection or colonization. Methods Definitions and Classification Although laboratory-confirmed infections are considered the gold standard measure of infection, studies with biological samples would be limited in African and southeast Asian countries, causing an underestimate of the effect measure. Rather than restricting our review to studies with only lab-confirmed measures, we also included clinical signs, colonization, and risk factors for infection (maternal only) in order to best estimate the risk of neonatal infection. Including various measures of infection allows us to understand how different measures may affect the estimate. Following PRISMA guidelines (Text S1), we specified these definitions, our methods of analysis, and our inclusion criteria in a protocol a priori (Text S2). We defined our exposure, maternal infection, or colonization during labor, in three categories: (i) Maternal infection: Laboratory-confirmed bacterial infection (hereafter referred to as “lab” and including bacteremia, amnionitis, urinary tract infections, or chorioamnionitis; measured by positive cultures of blood, amniotic fluid, urine, or placental swab; positive PCR—amniotic fluid only; or histopathologically confirmed chorioamnionitis) or clinical signs of infection (hereafter referred to as “signs” and including intrapartum maternal fever, uterine tenderness, maternal tachycardia, malodorous vaginal discharge, elevated white cell count, elevated C-reactive protein, physician diagnosis of clinical chorioamnionitis using a combination of the above signs, or clinical infection undefined). (ii) Maternal colonization: Positive reproductive tract/genital bacterial cultures without signs or symptoms of infection. (iii) Risk factors for infection: PROM (ROM prior to onset of labour ≥37 wk gestation), PPROM (ROM prior to onset of labour 27 7 (8.4%) 2 (5.9%) 3 (13.6%) 1 (4.0%) 3 (21.4%) Income range High income (≥US$12,276) per capita 66 (79.5%) 29 (85.3%) 17 (77.3%) 17 (68.0%) 10 (78.6%) Upper middle income (US$3,976–US$12,275) 8 (9.6%) 1 (2.9%) 1 (4.6%) 7 (28.0%) — Lower middle income (US$1,006–US$3,975) 8 (9.6%) 4 (11.8%) 4 (18.2%) 1 (4.0%) 3 (21.4%) Low income (≤US$1,005) 1 (1.2%) — — — 1 (7.1%) Numbers provided are n (%) unless otherwise specified. IQR, interquartile range; RCT, randomized controlled trial. 10.1371/journal.pmed.1001502.t002 Table 2 Studies included in the systematic review and meta-analysis. Ref # Author Year Years Conducted Country Study Sample Size Study Type Setting Urban or Rural Timing of EOS Diagnosis Antibiotic Use Specialized Population WHO Regiona Neonatal Mortality Rate (per 1,000 Live Births) Income (USD) 96 Barcaite 2012 2006–2007 Lithuania 998 Cohort Health facility Urban ≤7 days Used All EUR 3 11,390 26 Chemsi 2012 2009–2011 Morocco 99 Case-control Health facility Urban >7 days Unknown All EMR 20 2,850 28 Emamghorashi 2012 2010 Iran 114 Case-control Health facility Urban ≤7 days Unknown All EMR 19 2,500 100 Huang 2012 2005 Taiwan 92 Cohort Health facility Urban ≤7 days Unknown All WPR 4 41,385 29 Kovo 2012 2007–2009 Israel 120 Case-control Health facility Urban ≤7 days Used All EUR 2 27,170 47 Lee 2012 2005–2010 Hong Kong 212 Cohort Health facility Urban ≤7 days Used All WPR 1 51,490 62 Tudela 2012 2000–2008 USA 143,384 Cohort Multi-center Urban ≤7 days Used All AMR 4 47,390 64 Wojkowska 2012 2009 Poland 910 Cohort Multi-center Urban >7 days Used All EUR 4 12,440 66 Kordek 2011 n/a Poland 286 Cohort Health facility Urban ≤7 days Used All EUR 4 12,440 75 Kunze 2011 Jan–Dec 2004 Germany 869 Cohort Health facility Urban ≤7 days Used All EUR 2 43,110 57 Puopolo 2011 1993–2007 USA 1,413 Nested case-control Multi-center Unknown ≤7 days Used All AMR 4 47,390 99 Bourgeois-Nicolaos 2010 Jan 2004–Dec 2004 France 1,139 Cohort Health facility Urban ≤7 days Unknown All EUR 2 42,390 56 Dutta 2010 n/a India 728 Cohort Health facility Urban ≤7 days Used Preterm SEAR 34 1,330 74 Faro 2010 Jan 2003–Dec 2004 USA 2,108 Cohort Multi-center Urban ≤7 days Used All AMR 4 47,390 48 Kasper 2010 June 2001 Austria 118 Cohort Health facility Urban ≤7 days Unknown Preterm EUR 2 47,060 95 Seoud 2010 Feb 2004–Sep 2004 Lebanon 779 Cohort Multi-center Urban >7 days Used All EMR 7 8,880 101 Tameliene 2010 2006–2007 Lithuania 970 Cohort Health facility Unknown ≤7 days Unknown All EUR 3 11,390 94 Elzbieta 2009 Jan 2008–Mar 2008 Poland 100 Cohort Health facility Unknown ≤7 days Used All EUR 4 12,440 98 Pinter 2009 Jun–Dec 2005 USA 317 Cohort Health facility Urban ≤7 days Unknown All AMR 4 47,390 31 Andrews 2008 Jul 2003–Jun 2006 USA 5,732 Cohort Health facility Urban ≤7 days Unknown All AMR 4 47,390 46 Goldenberg 2008 1996–2001 USA 351 Cohort Health facility Unknown ≤7 days Unknown Preterm AMR 4 47,390 73 Namavar Jahromi 2008 Apr–Sep 2003 Iran 1,197 Cohort Health facility Urban ≤7 days Used All EMR 19 2,500 93 Lijoi 2007 Nov 2003–Nov 2004 Italy 2,158 Cohort Health facility Urban ≤7 days Not used All EUR 2 35,150 21 Muthusami 2007 May 2006–Jul 2006 India 77 Cohort Health facility Urban ≤7 days Unknown All SEAR 34 1,330 17 Kalinka 2006 May 2001–Dec 2002 Poland 120 Cohort Health facility Urban ≤7 days Not used All EUR 4 12,440 65 Kordek 2006 n/a Poland 46 Cohort Health facility Urban ≤7 days Used Preterm or PROM EUR 4 12,440 19 Kunze 2006 Jan 2011–Dec 2002 Germany 1,438 Cohort Health facility Urban ≤7 days Used All EUR 2 43,110 92 Eren 2005 May 2000–Jan 2001 Turkey 500 Cohort Health facility Urban ≤7 days Unknown Other EUR 12 9,890 55 Ronnestad 2005 1999–2000 Norway 119,611 Cohort Multi-center Urban ≤7 days Used Preterm EUR 2 84,290 102 Kafetzis 2004 Jun 2000–Dec 2001 Greece 251 Cohort Health facility Urban ≤7 days Unknown All EUR 2 26,940 91 Tsolia 2003 Jan 2000–May 2000 Greece 1,014 Cohort Multi-center Urban ≤7 days Used All EUR 2 26,940 63 Dollner 2002 1999 Norway 221 Cohort Health facility Urban ≤7 days Used All EUR 2 84,290 90 El-Kersh 2002 Jan 1963–Jul 1965 Saudi Arabia 217 Cohort Health facility Urban ≤7 days Not used All EMR 12 16,720 30 Oddie 2002 Apr 1988–Mar 2000 UK 62,786 Case-control Multi-center Unknown ≤7 days Used All EUR 3 38,370 24 Vergani 2002 1991–1994 USA 32,630 Cohort Health facility Urban ≤7 days Not used All AMR 4 47,390 80 Volumenie 2001 Jan 1994–Sep 1996 France 5,374 Cohort Health facility Urban >7 days Used All EUR 2 42,390 78 Ma 2000 Dec 1997–Dec 1998 China 768 Cohort Health facility Urban ≤7 days Unknown All WPR 11 4,270 45 Yoon 2000 n/a South Korea 315 Cohort Health facility Urban ≤7 days Unknown Preterm WPR 2 17,890 27 Cukrowska 1999 n/a Czech Republic 148 Case-control Health facility Urban ≤7 days Used Preterm EUR 2 17,890 89 Hickman 1999 Jan 1994–Feb 1995 USA 546 Cohort Multi-center Urban ≤7 days Used All AMR 4 47,390 61 Mercer 1999 Jul 1997–Feb 1998 USA 8,474 Cohort Multi-center Urban ≤7 days Used All AMR 4 47,390 72 Piper 1999 Jan 1992–Jun 1994 USA 1,046 Cohort Health facility Urban >7 days Used All AMR 4 47,390 25 Bhutta 1997 Jan 1990–Dec 1993 Pakistan 38 Case-control Health facility Urban ≤7 days Unknown All EMR 42 1,050 79 Mercer 1997 Feb 1992–Jan 1995 USA 1,867 Cohort Multi-center Unknown ≤7 days Not used PPROM AMR 4 47,390 54 Papantoniou 1997 Feb 1993–Jun 1994 Greece 32 Cohort Health facility Urban >7 days Used PPROM EUR 2 26,940 88 Sensini 1997 Mar 1993–Sep 1995 Italy 2,300 Cohort Health facility Urban ≤7 days Unknown All EUR 2 35,150 77 Itakura 1996 Jul 1987–Dec 1992 Japan 1,280 Cohort Health facility Urban ≤7 days Unknown All WPR 1 41,850 97 Mitsuda 1996 Jul 1991–Jun 1992 Japan 466 Cohort Health facility Urban ≤7 days Unknown All WPR 1 41,850 71 Regan 1996 1984–1989 USA 13,646 Cohort Multi-center Urban >7 days Not used All AMR 4 47,390 43 Averbuch 1995 n/a Israel 90 Cohort Health facility Urban >7 days Unknown PPROM EUR 2 27,170 44 Matsuda 1995 Feb–Oct 1992 Japan 41 Cohort Health facility Urban >7 days Unknown Preterm WPR 1 41,850 60 Rosemond 1995 Jun 1989–Dec 1993 USA 224 Cohort Health facility Urban >7 days Used PPROM AMR 4 47,390 86 Ayata 1994 n/a Turkey 114 Cohort Health facility Urban ≤7 days Unknown All EUR 12 9,890 53 de Araujo 1994 1991 Brazil 223 Cohort Health facility Urban ≤7 days Used All AMR 12 9,390 42 Gauthier 1994 n/a USA 225 Cohort Health facility Urban >7 days Not used PPROM AMR 4 47,390 16 Pylipow 1994 Jan 1991–Sep 1992 USA 2,040 Cohort Health facility Urban ≤7 days Used All AMR 4 47,390 87 Suara 1994 May 1992–Feb 1993 Gambia 196 Cohort Health facility Unknown ≤7 days Unknown All AFR 32 7,740 52 Puchner 1993 n/a Austria 80 Cohort Unknown Unknown >7 days Not used All EUR 2 47,060 70 Burman 1992 n/a Sweden 4,559 Cohort Multi-center Unknown >7 days Not used All EUR 2 50,110 6 Ayengar 1991 n/a India 1,792 Cohort Health facility Urban ≤7 days Unknown All SEAR 34 1,330 51 Dudley 1991 Feb 1988–Jul 1990 Australia 81 Cohort Health facility Urban ≤7 days Used PPROM WPR 3 46,320 69 Towers 1990 Jan 1989–Jul 1989 USA 131 Cohort Health facility Urban >7 days Used Preterm or PROM AMR 4 47,390 85 Kollee 1989 Apr 1986–Jan 1987 Netherlands 632 Cohort Health facility Urban ≤7 days Unknown All EUR 3 49,050 20 Morales 1989 Jan 1 1986–Mar 1988 USA 212 Cohort Multi-center Urban >7 days Not used PPROM AMR 4 47,390 59 Newton 1989 Apr–Dec 1986 USA 2,908 Cohort Health facility Urban >7 days Used All AMR 4 47,390 23 Tuppurainen 1989 Dec 1983–Jan 1986 Finland 8,977 Cohort Health facility Urban ≤7 days Not used All EUR 2 47,720 18 Kishore 1987 n/a India 109 Cohort Health facility Urban ≤7 days Not used All SEAR 34 1,330 41 Feinstein 1986 Jul 1983–Apr 1985 USA 146 Cohort Health facility Urban >7 days Not used PROM AMR 4 47,390 84 Liang 1986 Sep 1983–Mar 1984 Hong Kong 168 Cohort Health facility Urban ≤7 days Not used All WPR 1 51,490 22 Persson 1986 Sep 1983–Oct 1984 Sweden 1,786 Nested case-control Health facility Urban ≤7 days Used All EUR 2 50,110 76 Bobitt 1985 n/a USA 937 Cohort Health facility Urban >7 days Used All AMR 4 47,390 40 Broekhuizen 1985 Jul 1981–Dec 1983 USA 53 Cohort Health facility Urban >7 days Unknown PPROM AMR 4 47,390 50 McGrady 1985 1980–1981 USA 1,342 Cohort Multi-center Mixed >7 days Unknown All AMR 4 47,390 83 Visconti 1985 Apr 1980–Jan 1983 Italy 1,516 Cohort Multi-center Urban >7 days Unknown All EUR 2 35,150 82 Weintraub 1983 n/a Israel 385 Cohort Health facility Urban ≤7 days Unknown All EUR 2 27,170 68 Christensen 1982 Nov 1979–Jun 1980 Sweden 300 Cohort Health facility Unknown ≤7 days Unknown All EUR 2 50,110 39 Pass 1982 Jul 1977–Jun 1980 USA 68 Cohort Multi-center Urban >7 days Used All AMR 4 47,390 58 Wilson 1982 Sep 1978–Aug 1980 USA 143 Cohort Health facility Urban ≤7 days Used PPROM AMR 4 47,390 67 Boyer 1981 Sep 1977–Apr 1979 USA 924 Cohort Health facility Urban ≤7 days Not used Preterm or PROM AMR 4 47,390 81 Merenstein 1980 n/a USA 1,815 Cohort Unknown Unknown ≤7 days Not used All AMR 4 47,390 103 Tafari 1979 1975–1978 Ethiopia 1,351 Cohort Health facility Urban ≤7 days Unknown All AFR 36 390 38 Bobitt 1977 Oct 1974–May 1975 USA 12 Cohort Health facility Urban >7 days Unknown Preterm or PROM AMR 4 47,390 49 Elder 1971 n/a USA 9,156 Cohort Health facility Urban >7 days Not used All AMR 4 47,390 a WHO regions: AFR: Africa; AMR: Americas; EMR: Eastern Mediterrean; EUR: Europe; SEAR: Southeast Asia; WPR: Western Pacific. Regional Available data on laboratory cultures, clinical signs, colonization status, and risk factors varied by region. The Americas, Europe and eastern Mediterranean regions had studies that examined all of the above measures of maternal exposure. None of the studies in Africa provided lab-confirmed maternal infection data or clinical signs data. No study in southeast Asia provided lab-confirmed data. We were able to find studies in every region that provided data on maternal colonization and risk factors for infection, although the majority were from Europe and the Americas. All regions presented data on neonatal lab-confirmed infection, with the majority in the Americas. None of the studies in Africa or the eastern Mediterranean region had neonatal clinical signs of infection. No study in southeast Asia had neonatal colonization data. Risk of Bias After assessing attrition bias, selection bias, and confounding bias across the 83 studies, we rated two studies (2.4%) as having low risk, 53 (63.9%) as having unclear risk, and 28 (33.7%) as having high risk of bias (Figure S2). Among the 83 studies, 15 (18.1%) studies were considered as being at high risk for attrition bias. These studies lost more than 10% of participants to follow-up or had differential follow-up between the exposed and comparison groups. Thirteen (15.7%) studies had evidence of selection bias, defined as differential selection of the exposed and comparison groups resulting in a difference in the distribution of risk factors. Sixteen (19.3%) studies were rated as being at high risk for confounding bias, defined as a lack of adjustment for potential confounders through study design or statistical adjustment. Meta-analyses The meta-analyses results are presented by exposure outcome combinations: (i) maternal infection and neonatal infection; (ii) maternal colonization and neonatal infection; (iii) maternal colonization and neonatal colonization; and (iv) maternal risk factors and neonatal clinical infection. Maternal infection and neonatal infection Twenty-nine studies reported data on maternal infections and neonatal infections. As shown in Figure 2, studies that tested lab cultures for infection in both mother and newborn (“lab/lab”), newborns of infected mothers had a 6.6 (95% CI 3.9–11.2) times greater odds of infection than newborns of uninfected mothers. In studies that diagnosed maternal infection with clinical signs and neonatal infection with lab tests (“signs/lab”), newborns of infected mothers had a 7.7 (95% CI 4.6–13.0; I2 = 72.0%, 95% CI 45%–86%; adjusted OR 5.2, 95% CI 1.6–16.6; I2 = 77.1%, 95% CI 25%–93%) times greater odds of infection than newborns of uninfected mothers. Studies that diagnosed neonatal infection with lab tests or clinical signs (“lab/lab&signs”; “signs/lab&signs”) had a greater OR than those that diagnosed neonatal infection with only lab or only clinical signs (“lab/lab”; “lab/signs”; “signs/lab”; “signs/signs”) (Figure 2). 10.1371/journal.pmed.1001502.g002 Figure 2 Maternal infection and neonatal infection. *Adjusted ORs. These studies provided estimates adjusted for confounding factors. Sensitivity analyses excluding studies with a high risk of bias increased the ORs to 9.3 (95% CI 5.1–16.9) for the “lab/lab” analysis and slightly decreased the OR to 6.2 (95% CI 1.7–23.1) for the “signs/lab” analysis. Excluding studies with a high risk of confounding bias yielded ORs of 9.1 (95% CI 2.4–34.0) and 7.7 (95% CI 4.6–13.0) for “lab/lab” and “signs/lab” analyses, respectively. We also conducted a sensitivity analysis including only studies that clearly defined early-onset neonatal sepsis during the first 7 d of life. The ORs increased to 10.2 (95% CI 5.3–19.5) and 8.3 (95% CI 4.5–15.1) for “lab/lab” and “signs/lab” analyses, respectively. We did not have sufficient data to conduct a sensitivity analysis subgrouping studies with known or unknown antibiotic use. Maternal colonization and neonatal infection Given the heterogeneity of the data, we focused on GBS maternal colonization. Sixteen studies reported data on GBS maternal colonization and neonatal infection. As shown in Figure 3, in studies that tested GBS bacterial colonization in the mother and lab cultures for infection in the newborn (“colonization/lab”), newborns of colonized mothers had a 9.4 (95% CI 3.1–28.5; I2 = 76.3%, 95% CI 58%–87%) times greater odds of having infection than newborns of non-colonized mothers. A sensitivity analysis excluding studies with high risk of bias increased the ORs to 13.7 (95% CI 4.2–45.1). Excluding studies without a specified early-onset period to measure neonatal infection increased the odds to 11.0 (95% CI 2.3–54.0). A sensitivity analysis including only studies in which no antibiotics were used also increased the OR to 37.0 (95% CI 9.7–140.9). 10.1371/journal.pmed.1001502.g003 Figure 3 Maternal GBS colonization and neonatal infection. In studies that tested lab cultures for infection in newborns (“colonization/lab”), newborns of colonized mothers had higher odds of developing infection compared to those in studies that diagnosed neonatal infection clinical signs (“colonization/signs”) or that diagnosed neonatal infection with both lab tests and clinical signs (“colonization/lab &signs”) (Figure 3). Maternal colonization and neonatal colonization Twenty-five studies reported data on maternal colonization and neonatal colonization. We present these results by pathogen-specific subgroups: GBS, Staphylococcus aureus, Escherichia coli, and Ureaplasma (Figure 4). In studies that cultured GBS colonization for both the mother and newborn, newborns of colonized mothers had a 28.6 (95% CI 13.2–62.1; I2 = 88.8%, 95% CI 84%–92%) times higher odds of colonization compared to newborns of non-colonized mothers. 10.1371/journal.pmed.1001502.g004 Figure 4 Maternal colonization and neonatal colonization. A sensitivity analysis excluding high risk studies showed an increased OR to 43.8 (95% CI 11.0–174.8). Excluding studies that did not specify an early-onset neonatal infection period had a similar OR of 29.4 (95% CI 11.9–72.5, I2 = 89.1%, 95% CI 84%–92%). The OR for Staphylococcus aureus colonization was 7.5 (95% CI 2.9–19.1). The OR for E. coli colonization was 1.8 (95% CI 1.3–2.6). One study measured Ureaplasma colonization, which had lower ORs compared to studies measuring GBS or S. Aureus colonization (Figure 4). Maternal risk factors and neonatal infection Ten studies presented data on maternal risk factors (PPROM, PROM, prolonged ROM) and neonatal infections (Figure 5). In studies that observed risk factors for infection in the mother and tested lab cultures for the newborn (“risk/lab”), newborns of mothers with risk factors had a 2.3 (95% CI 1.0–5.4; I2 = 93.4%, 95% CI 89%–96%; adjusted OR 4.9, 95% CI 1.9–12.8) times greater odds of having infection than newborns of mothers without risk factors for infection. In two non-adjusted studies that classified PPROM as a risk factor for maternal infection and tested neonatal lab cultures for the newborn, newborns of mothers with PPROM had a 1.5 (95% CI 0.9–2.4) times greater odds of having an infection than newborns of mothers without PPROM, which was not statistically significant. In four non-adjusted studies that examined the risk factor ROM≥18–24 h, newborns of mothers with prolonged ROM had a 2.2 (95% CI 0.6–7.4) higher odds of having an infection than newborns of mothers with ROM 27 1 −0.06 0.94 0.11–7.75 0.95 3 0.47 1.61 0.10–25.58 0.71 1 −1.61 0.20 0.01–7.79 0.37 2 −0.85 0.43 0.08–0.26 0.26 Gross national income High income (≥12,276) per capita in USD 14 ref 9 ref 16 ref 7 ref Upper middle income (3,976–12,275) 1 0.96 2.61 0.34–20.12 0.33 1 −1.26 0.28 0.01–6.41 0.39 7 −1.02 0.36 0.07–1.80 0.20 0 — Lower middle income (1,006–3,975) 1 −0.06 0.94 0.11–7.75 0.95 4 0.24 1.27 0.12–13.54 0.83 1 4.60 99.78 6.26–39.49 0.03 1 0.99 2.69 0.53–13.67 0.19 Low income (≤1,005) 0 — 0 — 0 — 1 −2.02 0.13 0.06–0.32 0.00 Antibiotics None 0 4 ref 4 ref 0 Some 13 ref 5 0.26 1.29 0.08–19.72 0.84 7 1.42 4.15 0.27–63.06 0.29 7 ref Unknown 3 −0.58 0.56 1.41–20.12 0.20 5 −0.56 0.57 0.05–7.10 0.64 13 0.44 1.56 0.13–18.63 0.71 2 −1.19 0.30 0.07–1.42 0.11 Gestational age All 8 ref 12 24 — 5 ref Premature 8 −0.72 0.49 0.99–20.12 0.05 2 −0.61 0.54 0.03–10.29 0.66 0 4 0.12 1.13 0.18–6.98 0.88 WHO Region Americas 6 ref 5 ref 3 ref 3 ref Africa 0 — 0 — 1 −2.09 0.12 0.00–7.55 0.30 1 −2.19 0.11 0.03–0.37 0.01 Eastern Mediterranean 0 — 1 −0.51 0.60 0.00–96.20 0.83 2 3.29 26.91 0.60–1212.80 0.09 0 — Europe 6 −0.51 0.60 0.24–1.49 0.25 3 0.43 1.54 0.07–35.60 0.76 14 −0.12 0.89 0.08–9.83 0.92 3 −0.33 0.72 0.24–2.16 0.45 South east Asia 1 −0.32 0.72 0.08–6.49 0.75 3 0.60 1.82 0.07–50.27 0.69 0 — 1 0.81 2.26 0.32–15.96 0.31 Western Pacific 3 −0.49 0.61 0.16–2.36 0.44 2 −0.81 0.45 0.02–10.30 0.58 4 −1.60 0.20 0.01–3.23 0.24 1 −0.39 0.67 0.20–2.26 0.42 a Regression coefficient from metaregression. To examine if there were significant differences between subgroups, we conducted four meta-regression analyses testing each subgroup within the four groups: (i) maternal infection and neonatal infection, (ii) maternal colonization and neonatal infection, (iii) maternal colonization and neonatal colonization, and (iv) maternal risk factors and neonatal infections. Mothers with GBS colonization had a higher odds of having newborns with GBS colonization compared to mothers with E. coli colonization having newborns with E. coli colonization (OR = 12.9, 95% CI 1.2–143.4). There were no significant differences between other subgroups. Discussion We found consistent evidence of higher levels of early-onset neonatal infection among newborns of mothers with bacterial infection or colonization compared to newborns of mothers without infection or colonization. Although this relationship has long been understood, the magnitude of the disproportionate risk for infection has not yet been systematically documented. In studies with the most definitive measures of infection (“lab/lab”), newborns of infected mothers had a seven times higher odds of early-onset neonatal infection compared to newborns of uninfected mothers. Excluding high-risk-of-bias studies, the odds of neonatal infection increased to nine times higher among newborns of infected mothers compared to newborns of uninfected mothers. We included studies that measured clinical signs or risk factors of infection and compared estimates from these studies with estimates from studies with the gold standard lab-confirmed measures. In studies that tested neonatal lab cultures and diagnosed maternal infection with clinical signs (“signs/lab”), the OR was similar (with overlapping confidence intervals) to studies that diagnosed maternal infection with lab cultures (“lab/lab”), suggesting that maternal clinical signs may reliably identify maternal infections. Future studies could test the sensitivity and specificity of using maternal clinical signs to diagnose maternal infections. In studies documenting maternal risk factors, newborns of mothers with risk factors had higher odds of infection than newborns of mothers without risk factors, although this association was weaker in studies with maternal risk factors compared to studies with maternal lab-confirmed or clinical signs of infection. Maternal colonization with GBS has been shown to increase the odds of neonatal sepsis [32]. In this review, most studies that tested maternal colonization cultured for GBS. Colonization at delivery was associated with early-onset lab-confirmed neonatal infection, although we found a smaller effect (OR 11.0, 95% CI 3.6–33.5) than in a prior review on GBS colonization and neonatal infection published on developed countries (OR 204, 95% CI 100–419) [32]. In studies measuring maternal and neonatal colonization, there was strong evidence for increased odds of surface colonization among newborns of colonized mothers, supporting the idea that there is direct transmission through contact between the mother and newborn during delivery. In studies with neonatal clinical signs of infection, the magnitude of the association was smaller compared to studies with neonatal lab-confirmed infection. Neonatal clinical signs may not be specific enough to detect strong associations between maternal and neonatal infections. Studies that diagnosed neonatal infection with a more comprehensive definition, neonatal lab or clinical signs of infection, had a higher OR than studies with neonatal lab alone or clinical signs alone. Laboratory cultures may underestimate the true risk of early-onset neonatal infection because their sensitivity of detecting bacteria is dependent on several factors such as the volume of the specimen collected, timing of collection, technique used, and dilution methods [33],[34]. Studies with laboratory-confirmed infections were limited, especially from African and southeast Asian regions, and this presents challenges in estimating the global risk of infection among newborns of infected mothers. Because lab-confirmed data were not available in some regions, we looked at additional measures of infection such as clinical signs of infection, risk factors for infection, and colonization with the understanding that each measure of infection varied by completeness and accuracy. While this presented a comprehensive review of the literature, it also created significant heterogeneity among the studies included in the meta-analysis. To minimize heterogeneity, we grouped studies by exposure and outcome definitions and conducted separate meta-analyses for each group. To account for additional differences, we used a random-effects model. We did not provide an overall estimate measure across all studies because we assessed the studies to be too heterogeneous. Several subgroup analyses had high I2 values suggesting most of the variability across included studies is due to heterogeneity. We included pooled estimates for all subgroup analyses and I2 values and I2 confidence intervals to allow the reader to consider the extent of heterogeneity when interpreting these results. Since all studies were facilities-based and mostly concentrated in urban settings in the Americas and Europe, we were not able to capture the risk of neonatal infection among home births, rural births, or births at community facilities in lower-income countries, thereby limiting the generalizability of these findings. Furthermore, most studies included in the review were assessed to be at high or unclear risk of bias, which may lead to an underestimation or overestimation of the true effect. We used sensitivity analyses to exclude high-risk-of-bias studies and specifically examined confounding bias. After excluding studies with high risk of confounding bias, the magnitude of our effect size increased, suggesting that negative confounders may have biased results towards the null. There were limited data available on intrapartum antibiotic use. The inclusion of individuals who received antibiotics would lead a study to underestimate the magnitude of the association. When possible, we conducted sensitivity analyses including only studies with data where it was clear there was no antibiotic use. Lastly, we repeated the analyses with studies that specified an early-onset neonatal period of less than 7 d, which was associated with an increased risk of transmission. Misclassification of neonatal sepsis cases in the late-onset period likely underestimated our effect size, suggesting that these cases were unlikely to be maternally acquired. Finally, classification of studies by WHO region combines disparate countries but was performed to be consistent with past literature, and limited sample sizes resulted in wide confidence intervals, limiting the precision of our estimates. This study has important policy and research implications. The risk of early neonatal infection among women with maternal infections is high and presumably even higher in low-resource settings where most women deliver at home without access to health care. Intrapartum antibiotic prophylaxis could reduce the incidence of maternally acquired early-onset neonatal infections [7],[35],[36]. In settings where the case-fatality of early-onset neonatal sepsis is high, prophylaxis could potentially have a large benefit. Currently, a risk-based algorithm combined with GBS screening exists for use of intrapartum antibiotic prophylaxis in high income countries to prevent GBS early-onset neonatal sepsis. In this algorithm, antibiotics are given during labour to women who screened positive for GBS colonization at 35–37 wk gestation and to women with unknown GBS status and the following risk factors: less than 37 wk gestation, duration of membrane rupture ≥18 h, or temperature ≥38°C [37]. Temporal trends of decreasing GBS incidence have been observed before versus after implementation of these guidelines (1.7 per 1,000 live births in 1993 compared to 0.6 per 1,000 in 1998) [7]. This algorithm could be expanded to include other pathogens, especially in settings where GBS incidence is low such as southeast Asia (0.02 per 1,000 live births) [34]. A double-blinded randomized controlled trial testing the use of intrapartum antibiotic prophylaxis on early-onset neonatal sepsis is needed, although this would be expensive. In addition to focusing on the mother, other interventions could include administering antibiotic prophylaxis to newborns of high risk women. Emphasis should be placed on evaluating methods to diagnose and treat maternal infections and subsequently reducing early neonatal infections. Given the available resources, or lack thereof, in regions like Africa and Asia, better diagnostics and treatment of maternal infections in these settings have the potential to substantially reduce early neonatal infections. Development of a simple algorithm that combines clinical signs and risk factors to diagnose maternal infections would be useful in settings where lab facilities (culture or colonization) are not available. Conclusion To our knowledge, this is the first comprehensive review looking at maternally acquired early-onset neonatal infection. Based on the results, there is great potential to reduce early-onset neonatal infections by focusing interventions on women with maternal infections (laboratory-confirmed, clinical signs), colonization, and risk factors for infection (PROM, PPROM, and prolonged ROM). There is a need to understand the etiology of both maternal infections and colonization and neonatal infections in low- and middle-income countries. Standardizing definitions for maternal infections and newborns would be helpful to compare studies. High quality studies and better diagnostics are needed in low-resource areas, especially southeast Asia and Africa. Improving the detection of maternal infections during the intrapartum period using new technologies such as microfluidic assays, proteomic amniotic fluid analysis, or real-time polymerase chain reaction to develop point of care-devices that are cheap, fast, and highly sensitive and specific may allow health care workers to reach at-risk newborns sooner. In the meantime, improving identification of clinical signs and risk factors for maternal infection will have more immediate benefits, particularly in resource-limited settings. Although this review emphasizes targeting mothers to prevent neonatal infections, a comprehensive package would also focus on early detection of early-onset neonatal sepsis and neonatal treatment to decrease mortality and morbidity from neonatal infections during the first 7 d of life. Supporting Information Figure S1 Funnel plot with 95% CIs to assess for publication and small-study bias. (TIF) Click here for additional data file. Figure S2 Risk of bias summary for association measure: 77 cohort and nested case-control studies; six case-control studies. (PDF) Click here for additional data file. Table S1 Search terms by database. (PDF) Click here for additional data file. Table S2 Authors contacted regarding missing data. (XLSX) Click here for additional data file. Table S3 Full text non-English articles screened. (XLSX) Click here for additional data file. Table S4 Studies included in systematic review and meta-analysis: Maternal exposure and neonatal outcome combinations, relative risks, and definitions. (PDF) Click here for additional data file. Text S1 PRISMA statement. (DOC) Click here for additional data file. Text S2 Study protocol. (DOCX) Click here for additional data file.
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- Abstract: found
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Severe sepsis and septic shock in pregnancy.
B Sibai, Paul Barton (2012)
Pregnancies complicated by severe sepsis and septic shock are associated with increased rates of preterm labor, fetal infection, and preterm delivery. Sepsis onset in pregnancy can be insidious, and patients may appear deceptively well before rapidly deteriorating with the development of septic shock, multiple organ dysfunction syndrome, or death. The outcome and survivability in severe sepsis and septic shock in pregnancy are improved with early detection, prompt recognition of the source of infection, and targeted therapy. This improvement can be achieved by formulating a stepwise approach that consists of early provision of time-sensitive interventions such as: aggressive hydration (20 mL/kg of normal saline over the first hour), initiation of appropriate empiric intravenous antibiotics (gentamicin, clindamycin, and penicillin) within 1 hour of diagnosis, central hemodynamic monitoring, and the involvement of infectious disease specialists and critical care specialists familiar with the physiologic changes in pregnancy. Thorough physical examination and imaging techniques or empiric exploratory laparotomy are suggested to identify the septic source. Even with appropriate antibiotic therapy, patients may continue to deteriorate unless septic foci (ie, abscess, necrotic tissue) are surgically excised. The decision for delivery in the setting of antepartum severe sepsis or septic shock can be challenging but must be based on gestational age, maternal status, and fetal status. The natural inclination is to proceed with emergent delivery for a concerning fetal status, but it is imperative to stabilize the mother first, because in doing so the fetal status will likewise improve. Aggressive [corrected] treatment of sepsis can be expected to reduce the progression to severe sepsis and septic shock and prevention strategies can include preoperative skin preparations and prophylactic antibiotic therapy as well as appropriate immunizations.
Author and article information
Contributors
Mercedes Bonet: bonetm@who.int
Vicky Nogueira Pileggi: vicky.pileggi@gmail.com
Marcus J Rijken: mrijken2@umcutrecht.nl
Arri Coomarasamy: A.Coomarasamy@bham.ac.uk
David Lissauer: D.M.Lissauer@bham.ac.uk
João Paulo Souza: souzaj@who.int
Journal
Journal ID (nlm-ta): Reprod Health
Journal ID (iso-abbrev): Reprod Health
Title:
Reproductive Health
Publisher:
BioMed Central
(London
)
ISSN
(Electronic):
1742-4755
Publication date
(Electronic):
30
May
2017
Publication date PMC-release: 30
May
2017
Publication date Collection: 2017
Volume: 14
Electronic Location Identifier: 67
Affiliations
[1
]ISNI 0000000121633745, GRID grid.3575.4, UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research
Training in Human Reproduction (HRP), , Department of Reproductive Health and Research, World Health Organization, ; Geneva, Switzerland
[2
]ISNI 0000 0004 1937 0722, GRID grid.11899.38, Department of Social Medicine and Department of Paediatrics, Ribeirão Preto Medical
School, , University of São Paulo, ; Ribeirão Preto, SP Brazil
[3
]ISNI 0000000090126352, GRID grid.7692.a, Department of Obstetrics and Gynaecology and Julius Global Health, Julius Center for
Health Sciences and Primary Care, , Utrecht University Medical Centre, ; Utrecht, The Netherlands
Article
Publisher ID: 321DOI: 10.1186/s12978-017-0321-6
PMC ID: 5450299
PubMed ID: 28558733
SO-VID: ac27480a-2be6-4b32-a701-7cddbceee98d
Copyright © © The Author(s). 2017
License:
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
History
Date
received
: 20
February
2017
Date
accepted
: 3
May
2017
Funding
Funded by: UNDP-UNFPA-UNICEF-WHO-World Bank Special Programme of Research
Funded by: Utrecht University Medical Centre
Funded by: FundRef http://dx.doi.org/10.13039/501100000855, University of Birmingham;
Funded by: FundRef http://dx.doi.org/10.13039/501100000855, University of Birmingham;
Categories
Subject:
Review
Custom metadata
issue-copyright-statement © The Author(s) 2017
ScienceOpen disciplines: Obstetrics & Gynecology