# Predicting neonatal infection in PPROM with vaginal microbiology and metagenomics: a prospective cohort study

Laurent Mandelbrot, Sean P. Kennedy, Jessica Rousseau, François Goffinet, Luce Landraud, Céline Plainvert, Valérie Marcou, Luc Desfrère, Tiphaine Barral, Lahçene Allal, et al.

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## To cite this version:

Laurent Mandelbrot, Sean P. Kennedy, Jessica Rousseau, François Goffinet, Luce Landraud, et al. Predicting neonatal infection in PPROM with vaginal microbiology and metagenomics: a prospective cohort study. American Journal of Obstetrics and Gynecology, In press, 10.1016/j.ajog.2025.12.042. pasteur-05425557

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Predicting neonatal infection in PPROM with vaginal microbiology and metagenomics: a prospective cohort study

Laurent Mandelbrot, Sean Kennedy, Jessica Rousseau, François Goffinet, Luce Landraud, Céline Plainvert, Valérie Marcou, Luc Desfrère, Tiphaine Barral, Lahçene Allal, Agnès Baud, Nathalie Grall, Claire Poyart, Pierre-Yves Ancel, Asmaa Tazi

PII: S0002-9378(25)00939-1

DOI: https://doi.org/10.1016/j.ajog.2025.12.042

Reference: YMOB 16582

To appear in: *American Journal of Obstetrics and Gynecology*

Received Date: 10 June 2025

Revised Date: 22 November 2025

Accepted Date: 13 December 2025

Please cite this article as: Mandelbrot L, Kennedy S, Rousseau J, Goffinet F, Landraud L, Plainvert C, Marcou V, Desfrère L, Barral T, Allal L, Baud A, Grall N, Poyart C, Ancel P-Y, Tazi A, Predicting neonatal infection in PPROM with vaginal microbiology and metagenomics: a prospective cohort study, *American Journal of Obstetrics and Gynecology* (2026), doi: https://doi.org/10.1016/j.ajog.2025.12.042.

This is a PDF of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability. This version will undergo additional copyediting, typesetting and review before it is published in its final form. As such, this version is no longer the Accepted Manuscript, but it is not yet the definitive Version of Record; we are providing this early version to give early visibility of the article. Please note that Elsevier's sharing policy for the Published Journal Article applies to this version, see: https://www.elsevier.com/about/policies-and-standards/sharing#4-published-journal-article. Please also note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1 **Predicting neonatal infection in PPROM with vaginal microbiology and metagenomics: a prospective cohort study**

3

4 **Short title : Vaginal sampling to predict neonatal infection in PPROM**

5

6

7 Laurent Mandelbrot<sup>1,2,3</sup>, Sean Kennedy<sup>4</sup>, Jessica Rousseau<sup>5</sup>, François Goffinet<sup>3,6,7</sup>, Luce

8 Landraud<sup>2,8</sup>, Céline Plainvert<sup>9</sup>, Valérie Marcou<sup>3,10</sup>, Luc Desfrère<sup>3,11</sup>, Tiphaine Barral<sup>12</sup>, Lahçene

9 Allal<sup>13</sup>, Agnès Baud<sup>4</sup>, Nathalie Grall<sup>14</sup>, Claire Poyart<sup>3,9,15</sup>, Pierre-Yves Ancel<sup>5,6</sup>, Asmaa Tazi<sup>3,9,15</sup>

10

11 **Affiliations**

12 <sup>1</sup>Assistance Publique-Hôpitaux de Paris, Department of Obstetrics and Gynecology, Hôpital Louis

13 Mourier, Colombes, France

14 <sup>2</sup>Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME F-75018 Paris, France

15 <sup>3</sup>FHU Prem'Impact, Paris, France

16 <sup>4</sup>Computational Biology Department, Institut Pasteur, Université Paris Cité, Paris, France

17 <sup>5</sup>Assistance Publique- Hôpitaux de Paris, URC-CIC Paris Descartes Necker/Cochin, Paris, France

18 <sup>6</sup>Université Paris Cité and Université Sorbonne Paris Nord, INSERM, INRAE, Centre de

19 Recherche Epidémiologie et StatistiqueS (CRESS), Obstetrical, Perinatal and Pediatric Life

20 Course Epidemiology (OPPALE Team), Paris, France

21 <sup>7</sup>Assistance Publique-Hôpitaux de Paris, Department of Obstetrics and Gynecology, Hôpital

22 Cochin-Port Royal, Paris, France

23 <sup>8</sup>Assistance Publique-Hôpitaux de Paris, Department of Microbiology, Hôpital Louis Mourier,

24 Colombes, France

25 <sup>9</sup>Assistance Publique-Hôpitaux de Paris, Department of Bacteriology, National Reference Center

26 for Streptococci, Hôpital Cochin, Paris, France

27 <sup>10</sup>Assistance Publique-Hôpitaux de Paris, Department of Neonatal Medicine, Hôpital Cochin-Port

28 Royal, Paris, France
29 11 Assistance Publique-Hôpitaux de Paris, Department of Neonatal Medicine, Hôpital Louis
30 Mourier, Colombes, France

31 12 Assistance Publique-Hôpitaux de Paris, Department of Obstetrics and Gynecology, Hopital
32 Bichat, Paris, France.

33 13 Assistance Publique-Hôpitaux de Paris, Neonatal Medicine Unit, Hôpital Bichat, Paris, France

34 14 Assistance Publique-Hôpitaux de Paris, Department of Microbiology, Hôpital Bichat, Paris,
35 France

36 15 Inserm U1016, CNRS UMR 8104, Université Paris Cité, Institut Cochin, Paris, France.

37

38 **Corresponding author**

39 Prof Laurent Mandelbrot

40 Service de Gynécologie-Obstétrique, Hôpital Louis Mourier

41 178 rue des Renouillers – 92700 Colombes, FRANCE

42 laurent.mandelbrot@aphp.fr

43

44 **Alternate corresponding author**

45 Sean Kennedy, PhD

46 Institut Pasteur, Université Paris Cité

47 Département de biologie computationnelle, F-75015 Paris, France

48 sean.kennedy@pasteur.fr

49

50 This work was supported by the Programme d'Investissements d'Avenir and Bpifrance (Structuring
51 R&D Project for Competitiveness—PSPC): # DOS0053477 SUB et DOS0053473 AR. A full list
52 of contributors to this study, collectively called the InSPIRE Consortium, can be found in the
53 accompanying Supplementary Information file 3.”

54 **Conflicts of interest**

55 The authors declare no conflict of interest in relation with this research

56

57 **Authors' Contributions**
58 Conceptualization: LM, CPo

59 Formal analysis: JR, PYA, SK

60 Funding acquisition: LM, SK, CPo

61 Investigation: LM, SK, FG, LL, CPI, VM, LD, TB, LA, NG, AT

62 Methodology: PYA, LM, SK

63 Project administration: LM, AT

64 Validation: LM, SK, FG, LL, CPI, CPo, VM, LD, TB, LA, NG, AT

65 Writing – original draft: LM, SK, JR

66 Writing – review and editing: LM, SK, FG, LL, CPI, CPo, VM, LD, TB, LA, NG, CP, AT

67 All authors have made substantial contributions to all of the following: The conception and design of the study, or acquisition of data, or analysis and interpretation of data, drafting the article or revising it critically for important intellectual content, and final approval of the version to be submitted.

71
72 **CONDENSATION PAGE**

73 **CONDENSATION**

74 In Preterm Premature Rupture of Membranes, metagenomic analysis of vaginal samples did better
75 than conventional culture to predict the risk of Early-onset neonatal sepsis.

76 **TWEETABLE STATEMENT :**

77 Vaginal samples were useful to determine the risk of ascending route neonatal sepsis following
78 PPROM. The performance of metagenomic analysis was superior to culture.

79 **SHORT TITLE :**

80 Vaginal sampling to predict neonatal infection in PPROM

81 **AJOG AT A GLANCE :**

82 **A. Why was this study conducted?**

83 • Early-onset neonatal sepsis (EONS) is a major complication of PPROM, due to ascending
84 infection.

85 • Microbiological analysis of vaginal flora could be useful to predict the risk of EONS, but
86 evidence lacks.

87 **B. What are the key findings?**

88 • EONS occurred in 4.5% of PPROM. Main pathogens were *E. coli* and other enterobacteria,
89 with a single case of *S. agalactiae*.

90 • The same pathogen was cultured in the majority of paired maternal/neonatal samples,
91 documenting ascending route infection.

92 • A high metagenomics score based on the vaginal microbiome and presence of potential
93 pathogens was associated with a 9-fold increased risk of EONS.

94 **C. What does this study add to what is already known?**

95 • Metagenomic signatures from vaginal samples were more predictive of EONS than
96 conventional culture.

97 • The perspective is a rapid molecular-based test allowing for better use of antibiotics.

98
99

**Abstract**

100

**Objective**

101

102

103

104

Early-onset neonatal sepsis (EONS) due to ascending infection is a potentially preventable complication of preterm premature rupture of membranes (PPROM). Our objective was to determine whether the analysis of bacteria from vaginal swab samples is predictive of the risk of EONS in PPROM.

105

**Study Design**

106

107

108

109

110

111

In a prospective 3-center observational cohort, patients with PPROM were enrolled between 22 and 36 weeks' gestation (WG) + 6 days. Vaginal swab samples at delivery were analyzed using two different approaches, classical bacterial cultures and shotgun metagenomic sequencing analysis. A metagenomics score was constructed combining the characterization of the vaginal microbiome and the presence of pathogens and the optimal cut-off to predict EONS was tested on a receiver operating curve.

112

**Results**

113

114

115

116

117

118

563 PPROM cases were enrolled, with 646 liveborn neonates. PPROM occurred < 32 WG in 41.9% and deliveries were < 34 WG in 41.0%. The incidence of EONS was 29/646 (4.5%). When considering all central and peripheral microbiological samples available for 26 neonates, the main pathogens isolated were *Escherichia coli* in 14 cases (53.8%), other gram-negatives in 5 (19.2%), strict anaerobes in 3 (11.5%); there was a single case (3.8%) each with Group B *Streptococcus* (GBS), *Streptococcus anginosus*, *Staphylococcus aureus* and *Ureaplasma urealyticum*.

119

120

121

122

123

124

We studied the prediction of EONS among 272 mothers and their 310 neonates (20 EONS, 6.4%) with both culture and metagenomic data available. A culture positive for a major or intermediate pathogen in the vaginal sample at delivery had a sensitivity of 80.0 % (95% CI=56.3-94.3) and a specificity of 37.9% (95% CI=32.3-43.8), adjusted odds ratio (aOR) of 1.6 (95 % CI [0.5-5.0]) to predict EONS. The presence of *E. coli* was associated with an EONS risk of 10.6% vs 4.9%, in the absence of *E. coli* (p=0.07).

125

126

127

128

129

The metagenomics score was highly associated with EONS, with an area under the receiver operating curve of 0.75 (95% CI, 0.61-0.90). At the optimal cutoff value, sensitivity was 70% (95% CI, 64-95%), specificity was 85% (95% CI, 81-89%). A metagenomics score greater than 40 was associated with a significantly increased risk of EONS with an aOR of 8.9 (95% CI [3.5; 22.3]) in multivariate analysis adjusted for latency period and gestational age, p<0.001.

130

**Conclusion**
In PPROM, conventional microbial culture of maternal vaginal samples was associated with EONS, but its predictive values remain insufficient to guide perinatal care. Metagenomic microbial signatures improved predictive values. This opens the perspective for a rapid point-of-care test.

**Keywords:** Pregnancy ; Ascending route infection; Bacterial culture; Early-onset neonatal sepsis; Metagenomics; Nugent score; Preterm Premature Rupture of Membranes (PPROM); Vaginal microbiota ; Vaginal swab sampling
139 **Introduction**

140 Preterm premature rupture of the membranes (PPROM), which concerns 3% of all births (1) (2)
141 (3), is associated with neonatal morbidity due to early-onset neonatal sepsis (EONS), preterm birth,
142 fetal inflammatory response syndrome (4-6), as well as maternal infection risks (7) (7, 8). PPROM
143 has multiple underlying causes, including infection, inflammation, cervical insufficiency, multiple
144 pregnancy, polyhydramnios and membrane weakness (9). Infection is both a cause and a
145 consequence of PPROM (1, 10). Subclinical microbial invasion of the amniotic cavity (MIAC)
146 can lead to inflammation and PPROM, while ruptured membranes allow for ascending route
147 infection by pathogens from the vaginal compartment.

148 Preventing and predicting EONS remains elusive. Vaginal type micro-organisms are frequently
149 recovered from amniotic fluid in PPROM cases (11), however amniocentesis is not always feasible
150 or acceptable (12). Vaginal sampling is less invasive and is widely performed, but there has been
151 little study of its predictive value except for GBS detection (13). Consensus is lacking on whether
152 other pathogens which can cause EONS should be detected (2). Molecular methods have been
153 used to investigate vaginal microbiota patterns associated with MIAC (14, 15). To date, the
154 relation between PPROM and actual infection of the neonate has gained less attention.
155

156

157

158 **Objectives**

159 Our objective was to determine whether culture and metagenomic analysis of vaginal swab
160 samples near delivery are predictive of the risk of neonatal early-onset bacterial infection in
161 PPROM.

162

162 **Methods**

163 The Innovative Strategies for Perinatal Infectious Risk Reduction (InSPIRe) project aimed to
164 develop a point-of-care test to predict EONS based on the microbiological and immunological
165 profile of vaginal samples. Four prospective cohorts were enrolled at presentation for: A) routine
166 screening for GBS at 34-38 WG, B) term prelabor rupture of membranes, C) preterm labor, and
167 D) PPROM, from August 1, 2018 to June 30, 2023 in 3 centers in Paris, France. The present sub-
168 study concerned all PPROM cases (fig 1) in singleton or twin pregnancies between 22 and 36 WG
169 + 6 days. PPROM was diagnosed according to guidelines clinically (fluid discharge confirmed by
170 amniotic pooling at speculum examination), using commercial biochemical tests only when
diagnosis was uncertain. Exclusion criteria were fetal death or non-viable anomalies, age under 18 years, incapacity to express consent or lack of health coverage, according to French law.

Vaginal sampling was performed at enrollment as in usual care, without a speculum, by inserting the swabs about 5 cm into the vaginal canal and gently rotating for 10 to 30 seconds, with two additional swabs at the same time for storage. Repeat vaginal swab samples were obtained at admission for delivery. The present study was performed on delivery samples, or enrollment samples if taken within one week.

Antibiotics, obstetrical and neonatal care were performed as usual in all three centers, according to French guidelines(2). In summary, at the time of PPROM, amoxicillin was given at 2g/day orally for 7 days, which could be shortened if vaginal sample tested negative for GBS, and metronidazole could be used in case of bacterial vaginosis. In the absence of spontaneous preterm labor or signs of infection, delivery was planned at 37 WG. Cesarean sections were performed in case of abnormal CTGs or obstetrical indications, not solely because of preterm delivery or suspected infection. Amniocentesis was not performed. Intrapartum antibiotics were administered intravenously, usually amoxicillin as prophylaxis, clindamycin in case of documented maternal penicillin allergy, and third-generation cephalosporins or aminoglycoside with amoxicillin in case of signs of chorioamnionitis. Betamethasone, in a 2-day course of 12 mg was administered in case of PPROM before 34 WG, and magnesium sulfate was administered in case of imminent birth before 32 WG. Neonates were admitted to NICU in case of birth before 35 WG and/or clinical signs of distress or EONS. Neonates did not receive antibiotic prophylaxis systematically but were treated in case of suspected infection. Neonates were admitted to NICU in case of birth before 35 WG and/or any clinical signs of distress or EONS. Neonates did not receive antibiotic prophylaxis systematically but were treated in case of suspected infection, based on clinical examination supported by procalcitonin (PCT) measurements from cord blood and repeated C-reactive protein (CRP) in neonatal blood. Lumbar puncture was performed only if blood culture was positive, neurological signs or severe sepsis. No microbiological sampling was performed in neonates solely for the study. The first line of antibiotics was an amoxicillin and an aminoglycoside in the absence of culture results from the mother. No microbiological sampling was performed in neonates for the study.

## Ethics

Informed, written consent was obtained from all mothers, and co-parents consented to use of infants' data. The study was conducted according to the principles of the Declaration of Helsinki. The study was approved by the Committee for Protection of Persons (CPP Nord-Ouest, 11/4/2017) and was registered on Clinical trials (NCT03371056).
205 **Outcomes studied**

206 The main outcome was EONS, occurring within 72 hours postnatally. We applied the definition
207 of the French Health Authority (16), which was in the context of PPROM at least one major clinical
208 sign of sepsis (fever or hypothermia, grayish complexion, tachycardia, bradycardia, increased
209 capillary refill time, hypotension, respiratory signs, neurological signs) and one or more biological
210 sign (elevated PCT and/or CRP, requiring NICU hospitalization and 7 or more days of antibiotics.
211 Blood-culture positivity was considered as confirmatory but was not required in view of the
212 restrictive approach for invasive sampling. Tracheal cultures were also considered as
213 confirmatory. Culture from gastric aspirate, ear or meconium was not considered as sufficient
214 evidence of EONS, but when available we used the results as well as placental culture as evidence
215 of the potential causal pathogen. All cases reported by investigators as EONS were reviewed by
216 an adjudication committee of expert neonatologists and microbiologists.

217 Clinical chorioamnionitis was defined (17) as maternal fever without any other cause ≥ 39°C or
218 38°C-38.9°C persisting at least 30 minutes, associated with fetal tachycardia (baseline > 160/min),
219 hyperleukocytosis > 15000/µL (in the absence of corticosteroids) and/or purulent/fetid amniotic
220 fluid.

221 Histological chorioamnionitis was defined by the presence of neutrophilic infiltrates in the
222 amniotic membrane and chorion, and funisitis by neutrophile infiltrates in the fetal chorionic
223 vessels, umbilical vein or arteries. (18) (19). Histological placental examination was performed
224 according to routine clinical guidelines.

225 Bacterial culture

226 Vaginal swabs in Amies transport medium (ESwab™ system, Copan Diagnostics, Italy) and
227 neonatal samples including nasopharyngeal and tracheal aspirates, as well as meconium, were
228 immediately processed for analysis by conventional culture methods as recommended (20). Non-
229 selective media for fastidious bacteria (Columbia agar with 5% horse blood and chocolate agar
230 with PolyViteX) and enterobacteria, GBS and oxygen-free atmosphere for anaerobic culture were
231 used. For vaginal samples, direct microscopic examination was also performed to calculate the
232 Nugent score. All plates were examined after 16h and 44h of incubation. Blood cultures were
233 performed using the automated BACT/ALERT® Virtuo® system (bioMérieux, Marcy l'Etoile,
234 France). All different morphotypes of bacteria and yeast colonies were identified using
235 matrix assisted laser desorption ionization - time of flight (MALDI-TOF) mass spectrometry.

236 A positive vaginal sample was defined by the culture of bacteria with known pathogenic
237 potential: *Escherichia coli, Streptococcus agalactiae* (Group B Streptococcus, GBS),
238 *Haemophilus* spp. (*H. influenzae*, *H. parainfluenzae*, *H. haemolyticus*), *Staphylococcus aureus*,
239 *Streptococcus anginosus*, *Streptococcus constellatus*, *Enterococcus faecalis*, other gram negative
240 enterobacteriales (*Klebsiella pneumoniae*, *Proteus mirabilis*, etc.), anaerobes (*Prevotella* spp,
241 *Bacteroides* spp.).

242
243 **Metagenomics**

244 Whole-genome shotgun metagenomics was used as previously described (19). DNA was extracted
245 from ~500 µL of vaginal swab fluid (E-swabs, Copan) and sequenced (~10 M reads). Preliminary
246 processing included quality filtering of raw reads and removal of human sequences to retain only
247 high-quality microbial reads for downstream analysis. Filtered reads were taxonomically classified
248 using Kraken2, a classifier that assigns short DNA sequences to reference genomes in a vaginal
249 microbiota-specific database (20, 21). Kraken2 quantifications were normalized with Bracken
250 (22), which corrects for differences in genome length and improves species-level estimates.
251 Normalized quantifications were converted to relative abundances. Analysis 1 classified each
252 sample into a *Community State Type* (CST) according to its dominant taxa (23), from the
253 metagenomics relative abundance data (21), following standard definitions (22): CST I:
254 *Lactobacillus crispatus* dominated, CST II: *L. gasseri* dominated, CST III: *L. iners* dominated,
255 CST IV-A: non-*Lactobacillus* bacteria dominated, CST IV-B: *Gardnerella vaginalis* and *Sneathia*
256 *sanguinegens* dominated, CST V: *L. jensenii* dominated (24). Analysis 2 used relative abundances
257 to calculate a vaginal microbiota score to assess EONS risk using a logistic regression model
258 trained on 20 EONS cases and 290 controls. For each taxon, a relative-abundance threshold that
259 best discriminated between EONS and controls was identified to optimize sensitivity. Weighted
260 penalty scores were assigned based on each taxon's predictive value. Scores for major pathogens
261 (*E. coli*, GBS, *Streptococcus pyogenes* [Group A Streptococcus], *S. pneumoniae*) and intermediate
262 pathogens (*Enterobacteria*, *S. dysgalactiae*, *S. anginosus*, *S. aureus*, *E. faecalis*, *Haemophilus*
263 spp., *Candida* spp.) were summed separately, and the total for each group was multiplied by a
264 factor of 2 (major) or 1 (intermediate). The combined pathogen score was then multiplied by the
265 microbiota-environment component (ranging 1 to 10) to yield a final composite risk score.

266 We calculated a vaginal microbiota score to assess EONS risk using a logistic regression model
267 which was trained using 20 EONS cases and 290 controls. For each taxon, a relative abundance
268 threshold that best discriminated between EONS and controls was identified to optimize
269 sensitivity. Weighted penalty scores were then assigned based on each taxon's predictive value.
270 Scores for major pathogens (*E. coli*, GBS, *Streptococcus pyogenes* [Group A Streptococcus],
271 *Streptococcus pneumoniae*) and intermediate pathogens (e.g., Enterobacteria, *Streptococcus*
272 dysgalactiae, S. anginosus, S. aureus, E. faecalis, Haemophilus spp., Candida spp.) were summed
273 separately, and the total for each group was multiplied by a factor of 2 (major) or 1 (intermediate).
274 The combined pathogen score was then multiplied by the microbiota environment component
275 (ranging from 1 to 10) to yield a final composite risk score.

276 Statistical methods

277 For the metagenomic score, we performed Receiver Operating Characteristic (ROC) curve
278 analysis and calculated the area under the curve (AUC) to assess the model's ability to predict
279 EONS. The optimal threshold for predicting EONS was selected by maximizing the odds ratio
280 and minimizing the p-value. The Youden index was used to identify the threshold that maximizes
281 the sum of sensitivity and specificity.

282 Maternal characteristics, obstetrical and neonatal outcomes were compared between cases with
283 and without EONS. We then tested the performances of culture and metagenomic analysis of
284 vaginal samples to predict EONS. We studied the predictive values of vaginal culture and
285 metagenomic score for EONS in PPROM in univariate analysis and performed a multivariate
286 analysis adjusting for gestational age at delivery and time from PPROM to delivery, because they
287 were previously reported as risk factors for EONS. We did not adjust for mode of delivery or
288 antibiotics, which were significantly associated with EONS in univariate analysis, because they
289 were intermediate variables rather than confounders(23). The primary analytical cohort was the
290 population with both vaginal culture and metagenomic results, and data on the overall population
291 with culture results were presented as supplemental data.

292 Crude and adjusted Odds Ratios (OR) and their 95% Confidence Interval (CI) comparing the
293 proportion of EONS according to whether the metagenomic score was less than vs greater than or
294 equal to the optimal threshold were estimated using Generalized Estimating Equations to account
295 for the correlation between twins. Categorical variables were compared using Chi2 test or Fisher
296 exact tests and continuous variables were analyzed with t tests and Wilcoxon tests as appropriate.
297 All tests were 2-sided. The significance threshold was set at 0.05. Analyses were performed with
298 SAS version 9.4.

299

300 Results

301 Among 2566 pregnancies, 563 cases of PPROM occurred between 22 and 36 WG+6, with a total
302 of 646 liveborn neonates including twins (fig 1). The incidence of EONS was 29/646 (4.5% (95%
303 CI = 3.03-6.38)). Among the neonates with EONS, as defined by clinical and biological signs,
304 including one neonatal death in the delivery room at 33 WG, 24 had blood cultures sent, of which
4 (16.7%) were positive. Central and/or peripheral microbiological samples were available for 26 neonates. The main pathogens isolated were *E. coli* in 14 cases (53.8 %), other gram-negatives in 5 (19.2%), strict anaerobes in 3 (11.5%); there was a single case (3.8%) each with GBS, *S. anginosus*, *S. aureus* and *U. urealyticum*.

Metagenomic analysis was performed on vaginal swab samples from 272 mothers, corresponding to 310 neonates, including 20 with EONS. Among these cases with culture and metagenomic data, median gestational age at PPROM was 34 WG, and the latency period until delivery was < 24h in 34.6 % and > 14 days in 9.9 % (Table 1). Fever in labor occurred in 9.7%, with clinical chorioamnionitis in 6.4%. Histological chorioamnionitis was diagnosed in 56.8 % of the placentas studied. Antibiotics were administered in all cases at the time of rupture, and during labor in 95.2 %, for prophylaxis in 89.1 % and signs of infection in 10.9 %. The majority received amoxicillin; cephalosporins and other second-line antibiotics were used in 25.3%, mostly in cases with clinical chorioamnionitis. Most births were spontaneous preterm, and 8.1% were at 37 WG, the latest gestational age recommended for systematic induction for PPROM (2).

## Vaginal culture results

The presence of *E. coli* was associated with a trend towards a greater EONS risk (10.6 % vs 4.9% in the absence of *E. coli*, p=0.07). Neither GBS, nor bacterial vaginosis, were associated with the risk of EONS (Table 2). The presence of one or more pathogen was associated with an increased risk of EONS, resulting in a PPV=8.1 and a NPV=96.5, with an OR=2.4 (95%CI 0.8-7.4, p=0.12) which did not reach statistical significance (Table 4).

In the overall population with culture data, regarding 490 infants (including all 29 cases of EONS), *E. coli* in the vaginal sample culture was significantly associated with EONS (p=0.03) (Supplemental Table 1). The presence of one or more pathogen was associated with a higher risk of EONS (OR (95% CI) = 2.6 (1.0-7.1)), but which was not significant in the multivariate analysis (Supplemental Table 2).

Patients with metagenomic data differed from the overall population, in particular more EONS (20/310 vs 29/646). This was because some vaginal samples were not found in the designated storage facilities, requiring searching other locations. In practice, additional efforts were made to retrieve samples from EONS cases to be sent to the metagenomics laboratory. Among the 26 cases of EONS where bacteria were cultured from neonatal samples (Supplemental Table 3), the same pathogen was cultured in maternal vaginal samples and neonatal samples (central or peripheral sites) in 16 cases (61.5 %), including 11 *E. coli*, 3 other enterobacterales, 1 *S. aureus* and 1 GBS, were cultured from vaginal and neonatal samples.
338 **Metagenomic results (Tables 3 and 4).**

339 The majority of samples were classified as Community State Type (CST) I (L. crispatus), CST III
340 (L. iners) or CST IV (diverse anaerobes), complemented with a minority of CST II (L. gasseri) or
341 CST V (L. jensenii). CST I was associated with a significantly lower risk of EONS than the other
342 CSTs (p = 0.03), and most EONS cases (12/20) were associated with CST IV.

343 Since the Nugent test is used in clinical practice to diagnose dysbiosis, we quantified the taxa
344 included in the Nugent test (Lactobacillus, Bacteroides, Gardnerella and Mobiluncus) using
345 metagenomic counts. This clinically relevant scoring approach had higher sensitivity than the CST
346 approach. A threshold of ≥4 most effectively classified EONS cases (p < 0.001).

347 We next quantified major and intermediate pathogens (cf Methods). Detection of these major
348 pathogens was significantly associated with EONS risk (p < 0.001). The sensitivity of the
349 pathogen-based analysis alone was lower (15 of 20 cases) compared to the vaginal environment
350 score (19 of 20), but pathogen detection improved the precision of EONS prediction.

351 To further investigate this interaction, we combined the vaginal environment score with pathogen
352 penalties into a single composite risk score. EONS risk differed significantly according to the
353 vaginal microbiome score, the major pathogens score and a score combining major and
354 intermediate pathogens. The composite score linking EONS with the vaginal environment and
355 pathogen detection had an area under the ROC curve (AUC) of 0.75 (95% CI, 0.61–0.90; Fig 2).
356 A cutoff value of ≥40 provided the best predictive performance, with a sensitivity of 0.70 (95%
357 CI, 0.46–0.88), a specificity of 0.85 (95% CI, 0.80–0.89), PPV=24.1% and NPV=97.6%. A
358 metagenomic score above this threshold was associated with a significantly increased risk of
359 EONS (OR 12.9 [95% CI, 4.7–35.2] in univariate analysis; adjusted OR 8.9 [95% CI, 3.5–22.3]
360 in multivariate analysis). The metagenomic score was significantly higher, with a median score of
361 60.00 (IQR : 40.00-96.00) in the presence of concordance between maternal and neonatal
362 pathogens, vs 3.50 (IQR : -8.00-18.00) in EONS cases without concordance (and 2.00 in the
363 absence of EONS), p=0.002.

364

365 **Discussion**

366 **Main findings**

367 The presence of pathogenic bacteria in the vaginal swab sample was associated with EONS,
368 supporting ascending-route infection. We described a metagenomic score with a ROC-AUC of
369 0.75, demonstrating for the first time microbial signatures which were more predictive of EONS
370 than conventional culture-based diagnosis.
371 **Findings in the context of previous studies**

372 The incidence of EONS was 4.5%, similar to the French nationwide Epipage-2 study (24) where
373 it was 3.4% following PPROM. The incidence of EONS differs widely between studies (25-28),
374 due to differences in inclusion criteria, as well as definitions of EONS (29). Although culture-
375 positive is the most common definition today, there are false positives (30) as well as false
376 negatives (31), depending on the timing of collection relative to antibiotic administration, volume
377 and number of samples, resulting from practices limiting invasive lumbar punctures and blood
378 cultures especially in preterm infants.

379 *E. coli* was the main pathogen responsible for EONS following PPROM, as previously reported
380 (25, 32), partly because ampicillin prophylaxis for GBS has poor efficacy on gram-negative
381 infections (24).

382 Although the concept of ascending route infection is well established, and vaginal colonization
383 and neonatal colonization are correlated (33)(34), few studies attempted to correlate vaginal
384 colonization with pathogens in neonates with actual infection. In a retrospective study by Kwon et
385 al (33), maternal vaginal colonization with abnormal aerobic bacteria was associated with a 4-fold
386 higher rate of EONS, and the presence of *E. coli* and *S. aureus* were significantly correlated with
387 neonatal blood cultures. However, bacteria recovered from vaginal and neonatal cultures may
388 differ, due to failure to isolate microorganisms in infected neonates, bacterial concentration,
389 viability and phenotype (34, 35), recovery of bacteria during sampling and processing, and
390 sensitivity of culture. Also, antibiotics may bring pathogens under the detection limit without
391 eradicating them.

392 The molecular-based approach appears more sensitive than culture. A previous report from the
393 InSPIRe cohorts (36) demonstrated that metagenomic analysis of vaginal bacterial communities
394 allows for quantification of all species present in the vaginal microbiota, differentiating
395 *Lactobacillus* species and identifying species which are not captured in conventional
396 microbiology. However molecular methods may also detect non-infective material.

397 Our metagenomic score was more predictive of EONS than community state types (CSTs).
398 Using CST to predict EONS, Dos Anjos Borges et al. (28) reported a ROC-AUC of 0.69, which
399 was lower than our metagenomic score. Other researchers studied relations between CSTs and
400 MIAC and IAI (37) (38), but not EONS. Most microbes detected in MIAC, particularly *U.*
401 *urealyticum* and *G. vaginalis*, are evidence of bacterial vaginosis rather than causal pathogens for
402 EONS. The correlation between *Ureaplasma* spp. presence in vaginal samples and lower *L.*
403 *crispatus* and higher *L. iners*, as previously described (36), confirms the association with
404 dysbiosis.
405 Bacterial vaginosis does not cause EONS, but constitutes a favorable environment for ascending
406 infection (26), depending on the relative abundance of aerobic bacteria and lactobacilli (39).

407 Thus, predicting the risk of infection should consider both the vaginal microbiome environment
408 (i.e. healthy or pathogenic) and the pathogens which can be directly responsible for EONS.

409 **Strengths and limitations**

410 The main strengths were the large population, prospective multicenter design with data monitoring
411 and novel approach using culture and metagenomics to characterize vaginal swab samples.

412 The main limitation was lack of power due to the small number of EONS. The number of patients
413 enrolled was calculated based on the primary objective for the InSPIre project, not addressed in
414 this substudy, which was the ability of the final point-of-care test to detect pathogens. All cases of
415 suspected EONS were reviewed and adjudicated by experienced neonatologists and
416 microbiologists from at least two different centers. Although half of the vaginal swab samples
417 tested by culture were not tested by metagenomics, the population was large enough to obtain
418 statistically significant differences according to infection status. Furthermore, pathogens were not
419 always detected in neonates with EONS. According to current practices, invasive sampling is
420 avoided in babies, and peripheral microbiology sampling is no longer recommended. Finally, the
421 impact of antibiotics on microbiological and EONS results could not be determined due to the
422 observational nature of the study and would require a large-scale intervention study.

423 **Research implications**

424 The main challenge for the management of PPROM is the choice of antibiotics. According to
425 current guidelines, antibiotics are administered without taking into account exposure to pathogens
426 (2), but this is based on weak evidence (9) (40, 41). Amoxicillin prevents GBS, but it is largely
427 ineffective against *E. coli* and other enterobacterales (24, 35), which are predominant in EONS
428 today (25, 32), and it selects resistant bacteria (25) (42). In the United States, erythromycin (or
429 alternatively azithromycin) is recommended in addition to amoxicillin (8), but macrolides are
430 ineffective on enterobacterales. One approach is prophylaxis with larger spectrum antibiotics (43),
431 however antibiotics contribute to loss of protective *Lactobacillus* species, selection of pathogens,
432 and disruption of the neonatal microbiome (44, 45). An individualized treatment approach in
433 PPROM (46) showed better neonatal outcomes but required invasive sampling by amniocentesis.
434 Antibiotic therapies tailored according to the presence or absence of individual pathogens in the
435 genital tract may be a non-invasive approach, which needs to be evaluated.

436 Perinatal sepsis depends on host-related as well as bacteria-related factors. Choriodecidual
437 inflammatory response is considered as evidence of infection (14) and IL-6 mRNA may be
438 detected by RT-PCR in vaginal secretions (47, 48). Further study is underway in the InSPIRe
439 consortium to investigate inflammatory markers in the vaginal swab samples to predict EONS.

440 Point-of-care testing

441 Consensus lacks regarding vaginal swab testing in PPROM. French guidelines recommend
442 bacterial cultures (2), while some countries limit testing to GBS and others perform no testing at
443 all (49). The utility of vaginal swab samples is limited by a turnover time of 3-4 days. Existing
444 rapid tests are limited to GBS (50). Our findings open the way for a bedside molecular-based test
445 to detect *E. coli* and other important pathogens, and vaginal microbiome markers, which could
446 allow for a case-by-case approach, improving antibiotic stewardship, both for the mother and for
447 the neonate. The other perspectives for rapid testing include obstetrical and neonatal management.
448 Research is ongoing in the InSPIRe consortium to develop a rapid multiplex test.

449 Conclusion

450 In PPROM, metagenomic microbial signatures on maternal vaginal samples improve the
451 prediction of EONS risk, compared with conventional culture. However, since no single
452 laboratory test can entirely predict neonatal infection, clinical decisions should consider a range
453 of clinical and biological criteria.
<table><caption>Table 1. Maternal, pregnancy and neonatal characteristics in PPROM cohort with metagenomic and culture data, N = 272 mothers, 310 neonates</caption><thead><tr><th rowspan="2"></th><th colspan="2">Overall<br>(N = 272)</th><th colspan="2">EONS<br>(N = 20)</th><th colspan="2">No EONS<br>(N = 252)</th><th rowspan="2">p</th></tr><tr><th>n/N</th><th>%</th><th>n/N</th><th>%</th><th>n/N</th><th>%</th></tr></thead><tbody><tr><td>Maternal age, years</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.33</td></tr><tr><td>&lt; 30</td><td>62/272</td><td>22.8</td><td>6/20</td><td>30.0</td><td>56/252</td><td>22.2</td><td></td></tr><tr><td>[30-35]</td><td>117/272</td><td>43.0</td><td>11/20</td><td>55.0</td><td>106/252</td><td>42.1</td><td></td></tr><tr><td>[35-40]</td><td>68/272</td><td>25.0</td><td>2/20</td><td>10.0</td><td>66/252</td><td>26.2</td><td></td></tr><tr><td>≥ 40</td><td>25/272</td><td>9.2</td><td>1/20</td><td>5.0</td><td>24/252</td><td>9.5</td><td></td></tr><tr><td>Body mass index</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.11</td></tr><tr><td>&lt; 18.5</td><td>15/267</td><td>5.6</td><td>1/19</td><td>5.3</td><td>14/248</td><td>5.6</td><td></td></tr><tr><td>[18.5-30]</td><td>199/267</td><td>74.5</td><td>11/19</td><td>57.9</td><td>188/248</td><td>75.8</td><td></td></tr><tr><td>≥ 30</td><td>53/267</td><td>19.8</td><td>7/19</td><td>36.8</td><td>46/248</td><td>18.6</td><td></td></tr><tr><td>Smoking during pregnancy</td><td>19/270</td><td>7.0</td><td>0/20</td><td>0.0</td><td>19/250</td><td>7.6</td><td>0.38</td></tr><tr><td>Nulliparous</td><td>150/272</td><td>55.1</td><td>7/20</td><td>35.0</td><td>143/252</td><td>56.7</td><td>0.06</td></tr><tr><td>History of preterm birth</td><td>40/272</td><td>14.7</td><td>6/20</td><td>30.0</td><td>34/252</td><td>13.5</td><td>0.09</td></tr><tr><td>Twin pregnancy</td><td>39/272</td><td>14.3</td><td>4/20</td><td>20.0</td><td>35/252</td><td>13.9</td><td>0.50</td></tr><tr><td>Diabetes Mellitus</td><td>58/272</td><td>21.3</td><td>4/20</td><td>20.0</td><td>54/252</td><td>21.4</td><td>&gt;.99</td></tr><tr><td>HIV positive</td><td>4/272</td><td>1.5</td><td>0/20</td><td>0.0</td><td>4/252</td><td>1.6</td><td>&gt;.99</td></tr><tr><td>Cerclage</td><td>25/272</td><td>9.2</td><td>7/20</td><td>35.0</td><td>18/252</td><td>7.1</td><td>&lt;.001</td></tr><tr><td>Gestational age at rupture</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.02</td></tr><tr><td>&lt; 28 WG</td><td>50/272</td><td>18.4</td><td>7/20</td><td>35.0</td><td>43/252</td><td>17.1</td><td></td></tr><tr><td>28-31 WG</td><td>45/272</td><td>16.5</td><td>5/20</td><td>25.0</td><td>40/252</td><td>15.9</td><td></td></tr><tr><td>32-33 WG</td><td>40/272</td><td>14.7</td><td>4/20</td><td>20.0</td><td>36/252</td><td>14.3</td><td></td></tr><tr><td>34-36 WG</td><td>137/272</td><td>50.4</td><td>4/20</td><td>20.0</td><td>133/252</td><td>52.8</td><td></td></tr><tr><td>Time from rupture to delivery</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.04</td></tr><tr><td>≤ 24h</td><td>94/272</td><td>34.6</td><td>2/20</td><td>10.0</td><td>92/252</td><td>36.5</td><td></td></tr><tr><td>]24h-7 days]</td><td>122/272</td><td>44.8</td><td>11/20</td><td>55.0</td><td>111/252</td><td>44.1</td><td></td></tr><tr><td>]7-14 days]</td><td>29/272</td><td>10.7</td><td>4/20</td><td>20.0</td><td>25/252</td><td>9.9</td><td></td></tr><tr><td>&gt; 14 days</td><td>27/272</td><td>9.9</td><td>3/20</td><td>15.0</td><td>24/252</td><td>9.5</td><td></td></tr><tr><td>Gestational age at delivery</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.02</td></tr><tr><td>&lt; 28</td><td>36/272</td><td>13.2</td><td>6/20</td><td>30.0</td><td>30/252</td><td>11.9</td><td></td></tr><tr><td>28-31</td><td>40/272</td><td>14.7</td><td>6/20</td><td>30.0</td><td>34/252</td><td>13.5</td><td></td></tr><tr><td>32-33</td><td>32/272</td><td>11.8</td><td>1/20</td><td>5.0</td><td>31/252</td><td>12.3</td><td></td></tr><tr><td>34-36</td><td>142/272</td><td>52.2</td><td>7/20</td><td>35.0</td><td>135/252</td><td>53.6</td><td></td></tr><tr><td>≥ 37</td><td>22/272</td><td>8.1</td><td>0/20</td><td>0.00</td><td>22/252</td><td>8.7</td><td></td></tr><tr><td>Labor type</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.54</td></tr><tr><td>Spontaneous labor</td><td>181/272</td><td>66.5</td><td>12/20</td><td>60.0</td><td>169/252</td><td>67.1</td><td></td></tr><tr><td>Induction</td><td>66/272</td><td>24.3</td><td>5/20</td><td>25.0</td><td>61/252</td><td>24.2</td><td></td></tr><tr><td>Cesarean section without labor</td><td>25/272</td><td>9.2</td><td>3/20</td><td>15.0</td><td>22/252</td><td>8.7</td><td></td></tr><tr><td>Mode of delivery</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.004</td></tr><tr><td>Vaginal</td><td>205/272</td><td>75.4</td><td>9/20</td><td>45.0</td><td>196/252</td><td>77.8</td><td></td></tr></tbody></table>
<table><thead><tr><th rowspan="2"></th><th colspan="2">Overall<br>(N = 272)</th><th colspan="2">EONS<br>(N = 20)</th><th colspan="2">No EONS<br>(N = 252)</th><th rowspan="2">p</th></tr><tr><th>n/N</th><th>%</th><th>n/N</th><th>%</th><th>n/N</th><th>%</th></tr></thead><tbody><tr><td>Caesarean section before labor</td><td>26/272</td><td>9.5</td><td>4/20</td><td>20.0</td><td>22/252</td><td>8.7</td><td></td></tr><tr><td>Caesarean section during labor</td><td>41/272</td><td>15.1</td><td>7/20</td><td>35.0</td><td>34/252</td><td>13.5</td><td></td></tr><tr><td>Fever during labor</td><td>26/267</td><td>9.7</td><td>10/20</td><td>50.0</td><td>16/247</td><td>6.5</td><td><strong>&lt;.001</strong></td></tr><tr><td>Chorioamnionitis, clinical*</td><td>17/265</td><td>6.4</td><td>9/20</td><td>45.0</td><td>8/245</td><td>3.3</td><td><strong>&lt;.001</strong></td></tr><tr><td>Chorioamnionitis, histological</td><td>71/125</td><td>56.8</td><td>14/14</td><td>100.0</td><td>57/111</td><td>51.3</td><td><strong>&lt;.001</strong></td></tr><tr><td>Funicitis</td><td>42/126</td><td>33.3</td><td>9/14</td><td>64.3</td><td>33/112</td><td>29.5</td><td><strong>0.01</strong></td></tr><tr><td>Antibiotics ≤ 48h before delivery</td><td>257/270</td><td>95.2</td><td>20/20</td><td>100.0</td><td>237/250</td><td>94.8</td><td>0.61</td></tr><tr><td>Indication for antibiotics</td><td></td><td></td><td></td><td></td><td></td><td></td><td><strong>0.01</strong></td></tr><tr><td>Clinical signs</td><td>28/257</td><td>10.9</td><td>6/20</td><td>30.0</td><td>22/237</td><td>9.3</td><td></td></tr><tr><td>Prophylaxis</td><td>229/257</td><td>89.1</td><td>14/20</td><td>70.0</td><td>215/237</td><td>90.7</td><td></td></tr><tr><td>Antibiotics used</td><td></td><td></td><td></td><td></td><td></td><td></td><td><strong>&lt;.001</strong></td></tr><tr><td>Amoxicillin or penicillin or macrolide</td><td>190/257</td><td>73.9</td><td>5/20</td><td>25.0</td><td>185/237</td><td>78.1</td><td></td></tr><tr><td>Cephalosporin, carbapenem or aztreonam and/or aminoglycoside**</td><td>65/257</td><td>25.3</td><td>15/20</td><td>75.0</td><td>50/237</td><td>21.1</td><td></td></tr><tr><td>Other</td><td>2/257</td><td>0.8</td><td>0/20</td><td>0.0</td><td>2/237</td><td>0.8</td><td></td></tr><tr><td>Liveborn neonates</td><td>(N = 310)</td><td></td><td>(N = 20)</td><td></td><td>(N = 290)</td><td></td><td></td></tr><tr><td>Gender, male</td><td>161/310</td><td>51.9</td><td>10/20</td><td>50.0</td><td>151/290</td><td>52.1</td><td>0.86</td></tr><tr><td>Apgar score at 5 minutes &lt; 7</td><td>31/306</td><td>10.1</td><td>6/19</td><td>31.6</td><td>25/287</td><td>8.7</td><td><strong>0.007</strong></td></tr><tr><td>Birthweight &lt; 10th centile</td><td>53/310</td><td>17.1</td><td>3/20</td><td>15.0</td><td>50/290</td><td>17.2</td><td>&gt;.99</td></tr><tr><td>NICU admission at birth</td><td>124/309</td><td>40.1</td><td>16/20</td><td>80.0</td><td>108/289</td><td>37.4</td><td><strong>&lt;.001</strong></td></tr></tbody></table>

* Fever + leukocytosis (>15000), fetal tachycardia (>160 bpm), fetid amniotic fluid

** aminoglycosides associated with ampicillin or cephalosporin

SGA: small for gestational age, FGR: fetal growth restriction, WG: weeks of gestation
<table><caption>**Table 2. Risk of EONS following PPROM according to vaginal swab culture results at delivery.** Population with culture and metagenomic data, N = 310 neonates including 20 cases of EONS. Pathogens listed only if present in at least one case of EONS</caption><thead><tr><th></th><th>n/N</th><th>%</th><th>p</th></tr></thead><tbody><tr><td>Group B Streptococcus</td><td></td><td></td><td>&gt;.99</td></tr><tr><td>No</td><td>18/281</td><td>6.4</td><td></td></tr><tr><td>Yes</td><td>2/29</td><td>6.9</td><td></td></tr><tr><td>Escherichia coli</td><td></td><td></td><td>0.07</td></tr><tr><td>No</td><td>11/225</td><td>4.9</td><td></td></tr><tr><td>Yes</td><td>9/85</td><td>10.6</td><td></td></tr><tr><td>Klebsiella pneumoniae</td><td></td><td></td><td>0.13</td></tr><tr><td>No</td><td>17/290</td><td>5.9</td><td></td></tr><tr><td>Yes</td><td>3/20</td><td>15.0</td><td></td></tr><tr><td>Proteus mirabilis</td><td></td><td></td><td>&gt;.99</td></tr><tr><td>No</td><td>20/297</td><td>6.7</td><td></td></tr><tr><td>Yes</td><td>0/13</td><td>0.0</td><td></td></tr><tr><td>Staphylococcus aureus</td><td></td><td></td><td>0.28</td></tr><tr><td>No</td><td>18/294</td><td>6.1</td><td></td></tr><tr><td>Yes</td><td>2/16</td><td>12.5</td><td></td></tr><tr><td>Streptococcus anginosus</td><td></td><td></td><td>&gt;.99</td></tr><tr><td>No</td><td>19/292</td><td>6.5</td><td></td></tr><tr><td>Yes</td><td>1/18</td><td>5.6</td><td></td></tr><tr><td>Enterococcus faecalis</td><td></td><td></td><td>0.18</td></tr><tr><td>No</td><td>18/236</td><td>7.6</td><td></td></tr><tr><td>Yes</td><td>2/74</td><td>2.7</td><td></td></tr><tr><td>Prevotella spp.</td><td></td><td></td><td>0.53</td></tr><tr><td>No</td><td>19/299</td><td>6.3</td><td></td></tr><tr><td>Yes</td><td>1/11</td><td>9.1</td><td></td></tr><tr><td>Gardnerella vaginalis</td><td></td><td></td><td>&gt;.99</td></tr><tr><td>No</td><td>18/278</td><td>6.5</td><td></td></tr><tr><td>Yes</td><td>2/32</td><td>6.2</td><td></td></tr><tr><td>Any anaerobe</td><td></td><td></td><td>0.77</td></tr><tr><td>No</td><td>16/253</td><td>6.3</td><td></td></tr><tr><td>Yes</td><td>4/57</td><td>7.0</td><td></td></tr><tr><td>At least one pathogen</td><td></td><td></td><td>0.11</td></tr><tr><td>No</td><td>4/114</td><td>3.5</td><td></td></tr><tr><td>Yes</td><td>16/196</td><td>8.2</td><td></td></tr><tr><td>Lactobacilli present</td><td></td><td></td><td>0.72</td></tr><tr><td>No</td><td>10/143</td><td>7.0</td><td></td></tr><tr><td>Yes</td><td>10/167</td><td>6.0</td><td></td></tr><tr><td>Nugent Score, conventional</td><td>(n = 203)</td><td></td><td>&gt;.99</td></tr><tr><td>1-3 : normal flora</td><td>11/159</td><td>6.9</td><td></td></tr><tr><td>4-6 : intermediate microbiota</td><td>3/41</td><td>7.3</td><td></td></tr><tr><td>7-10 : vaginosis</td><td>0/3</td><td>0.0</td><td></td></tr></tbody></table>
<table><caption>Table 3. Risk of EONS following PPROM according to vaginal sample metagenomic data at delivery, N = 310 neonates including 20 EONS</caption><thead><tr><th></th><th>n/N</th><th>%</th><th>p</th></tr></thead><tbody><tr><td>Vaginal microbiome score</td><td></td><td></td><td>&lt;.001</td></tr><tr><td>1-3 : normal flora</td><td>1/139</td><td>0.7</td><td></td></tr><tr><td>4-6 : intermediate microbiota</td><td>14/115</td><td>12.2</td><td></td></tr><tr><td>7-10 : vaginosis</td><td>5/56</td><td>8.9</td><td></td></tr><tr><td>Vaginal microbiome score, 2 classes</td><td></td><td></td><td>&lt;.001</td></tr><tr><td>&lt; 4</td><td>1/139</td><td>0.7</td><td></td></tr><tr><td>≥ 4</td><td>19/171</td><td>11.1</td><td></td></tr><tr><td>Major pathogens score*</td><td></td><td></td><td>&lt;.001</td></tr><tr><td>&lt; 2</td><td>5/235</td><td>2.1</td><td></td></tr><tr><td>≥ 2</td><td>15/75</td><td>20.0</td><td></td></tr><tr><td>Score combining vaginal microbiome and major pathogens*</td><td></td><td></td><td>&lt;.001</td></tr><tr><td>&lt; 6</td><td>1/189</td><td>0.5</td><td></td></tr><tr><td>≥ 6</td><td>19/121</td><td>15.7</td><td></td></tr><tr><td>Score combining vaginal microbiome and major* and intermediate** pathogens</td><td></td><td></td><td>&lt;.001</td></tr><tr><td>&lt; 40</td><td>6/252</td><td>2.4</td><td></td></tr><tr><td>≥ 40</td><td>14/58</td><td>24.1</td><td></td></tr><tr><td>Community state types (CST)</td><td></td><td></td><td>0.03</td></tr><tr><td>I</td><td>2/116</td><td>1.7</td><td></td></tr><tr><td>II</td><td>2/13</td><td>15.4</td><td></td></tr><tr><td>III</td><td>4/64</td><td>6.2</td><td></td></tr><tr><td>IV-B</td><td>8/64</td><td>12.5</td><td></td></tr><tr><td>IV-C</td><td>4/45</td><td>8.9</td><td></td></tr><tr><td>V</td><td>0/8</td><td>0.0</td><td></td></tr></tbody></table>

<footnote>*Major pathogens: *E. coli*, *S. agalactiae*, *S. pyogenes*, *S. pneumoniae*</footnote>

<footnote>**Intermediate pathogens: *S. dysgalactiae*, *S. anginosus*, *S. aureus*, *Proteus mirabilias*, *Enterococcus faecalis*, *Haemophilus* spp., *Candida* spp.</footnote>
<table><caption>**Table 4. Risk of Early-onset Neonatal Sepsis in PPROM according to culture and metagenomic scores on maternal vaginal swab at delivery.** Population with culture and metagenomic data, N = 310 neonates including 20 cases of EONS</caption><thead><tr><th></th><th>OR (95% CI)</th><th>p</th><th>Model 1<br>ORa (95% CI)</th><th>p</th><th>Model 2<br>ORa (95% CI)</th><th>p</th></tr></thead><tbody><tr><td>Culture of a major or intermediate pathogen</td><td></td><td>0.12</td><td></td><td>0.45</td><td></td><td></td></tr><tr><td>No</td><td>1 (Ref)</td><td></td><td>1 (Ref)</td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>2.4 (0.8-7.4)</td><td></td><td>1.6 (0.5-5.0)</td><td></td><td></td><td></td></tr><tr><td>Metagenomic score combining vaginal microbiome and major and intermediate pathogens</td><td></td><td>&lt;.001</td><td></td><td></td><td></td><td>&lt;.001</td></tr><tr><td>&lt; 40</td><td>1 (Ref)</td><td></td><td></td><td></td><td>1 (Ref)</td><td></td></tr><tr><td>≥ 40</td><td>12.9 (4.7-35.2)</td><td></td><td></td><td></td><td>8.9 (3.5-22.3)</td><td></td></tr><tr><td>Time from rupture to delivery</td><td></td><td>0.10</td><td></td><td>0.19</td><td></td><td>0.67</td></tr><tr><td>≤ 24h</td><td>1 (Ref)</td><td></td><td>1 (Ref)</td><td></td><td>1 (Ref)</td><td></td></tr><tr><td>]24h-7 days]</td><td>4.9 (1.1-22.5)</td><td></td><td>3.8 (0.9-16.6)</td><td></td><td>2.3 (0.4-11.8)</td><td></td></tr><tr><td>]7-14 days]</td><td>9.0 (1.6-52.1)</td><td></td><td>6.4 (1.1-38.3)</td><td></td><td>3.0 (0.5-16.9)</td><td></td></tr><tr><td>> 14 days</td><td>6.1 (1.0-37.5)</td><td></td><td>4.8 (0.9-26.5)</td><td></td><td>2.2 (0.3-16.2)</td><td></td></tr><tr><td>Gestational age at delivery</td><td></td><td>0.02</td><td></td><td>0.07</td><td></td><td>0.28</td></tr><tr><td>&lt; 28 WG</td><td>4.3 (1.4-13.2)</td><td></td><td>3.2 (0.9-11.1)</td><td></td><td>2.3 (0.6-8.3)</td><td></td></tr><tr><td>28-31 WG</td><td>3.8 (1.2-12.0)</td><td></td><td>3.2 (1.0-10.2)</td><td></td><td>2.1 (0.6-6.7)</td><td></td></tr><tr><td>32-33 WG</td><td>0.6 (0.1-5.1)</td><td></td><td>0.6 (0.1-5.6)</td><td></td><td>0.4 (0.0-4.7)</td><td></td></tr><tr><td>≥ 34 WG</td><td>1 (Ref)</td><td></td><td>1 (Ref)</td><td></td><td>1 (Ref)</td><td></td></tr></tbody></table>
<table><caption>Supplemental Table 1. Risk of EONS following PPROM according to vaginal sample results at delivery, in overall population with culture data, N=490 infants (including 29 EONS). Pathogens listed only if present in at least one case of EONS</caption><thead><tr><th></th><th>n/N</th><th>%</th><th>p</th></tr></thead><tbody><tr><td>Group B Streptococcus</td><td></td><td></td><td>0.74</td></tr><tr><td>No</td><td>23/441</td><td>5.22</td><td></td></tr><tr><td>Yes</td><td>3/49</td><td>6.12</td><td></td></tr><tr><td><em>Escherichia coli</em></td><td></td><td></td><td><strong>0.03</strong></td></tr><tr><td>No</td><td>14/355</td><td>3.94</td><td></td></tr><tr><td>Yes</td><td>12/135</td><td>8.89</td><td></td></tr><tr><td><em>Klebsiella pneumoniae</em></td><td></td><td></td><td>0.43</td></tr><tr><td>No</td><td>23/454</td><td>5.07</td><td></td></tr><tr><td>Yes</td><td>3/36</td><td>8.33</td><td></td></tr><tr><td><em>Staphylococcus aureus</em></td><td></td><td></td><td>0.29</td></tr><tr><td>No</td><td>24/470</td><td>5.11</td><td></td></tr><tr><td>Yes</td><td>2/20</td><td>10.00</td><td></td></tr><tr><td><em>Streptococcus anginosus</em></td><td></td><td></td><td>&gt;.99</td></tr><tr><td>No</td><td>25/463</td><td>5.40</td><td></td></tr><tr><td>Yes</td><td>1/27</td><td>3.70</td><td></td></tr><tr><td><em>Enterococcus faecalis</em></td><td></td><td></td><td>0.23</td></tr><tr><td>No</td><td>23/388</td><td>5.93</td><td></td></tr><tr><td>Yes</td><td>3/102</td><td>2.94</td><td></td></tr><tr><td><em>Prevotella</em> spp.</td><td></td><td></td><td>0.56</td></tr><tr><td>No</td><td>25/475</td><td>5.26</td><td></td></tr><tr><td>Yes</td><td>1/15</td><td>6.67</td><td></td></tr><tr><td><em>Gardnerella vaginalis</em></td><td></td><td></td><td>&gt;.99</td></tr><tr><td>No</td><td>24/444</td><td>5.41</td><td></td></tr><tr><td>Yes</td><td>2/46</td><td>4.35</td><td></td></tr><tr><td>Any anaerobe</td><td></td><td></td><td>&gt;.99</td></tr><tr><td>No</td><td>22/407</td><td>5.41</td><td></td></tr><tr><td>Yes</td><td>4/83</td><td>4.82</td><td></td></tr><tr><td>At least one major pathogen*</td><td></td><td></td><td><strong>0.02</strong></td></tr><tr><td>No</td><td>11/315</td><td>3.49</td><td></td></tr><tr><td>Yes</td><td>15/175</td><td>8.57</td><td></td></tr><tr><td>At least one intermediate pathogen**</td><td></td><td></td><td>0.44</td></tr><tr><td>No</td><td>17/285</td><td>5.96</td><td></td></tr><tr><td>Yes</td><td>9/205</td><td>4.39</td><td></td></tr><tr><td>At least one major or intermediate pathogen</td><td></td><td></td><td><strong>0.045</strong></td></tr><tr><td>No</td><td>5/185</td><td>2.70</td><td></td></tr><tr><td>Yes</td><td>21/305</td><td>6.89</td><td></td></tr><tr><td>Lactobacilli present</td><td></td><td></td><td>&gt;.99</td></tr><tr><td>No</td><td>13/244</td><td>5.33</td><td></td></tr><tr><td>Yes</td><td>13/246</td><td>5.28</td><td></td></tr><tr><td>Nugent Score, conventional</td><td>(n = 300)</td><td></td><td>0.82</td></tr></tbody></table>
<table><thead><tr><th></th><th>n/N</th><th>%</th><th>p</th></tr></thead><tbody><tr><td>1-3 : normal flora</td><td>14/236</td><td>5.93</td><td></td></tr><tr><td>4-6 : intermediate microbiota</td><td>4/60</td><td>6.67</td><td></td></tr><tr><td>7-10 : vaginosis</td><td>0/4</td><td>0.00</td><td></td></tr></tbody></table>

*Major pathogens: *E. coli*, *S. agalactiae*, *S. pyogenes*, *S. pneumoniae*

**Intermediate pathogens: *S. dysgalactiae*, *S. anginosus*, *S. aureus*, *Proteus mirabilis*, *Enterococcus faecalis*, *Haemophilus* spp., *Candida* spp.
<table><caption>**Supplemental Table 2. Risk of Early-onset Neonatal Sepsis in PPROM according to microbiology on overall population with maternal vaginal swab culture at delivery, N=646 neonates, including 26 cases with EONS**</caption><thead><tr><th></th><th>OR (IC 95%)</th><th>p</th><th>aOR (IC 95%)</th><th>p</th></tr></thead><tbody><tr><td>At least one major or intermediate pathogen</td><td></td><td>0.054</td><td></td><td>0.16</td></tr><tr><td>No</td><td>1 (Ref)</td><td></td><td>1 (Ref)</td><td></td></tr><tr><td>Yes</td><td>2.6 (1.0-7.1)</td><td></td><td>2.0 (0.8-5.5)</td><td></td></tr><tr><td>Time from rupture to delivery</td><td></td><td>0.26</td><td></td><td>0.50</td></tr><tr><td>≤ 24h</td><td>1 (Ref)</td><td></td><td>1 (Ref)</td><td></td></tr><tr><td>]24h-7 days]</td><td>2.6 (0.8-8.1)</td><td></td><td>2.0 (0.6-6.0)</td><td></td></tr><tr><td>]7-14 days]</td><td>3.8 (1.0-14.9)</td><td></td><td>2.9 (0.7-12.0)</td><td></td></tr><tr><td>> 14 days</td><td>2.4 (0.6-9.6)</td><td></td><td>1.8 (0.5-7.1)</td><td></td></tr><tr><td>Gestational age at delivery</td><td></td><td>0.02</td><td></td><td>0.06</td></tr><tr><td>&lt; 28 WG</td><td>3.5 (1.3-9.5)</td><td></td><td>2.8 (0.9-8.5)</td><td></td></tr><tr><td>28-31 WG</td><td>3.7 (1.4-9.9)</td><td></td><td>3.4 (1.3-9.1)</td><td></td></tr><tr><td>32-33 WG</td><td>1.1 (0.2-5.3)</td><td></td><td>1.0 (0.2-5.1)</td><td></td></tr><tr><td>≥ 34 WG</td><td>1 (Ref)</td><td></td><td>1 (Ref)</td><td></td></tr></tbody></table>
<table><caption>Supplemental Table 3. Correspondence between the main pathogens detected in maternal vaginal sample cultures at delivery and neonatal cultures in 29 cases of EONS following PPROM</caption><thead><tr><th>Case</th><th>Gestational age at birth, weeks + days</th><th>Main pathogen in vaginal sample</th><th>Pathogen in neonate</th><th>Concordance</th><th>Metagenomic data available</th></tr></thead><tbody><tr><td>1</td><td>30+1</td><td>E. coli</td><td>E. coli</td><td>E. coli</td><td>Yes</td></tr><tr><td>2</td><td>28+1</td><td>E. coli</td><td>E. coli</td><td>E. coli</td><td>Yes</td></tr><tr><td>3</td><td>31+1</td><td>E. coli</td><td>E. coli</td><td>E. coli</td><td>Yes</td></tr><tr><td>4</td><td>33+1</td><td>GBS</td><td>E. coli</td><td>No</td><td>No</td></tr><tr><td>5</td><td>24+3</td><td>No pathogen</td><td>Fusobacterium nucleatum</td><td>No</td><td>Yes</td></tr><tr><td>6</td><td>25+5</td><td>E. coli</td><td>E. coli</td><td>E. coli</td><td>Yes</td></tr><tr><td>7</td><td>28+5</td><td>GBS*</td><td>E. coli</td><td>No</td><td>No</td></tr><tr><td>8</td><td>35+2</td><td>GBS</td><td>Bacteroides sp.</td><td>No</td><td>Yes</td></tr><tr><td>9</td><td>34+0</td><td>K. pneumoniae</td><td>K. pneumoniae</td><td>K. pneumoniae</td><td>Yes</td></tr><tr><td>10</td><td>35+3</td><td>C. albicans</td><td>H. haemolyticus</td><td>No</td><td>Yes</td></tr><tr><td>11</td><td>26+1</td><td>S. aureus<br>S. anginosus,<br>E. faecalis</td><td>U. urealyticum</td><td>No</td><td>Yes</td></tr><tr><td>12</td><td>29+6</td><td>E. coli</td><td>E. coli</td><td>E. coli</td><td>Yes</td></tr><tr><td>13</td><td>28+2</td><td>E. coli</td><td>Prevotella sp.</td><td>No</td><td>No</td></tr><tr><td>14</td><td>26+1</td><td>E. faecalis</td><td>E. faecalis</td><td>E. faecalis</td><td>No</td></tr><tr><td>15</td><td>35+3</td><td>No pathogen</td><td>E. coli</td><td>No</td><td>Yes</td></tr><tr><td>16</td><td>30+5</td><td>E. faecalis</td><td>Citrobacter koseri</td><td>No</td><td>No</td></tr><tr><td>17</td><td>34+2</td><td>E. coli*</td><td>E. coli</td><td>E. coli</td><td>No</td></tr><tr><td>18</td><td>29+5</td><td>E. coli</td><td>E. coli</td><td>E. coli</td><td>Yes</td></tr><tr><td>19</td><td>31+4</td><td>K. pneumoniae</td><td>K. pneumoniae</td><td>K. pneumoniae</td><td>Yes</td></tr><tr><td>20</td><td>26+0</td><td>E. coli</td><td>E. coli</td><td>E. coli</td><td>Yes</td></tr><tr><td>21</td><td>31+4</td><td>GBS*</td><td>GBS</td><td>GBS</td><td>No</td></tr><tr><td>22</td><td>23+5</td><td>E. coli<br>S. aureus*</td><td>S. aureus</td><td>S. aureus</td><td>Yes</td></tr><tr><td>23</td><td>34+1</td><td>E. coli</td><td>E. coli</td><td>E. coli</td><td>No</td></tr><tr><td>24</td><td>34+2</td><td>S. aureus</td><td>N/A</td><td>N/A</td><td>Yes</td></tr><tr><td>25</td><td>26+6</td><td>E. coli</td><td>E. coli</td><td>E. coli</td><td>Yes</td></tr><tr><td>26</td><td>35+3</td><td>E. coli</td><td>E. coli</td><td>E. coli</td><td>No</td></tr><tr><td>27</td><td>33+0</td><td>Gardnerella vaginalis</td><td>S. anginosus</td><td>No</td><td>Yes</td></tr><tr><td>28</td><td>36+0</td><td>E. coli</td><td>N/A</td><td>N/A</td><td>Yes</td></tr><tr><td>29</td><td>36+5</td><td>GBS</td><td>N/A</td><td>N/A</td><td>Yes</td></tr></tbody></table>

<footnote>*Vaginal sample performed prior to delivery</footnote>
Figure captions

Figure 1. Flowchart of InSPIRe cohorts

Figure 2. ROC curve linking the risk of EONS and the score combining vaginal microbiome and major and intermediate pathogens

$$AUC = 0.75 (IC95\% = (0.61-0.90))$$

The black point denotes optimal cut-point value according to the Youden index.

For this threshold (score combining vaginal microbiome and major and intermediate pathogens=40) :

$$Sensitivity = 0.70, Specificity = 0.85, PPV = 0.24, NPV = 0.98$$
**Supplemental file**

InSPIRe Consortium

**Microbiology**

Claire Poyart U 1016 Institut Cochin Bacteria and Perinatality, FHU Prema, Université Paris
Cité, APHP Centre, Streptococci National Reference Center, Cochin

Asmaa Tazi, U 1016 Institut Cochin Cochin Bacteria and Perinatality, FHU Prema Université
Paris Cité, APHP Centre, Streptococci National Reference Center, Cochin

Céline Plainvert, U1016 Institut Cochin Bacteria and Perinatality, FHU Prema, APHP,
Streptococci National Reference Center, Cochin

Luce Landraud, Inserm 1137 IAME Université Paris Cité, APHP Louis Mourier
Microbiology

Clermont Olivier, Inserm 1137 IAME Université Paris Cité

Nathalie Grall, APHP Bichat Microbiology

**Methodology**

Pierre-Yves Ancel, APHP URC-CIC Cochin-Necker Mère-Enfant – U1153 EPOPé, FHU
Prema

Laurence Lecomte, APHP DRCI, FHU Prema

Hendy Abdoul, APHP URC-CIC Cochin-Necker Mère-Enfant, FHU Prema

Jessica Rousseau, Biostatistician, APHP URC-CIC Cochin-Necker Mère-Enfant

**Obstetrics**

Laurent Mandelbrot, APHP Louis Mourier Obstetrics/Gynecology, FHU Prema, Inserm 1137
IAME Université Paris Cité

François Goffinet, APHP Cochin Port-Royal Obstetrics/Gynecology, FHU Prema, U1153
EPOPé, Université Paris Cité

Dominique Luton, APHP Bichat Obstetrics/Gynecology, Université Paris Cité

**Neonatalogy**
Pierre-Henri Jarreau, APHP Cochin Port-Royal, Neonatology, FHU Prema, Université Paris
Cité

Luc Desfrère, APHP Louis Mourier Neonatology, FHU Prema

Lahçene Allal, APHP Bichat Neonatology, FHU Prema

## Metagenomics

Sean Kennedy, Institut Pasteur, Université Paris Cité, Département de biologie
computationnelle, F-75015 Paris, France

Agnes Baud, Institut Pasteur, Université Paris Cité, Département de biologie
computationnelle, F-75015 Paris, France

Kenzo-Hugo Hillion, Institut Pasteur, Université Paris Cité, Département de biologie
computationnelle, F-75015 Paris, France

## Genomics

Céline Méhats, Institut Cochin Inserm U 1016, UMR CNRS 8104, Université Paris Cité,
« Des gamètes à la naissance », Génomique, épigénétique et physiopathologie de la
reproduction, FHU Prema

Frédéric Batteux, Institut Cochin Inserm U 1016, UMR CNRS 8104, Université Paris Cité,
« Des gamètes à la naissance », - Stress oxydant, prolifération cellulaire et inflammation,
FHU Prema

## Program manager

Véronique Tessier, APHP DRCI

## Data monitoring and management

Sinthiya Sivanesan, APHP URC/CIC Necker Cochin, FHU Prema

Hélène Jabbarian, APHP Louis Mourier, URC Paris-Nord, FHU Prema

## Industrial partner

Christophe Pannetier, BforCure

Laura Lesimple, Université Paris Cité, Institut Cochin, Inserm U1016, CNRS UMR8104,
Bacteria and Perinatality team, BforCure
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