Bryn Kemp

Maternal colonization with Streptococcus agalactiae and associated stillbirth and neonatal disease in coastal Kenya

Streptococcus agalactiae (group B streptococcus, GBS) causes neonatal disease and stillbirth, but its burden in sub-Saharan Africa is uncertain. We assessed maternal recto–vaginal GBS colonization (7,967 women), stillbirth and neonatal disease. Whole-genome sequencing was used to determine serotypes, sequence types and phylogeny. We found low maternal GBS colonization prevalence (934/7,967, 12%), but comparatively high incidence of GBS-associated stillbirth and early onset neonatal disease (EOD) in hospital (0.91 (0.25–2.3)/1,000 births and 0.76 (0.25–1.77)/1,000 live births, respectively). However, using a population denominator, EOD incidence was considerably reduced (0.13 (0.07–0.21)/1,000 live births). Treated cases of EOD had very high case fatality (17/36, 47%), especially within 24 h of birth, making under-ascertainment of community-born cases highly likely, both here and in similar facility-based studies. Maternal GBS colonization was less common in women with low socio-economic status, HIV infection and undernutrition, but when GBS-colonized, they were more probably colonized by the most virulent clone, CC17. CC17 accounted for 267/915 (29%) of maternal colonizing (265/267 (99%) serotype III; 2/267 (0.7%) serotype IV) and 51/73 (70%) of neonatal disease cases (all serotype III). Trivalent (Ia/II/III) and pentavalent (Ia/Ib/II/III/V) vaccines would cover 71/73 (97%) and 72/73 (99%) of disease-causing serotypes, respectively. Serotype IV should be considered for inclusion, with evidence of capsular switching in CC17 strains.

Learning-based prediction of gestational age from ultrasound images of the fetal brain

Graphical abstract

Scientific basis for standardization of fetal head measurements by ultrasound: a reproducibility study

To compare the standard methods for ultrasound measurement of fetal head circumference (HC) and biparietal diameter (BPD) (outer‐to‐outer (BPDoo) vs outer‐to‐inner (BPDoi) caliper placement), and compare acquisition of these measurements in transthalamic (TT) vs transventricular (TV) planes.

Single point biochemical measurement algorithm for early diagnosis of ectopic pregnancy.

OBJECTIVES Tubal rupture as a result of an ectopic pregnancy is the leading cause of first trimester maternal mortality. Currently, the diagnosis of ectopic pregnancy depends on transvaginal ultrasound and serial serum measurements of human chorionic gonadotrophin (hCG), which requires follow up. The objective of this study was to examine whether single point measurements at presentation could distinguish between women with ectopic pregnancy, viable pregnancy, and spontaneous miscarriage. DESIGN AND METHODS Serum total hCG (hCGt), hyperglycosylated hCG (hCGh), free beta subunit of hCG (hCGβ), progesterone (P), and CA-125 were measured by chemiluminescence immunoassay over a 3 month period in 441 women presenting at the emergency room with abdominal pain and a positive pregnancy test. Patient outcomes were followed and confirmed by histology. 65 samples were excluded due to poor sample storage, or lost to follow up. RESULTS The pregnancy outcomes were 175 viable pregnancies, 175 spontaneous miscarriages, and 26 ectopic pregnancies. A serum hCGt <3736 mIU/mL cut off was 100% sensitive, with 76% specificity, for distinguishing ectopic pregnancy from viable pregnancy; but did not differentiate spontaneous miscarriage. Serum CA125 <41.98 U/mL produced 100% sensitivity and 43% specificity in distinguishing ectopic pregnancy from spontaneous miscarriage. Sequential application of hCGt and CA-125 cut off followed by ultrasound could detect 100% of ectopic pregnancies with 87% specificity for all intrauterine pregnancies. CONCLUSION The combination of serum hCGt <3736 mIU/mL, followed by CA125 <41.98 U/mL is a promising algorithm for detecting all ectopic pregnancy at initial presentation.

Towards optimising local reviews of severe incidents in maternity care: messages from a comparison of local and external reviews

Background Detailed local case review is commonly used as a strategy to improve care. However, recent reports have highlighted concerns over quality of local reviews in maternity care. The aim of this project was to describe the methods used for conducting local reviews of care of women with severe maternal morbidity, and to compare lessons identified for future care through external and local reviews. Methods Thirty-three anonymised clinical records from women with severe maternal morbidities were obtained, together with the report of the local review of their care. The methodology used for the local reviews was described, including specific tools used, team members involved, their disciplines, report format and whether an action plan with recommendations for audit was produced. Multidisciplinary external reviewers considered the records using a standard confidential enquiry approach. A thematic analysis of lessons learned from the two approaches was undertaken. Results A formal report of the local review was produced for 11/33 cases; 4 of these used root cause analysis. A further 12 local reviews consisted of a group discussion with output noted in a spreadsheet; 5 consisted of a timeline with good practice points and 5 had no formal review. Patients were involved in five local reviews; only one was multidisciplinary. Action plans were recorded in 14 local reviews; 3 of these included a recommendation to audit the proposed changes. External reviews identified additional messages for care and highlighted aspects of good care in every case, whereas only 55% (n=18) of local reviews identified good care (p<0.0005). Conclusions The quality of local reviews can clearly be improved. Very few of the reviews involved patients. Local reviews should be multidisciplinary, generate an action plan, and the implementation of recommendations should be audited. Improvements in local reviews may be achieved by standardised training or development of national protocols.

Predicting Fetal Neurodevelopmental Age from Ultrasound Images

We propose an automated framework for predicting age and neurodevelopmental maturation of a fetus based on 3D ultrasound (US) brain image appearance. A topology-preserving manifold representation of the fetal skull enabled design of bespoke scale-invariant image features. Our regression forest model used these features to learn a mapping from age-related sonographic image patterns to fetal age and development. The Sylvian Fissure was identified as a critical region for accurate age estimation, and restricting the search space to this anatomy improved prediction accuracy on a set of 130 healthy fetuses (error ± 3.8 days; r = 0.98 performing the best current clinical method. Our framework remained robust when applied to a routine clinical population.