An evaluation into the use of procalcitonin levels as a biomarker of bacterial sepsis to aid the management of intrapartum pyrexia and chorioamnionitis.

BACKGROUND: Procalcitonin is an established biomarker for bacterial sepsis in the nonpregnant population with better diagnostic and prognostic value for bacterial infections. OBJECTIVE: This study aimed to evaluate whether procalcitonin levels could be used in the diagnosis and management of intrapartum sepsis in women and their neonates suspected of intrapartum bacterial sepsis. STUDY DESIGN: A prospective observational cohort study was conducted at the University Hospitals of Bristol and Weston NHS Foundation Trust. Overall, 117 women and their neonates managed for suspected intrapartum sepsis from June 2020 to October 2020 were included. Procalcitonin levels were measured in addition to routine biomarkers white cell count and C-reactive protein in women and their neonates during the initial septic screen and follow-up blood samples. The placentas underwent detailed histopathology. Maternal and neonatal parameters were used to categorize cases into "high-suspicion bacterial sepsis," "equivocal bacterial sepsis," and "low-suspicion bacterial sepsis." The Kruskal-Wallis test was used to compare categories with biomarker values and placental histology scores. RESULTS: Procalcitonin level was increased in 6 women in the initial septic screen sample, compared with 100 women with an increased C-reactive protein level. There was a significant difference in maternal postnatal procalcitonin results between "high-suspicion bacterial sepsis" and "low-suspicion bacterial sepsis" categories (P=.004). Moreover, 71.2% of placentas showed varying degrees of chorioamnionitis. CONCLUSION: In our cohort of women, 94.6% had normal procalcitonin levels while in labor at the time of the septic screen, consistent with the low number of confirmed bacteremia. The result provided a basis that procalcitonin may complement clinical judgment and interpretation of already used prognostic and diagnostic tests, improving patient care in the management of intrapartum sepsis.

Research traceability using provenance services for biomedical analysis.

We outline the approach being developed in the neuGRID project to use provenance management techniques for the purposes of capturing and preserving the provenance data that emerges in the specification and execution of workflows in biomedical analyses. In the neuGRID project a provenance service has been designed and implemented that is intended to capture, store, retrieve and reconstruct the workflow information needed to facilitate users in conducting user analyses. We describe the architecture of the neuGRID provenance service and discuss how the CRISTAL system from CERN is being adapted to address the requirements of the project and then consider how a generalised approach for provenance management could emerge for more generic application to the (Health)Grid community.

Providing traceability for neuroimaging analyses.

INTRODUCTION: With the increasingly digital nature of biomedical data and as the complexity of analyses in medical research increases, the need for accurate information capture, traceability and accessibility has become crucial to medical researchers in the pursuance of their research goals. Grid- or Cloud-based technologies, often based on so-called Service Oriented Architectures (SOA), are increasingly being seen as viable solutions for managing distributed data and algorithms in the bio-medical domain. For neuroscientific analyses, especially those centred on complex image analysis, traceability of processes and datasets is essential but up to now this has not been captured in a manner that facilitates collaborative study. PURPOSE AND METHOD: Few examples exist, of deployed medical systems based on Grids that provide the traceability of research data needed to facilitate complex analyses and none have been evaluated in practice. Over the past decade, we have been working with mammographers, paediatricians and neuroscientists in three generations of projects to provide the data management and provenance services now required for 21st century medical research. This paper outlines the finding of a requirements study and a resulting system architecture for the production of services to support neuroscientific studies of biomarkers for Alzheimer's disease. RESULTS: The paper proposes a software infrastructure and services that provide the foundation for such support. It introduces the use of the CRISTAL software to provide provenance management as one of a number of services delivered on a SOA, deployed to manage neuroimaging projects that have been studying biomarkers for Alzheimer's disease. CONCLUSIONS: In the neuGRID and N4U projects a Provenance Service has been delivered that captures and reconstructs the workflow information needed to facilitate researchers in conducting neuroimaging analyses. The software enables neuroscientists to track the evolution of workflows and datasets. It also tracks the outcomes of various analyses and provides provenance traceability throughout the lifecycle of their studies. As the Provenance Service has been designed to be generic it can be applied across the medical domain as a reusable tool for supporting medical researchers thus providing communities of researchers for the first time with the necessary tools to conduct widely distributed collaborative programmes of medical analysis.