Defining normal inflammatory marker and vital sign responses to suspected bloodstream infection in adults with positive and negative blood cultures

Background Patients respond differently to bloodstream infection (BSI) and associated antibiotic treatment, for many reasons, including different causative pathogens, sources of infection, and patient characteristics. This heterogeneity can hamper use of different clinical parameters to track treatment response as the same absolute values, or even change from presentation, may have different implications, depending on the expected trajectory, which is often incompletely understood. Methods We included patients ≥16y from Oxford University Hospitals (01-January-2016 to 28-June-2021) with any blood culture taken, grouping cultures into suspected BSI episodes (14-day de-duplication). We used linear and latent class mixed models to estimate trajectories in C-reactive protein (CRP), white blood count, heart rate, respiratory rate and temperature and identify subgroups with heterogenous CRP responses. Centile charts for expected CRP responses were constructed via the lambda-mu-sigma method. Findings 88,348 suspected BSI episodes occurred in 60,647 adults; 6,910(7.8%) were culture-positive with a probable pathogen (1,914[2.2%] Gram-positive, 3,736[4.2%] Gram-negative, 1,260[1.4%] other pathogens/polymicrobial), 4,307(4.9%) contained potential contaminants, and 77,131(87.3%) were culture-negative. Overall, CRP levels generally peaked between day 1-2 after blood culture collection, with varying responses for different pathogens and infection sources in adjusted models (interaction p<0.0001). We identified five different CRP trajectory subgroups: peak on day 1 (36,091;46.3%) or 2 (4,529;5.8%), slow recovery (10,666;13.7%), peak on day 6 (743;1.0%), and low response (25,928;33.3%). 42,818(63.5%) culture-negative vs. 5,879(89.6%) pathogen-culture-positive episodes had acute response (day 1-2 peak/slow recovery). Centile reference charts constructed from those peaking on day 1-2 showed the same post-presentation CRP values and change from presentation reflected different responses depending on patients’ initial values. Interpretation Although infection sources and pathogens are associated with varying responses to BSI, there is distinct underlying heterogeneity in responses. The centile reference charts developed could facilitate more precise tracking of recovery, enable identification of patients not recovering as expected, and help personalise infection management. Evidence before this study We searched PubMed up to 28 June 2023, for published English articles with the terms “response” AND (“pattern” OR “trend” OR “trajector*”) AND (“bloodstream infection” OR “sepsis”). No studies described pathogen-specific response trajectories for laboratory tests and vital signs. Several studies identified sepsis sub-phenotypes using group-based trajectory modelling based on trajectories of vital signs, white blood cell and Sequential Organ Failure Assessment score. Specifically, three studies identified four temperature trajectory subgroups using measurement within first 72h: “hyperthermic, slow resolvers”, “hyperthermic, fast resolvers”, “normothermic”, and “hypothermic”. One study identified seven different systolic blood pressure trajectory subgroups using measurements within 10h after hospitalisation and investigated their association with hospital mortality. One study identified seven white blood cell (WBC) count trajectories over the first seven days in the ICU and concluded rising trajectory was independently associated with increased mortality compared with the stable trajectory. Another study found four sub-phenotypes based on four different longitudinal vital signs from the first 8h of hospitalisation, including temperature, heart rate, respiratory rate, systolic and diastolic blood pressure. Several studies used Sequential Organ Failure Assessment score to identify trajectory subgroups, and they identified four or five subgroups using data from the first 72h or first 8 days. There were no published studies estimating expected C-reactive protein (CRP) response in standard responders. Added value of this study To our knowledge, this is the first study to characterise pathogen-specific and infection source-specific response trajectories of multiple clinical parameters, including CRP, WBC count, heart rate, respiratory rate, and temperature. We identified five different CRP trajectory subgroups and found that 42,818 (63.5%) of culture-negative vs. 5,879 (89.6%) of pathogen-culture-positive episodes had acute response, i.e. a peak in CRP on day 1 or 2 or a slow recovery, and that these CRP subgroups had equivalent parallel responses for the other clinical parameters. Centile reference charts (analogous to paediatric growth charts) were created based on the standard CRP responders (i.e., a peak in CRP on day 1 or 2, assuming that these reflected “normal” response to effective antibiotics). These can be used to standardise assessment of infection progression and treatment response in patients with suspected bloodstream infection given the heterogeneity in these responses. These reference charts could be useful to guide management independent of microbiological test results, e.g., prior to culture results becoming available. Implications of all the available evidence Patient characteristics and host responses are heterogeneous, both initially at presentation and throughout responses to infection, making it challenging to define a single “normal” response to culture-positive and culture-negative suspected bloodstream infection. By applying centile-based methods to large-scale electronic health records, we provide a visually intuitive means of assessing biomarker response, potentially aiding clinical decisions by allowing individual-level observations to be assessed against evidence-based references for expected recovery in patients treated with effective antibiotics, taking into account individual-level heterogeneity. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare Associated Infections and Antimicrobial Resistance at Oxford University in partnership with the UK Health Security Agency (NIHR200915), and the NIHR Biomedical Research Centre, Oxford. DWE is a Big Data Institute Robertson Fellow. ASW is an NIHR Senior Investigator. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, the Department of Health or the UK Health Security Agency. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The National Research Ethics Service South Central Oxford C Research Ethics Committee (19/SC/0403) and the national Confidentiality Advisory Group (19/CAG/0144) gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data analysed are available from the Infections in Oxfordshire Research Database (https://oxfordbrc.nihr.ac.uk/research-themes/modernising-medical-microbiology-and-big-infection-diagnostics/infections-in-oxfordshire-research-database-iord/), subject to an application and research proposal meeting on the ethical and governance requirements of the Database.