PROcalcitonin and NEWS2 evaluation for Timely identification of sepsis and Optimal use of antibiotics in the emergency department (PRONTO): protocol for a multicentre, open-label, randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Sepsis is a common, potentially life-threatening complication of infection. The optimal treatment for sepsis includes prompt antibiotics and intravenous fluids, facilitated by its early and accurate recognition. Currently, clinicians identify and assess severity of suspected sepsis using validated clinical scoring systems. In England, the National Early Warning Score 2 (NEWS2) has been mandated across all National Health Service (NHS) trusts and ambulance organisations. Like many clinical scoring systems, NEWS2 should not be used without clinical judgement to determine either the level of acuity or a diagnosis. Despite this, there is a tendency to overemphasise the score in isolation in patients with suspected infection, leading to the overprescription of antibiotics and potentially treatment-related complications and rising antimicrobial resistance. The biomarker procalcitonin (PCT) has been shown to be useful in specific circumstances to support appropriate antibiotics prescribing by identifying bacterial infection. PCT is not routinely used in the care of undifferentiated patients presenting to emergency departments (EDs), and the evidence base of its optimal usage is poor. The PROcalcitonin and NEWS2 evaluation for Timely identification of sepsis and Optimal (PRONTO) study is a randomised controlled trial (RCT) in adults with suspected sepsis presenting to the ED to compare standard clinical management based on NEWS2 scoring plus PCT-guided risk assessment with standard clinical management based on NEWS2 scoring alone and compare if this approach reduces prescriptions of antibiotics without increasing mortality. METHODS AND ANALYSIS: PRONTO is a parallel two-arm open-label individually RCT set in up to 20 NHS EDs in the UK with a target sample size of 7676 participants. Participants will be randomised in a ratio of 1:1 to standard clinical management based on NEWS2 scoring or standard clinical management based on NEWS2 scoring plus PCT-guided risk assessment. We will compare whether the addition of PCT measurement to NEWS2 scoring can lead to a reduction in intravenous antibiotic initiation in ED patients managed as suspected sepsis, with at least no increase in 28-day mortality compared with NEWS2 scoring alone (in conjunction with local standard care pathways). PRONTO has two coprimary endpoints: initiation of intravenous antibiotics at 3 hours (superiority comparison) and 28-day mortality (non-inferiority comparison). The study has an internal pilot phase and group-sequential stopping rules for effectiveness and futility/safety, as well as a qualitative substudy and a health economic evaluation. ETHICS AND DISSEMINATION: The trial protocol was approved by the Health Research Authority (HRA) and NHS Research Ethics Committee (Wales REC 2, reference 20/WA/0058). In England and Wales, the law allows the use of deferred consent in approved research situations (including ED studies) where the time dependent nature of intervention would not allow true informed consent to be obtained. PRONTO has approval for a deferred consent process to be used. Findings will be disseminated through peer-reviewed journals and presented at scientific conferences. TRIAL REGISTRATION NUMBER: ISRCTN54006056.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.034 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.008 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.065 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".