PLUS-IS-LESS project: Procalcitonin and Lung UltraSonography-based antibiotherapy in patients with Lower rESpiratory tract infection in Swiss Emergency Departments: study protocol for a pragmatic stepped-wedge cluster-randomized trial
Cécile Bessat,
Roland Bingisser,
Markus Schwendinger,
Tim Bulaty,
Yvan Fournier,
Vincent Della Santa,
Magali Pfeil,
Dominique Schwab,
Jörg D. Leuppi,
Nicolas Geigy,
Stephan Steuer,
Friedemann Roos,
Michael Christ,
Adriana Sirova,
Tanguy Espejo,
Henk Riedel,
Alexandra Atzl,
Fabian Napieralski,
Joachim Marti,
Giulio Cisco,
Rose-Anna Foley,
Melinée Schindler,
Mary-Anne Hartley,
Aurélie Fayet,
Elena Garcia,
Isabella Locatelli,
Werner C. Albrich,
Olivier Hugli,
Noémie Boillat-Blanco,
for the PLUS-IS-LESS study group
Affiliations
Cécile Bessat
Infectious Diseases Service, University Hospital of Lausanne and University of Lausanne
Roland Bingisser
Emergency Department, University Hospital of Basel
Markus Schwendinger
Emergency Department, Cantonal Hospital of Baden
Tim Bulaty
Emergency Department, Cantonal Hospital of Baden
Yvan Fournier
Emergency Department, Intercantonal Hospital of Broye
Vincent Della Santa
Emergency Department, Hospital of Neuchâtel
Magali Pfeil
Emergency Department, Hospital Riviera-Chablais
Dominique Schwab
Emergency Department, Hospital Riviera-Chablais
Jörg D. Leuppi
Emergency Department and University Medicine, Cantonal Hospital Baselland
Nicolas Geigy
Emergency Department and University Medicine, Cantonal Hospital Baselland
Stephan Steuer
Emergency Department, St Claraspital
Friedemann Roos
Emergency Department, St Claraspital
Michael Christ
Emergency Department, Cantonal Hospital of Lucerne
Adriana Sirova
Emergency Department, Cantonal Hospital of Lucerne
Tanguy Espejo
Emergency Department, University Hospital of Basel
Henk Riedel
Emergency Department, University Hospital of Basel
Alexandra Atzl
Emergency Department, Cantonal Hospital of St Gallen
Fabian Napieralski
Emergency Department, Cantonal Hospital of St Gallen
Joachim Marti
Health Economics and Policy Unit, Department of Epidemiology and Health Systems, Centre for Primary Care and Public Health (Unisanté), University of Lausanne
Giulio Cisco
Health Economics and Policy Unit, Department of Epidemiology and Health Systems, Centre for Primary Care and Public Health (Unisanté), University of Lausanne
Rose-Anna Foley
Qualitative research platform, social sciences sector, Department of Epidemiology and Health Services, Centre for Primary Care and Public Health (Unisanté), University of Lausanne
Melinée Schindler
Qualitative research platform, social sciences sector, Department of Epidemiology and Health Services, Centre for Primary Care and Public Health (Unisanté), University of Lausanne
Mary-Anne Hartley
Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL)
Aurélie Fayet
Clinical Research Center (CRC), University Hospital of Lausanne and University of Lausanne
Elena Garcia
Emergency Department, University Hospital of Lausanne and University of Lausanne
Isabella Locatelli
Health Economics and Policy Unit, Department of Epidemiology and Health Systems, Centre for Primary Care and Public Health (Unisanté), University of Lausanne
Werner C. Albrich
Division of Infectious Diseases & Hospital Epidemiology, Cantonal Hospital St Gallen
Olivier Hugli
Emergency Department, University Hospital of Lausanne and University of Lausanne
Noémie Boillat-Blanco
Infectious Diseases Service, University Hospital of Lausanne and University of Lausanne
Abstract Background Lower respiratory tract infections (LRTIs) are among the most frequent infections and a significant contributor to inappropriate antibiotic prescription. Currently, no single diagnostic tool can reliably identify bacterial pneumonia. We thus evaluate a multimodal approach based on a clinical score, lung ultrasound (LUS), and the inflammatory biomarker, procalcitonin (PCT) to guide prescription of antibiotics. LUS outperforms chest X-ray in the identification of pneumonia, while PCT is known to be elevated in bacterial and/or severe infections. We propose a trial to test their synergistic potential in reducing antibiotic prescription while preserving patient safety in emergency departments (ED). Methods The PLUS-IS-LESS study is a pragmatic, stepped-wedge cluster-randomized, clinical trial conducted in 10 Swiss EDs. It assesses the PLUS algorithm, which combines a clinical prediction score, LUS, PCT, and a clinical severity score to guide antibiotics among adults with LRTIs, compared with usual care. The co-primary endpoints are the proportion of patients prescribed antibiotics and the proportion of patients with clinical failure by day 28. Secondary endpoints include measurement of change in quality of life, length of hospital stay, antibiotic-related side effects, barriers and facilitators to the implementation of the algorithm, cost-effectiveness of the intervention, and identification of patterns of pneumonia in LUS using machine learning. Discussion The PLUS algorithm aims to optimize prescription of antibiotics through improved diagnostic performance and maximization of physician adherence, while ensuring safety. It is based on previously validated tests and does therefore not expose participants to unforeseeable risks. Cluster randomization prevents cross-contamination between study groups, as physicians are not exposed to the intervention during or before the control period. The stepped-wedge implementation of the intervention allows effect calculation from both between- and within-cluster comparisons, which enhances statistical power and allows smaller sample size than a parallel cluster design. Moreover, it enables the training of all centers for the intervention, simplifying implementation if the results prove successful. The PLUS algorithm has the potential to improve the identification of LRTIs that would benefit from antibiotics. When scaled, the expected reduction in the proportion of antibiotics prescribed has the potential to not only decrease side effects and costs but also mitigate antibiotic resistance. Trial registration This study was registered on July 19, 2022, on the ClinicalTrials.gov registry using reference number: NCT05463406. Trial status Recruitment started on December 5, 2022, and will be completed on November 3, 2024. Current protocol version is version 3.0, dated April 3, 2023.