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.

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.

The potential clinical value of pairing procalcitonin and lung ultrasonography to guide antibiotic therapy in patients with community-acquired pneumonia: a narrative review.

INTRODUCTION: Lower respiratory tract infections (LRTIs) are among the most frequent infections and are prone to inappropriate antibiotic treatments. This results from a limited accuracy of diagnostic tools in identifying bacterial pneumonia. Lung ultrasound (LUS) has excellent sensitivity and specificity in diagnosing pneumonia. Additionally, elevated procalcitonin (PCT) levels correlate with an increased likelihood of bacterial infection. LUS and PCT appear to be complementary in identifying patients with bacterial pneumonia who are likely to benefit from antibiotics. AREAS COVERED: This narrative review aims to summarize the current evidence for LUS to diagnose pneumonia, for PCT to guide antibiotic therapy and the clinical value of pairing both tools. EXPERT OPINION: LUS has excellent diagnostic accuracy for pneumonia in different settings, regardless of the examiner's experience. PCT guidance safely reduces antibiotic prescription in LRTIs. The combination of both tools has demonstrated an enhanced accuracy in the diagnosis of pneumonia, including CAP in the ED and VAP in the ICU, but randomized controlled studies need to validate the clinical impact of a combined approach.

Comparison of the 22nd World Health Organization Model List of Essential Medicines with the explicit criteria for the treatment of chronicity in elderly patients.

OBJECTIVES: This study analysed whether the Model List of Essential Medicines is suitable for elderly patients. Furthermore, it investigated the specific issues that should be considered when prescribing a drug and which drugs should be added to improve the list according to the explicit criteria guidelines. METHODS: A qualitative descriptive review was performed comparing the explicit criteria guidelines of Beers 2019, Laroche, McLeod, NORGEP, PRISCUS, STOPP/START 2014 and Winit-Watjana with the 22nd edition of the Model List of Essential Medicines. RESULTS: The Model List of Essential Medicines has 458 drugs. Depending on the explicit criteria considered, there were different numbers of potentially inappropriate medications and potential prescribing omissions. When all explicit criteria were combined, a total of 73 medicines were classified as potentially inappropriate. Using the STOPP/START criteria, 46 potential prescribing omissions were detected. According to these explicit criteria, the Model List of Essential Medicines appeared to lack some medicines. CONCLUSIONS: Explicit criteria guidelines have different potential for detecting potentially inappropriate medications. Our findings suggest that some drugs should be added to the next edition of the Model List of Essential Medicines to cover some therapeutic gaps.

Large-scale implementation of electronic Integrated Management of Childhood Illness (eIMCI) at the primary care level in Burkina Faso: a qualitative study on health worker perception of its medical content, usability and impact on antibiotic prescription and resistance.

BACKGROUND: Electronic clinical decision algorithms (eCDAs) that guide clinicians during patient management are being deployed in resource-limited settings to improve the quality of care and rational use of medicines (especially antimicrobials). Little is known on how local clinicians perceive the use and impact of these tools in their daily practice. This study investigates clinician insights on an eIMCI tool. Specifically, we report their views on its medical content, assess their knowledge on microbes, antimicrobials and the development of resistance. METHODS: This qualitative study was conducted in the frame of a large-scale implementation in Burkina Faso of an eIMCI tool developed by the Swiss NGO Terre des hommes. Twelve in-depth interviews and 2 focus-group discussions were conducted including 21 health workers from 10 primary care facilities. Emerging themes were identified using qualitative data analysis software. RESULTS: eIMCI users expressed a high level of satisfaction, slowness of the tablet was perceived as the major inconvenience limiting uptake. Several frequent illnesses were identified as missing in the algorithm along with guidance for fever without focus. When asked about existing types of microbes, 9 and 4 out of 21 participants could mention bacteria and virus respectively; only 5 correctly answered that antibiotics had no action on viral disease and 6 mentioned the risk of antibiotic resistance. Level of knowledge was higher in nurses than in less trained health workers. The tool was perceived as improving patient management and the rational use of antibiotics. Positive changes in health facility organisation were reported, such as task shifting and improved triage. eIMCI was also perceived as a learning tool, and users expressed a strong desire to expand the geographic and temporal scope of the intervention. CONCLUSION: The use of eICMI was widely accepted and perceived as a powerful tool guiding daily practice. Findings suggest that it has positive effects on the health care system beyond the quality of consultation. To support large uptake and sustainability, better training of health workers in infectiology is essential and the medical content of eIMCI should be optimized to include frequent diseases and, for each of them, the appropriate management plan.