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Cook A, Atkinson A, Kronenberg A, Agyeman PKA, Schlapbach LJ, Berger C, Bielicki JA. Estimating antibiotic coverage from linked microbiological and clinical data from the Swiss Paediatric Sepsis Study to support empiric antibiotic regimen selection. Front Pediatr 2023; 11:1124165. [PMID: 37252038 PMCID: PMC10213904 DOI: 10.3389/fped.2023.1124165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 03/20/2023] [Indexed: 05/31/2023] Open
Abstract
In light of rising antibiotic resistance, better methods for selection of empiric antibiotic treatment based on clinical and microbiological data are needed. Most guidelines target specific clinical infections, and variably adjust empiric antibiotic selection by certain patient characteristics. Coverage estimates reflect the probability that an antibiotic regimen will be active against the causative pathogen once confirmed and can provide an objective basis for empiric regimen selection. Coverage can be estimated for specific infections using a weighted incidence syndromic combination antibiograms (WISCAs) framework. However, no comprehensive data combining clinical and microbiological data for specific clinical syndromes are available in Switzerland. We therefore describe estimating coverage from semi-deterministically linked routine microbiological and cohort data of hospitalised children with sepsis. Coverage estimates were generated for each hospital and separately pooling data across ten contributing hospitals for five pre-defined patient risk groups. Data from 1,082 patients collected during the Swiss Paediatric Sepsis Study (SPSS) 2011-2015 were included. Preterm neonates were the most commonly represented group, and half of infants and children had a comorbidity. 67% of neonatal sepsis cases were hospital-acquired late-onset whereas in children 76% of infections were community-acquired. Escherichia coli, Coagulase-negative staphylococci (CoNS) and Staphylococcus aureus were the most common pathogens. At all hospitals, ceftazidime plus amikacin regimen had the lowest coverage, and coverage of amoxicillin plus gentamicin and meropenem were generally comparable. Coverage was improved when vancomycin was included in the regimen, reflecting uncertainty about the empirically targeted pathogen spectrum. Children with community-acquired infections had high coverage overall. It is feasible to estimate coverage of common empiric antibiotic regimens from linked data. Pooling data by patient risk groups with similar expected pathogen and susceptibility profiles may improve coverage estimate precision, supporting better differentiation of coverage between regimens. Identification of data sources, selection of regimens and consideration of pathogens to target for improved empiric coverage is important.
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Affiliation(s)
- Aislinn Cook
- Centre for Neonatal and Paediatric Infection, St. George’s University of London, London, United Kingdom
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Andrew Atkinson
- Pediatric Research Centre, University Children's Hospital Basel, Basel, Switzerland
| | - Andreas Kronenberg
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Philipp K. A. Agyeman
- Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Luregn J. Schlapbach
- Department of Intensive Care and Neonatology, Children's Research Center, University children's Hospital Zürich, Zürich, Switzerland
| | | | - Christoph Berger
- Division of Infectious Diseases and Hospital Epidemiology, Children’s Research Center, University Children’s Hospital Zurich, Zurich, Switzerland
| | - Julia Anna Bielicki
- Centre for Neonatal and Paediatric Infection, St. George’s University of London, London, United Kingdom
- Pediatric Research Centre, University Children's Hospital Basel, Basel, Switzerland
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Whitney L, Armstrong‐James D, Lyster HS, Reed AK, Dunning J, Nwankwo L, Cheong J. Antifungal stewardship in solid‐organ transplantation: What is needed? Transpl Infect Dis 2022; 24:e13894. [DOI: 10.1111/tid.13894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 05/15/2022] [Indexed: 11/06/2022]
Affiliation(s)
| | | | - Haifa S. Lyster
- Department of Heart and Lung Transplantation The Royal Brompton and Harefield NHS Foundation Trust, Harefield Hospital Harefield Middlesex UK
| | - Anna K. Reed
- Department of Lung Transplantation Royal Brompton and Harefield National Health Service (NHS) Foundation Trust London UK
| | - John Dunning
- Department of Lung Transplantation Royal Brompton and Harefield National Health Service (NHS) Foundation Trust London UK
| | - Lisa Nwankwo
- Department of Pharmacy Royal Brompton & Harefield NHS Foundation Trust London UK
| | - Jamie Cheong
- Department of Pharmacy Royal Brompton & Harefield NHS Foundation Trust London UK
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Kherabi Y, Messika J, Peiffer‐Smadja N. Machine learning, antimicrobial stewardship, and solid organ transplantation: Is this the future? Transpl Infect Dis 2022; 24:e13957. [DOI: 10.1111/tid.13957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 08/15/2022] [Accepted: 08/17/2022] [Indexed: 11/05/2022]
Affiliation(s)
- Yousra Kherabi
- Infectious and Tropical Diseases Department Bichat‐Claude Bernard Hospital Assistance Publique‐Hôpitaux de Paris Paris France
| | - Jonathan Messika
- Université Paris Cité AP‐HP Bichat‐Claude Bernard Hospital Pneumologie B et Transplantation Pulmonaire Paris France
| | - Nathan Peiffer‐Smadja
- Infectious and Tropical Diseases Department Bichat‐Claude Bernard Hospital Assistance Publique‐Hôpitaux de Paris Paris France
- Université Paris Cité and Université Sorbonne Paris Nord Inserm IAME Paris France
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Assadi A, Laussen PC, Freire G, Ghassemi M, Trbovich PC. Effect of clinical decision support systems on emergency medicine physicians' decision-making: A pilot scenario-based simulation study. Front Pediatr 2022; 10:1047202. [PMID: 36589162 PMCID: PMC9798305 DOI: 10.3389/fped.2022.1047202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 11/17/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Children with congenital heart disease (CHD) are predisposed to rapid deterioration in the face of common childhood illnesses. When they present to their local emergency departments (ED) with acute illness, rapid and accurate diagnosis and treatment is crucial to recovery and survival. Previous studies have shown that ED physicians are uncomfortable caring for patients with CHD and there is a lack of actionable guidance to aid in their decision making. To support ED physicians' key decision components (sensemaking, anticipation, and managing complexity) when managing CHD patients, a Clinical Decision Support System (CDSS) was previously designed. This pilot study evaluates the effect of this CDSS on ED physicians' decision making compared to usual care without clinical decision support. METHODS In a pilot scenario-based simulation study with repeated measures, ED physicians managed mock CHD patients with and without the CDSS. We compared ED physicians' CHD-specific and general decision-making processes (e.g., recognizing sepsis, starting antibiotics, and managing symptoms) with and without the use of CDSS. The frequency of participants' utterances related to each key decision components of sensemaking, anticipation, and managing complexity were coded and statistically analyzed for significance. RESULTS Across all decision-making components, the CDSS significantly increased ED physicians' frequency of "CHD specific utterances" (Mean = 5.43, 95%CI: 3.7-7.2) compared to the without CDSS condition (Mean = 2.05, 95%CI: 0.3-3.8) whereas there was no significant difference in frequencies of "general utterances" when using CDSS (Mean = 4.62, 95%CI: 3.1-6.1) compared to without CDSS (Mean = 5.14 95%CI: 4.4-5.9). CONCLUSION A CDSS that integrates key decision-making components (sensemaking, anticipation, and managing complexity) can trigger and enrich communication between clinicians and enhance the clinical management of CHD patients. For patients with complex and subspecialized diseases such as CHD, a well-designed CDSS can become part of a multifaceted solution that includes knowledge translation, broader communication around interpretation of information, and access to additional expertise to support CHD specific decision-making.
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Affiliation(s)
- Azadeh Assadi
- Labatt Family Heart Centre, Department of Critical Care Medicine, Hospital for Sick Children, Toronto, ON, Canada.,HumanEra, Institute of Biomaterials and Biomedical Engineering, Department of Engineering and Applied Sciences, University of Toronto, Toronto, ON, Canada
| | - Peter C Laussen
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.,Executive Vice President for Health Affairs, Boston Children's Hospital, Boston, MA, United States.,Professor of Anaesthesia, Harvard Medical School, Boston, MA, United States
| | - Gabrielle Freire
- Division of Emergency Medicine, Department of Pediatrics, University of Toronto, Toronto, ON, Canada
| | - Marzyeh Ghassemi
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Boston, MA, United States.,Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Boston, MA, United States.,Vector Institute, Toronto, ON, Canada.,CIFAR AI Chair, Vector Institute, Toronto, ON, Canada
| | - Patricia C Trbovich
- HumanEra, Institute of Biomaterials and Biomedical Engineering, Department of Engineering and Applied Sciences, University of Toronto, Toronto, ON, Canada.,Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada.,Research and Innovation, North York General Hospital, Toronto, ON, Canada
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