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Li J, Chaudhary D, Sharma V, Sharma V, Avula V, Ssentongo P, Wolk DM, Zand R, Abedi V. An integrated pipeline for prediction of Clostridioides difficile infection. Sci Rep 2023; 13:16532. [PMID: 37783691 PMCID: PMC10545794 DOI: 10.1038/s41598-023-41753-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 08/31/2023] [Indexed: 10/04/2023] Open
Abstract
With the expansion of electronic health records(EHR)-linked genomic data comes the development of machine learning-enable models. There is a pressing need to develop robust pipelines to evaluate the performance of integrated models and minimize systemic bias. We developed a prediction model of symptomatic Clostridioides difficile infection(CDI) by integrating common EHR-based and genetic risk factors(rs2227306/IL8). Our pipeline includes (1) leveraging phenotyping algorithm to minimize temporal bias, (2) performing simulation studies to determine the predictive power in samples without genetic information, (3) propensity score matching to control for the confoundings, (4) selecting machine learning algorithms to capture complex feature interactions, (5) performing oversampling to address data imbalance, and (6) optimizing models and ensuring proper bias-variance trade-off. We evaluate the performance of prediction models of CDI when including common clinical risk factors and the benefit of incorporating genetic feature(s) into the models. We emphasize the importance of building a robust integrated pipeline to avoid systemic bias and thoroughly evaluating genetic features when integrated into the prediction models in the general population and subgroups.
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Affiliation(s)
- Jiang Li
- Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA, USA
| | - Durgesh Chaudhary
- Neuroscience Institute, Geisinger Health System, Danville, PA, USA
- Department of Neurology, College of Medicine, The Pennsylvania State University, Hershey, PA, 17033, USA
| | - Vaibhav Sharma
- Geisinger Commonwealth School of Medicine, Danville, PA, USA
| | - Vishakha Sharma
- College of Osteopathic Medicine, Kansas City University, Kansas City, MO, USA
| | - Venkatesh Avula
- Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA, USA
| | - Paddy Ssentongo
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, Hershey, PA, USA
| | - Donna M Wolk
- Molecular and Microbial Diagnostics and Development, Geisinger Medical Center, Danville, PA, USA
| | - Ramin Zand
- Neuroscience Institute, Geisinger Health System, Danville, PA, USA
- Department of Neurology, College of Medicine, The Pennsylvania State University, Hershey, PA, 17033, USA
| | - Vida Abedi
- Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA, USA.
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, Hershey, PA, USA.
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Vázquez-Cuesta S, Lozano García N, Fernández AI, Olmedo M, Kestler M, Alcalá L, Marín M, Bermejo J, Díaz FFA, Muñoz P, Bouza E, Reigadas E. Microbiome profile and calprotectin levels as markers of risk of recurrent Clostridioides difficile infection. Front Cell Infect Microbiol 2023; 13:1237500. [PMID: 37780848 PMCID: PMC10534046 DOI: 10.3389/fcimb.2023.1237500] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/23/2023] [Indexed: 10/03/2023] Open
Abstract
Introduction Clostridioides difficile infection (CDI) is the main cause of nosocomial diarrhoea in developed countries. Recurrent CDI (R-CDI), which affects 20%-30% of patients and significantly increases hospital stay and associated costs, is a key challenge. The main objective of this study was to explore the role of the microbiome and calprotectin levels as predictive biomarkers of R-CDI. Methods We prospectively (2019-2021) included patients with a primary episode of CDI. Clinical data and faecal samples were collected. The microbiome was analysed by sequencing the hypervariable V4 region of the 16S rRNA gene on an Illumina Miseq platform. Results We enrolled 200 patients with primary CDI, of whom 54 developed R-CDI and 146 did not. We analysed 200 primary samples and found that Fusobacterium increased in abundance, while Collinsella, Senegalimassilia, Prevotella and Ruminococcus decreased in patients with recurrent versus non-recurrent disease. Elevated calprotectin levels correlated significantly with R-CDI (p=0.01). We built a risk index for R-CDI, including as prognostic factors age, sex, immunosuppression, toxin B amplification cycle, creatinine levels and faecal calprotectin levels (overall accuracy of 79%). Discussion Calprotectin levels and abundance of microbial genera such as Fusobacterium and Prevotella in primary episodes could be useful as early markers of R-CDI. We propose a readily available model for prediction of R-CDI that can be applied at the initial CDI episode. The use of this tool could help to better tailor treatments according to the risk of R-CDI.
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Affiliation(s)
- Silvia Vázquez-Cuesta
- Department of Clinical Microbiology and Infectious Diseases, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
- Biochemistry and Molecular Biology Department, Faculty of Biology, Universidad Complutense de Madrid (UCM), Madrid, Spain
| | - Nuria Lozano García
- Department of Clinical Microbiology and Infectious Diseases, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Ana I. Fernández
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
- Department of Cardiology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - María Olmedo
- Department of Clinical Microbiology and Infectious Diseases, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Martha Kestler
- Department of Clinical Microbiology and Infectious Diseases, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
- Medicine Department, School of Medicine, Universidad Complutense de Madrid (UCM), Madrid, Spain
| | - Luis Alcalá
- Department of Clinical Microbiology and Infectious Diseases, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
- Centro de Investigación Biomédica en red de Enfermedades Respiratorias (CIBERES CB06/06/0058), Madrid, Spain
| | - Mercedes Marín
- Department of Clinical Microbiology and Infectious Diseases, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
- Medicine Department, School of Medicine, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Centro de Investigación Biomédica en red de Enfermedades Respiratorias (CIBERES CB06/06/0058), Madrid, Spain
| | - Javier Bermejo
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
- Department of Cardiology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Medicine Department, School of Medicine, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Centro de Investigación Biomédica en red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Francisco Fernández-Avilés Díaz
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
- Department of Cardiology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Medicine Department, School of Medicine, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Centro de Investigación Biomédica en red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Patricia Muñoz
- Department of Clinical Microbiology and Infectious Diseases, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
- Medicine Department, School of Medicine, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Centro de Investigación Biomédica en red de Enfermedades Respiratorias (CIBERES CB06/06/0058), Madrid, Spain
| | - Emilio Bouza
- Department of Clinical Microbiology and Infectious Diseases, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
- Medicine Department, School of Medicine, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Centro de Investigación Biomédica en red de Enfermedades Respiratorias (CIBERES CB06/06/0058), Madrid, Spain
| | - Elena Reigadas
- Department of Clinical Microbiology and Infectious Diseases, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
- Medicine Department, School of Medicine, Universidad Complutense de Madrid (UCM), Madrid, Spain
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Dawkins JJ, Allegretti JR, Gibson TE, McClure E, Delaney M, Bry L, Gerber GK. Gut metabolites predict Clostridioides difficile recurrence. Microbiome 2022; 10:87. [PMID: 35681218 PMCID: PMC9178838 DOI: 10.1186/s40168-022-01284-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 05/02/2022] [Indexed: 05/10/2023]
Abstract
BACKGROUND Clostridioides difficile infection (CDI) is the most common hospital acquired infection in the USA, with recurrence rates > 15%. Although primary CDI has been extensively linked to gut microbial dysbiosis, less is known about the factors that promote or mitigate recurrence. Moreover, previous studies have not shown that microbial abundances in the gut measured by 16S rRNA amplicon sequencing alone can accurately predict CDI recurrence. RESULTS We conducted a prospective, longitudinal study of 53 non-immunocompromised participants with primary CDI. Stool sample collection began pre-CDI antibiotic treatment at the time of diagnosis, and continued up to 8 weeks post-antibiotic treatment, with weekly or twice weekly collections. Samples were analyzed using (1) 16S rRNA amplicon sequencing, (2) liquid chromatography/mass-spectrometry metabolomics measuring 1387 annotated metabolites, and (3) short-chain fatty acid profiling. The amplicon sequencing data showed significantly delayed recovery of microbial diversity in recurrent participants, and depletion of key anaerobic taxa at multiple time-points, including Clostridium cluster XIVa and IV taxa. The metabolomic data also showed delayed recovery in recurrent participants, and moreover mapped to pathways suggesting distinct functional abnormalities in the microbiome or host, such as decreased microbial deconjugation activity, lowered levels of endocannabinoids, and elevated markers of host cell damage. Further, using predictive statistical/machine learning models, we demonstrated that the metabolomic data, but not the other data sources, can accurately predict future recurrence at 1 week (AUC 0.77 [0.71, 0.86; 95% interval]) and 2 weeks (AUC 0.77 [0.69, 0.85; 95% interval]) post-treatment for primary CDI. CONCLUSIONS The prospective, longitudinal, and multi-omic nature of our CDI recurrence study allowed us to uncover previously unrecognized dynamics in the microbiome and host presaging recurrence, and, in particular, to elucidate changes in the understudied gut metabolome. Moreover, we demonstrated that a small set of metabolites can accurately predict future recurrence. Our findings have implications for development of diagnostic tests and treatments that could ultimately short-circuit the cycle of CDI recurrence, by providing candidate metabolic biomarkers for diagnostics development, as well as offering insights into the complex microbial and metabolic alterations that are protective or permissive for recurrence. Video Abstract.
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Affiliation(s)
- Jennifer J. Dawkins
- Department of Pathology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
- Harvard-MIT Health Sciences & Technology, Harvard Medical School, MIT, Cambridge, MA USA
| | - Jessica R. Allegretti
- Massachusetts Host-Microbiome Center, Boston, MA USA
- Division of Gastroenterology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
| | - Travis E. Gibson
- Department of Pathology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
| | - Emma McClure
- Division of Gastroenterology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
| | - Mary Delaney
- Massachusetts Host-Microbiome Center, Boston, MA USA
| | - Lynn Bry
- Department of Pathology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
- Massachusetts Host-Microbiome Center, Boston, MA USA
| | - Georg K. Gerber
- Department of Pathology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
- Harvard-MIT Health Sciences & Technology, Harvard Medical School, MIT, Cambridge, MA USA
- Massachusetts Host-Microbiome Center, Boston, MA USA
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Chen Y, Xi M, Johnson A, Tomlinson G, Campigotto A, Chen L, Sung L. Machine Learning Approaches to Investigate Clostridioides difficile Infection and Outcomes: A Systematic Review. Int J Med Inform 2022. [DOI: 10.1016/j.ijmedinf.2022.104706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 12/21/2021] [Accepted: 01/22/2022] [Indexed: 11/20/2022]
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Rao K, Dubberke ER. Can prediction scores be used to identify patients at risk of Clostridioides difficile infection? Curr Opin Gastroenterol 2022; 38:7-14. [PMID: 34628418 DOI: 10.1097/mog.0000000000000793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
PURPOSE OF REVIEW To describe the current state of literature on modeling risk of incident and recurrent Clostridioides difficile infection (iCDI and rCDI), to underscore limitations, and to propose a path forward for future research. RECENT FINDINGS There are many published risk factors and models for both iCDI and rCDI. The approaches include scores with a limited list of variables designed to be used at the bedside, but more recently have also included automated tools that take advantage of the entire electronic health record. Recent attempts to externally validate scores have met with mixed success. SUMMARY For iCDI, the performance largely hinges on the incidence, which even for hospitalized patients can be low (often <1%). Most scores fail to achieve high accuracy and/or are not externally validated. A challenge in predicting rCDI is the significant overlap with risk factors for iCDI, reducing the discriminatory ability of models. Automated electronic health record-based tools show promise but portability to other centers is challenging. Future studies should include external validation and consider biomarkers to augment performance.
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Affiliation(s)
- Krishna Rao
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Erik R Dubberke
- Division of Infectious Diseases, Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri, USA
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van Rossen TM, Ooijevaar RE, Vandenbroucke-Grauls CMJE, Dekkers OM, Kuijper EJ, Keller JJ, van Prehn J. Prognostic factors for severe and recurrent Clostridioides difficile infection: a systematic review. Clin Microbiol Infect 2021; 28:321-331. [PMID: 34655745 DOI: 10.1016/j.cmi.2021.09.026] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 09/24/2021] [Accepted: 09/25/2021] [Indexed: 12/13/2022]
Abstract
OBJECTIVES Clostridioides difficile infection (CDI), its subsequent recurrences (rCDIs), and severe CDI (sCDI) provide a significant burden for both patients and the healthcare system. Identifying patients diagnosed with initial CDI who are at increased risk of developing sCDI/rCDI could lead to more cost-effective therapeutic choices. In this systematic review we aimed to identify clinical prognostic factors associated with an increased risk of developing sCDI or rCDI. METHODS PubMed, Embase, Emcare, Web of Science and COCHRANE Library databases were searched from database inception through March, 2021. The study eligibility criteria were cohort and case-control studies. Participants were patients ≥18 years old diagnosed with CDI, in which clinical or laboratory factors were analysed to predict sCDI/rCDI. Risk of bias was assessed by using the Quality in Prognostic Research (QUIPS) tool and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool modified for prognostic studies. Study selection was performed by two independent reviewers. Overview tables of prognostic factors were constructed to assess the number of studies and the respective effect direction and statistical significance of an association. RESULTS 136 studies were included for final analysis. Greater age and the presence of multiple comorbidities were prognostic factors for sCDI. Identified risk factors for rCDI were greater age, healthcare-associated CDI, prior hospitalization, proton pump inhibitors (PPIs) started during or after CDI diagnosis, and previous rCDI. CONCLUSIONS Prognostic factors for sCDI and rCDI could aid clinicians to make treatment decisions based on risk stratification. We suggest that future studies use standardized definitions for sCDI/rCDI and systematically collect and report the risk factors assessed in this review, to allow for meaningful meta-analysis of risk factors using data of high-quality trials.
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Affiliation(s)
- Tessel M van Rossen
- Amsterdam UMC, VU University Medical Center, Medical Microbiology & Infection Control, Amsterdam Infection & Immunity, Amsterdam, the Netherlands.
| | - Rogier E Ooijevaar
- Amsterdam UMC, VU University Medical Center, Gastroenterology & Hepatology, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands.
| | - Christina M J E Vandenbroucke-Grauls
- Amsterdam UMC, VU University Medical Center, Medical Microbiology & Infection Control, Amsterdam Infection & Immunity, Amsterdam, the Netherlands; Aarhus University, Clinical Epidemiology, Aarhus, Denmark
| | - Olaf M Dekkers
- Leiden University Medical Center, Clinical Epidemiology, Leiden, the Netherlands
| | - Ed J Kuijper
- Leiden University Medical Center, Center for Infectious Diseases, Medical Microbiology, Leiden, the Netherlands
| | - Josbert J Keller
- Haaglanden Medical Center, Gastroenterology & Hepatology, The Hague, the Netherlands; Leiden University Medical Center, Gastroenterology & Hepatology, Leiden, the Netherlands
| | - Joffrey van Prehn
- Leiden University Medical Center, Center for Infectious Diseases, Medical Microbiology, Leiden, the Netherlands
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van Rossen TM, van Dijk LJ, Heymans MW, Dekkers OM, Vandenbroucke-Grauls CMJE, van Beurden YH. External validation of two prediction tools for patients at risk for recurrent Clostridioides difficile infection. Therap Adv Gastroenterol 2021; 14:1756284820977385. [PMID: 33456500 PMCID: PMC7797589 DOI: 10.1177/1756284820977385] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 11/03/2020] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND One in four patients with primary Clostridioides difficile infection (CDI) develops recurrent CDI (rCDI). With every recurrence, the chance of a subsequent CDI episode increases. Early identification of patients at risk for rCDI might help doctors to guide treatment. The aim of this study was to externally validate published clinical prediction tools for rCDI. METHODS The validation cohort consisted of 129 patients, diagnosed with CDI between 2018 and 2020. rCDI risk scores were calculated for each individual patient in the validation cohort using the scoring tools described in the derivation studies. Per score value, we compared the average predicted risk of rCDI with the observed number of rCDI cases. Discrimination was assessed by calculating the area under the receiver operating characteristic curve (AUC). RESULTS Two prediction tools were selected for validation (Cobo 2018 and Larrainzar-Coghen 2016). The two derivation studies used different definitions for rCDI. Using Cobo's definition, rCDI occurred in 34 patients (26%) of the validation cohort: using the definition of Larrainzar-Coghen, we observed 19 recurrences (15%). The performance of both prediction tools was poor when applied to our validation cohort. The estimated AUC was 0.43 [95% confidence interval (CI); 0.32-0.54] for Cobo's tool and 0.42 (95% CI; 0.28-0.56) for Larrainzar-Coghen's tool. CONCLUSION Performance of both prediction tools was disappointing in the external validation cohort. Currently identified clinical risk factors may not be sufficient for accurate prediction of rCDI.
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Affiliation(s)
| | - Laura J. van Dijk
- Amsterdam UMC, Vrije Universiteit Amsterdam, Gastroenterology and Hepatology, Amsterdam Gastroenterology Endocrinology Metabolism Institute, Amsterdam, The Netherlands
| | - Martijn W. Heymans
- Amsterdam UMC, Vrije Universiteit Amsterdam, Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Olaf M. Dekkers
- Leiden University Medical Center, Clinical Epidemiology, Leiden, The Netherlands
| | - Christina M. J. E. Vandenbroucke-Grauls
- Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Microbiology and Infection Control, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands
| | - Yvette H. van Beurden
- Amsterdam UMC, Vrije Universiteit Amsterdam, Gastroenterology and Hepatology, Amsterdam Gastroenterology Endocrinology Metabolism Institute, Amsterdam, The Netherlands
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Scaria E, Powell WR, Birstler J, Alagoz O, Shirley D, Kind AJH, Safdar N. Neighborhood disadvantage and 30-day readmission risk following Clostridioides difficile infection hospitalization. BMC Infect Dis 2020; 20:762. [PMID: 33066737 PMCID: PMC7565791 DOI: 10.1186/s12879-020-05481-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 10/06/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Clostridioides difficile infection (CDI) is commonly associated with outcomes like recurrence and readmission. The effect of social determinants of health, such as 'neighborhood' socioeconomic disadvantage, on a CDI patient's health outcomes is unclear. Living in a disadvantaged neighborhood could interfere with a CDI patient's ability to follow post-discharge care recommendations and the success probability of these recommendations, thereby increasing risk of readmission. We hypothesized that neighborhood disadvantage was associated with 30-day readmission risk in Medicare patients with CDI. METHODS In this retrospective cohort study, odds of 30-day readmission for CDI patients are evaluated controlling for patient sociodemographics, comorbidities, and hospital and stay-level variables. The cohort was created from a random 20% national sample of Medicare patients during the first 11 months of 2014. RESULTS From the cohort of 19,490 patients (39% male; 80% white; 83% 65 years or older), 22% were readmitted within 30 days of an index stay. Unadjusted analyses showed that patients from the most disadvantaged neighborhoods were readmitted at a higher rate than those from less disadvantaged neighborhoods (26% vs. 21% rate: unadjusted OR = 1.32 [1.20, 1.45]). This relationship held in adjusted analyses, in which residence in the most disadvantaged neighborhoods was associated with 16% increased odds of readmission (adjusted OR = 1.16 [1.04, 1.28]). CONCLUSIONS Residence in disadvantaged neighborhoods poses a significantly increased risk of readmission in CDI patients. Further research should focus on in-depth assessments of this population to better understand the mechanisms underlying these risks and if these findings apply to other infectious diseases.
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Affiliation(s)
- Elizabeth Scaria
- Department of Industrial and Systems Engineering, University of Wisconsin-Madison, 1513 University Avenue, Madison, WI, 53706, USA
| | - W Ryan Powell
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison, School of Medicine and Public Health, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI, 53705, USA
| | - Jen Birstler
- Department of Biostatics & Medical Informatics, University of Wisconsin-Madison, School of Medicine and Public Health, 201 WARF Building, 610 Walnut Street, Madison, WI, 53726, USA
| | - Oguzhan Alagoz
- Department of Industrial and Systems Engineering, University of Wisconsin-Madison, 1513 University Avenue, Madison, WI, 53706, USA.,Department of Population Health Sciences, University of Wisconsin-Madison, School of Medicine and Public Health, 707 WARF Building, 610 Walnut Street, Madison, WI, 53726, USA
| | - Daniel Shirley
- Division of Infectious Diseases, Department of Medicine, University of Wisconsin-Madison, School of Medicine and Public Health, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI, 53705, USA
| | - Amy J H Kind
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison, School of Medicine and Public Health, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI, 53705, USA.,Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI, 53705, USA
| | - Nasia Safdar
- Division of Infectious Diseases, Department of Medicine, University of Wisconsin-Madison, School of Medicine and Public Health, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI, 53705, USA. .,William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI, 53705, USA.
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Feuerstadt P, Stong L, Dahdal DN, Sacks N, Lang K, Nelson WW. Healthcare resource utilization and direct medical costs associated with index and recurrent Clostridioides difficile infection: a real-world data analysis. J Med Econ 2020; 23:603-609. [PMID: 31999199 DOI: 10.1080/13696998.2020.1724117] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Aims: This study aimed to evaluate all-cause economic outcomes, healthcare resource utilization (HRU), and costs in patients with Clostridioides difficile infection (CDI) and recurrent CDI (rCDI) using commercial claims from a large database representing various healthcare settings.Materials and methods: A retrospective analysis of commercial claims data from the IQVIA PharMetrics Plus database was conducted for patients aged 18-64 years with CDI episodes requiring inpatient stay with CDI diagnosis code or an outpatient medical claim for CDI plus a CDI treatment. Index CDI episodes occurred between 1 January 2010 and 30 June 2017, including only those where patients were observable 6 months before and 12 months after the index episode. Each CDI episode was followed by a 14-d claim-free period. rCDI was defined as another CDI episode within an 8-week window following the claim-free period. HRU, all-cause direct medical costs and time to rCDI were calculated over 12 months and stratified by number of rCDI episodes.Results: A total of 46,571 patients with index CDI were included. Mean time from one CDI episode to the next was approximately 1 month. In the 12-month follow-up period, those with no recurrence had 1.4 inpatient visits per person and those with 3 or more recurrences had 5.8. Most patients with 3 or more recurrences had 2 or more hospital admissions. The mean annual, total all-cause direct medical costs per patient were $71,980 for those with no recurrence and $207,733 for those with 3 or more recurrences.Limitations: The study included individuals 18-64 years only. A stringent definition of rCDI was used, which may have underestimated the incidence of rCDI.Conclusions: CDI and rCDI are associated with substantial healthcare resource utilization and direct medical costs. Timing of recurrences can be predictable, providing a window of opportunity for interventions. Prevention of multiple rCDI appears essential to reduce healthcare costs.
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Affiliation(s)
- Paul Feuerstadt
- Gastroenterology Center of Connecticut, Hamden, CT, USA
- Division of Gastroenterology, Yale University School of Medicine, New Haven, CT, USA
| | - Laura Stong
- Ferring Pharmaceuticals Inc, Parsippany, NJ, USA
| | | | - Naomi Sacks
- Precision Health Economics and Outcomes Research, Boston, MA, USA
- Department of Public Health, Tufts University School of Medicine, Boston, MA, USA
| | - Kathleen Lang
- Precision Health Economics and Outcomes Research, Boston, MA, USA
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Bush K, Barbosa H, Farooq S, Weisenthal SJ, Trayhan M, White RJ, Noyes EI, Ghoshal G, Zand MS. Predicting hospital-onset Clostridium difficile using patient mobility data: A network approach. Infect Control Hosp Epidemiol 2019; 40:1380-6. [PMID: 31656216 DOI: 10.1017/ice.2019.288] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE To examine the relationship between unit-wide Clostridium difficile infection (CDI) susceptibility and inpatient mobility and to create contagion centrality as a new predictive measure of CDI. DESIGN Retrospective cohort study. METHODS A mobility network was constructed using 2 years of patient electronic health record data for a 739-bed hospital (n = 72,636 admissions). Network centrality measures were calculated for each hospital unit (node) providing clinical context for each in terms of patient transfers between units (ie, edges). Daily unit-wide CDI susceptibility scores were calculated using logistic regression and were compared to network centrality measures to determine the relationship between unit CDI susceptibility and patient mobility. RESULTS Closeness centrality was a statistically significant measure associated with unit susceptibility (P < .05), highlighting the importance of incoming patient mobility in CDI prevention at the unit level. Contagion centrality (CC) was calculated using inpatient transfer rates, unit-wide susceptibility of CDI, and current hospital CDI infections. The contagion centrality measure was statistically significant (P < .05) with our outcome of hospital-onset CDI cases, and it captured the additional opportunities for transmission associated with inpatient transfers. We have used this analysis to create easily interpretable clinical tools showing this relationship as well as the risk of hospital-onset CDI in real time, and these tools can be implemented in hospital EHR systems. CONCLUSIONS Quantifying and visualizing the combination of inpatient transfers, unit-wide risk, and current infections help identify hospital units at risk of developing a CDI outbreak and, thus, provide clinicians and infection prevention staff with advanced warning and specific location data to inform prevention efforts.
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11
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Medic G, Kosaner Kließ M, Atallah L, Weichert J, Panda S, Postma M, EL-Kerdi A. Evidence-based Clinical Decision Support Systems for the prediction and detection of three disease states in critical care: A systematic literature review. F1000Res 2019; 8:1728. [PMID: 31824670 PMCID: PMC6894361 DOI: 10.12688/f1000research.20498.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/24/2019] [Indexed: 10/21/2023] Open
Abstract
Background: Clinical decision support (CDS) systems have emerged as tools providing intelligent decision making to address challenges of critical care. CDS systems can be based on existing guidelines or best practices; and can also utilize machine learning to provide a diagnosis, recommendation, or therapy course. Methods: This research aimed to identify evidence-based study designs and outcome measures to determine the clinical effectiveness of clinical decision support systems in the detection and prediction of hemodynamic instability, respiratory distress, and infection within critical care settings. PubMed, ClinicalTrials.gov and Cochrane Database of Systematic Reviews were systematically searched to identify primary research published in English between 2013 and 2018. Studies conducted in the USA, Canada, UK, Germany and France with more than 10 participants per arm were included. Results: In studies on hemodynamic instability, the prediction and management of septic shock were the most researched topics followed by the early prediction of heart failure. For respiratory distress, the most popular topics were pneumonia detection and prediction followed by pulmonary embolisms. Given the importance of imaging and clinical notes, this area combined Machine Learning with image analysis and natural language processing. In studies on infection, the most researched areas were the detection, prediction, and management of sepsis, surgical site infections, as well as acute kidney injury. Overall, a variety of Machine Learning algorithms were utilized frequently, particularly support vector machines, boosting techniques, random forest classifiers and neural networks. Sensitivity, specificity, and ROC AUC were the most frequently reported performance measures. Conclusion: This review showed an increasing use of Machine Learning for CDS in all three areas. Large datasets are required for training these algorithms; making it imperative to appropriately address, challenges such as class imbalance, correct labelling of data and missing data. Recommendations are formulated for the development and successful adoption of CDS systems.
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Affiliation(s)
- Goran Medic
- Health Economics, Philips, Eindhoven, Noord-Brabant, 5621JG, The Netherlands
- Department of Pharmacy, Unit of PharmacoTherapy, -Epidemiology & -Economics, University of Groningen, Groningen, 9700 AB, The Netherlands
| | | | | | | | - Saswat Panda
- Global Market Access Solutions Sàrl, St-Prex, 1162, Switzerland
| | - Maarten Postma
- Department of Pharmacy, Unit of PharmacoTherapy, -Epidemiology & -Economics, University of Groningen, Groningen, 9700 AB, The Netherlands
- Department of Health Sciences, University Medical Centre Groningen, University of Groningen, Groningen, 9700 AB, The Netherlands
- Department of Economics, Econometrics & Finance, University of Groningen, Groningen, 9700 AB, The Netherlands
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12
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Medic G, Kosaner Kließ M, Atallah L, Weichert J, Panda S, Postma M, EL-Kerdi A. Evidence-based Clinical Decision Support Systems for the prediction and detection of three disease states in critical care: A systematic literature review. F1000Res 2019; 8:1728. [PMID: 31824670 PMCID: PMC6894361 DOI: 10.12688/f1000research.20498.2] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/22/2019] [Indexed: 02/01/2023] Open
Abstract
Background: Clinical decision support (CDS) systems have emerged as tools providing intelligent decision making to address challenges of critical care. CDS systems can be based on existing guidelines or best practices; and can also utilize machine learning to provide a diagnosis, recommendation, or therapy course. Methods: This research aimed to identify evidence-based study designs and outcome measures to determine the clinical effectiveness of clinical decision support systems in the detection and prediction of hemodynamic instability, respiratory distress, and infection within critical care settings. PubMed, ClinicalTrials.gov and Cochrane Database of Systematic Reviews were systematically searched to identify primary research published in English between 2013 and 2018. Studies conducted in the USA, Canada, UK, Germany and France with more than 10 participants per arm were included. Results: In studies on hemodynamic instability, the prediction and management of septic shock were the most researched topics followed by the early prediction of heart failure. For respiratory distress, the most popular topics were pneumonia detection and prediction followed by pulmonary embolisms. Given the importance of imaging and clinical notes, this area combined Machine Learning with image analysis and natural language processing. In studies on infection, the most researched areas were the detection, prediction, and management of sepsis, surgical site infections, as well as acute kidney injury. Overall, a variety of Machine Learning algorithms were utilized frequently, particularly support vector machines, boosting techniques, random forest classifiers and neural networks. Sensitivity, specificity, and ROC AUC were the most frequently reported performance measures. Conclusion: This review showed an increasing use of Machine Learning for CDS in all three areas. Large datasets are required for training these algorithms; making it imperative to appropriately address, challenges such as class imbalance, correct labelling of data and missing data. Recommendations are formulated for the development and successful adoption of CDS systems.
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Affiliation(s)
- Goran Medic
- Health Economics, Philips, Eindhoven, Noord-Brabant, 5621JG, The Netherlands
- Department of Pharmacy, Unit of PharmacoTherapy, -Epidemiology & -Economics, University of Groningen, Groningen, 9700 AB, The Netherlands
| | | | | | | | - Saswat Panda
- Global Market Access Solutions Sàrl, St-Prex, 1162, Switzerland
| | - Maarten Postma
- Department of Pharmacy, Unit of PharmacoTherapy, -Epidemiology & -Economics, University of Groningen, Groningen, 9700 AB, The Netherlands
- Department of Health Sciences, University Medical Centre Groningen, University of Groningen, Groningen, 9700 AB, The Netherlands
- Department of Economics, Econometrics & Finance, University of Groningen, Groningen, 9700 AB, The Netherlands
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Peiffer-Smadja N, Rawson TM, Ahmad R, Buchard A, Georgiou P, Lescure FX, Birgand G, Holmes AH. Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Clin Microbiol Infect 2019; 26:584-595. [PMID: 31539636 DOI: 10.1016/j.cmi.2019.09.009] [Citation(s) in RCA: 159] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 08/29/2019] [Accepted: 09/09/2019] [Indexed: 12/22/2022]
Abstract
BACKGROUND Machine learning (ML) is a growing field in medicine. This narrative review describes the current body of literature on ML for clinical decision support in infectious diseases (ID). OBJECTIVES We aim to inform clinicians about the use of ML for diagnosis, classification, outcome prediction and antimicrobial management in ID. SOURCES References for this review were identified through searches of MEDLINE/PubMed, EMBASE, Google Scholar, biorXiv, ACM Digital Library, arXiV and IEEE Xplore Digital Library up to July 2019. CONTENT We found 60 unique ML-clinical decision support systems (ML-CDSS) aiming to assist ID clinicians. Overall, 37 (62%) focused on bacterial infections, 10 (17%) on viral infections, nine (15%) on tuberculosis and four (7%) on any kind of infection. Among them, 20 (33%) addressed the diagnosis of infection, 18 (30%) the prediction, early detection or stratification of sepsis, 13 (22%) the prediction of treatment response, four (7%) the prediction of antibiotic resistance, three (5%) the choice of antibiotic regimen and two (3%) the choice of a combination antiretroviral therapy. The ML-CDSS were developed for intensive care units (n = 24, 40%), ID consultation (n = 15, 25%), medical or surgical wards (n = 13, 20%), emergency department (n = 4, 7%), primary care (n = 3, 5%) and antimicrobial stewardship (n = 1, 2%). Fifty-three ML-CDSS (88%) were developed using data from high-income countries and seven (12%) with data from low- and middle-income countries (LMIC). The evaluation of ML-CDSS was limited to measures of performance (e.g. sensitivity, specificity) for 57 ML-CDSS (95%) and included data in clinical practice for three (5%). IMPLICATIONS Considering comprehensive patient data from socioeconomically diverse healthcare settings, including primary care and LMICs, may improve the ability of ML-CDSS to suggest decisions adapted to various clinical contexts. Currents gaps identified in the evaluation of ML-CDSS must also be addressed in order to know the potential impact of such tools for clinicians and patients.
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Affiliation(s)
- N Peiffer-Smadja
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK; French Institute for Medical Research (Inserm), Infection Antimicrobials Modelling Evolution (IAME), UMR 1137, University Paris Diderot, Paris, France.
| | - T M Rawson
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
| | - R Ahmad
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
| | | | - P Georgiou
- Department of Electrical and Electronic Engineering, Imperial College, London, UK
| | - F-X Lescure
- French Institute for Medical Research (Inserm), Infection Antimicrobials Modelling Evolution (IAME), UMR 1137, University Paris Diderot, Paris, France; Infectious Diseases Department, Bichat-Claude Bernard Hospital, Assistance-Publique Hôpitaux de Paris, Paris, France
| | - G Birgand
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
| | - A H Holmes
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
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14
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Kimura T, Snijder R, Sugitani T. Characterization and risk factors for recurrence of Clostridioides (Clostridium) difficile infection in Japan: A nationwide real-world analysis using a large hospital-based administrative dataset. J Infect Chemother 2019; 25:615-620. [PMID: 30987950 DOI: 10.1016/j.jiac.2019.03.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Revised: 02/15/2019] [Accepted: 03/14/2019] [Indexed: 12/17/2022]
Abstract
OBJECTIVE Recurrent Clostridioides (Clostridium) difficile infection (rCDI) is common and increases healthcare resource utilization. In this study, we assessed rCDI risk factors using an up-to-date, Japanese national hospital-based database. METHODS C. difficile infection (CDI) episodes, occurring July 2014-June 2017, in patients aged ≥18 years were extracted from the database and a nested case-control analysis was performed. Cases were defined as rCDI episodes which required re-initiation of oral vancomycin or oral/intravenous metronidazole treatment within 8 weeks from the start of initial treatment. Cases were matched to 4 non-rCDI episodes at the timing of rCDI occurrence. Adjusted odds ratios (ORs) were estimated using multivariate conditional logistic regression model. RESULTS Of 18,246 initial CDI episodes, 3250 (17.8%) had at least one rCDI. Approximately 90% of episodes occurred in inpatients and 65% were treated with metronidazole. Older age (<75 years vs 75-84 years and vs 85 + years) was associated with higher risk of rCDI (OR = 1.27, 95% confidence interval [1.15, 1.41] and 1.45 [1.30, 1.61], respectively). Use of systemic antibiotics (3.16 [2.90, 3.44]), probiotics (2.53 [2.32, 2.77]), chemotherapy (1.28 [1.08, 1.53]), or proton pump inhibitors (PPIs) (1.17 [1.07, 1.28]), and prior CDI history (1.22 [1.03, 1.43]) were also identified as rCDI risk factors. Vancomycin reduced the risk of rCDI compared with metronidazole treatment (0.83 [0.76, 0.91]). CONCLUSION This large, multicenter, nationwide study confirmed that older age, PPIs, antibiotics, probiotics, chemotherapy, and prior CDI history are risk factors for rCDI in Japan. There was a 17% decrease of rCDI risk with vancomycin vs metronidazole treatment. CLINICAL TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
- Tomomi Kimura
- Astellas Pharma Inc., 2-5-1 Nihonbashi-Honcho, Chuo-ku, Tokyo, 103-8411, Japan.
| | - Robert Snijder
- Astellas Pharma, B.V., Sylviusweg 62, 2333 BE, Leiden, the Netherlands
| | - Toshifumi Sugitani
- Astellas Pharma Inc., 2-5-1 Nihonbashi-Honcho, Chuo-ku, Tokyo, 103-8411, Japan
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15
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Marley C, El Hahi Y, Ferreira G, Woods L, Ramirez Villaescusa A. Evaluation of a risk score to predict future Clostridium difficile disease using UK primary care and hospital data in Clinical Practice Research Datalink. Hum Vaccin Immunother 2019; 15:2475-2481. [PMID: 30945972 PMCID: PMC6816380 DOI: 10.1080/21645515.2019.1589288] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
We evaluated the applicability of a Clostridium difficile infection (CDI) risk index developed for patients at hospital discharge to identify persons at high-risk of CDI in a primary care population. This retrospective observational study used data from the UK Clinical Practice Research Datalink, linked with Hospital Episodes Statistics. The risk index was based on the following patient characteristics: age, previous hospitalizations, days in hospital, and prior antibiotics use. Individual risk scores were calculated by summing points assigned to pre-defined categories for each characteristic. We assessed the association of risk factors with CDI by multivariate logistic regression. The estimated CDI incidence rate was 4/10,000 and 2/10,000 person-years in 2008 and 2012, respectively. On an index with a maximal risk of 19, a cut-off for high risk of ≥7 had sensitivity, specificity and positive predictive values of 80%, 87% and 12%, respectively. A high-risk person had a ~ 35% higher risk of CDI than a low-risk person. Multivariate risk factor analysis indicated a need to reconsider the relative risk scores. The CDI risk index can be applied to the UK primary care population and help identify study populations for vaccine development studies. Reassessing the relative weights assigned to risk factors could improve the index performance in this setting.
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Affiliation(s)
| | | | | | - Laura Woods
- Department of Non communicable disease epidemiology, London School of Hygiene & Tropical medicine , London , UK
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Sartelli M, Di Bella S, McFarland LV, Khanna S, Furuya-Kanamori L, Abuzeid N, Abu-Zidan FM, Ansaloni L, Augustin G, Bala M, Ben-Ishay O, Biffl WL, Brecher SM, Camacho-Ortiz A, Caínzos MA, Chan S, Cherry-Bukowiec JR, Clanton J, Coccolini F, Cocuz ME, Coimbra R, Cortese F, Cui Y, Czepiel J, Demetrashvili Z, Di Carlo I, Di Saverio S, Dumitru IM, Eckmann C, Eiland EH, Forrester JD, Fraga GP, Frossard JL, Fry DE, Galeiras R, Ghnnam W, Gomes CA, Griffiths EA, Guirao X, Ahmed MH, Herzog T, Kim JI, Iqbal T, Isik A, Itani KMF, Labricciosa FM, Lee YY, Juang P, Karamarkovic A, Kim PK, Kluger Y, Leppaniemi A, Lohsiriwat V, Machain GM, Marwah S, Mazuski JE, Metan G, Moore EE, Moore FA, Ordoñez CA, Pagani L, Petrosillo N, Portela F, Rasa K, Rems M, Sakakushev BE, Segovia-Lohse H, Sganga G, Shelat VG, Spigaglia P, Tattevin P, Tranà C, Urbánek L, Ulrych J, Viale P, Baiocchi GL, Catena F. 2019 update of the WSES guidelines for management of Clostridioides ( Clostridium) difficile infection in surgical patients. World J Emerg Surg 2019. [PMID: 30858872 DOI: 10.1186/s13017-19-0228-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
In the last three decades, Clostridium difficile infection (CDI) has increased in incidence and severity in many countries worldwide. The increase in CDI incidence has been particularly apparent among surgical patients. Therefore, prevention of CDI and optimization of management in the surgical patient are paramount. An international multidisciplinary panel of experts from the World Society of Emergency Surgery (WSES) updated its guidelines for management of CDI in surgical patients according to the most recent available literature. The update includes recent changes introduced in the management of this infection.
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Affiliation(s)
- Massimo Sartelli
- Department of Surgery, Macerata Hospital, Via Santa Lucia 2, 62100 Macerata, Italy
| | - Stefano Di Bella
- 2Infectious Diseases Department, Trieste University Hospital, Trieste, Italy
| | - Lynne V McFarland
- 3Medicinal Chemistry, School of Pharmacy, University of Washington, Seattle, WA USA
| | - Sahil Khanna
- 4Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN USA
| | - Luis Furuya-Kanamori
- 5Research School of Population Health, Australian National University, Acton, ACT Australia
| | - Nadir Abuzeid
- 6Department of Microbiology, Faculty of Medical Laboratory Sciences, Omdurman Islamic University, Khartoum, Sudan
| | - Fikri M Abu-Zidan
- 7Department of Surgery, College of Medicine and Health Sciences, UAE University, Al-Ain, United Arab Emirates
| | - Luca Ansaloni
- 8Department of General Surgery, Bufalini Hospital, Cesena, Italy
| | - Goran Augustin
- 9Department of Surgery, University Hospital Centre Zagreb and School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Miklosh Bala
- 10Trauma and Acute Care Surgery Unit, Hadassah Hebrew University Medical Center, Jerusalem, Israel
| | - Offir Ben-Ishay
- 11Department of General Surgery, Rambam Health Care Campus, Haifa, Israel
| | - Walter L Biffl
- 12Trauma and Acute Care Surgery, Scripps Memorial Hospital La Jolla, La Jolla, CA USA
| | - Stephen M Brecher
- 13Pathology and Laboratory Medicine, VA Boston Healthcare System, West Roxbury MA and BU School of Medicine, Boston, MA USA
| | - Adrián Camacho-Ortiz
- Department of Internal Medicine, University Hospital, Dr. José E. González, Monterrey, Mexico
| | - Miguel A Caínzos
- 15Department of Surgery, University of Santiago de Compostela, A Coruña, Spain
| | - Shirley Chan
- 16Department of General Surgery, Medway Maritime Hospital, Gillingham, Kent UK
| | - Jill R Cherry-Bukowiec
- 17Department of Surgery, Division of Acute Care Surgery, University of Michigan, Ann Arbor, MI USA
| | - Jesse Clanton
- 18Department of Surgery, West Virginia University Charleston Division, Charleston, WV USA
| | | | - Maria E Cocuz
- 19Faculty of Medicine, Transilvania University, Infectious Diseases Hospital, Brasov, Romania
| | - Raul Coimbra
- 20Riverside University Health System Medical Center and Loma Linda University School of Medicine, Moreno Valley, CA USA
| | | | - Yunfeng Cui
- Department of Surgery, Tianjin Nankai Hospital, Nankai Clinical School of Medicine, Tianjin Medical University, Tianjin, China
| | - Jacek Czepiel
- 23Department of Infectious Diseases, Jagiellonian University, Medical College, Kraków, Poland
| | - Zaza Demetrashvili
- 24Department of Surgery, Tbilisi State Medical University, Kipshidze Central University Hospital, Tbilisi, Georgia
| | - Isidoro Di Carlo
- 25Department of Surgical Sciences, Cannizzaro Hospital, University of Catania, Catania, Italy
| | - Salomone Di Saverio
- 26Department of Surgery, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Irina M Dumitru
- 27Clinical Infectious Diseases Hospital, Ovidius University, Constanta, Romania
| | - Christian Eckmann
- Department of General, Visceral and Thoracic Surgery, Klinikum Peine, Hospital of Medical University Hannover, Peine, Germany
| | | | | | - Gustavo P Fraga
- 31Division of Trauma Surgery, Hospital de Clinicas, School of Medical Sciences, University of Campinas, Campinas, Brazil
| | - Jean L Frossard
- 32Service of Gastroenterology and Hepatology, Geneva University Hospital, Genève, Switzerland
| | - Donald E Fry
- 33Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL USA.,34University of New Mexico School of Medicine, Albuquerque, NM USA
| | - Rita Galeiras
- 35Critical Care Unit, Instituto de Investigación Biomédica de A Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), Sergas, Universidade da Coruña (UDC), A Coruña, Spain
| | - Wagih Ghnnam
- 36Department of Surgery Mansoura, Faculty of Medicine, Mansoura University, Mansoura, Egypt
| | - Carlos A Gomes
- 37Surgery Department, Hospital Universitario (HU) Terezinha de Jesus da Faculdade de Ciencias Medicas e da Saude de Juiz de Fora (SUPREMA), Hospital Universitario (HU) Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, Brazil
| | - Ewen A Griffiths
- 38Department of Surgery, Queen Elizabeth Hospital, Birmingham, UK
| | - Xavier Guirao
- Unit of Endocrine, Head, and Neck Surgery and Unit of Surgical Infections Support, Department of General Surgery, Parc Taulí, Hospital Universitari, Sabadell, Spain
| | - Mohamed H Ahmed
- 40Department of Medicine, Milton Keynes University Hospital NHS Foundation Trust, Milton Keynes, Buckinghamshire UK
| | - Torsten Herzog
- 41Department of Surgery, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Jae Il Kim
- 42Department of Surgery, Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Republic of Korea
| | - Tariq Iqbal
- 43Department of Gastroenterology, Queen Elizabeth Hospital, Birmingham, UK
| | - Arda Isik
- 44General Surgery Department, Magee Womens Hospital, UPMC, Pittsburgh, USA
| | - Kamal M F Itani
- 45Department of Surgery, VA Boston Health Care System, Boston University and Harvard Medical School, Boston, MA USA
| | | | - Yeong Y Lee
- 47School of Medical Sciences, University Sains Malaysia, Kota Bharu, Kelantan Malaysia
| | - Paul Juang
- 48Department of Pharmacy Practice, St Louis College of Pharmacy, St Louis, MO USA
| | - Aleksandar Karamarkovic
- Faculty of Mediine University of Belgrade Clinic for Surgery "Nikola Spasic", University Clinical Center "Zvezdara" Belgrade, Belgrade, Serbia
| | - Peter K Kim
- 50Department of Surgery, Jacobi Medical Center, Albert Einstein College of Medicine, Bronx, NY USA
| | - Yoram Kluger
- 11Department of General Surgery, Rambam Health Care Campus, Haifa, Israel
| | - Ari Leppaniemi
- 51Abdominal Center, Helsinki University Hospital Meilahti, Helsinki, Finland
| | - Varut Lohsiriwat
- 52Department of Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Gustavo M Machain
- 53Department of Surgery, Universidad Nacional de Asuncion, Asuncion, Paraguay
| | - Sanjay Marwah
- 54Department of Surgery, Post-Graduate Institute of Medical Sciences, Rohtak, India
| | - John E Mazuski
- 55Department of Surgery, Washington University School of Medicine, Saint Louis, USA
| | - Gokhan Metan
- 56Department of Infectious Diseases and Clinical Microbiology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Ernest E Moore
- Department of Surgery, University of Colorado, Denver Health Medical Center, Denver, CO USA
| | | | - Carlos A Ordoñez
- 59Department of Surgery, Fundación Valle del Lili, Hospital Universitario del Valle, Universidad del Valle, Cali, Colombia
| | - Leonardo Pagani
- Infectious Diseases Unit, Bolzano Central Hospital, Bolzano, Italy
| | - Nicola Petrosillo
- National Institute for Infectious Diseases - INMI - Lazzaro Spallanzani IRCCS, Rome, Italy
| | - Francisco Portela
- 62Gastroenterology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Kemal Rasa
- Department of Surgery, Anadolu Medical Center, Kocaali, Turkey
| | - Miran Rems
- Department of Abdominal and General Surgery, General Hospital Jesenice, Jesenice, Slovenia
| | - Boris E Sakakushev
- 65Department of Surgery, Medical University of Plovdiv, Plovdiv, Bulgaria
| | | | - Gabriele Sganga
- 66Division of Emergency Surgery, Department of Surgery, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Vishal G Shelat
- 67Department of Surgery, Tan Tock Seng Hospital, Singapore, Singapore
| | - Patrizia Spigaglia
- 68Department of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy
| | - Pierre Tattevin
- 69Infectious Diseases and Intensive Care Unit, Pontchaillou University Hospital, Rennes, France
| | - Cristian Tranà
- Department of Surgery, Macerata Hospital, Via Santa Lucia 2, 62100 Macerata, Italy
| | - Libor Urbánek
- 70First Department of Surgery, Faculty of Medicine, Masaryk University Brno and University Hospital of St. Ann Brno, Brno, Czech Republic
| | - Jan Ulrych
- 71First Department of Surgery, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic
| | - Pierluigi Viale
- 72Clinic of Infectious Diseases, St Orsola-Malpighi University Hospital, Bologna, Italy
| | - Gian L Baiocchi
- 73Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Fausto Catena
- 74Emergency Surgery Department, Maggiore Parma Hospital, Parma, Italy
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17
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Sartelli M, Di Bella S, McFarland LV, Khanna S, Furuya-Kanamori L, Abuzeid N, Abu-Zidan FM, Ansaloni L, Augustin G, Bala M, Ben-Ishay O, Biffl WL, Brecher SM, Camacho-Ortiz A, Caínzos MA, Chan S, Cherry-Bukowiec JR, Clanton J, Coccolini F, Cocuz ME, Coimbra R, Cortese F, Cui Y, Czepiel J, Demetrashvili Z, Di Carlo I, Di Saverio S, Dumitru IM, Eckmann C, Eiland EH, Forrester JD, Fraga GP, Frossard JL, Fry DE, Galeiras R, Ghnnam W, Gomes CA, Griffiths EA, Guirao X, Ahmed MH, Herzog T, Kim JI, Iqbal T, Isik A, Itani KMF, Labricciosa FM, Lee YY, Juang P, Karamarkovic A, Kim PK, Kluger Y, Leppaniemi A, Lohsiriwat V, Machain GM, Marwah S, Mazuski JE, Metan G, Moore EE, Moore FA, Ordoñez CA, Pagani L, Petrosillo N, Portela F, Rasa K, Rems M, Sakakushev BE, Segovia-Lohse H, Sganga G, Shelat VG, Spigaglia P, Tattevin P, Tranà C, Urbánek L, Ulrych J, Viale P, Baiocchi GL, Catena F. 2019 update of the WSES guidelines for management of Clostridioides ( Clostridium) difficile infection in surgical patients. World J Emerg Surg 2019; 14:8. [PMID: 30858872 PMCID: PMC6394026 DOI: 10.1186/s13017-019-0228-3] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 02/17/2019] [Indexed: 02/08/2023] Open
Abstract
In the last three decades, Clostridium difficile infection (CDI) has increased in incidence and severity in many countries worldwide. The increase in CDI incidence has been particularly apparent among surgical patients. Therefore, prevention of CDI and optimization of management in the surgical patient are paramount. An international multidisciplinary panel of experts from the World Society of Emergency Surgery (WSES) updated its guidelines for management of CDI in surgical patients according to the most recent available literature. The update includes recent changes introduced in the management of this infection.
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Affiliation(s)
- Massimo Sartelli
- Department of Surgery, Macerata Hospital, Via Santa Lucia 2, 62100 Macerata, Italy
| | - Stefano Di Bella
- 0000000459364044grid.460062.6Infectious Diseases Department, Trieste University Hospital, Trieste, Italy
| | - Lynne V. McFarland
- 0000000122986657grid.34477.33Medicinal Chemistry, School of Pharmacy, University of Washington, Seattle, WA USA
| | - Sahil Khanna
- 0000 0004 0459 167Xgrid.66875.3aDivision of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN USA
| | - Luis Furuya-Kanamori
- 0000 0001 2180 7477grid.1001.0Research School of Population Health, Australian National University, Acton, ACT Australia
| | - Nadir Abuzeid
- grid.442422.6Department of Microbiology, Faculty of Medical Laboratory Sciences, Omdurman Islamic University, Khartoum, Sudan
| | - Fikri M. Abu-Zidan
- 0000 0001 2193 6666grid.43519.3aDepartment of Surgery, College of Medicine and Health Sciences, UAE University, Al-Ain, United Arab Emirates
| | - Luca Ansaloni
- 0000 0004 1758 8744grid.414682.dDepartment of General Surgery, Bufalini Hospital, Cesena, Italy
| | - Goran Augustin
- 0000 0001 0657 4636grid.4808.4Department of Surgery, University Hospital Centre Zagreb and School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Miklosh Bala
- 0000 0001 2221 2926grid.17788.31Trauma and Acute Care Surgery Unit, Hadassah Hebrew University Medical Center, Jerusalem, Israel
| | - Offir Ben-Ishay
- 0000 0000 9950 8111grid.413731.3Department of General Surgery, Rambam Health Care Campus, Haifa, Israel
| | - Walter L. Biffl
- 0000 0004 0449 3295grid.415402.6Trauma and Acute Care Surgery, Scripps Memorial Hospital La Jolla, La Jolla, CA USA
| | - Stephen M. Brecher
- 0000 0004 0367 5222grid.475010.7Pathology and Laboratory Medicine, VA Boston Healthcare System, West Roxbury MA and BU School of Medicine, Boston, MA USA
| | - Adrián Camacho-Ortiz
- Department of Internal Medicine, University Hospital, Dr. José E. González, Monterrey, Mexico
| | - Miguel A. Caínzos
- 0000000109410645grid.11794.3aDepartment of Surgery, University of Santiago de Compostela, A Coruña, Spain
| | - Shirley Chan
- grid.439210.dDepartment of General Surgery, Medway Maritime Hospital, Gillingham, Kent UK
| | - Jill R. Cherry-Bukowiec
- 0000000086837370grid.214458.eDepartment of Surgery, Division of Acute Care Surgery, University of Michigan, Ann Arbor, MI USA
| | - Jesse Clanton
- 0000 0001 2156 6140grid.268154.cDepartment of Surgery, West Virginia University Charleston Division, Charleston, WV USA
| | - Federico Coccolini
- 0000 0004 1758 8744grid.414682.dDepartment of General Surgery, Bufalini Hospital, Cesena, Italy
| | - Maria E. Cocuz
- 0000 0001 2159 8361grid.5120.6Faculty of Medicine, Transilvania University, Infectious Diseases Hospital, Brasov, Romania
| | - Raul Coimbra
- 0000 0000 9852 649Xgrid.43582.38Riverside University Health System Medical Center and Loma Linda University School of Medicine, Moreno Valley, CA USA
| | | | - Yunfeng Cui
- Department of Surgery, Tianjin Nankai Hospital, Nankai Clinical School of Medicine, Tianjin Medical University, Tianjin, China
| | - Jacek Czepiel
- 0000 0001 2162 9631grid.5522.0Department of Infectious Diseases, Jagiellonian University, Medical College, Kraków, Poland
| | - Zaza Demetrashvili
- 0000 0004 0428 8304grid.412274.6Department of Surgery, Tbilisi State Medical University, Kipshidze Central University Hospital, Tbilisi, Georgia
| | - Isidoro Di Carlo
- 0000 0004 1757 1969grid.8158.4Department of Surgical Sciences, Cannizzaro Hospital, University of Catania, Catania, Italy
| | - Salomone Di Saverio
- 0000 0004 0622 5016grid.120073.7Department of Surgery, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Irina M. Dumitru
- 0000 0001 1089 1079grid.412430.0Clinical Infectious Diseases Hospital, Ovidius University, Constanta, Romania
| | - Christian Eckmann
- Department of General, Visceral and Thoracic Surgery, Klinikum Peine, Hospital of Medical University Hannover, Peine, Germany
| | | | - Joseph D. Forrester
- 0000000419368956grid.168010.eDepartment of Surgery, Stanford University, Stanford, CA USA
| | - Gustavo P. Fraga
- 0000 0001 0723 2494grid.411087.bDivision of Trauma Surgery, Hospital de Clinicas, School of Medical Sciences, University of Campinas, Campinas, Brazil
| | - Jean L. Frossard
- 0000 0001 0721 9812grid.150338.cService of Gastroenterology and Hepatology, Geneva University Hospital, Genève, Switzerland
| | - Donald E. Fry
- 0000 0001 2299 3507grid.16753.36Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL USA
- 0000 0001 2188 8502grid.266832.bUniversity of New Mexico School of Medicine, Albuquerque, NM USA
| | - Rita Galeiras
- 0000 0001 2176 8535grid.8073.cCritical Care Unit, Instituto de Investigación Biomédica de A Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), Sergas, Universidade da Coruña (UDC), A Coruña, Spain
| | - Wagih Ghnnam
- 0000000103426662grid.10251.37Department of Surgery Mansoura, Faculty of Medicine, Mansoura University, Mansoura, Egypt
| | - Carlos A. Gomes
- 0000 0001 2170 9332grid.411198.4Surgery Department, Hospital Universitario (HU) Terezinha de Jesus da Faculdade de Ciencias Medicas e da Saude de Juiz de Fora (SUPREMA), Hospital Universitario (HU) Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, Brazil
| | - Ewen A. Griffiths
- 0000 0001 2177 007Xgrid.415490.dDepartment of Surgery, Queen Elizabeth Hospital, Birmingham, UK
| | - Xavier Guirao
- Unit of Endocrine, Head, and Neck Surgery and Unit of Surgical Infections Support, Department of General Surgery, Parc Taulí, Hospital Universitari, Sabadell, Spain
| | - Mohamed H. Ahmed
- grid.415667.7Department of Medicine, Milton Keynes University Hospital NHS Foundation Trust, Milton Keynes, Buckinghamshire UK
| | - Torsten Herzog
- grid.416438.cDepartment of Surgery, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Jae Il Kim
- 0000 0004 0371 8173grid.411633.2Department of Surgery, Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Republic of Korea
| | - Tariq Iqbal
- 0000 0001 2177 007Xgrid.415490.dDepartment of Gastroenterology, Queen Elizabeth Hospital, Birmingham, UK
| | - Arda Isik
- 0000 0004 0455 1723grid.411487.fGeneral Surgery Department, Magee Womens Hospital, UPMC, Pittsburgh, USA
| | - Kamal M. F. Itani
- 000000041936754Xgrid.38142.3cDepartment of Surgery, VA Boston Health Care System, Boston University and Harvard Medical School, Boston, MA USA
| | | | - Yeong Y. Lee
- 0000 0001 2294 3534grid.11875.3aSchool of Medical Sciences, University Sains Malaysia, Kota Bharu, Kelantan Malaysia
| | - Paul Juang
- 0000 0000 8660 3507grid.419579.7Department of Pharmacy Practice, St Louis College of Pharmacy, St Louis, MO USA
| | - Aleksandar Karamarkovic
- Faculty of Mediine University of Belgrade Clinic for Surgery “Nikola Spasic”, University Clinical Center “Zvezdara” Belgrade, Belgrade, Serbia
| | - Peter K. Kim
- 0000000121791997grid.251993.5Department of Surgery, Jacobi Medical Center, Albert Einstein College of Medicine, Bronx, NY USA
| | - Yoram Kluger
- 0000 0000 9950 8111grid.413731.3Department of General Surgery, Rambam Health Care Campus, Haifa, Israel
| | - Ari Leppaniemi
- 0000 0000 9950 5666grid.15485.3dAbdominal Center, Helsinki University Hospital Meilahti, Helsinki, Finland
| | - Varut Lohsiriwat
- 0000 0004 1937 0490grid.10223.32Department of Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Gustavo M. Machain
- 0000 0001 2289 5077grid.412213.7Department of Surgery, Universidad Nacional de Asuncion, Asuncion, Paraguay
| | - Sanjay Marwah
- 0000 0004 1771 1642grid.412572.7Department of Surgery, Post-Graduate Institute of Medical Sciences, Rohtak, India
| | - John E. Mazuski
- 0000 0001 2355 7002grid.4367.6Department of Surgery, Washington University School of Medicine, Saint Louis, USA
| | - Gokhan Metan
- 0000 0001 2342 7339grid.14442.37Department of Infectious Diseases and Clinical Microbiology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Ernest E. Moore
- Department of Surgery, University of Colorado, Denver Health Medical Center, Denver, CO USA
| | - Frederick A. Moore
- 0000 0004 1936 8091grid.15276.37Department of Surgery, University of Florida, Gainesville, FL USA
| | - Carlos A. Ordoñez
- 0000 0001 2295 7397grid.8271.cDepartment of Surgery, Fundación Valle del Lili, Hospital Universitario del Valle, Universidad del Valle, Cali, Colombia
| | - Leonardo Pagani
- Infectious Diseases Unit, Bolzano Central Hospital, Bolzano, Italy
| | - Nicola Petrosillo
- National Institute for Infectious Diseases - INMI - Lazzaro Spallanzani IRCCS, Rome, Italy
| | - Francisco Portela
- 0000000106861985grid.28911.33Gastroenterology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Kemal Rasa
- Department of Surgery, Anadolu Medical Center, Kocaali, Turkey
| | - Miran Rems
- Department of Abdominal and General Surgery, General Hospital Jesenice, Jesenice, Slovenia
| | - Boris E. Sakakushev
- 0000 0001 0726 0380grid.35371.33Department of Surgery, Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Helmut Segovia-Lohse
- 0000 0001 2289 5077grid.412213.7Department of Surgery, Universidad Nacional de Asuncion, Asuncion, Paraguay
| | - Gabriele Sganga
- grid.414603.4Division of Emergency Surgery, Department of Surgery, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Vishal G. Shelat
- grid.240988.fDepartment of Surgery, Tan Tock Seng Hospital, Singapore, Singapore
| | - Patrizia Spigaglia
- 0000 0000 9120 6856grid.416651.1Department of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy
| | - Pierre Tattevin
- grid.414271.5Infectious Diseases and Intensive Care Unit, Pontchaillou University Hospital, Rennes, France
| | - Cristian Tranà
- Department of Surgery, Macerata Hospital, Via Santa Lucia 2, 62100 Macerata, Italy
| | - Libor Urbánek
- 0000 0001 2194 0956grid.10267.32First Department of Surgery, Faculty of Medicine, Masaryk University Brno and University Hospital of St. Ann Brno, Brno, Czech Republic
| | - Jan Ulrych
- 0000 0000 9100 9940grid.411798.2First Department of Surgery, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic
| | - Pierluigi Viale
- grid.412311.4Clinic of Infectious Diseases, St Orsola-Malpighi University Hospital, Bologna, Italy
| | - Gian L. Baiocchi
- 0000000417571846grid.7637.5Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Fausto Catena
- grid.411482.aEmergency Surgery Department, Maggiore Parma Hospital, Parma, Italy
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18
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Cobo J. A comprehensive approach for the patient with Clostridium difficile infection. Rev Esp Quimioter 2018; 31 Suppl 1:27-31. [PMID: 30209919 PMCID: PMC6459568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
During the last decade there have been many changes and advances in the research on Clostridium difficile infection (CDI). We have improved diagnostic and therapeutic tools and, at the same time, we have learned that the CDI implies, especially in the most vulnerable patients, an important morbidity. CDI has traditionally been undervalued and it is widely dispersed in hospitals. Surely, there is inertness in its management and there are also broad areas of improvement. If we add to this the high cost of the new drugs and the practical difficulties to implement the faecal microbiota transplant, we realize that we may not be taking full advantage of all the opportunities to improve patient's outcomes. The implementation of policies that favour the supervision of all CDI cases by an expert in infectious diseases will contribute to a better global management of this important disease.
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19
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Abstract
The pathogenesis of recurrent Clostridium difficile infection (CDI) is still poorly understood. The risk of recurrence is approximately 20% after an initial CDI episode and dramatically increases with subsequent CDI recurrences. Several factors may play a role in recurrent CDI (rCDI), including conditions influencing germination, metabolic pathways that influence toxin production of C. difficile, and the microbiota composition offering protection against colonization and disease caused by C. difficile. Paradoxically, the currently recommended treatment for acute symptomatic CDI, i.e. metronidazole or vancomycin, can cause modification of the intestinal flora. Indeed, administration of anti-CDI antibiotics leads to suppression of C. difficile, along with collateral damage of the protective intestinal microbiota and opening of a "window of vulnerability" for recurrence. Host factors also have a prominent role, including innate and acquired humoral immunity, i.e. passive antibodies administration or active vaccination as a prevention strategy. They play a crucial role in the protection against severe and recurrent CDI. The assessment of risk factors of recurrence and modeling prediction scores could help in preventing the troublesome experience of CDI recurrence. Six studies have methodologically assessed prediction scores for rCDI. However, the definition of recurrence was heterogeneous, external validation was often not performed, and immunological factors were often not considered. There is a need for further studies on the pathophysiology of recurrence to design models for prediction that are sound and applicable in clinical practice.
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Affiliation(s)
- N Petrosillo
- Clinical and Research Department for Infectious Diseases, National Institute for Infectious Diseases L. Spallanzani, Via Portuense 292, 00149 Rome, Italy.
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20
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Sartelli M, Malangoni MA, Abu-Zidan FM, Griffiths EA, Di Bella S, McFarland LV, Eltringham I, Shelat VG, Velmahos GC, Kelly CP, Khanna S, Abdelsattar ZM, Alrahmani L, Ansaloni L, Augustin G, Bala M, Barbut F, Ben-Ishay O, Bhangu A, Biffl WL, Brecher SM, Camacho-Ortiz A, Caínzos MA, Canterbury LA, Catena F, Chan S, Cherry-Bukowiec JR, Clanton J, Coccolini F, Cocuz ME, Coimbra R, Cook CH, Cui Y, Czepiel J, Das K, Demetrashvili Z, Di Carlo I, Di Saverio S, Dumitru IM, Eckert C, Eckmann C, Eiland EH, Enani MA, Faro M, Ferrada P, Forrester JD, Fraga GP, Frossard JL, Galeiras R, Ghnnam W, Gomes CA, Gorrepati V, Ahmed MH, Herzog T, Humphrey F, Kim JI, Isik A, Ivatury R, Lee YY, Juang P, Furuya-Kanamori L, Karamarkovic A, Kim PK, Kluger Y, Ko WC, LaBarbera FD, Lee JG, Leppaniemi A, Lohsiriwat V, Marwah S, Mazuski JE, Metan G, Moore EE, Moore FA, Nord CE, Ordoñez CA, Júnior GAP, Petrosillo N, Portela F, Puri BK, Ray A, Raza M, Rems M, Sakakushev BE, Sganga G, Spigaglia P, Stewart DB, Tattevin P, Timsit JF, To KB, Tranà C, Uhl W, Urbánek L, van Goor H, Vassallo A, Zahar JR, Caproli E, Viale P. WSES guidelines for management of Clostridium difficile infection in surgical patients. World J Emerg Surg 2015; 10:38. [PMID: 26300956 PMCID: PMC4545872 DOI: 10.1186/s13017-015-0033-6] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2015] [Accepted: 08/12/2015] [Indexed: 02/08/2023] Open
Abstract
In the last two decades there have been dramatic changes in the epidemiology of Clostridium difficile infection (CDI), with increases in incidence and severity of disease in many countries worldwide. The incidence of CDI has also increased in surgical patients. Optimization of management of C difficile, has therefore become increasingly urgent. An international multidisciplinary panel of experts prepared evidenced-based World Society of Emergency Surgery (WSES) guidelines for management of CDI in surgical patients.
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Affiliation(s)
- Massimo Sartelli
- />Department of Surgery, Macerata Hospital, Via Santa Lucia 2, 62019 Macerata, Italy
| | | | - Fikri M. Abu-Zidan
- />Department of Surgery, College of Medicine and Health Sciences, UAE University, Al-Ain, United Arab Emirates
| | | | - Stefano Di Bella
- />2nd Infectious Diseases Division, National Institute for Infectious Diseases L. Spallanzani, Rome, Italy
| | - Lynne V. McFarland
- />Department of Medicinal Chemistry, School of Pharmacy, University of Washington, Washington, USA
| | - Ian Eltringham
- />Department of Medical Microbiology, King’s College Hospital, London, UK
| | - Vishal G. Shelat
- />Department of Surgery, Tan Tock Seng Hospital, Singapore, Singapore
| | - George C. Velmahos
- />Emergency Surgery, and Surgical Critical Care, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - Ciarán P. Kelly
- />Gastroenterology Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA USA
| | - Sahil Khanna
- />Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN USA
| | | | - Layan Alrahmani
- />Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI USA
| | - Luca Ansaloni
- />General Surgery I, Papa Giovanni XXIII Hospital, Bergamo, Italy
| | - Goran Augustin
- />Department of Surgery, University Hospital Center Zagreb and School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Miklosh Bala
- />Trauma and Acute Care Surgery Unit, Hadassah Hebrew University Medical Center, Jerusalem, Israel
| | - Frédéric Barbut
- />UHLIN (Unité d’Hygiène et de Lutte contre les Infections Nosocomiales) National Reference Laboratory for Clostridium difficile Groupe Hospitalier de l’Est Parisien (HUEP), Paris, France
| | - Offir Ben-Ishay
- />Department of General Surgery, Rambam Health Care Campus, Haifa, Israel
| | - Aneel Bhangu
- />Academic Department of Surgery, Queen Elizabeth Hospital, Edgbaston, Birmingham, UK
| | - Walter L. Biffl
- />Department of Surgery, University of Colorado, Denver Health Medical Center, Denver, USA
| | - Stephen M. Brecher
- />Pathology and Laboratory Medicine, VA Boston Healthcare System, West Roxbury MA and BU School of Medicine, Boston, MA USA
| | - Adrián Camacho-Ortiz
- />Department of Internal Medicine, University Hospital, Dr.José E. González, Monterrey, Mexico
| | - Miguel A. Caínzos
- />Department of Surgery, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Laura A. Canterbury
- />Department of Pathology, University of Alberta Edmonton, Edmonton, AB Canada
| | - Fausto Catena
- />Emergency Surgery Department, Maggiore Parma Hospital, Parma, Italy
| | - Shirley Chan
- />Department of General Surgery, Medway Maritime Hospital, Gillingham Kent, UK
| | - Jill R. Cherry-Bukowiec
- />Department of Surgery, Division of Acute Care Surgery, University of Michigan, Ann Arbor, MI USA
| | - Jesse Clanton
- />Department of Surgery, Northeast Ohio Medical University, Summa Akron City Hospital, Akron, OH USA
| | | | - Maria Elena Cocuz
- />Faculty of Medicine, Transilvania University, Infectious Diseases Hospital, Brasov, Romania
| | - Raul Coimbra
- />Division of Trauma, Surgical Critical Care, Burns, and Acute Care Surgery, University of California San Diego Health Science, San Diego, USA
| | - Charles H. Cook
- />Division of Acute Care Surgery, Trauma and Surgical Critical Care, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA USA
| | - Yunfeng Cui
- />Department of Surgery,Tianjin Nankai Hospital, Nankai Clinical School of Medicine, Tianjin Medical University, Tianjin, China
| | - Jacek Czepiel
- />Department of Infectious Diseases, Jagiellonian University, Medical College, Kraków, Poland
| | - Koray Das
- />Department of General Surgery, Adana Numune Training and Research Hospital, Adana, Turkey
| | - Zaza Demetrashvili
- />Department of Surgery, Tbilisi State Medical University, Kipshidze Central University Hospital, Tbilisi, Georgia
| | | | | | | | - Catherine Eckert
- />National Reference Laboratory for Clostridium difficile, AP-HP, Saint-Antoine Hospital, Paris, France
| | - Christian Eckmann
- />Department of General, Visceral and Thoracic Surgery, Klinikum Peine, Hospital of Medical University Hannover, Peine, Germany
| | | | - Mushira Abdulaziz Enani
- />Department of Medicine, Section of Infectious Diseases, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Mario Faro
- />Department of General Surgery, Trauma and Emergency Surgery Division, ABC Medical School, Santo André, SP Brazil
| | - Paula Ferrada
- />Division of Trauma, Critical Care and Emergency Surgery, Virginia Commonwealth University, Richmond, VA USA
| | | | - Gustavo P. Fraga
- />Division of Trauma Surgery, Hospital de Clinicas, School of Medical Sciences, University of Campinas, Campinas, Brazil
| | - Jean Louis Frossard
- />Service of Gastroenterology and Hepatology, Geneva University Hospital, Genève, Switzerland
| | - Rita Galeiras
- />Critical Care Unit, Instituto de Investigación Biomédica de A Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), Sergas, Universidade da Coruña (UDC), A Coruña, Spain
| | - Wagih Ghnnam
- />Department of Surgery Mansoura, Faculty of Medicine, Mansoura University, Mansoura, Egypt
| | - Carlos Augusto Gomes
- />Surgery Department, Hospital Universitario (HU) Terezinha de Jesus da Faculdade de Ciencias Medicas e da Saude de Juiz de Fora (SUPREMA), Hospital Universitario (HU) Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, Brazil
| | - Venkata Gorrepati
- />Department of Internal Medicine, Pinnacle Health Hospital, Harrisburg, PA USA
| | - Mohamed Hassan Ahmed
- />Department of Medicine, Milton Keynes University Hospital NHS Foundation Trust, Milton Keynes, Buckinghamshire UK
| | - Torsten Herzog
- />Department of Surgery, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Felicia Humphrey
- />Department of Gastroenterology and Hepatology, Ochsner Clinic Foundation, New Orleans, LA USA
| | - Jae Il Kim
- />Department of Surgery, Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Republic of Korea
| | - Arda Isik
- />General Surgery Department, Erzincan University Mengücek Gazi Training and Research Hospital, Erzincan, Turkey
| | - Rao Ivatury
- />Division of Trauma, Critical Care and Emergency Surgery, Virginia Commonwealth University, Richmond, VA USA
| | - Yeong Yeh Lee
- />School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Kelantan Malaysia
| | - Paul Juang
- />Department of Pharmacy Practice, St Louis College of Pharmacy, St Louis, MO USA
| | - Luis Furuya-Kanamori
- />Research School of Population Health, The Australian National University, Acton, ACT Australia
| | - Aleksandar Karamarkovic
- />Clinic For Emergency surgery, University Clinical Center of Serbia, Faculty of Medicine University of Belgrade, Belgrade, Serbia
| | - Peter K Kim
- />General and Trauma Surgery, Albert Einstein College of Medicine, North Bronx Healthcare Network, Bronx, NY USA
| | - Yoram Kluger
- />Department of General Surgery, Rambam Health Care Campus, Haifa, Israel
| | - Wen Chien Ko
- />Division of Infectious Diseases, Department of Internal Medicine, National Cheng Kung University Hospital, Tainan, Taiwan
| | | | - Jae Gil Lee
- />Division of Critical Care & Trauma Surgery, Department of Surgery, Yonsei University College of Medicine, Seoul, South Korea
| | - Ari Leppaniemi
- />Abdominal Center, Helsinki University Hospital Meilahti, Helsinki, Finland
| | - Varut Lohsiriwat
- />Department of Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Sanjay Marwah
- />Department of Surgery, Post-Graduate Institute of Medical Sciences, Rohtak, India
| | - John E. Mazuski
- />Department of Surgery, Washington University School of Medicine, Saint Louis, USA
| | - Gokhan Metan
- />Department of Infectious Diseases and Clinical Microbiology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Ernest E. Moore
- />Department of Surgery, University of Colorado, Denver Health Medical Center, Denver, USA
| | | | - Carl Erik Nord
- />Department of Laboratory Medicine, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden
| | - Carlos A. Ordoñez
- />Department of Surgery, Fundación Valle del Lili, Hospital Universitario del Valle, Universidad del Valle, Cali, Colombia
| | | | - Nicola Petrosillo
- />2nd Infectious Diseases Division, National Institute for Infectious Diseases L. Spallanzani, Rome, Italy
| | - Francisco Portela
- />Gastroenterology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Basant K. Puri
- />Department of Medicine, Hammersmith Hospital and Imperial College London, London, UK
| | - Arnab Ray
- />Department of Gastroenterology and Hepatology, Ochsner Clinic Foundation, New Orleans, LA USA
| | - Mansoor Raza
- />Infectious Diseases and Microbiology Unit, Milton Keynes University Hospital NHS Foundation Trust, Milton Keynes, Buckinghamshire UK
| | - Miran Rems
- />Department of Abdominal and General Surgery, General Hospital Jesenice, Jesenice, Slovenia
| | | | - Gabriele Sganga
- />Division of General Surgery and Organ Transplantation, Department of Surgery, Catholic University of the Sacred Heart, Rome, Italy
| | - Patrizia Spigaglia
- />Department of Infectious, Parasitic and Immune-Mediated Diseases, Istituto Superiore di Sanità, Rome, Italy
| | - David B. Stewart
- />Department of Surgery, The Pennsylvania State University, College of Medicine, Hershey, PA USA
| | - Pierre Tattevin
- />Infectious Diseases and Intensive Care Unit, Pontchaillou University Hospital, Rennes, France
| | | | - Kathleen B. To
- />Department of Surgery, Division of Acute Care Surgery, University of Michigan, Ann Arbor, MI USA
| | - Cristian Tranà
- />Emergency Medicine and Surgery, Macerata hospital, Macerata, Italy
| | - Waldemar Uhl
- />Department of Surgery, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Libor Urbánek
- />1st Surgical Clinic, University Hospital of St. Ann Brno, Brno, Czech Republic
| | - Harry van Goor
- />Department of Surgery, Radboud University Medical Center, Nijmegen, Netherlands
| | - Angela Vassallo
- />Infection Prevention/Epidemiology, Providence Saint John’s Health Center, Santa Monica, CA USA
| | - Jean Ralph Zahar
- />Infection Control Unit, Angers University, CHU d’Angers, Angers, France
| | - Emanuele Caproli
- />Department of Surgery, Ancona University Hospital, Ancona, Italy
| | - Pierluigi Viale
- />Clinic of Infectious Diseases, St Orsola-Malpighi University Hospital, Bologna, Italy
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Ferguson RP. Editor’s notes. J Community Hosp Intern Med Perspect 2015; 5:27294. [PMID: 25656677 PMCID: PMC4318831 DOI: 10.3402/jchimp.v5.27294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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