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Bergmark RW, Jin G, Semco RS, Santolini M, Olsen MA, Dhand A. Association of hospital centrality in inter-hospital patient-sharing networks with patient mortality and length of stay. PLoS One 2023; 18:e0281871. [PMID: 36920981 PMCID: PMC10016671 DOI: 10.1371/journal.pone.0281871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 02/02/2023] [Indexed: 03/16/2023] Open
Abstract
OBJECTIVE The interdependence of hospitals is underappreciated in patient outcomes studies. We used a network science approach to foreground this interdependence. Specifically, within two large state-based interhospital networks, we examined the relationship of a hospital's network position with in-hospital mortality and length of stay. METHODS We constructed interhospital network graphs using data from the Healthcare Cost and Utilization Project and the American Hospital Association Annual Survey for Florida (2014) and California (2011). The exposure of interest was hospital centrality, defined as weighted degree (sum of all ties to a given hospital from other hospitals). The outcomes were in-hospital mortality and length of stay with sub-analyses for four acute medical conditions: pneumonia, heart failure, ischemic stroke, myocardial infarction. We compared outcomes for each quartile of hospital centrality relative to the most central quartile (Q4), independent of patient- and hospital-level characteristics, in this retrospective cross-sectional study. RESULTS The inpatient cohorts had 1,246,169 patients in Florida and 1,415,728 in California. Compared to Florida's central hospitals which had an overall mortality 1.60%, peripheral hospitals had higher in-hospital mortality (1.97%, adjusted OR (95%CI): Q1 1.61 (1.37, 1.89), p<0.001). Hospitals in the middle quartiles had lower in-hospital mortality compared to central hospitals (%, adjusted OR (95% CI): Q2 1.39%, 0.79 (0.70, 0.89), p<0.001; Q3 1.33%, 0.78 (0.70, 0.87), p<0.001). Peripheral hospitals had longer lengths of stay (adjusted incidence rate ratio (95% CI): Q1 2.47 (2.44, 2.50), p<0.001). These findings were replicated in California, and in patients with heart failure and pneumonia in Florida. These results show a u-shaped distribution of outcomes based on hospital network centrality quartile. CONCLUSIONS The position of hospitals within an inter-hospital network is associated with patient outcomes. Specifically, hospitals located in the peripheral or central positions may be most vulnerable to diminished quality outcomes due to the network. Results should be replicated with deeper clinical data.
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Affiliation(s)
- Regan W. Bergmark
- Center for Surgery and Public Health, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States of America
- Brigham and Women’s Hospital and Dana Farber Cancer Institute and Department of Otolaryngology-Head and Neck Surgery, Division of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA, United States of America
| | - Ginger Jin
- Center for Surgery and Public Health, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Robert S. Semco
- Center for Surgery and Public Health, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Marc Santolini
- Université Paris Cité, Inserm, System Engineering and Evolution Dynamics, Paris, France
- Network Science Institute, Northeastern University, Boston, MA, United States of America
| | - Margaret A. Olsen
- Department of Medicine, Division of Infectious Disease, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Amar Dhand
- Network Science Institute, Northeastern University, Boston, MA, United States of America
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States of America
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2
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Fridkin SK. Advances in Data-Driven Responses to Preventing Spread of Antibiotic Resistance Across Health-Care Settings. Epidemiol Rev 2020; 41:6-12. [PMID: 31673712 DOI: 10.1093/epirev/mxz010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Revised: 05/08/2019] [Accepted: 09/13/2019] [Indexed: 12/25/2022] Open
Abstract
Among the most urgent and serious threats to public health are 7 antibiotic-resistant bacterial infections predominately acquired during health-care delivery. There is an emerging field of health-care epidemiology that is focused on preventing health care-associated infections with antibiotic-resistant bacteria and incorporates data from patient transfers or patient movements within and between facilities. This analytic field is being used to help public health professionals identify best opportunities for prevention. Different analytic approaches that draw on uses of big data are being explored to help target the use of limited public health resources, leverage expertise, and enact effective policy to maximize an impact on population-level health. Here, the following recent advances in data-driven responses to preventing spread of antibiotic resistance across health-care settings are summarized: leveraging big data for machine learning, integration or advances in tracking patient movement, and highlighting the value of coordinating response across institutions within a region.
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Affiliation(s)
- Scott K Fridkin
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia.,Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
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3
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Spread of Carbapenem-Resistant Klebsiella pneumoniae in Hub and Spoke Connected Health-Care Networks: A Case Study from Italy. Microorganisms 2019; 8:microorganisms8010037. [PMID: 31878097 PMCID: PMC7022417 DOI: 10.3390/microorganisms8010037] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 12/16/2019] [Indexed: 11/30/2022] Open
Abstract
The study describes the spread of carbapenem-resistant Klebsiella pneumoniae (CRKP) in a regional healthcare network in Italy. The project included several stages: (1) Establishment of a laboratory-based regional surveillance network, including all the acute care hospitals of the Marches Region (n = 20). (2) Adoption of a shared protocol for the surveillance of Multi-Drug Resistant Organisms (MDROs). Only the first CRKP isolate for each patient has been included in the surveillance in each hospital. The anonymous tracking of patients, and their subsequent microbial records within the hospital network, allowed detection of networks of inter-hospital exchange of CRKP and its comparison with transfer of patients within the hospital network. Pulsed-Field Gel Electrophoresis (PFGE) analysis has been used to study selected isolates belonging to different hospitals. 371,037 admitted patients have been included in the surveillance system. CRKP has shown an overall incidence rate of 41.0 per 100,000 days of stay (95% confidence interval, CI 38.5–43.5/100,000 DOS), a CRKP incidence rate of isolation in blood of 2.46/100,000 days of stay (95% CI 1.89–3.17/100,000 days of stay (DOS) has been registered; significant variability has been registered in facilities providing different levels of care. The network of CRKP patients’ exchange was correlated to that of the healthcare organization, with some inequalities and the identification of bridges in CRKP transfers. More than 73% of isolates were closely related. Patients’ exchange was an important route of spread of antimicrobial resistance, highlighting the pivotal role played by the hub, and selected institution to be used in prioritizing infection control efforts.
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4
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Sewell DK. Analysis of network interventions with an application to hospital-acquired infections. Stat Med 2019; 38:5376-5390. [PMID: 31631371 DOI: 10.1002/sim.8373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 08/20/2019] [Accepted: 08/24/2019] [Indexed: 11/06/2022]
Abstract
Regional interventions to prevent the spread of hospital-acquired infections, vaccination campaigns, and information dissemination strategies are examples of treatment interventions applied to members of a network with the intent of effecting a network-wide change. In designing clinical trials or determining policy changes, it may not be cost effective or otherwise possible to treat all actors of a network. There is a notable lack of study designs and statistical frameworks with which to plan a network-wide intervention in this context and analyze the resulting data. This paper builds off of the network autocorrelation model in order to provide such a framework for a pre-post study design. We derive key quantitative measures of the network-wide treatment effect, exact formulas for power analyses of these measures, and extensions for the context in which the network is unknown. As the treatment assignation is part of the network-wide treatment, we provide methods for determining the assignation which optimizes the overall treatment effect over all members of the network subject to any arbitrary set of implementation costs and cost constraint. We implement these methods on Clostridioides difficile data for the state of California, where the hospitals are linked through patient sharing.
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Affiliation(s)
- Daniel K Sewell
- Department of Biostatistics, University of Iowa, Iowa City, Iowa
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5
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Tosas Auguet O, Stabler RA, Betley J, Preston MD, Dhaliwal M, Gaunt M, Ioannou A, Desai N, Karadag T, Batra R, Otter JA, Marbach H, Clark TG, Edgeworth JD. Frequent Undetected Ward-Based Methicillin-Resistant Staphylococcus aureus Transmission Linked to Patient Sharing Between Hospitals. Clin Infect Dis 2019; 66:840-848. [PMID: 29095965 PMCID: PMC5850096 DOI: 10.1093/cid/cix901] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 11/16/2017] [Indexed: 12/04/2022] Open
Abstract
Background Recent evidence suggests that hospital transmission of methicillin-resistant Staphylococcus aureus (MRSA) is uncommon in UK centers that have implemented sustained infection control programs. We investigated whether a healthcare-network analysis could shed light on transmission paths currently sustaining MRSA levels in UK hospitals. Methods A cross-sectional observational study was performed in 2 National Health Service hospital groups and a general district hospital in Southeast London. All MRSA patients identified at inpatient, outpatient, and community settings between 1 November 2011 and 29 February 2012 were included. We identified genetically defined MRSA transmission clusters in individual hospitals and across the healthcare network, and examined genetic differentiation of sequence type (ST) 22 MRSA isolates within and between hospitals and inpatient or outpatient and community settings, as informed by average and median pairwise single-nucleotide polymorphisms (SNPs) and SNP-based proportions of nearly identical isolates. Results Two hundred forty-eight of 610 (40.7%) MRSA patients were linked in 90 transmission clusters, of which 27 spanned multiple hospitals. Analysis of a large 32 patient ST22-MRSA cluster showed that 26 of 32 patients (81.3%) had multiple contacts with one another during ward stays at any hospital. No residential, outpatient, or significant community healthcare contacts were identified. Genetic differentiation between ST22 MRSA inpatient isolates from different hospitals was less than between inpatient isolates from the same hospitals (P ≤ .01). Conclusions There is evidence of frequent ward-based transmission of MRSA brought about by frequent patient admissions to multiple hospitals. Limiting in-ward transmission requires sharing of MRSA status data between hospitals.
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Affiliation(s)
- Olga Tosas Auguet
- Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, King's College London and Guy's and St Thomas' NHS Foundation Trust.,Oxford Health Systems Collaboration, Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford
| | - Richard A Stabler
- Department of Pathogen Molecular Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine
| | - Jason Betley
- Illumina, Cambridge Ltd, Chesterford Research Park, Little Chesterford, Essex
| | - Mark D Preston
- Department of Pathogen Molecular Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine
| | - Mandeep Dhaliwal
- Department of Pathogen Molecular Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine
| | - Michael Gaunt
- Department of Pathogen Molecular Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine
| | - Avgousta Ioannou
- Illumina, Cambridge Ltd, Chesterford Research Park, Little Chesterford, Essex
| | - Nergish Desai
- Department of Medical Microbiology, King's College Hospital NHS Foundation Trust
| | - Tacim Karadag
- Department of Microbiology, University Hospital Lewisham, Lewisham and Greenwich NHS Trust
| | - Rahul Batra
- Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, King's College London and Guy's and St Thomas' NHS Foundation Trust
| | - Jonathan A Otter
- Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, King's College London and Guy's and St Thomas' NHS Foundation Trust.,National Institute for Health Research Health Protection Research Unit in Healthcare-Associated Infections and Antimicrobial Resistance at Imperial College London, and Imperial College Healthcare NHS Trust, Infection Prevention and Control
| | - Helene Marbach
- Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, King's College London and Guy's and St Thomas' NHS Foundation Trust
| | - Taane G Clark
- Department of Pathogen Molecular Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine.,Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Jonathan D Edgeworth
- Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, King's College London and Guy's and St Thomas' NHS Foundation Trust
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6
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Snitkin ES, Won S, Pirani A, Lapp Z, Weinstein RA, Lolans K, Hayden MK. Integrated genomic and interfacility patient-transfer data reveal the transmission pathways of multidrug-resistant Klebsiella pneumoniae in a regional outbreak. Sci Transl Med 2018; 9:9/417/eaan0093. [PMID: 29167391 DOI: 10.1126/scitranslmed.aan0093] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Revised: 06/16/2017] [Accepted: 08/18/2017] [Indexed: 12/15/2022]
Abstract
Development of effective strategies to limit the proliferation of multidrug-resistant organisms requires a thorough understanding of how such organisms spread among health care facilities. We sought to uncover the chains of transmission underlying a 2008 U.S. regional outbreak of carbapenem-resistant Klebsiella pneumoniae by performing an integrated analysis of genomic and interfacility patient-transfer data. Genomic analysis yielded a high-resolution transmission network that assigned directionality to regional transmission events and discriminated between intra- and interfacility transmission when epidemiologic data were ambiguous or misleading. Examining the genomic transmission network in the context of interfacility patient transfers (patient-sharing networks) supported the role of patient transfers in driving the outbreak, with genomic analysis revealing that a small subset of patient-transfer events was sufficient to explain regional spread. Further integration of the genomic and patient-sharing networks identified one nursing home as an important bridge facility early in the outbreak-a role that was not apparent from analysis of genomic or patient-transfer data alone. Last, we found that when simulating a real-time regional outbreak, our methodology was able to accurately infer the facility at which patients acquired their infections. This approach has the potential to identify facilities with high rates of intra- or interfacility transmission, data that will be useful for triggering targeted interventions to prevent further spread of multidrug-resistant organisms.
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Affiliation(s)
- Evan S Snitkin
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI 48109, USA. .,Division of Infectious Diseases, Department of Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sarah Won
- Division of Infectious Diseases, Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA
| | - Ali Pirani
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI 48109, USA.,Division of Infectious Diseases, Department of Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Zena Lapp
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Robert A Weinstein
- Division of Infectious Diseases, Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA.,Division of Infectious Diseases, Department of Medicine, Cook County Health and Hospitals System, Chicago, IL 60612, USA
| | - Karen Lolans
- Division of Clinical Microbiology, Department of Pathology, Rush University Medical Center, Chicago, IL 60612, USA
| | - Mary K Hayden
- Division of Infectious Diseases, Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA. .,Division of Clinical Microbiology, Department of Pathology, Rush University Medical Center, Chicago, IL 60612, USA
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7
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O'Reilly-Shah VN, Easton GS, Jabaley CS, Lynde GC. Variable effectiveness of stepwise implementation of nudge-type interventions to improve provider compliance with intraoperative low tidal volume ventilation. BMJ Qual Saf 2018; 27:1008-1018. [PMID: 29776982 DOI: 10.1136/bmjqs-2017-007684] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 03/13/2018] [Accepted: 04/28/2018] [Indexed: 02/04/2023]
Abstract
BACKGROUND Identifying mechanisms to improve provider compliance with quality metrics is a common goal across medical disciplines. Nudge interventions are minimally invasive strategies that can influence behavioural changes and are increasingly used within healthcare settings. We hypothesised that nudge interventions may improve provider compliance with lung-protective ventilation (LPV) strategies during general anaesthesia. METHODS We developed an audit and feedback dashboard that included information on both provider-level and department-level compliance with LPV strategies in two academic hospitals, two non-academic hospitals and two academic surgery centres affiliated with a single healthcare system. Dashboards were emailed to providers four times over the course of the 9-month study. Additionally, the default setting on anaesthesia machines for tidal volume was decreased from 700 mL to 400 mL. Data on surgical cases performed between 1 September 2016 and 31 May 2017 were examined for compliance with LPV. The impact of the interventions was assessed via pairwise logistic regression analysis corrected for multiple comparisons. RESULTS A total of 14 793 anaesthesia records were analysed. Absolute compliance rates increased from 59.3% to 87.8%preintervention to postintervention. Introduction of attending physician dashboards resulted in a 41% increase in the odds of compliance (OR 1.41, 95% CI 1.17 to 1.69, p=0.002). Subsequently, the addition of advanced practice provider and resident dashboards lead to an additional 93% increase in the odds of compliance (OR 1.93, 95% CI 1.52 to 2.46, p<0.001). Lastly, modifying ventilator defaults led to a 376% increase in the odds of compliance (OR 3.76, 95% CI 3.1 to 4.57, p<0.001). CONCLUSION Audit and feedback tools in conjunction with default changes improve provider compliance.
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Affiliation(s)
| | - George S Easton
- Department of Information Systems and Operations Management, Emory University, Goizueta Business School, Atlanta, Georgia, USA
| | - Craig S Jabaley
- Department of Anesthesiology, Emory University, Atlanta, Georgia, USA
| | - Grant C Lynde
- Department of Anesthesiology, Emory University, Atlanta, Georgia, USA
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8
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Brunson JC, Laubenbacher RC. Applications of network analysis to routinely collected health care data: a systematic review. J Am Med Inform Assoc 2018; 25:210-221. [PMID: 29025116 PMCID: PMC6664849 DOI: 10.1093/jamia/ocx052] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2017] [Revised: 04/18/2017] [Accepted: 04/23/2017] [Indexed: 01/21/2023] Open
Abstract
Objective To survey network analyses of datasets collected in the course of routine operations in health care settings and identify driving questions, methods, needs, and potential for future research. Materials and Methods A search strategy was designed to find studies that applied network analysis to routinely collected health care datasets and was adapted to 3 bibliographic databases. The results were grouped according to a thematic analysis of their settings, objectives, data, and methods. Each group received a methodological synthesis. Results The search found 189 distinct studies reported before August 2016. We manually partitioned the sample into 4 groups, which investigated institutional exchange, physician collaboration, clinical co-occurrence, and workplace interaction networks. Several robust and ongoing research programs were discerned within (and sometimes across) the groups. Little interaction was observed between these programs, despite conceptual and methodological similarities. Discussion We use the literature sample to inform a discussion of good practice at this methodological interface, including the concordance of motivations, study design, data, and tools and the validation and standardization of techniques. We then highlight instances of positive feedback between methodological development and knowledge domains and assess the overall cohesion of the sample.
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9
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Donker T, Reuter S, Scriberras J, Reynolds R, Brown NM, Török ME, James R, Network EOEMR, Aanensen DM, Bentley SD, Holden MTG, Parkhill J, Spratt BG, Peacock SJ, Feil EJ, Grundmann H. Population genetic structuring of methicillin-resistant Staphylococcus aureus clone EMRSA-15 within UK reflects patient referral patterns. Microb Genom 2017; 3:e000113. [PMID: 29026654 PMCID: PMC5605955 DOI: 10.1099/mgen.0.000113] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Accepted: 04/07/2017] [Indexed: 12/21/2022] Open
Abstract
Antibiotic resistance forms a serious threat to the health of hospitalised patients, rendering otherwise treatable bacterial infections potentially life-threatening. A thorough understanding of the mechanisms by which resistance spreads between patients in different hospitals is required in order to design effective control strategies. We measured the differences between bacterial populations of 52 hospitals in the United Kingdom and Ireland, using whole-genome sequences from 1085 MRSA clonal complex 22 isolates collected between 1998 and 2012. The genetic differences between bacterial populations were compared with the number of patients transferred between hospitals and their regional structure. The MRSA populations within single hospitals, regions and countries were genetically distinct from the rest of the bacterial population at each of these levels. Hospitals from the same patient referral regions showed more similar MRSA populations, as did hospitals sharing many patients. Furthermore, the bacterial populations from different time-periods within the same hospital were generally more similar to each other than contemporaneous bacterial populations from different hospitals. We conclude that, while a large part of the dispersal and expansion of MRSA takes place among patients seeking care in single hospitals, inter-hospital spread of resistant bacteria is by no means a rare occurrence. Hospitals are exposed to constant introductions of MRSA on a number of levels: (1) most MRSA is received from hospitals that directly transfer large numbers of patients, while (2) fewer introductions happen between regions or (3) across national borders, reflecting lower numbers of transferred patients. A joint coordinated control effort between hospitals, is therefore paramount for the national control of MRSA, antibiotic-resistant bacteria and other hospital-associated pathogens.
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Affiliation(s)
- Tjibbe Donker
- Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK
- Department of Medical Microbiology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Sandra Reuter
- Department of Medicine, University of Cambridge, Cambridge, UK
- Pathogen Genomics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - James Scriberras
- The Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath, UK
| | - Rosy Reynolds
- British Society for Antimicrobial Chemotherapy, UK
- North Bristol NHS Trust, Bristol, UK
| | - Nicholas M. Brown
- British Society for Antimicrobial Chemotherapy, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Public Health England, UK
| | - M. Estée Török
- Department of Medicine, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Public Health England, UK
| | - Richard James
- Department of Physics and Centre for Networks and Collective Behaviour, University of Bath, Bath, UK
| | | | - David M. Aanensen
- Faculty of Medicine, School of Public Health, Imperial College, London, UK
| | | | - Matthew T. G. Holden
- Pathogen Genomics, Wellcome Trust Sanger Institute, Hinxton, UK
- School of Medicine, University of St Andrews, St Andrews, UK
| | - Julian Parkhill
- Pathogen Genomics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - Brian G. Spratt
- Faculty of Medicine, School of Public Health, Imperial College, London, UK
| | - Sharon J. Peacock
- Department of Medicine, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Public Health England, UK
| | - Edward J. Feil
- The Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath, UK
| | - Hajo Grundmann
- Department of Medical Microbiology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
- Department of Infection Prevention and Hospital Hygiene, University Medical Centre Freiburg, Medical Faculty, University of Freiburg, Freiburg, Germany
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10
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Donker T, Henderson KL, Hopkins KL, Dodgson AR, Thomas S, Crook DW, Peto TEA, Johnson AP, Woodford N, Walker AS, Robotham JV. The relative importance of large problems far away versus small problems closer to home: insights into limiting the spread of antimicrobial resistance in England. BMC Med 2017; 15:86. [PMID: 28446169 PMCID: PMC5406888 DOI: 10.1186/s12916-017-0844-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Accepted: 03/24/2017] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND To combat the spread of antimicrobial resistance (AMR), hospitals are advised to screen high-risk patients for carriage of antibiotic-resistant bacteria on admission. This often includes patients previously admitted to hospitals with a high AMR prevalence. However, the ability of such a strategy to identify introductions (and hence prevent onward transmission) is unclear, as it depends on AMR prevalence in each hospital, the number of patients moving between hospitals, and the number of hospitals considered 'high risk'. METHODS We tracked patient movements using data from the National Health Service of England Hospital Episode Statistics and estimated differences in regional AMR prevalences using, as an exemplar, data collected through the national reference laboratory service of Public Health England on carbapenemase-producing Enterobacteriaceae (CPE) from 2008 to 2014. Combining these datasets, we calculated expected CPE introductions into hospitals from across the hospital network to assess the effectiveness of admission screening based on defining high-prevalence hospitals as high risk. RESULTS Based on numbers of exchanged patients, the English hospital network can be divided into 14 referral regions. England saw a sharp increase in numbers of CPE isolates referred to the national reference laboratory over 7 years, from 26 isolates in 2008 to 1649 in 2014. Large regional differences in numbers of confirmed CPE isolates overlapped with regional structuring of patient movements between hospitals. However, despite these large differences in prevalence between regions, we estimated that hospitals received only a small proportion (1.8%) of CPE-colonised patients from hospitals outside their own region, which decreased over time. CONCLUSIONS In contrast to the focus on import screening based on assigning a few hospitals as 'high risk', patient transfers between hospitals with small AMR problems in the same region often pose a larger absolute threat than patient transfers from hospitals in other regions with large problems, even if the prevalence in other regions is orders of magnitude higher. Because the difference in numbers of exchanged patients, between and within regions, was mostly larger than the difference in CPE prevalence, it would be more effective for hospitals to focus on their own populations or region to inform control efforts rather than focussing on problems elsewhere.
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Affiliation(s)
- Tjibbe Donker
- The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK. .,Nuffield Department of Medicine, University of Oxford, Oxford, UK. .,National Infection Service, Public Health England, Colindale, London, UK.
| | | | - Katie L Hopkins
- The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK.,National Infection Service, Public Health England, Colindale, London, UK
| | - Andrew R Dodgson
- Public Health Laboratory, Public Health England, Manchester Royal Infirmary, Manchester, UK.,Department of Microbiology, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Stephanie Thomas
- Microbiology Department, University Hospital South Manchester, Manchester, UK
| | - Derrick W Crook
- The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK.,Nuffield Department of Medicine, University of Oxford, Oxford, UK.,National Infection Service, Public Health England, Colindale, London, UK.,NIHR Biomedical Research Centre, Oxford, UK
| | - Tim E A Peto
- The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK.,Nuffield Department of Medicine, University of Oxford, Oxford, UK.,NIHR Biomedical Research Centre, Oxford, UK
| | - Alan P Johnson
- The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK.,National Infection Service, Public Health England, Colindale, London, UK
| | - Neil Woodford
- The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK.,National Infection Service, Public Health England, Colindale, London, UK
| | - A Sarah Walker
- The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK.,Nuffield Department of Medicine, University of Oxford, Oxford, UK.,NIHR Biomedical Research Centre, Oxford, UK
| | - Julie V Robotham
- The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK.,National Infection Service, Public Health England, Colindale, London, UK
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11
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The Role of Nursing Homes in the Spread of Antimicrobial Resistance Over the Healthcare Network. Infect Control Hosp Epidemiol 2016; 37:761-7. [PMID: 27052880 PMCID: PMC4926272 DOI: 10.1017/ice.2016.59] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
OBJECTIVE Recerntly, the role of the healthcare network, defined as a set of hospitals linked by
patient transfers, has been increasingly considered in the control of antimicrobial
resistance. Here, we investigate the potential impact of nursing homes on the spread of
antimicrobial-resistant pathogens across the healthcare network and its importance for
control strategies. METHODS Based on patient transfer data, we designed a network model representing the Dutch
healthcare system of hospitals and nursing homes. We simulated the spread of an
antimicrobial-resistant pathogen across the healthcare network, and we modeled
transmission within institutions using a stochastic susceptible–infected–susceptible
(SIS) epidemic model. Transmission between institutions followed transfers. We
identified the contribution of nursing homes to the dispersal of the pathogen by
comparing simulations of the network with and without nursing homes. RESULTS Our results strongly suggest that nursing homes in the Netherlands have the potential
to drive and sustain epidemics across the healthcare network. Even when the daily
probability of transmission in nursing homes is much lower than in hospitals,
transmission of resistance can be more effective because of the much longer length of
stay of patients in nursing homes. CONCLUSIONS If an antimicrobial-resistant pathogen emerges that spreads easily within nursing
homes, control efforts aimed at hospitals may no longer be effective in preventing
nationwide outbreaks. It is important to consider nursing homes in planning regional and
national infection control and in implementing surveillance systems that monitor the
spread of antimicrobial resistance. Infect Control Hosp Epidemiol 2016;37:761–767
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12
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Chang HH, Dordel J, Donker T, Worby CJ, Feil EJ, Hanage WP, Bentley SD, Huang SS, Lipsitch M. Identifying the effect of patient sharing on between-hospital genetic differentiation of methicillin-resistant Staphylococcus aureus. Genome Med 2016; 8:18. [PMID: 26873713 PMCID: PMC4752745 DOI: 10.1186/s13073-016-0274-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Accepted: 01/29/2016] [Indexed: 01/17/2023] Open
Abstract
Background Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most common healthcare-associated pathogens. To examine the role of inter-hospital patient sharing on MRSA transmission, a previous study collected 2,214 samples from 30 hospitals in Orange County, California and showed by spa typing that genetic differentiation decreased significantly with increased patient sharing. In the current study, we focused on the 986 samples with spa type t008 from the same population. Methods We used genome sequencing to determine the effect of patient sharing on genetic differentiation between hospitals. Genetic differentiation was measured by between-hospital genetic diversity, FST, and the proportion of nearly identical isolates between hospitals. Results Surprisingly, we found very similar genetic diversity within and between hospitals, and no significant association between patient sharing and genetic differentiation measured by FST. However, in contrast to FST, there was a significant association between patient sharing and the proportion of nearly identical isolates between hospitals. We propose that the proportion of nearly identical isolates is more powerful at determining transmission dynamics than traditional estimators of genetic differentiation (FST) when gene flow between populations is high, since it is more responsive to recent transmission events. Our hypothesis was supported by the results from coalescent simulations. Conclusions Our results suggested that there was a high level of gene flow between hospitals facilitated by patient sharing, and that the proportion of nearly identical isolates is more sensitive to population structure than FST when gene flow is high. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0274-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Hsiao-Han Chang
- Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Janina Dordel
- Pathogen Genomics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, UK. .,Department of Biology, Drexel University, Philadelphia, PA, USA.
| | - Tjibbe Donker
- Nuffield Department of Medicine, University of Oxford, Oxford, UK.
| | - Colin J Worby
- Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Edward J Feil
- Department of Biology and Biochemistry, University of Bath, Bath, BA2 7AY, UK.
| | - William P Hanage
- Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Stephen D Bentley
- Pathogen Genomics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, UK.
| | - Susan S Huang
- Division of Infectious Diseases and Health Policy Research Institute, University of California Irvine School of Medicine, Irvine, CA, USA.
| | - Marc Lipsitch
- Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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13
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Li H, Xin H, Li SFY. Multiplex PMA-qPCR Assay with Internal Amplification Control for Simultaneous Detection of Viable Legionella pneumophila, Salmonella typhimurium, and Staphylococcus aureus in Environmental Waters. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2015; 49:14249-56. [PMID: 26512952 DOI: 10.1021/acs.est.5b03583] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Pathogenic microorganisms are responsible for many infectious diseases, and pathogen monitoring is important and necessary for water quality control. This study for the first time explored a multiplex quantitative real-time PCR (qPCR) technique combined with propidium monoazide (PMA) to simultaneously detect viable Legionella pneumophila, Salmonella typhimurium, and Staphylococcus aureus in one reaction from water samples. Sodium lauroyl sarcosinate (sarkosyl) was applied to enhance the dead bacterial permeability of PMA. The sensitivity of the multiplex PMA-qPCR assay achieved two colony-forming units (CFU) per reaction for L. pneumophila and three CFU per reaction for S. typhimurium and S. aureus. No PCR products were amplified from all nontarget control samples. Significantly, with comparable specificity and sensitivity, this newly invented multiplex PMA-qPCR assay took a much shorter time than did conventional culture assays when testing water samples with spiked bacteria and simulated environmental water treatment. The viable multiplex PMA-qPCR assay was further successfully applied to pathogen detection from rivers, canals, and tap water samples after simple water pretreatment.
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Affiliation(s)
- Haiyan Li
- Department of Chemistry, Faculty of Science, National University of Singapore , 3 Science Drive 3, Singapore 117543
| | - Hongyi Xin
- Bioinformatics Institute, Agency for Science, Technology and Research , 30 Biopolis Street, Singapore 138671
| | - Sam Fong Yau Li
- Department of Chemistry, Faculty of Science, National University of Singapore , 3 Science Drive 3, Singapore 117543
- NUS Environmental Research Institute, National University of Singapore , 5A Engineering Drive 1, Singapore 117411
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14
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Macal CM, North MJ, Collier N, Dukic VM, Wegener DT, David MZ, Daum RS, Schumm P, Evans JA, Wilder JR, Miller LG, Eells SJ, Lauderdale DS. Modeling the transmission of community-associated methicillin-resistant Staphylococcus aureus: a dynamic agent-based simulation. J Transl Med 2014; 12:124. [PMID: 24886400 PMCID: PMC4049803 DOI: 10.1186/1479-5876-12-124] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2013] [Accepted: 04/08/2014] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Methicillin-resistant Staphylococcus aureus (MRSA) has been a deadly pathogen in healthcare settings since the 1960s, but MRSA epidemiology changed since 1990 with new genetically distinct strain types circulating among previously healthy people outside healthcare settings. Community-associated (CA) MRSA strains primarily cause skin and soft tissue infections, but may also cause life-threatening invasive infections. First seen in Australia and the U.S., it is a growing problem around the world. The U.S. has had the most widespread CA-MRSA epidemic, with strain type USA300 causing the great majority of infections. Individuals with either asymptomatic colonization or infection may transmit CA-MRSA to others, largely by skin-to-skin contact. Control measures have focused on hospital transmission. Limited public health education has focused on care for skin infections. METHODS We developed a fine-grained agent-based model for Chicago to identify where to target interventions to reduce CA-MRSA transmission. An agent-based model allows us to represent heterogeneity in population behavior, locations and contact patterns that are highly relevant for CA-MRSA transmission and control. Drawing on nationally representative survey data, the model represents variation in sociodemographics, locations, behaviors, and physical contact patterns. Transmission probabilities are based on a comprehensive literature review. RESULTS Over multiple 10-year runs with one-hour ticks, our model generates temporal and geographic trends in CA-MRSA incidence similar to Chicago from 2001 to 2010. On average, a majority of transmission events occurred in households, and colonized rather than infected agents were the source of the great majority (over 95%) of transmission events. The key findings are that infected people are not the primary source of spread. Rather, the far greater number of colonized individuals must be targeted to reduce transmission. CONCLUSIONS Our findings suggest that current paradigms in MRSA control in the United States cannot be very effective in reducing the incidence of CA-MRSA infections. Furthermore, the control measures that have focused on hospitals are unlikely to have much population-wide impact on CA-MRSA rates. New strategies need to be developed, as the incidence of CA-MRSA is likely to continue to grow around the world.
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Affiliation(s)
- Charles M Macal
- Decision and Information Sciences Division, Argonne National Laboratory, 9700 S. Cass Ave., Bldg 221, Argonne, IL 60439, USA
- Computation Institute, University of Chicago, Chicago, IL 60637, USA
| | - Michael J North
- Decision and Information Sciences Division, Argonne National Laboratory, 9700 S. Cass Ave., Bldg 221, Argonne, IL 60439, USA
- Computation Institute, University of Chicago, Chicago, IL 60637, USA
| | - Nicholson Collier
- Decision and Information Sciences Division, Argonne National Laboratory, 9700 S. Cass Ave., Bldg 221, Argonne, IL 60439, USA
| | - Vanja M Dukic
- Applied Mathematics, University of Colorado Boulder, Boulder, CO 80309, USA
| | | | - Michael Z David
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
- Health Studies, University of Chicago, Chicago, IL 60637, USA
| | - Robert S Daum
- Pediatrics, University of Chicago, Chicago, IL 60637, USA
| | - Philip Schumm
- Health Studies, University of Chicago, Chicago, IL 60637, USA
| | - James A Evans
- Sociology, University of Chicago, Chicago, IL 60637, USA
| | | | - Loren G Miller
- Harbor-UCLA Medical Center, Division of Infectious Diseases, Torrance, CA 90509, USA
| | - Samantha J Eells
- Harbor-UCLA Medical Center, Division of Infectious Diseases, Torrance, CA 90509, USA
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15
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Duan F, Li X, Cai S, Xin G, Wang Y, Du D, He S, Huang B, Guo X, Zhao H, Zhang R, Ma L, Liu Y, Du Q, Wei Z, Xing Z, Liang Y, Wu X, Fan C, Ji C, Zeng D, Chen Q, He Y, Liu X, Huang W. Haloemodin as Novel Antibacterial Agent Inhibiting DNA Gyrase and Bacterial Topoisomerase I. J Med Chem 2014; 57:3707-14. [PMID: 24588790 DOI: 10.1021/jm401685f] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Feixia Duan
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
- College
of Light Industry, Textile and Food Engineering, Sichuan University, Chengdu, Sichuan 610065, China
| | - Xiaohong Li
- Department
of Biopharmaceutics, Key Laboratory of Drug Targeting and Drug Delivery
Systems, Ministry of Education, West China School of Pharmacy, Sichuan University, No. 17, Section 3 Southern Renmin Road, Chengdu 610041, China
| | - Suping Cai
- Shenzhen
Eye Hospital, Jinan University, No. 18, Zetian Road, Futian District, Shenzhen 518040, China
| | - Guang Xin
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Yanyan Wang
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Dan Du
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Shiliang He
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Baozhan Huang
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Xiurong Guo
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Hang Zhao
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
- State
Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University Chengdu, Sichuan 610041, China
| | - Rui Zhang
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Limei Ma
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Yan Liu
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Qigen Du
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Zeliang Wei
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Zhihua Xing
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Yong Liang
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Xiaohua Wu
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Chengzhong Fan
- Department
of Nuclear Medicine, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, Sichuan 610041, China
| | - Chengjie Ji
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Dequan Zeng
- State
Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University Chengdu, Sichuan 610041, China
| | - Qianming Chen
- State
Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University Chengdu, Sichuan 610041, China
| | - Yang He
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
| | - Xuyang Liu
- Shenzhen
Eye Hospital, Jinan University, No. 18, Zetian Road, Futian District, Shenzhen 518040, China
| | - Wen Huang
- Laboratory
of Ethnopharmacology, Institute for Nanobiomedical Technology and
Membrane Biology, Regenerative Medicine Research Center, West China
Hospital, West China Medical School, Sichuan University Keyuan 4 Road
No. 1, Gaopeng Avenue, Gaoxinqu, Chengdu, Sichuan 610041 China
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16
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Mocan L, Ilie I, Matea C, Tabaran F, Kalman E, Iancu C, Mocan T. Surface plasmon resonance-induced photoactivation of gold nanoparticles as bactericidal agents against methicillin-resistant Staphylococcus aureus. Int J Nanomedicine 2014; 9:1453-61. [PMID: 24711697 PMCID: PMC3968082 DOI: 10.2147/ijn.s54950] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Systemic infections caused by methicillin-resistant Staphylococcus aureus (MRSA) and other bacteria are responsible for millions of deaths worldwide, and much of this mortality is due to the rise of antibiotic-resistant organisms as a result of natural selection. Gold nanoparticles synthesized using the standard wet chemical procedure were photoexcited using an 808 nm 2 W laser diode and further administered to MRSA bacteria. Flow cytometry, transmission electron microscopy, contrast phase microscopy, and fluorescence microscopy combined with immunochemical staining were used to examine the interaction of the photoexcited gold nano-particles with MRSA bacteria. We show here that phonon–phonon interactions following laser photoexcitation of gold nanoparticles exhibit increased MRSA necrotic rates at low concentrations and short incubation times compared with MRSA treated with gold nanoparticles alone. These unique data may represent a step forward in the study of bactericidal effects of various nanomaterials, with applications in biology and medicine.
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Affiliation(s)
- Lucian Mocan
- 3rd Surgery Clinic, Department of Nanomedicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Ioana Ilie
- Department of Endocrinology, Department of Nanomedicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Cristian Matea
- 3rd Surgery Clinic, Department of Nanomedicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Flaviu Tabaran
- 3rd Surgery Clinic, Department of Nanomedicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Ersjebet Kalman
- 3rd Surgery Clinic, Department of Nanomedicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Cornel Iancu
- 3rd Surgery Clinic, Department of Nanomedicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Teodora Mocan
- Department of Physiology, Department of Nanomedicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania
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17
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Ciccolini M, Donker T, Grundmann H, Bonten MJM, Woolhouse MEJ. Efficient surveillance for healthcare-associated infections spreading between hospitals. Proc Natl Acad Sci U S A 2014; 111:2271-6. [PMID: 24469791 PMCID: PMC3926017 DOI: 10.1073/pnas.1308062111] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Early detection of new or novel variants of nosocomial pathogens is a public health priority. We show that, for healthcare-associated infections that spread between hospitals as a result of patient movements, it is possible to design an effective surveillance system based on a relatively small number of sentinel hospitals. We apply recently developed mathematical models to patient admission data from the national healthcare systems of England and The Netherlands. Relatively short detection times are achieved once 10-20% hospitals are recruited as sentinels and only modest reductions are seen as more hospitals are recruited thereafter. Using a heuristic optimization approach to sentinel selection, the same expected time to detection can be achieved by recruiting approximately half as many hospitals. Our study provides a robust evidence base to underpin the design of an efficient sentinel hospital surveillance system for novel nosocomial pathogens, delivering early detection times for reduced expenditure and effort.
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Affiliation(s)
- Mariano Ciccolini
- Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh EH9 3JT, United Kingdom
- Department of Medical Microbiology, University Medical Center Groningen, University of Groningen, Groningen, 9713 GZ, The Netherlands
| | - Tjibbe Donker
- Department of Medical Microbiology, University Medical Center Groningen, University of Groningen, Groningen, 9713 GZ, The Netherlands
- Center for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, 3721 MA, The Netherlands, and
| | - Hajo Grundmann
- Department of Medical Microbiology, University Medical Center Groningen, University of Groningen, Groningen, 9713 GZ, The Netherlands
- Center for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, 3721 MA, The Netherlands, and
| | - Marc J. M. Bonten
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, 3584 CX, The Netherlands
| | - Mark E. J. Woolhouse
- Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh EH9 3JT, United Kingdom
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18
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Donker T, Wallinga J, Grundmann H. Dispersal of antibiotic-resistant high-risk clones by hospital networks: changing the patient direction can make all the difference. J Hosp Infect 2013; 86:34-41. [PMID: 24075292 DOI: 10.1016/j.jhin.2013.06.021] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Accepted: 06/24/2013] [Indexed: 11/16/2022]
Abstract
BACKGROUND Patients who seek treatment in hospitals can introduce high-risk clones of hospital-acquired, antibiotic-resistant pathogens from previous admissions. In this manner, different healthcare institutions become linked epidemiologically. All links combined form the national patient referral network, through which high-risk clones can propagate. AIM To assess the influence of changes in referral patterns and network structure on the dispersal of these pathogens. METHODS Hospital admission data were mapped to reconstruct the English patient referral network, and 12 geographically distinct healthcare collectives were identified. The number of patients admitted and referred to hospitals outside their collective was measured. Simulation models were used to assess the influence of changing network structure on the spread of hospital-acquired pathogens. FINDINGS Simulation models showed that decreasing the number of between-collective referrals by redirecting, on average, just 1.5 patients/hospital/day had a strong effect on dispersal. By decreasing the number of between-collective referrals, the spread of high-risk clones through the network can be reduced by 36%. Conversely, by creating supra-regional specialist centres that provide specialist care at national level, the rate of dispersal can increase by 48%. CONCLUSION The structure of the patient referral network has a profound effect on the epidemic behaviour of high-risk clones. Any changes that affect the number of referrals between healthcare collectives, inevitably affect the national dispersal of these pathogens. These effects should be taken into account when creating national specialist centres, which may jeopardize control efforts.
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Affiliation(s)
- T Donker
- Department of Medical Microbiology, University Medical Centre Groningen, University of Groningen, The Netherlands; Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
| | - J Wallinga
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - H Grundmann
- Department of Medical Microbiology, University Medical Centre Groningen, University of Groningen, The Netherlands; Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
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19
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Ciccolini M, Donker T, Köck R, Mielke M, Hendrix R, Jurke A, Rahamat-Langendoen J, Becker K, Niesters HGM, Grundmann H, Friedrich AW. Infection prevention in a connected world: the case for a regional approach. Int J Med Microbiol 2013; 303:380-7. [PMID: 23499307 DOI: 10.1016/j.ijmm.2013.02.003] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Results from microbiological and epidemiological investigations, as well as mathematical modelling, show that the transmission dynamics of nosocomial pathogens, especially of multiple antibiotic-resistant bacteria, is not exclusively amenable to single-hospital infection prevention measures. Crucially, their extent of spread depends on the structure of an underlying "healthcare network", as determined by inter-institutional referrals of patients. The current trend towards centralized healthcare systems favours the spread of hospital-associated pathogens, and must be addressed by coordinated regional or national approaches to infection prevention in order to maintain patient safety. Here we review recent advances that support this hypothesis, and propose a "next-generation" network-approach to hospital infection prevention and control.
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Affiliation(s)
- Mariano Ciccolini
- Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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20
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Lu X, Samuelson DR, Xu Y, Zhang H, Wang S, Rasco BA, Xu J, Konkel ME. Detecting and tracking nosocomial methicillin-resistant Staphylococcus aureus using a microfluidic SERS biosensor. Anal Chem 2013; 85:2320-7. [PMID: 23327644 DOI: 10.1021/ac303279u] [Citation(s) in RCA: 81] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Rapid detection and differentiation of methicillin-resistant Staphylococcus aureus (MRSA) are critical for the early diagnosis of difficult-to-treat nosocomial and community acquired clinical infections and improved epidemiological surveillance. We developed a microfluidics chip coupled with surface enhanced Raman scattering (SERS) spectroscopy (532 nm) "lab-on-a-chip" system to rapidly detect and differentiate methicillin-sensitive S. aureus (MSSA) and MRSA using clinical isolates from China and the United States. A total of 21 MSSA isolates and 37 MRSA isolates recovered from infected humans were first analyzed by using polymerase chain reaction (PCR) and multilocus sequence typing (MLST). The mecA gene, which refers resistant to methicillin, was detected in all the MRSA isolates, and different allelic profiles were identified assigning isolates as either previously identified or novel clones. A total of 17 400 SERS spectra of the 58 S. aureus isolates were collected within 3.5 h using this optofluidic platform. Intra- and interlaboratory spectral reproducibility yielded a differentiation index value of 3.43-4.06 and demonstrated the feasibility of using this optofluidic system at different laboratories for bacterial identification. A global SERS-based dendrogram model for MRSA and MSSA identification and differentiation to the strain level was established and cross-validated (Simpson index of diversity of 0.989) and had an average recognition rate of 95% for S. aureus isolates associated with a recent outbreak in China. SERS typing correlated well with MLST indicating that it has high sensitivity and selectivity and would be suitable for determining the origin and possible spread of MRSA. A SERS-based partial least-squares regression model could quantify the actual concentration of a specific MRSA isolate in a bacterial mixture at levels from 5% to 100% (regression coefficient, >0.98; residual prediction deviation, >10.05). This optofluidic platform has advantages over traditional genotyping for ultrafast, automated, and reliable detection and epidemiological surveillance of bacterial infections.
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Affiliation(s)
- Xiaonan Lu
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, Washington 99164-7520, United States
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Laxminarayan R. Crafting a system-wide response to healthcare-associated infections. Proc Natl Acad Sci U S A 2012; 109:6364-5. [PMID: 22509019 PMCID: PMC3340060 DOI: 10.1073/pnas.1203676109] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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