1
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Raabe NJ, Valek AL, Griffith MP, Mills E, Waggle K, Srinivasa VR, Ayres AM, Bradford C, Creager HM, Pless LL, Sundermann AJ, Van Tyne D, Snyder GM, Harrison LH. Real-time genomic epidemiologic investigation of a multispecies plasmid-associated hospital outbreak of NDM-5-producing Enterobacterales infections. Int J Infect Dis 2024; 142:106971. [PMID: 38373647 PMCID: PMC11055495 DOI: 10.1016/j.ijid.2024.02.014] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 02/05/2024] [Accepted: 02/14/2024] [Indexed: 02/21/2024] Open
Abstract
OBJECTIVES New Delhi metallo-β-lactamase (NDM) is an emergent mechanism of carbapenem resistance associated with high mortality and limited treatment options. Because the blaNDM resistance gene is often carried on plasmids, traditional infection prevention and control (IP&C) surveillance methods and reactive whole genome sequencing (WGS) may not detect plasmid transfer in multispecies outbreaks. METHODS Initial outbreak detection of NDM-producing Enterobacterales identified at an acute care hospital occurred via traditional IP&C methods and was supplemented by real-time WGS surveillance performed weekly. To resolve NDM-encoding plasmids, we performed long-read sequencing and constructed hybrid assemblies. WGS data for suspected outbreaks was shared with the IP&C team for assessment and intervention. RESULTS We observed a multispecies outbreak of NDM-5-producing Enterobacterales isolated from 15 patients between February 2021 and February 2023. The 19 clinical and surveillance isolates sequenced included 7 bacterial species encoding the same NDM-5 plasmid. WGS surveillance and epidemiologic investigation characterized 10 horizontal plasmid transfer events and 6 bacterial transmission events between patients in varying hospital units. CONCLUSIONS Our investigation revealed a complex, multispecies outbreak of NDM involving multiple plasmid transfer and bacterial transmission events. We highlight the utility of combining traditional IP&C and prospective genomic methods in identifying and containing plasmid-associated outbreaks.
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Affiliation(s)
- Nathan J Raabe
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA; Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Abby L Valek
- Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, Pittsburgh, PA, USA
| | - Marissa P Griffith
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA; Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Emma Mills
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kady Waggle
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA; Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Vatsala Rangachar Srinivasa
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA; Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashley M Ayres
- Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, Pittsburgh, PA, USA
| | - Claire Bradford
- Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, Pittsburgh, PA, USA
| | - Hannah M Creager
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Lora L Pless
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA; Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Alexander J Sundermann
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA; Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Daria Van Tyne
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Graham M Snyder
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, Pittsburgh, PA, USA
| | - Lee H Harrison
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA; Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
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Sundermann AJ, Rangachar Srinivasa V, Mills EG, Griffith MP, Waggle KD, Ayres AM, Pless L, Snyder GM, Harrison LH, Van Tyne D. Two Artificial Tears Outbreak-Associated Cases of Extensively Drug-Resistant Pseudomonas aeruginosa Detected Through Whole Genome Sequencing-Based Surveillance. J Infect Dis 2024; 229:517-521. [PMID: 37700467 PMCID: PMC10873170 DOI: 10.1093/infdis/jiad318] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 08/03/2023] [Indexed: 09/14/2023] Open
Abstract
We describe 2 cases of extensively drug-resistant Pseudomonas aeruginosa infection caused by a strain of public health concern, as it was recently associated with a nationwide outbreak of contaminated artificial tears. Both cases were detected through database review of genomes in the Enhanced Detection System for Hospital-Associated Transmission (EDS-HAT), a routine genome sequencing-based surveillance program. We generated a high-quality reference genome for the outbreak strain from an isolate from our center and examined the mobile elements encoding blaVIM-80 and bla-GES-9 carbapenemases. We used publicly available Pseudomonas aeruginosa genomes to explore the genetic relatedness and antimicrobial resistance genes of the outbreak strain.
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Affiliation(s)
- Alexander J Sundermann
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh
- Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Vatsala Rangachar Srinivasa
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh
- Division of Infectious Diseases, University of Pittsburgh School of Medicine
- Department of Epidemiology, School of Public Health, University of Pittsburgh
| | - Emma G Mills
- Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Marissa P Griffith
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh
- Division of Infectious Diseases, University of Pittsburgh School of Medicine
- Department of Epidemiology, School of Public Health, University of Pittsburgh
| | - Kady D Waggle
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh
- Division of Infectious Diseases, University of Pittsburgh School of Medicine
- Department of Epidemiology, School of Public Health, University of Pittsburgh
| | - Ashley M Ayres
- Department of Infection Control and Hospital Epidemiology, University of Pittsburgh Medical Center–Presbyterian Hospital, Pittsburgh, Pennsylvania
| | - Lora Pless
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh
- Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Graham M Snyder
- Division of Infectious Diseases, University of Pittsburgh School of Medicine
- Department of Infection Control and Hospital Epidemiology, University of Pittsburgh Medical Center–Presbyterian Hospital, Pittsburgh, Pennsylvania
| | - Lee H Harrison
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh
- Division of Infectious Diseases, University of Pittsburgh School of Medicine
- Department of Epidemiology, School of Public Health, University of Pittsburgh
| | - Daria Van Tyne
- Division of Infectious Diseases, University of Pittsburgh School of Medicine
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Doyle H, Valek AL, Murillo T, Ayres AM, Slaughter J, Berg ML, Snyder GM. A novel approach to correcting attribution of Clostridioides difficile in a healthcare setting. Antimicrob Steward Healthc Epidemiol 2023; 3:e246. [PMID: 38156213 PMCID: PMC10753511 DOI: 10.1017/ash.2023.516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/09/2023] [Accepted: 11/13/2023] [Indexed: 12/30/2023]
Abstract
Objective To describe a novel attribution metric estimating the causal source location of healthcare-associated Clostridioides difficile and compare it with the current US National Healthcare Safety Network (NHSN) surveillance reporting standard. Design Quality improvement study. Setting Two acute care facilities. Methods A novel attribution metric assigned days of attribution to locations where patients were located for 14 days before and the day of their C. difficile diagnosis. We correlated the NHSN-assigned unit attribution with the novel attribution measure and compared the proportion of attribution assigned to inpatient units. Results During a 30-month period, there were 727 NHSN C. difficile healthcare-associated infections (HAIs) and 409 non-HAIs; the novel metric attributed 17,034 days. The correlation coefficients for NHSN and novel attributions among non-ICU units were 0.79 (95% CI, 0.76-0.82) and 0.74 (95% CI, 0.70-0.78) and among ICU units were 0.70 (95% CI, 0.63-0.76) and 0.69 (95% CI, 0.60-0.77) at facilities A and B, respectively. The distribution of difference in percent attribution showed higher inpatient unit attribution using NHSN measure than the novel attribution metric: 38% of ICU units and 15% of non-ICU units in facility A, and 20% of ICU units and 25% of non-ICU units in facility B had a median difference >0; no inpatient units showed a greater attribution using the novel attribution metric. Conclusion The novel attribution metric shifts attribution from inpatient units to other settings and correlates modestly with NHSN methodology of attribution. If validated, the attribution metric may more accurately target C. difficile reduction efforts.
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Affiliation(s)
- Hunter Doyle
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA
| | - Abby L. Valek
- Department of Infection Prevention and Control, UPMC Presbyterian/Shadyside, Pittsburgh, PA, USA
| | - Theresa Murillo
- Department of Infection Prevention and Control, UPMC Senior Communities, Pittsburgh, PA, USA
| | - Ashley M. Ayres
- Department of Infection Prevention and Control, UPMC Presbyterian/Shadyside, Pittsburgh, PA, USA
| | - Julie Slaughter
- Department of Infection Prevention and Control, UPMC Presbyterian/Shadyside, Pittsburgh, PA, USA
| | - Madeline L. Berg
- Department of Infection Prevention and Control, UPMC Presbyterian/Shadyside, Pittsburgh, PA, USA
| | - Graham M. Snyder
- Department of Infection Prevention and Control, UPMC Presbyterian/Shadyside, Pittsburgh, PA, USA
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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Berg ML, Baxter C, Ayres AM, Chung A, Slaughter J, Bilderback A, Feterik K, Ambrosino R, Wagester S, Snyder GM. The impact of autocancellation of uncollected Clostridioides difficile specimens after 24 hours on reported healthcare-associated infections: A quality improvement intervention. Infect Control Hosp Epidemiol 2023; 44:1942-1947. [PMID: 37332187 PMCID: PMC10755141 DOI: 10.1017/ice.2023.117] [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] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/18/2023] [Accepted: 05/07/2023] [Indexed: 06/20/2023]
Abstract
OBJECTIVE To assess the impact of a 24-hour autocancellation of uncollected Clostridioides difficile samples in reducing reported healthcare-associated infections (HAIs). DESIGN Quality-improvement, before-and-after implementation study. SETTING The study was conducted in 17 hospitals in Pennsylvania. INTERVENTIONS Clostridioides difficile tests that are not collected within 24 hours are automatically canceled ("autocancel") through the electronic health record. The intervention took place at 2 facilities (intervention period November 2021-July 2022) and subsequently at 15 additional facilities (April 2022-July 2022). Quality measures included percentage of orders canceled, C. difficile HAI rate, percent positivity of completed tests, and potential adverse outcomes of canceled or delayed testing. RESULTS Of 6,101 orders, 1,090 (17.9%) were automatically canceled after not being collected for 24 hours during the intervention periods. The reported C. difficile HAI rates per 10,000 patient days did not significantly change. These rates were 8.07 in the 6-month preintervention period and 8.77 in the intervention period for facilities A and B combined (incidence rate ratio [IRR], 1.09; 95% CI, 0.88-1.34; P = .43), and were 5.23 HAIs per 10,000 patient days in the 6-month preintervention period and 5.33 in the intervention period for facilities C-Q combined (IRR, 1.02; 95% CI, 0.79-1.32; P = .87). From the preintervention to the intervention periods, the percent positivity rates of completed C. difficile tests increased by 1.1% for facilities A and B and by 1.4% for facilities C-Q. No adverse outcomes were observed. CONCLUSIONS The 24-hour autocancellation of uncollected C. difficile orders reduced testing but did not result in reported HAI reduction.
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Affiliation(s)
- Madeline L. Berg
- Department of Infection Prevention and Control, UPMC Presbyterian/Shadyside, Pittsburgh, Pennsylvania
| | - Carla Baxter
- Wolff Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Ashley M. Ayres
- Department of Infection Prevention and Control, UPMC Presbyterian/Shadyside, Pittsburgh, Pennsylvania
| | - Ashley Chung
- Wolff Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Julie Slaughter
- Department of Infection Prevention and Control, UPMC Presbyterian/Shadyside, Pittsburgh, Pennsylvania
| | - Andrew Bilderback
- Wolff Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Kristian Feterik
- Division of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Richard Ambrosino
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Suzanne Wagester
- Wolff Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Graham M. Snyder
- Department of Infection Prevention and Control, UPMC Presbyterian/Shadyside, Pittsburgh, Pennsylvania
- Wolff Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
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Raabe NJ, Valek AL, Griffith MP, Mills E, Waggle K, Srinivasa VR, Ayres AM, Bradford C, Creager H, Pless LL, Sundermann AJ, Van Tyne D, Snyder GM, Harrison LH. Genomic Epidemiologic Investigation of a Multispecies Hospital Outbreak of NDM-5-Producing Enterobacterales Infections. medRxiv 2023:2023.08.31.23294545. [PMID: 37693518 PMCID: PMC10491379 DOI: 10.1101/2023.08.31.23294545] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Background New Delhi metallo-β-lactamase (NDM) represents an emergent mechanism of carbapenem resistance associated with high mortality and limited antimicrobial treatment options. Because the blaNDM resistance gene is often carried on plasmids, traditional infection prevention and control (IP&C) surveillance methods like speciation, antimicrobial resistance testing, and reactive whole genome sequencing (WGS) may not detect plasmid transfer in multispecies outbreaks. Methods Initial outbreak detection of NDM-producing Enterobacterales identified at an acute care hospital occurred via traditional IP&C methods and was supplemented by real-time WGS surveillance, which was performed weekly using the Illumina platform. To resolve NDM-encoding plasmids, we performed long-read Oxford Nanopore sequencing and constructed hybrid assemblies using Illumina and Nanopore sequencing data. Reports of relatedness between NDM-producing organisms and reactive WGS for suspected outbreaks were shared with the IP&C team for assessment and intervention. Findings We observed a multispecies outbreak of NDM-5-producing Enterobacterales isolated from 15 patients between February 2021 and February 2023. The 19 clinical and surveillance isolates sequenced included seven bacterial species and each encoded the same NDM-5 plasmid, which showed high homology to NDM plasmids previously observed in Asia. WGS surveillance and epidemiologic investigation characterized ten horizontal plasmid transfer events and six bacterial transmission events between patients housed in varying hospital units. Transmission prevention focused on enhanced observation and adherence to basic infection prevention measures. Interpretation Our investigation revealed a complex, multispecies outbreak of NDM that involved multiple plasmid transfer and bacterial transmission events, increasing the complexity of outbreak identification and transmission prevention. Our investigation highlights the utility of combining traditional IP&C and prospective genomic methods in identifying and containing plasmid-associated outbreaks. Funding This work was funded in part by the National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH) (R01AI127472) (R21AI1783691).
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Affiliation(s)
- Nathan J. Raabe
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, 3507 Victoria Street, BST-10 E1000-4A, Pittsburgh, Pennsylvania 15213, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, 3550 Terrace Street, 818 Scaife Hall, Pittsburgh, Pennsylvania 15261, USA
- Department of Epidemiology, School of Public Health, University of Pittsburgh, 130 De Soto Street, Pittsburgh, Pennsylvania 15261, USA
| | - Abby L. Valek
- Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, 200 Lothrop Street, Pittsburgh, Pennsylvania 15213, USA
| | - Marissa P. Griffith
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, 3507 Victoria Street, BST-10 E1000-4A, Pittsburgh, Pennsylvania 15213, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, 3550 Terrace Street, 818 Scaife Hall, Pittsburgh, Pennsylvania 15261, USA
| | - Emma Mills
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, 3550 Terrace Street, 818 Scaife Hall, Pittsburgh, Pennsylvania 15261, USA
| | - Kady Waggle
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, 3507 Victoria Street, BST-10 E1000-4A, Pittsburgh, Pennsylvania 15213, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, 3550 Terrace Street, 818 Scaife Hall, Pittsburgh, Pennsylvania 15261, USA
- Department of Epidemiology, School of Public Health, University of Pittsburgh, 130 De Soto Street, Pittsburgh, Pennsylvania 15261, USA
| | - Vatsala Rangachar Srinivasa
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, 3507 Victoria Street, BST-10 E1000-4A, Pittsburgh, Pennsylvania 15213, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, 3550 Terrace Street, 818 Scaife Hall, Pittsburgh, Pennsylvania 15261, USA
| | - Ashley M. Ayres
- Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, 200 Lothrop Street, Pittsburgh, Pennsylvania 15213, USA
| | - Claire Bradford
- Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, 200 Lothrop Street, Pittsburgh, Pennsylvania 15213, USA
| | - Hannah Creager
- Department of Pathology, University of Pittsburgh Medical Center, 200 Lothrop Street Pittsburgh, PA 15213
- Department of Pathology, University of Pittsburgh School of Medicine, 200 Lothrop St, S-417 BST, Pittsburgh, PA 15261
| | - Lora L. Pless
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, 3507 Victoria Street, BST-10 E1000-4A, Pittsburgh, Pennsylvania 15213, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, 3550 Terrace Street, 818 Scaife Hall, Pittsburgh, Pennsylvania 15261, USA
| | - Alexander J. Sundermann
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, 3507 Victoria Street, BST-10 E1000-4A, Pittsburgh, Pennsylvania 15213, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, 3550 Terrace Street, 818 Scaife Hall, Pittsburgh, Pennsylvania 15261, USA
| | - Daria Van Tyne
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, 3550 Terrace Street, 818 Scaife Hall, Pittsburgh, Pennsylvania 15261, USA
| | - Graham M. Snyder
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, 3550 Terrace Street, 818 Scaife Hall, Pittsburgh, Pennsylvania 15261, USA
- Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, 200 Lothrop Street, Pittsburgh, Pennsylvania 15213, USA
| | - Lee H. Harrison
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, 3507 Victoria Street, BST-10 E1000-4A, Pittsburgh, Pennsylvania 15213, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, 3550 Terrace Street, 818 Scaife Hall, Pittsburgh, Pennsylvania 15261, USA
- Department of Epidemiology, School of Public Health, University of Pittsburgh, 130 De Soto Street, Pittsburgh, Pennsylvania 15261, USA
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Ayres AM, Wozniak J, O’Neil J, Stewart K, Leger JS, Pasculle AW, Lewis C, McGrath K, Slivka A, Snyder GM. Endoscopic retrograde cholangiopancreatography and endoscopic ultrasound endoscope reprocessing: Variables impacting contamination risk. Infect Control Hosp Epidemiol 2023; 44:1485-1489. [PMID: 36645014 PMCID: PMC10507511 DOI: 10.1017/ice.2022.319] [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] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/13/2022] [Accepted: 12/15/2022] [Indexed: 01/17/2023]
Abstract
OBJECTIVE To evaluate variables that affect risk of contamination for endoscopic retrograde cholangiopancreatography and endoscopic ultrasound endoscopes. DESIGN Observational, quality improvement study. SETTING University medical center with a gastrointestinal endoscopy service performing ∼1,000 endoscopic retrograde cholangiopancreatography and ∼1,000 endoscopic ultrasound endoscope procedures annually. METHODS Duodenoscope and linear echoendoscope sampling (from the elevator mechanism and instrument channel) was performed from June 2020 through September 2021. Operational changes during this period included standard reprocessing with high-level disinfection with ethylene oxide gas sterilization (HLD-ETO) was switched to double high-level disinfection (dHLD) (June 16, 2020-July 15, 2020), and duodenoscopes changed to disposable tip model (March 2021). The frequency of contamination for the co-primary outcomes were characterized by calculated risk ratios. RESULTS The overall pathogenic contamination rate was 4.72% (6 of 127). Compared to duodenoscopes, linear echoendoscopes had a contamination risk ratio of 3.64 (95% confidence interval [CI], 0.69-19.1). Reprocessing using HLD-ETO was associated with a contamination risk ratio of 0.29 (95% CI, 0.06-1.54). Linear echoendoscopes undergoing dHLD had the highest risk of contamination (2 of 18, 11.1%), and duodenoscopes undergoing HLD-ETO and the lowest risk of contamination (0 of 53, 0%). Duodenoscopes with a disposable tip had a 0% contamination rate (0 of 27). CONCLUSIONS We did not detect a significant reduction in endoscope contamination using HLD-ETO versus dHLD reprocessing. Linear echoendoscopes have a risk of contamination similar to that of duodenoscopes. Disposable tips may reduce the risk of duodenoscope contamination.
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Affiliation(s)
- Ashley M. Ayres
- Department of Infection Prevention and Control, UPMC Presbyterian–Shadyside, Pittsburgh, Pennsylvania
| | - Julia Wozniak
- Department of Infection Prevention and Control, UPMC Presbyterian–Shadyside, Pittsburgh, Pennsylvania
| | - Jose O’Neil
- Department of Gastroenterology, Hepatology, and Nutrition, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Kimberly Stewart
- Department of Gastroenterology, Hepatology, and Nutrition, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - John St. Leger
- Department of Gastroenterology, Hepatology, and Nutrition, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - A. William Pasculle
- Division of Microbiology, Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Casey Lewis
- Department of Infection Prevention and Control, UPMC Presbyterian–Shadyside, Pittsburgh, Pennsylvania
| | - Kevin McGrath
- Department of Gastroenterology, Hepatology, and Nutrition, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Adam Slivka
- Department of Gastroenterology, Hepatology, and Nutrition, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Graham M Snyder
- Department of Infection Prevention and Control, UPMC Presbyterian–Shadyside, Pittsburgh, Pennsylvania
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
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Sundermann AJ, Srinivasa VR, Mills EG, Griffith MP, Waggle KD, Ayres AM, Pless L, Snyder GM, Harrison LH, Van Tyne D. Two artificial tears outbreak-associated cases of XDR Pseudomonas aeruginosa detected through whole genome sequencing-based surveillance. medRxiv 2023:2023.04.11.23288417. [PMID: 37131775 PMCID: PMC10153325 DOI: 10.1101/2023.04.11.23288417] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
We describe two cases of XDR Pseudomonas aeruginosa infection caused by a strain of public health concern recently associated with a nationwide outbreak of contaminated artificial tears. Both cases were detected through database review of genomes in the Enhanced Detection System for Hospital-Associated Transmission (EDS-HAT), a routine genome sequencing-based surveillance program. We generated a high-quality reference genome for the outbreak strain from one of the case isolates from our center and examined the mobile elements encoding bla VIM-80 and bla GES-9 carbapenemases. We then used publicly available P. aeruginosa genomes to explore the genetic relatedness and antimicrobial resistance genes of the outbreak strain.
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Affiliation(s)
- Alexander J. Sundermann
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Vatsala Rangachar Srinivasa
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Emma G. Mills
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Marissa P. Griffith
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Kady D. Waggle
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Ashley M. Ayres
- Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, Pittsburgh, Pennsylvania, USA
| | - Lora Pless
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Graham M. Snyder
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, Pittsburgh, Pennsylvania, USA
| | - Lee H. Harrison
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Daria Van Tyne
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
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8
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Berg ML, Ayres AM, Weber DR, McCullough M, Crall VD, Lewis CL, Valek AL, Vincent LA, Penzelik J, Sasinoski CA, Cheng AL, Bradford CF, Bell EO, Edwards KM, Castronova IA, Brady MB, Slaughter J, Oleksiuk LM, Snyder GM. Diagnostic stewardship for Clostridioides difficile testing in an acute care hospital: A quality improvement intervention. ASHE 2023; 3:e67. [PMID: 37113206 PMCID: PMC10127245 DOI: 10.1017/ash.2023.141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 02/17/2023] [Indexed: 04/09/2023]
Abstract
Abstract
Objective:
To evaluate the impact of a diagnostic stewardship intervention on Clostridioides difficile healthcare-associated infections (HAI).
Design:
Quality improvement study.
Setting:
Two urban acute care hospitals.
Interventions:
All inpatient stool testing for C. difficile required review and approval prior to specimen processing in the laboratory. An infection preventionist reviewed all orders daily through chart review and conversations with nursing; orders meeting clinical criteria for testing were approved, orders not meeting clinical criteria were discussed with the ordering provider. The proportion of completed tests meeting clinical criteria for testing and the primary outcome of C. difficile HAI were compared before and after the intervention.
Results:
The frequency of completed C. difficile orders not meeting criteria was lower [146 (7.5%) of 1,958] in the intervention period (January 10, 2022–October 14, 2022) than in the sampled 3-month preintervention period [26 (21.0%) of 124; P < .001]. C. difficile HAI rates were 8.80 per 10,000 patient days prior to the intervention (March 1, 2021–January 9, 2022) and 7.69 per 10,000 patient days during the intervention period (incidence rate ratio, 0.87; 95% confidence interval, 0.73–1.05; P = .13).
Conclusions:
A stringent order-approval process reduced clinically nonindicated testing for C. difficile but did not significantly decrease HAIs.
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9
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Sundermann AJ, Chen J, Kumar P, Ayres AM, Cho ST, Ezeonwuka C, Griffith MP, Miller JK, Mustapha MM, Pasculle AW, Saul MI, Shutt KA, Srinivasa V, Waggle K, Snyder DJ, Cooper VS, Van Tyne D, Snyder GM, Marsh JW, Dubrawski A, Roberts MS, Harrison LH. Whole Genome Sequencing Surveillance and Machine Learning of the Electronic Health Record for Enhanced Healthcare Outbreak Detection. Clin Infect Dis 2021; 75:476-482. [PMID: 34791136 PMCID: PMC9427134 DOI: 10.1093/cid/ciab946] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [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: 09/08/2021] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Most hospitals use traditional infection prevention (IP) methods for outbreak detection. We developed the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), which combines whole genome sequencing (WGS) surveillance and machine learning (ML) of the electronic health record (EHR) to identify undetected outbreaks and the responsible transmission routes, respectively. METHODS We performed WGS surveillance of healthcare-associated bacterial pathogens from November 2016 to November 2018. EHR ML was used to identify the transmission routes for WGS-detected outbreaks, which were investigated by an IP expert. Potential infections prevented were estimated and compared to traditional IP practice during the same period. RESULTS Of 3,165 isolates, there were 2,752 unique patient isolates in 99 clusters involving 297 (10.8%) patient isolates were identified by WGS; clusters ranged from 2-14 patients. At least one transmission route was detected for 65.7% of clusters. During the same time, traditional IP investigation prompted WGS for 15 suspected outbreaks involving 133 patients, for which transmission events were identified for 5 (3.8%). If EDS-HAT had been running in real-time, 25-63 transmissions could have been prevented. EDS-HAT was found to be cost-saving and more effective than traditional IP practice, with overall savings of $192,408 - $692,532. CONCLUSION EDS-HAT detected multiple outbreaks not identified using traditional IP methods, correctly identified the transmission routes for most outbreaks, and would save the hospital substantial costs. Traditional IP practice misidentified outbreaks for which transmission did not occur. WGS surveillance combined with EHR ML has the potential to save costs and enhance patient safety.
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Affiliation(s)
- Alexander J Sundermann
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.,Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Jieshi Chen
- Auton Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Praveen Kumar
- Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Ashley M Ayres
- Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, Pittsburgh, Pennsylvania, USA
| | - Shu-Ting Cho
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Chinelo Ezeonwuka
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Marissa P Griffith
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - James K Miller
- Auton Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Mustapha M Mustapha
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - A William Pasculle
- Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Melissa I Saul
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Kathleen A Shutt
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Vatsala Srinivasa
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Kady Waggle
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Daniel J Snyder
- Department of Microbiology and Molecular Genetics, and Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pennsylvania, USA
| | - Vaughn S Cooper
- Department of Microbiology and Molecular Genetics, and Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pennsylvania, USA
| | - Daria Van Tyne
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Graham M Snyder
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.,Department of Infection Control and Hospital Epidemiology, UPMC Presbyterian, Pittsburgh, Pennsylvania, USA
| | - Jane W Marsh
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Artur Dubrawski
- Auton Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Mark S Roberts
- Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Lee H Harrison
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.,Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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10
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Sundermann AJ, Chen J, Miller JK, Saul MI, Shutt KA, Griffith MP, Mustapha MM, Ezeonwuka C, Waggle K, Srinivasa V, Kumar P, Pasculle AW, Ayres AM, Snyder GM, Cooper VS, Van Tyne D, Marsh JW, Dubrawski AW, Harrison LH. Outbreak of Pseudomonas aeruginosa Infections from a Contaminated Gastroscope Detected by Whole Genome Sequencing Surveillance. Clin Infect Dis 2021; 73:e638-e642. [PMID: 33367518 DOI: 10.1093/cid/ciaa1887] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [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: 10/26/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Traditional methods of outbreak investigations utilize reactive whole genome sequencing (WGS) to confirm or refute the outbreak. We have implemented WGS surveillance and a machine learning (ML) algorithm for the electronic health record (EHR) to retrospectively detect previously unidentified outbreaks and to determine the responsible transmission routes. METHODS We performed WGS surveillance to identify and characterize clusters of genetically-related Pseudomonas aeruginosa infections during a 24-month period. ML of the EHR was used to identify potential transmission routes. A manual review of the EHR was performed by an infection preventionist to determine the most likely route and results were compared to the ML algorithm. RESULTS We identified a cluster of 6 genetically related P. aeruginosa cases that occurred during a 7-month period. The ML algorithm identified gastroscopy as a potential transmission route for 4 of the 6 patients. Manual EHR review confirmed gastroscopy as the most likely route for 5 patients. This transmission route was confirmed by identification of a genetically-related P. aeruginosa incidentally cultured from a gastroscope used on 4of the 5 patients. Three infections, 2 of which were blood stream infections, could have been prevented if the ML algorithm had been running in real-time. CONCLUSIONS WGS surveillance combined with a ML algorithm of the EHR identified a previously undetected outbreak of gastroscope-associated P. aeruginosa infections. These results underscore the value of WGS surveillance and ML of the EHR for enhancing outbreak detection in hospitals and preventing serious infections.
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Affiliation(s)
- Alexander J Sundermann
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.,Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Jieshi Chen
- Anton Laboratory, Carnegie Mellon University
| | | | - Melissa I Saul
- Department of Medicine, University of Pittsburgh School of Medicine
| | - Kathleen A Shutt
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.,Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Marissa P Griffith
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.,Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Mustapha M Mustapha
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.,Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Chinelo Ezeonwuka
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.,Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Kady Waggle
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.,Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Vatsala Srinivasa
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.,Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Praveen Kumar
- Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh
| | | | - Ashley M Ayres
- Department of Infection Prevention and Control, University of Pittsburgh Medical Center
| | - Graham M Snyder
- Division of Infectious Diseases, University of Pittsburgh School of Medicine.,Department of Infection Prevention and Control, University of Pittsburgh Medical Center
| | - Vaughn S Cooper
- Department of Microbiology and Molecular Genetics, and Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Daria Van Tyne
- Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | - Jane W Marsh
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.,Division of Infectious Diseases, University of Pittsburgh School of Medicine
| | | | - Lee H Harrison
- Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.,Division of Infectious Diseases, University of Pittsburgh School of Medicine
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11
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Sundermann AJ, Babiker A, Marsh JW, Shutt KA, Mustapha MM, Pasculle AW, Ezeonwuka C, Saul MI, Pacey MP, Van Tyne D, Ayres AM, Cooper VS, Snyder GM, Harrison LH. Outbreak of Vancomycin-resistant Enterococcus faecium in Interventional Radiology: Detection Through Whole-genome Sequencing-based Surveillance. Clin Infect Dis 2021; 70:2336-2343. [PMID: 31312842 DOI: 10.1093/cid/ciz666] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [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: 04/23/2019] [Accepted: 07/15/2019] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Vancomycin-resistant enterococci (VRE) are a major cause of hospital-acquired infections. The risk of infection from interventional radiology (IR) procedures is not well documented. Whole-genome sequencing (WGS) surveillance of clinical bacterial isolates among hospitalized patients can identify previously unrecognized outbreaks. METHODS We analyzed WGS surveillance data from November 2016 to November 2017 for evidence of VRE transmission. A previously unrecognized cluster of 10 genetically related VRE (Enterococcus faecium) infections was discovered. Electronic health record review identified IR procedures as a potential source. An outbreak investigation was conducted. RESULTS Of the 10 outbreak patients, 9 had undergone an IR procedure with intravenous (IV) contrast ≤22 days before infection. In a matched case-control study, preceding IR procedure and IR procedure with contrast were associated with VRE infection (matched odds ratio [MOR], 16.72; 95% confidence interval [CI], 2.01 to 138.73; P = .009 and MOR, 39.35; 95% CI, 7.85 to infinity; P < .001, respectively). Investigation of IR practices and review of the manufacturer's training video revealed sterility breaches in contrast preparation. Our investigation also supported possible transmission from an IR technician. Infection prevention interventions were implemented, and no further IR-associated VRE transmissions have been observed. CONCLUSIONS A prolonged outbreak of VRE infections related to IR procedures with IV contrast resulted from nonsterile preparation of injectable contrast. The fact that our VRE outbreak was discovered through WGS surveillance and the manufacturer's training video that demonstrated nonsterile technique raise the possibility that infections following invasive IR procedures may be more common than previously recognized.
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Affiliation(s)
- Alexander J Sundermann
- Microbial Genomic Epidemiology Laboratory, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pennsylvania.,Department of Infection Control and Hospital Epidemiology, University of Pittsburgh Medical Center, Pennsylvania
| | - Ahmed Babiker
- Microbial Genomic Epidemiology Laboratory, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pennsylvania.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pennsylvania
| | - Jane W Marsh
- Microbial Genomic Epidemiology Laboratory, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pennsylvania.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pennsylvania
| | - Kathleen A Shutt
- Microbial Genomic Epidemiology Laboratory, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pennsylvania.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pennsylvania
| | - Mustapha M Mustapha
- Microbial Genomic Epidemiology Laboratory, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pennsylvania.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pennsylvania
| | | | - Chinelo Ezeonwuka
- Microbial Genomic Epidemiology Laboratory, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pennsylvania.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pennsylvania
| | - Melissa I Saul
- Microbial Genomic Epidemiology Laboratory, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pennsylvania
| | - Marissa P Pacey
- Microbial Genomic Epidemiology Laboratory, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pennsylvania.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pennsylvania
| | - Daria Van Tyne
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pennsylvania
| | - Ashley M Ayres
- Department of Infection Control and Hospital Epidemiology, University of Pittsburgh Medical Center, Pennsylvania
| | - Vaughn S Cooper
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pennsylvania
| | - Graham M Snyder
- Department of Infection Control and Hospital Epidemiology, University of Pittsburgh Medical Center, Pennsylvania.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pennsylvania
| | - Lee H Harrison
- Microbial Genomic Epidemiology Laboratory, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pennsylvania.,Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pennsylvania
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12
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Marsh JW, Mustapha MM, Griffith MP, Evans DR, Ezeonwuka C, Pasculle AW, Shutt KA, Sundermann A, Ayres AM, Shields RK, Babiker A, Cooper VS, Van Tyne D, Harrison LH. Evolution of Outbreak-Causing Carbapenem-Resistant Klebsiella pneumoniae ST258 at a Tertiary Care Hospital over 8 Years. mBio 2019; 10:e01945-19. [PMID: 31481386 PMCID: PMC6722418 DOI: 10.1128/mbio.01945-19] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 08/09/2019] [Indexed: 12/21/2022] Open
Abstract
Carbapenem-resistant Klebsiella pneumoniae (CRKP) strains belonging to sequence type 258 (ST258) are frequent causes of hospital-associated outbreaks and are a major contributor to the spread of carbapenemases. This genetic lineage emerged several decades ago and remains a major global health care challenge. In this study, genomic epidemiology was used to investigate the emergence, evolution, and persistence of ST258 carbapenem-resistant K. pneumoniae outbreak-causing lineages at a large tertiary care hospital over 8 years. A time-based phylogenetic analysis of 136 ST258 isolates demonstrated the succession of multiple genetically distinct ST258 sublineages over the 8-year period. Ongoing genomic surveillance identified the emergence and persistence of several distinct clonal ST258 populations. Patterns of multidrug resistance determinants and plasmid replicons were consistent with continued evolution and persistence of these populations. Five ST258 outbreaks were documented, including three that were caused by the same clonal lineage. Mutations in genes encoding effectors of biofilm production and iron acquisition were identified among persistent clones. Two emergent lineages bearing K. pneumoniae integrative conjugative element 10 (ICEKp10) and harboring yersiniabactin and colibactin virulence factors were identified. The results show how distinct ST258 subpopulations have evolved and persisted within the same hospital over nearly a decade.IMPORTANCE The carbapenem class of antibiotics is invaluable for the treatment of selected multidrug-resistant Gram-negative pathogens. The continued transmission of carbapenem-resistant bacteria such as ST258 K. pneumoniae is of serious global public health concern, as treatment options for these infections are limited. This genomic epidemiologic investigation traced the natural history of ST258 K. pneumoniae in a single health care setting over nearly a decade. We found that distinct ST258 subpopulations have caused both device-associated and ward-associated outbreaks, and some of these populations remain endemic within our hospital to the present day. The finding of virulence determinants among emergent ST258 clones supports the idea of convergent evolution of drug-resistant and virulent CRKP strains and highlights the need for continued surveillance, prevention, and control efforts to address emergent and evolving ST258 populations in the health care setting.
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Affiliation(s)
- Jane W Marsh
- Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Mustapha M Mustapha
- Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Marissa P Griffith
- Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Daniel R Evans
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Chinelo Ezeonwuka
- Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
| | - A William Pasculle
- Division of Microbiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Kathleen A Shutt
- Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Alexander Sundermann
- Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
- Division of Hospital Epidemiology and Infection Control, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Ashley M Ayres
- Division of Hospital Epidemiology and Infection Control, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Ryan K Shields
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Ahmed Babiker
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Vaughn S Cooper
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Daria Van Tyne
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Lee H Harrison
- Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
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13
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Marshall AL, Levine M, Howell ML, Chang Y, Riklin E, Parry BA, Callahan RT, Okechukwu I, Ayres AM, Nahed BV, Goldstein JN. Dose-associated pulmonary complication rates after fresh frozen plasma administration for warfarin reversal. J Thromb Haemost 2016; 14:324-30. [PMID: 26644327 DOI: 10.1111/jth.13212] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [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: 08/05/2015] [Accepted: 11/19/2015] [Indexed: 11/28/2022]
Abstract
UNLABELLED ESSENTIALS: Fresh frozen plasma (FFP) may be associated with a dose-based risk of pulmonary complications. Patients received FFP for warfarin reversal at a large academic hospital over a 3-year period. Almost 20% developed pulmonary complications, and the risk was highest after > 3 units of FFP. The risk of pulmonary complications remained significant in multivariable analysis. BACKGROUND Fresh frozen plasma (FFP) is often administered to reverse warfarin anticoagulation. Administration has been associated with pulmonary complications, but it is unclear whether this risk is dose-related. Aims We sought to characterize the incidence and dose relationship of pulmonary complications, including transfusion-associated circulatory overload (TACO) and transfusion-related acute lung injury (TRALI), after FFP administration for warfarin reversal. METHODS We performed a structured retrospective review of patients who received FFP for warfarin reversal in the emergency department (ED) of an academic tertiary-care hospital over a 3-year period. Logistic regression was used to explore the relationship between FFP dose and risk of pulmonary events. RESULTS Two hundred and fifty-one patients met the inclusion criteria. Overall, 49 patients (20%) developed pulmonary complications, including 30 (12%) with TACO, two (1%) with TRALI, and 17 (7%) with pulmonary edema not meeting the criteria for TACO. Pulmonary complications were significantly more frequent in those who received > 3 units of FFP (34.0% versus 15.6%, 95% confidence interval for risk difference 7.9%-8.9%). After stratification by subtype of complication, only the risk of TACO was statistically significant (28.3% versus 7.6%, 95% confidence interval for risk difference 8.2%-16.6%). In multivariable analysis controlling for age, sex, initial systolic blood pressure, and intravenous fluids given in the ED, > 3 units of FFP remained a significant risk factor for pulmonary complications (odds ratio 2.49, 95% confidence interval 1.21-5.13). CONCLUSIONS Almost 20% of patients who received FFP for warfarin reversal developed pulmonary complications, primarily TACO, and this risk increased with > 3 units of FFP. Clinicians should be aware of and prepared to manage these complications.
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Affiliation(s)
| | - M Levine
- University of Southern California, Los Angeles, CA, USA
| | - M L Howell
- Massachusetts General Hospital, Boston, MA, USA
| | - Y Chang
- Massachusetts General Hospital, Boston, MA, USA
| | - E Riklin
- Massachusetts General Hospital, Boston, MA, USA
| | - B A Parry
- Massachusetts General Hospital, Boston, MA, USA
| | | | - I Okechukwu
- Massachusetts General Hospital, Boston, MA, USA
| | - A M Ayres
- Massachusetts General Hospital, Boston, MA, USA
| | - B V Nahed
- Massachusetts General Hospital, Boston, MA, USA
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14
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Biffi A, Shulman JM, Jagiella JM, Cortellini L, Ayres AM, Schwab K, Brown DL, Silliman SL, Selim M, Worrall BB, Meschia JF, Slowik A, De Jager PL, Greenberg SM, Schneider JA, Bennett DA, Rosand J. Genetic variation at CR1 increases risk of cerebral amyloid angiopathy. Neurology 2012; 78:334-41. [PMID: 22262751 DOI: 10.1212/wnl.0b013e3182452b40] [Citation(s) in RCA: 75] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
OBJECTIVE Accumulated evidence suggests that a variant within the CR1 gene (single nucleotide polymorphism rs6656401), known to increase risk for Alzheimer disease (AD), influences β-amyloid (Aβ) deposition in brain tissue. Given the biologic overlap between AD and cerebral amyloid angiopathy (CAA), a leading cause of intracerebral hemorrhage (ICH) in elderly individuals, we investigated whether rs6656401 increases the risk of CAA-related ICH and influences vascular Aβ deposition. METHODS We performed a case-control genetic association study of 89 individuals with CAA-related ICH and 280 individuals with ICH unrelated to CAA and compared them with 324 ICH-free control subjects. We also investigated the effect of rs6656401 on risk of recurrent CAA-ICH in a prospective longitudinal cohort of ICH survivors. Finally, association with severity of histopathologic CAA was investigated in 544 autopsy specimens from 2 longitudinal studies of aging. RESULTS rs6656401 was associated with CAA-ICH (odds ratio [OR] = 1.61, 95% confidence interval [CI] 1.19-2.17, p = 8.0 × 10(-4)) as well as with risk of recurrent CAA-ICH (hazard ratio = 1.35, 95% CI 1.04-1.76, p = 0.024). Genotype at rs6656401 was also associated with severity of CAA pathology at autopsy (OR = 1.34, 95% CI 1.05-1.71, p = 0.009). Adjustment for parenchymal amyloid burden did not cancel this effect, suggesting that, despite the correlation between parenchymal and vascular amyloid pathology, CR1 acts independently on both processes, thus increasing risk of both AD and CAA. CONCLUSION The CR1 variant rs6656401 influences risk and recurrence of CAA-ICH, as well as the severity of vascular amyloid deposition.
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Affiliation(s)
- A Biffi
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
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15
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Biffi A, Battey TWK, Ayres AM, Cortellini L, Schwab K, Gilson AJ, Rost NS, Viswanathan A, Goldstein JN, Greenberg SM, Rosand J. Warfarin-related intraventricular hemorrhage: imaging and outcome. Neurology 2011; 77:1840-6. [PMID: 22049204 DOI: 10.1212/wnl.0b013e3182377e12] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE Oral anticoagulation therapy (OAT) with warfarin increases mortality and disability after intracerebral hemorrhage (ICH), the result of increased ICH volume and risk of hematoma expansion. We investigated whether OAT also influences risk of development of intraventricular hemorrhage (IVH), the volume of IVH and IVH expansion, and whether IVH is a substantive mediator of the overall effect of OAT on ICH outcome. METHODS We performed a retrospective analysis of a prospectively collected single-center cohort of 1,879 consecutive ICH cases (796 lobar, 865 deep, 153 cerebellar, 15 multiple location, 50 primary IVH) from 1999 to 2009. ICH and IVH volumes at presentation, as well as hematoma expansion (>33% or >6 mL increase) and IVH expansion (>2 mL increase), were determined using established semiautomated methods. Outcome was assessed at 90 days using either the modified Rankin Scale or Glasgow Outcome Scale. RESULTS Warfarin use was associated with IVH risk, IVH volume at presentation, and IVH expansion in both lobar and deep ICH (all p < 0.05) in a dose-response relationship with international normalized ratio. Warfarin was associated with poor outcome in both lobar and deep ICH (p < 0.01), and >95% of this effect was accounted for by baseline ICH and IVH volumes, as well as ICH and IVH expansion. CONCLUSION Warfarin increases IVH volume and risk of IVH expansion in lobar and deep ICH. These findings (along with effects on ICH volume and expansion) likely represent the mechanisms by which anticoagulation worsens ICH functional outcome.
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Affiliation(s)
- A Biffi
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
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16
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Biffi A, Devan WJ, Anderson CD, Ayres AM, Schwab K, Cortellini L, Viswanathan A, Rost NS, Smith EE, Goldstein JN, Greenberg SM, Rosand J. Statin use and outcome after intracerebral hemorrhage: case-control study and meta-analysis. Neurology 2011; 76:1581-8. [PMID: 21451150 DOI: 10.1212/wnl.0b013e3182194be9] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVES Intracerebral hemorrhage (ICH) is a highly lethal disease of the elderly. Use of statins is increasingly widespread among the elderly, and therefore common in patients who develop ICH. Accumulating data suggests that statins have neuroprotective effects, but their association with ICH outcome has been inconsistent. We therefore performed a meta-analysis of all available evidence, including unpublished data from our own institution, to determine whether statin exposure is protective for patients who develop ICH. METHODS In our prospectively ascertained cohort, we compared 90-day functional outcome in 238 pre-ICH statin cases and 461 statin-free ICH cases. We then meta-analyzed results from our cohort along with previously published studies using a random effects model, for a total of 698 ICH statin cases and 1,823 non-statin-exposed subjects. RESULTS Data from our center demonstrated an association between statin use before ICH and increased probability of favorable outcome (odds ratio [OR] = 2.08, 95% confidence interval [CI] 1.37-3.17) and reduced mortality (OR = 0.47, 95% CI 0.32-0.70) at 90 days. No compound-specific statin effect was identified. Meta-analysis of all published evidence confirmed the effect of statin use on good outcome (OR = 1.91, 95% CI 1.38-2.65) and mortality (OR = 0.55, 95% CI 0.42-0.72) after ICH. CONCLUSION Antecedent use of statins prior to ICH is associated with favorable outcome and reduced mortality after ICH. This phenomenon appears to be a class effect of statins. Further studies are required to clarify the biological mechanisms underlying these observations.
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Affiliation(s)
- A Biffi
- Center for Human Genetic Research, Massachusetts General Hospital, 185 Cambridge Street, CPZN-6818, Boston, MA 02114, USA
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