7 results
An outbreak of Burkholderia cepacia bloodstream infections in a tertiary-care facility in northern India detected by a healthcare-associated infection surveillance network
- Bashir Fomda, Anoop Velayudhan, Valan A. Siromany, Gulnaz Bashir, Shaista Nazir, Aamir Ali, Omika Katoch, Alphina Karoung, Jacinta Gunjiyal, Nayeem Wani, Indranil Roy, Daniel VanderEnde, Neil Gupta, Aditya Sharma, Paul Malpiedi, Kamini Walia, Purva Mathur
-
- Journal:
- Infection Control & Hospital Epidemiology / Volume 44 / Issue 3 / March 2023
- Published online by Cambridge University Press:
- 07 June 2022, pp. 467-473
- Print publication:
- March 2023
-
- Article
- Export citation
-
Objective:
The burden of healthcare-associated infections (HAIs) is higher in low- and middle-income countries, but HAIs are often missed because surveillance is not conducted. Here, we describe the identification of and response to a cluster of Burkholderia cepacia complex (BCC) bloodstream infections (BSIs) associated with high mortality in a surgical ICU (SICU) that joined an HAI surveillance network.
Setting:A 780-bed, tertiary-level, public teaching hospital in northern India.
Methods:After detecting a cluster of BCC in the SICU, cases were identified by reviewing laboratory registers and automated identification and susceptibility testing outputs. Sociodemographic details, clinical records, and potential exposure histories were collected, and a self-appraisal of infection prevention and control (IPC) practices using assessment tools from the World Health Organization and the US Centers for Disease Control and Prevention was conducted. Training and feedback were provided to hospital staff. Environmental samples were collected from high-touch surfaces, intravenous medications, saline, and mouthwash.
Results:Between October 2017 and October 2018, 183 BCC BSI cases were identified. Case records were available for 121 case patients. Of these 121 cases, 91 (75%) were male, the median age was 35 years, and 57 (47%) died. IPC scores were low in the areas of technical guidelines, human resources, and monitoring and evaluation. Of the 30 environmental samples, 4 grew BCC. A single source of the outbreak was not identified.
Conclusions:Implementing standardized HAI surveillance in a low-resource setting detected an ongoing Burkholderia cepacia outbreak. The outbreak investigation and use of a multimodal approach reduced incident cases and informed changes in IPC practices.
Surveillance of Healthcare-Associated Bloodstream and Urinary Tract Infections in a National Level Network of Indian Hospitals
- Purva Mathur, Paul Malpiedi, Kamini Walia, Rajesh Malhotra, Padmini Srikantiah, Omika Katoch, Sonal Katyal, Surbhi Khurana, Mahesh Chandra Misra, Sunil Gupta, Subodh Kumar, Sushma Sagar, Naveet Vig, Pramod Garg, Arti Kapil, Manoj Sahu, Arunaloke Chakrabarti, Pallab Ray, Manisha Biswal, Neelam Taneja, Priscilla Rupali, Vellore Binila Chacko, Joy Sarojini Michael, Veeraraghavan Balaji, Camilla Rodrigues, Vijaya Lakshmi Nag, Vibhor Tak, Vimala Venkatesh, Chiranjay Mukhopadhyay, KE Vandana, Muralidhar Varma, Vijayshri Deotale, Ruchita Attal, Kanne Padmaja, Chand Wattal, Neeraj Goel, Sanjay Bhattacharya, Tadepalli Karuna, Saurabh Saigal, Bijayini Behera, Sanjeev Singh, MA Thirunarayan, Reema Nath, Raja Ray, Sujata Baveja, Mammen Chandy, Sudipta Mukherjee, Manas Roy, Gaurav Goel, Swagata Tripathy, Satyajeet Misra, Anupam Dey, Tushar Mishra, Hirak Raj, Bashir Fomda, Gulnaz Bashir, Shaista Nazir, Sulochana Devi, Khuraijam Ranjana Devi, Langpoklakpam Chaoba Singh, Padma Das, Anudita Bhargava, Ujjwala Gaikwad, Neeta Khandelwal, Geeta Vaghela, Tanvi Sukharamwala, Prachi Verma, Mamta Lamba, Shristi Jain, Prithwis Bhattacharyya, Anil Phukan, Clarissa Lyngdoh, Rajeev Sharma, Rajni Gaind, Rushika Saksena, Lata Kapoor, Neil Gupta, Aditya Sharma, Daniel VanderEnde, Anoop Velayudhan, Valan Siromany, Kayla Laserson, Randeep Guleria
-
- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s398-s399
- Print publication:
- October 2020
-
- Article
-
- You have access Access
- Export citation
-
Background: Healthcare-associated infections (HAIs) are a major global threat to patient safety. Systematic surveillance is crucial for understanding HAI rates and antimicrobial resistance trends and to guide infection prevention and control (IPC) activities based on local epidemiology. In India, no standardized national HAI surveillance system was in place before 2017. Methods: Public and private hospitals from across 21 states in India were recruited to participate in an HAI surveillance network. Baseline assessments followed by trainings ensured that basic microbiology and IPC implementation capacity existed at all sites. Standardized surveillance protocols for central-line–associated bloodstream infections (CLABSIs) and catheter-associated urinary tract infections (CAUTIs) were modified from the NHSN for the Indian context. IPC nurses were trained to implement surveillance protocols. Data were reported through a locally developed web portal. Standardized external data quality checks were performed to assure data quality. Results: Between May 2017 and April 2019, 109 ICUs from 37 hospitals (29 public and 8 private) enrolled in the network, of which 33 were teaching hospitals with >500 beds. The network recorded 679,109 patient days, 212,081 central-line days, and 387,092 urinary catheter days. Overall, 4,301 bloodstream infection (BSI) events and 1,402 urinary tract infection (UTI) events were reported. The network CLABSI rate was 9.4 per 1,000 central-line days and the CAUTI rate was 3.4 per 1,000 catheter days. The central-line utilization ratio was 0.31 and the urinary catheter utilization ratio was 0.57. Moreover, 3,542 (73%) of 4,742 pathogens reported from BSIs and 868 (53%) of 1,644 pathogens reported from UTIs were gram negative. Also, 1,680 (26.3%) of all 6,386 pathogens reported were Enterobacteriaceae. Of 1,486 Enterobacteriaceae with complete antibiotic susceptibility testing data reported, 832 (57%) were carbapenem resistant. Of 951 Enterobacteriaceae subjected to colistin broth microdilution testing, 62 (7%) were colistin resistant. The surveillance platform identified 2 separate hospital-level HAI outbreaks; one caused by colistin-resistant K. pneumoniae and another due to Burkholderia cepacia. Phased expansion of surveillance to additional hospitals continues. Conclusions: HAI surveillance was successfully implemented across a national network of diverse hospitals using modified NHSN protocols. Surveillance data are being used to understand HAI burden and trends at the facility and national levels, to inform public policy, and to direct efforts to implement effective hospital IPC activities. This network approach to HAI surveillance may provide lessons to other countries or contexts with limited surveillance capacity.
Funding: None
Disclosures: None
Supporting Healthcare-Associated Infection (HAI) Surveillance in Resource-Limited Settings: Lessons Learned, 2015–2019
- Matthew Westercamp, Paul Malpiedi, Amber Vasquez, Danica Gomes, Carmen Hazim, Benjamin J. Park, Rachel Smith
-
- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s395-s396
- Print publication:
- October 2020
-
- Article
-
- You have access Access
- Export citation
-
Background: Since 2015, the CDC has supported the development and implementation of healthcare-associated infection (HAI) surveillance in resource-limited settings through technical support of case definitions and methods that are feasible with existing surveillance capacity and integration with clinical care to maximize sustainability and data use for action. Methods: Surveillance initiatives included facility-level implementation programs in Kenya, Sierra Leone, Thailand, and Georgia; larger national or regional network-level projects in India and Vietnam were also supported. For assessment and planning, surveillance capacities were grouped into 3 domains: staff, informatics, and diagnostic capacities. Based on these capacities, simplified case definitions surveillance methodologies were devised to balance resources and effort with the anticipated value and use of findings. Results: There was broad understanding of the importance of HAI surveillance; however, the required resources and other challenges (eg, training, staffing, quality of available data) were underappreciated. Staff capacities were often influenced by a lack of dedicated surveillance staff and limited experience in systematic data collection and analysis. Informatics capacities were generally limited by the lack of digital data management, nonstandardized clinical data collection and storage, and the inability to assign and maintain unique patient identifiers. We found that capacity for diagnostics, a critical component of traditional HAI surveillance systems, was limited by its availability, frequency of use, and inconsistent rationale in clinical care. We found that successful surveillance strategies were generally simple, matched existing capacities, and targeted specific HAI priorities identified by clinical teams. For example, in Kenya and Sierra Leone, participating facilities established, with minimal external support, simplified SSI surveillance among post–caesarean-delivery patients. These initiatives improved integration of surveillance with clinical care through encouraging participation of the clinical team in surveillance and planning. Furthermore, these models directly linked surveillance activities to improved patient care (eg, combined clinical checklists with surveillance data collection forms). Discussion: In resource-limited settings, the local cost and effort required to establish and sustain the necessary infrastructure for HAI surveillance can be substantial. Establishing actionable and sustainable HAI surveillance can be achieved through simplifying HAI surveillance to match existing capacities and can result in valuable surveillance programs, even in very resource-limited settings.
Funding: None
Disclosures: None
Infection Prevention and Control Capacity Building During 2018–2019 Democratic Republic of Congo Ebola Virus Disease Outbreak
- April Baller, Kevin Ousman, Maria Clara Padoveze, Charles Basilubo, Rodrigue Bobwa, Antoine Engrand, Bienvenu Houndjo, Landry Cihambanya, Jonathan Lotemo, Samuel Mangala, Patrick Mirindi, Jude Tatabod, Deye Niang, Awa Ndir, Michel Yao, Bryan Christensen, Ibrahima Fall, Danica Gomes, Abdou Gueye, Carmen Hazim, Paul Malpiedi, Jonas Nsenda Nsenda, Molly Patrick, Nathalie tremblay, Vasquez Amber, Matthew Westercamp, Katie Wilson, Remegie Nzeyimana, Lucia Saenz, Benedetta Allegranzi
-
- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, p. s300
- Print publication:
- October 2020
-
- Article
-
- You have access Access
- Export citation
-
Background: As of July 1, 2019, ~18% of all cases in the Ebola virus disease (EVD) outbreak in the Democratic Republic of Congo (DRC) were healthcare-associated (ie, nosocomial) infections (HAIs) and healthcare worker (HCW) infections. Although progress has been achieved, gaps remained in infection prevention and control (IPC), specifically, a need to reinforce standardized, evidence-based IPC practices to effectively address HAIs. The Ministry of Health (MOH), in collaboration with partners, developed an IPC tool kit consisting of >70 documents (ie, terms of reference, standard operating procedures, training modules, etc) to improve HCW IPC knowledge and practices at healthcare facilities among staff. The tool kit incorporated international IPC standards, DRC-specific experiences, and best practices. Thus, it serves as a technical and operational package, covering general guidance (standard precautions) and EVD specific issues. Methods: A decentralized rollout approach was used to disseminate the tool kit content at the various health-system levels over several months. Initially, national-level training of trainers was held, followed by subnational-level training of IPC supervisors and key IPC implementers, and lastly, training of healthcare facility (HCF) IPC focal persons. The 5-day training adhered to the MOH standard of 60% theory and 40% practice. Participants completed evaluations before and after training; changes in knowledge between the pre- and posttraining tests were analyzed and the results of the statistical tests were reported (P < .05 was considered statistically significant). Results: In total, 294 IPC supervisors were trained across 7 subnational commissions. Data were analyzed for 138 participants. Participants were 60.9% IPC supervisors, 8% WASH supervisors, and 31% others. MOH representation was 52.9% The average results before the test were 66% (19.8 of 30), the average posttest results were 72% (21.6 of 30)—a significant improvement. The worst-performing pretest IPC domain was IPC approach, and facility closure was the worst performing for posttest. As of November 11, 15.7% of all cases were HAIs. Conclusions: The IPC training program initiated during an outbreak can increase knowledge and potentially improve practices and confidence. An association with the downward HAI trend is yet to be validated. The MOH anticipates that this tool kit will be the go-to resource for future Ebola outbreaks and that it will be incorporated into the preservice medical curriculum to ensure a resilient heath system.
Funding: None
Disclosures: None
Colonization With Antibiotic-Resistant Gram-Negative Bacteria in Population-Based Hospital and Community Settings in Chile
- Rafael Araos Bralic, Anne Peters, Felipe Sanchez, Danilo Alvares, Lina Rivas, Maria Spencer, Rodrigo Martinez, Francisco Moya, Loreto Rojas, Maria Luisa Rioseco, Pamela Rojas, Pedro Usedo, Rachel Smith, Paul Malpiedi, Benjamin J. Park, Aditya Sharma, Andrea Huidobro, Catterina Ferreccio, Erika DAgata, Jose Munita
-
- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s175-s176
- Print publication:
- October 2020
-
- Article
-
- You have access Access
- Export citation
-
Background: Estimating the burden of intestinal colonization with antibiotic-resistant gram-negative bacteria (AR-GNB) is critical to understanding their global epidemiology and spread. We aimed to determine the prevalence of, and risk factors for, intestinal colonization due to AR-GNB in population-based hospital and community settings in Chile. Methods: Between December 2018 and May 2019, we enrolled randomly selected hospitalized adults in 4 tertiary-care public hospitals (Antofagasta, Santiago, Curico and Puerto Montt), and adults residing in a community-based cohort in the rural town of Molina. Following informed consent, we collected rectal swabs and epidemiological information through a standardized questionnaire. Swabs were plated onto MacConkey agar with 2 µg/mL ciprofloxacin or ceftazidime. All recovered morphotypes were identified, and antibiotic susceptibility testing was performed via disk diffusion. The primary outcome was the prevalence of colonization with fluoroquinolone (FQ)- or third-generation cephalosporin (3GC)–resistant GNB. The secondary outcome was the prevalence of colonization with multidrug-resistant (MDR) GNB, defined as GNB resistant to ≥3 antibiotic classes. Categories were not mutually exclusive. Bivariate and multivariate analyses were performed to describe risk factors for colonization with these categories. Results: In total, 775 hospitalized adults and 357 community participants were enrolled, with a median age of 60 years (IQR, 42–72) and 55 years (IQR, 48–62) years, respectively. Among hospitalized participants, the prevalence of colonization with FQ- or 3GC-resistant GNB was 47% (95% CI, 43%–50%) and 41% (95% CI, 38%–45%), respectively, whereas the prevalence of MDR-GNB colonization was 27% (95% CI, 24%–31%). In the community setting, the prevalence of colonization with either FQ-, 3GC-resistant GNB, or MDR-GNB was 40% (95% CI, 34%–45%), 29% (95% CI, 24%– 34%), and 5% (95% CI, 3%–8%), respectively. Independent risk factors for hospital MDR-GNB colonization included the hospital of admission, unit of hospitalization (intensive care units carried the highest risk), in-hospital antimicrobial exposure, comorbidities (Charlson index), and length of stay. In the community setting, recent antibiotic exposure (<3 months) predicted colonization with either FQ- or 3GC-resistant GNB, and alcohol consumption was inversely associated with MDR GNB colonization. Conclusions: A high burden of colonization with AR-GNB was observed in this sample of hospitalized and community-dwelling adults in Chile. The high burden of colonization with GNB resistant to commonly used antibiotics such as FQ and 3GC found in community dwellers, suggests that the community may be a relevant source of antibiotic resistance. Efforts to understand relatedness between resistant strains circulating in the community and the hospital are needed.
Funding: None
Disclosures: None
Multiple importations and transmission of colistin-resistant Klebsiella pneumoniae in a hospital in northern India
- Purva Mathur, Surbhi Khurana, Tom J.B. de Man, Neha Rastogi, Omika Katoch, Balaji Veeraraghavan, Ayyan Raj Neeravi, Manigandan Venkatesan, Subodh Kumar, Sushma Sagar, Amit Gupta, Richa Aggarwal, Kapil Dev Soni, Rajesh Malhotra, Anoop Velayudhan, Valan Siromany, Paul Malpiedi, Joseph Lutgring, Kayla Laserson, Neil Gupta, Padmini Srikantiah, Aditya Sharma
-
- Journal:
- Infection Control & Hospital Epidemiology / Volume 40 / Issue 12 / December 2019
- Published online by Cambridge University Press:
- 18 October 2019, pp. 1387-1393
- Print publication:
- December 2019
-
- Article
- Export citation
-
Objective:
Resistance to colistin, a last resort antibiotic, has emerged in India. We investigated colistin-resistant Klebsiella pneumoniae(ColR-KP) in a hospital in India to describe infections, characterize resistance of isolates, compare concordance of detection methods, and identify transmission events.
Design:Retrospective observational study.
Methods:Case-patients were defined as individuals from whom ColR-KP was isolated from a clinical specimen between January 2016 and October 2017. Isolates resistant to colistin by Vitek 2 were confirmed by broth microdilution (BMD). Isolates underwent colistin susceptibility testing by disk diffusion and whole-genome sequencing. Medical records were reviewed.
Results:Of 846 K. pneumoniae isolates, 34 (4%) were colistin resistant. In total, 22 case-patients were identified. Most (90%) were male; their median age was 33 years. Half were transferred from another hospital; 45% died. Case-patients were admitted for a median of 14 days before detection of ColR-KP. Also, 7 case-patients (32%) received colistin before detection of ColR-KP. All isolates were resistant to carbapenems and susceptible to tigecycline. Isolates resistant to colistin by Vitek 2 were also resistant by BMD; 2 ColR-KP isolates were resistant by disk diffusion. Moreover, 8 multilocus sequence types were identified. Isolates were negative for mobile colistin resistance (mcr) genes. Based on sequencing analysis, in-hospital transmission may have occurred with 8 case-patients (38%).
Conclusions:Multiple infections caused by highly resistant, mcr-negative ColR-KP with substantial mortality were identified. Disk diffusion correlated poorly with Vitek 2 and BMD for detection of ColR-KP. Sequencing indicated multiple importation and in-hospital transmission events. Enhanced detection for ColR-KP may be warranted in India.
Probabilistic Measurement of Central Line–Associated Bloodstream Infections
- Bala Hota, Paul Malpiedi, Scott K. Fridkin, John Martin, William Trick
-
- Journal:
- Infection Control & Hospital Epidemiology / Volume 37 / Issue 2 / February 2016
- Published online by Cambridge University Press:
- 14 December 2015, pp. 149-155
- Print publication:
- February 2016
-
- Article
- Export citation
-
OBJECTIVE
To develop a probabilistic method for measuring central line–associated bloodstream infection (CLABSI) rates that reduces the variability associated with traditional, manual methods of applying CLABSI surveillance definitions.
DESIGNMulticenter retrospective cohort study of bacteremia episodes among patients hospitalized in adult patient-care units; the study evaluated presence of CLABSI.
SETTINGHospitals that used SafetySurveillor software system (Premier) and who also reported to the Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN).
PATIENTSPatients were identified from a stratified sample from all eligible blood culture isolates from all eligible hospital units to generate a final set with an equal distribution (ie, 20%) from each unit type. Units were divided a priori into 5 major groups: medical intensive care unit, surgical intensive care unit, medical-surgical intensive care unit, hematology unit, or general medical wards.
INTERVENTIONSEpisodes were reviewed by 2 experts, and a selection of discordant reviews were re-reviewed. Data were joined with NHSN data for hospitals for in-plan months. A predictive model was created; model performance was assessed using the c statistic in a validation set and comparison with NHSN reported rates for in-plan months.
RESULTSA final model was created with predictors of CLABSI. The c statistic for the final model was 0.75 (0.68–0.80). Rates from regression modeling correlated better with expert review than NHSN-reported rates.
CONCLUSIONSThe use of a regression model based on the clinical characteristics of the bacteremia outperformed traditional infection preventionist surveillance compared with an expert-derived reference standard.
Infect. Control Hosp. Epidemiol. 2016;37(2):149–155