13 results
Integration of genomic and clinical data augments surveillance of healthcare-acquired infections
- Doyle V. Ward, Andrew G. Hoss, Raivo Kolde, Helen C. van Aggelen, Joshua Loving, Stephen A. Smith, Deborah A. Mack, Raja Kathirvel, Jeffery A. Halperin, Douglas J. Buell, Brian E. Wong, Judy L. Ashworth, Mary M. Fortunato-Habib, Liyi Xu, Bruce A. Barton, Peter Lazar, Juan J. Carmona, Jomol Mathew, Ivan S. Salgo, Brian D. Gross, Richard T. Ellison III
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 40 / Issue 6 / June 2019
- Published online by Cambridge University Press:
- 23 April 2019, pp. 649-655
- Print publication:
- June 2019
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Background:
Determining infectious cross-transmission events in healthcare settings involves manual surveillance of case clusters by infection control personnel, followed by strain typing of clinical/environmental isolates suspected in said clusters. Recent advances in genomic sequencing and cloud computing now allow for the rapid molecular typing of infecting isolates.
Objective:To facilitate rapid recognition of transmission clusters, we aimed to assess infection control surveillance using whole-genome sequencing (WGS) of microbial pathogens to identify cross-transmission events for epidemiologic review.
Methods:Clinical isolates of Staphylococcus aureus, Enterococcus faecium, Pseudomonas aeruginosa, and Klebsiella pneumoniae were obtained prospectively at an academic medical center, from September 1, 2016, to September 30, 2017. Isolate genomes were sequenced, followed by single-nucleotide variant analysis; a cloud-computing platform was used for whole-genome sequence analysis and cluster identification.
Results:Most strains of the 4 studied pathogens were unrelated, and 34 potential transmission clusters were present. The characteristics of the potential clusters were complex and likely not identifiable by traditional surveillance alone. Notably, only 1 cluster had been suspected by routine manual surveillance.
Conclusions:Our work supports the assertion that integration of genomic and clinical epidemiologic data can augment infection control surveillance for both the identification of cross-transmission events and the inclusion of missed and exclusion of misidentified outbreaks (ie, false alarms). The integration of clinical data is essential to prioritize suspect clusters for investigation, and for existing infections, a timely review of both the clinical and WGS results can hold promise to reduce HAIs. A richer understanding of cross-transmission events within healthcare settings will require the expansion of current surveillance approaches.
2381 Childhood adversity, attachment style, and home visiting engagement
- Kelly M. Bower, Deborah Gross, Phyllis Sharps
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- Journal:
- Journal of Clinical and Translational Science / Volume 2 / Issue S1 / June 2018
- Published online by Cambridge University Press:
- 21 November 2018, p. 65
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OBJECTIVES/SPECIFIC AIMS: This case-control study aims to determine the relationships among childhood adversity, attachment style, and the likelihood of accepting or declining a referral for HV. The study will serve as a pilot to inform the power analysis of a subsequently proposed full-scale study. METHODS/STUDY POPULATION: Using a case-control study design, 25 women who decline HV referral (cases) will be compared with 25 women who accept HV referral (controls) on their exposure to childhood adversity and attachment style. Women who are eligible for the study are English-speaking mothers who have been offered HV services by Health Care Access Maryland. Surveys are administered in-person, either in the participant’s home or at another location (e.g., public library), based on participant preference. The dependent variable is participant’s verbal response to the HV referral (accept/decline). The independent variable, childhood adversity, will be measured using the Philadelphia Urban Adverse Childhood Experiences (ACEs) Survey and the Attachment Style Questionnaire (ASQ). Control variables include demographics (i.e., age, race, education, employment, housing, marital status), obstetric history (i.e., previous preterm birth, miscarriage, fetal death, infant death, abortion), and current psychosocial risk factors (i.e., history of substance use, intimate partner violence, depression). Descriptive comparisons will be done for the independent and control variables in controls versus cases. Bivariate analysis will examine associations between the odds of being a case and ACE score and ASQ score. Multivariate logistic regression models will be used to examine the relationship between ACE total and ASQ score; exposure to ACE in cases versus controls; and the odds of an avoidant and anxious attachment styles in cases versus controls. RESULTS/ANTICIPATED RESULTS: We hypothesize that (a) higher ACE scores will be positively associated with a higher level of avoidant attachment; (b) higher ACE scores will be positively associated with declining a HV referral; and (c) higher levels of avoidant attachment will be associated with declining a HV referral. DISCUSSION/SIGNIFICANCE OF IMPACT: Racial inequities in birth outcomes are pervasive and unjust. Non-Hispanic Black women experience births that result in infant mortality, fetal mortality, preterm birth, and low birth weight babies at more than double the rate of non-Hispanic White women in Baltimore and nationally. Prenatal and early childhood home visiting programs have been found to decrease maternal smoking and hypertensive disorder which are associated with PTB, reduce closely spaced births which is associated with fetal and infant death, and improve women’s long-term economic self-sufficiency, child health and social outcomes. However, as community-based programs, these services are not reaching the majority of eligible women in low-income urban settings—women who are also disproportionately burdened with poor pregnancy-related health outcomes. Considering the potential to improve outcomes, the importance of eliminating health disparities, and the national and local investment in HV services, it is vital to understand why some women are not enrolling in prenatal HV programs. The findings from this and subsequent studies will inform the translation of evidence-based HV program outreach efforts for women with complex social history. It will inform the design of enhanced outreach and engagement efforts of HV programs to more reliably engage women.
2358: Association of medical and psychosocial risk factors with engagement in prenatal home visiting
- Kelly M. Bower, Deborah Gross, Margaret Ensminger, Jana Goins, Phyllis Sharps
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- Journal:
- Journal of Clinical and Translational Science / Volume 1 / Issue S1 / September 2017
- Published online by Cambridge University Press:
- 10 May 2018, p. 27
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OBJECTIVES/SPECIFIC AIMS: The purpose of this study is to understand factors that are associated with identifying which eligible pregnant women in Baltimore City accept a referral for HV services. Taking into account demographic and obstetrical variables, we will examine the extent to which 13 medical and 14 psychosocial risk factors differentiate pregnant women who (1) accepted a HV referral, (2) could not be located, or (3) refused a HV referral. METHODS/STUDY POPULATION: In this observational study, we will use secondary data on 8172 pregnant women collected by Health Care Access Maryland (HCAM) between 2014 and 2016. HCAM is the single point of entry for all pregnant women in Baltimore City into HV. HV eligibility includes being a pregnant woman, residing in Baltimore City, being uninsured or receiving Medicaid, and being identified by a prenatal care provider who completed an assessment profile of the woman’s medical and psychosocial risk (prenatal risk assessment). The outcome variable, HV engagement status (ie, accepted referral, could not be located, refused referral), will be based on HCAM discharge codes. Medical risk factors include BMI, hypertension, anemia, asthma, sickle cell, diabetes, vaginal bleeding, genetic risk, sexually transmitted disease, last dental visit >1 year ago, and taking prescription medications. Psychosocial risk factors include current pregnancy unintended; <1 year since last delivery; late entry to prenatal care (>20 wk gestation); mental, physical, or developmental disability; history of abuse or violence within past 6 months; tobacco use; alcohol use; illegal substance use within the past 6 months; resides in home built before 1978; homelessness; lack of social/emotional support; exposure to long-term stress; lack of transportation; and history of depression or mental illness. All risk factor variables are categorical (yes/no). Control variables will include demographics (eg, age, race, ethnicity, marital status, educational level) and OB history (eg, history of preterm labor, history of fetal or infant death). We will conduct descriptive statistics to characterize the sample and look for interrelatedness among the risk factors. Where there is a high level of inter-relatedness we will consider combining or omitting variables to reduce redundancy. We will use multinomial regression to examine which medical and psychological factors are associated with referral category. RESULTS/ANTICIPATED RESULTS: We hypothesize that (a) women with more medical risk factors will be more likely to accept a referral for HV services, (b) women with more psychosocial risk factors will be more likely to refuse HV or not be located, and (c) certain risk factors, such as depression/mental illness, history of abuse/violence, illegal substance use, homelessness, and exposure to long-term stress will be the strongest predictors of not accepting HV referral and/or not being located. DISCUSSION/SIGNIFICANCE OF IMPACT: The translation of effective randomized control trials (RCTs) to successful implementation in community-based programs can be challenging. Community-based programs serving low-income communities typically lack the same resources available to recruit and retain participants in RCTs. And, exclusion criteria applied in RCTs are often not applied in real world implementation which can open program to participants with more complex social and medical characteristics. Findings from this study will inform the translation of evidence-based HV programs into real world settings through an enhanced understanding of the characteristics of women who are not engaged by HV programs. This will inform development of improved outreach methods that may more effectively engage at-risk women for prenatal HV services.
Contributors
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- By Lenard A. Adler, Pinky Agarwal, Rehan Ahmed, Jagga Rao Alluri, Fawaz Al-Mufti, Samuel Alperin, Michael Amoashiy, Michael Andary, David J. Anschel, Padmaja Aradhya, Vandana Aspen, Esther Baldinger, Jee Bang, George D. Baquis, John J. Barry, Jason J. S. Barton, Julius Bazan, Amanda R. Bedford, Marlene Behrmann, Lourdes Bello-Espinosa, Ajay Berdia, Alan R. Berger, Mark Beyer, Don C. Bienfang, Kevin M. Biglan, Thomas M. Boes, Paul W. Brazis, Jonathan L. Brisman, Jeffrey A. Brown, Scott E. Brown, Ryan R. Byrne, Rina Caprarella, Casey A. Chamberlain, Wan-Tsu W. Chang, Grace M. Charles, Jasvinder Chawla, David Clark, Todd J. Cohen, Joe Colombo, Howard Crystal, Vladimir Dadashev, Sarita B. Dave, Jean Robert Desrouleaux, Richard L. Doty, Robert Duarte, Jeffrey S. Durmer, Christyn M. Edmundson, Eric R. Eggenberger, Steven Ender, Noam Epstein, Alberto J. Espay, Alan B. Ettinger, Niloofar (Nelly) Faghani, Amtul Farheen, Edward Firouztale, Rod Foroozan, Anne L. Foundas, David Elliot Friedman, Deborah I. Friedman, Steven J. Frucht, Oded Gerber, Tal Gilboa, Martin Gizzi, Teneille G. Gofton, Louis J. Goodrich, Malcolm H. Gottesman, Varda Gross-Tsur, Deepak Grover, David A. Gudis, John J. Halperin, Maxim D. Hammer, Andrew R. Harrison, L. Anne Hayman, Galen V. Henderson, Steven Herskovitz, Caitlin Hoffman, Laryssa A. Huryn, Andres M. Kanner, Gary P. Kaplan, Bashar Katirji, Kenneth R. Kaufman, Annie Killoran, Nina Kirz, Gad E. Klein, Danielle G. Koby, Christopher P. Kogut, W. Curt LaFrance, Patrick J.M. Lavin, Susan W. Law, James L. Levenson, Richard B. Lipton, Glenn Lopate, Daniel J. Luciano, Reema Maindiratta, Robert M. Mallery, Georgios Manousakis, Alan Mazurek, Luis J. Mejico, Dragana Micic, Ali Mokhtarzadeh, Walter J. Molofsky, Heather E. Moss, Mark L. Moster, Manpreet Multani, Siddhartha Nadkarni, George C. Newman, Rolla Nuoman, Paul A. Nyquist, Gaia Donata Oggioni, Odi Oguh, Denis Ostrovskiy, Kristina Y. Pao, Juwen Park, Anastas F. Pass, Victoria S. Pelak, Jeffrey Peterson, John Pile-Spellman, Misha L. Pless, Gregory M. Pontone, Aparna M. Prabhu, Michael T. Pulley, Philip Ragone, Prajwal Rajappa, Venkat Ramani, Sindhu Ramchandren, Ritesh A. Ramdhani, Ramses Ribot, Heidi D. Riney, Diana Rojas-Soto, Michael Ronthal, Daniel M. Rosenbaum, David B. Rosenfield, Durga Roy, Michael J. Ruckenstein, Max C. Rudansky, Eva Sahay, Friedhelm Sandbrink, Jade S. Schiffman, Angela Scicutella, Maroun T. Semaan, Robert C. Sergott, Aashit K. Shah, David M. Shaw, Amit M. Shelat, Claire A. Sheldon, Anant M. Shenoy, Yelizaveta Sher, Jessica A. Shields, Tanya Simuni, Rajpaul Singh, Eric E. Smouha, David Solomon, Mehri Songhorian, Steven A. Sparr, Egilius L. H. Spierings, Eve G. Spratt, Beth Stein, S.H. Subramony, Rosa Ana Tang, Cara Tannenbaum, Hakan Tekeli, Amanda J. Thompson, Michael J. Thorpy, Matthew J. Thurtell, Pedro J. Torrico, Ira M. Turner, Scott Uretsky, Ruth H. Walker, Deborah M. Weisbrot, Michael A. Williams, Jacques Winter, Randall J. Wright, Jay Elliot Yasen, Shicong Ye, G. Bryan Young, Huiying Yu, Ryan J. Zehnder
- Edited by Alan B. Ettinger, Albert Einstein College of Medicine, New York, Deborah M. Weisbrot, State University of New York, Stony Brook
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- Book:
- Neurologic Differential Diagnosis
- Published online:
- 05 June 2014
- Print publication:
- 17 April 2014, pp xi-xx
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Contributors
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- By Aakash Agarwala, Linda S. Aglio, Rae M. Allain, Paul D. Allen, Houman Amirfarzan, Yasodananda Kumar Areti, Amit Asopa, Edwin G. Avery, Patricia R. Bachiller, Angela M. Bader, Rana Badr, Sibinka Bajic, David J. Baker, Sheila R. Barnett, Rena Beckerly, Lorenzo Berra, Walter Bethune, Sascha S. Beutler, Tarun Bhalla, Edward A. Bittner, Jonathan D. Bloom, Alina V. Bodas, Lina M. Bolanos-Diaz, Ruma R. Bose, Jan Boublik, John P. Broadnax, Jason C. Brookman, Meredith R. Brooks, Roland Brusseau, Ethan O. Bryson, Linda A. Bulich, Kenji Butterfield, William R. Camann, Denise M. Chan, Theresa S. Chang, Jonathan E. Charnin, Mark Chrostowski, Fred Cobey, Adam B. Collins, Mercedes A. Concepcion, Christopher W. Connor, Bronwyn Cooper, Jeffrey B. Cooper, Martha Cordoba-Amorocho, Stephen B. Corn, Darin J. Correll, Gregory J. Crosby, Lisa J. Crossley, Deborah J. Culley, Tomas Cvrk, Michael N. D'Ambra, Michael Decker, Daniel F. Dedrick, Mark Dershwitz, Francis X. Dillon, Pradeep Dinakar, Alimorad G. Djalali, D. John Doyle, Lambertus Drop, Ian F. Dunn, Theodore E. Dushane, Sunil Eappen, Thomas Edrich, Jesse M. Ehrenfeld, Jason M. Erlich, Lucinda L. Everett, Elliott S. Farber, Khaldoun Faris, Eddy M. Feliz, Massimo Ferrigno, Richard S. Field, Michael G. Fitzsimons, Hugh L. Flanagan Jr., Vladimir Formanek, Amanda A. Fox, John A. Fox, Gyorgy Frendl, Tanja S. Frey, Samuel M. Galvagno Jr., Edward R. Garcia, Jonathan D. Gates, Cosmin Gauran, Brian J. Gelfand, Simon Gelman, Alexander C. Gerhart, Peter Gerner, Omid Ghalambor, Christopher J. Gilligan, Christian D. Gonzalez, Noah E. Gordon, William B. Gormley, Thomas J. Graetz, Wendy L. Gross, Amit Gupta, James P. Hardy, Seetharaman Hariharan, Miriam Harnett, Philip M. Hartigan, Joaquim M. Havens, Bishr Haydar, Stephen O. Heard, James L. Helstrom, David L. Hepner, McCallum R. Hoyt, Robert N. Jamison, Karinne Jervis, Stephanie B. Jones, Swaminathan Karthik, Richard M. Kaufman, Shubjeet Kaur, Lee A. Kearse Jr., John C. Keel, Scott D. Kelley, Albert H. Kim, Amy L. Kim, Grace Y. Kim, Robert J. Klickovich, Robert M. Knapp, Bhavani S. Kodali, Rahul Koka, Alina Lazar, Laura H. Leduc, Stanley Leeson, Lisa R. Leffert, Scott A. LeGrand, Patricio Leyton, J. Lance Lichtor, John Lin, Alvaro A. Macias, Karan Madan, Sohail K. Mahboobi, Devi Mahendran, Christine Mai, Sayeed Malek, S. Rao Mallampati, Thomas J. Mancuso, Ramon Martin, Matthew C. Martinez, J. A. Jeevendra Martyn, Kai Matthes, Tommaso Mauri, Mary Ellen McCann, Shannon S. McKenna, Dennis J. McNicholl, Abdel-Kader Mehio, Thor C. Milland, Tonya L. K. Miller, John D. Mitchell, K. Annette Mizuguchi, Naila Moghul, David R. Moss, Ross J. Musumeci, Naveen Nathan, Ju-Mei Ng, Liem C. Nguyen, Ervant Nishanian, Martina Nowak, Ala Nozari, Michael Nurok, Arti Ori, Rafael A. Ortega, Amy J. Ortman, David Oxman, Arvind Palanisamy, Carlo Pancaro, Lisbeth Lopez Pappas, Benjamin Parish, Samuel Park, Deborah S. Pederson, Beverly K. Philip, James H. Philip, Silvia Pivi, Stephen D. Pratt, Douglas E. Raines, Stephen L. Ratcliff, James P. Rathmell, J. Taylor Reed, Elizabeth M. Rickerson, Selwyn O. Rogers Jr., Thomas M. Romanelli, William H. Rosenblatt, Carl E. Rosow, Edgar L. Ross, J. Victor Ryckman, Mônica M. Sá Rêgo, Nicholas Sadovnikoff, Warren S. Sandberg, Annette Y. Schure, B. Scott Segal, Navil F. Sethna, Swapneel K. Shah, Shaheen F. Shaikh, Fred E. Shapiro, Torin D. Shear, Prem S. Shekar, Stanton K. Shernan, Naomi Shimizu, Douglas C. Shook, Kamal K. Sikka, Pankaj K. Sikka, David A. Silver, Jeffrey H. Silverstein, Emily A. Singer, Ken Solt, Spiro G. Spanakis, Wolfgang Steudel, Matthias Stopfkuchen-Evans, Michael P. Storey, Gary R. Strichartz, Balachundhar Subramaniam, Wariya Sukhupragarn, John Summers, Shine Sun, Eswar Sundar, Sugantha Sundar, Neelakantan Sunder, Faraz Syed, Usha B. Tedrow, Nelson L. Thaemert, George P. Topulos, Lawrence C. Tsen, Richard D. Urman, Charles A. Vacanti, Francis X. Vacanti, Joshua C. Vacanti, Assia Valovska, Ivan T. Valovski, Mary Ann Vann, Susan Vassallo, Anasuya Vasudevan, Kamen V. Vlassakov, Gian Paolo Volpato, Essi M. Vulli, J. Matthias Walz, Jingping Wang, James F. Watkins, Maxwell Weinmann, Sharon L. Wetherall, Mallory Williams, Sarah H. Wiser, Zhiling Xiong, Warren M. Zapol, Jie Zhou
- Edited by Charles Vacanti, Scott Segal, Pankaj Sikka, Richard Urman
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- Book:
- Essential Clinical Anesthesia
- Published online:
- 05 January 2012
- Print publication:
- 11 July 2011, pp xv-xxviii
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Strategies to Prevent Clostridium difficile Infections in Acute Care Hospitals
- Erik R. Dubberke, Dale N. Gerding, David Classen, Kathleen M. Arias, Kelly Podgorny, Deverick J. Anderson, Helen Burstin, David P. Calfee, Susan E. Coffin, Victoria Fraser, Frances A. Griffin, Peter Gross, Keith S. Kaye, Michael Klompas, Evelyn Lo, Jonas Marschall, Leonard A. Mermel, Lindsay Nicolle, David A. Pegues, Trish M. Perl, Sanjay Saint, Cassandra D. Salgado, Robert A. Weinstein, Robert Wise, Deborah S. Yokoe
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 29 / Issue S1 / October 2008
- Published online by Cambridge University Press:
- 02 January 2015, pp. S81-S92
- Print publication:
- October 2008
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Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections. The intent of this document is to highlight practical recommendations in a concise format designed to assist acute care hospitals in implementing and prioritizing their Clostridium difficile infection (CDI) prevention efforts. Refer to the Society for Healthcare Epidemiology of America/Infectious Diseases Society of America “Compendium of Strategies to Prevent Healthcare-Associated Infections” Executive Summary and Introduction and accompanying editorial for additional discussion.
1. Increasing rates of CDI
C. difficile now rivals methicillin-resistant Staphylococcus aureus (MRSA) as the most common organism to cause healthcare-associated infections in the United States.
a. In the United States, the proportion of hospital discharges in which the patient received the International Classification of Diseases, Ninth Revision discharge diagnosis code for CDI more than doubled between 2000 and 2003, and CDI rates continued to increase in 2004 and 2005 (L. C. McDonald, MD, personal communication, July 2007). These increases have been seen in pediatric and adult populations, but elderly individuals have been disproportionately affected. CDI incidence has also increased in Canada and Europe.
b. There have been numerous reports of an increase in CDI severity.
c. Most reports of increases in the incidence and severity of CDI have been associated with the BI/NAP1/027 strain of C. difficile. This strain produces more toxins A and B in vitro than do many other strains of C. difficile, produces a third toxin (binary toxin), and is highly resistant to fluoroquinolones.
Strategies to Prevent Transmission of Methicillin-Resistant Staphylococcus aureus in Acute Care Hospitals
- David P. Calfee, Cassandra D. Salgado, David Classen, Kathleen M. Arias, Kelly Podgorny, Deverick J. Anderson, Helen Burstin, Susan E. Coffin, Erik R. Dubberke, Victoria Fraser, Dale N. Gerding, Frances A. Griffin, Peter Gross, Keith S. Kaye, Michael Klompas, Evelyn Lo, Jonas Marschall, Leonard A. Mermel, Lindsay Nicolle, David A. Pegues, Trish M. Perl, Sanjay Saint, Robert A. Weinstein, Robert Wise, Deborah S. Yokoe
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 29 / Issue S1 / October 2008
- Published online by Cambridge University Press:
- 02 January 2015, pp. S62-S80
- Print publication:
- October 2008
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Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections (HAIs). Our intent in this document is to highlight practical recommendations in a concise format to assist acute care hospitals in their efforts to prevent transmission of methicillin-resistant Staphylococcus aureus (MRSA). Refer to the Society for Healthcare Epidemiology of America/Infectious Diseases Society of America “Compendium of Strategies to Prevent Healthcare-Associated Infections” Executive Summary, Introduction, and accompanying editorial for additional discussion.
1. Burden of HAIs caused by MRSA in acute care facilities
a. In the United States, the proportion of hospital-associated S. aureus infections that are caused by strains resistant to methicillin has steadily increased. In 2004, MRSA accounted for 63% of S. aureus infections in hospitals.
b. Although the proportion of S. aureus–associated HAIs among intensive care unit (ICU) patients that are due to methicillin-resistant strains has increased (a relative measure of the MRSA problem), recent data suggest that the incidence of central line–associated bloodstream infection caused by MRSA (an absolute measure of the problem) has decreased in several types of ICUs since 2001. Although these findings suggest that there has been some success in preventing nosocomial MRSA transmission and infection, many patient groups continue to be at risk for such transmission.
c. MRSA has also been documented in other areas of the hospital and in other types of healthcare facilities, including those that provide long-term care.
Strategies to Prevent Ventilator-Associated Pneumonia in Acute Care Hospitals
- Susan E. Coffin, Michael Klompas, David Classen, Kathleen M. Arias, Kelly Podgorny, Deverick J. Anderson, Helen Burstin, David P. Calfee, Erik R. Dubberke, Victoria Fraser, Dale N. Gerding, Frances A. Griffin, Peter Gross, Keith S. Kaye, Evelyn Lo, Jonas Marschall, Leonard A. Mermel, Lindsay Nicolle, David A. Pegues, Trish M. Perl, Sanjay Saint, Cassandra D. Salgado, Robert A. Weinstein, Robert Wise, Deborah S. Yokoe
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 29 / Issue S1 / October 2008
- Published online by Cambridge University Press:
- 02 January 2015, pp. S31-S40
- Print publication:
- October 2008
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Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections. The intent of this document is to highlight practical recommendations in a concise format designed to assist acute care hospitals in implementing and prioritizing their ventilator-associated pneumonia (VAP) prevention efforts. Refer to the Society for Healthcare Epidemiology of America/Infectious Diseases Society of America “Compendium of Strategies to Prevent Healthcare-Associated Infections” Executive Summary and Introduction and accompanying editorial for additional discussion.
1. Occurrence of VAP in acute care facilities.
a. VAP is one of the most common infections acquired by adults and children in intensive care units (ICUs).
i. In early studies, it was reported that 10%-20% of patients undergoing ventilation developed VAP. More-recent publications report rates of VAP that range from 1 to 4 cases per 1,000 ventilator-days, but rates may exceed 10 cases per 1,000 ventilator-days in some neonatal and surgical patient populations. The results of recent quality improvement initiatives, however, suggest that many cases of VAP might be prevented by careful attention to the process of care.
2. Outcomes associated with VAP
a. VAP is a cause of significant patient morbidity and mortality, increased utilization of healthcare resources, and excess cost.
i. The mortality attributable to VAP may exceed 10%.
ii. Patients with VAP require prolonged periods of mechanical ventilation, extended hospitalizations, excess use of antimicrobial medications, and increased direct medical costs.
Strategies to Prevent Surgical Site Infections in Acute Care Hospitals
- Deverick J. Anderson, Keith S. Kaye, David Classen, Kathleen M. Arias, Kelly Podgorny, Helen Burstin, David P. Calfee, Susan E. Coffin, Erik R. Dubberke, Victoria Fraser, Dale N. Gerding, Frances A. Griffin, Peter Gross, Michael Klompas, Evelyn Lo, Jonas Marschall, Leonard A. Mermel, Lindsay Nicolle, David A. Pegues, Trish M. Perl, Sanjay Saint, Cassandra D. Salgado, Robert A. Weinstein, Robert Wise, Deborah S. Yokoe
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 29 / Issue S1 / October 2008
- Published online by Cambridge University Press:
- 02 January 2015, pp. S51-S61
- Print publication:
- October 2008
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Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections. The intent of this document is to highlight practical recommendations in a concise format designed to assist acute care hospitals to implement and prioritize their surgical site infection (SSI) prevention efforts. Refer to the Society for Healthcare Epidemiology of America/Infectious Diseases Society of America “Compendium of Strategies to Prevent Healthcare-Associated Infections” Executive Summary and Introduction and accompanying editorial for additional discussion.
1. Burden of SSIs as complications in acute care facilities.
a. SSIs occur in 2%-5% of patients undergoing inpatient surgery in the United States.
b. Approximately 500,000 SSIs occur each year.
2. Outcomes associated with SSI
a. Each SSI is associated with approximately 7-10 additional postoperative hospital days.
b. Patients with an SSI have a 2-11 times higher risk of death, compared with operative patients without an SSI.
i. Seventy-seven percent of deaths among patients with SSI are direcdy attributable to SSI.
c. Attributable costs of SSI vary, depending on the type of operative procedure and the type of infecting pathogen; published estimates range from $3,000 to $29,000.
i. SSIs are believed to account for up to $10 billion annually in healthcare expenditures.
1. Definitions
a. The Centers for Disease Control and Prevention National Nosocomial Infections Surveillance System and the National Healthcare Safety Network definitions for SSI are widely used.
b. SSIs are classified as follows (Figure):
i. Superficial incisional (involving only skin or subcutaneous tissue of the incision)
ii. Deep incisional (involving fascia and/or muscular layers)
iii. Organ/space
Strategies to Prevent Central Line–Associated Bloodstream Infections in Acute Care Hospitals
- Jonas Marschall, Leonard A. Mermel, David Classen, Kathleen M. Arias, Kelly Podgorny, Deverick J. Anderson, Helen Burstin, David P. Calfee, Susan E. Coffin, Erik R. Dubberke, Victoria Fraser, Dale N. Gerding, Frances A. Griffin, Peter Gross, Keith S. Kaye, Michael Klompas, Evelyn Lo, Lindsay Nicolle, David A. Pegues, Trish M. Perl, Sanjay Saint, Cassandra D. Salgado, Robert A. Weinstein, Robert Wise, Deborah S. Yokoe
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 29 / Issue S1 / October 2008
- Published online by Cambridge University Press:
- 02 January 2015, pp. S22-S30
- Print publication:
- October 2008
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Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections. The intent of this document is to highlight practical recommendations in a concise format designed to assist acute care hospitals in implementing and prioritizing their central line–associated bloodstream infection (CLABSI) prevention efforts. Refer to the Society for Healthcare Epidemiology of America/Infectious Diseases Society of America “Compendium of Strategies to Prevent Healthcare-Associated Infections” Executive Summary and Introduction and accompanying editorial for additional discussion.
1. Patients at risk for CLABSIs in acute care facilities
a. Intensive care unit (ICU) population: The risk of CLABSI in ICU patients is high. Reasons for this include the frequent insertion of multiple catheters, the use of specific types of catheters that are almost exclusively inserted in ICU patients and associated with substantial risk (eg, arterial catheters), and the fact that catheters are frequently placed in emergency circumstances, repeatedly accessed each day, and often needed for extended periods.
b. Non-ICU population: Although the primary focus of attention over the past 2 decades has been the ICU setting, recent data suggest that the greatest numbers of patients with central lines are in hospital units outside the ICU, where there is a substantial risk of CLABSI.
2. Outcomes associated with hospital-acquired CLABSI
a. Increased length of hospital stay
b. Increased cost; the non-inflation-adjusted attributable cost of CLABSIs has been found to vary from $3,700 to $29,000 per episode
Executive Summary: A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals
- Deborah S. Yokoe, Leonard A. Mermel, Deverick J. Anderson, Kathleen M. Arias, Helen Burstin, David P. Calfee, Susan E. Coffin, Erik R. Dubberke, Victoria Fraser, Dale N. Gerding, Frances A. Griffin, Peter Gross, Keith S. Kaye, Michael Klompas, Evelyn Lo, Jonas Marschall, Lindsay Nicolle, David A. Pegues, Trish M. Perl, Kelly Podgorny, Sanjay Saint, Cassandra D. Salgado, Robert A. Weinstein, Robert Wise, David Classen
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 29 / Issue S1 / October 2008
- Published online by Cambridge University Press:
- 02 January 2015, pp. S12-S21
- Print publication:
- October 2008
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Preventable healthcare-associated infections (HAIs) occur in US hospitals. Preventing these infections is a national priority, with initiatives led by healthcare organizations, professional associations, government and accrediting agencies, legislators, regulators, payers, and consumer advocacy groups. To assist acute care hospitals in focusing and prioritizing efforts to implement evidence-based practices for prevention of HAIs, the Society for Healthcare Epidemiology of America and the Infectious Diseases Society of America Standards and Practice Guidelines Committee appointed a task force to create a concise compendium of recommendations for the prevention of common HAIs. This compendium is implementation focused and differs from most previously published guidelines in that it highlights a set of basic HAI prevention strategies plus special approaches for use in locations and/or populations within the hospital when infections are not controlled by use of basic practices, recommends that accountability for implementing infection prevention practices be assigned to specific groups and individuals, and includes proposed performance measures for internal quality improvement efforts.
Strategies to Prevent Catheter-Associated Urinary Tract Infections in Acute Care Hospitals
- Evelyn Lo, Lindsay Nicolle, David Classen, Kathleen M. Arias, Kelly Podgorny, Deverick J. Anderson, Helen Burstin, David P. Calfee, Susan E. Coffin, Erik R. Dubberke, Victoria Fraser, Dale N. Gerding, Frances A. Griffin, Peter Gross, Keith S. Kaye, Michael Klompas, Jonas Marschall, Leonard A. Mermel, David A. Pegues, Trish M. Perl, Sanjay Saint, Cassandra D. Salgado, Robert A. Weinstein, Robert Wise, Deborah S. Yokoe
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 29 / Issue S1 / October 2008
- Published online by Cambridge University Press:
- 02 January 2015, pp. S41-S50
- Print publication:
- October 2008
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Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections. The intent of this document is to highlight practical recommendations in a concise format designed to assist acute care hospitals in implementing and prioritizing their catheter-associated urinary tract infection (CAUTI) prevention efforts. Refer to the Society for Healthcare Epidemiology of America/Infectious Diseases Society of America “Compendium of Strategies to Prevent Healthcare-Associated Infections” Executive Summary and Introduction and accompanying editorial for additional discussion.
1. Burden of CAUTIs
a. Urinary tract infection is the most common hospital-acquired infection; 80% of these infections are attributable to an indwelling urethral catheter.
b. Twelve to sixteen percent of hospital inpatients will have a urinary catheter at some time during their hospital stay.
c. The daily risk of acquisition of urinary infection varies from 3% to 7% when an indwelling urethral catheter remains in situ.
2. Outcomes associated with CAUTI
a. Urinary tract infection is the most important adverse outcome of urinary catheter use. Bacteremia and sepsis may occur in a small proportion of infected patients.
b. Morbidity attributable to any single episode of catheterization is limited, but the high frequency of catheter use in hospitalized patients means that the cumulative burden of CAUTI is substantial.
c. Catheter use is also associated with negative outcomes other than infection, including nonbacterial urethral inflammation, urethral strictures, and mechanical trauma.
Formation of amyloid fibrils by peptides derived from the bacterial cold shock protein CspB
- MICHAEL GROß, DEBORAH K. WILKINS, MAUREEN C. PITKEATHLY, EVONNE W. CHUNG, CLAIRE HIGHAM, ANNE CLARK, CHRISTOPHER M. DOBSON
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- Journal:
- Protein Science / Volume 8 / Issue 6 / June 1999
- Published online by Cambridge University Press:
- 01 June 1999, pp. 1350-1357
- Print publication:
- June 1999
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Three peptides covering the sequence regions corresponding to the first two (CspB-1), the first three (CspB-2), and the last two (CspB-3) β-strands of CspB, the major cold shock protein of Bacillus subtilis, have been synthesized and analyzed for their conformations in solution and for their precipitation behavior. The peptides are nearly insoluble in water, but highly soluble in aqueous solutions containing 50% acetonitrile (pH 4.0). Upon shifts of the solvent condition toward lower or higher acetonitrile concentrations, the peptides all form fibrils resembling those observed in amyloid associated diseases. These fibrils have been identified and characterized by electron microscopy, binding of the dye congo red, and X-ray fiber diffraction. Characterization of the peptides in solution by circular dichroism and NMR spectroscopy shows that the formation of these fibrils does not require specific preformed secondary structure in the solution state species. While the majority of the soluble fraction of each peptide is monomeric and unstructured, different types of structures including α-helical, β-sheet, and random coil conformations are observed under conditions that eventually lead to fibril formation. We conclude that the absence of tertiary contacts under solution conditions where binding interactions between peptide units are still favorable is a crucial requirement for amyloid formation. Thus, fragmentation of a sequence, like partial chemical denaturation or mutation, can enhance the capacity of specific protein sequences to form such fibrils.