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Pettrone K, Burnett E, Link-Gelles R, Haight SC, Schrodt C, England L, Gomes DJ, Shamout M, O'Laughlin K, Kimball A, Blau EF, Ladva CN, Szablewski CM, Tobin-D'Angelo M, Oosmanally N, Drenzek C, Browning SD, Bruce BB, da Silva J, Gold JAW, Jackson BR, Morris SB, Natarajan P, Fanfair RN, Patel PR, Rogers-Brown J, Rossow J, Wong KK, Murphy DJ, Blum JM, Hollberg J, Lefkove B, Brown FW, Shimabukuro T, Midgley CM, Tate JE, Killerby ME. Characteristics and Risk Factors of Hospitalized and Nonhospitalized COVID-19 Patients, Atlanta, Georgia, USA, March-April 2020. Emerg Infect Dis 2021; 27:1164-1168. [PMID: 33754981 PMCID: PMC8007327 DOI: 10.3201/eid2704.204709] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
We compared the characteristics of hospitalized and nonhospitalized patients who had coronavirus disease in Atlanta, Georgia, USA. We found that risk for hospitalization increased with a patient’s age and number of concurrent conditions. We also found a potential association between hospitalization and high hemoglobin A1c levels in persons with diabetes.
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2
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Abstract
Shigella commonly causes gastroenteritis but rarely spreads to the blood. During 2002–2012, we identified 11,262 Shigella infections through population-based active surveillance in Georgia; 72 (0.64%) were isolated from blood. Bacteremia was associated with age >18 years, black race, and S. flexneri. More than half of patients with bacteremia were HIV-infected.
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3
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da Silva JF, Hernandez-Romieu AC, Browning SD, Bruce BB, Natarajan P, Morris SB, Gold JAW, Neblett Fanfair R, Rogers-Brown J, Rossow J, Szablewski CM, Oosmanally N, D’Angelo MT, Drenzek C, Murphy DJ, Hollberg J, Blum JM, Jansen R, Wright DW, Sewell W, Owens J, Lefkove B, Brown FW, Burton DC, Uyeki TM, Patel PR, Jackson BR, Wong KK. COVID-19 Clinical Phenotypes: Presentation and Temporal Progression of Disease in a Cohort of Hospitalized Adults in Georgia, United States. Open Forum Infect Dis 2021; 8:ofaa596. [PMID: 33537363 PMCID: PMC7798484 DOI: 10.1093/ofid/ofaa596] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 12/03/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND The epidemiological features and outcomes of hospitalized adults with coronavirus disease 2019 (COVID-19) have been described; however, the temporal progression and medical complications of disease among hospitalized patients require further study. Detailed descriptions of the natural history of COVID-19 among hospitalized patients are paramount to optimize health care resource utilization, and the detection of different clinical phenotypes may allow tailored clinical management strategies. METHODS This was a retrospective cohort study of 305 adult patients hospitalized with COVID-19 in 8 academic and community hospitals. Patient characteristics included demographics, comorbidities, medication use, medical complications, intensive care utilization, and longitudinal vital sign and laboratory test values. We examined laboratory and vital sign trends by mortality status and length of stay. To identify clinical phenotypes, we calculated Gower's dissimilarity matrix between each patient's clinical characteristics and clustered similar patients using the partitioning around medoids algorithm. RESULTS One phenotype of 6 identified was characterized by high mortality (49%), older age, male sex, elevated inflammatory markers, high prevalence of cardiovascular disease, and shock. Patients with this severe phenotype had significantly elevated peak C-reactive protein creatinine, D-dimer, and white blood cell count and lower minimum lymphocyte count compared with other phenotypes (P < .01, all comparisons). CONCLUSIONS Among a cohort of hospitalized adults, we identified a severe phenotype of COVID-19 based on the characteristics of its clinical course and poor prognosis. These findings need to be validated in other cohorts, as improved understanding of clinical phenotypes and risk factors for their development could help inform prognosis and tailored clinical management for COVID-19.
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Affiliation(s)
- Juliana F da Silva
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Alfonso C Hernandez-Romieu
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- United States Public Health Service
| | - Sean D Browning
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Beau B Bruce
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Pavithra Natarajan
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Sapna B Morris
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- United States Public Health Service
| | - Jeremy A W Gold
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Robyn Neblett Fanfair
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- United States Public Health Service
| | - Jessica Rogers-Brown
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - John Rossow
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- United States Public Health Service
| | - Christine M Szablewski
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- Georgia Department of Public Health, Atlanta, Georgia, USA
| | | | | | - Cherie Drenzek
- Georgia Department of Public Health, Atlanta, Georgia, USA
| | - David J Murphy
- Emory University School of Medicine, Atlanta, Georgia, USA
| | - Julie Hollberg
- Emory University School of Medicine, Atlanta, Georgia, USA
| | - James M Blum
- Emory University School of Medicine, Atlanta, Georgia, USA
- Georgia Clinical & Translational Science Alliance, Atlanta, Georgia, USA
| | | | - David W Wright
- Georgia Clinical & Translational Science Alliance, Atlanta, Georgia, USA
- Grady Health System, Atlanta, Georgia, USA
| | | | - Jack Owens
- Phoebe Putney Memorial Hospital, Albany, Georgia, USA
| | | | - Frank W Brown
- Georgia Clinical & Translational Science Alliance, Atlanta, Georgia, USA
- Emory Decatur Hospital, Decatur, Georgia, USA
| | - Deron C Burton
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- United States Public Health Service
| | - Timothy M Uyeki
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- United States Public Health Service
| | - Priti R Patel
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- United States Public Health Service
| | - Brendan R Jackson
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- United States Public Health Service
| | - Karen K Wong
- CDC COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- United States Public Health Service
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4
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Jackson BR, Gold JAW, Natarajan P, Rossow J, Neblett Fanfair R, da Silva J, Wong KK, Browning SD, Bamrah Morris S, Rogers-Brown J, Hernandez-Romieu AC, Szablewski CM, Oosmanally N, Tobin-D'Angelo M, Drenzek C, Murphy DJ, Hollberg J, Blum JM, Jansen R, Wright DW, SeweSll WM, Owens JD, Lefkove B, Brown FW, Burton DC, Uyeki TM, Bialek SR, Patel PR, Bruce BB. Predictors at admission of mechanical ventilation and death in an observational cohort of adults hospitalized with COVID-19. Clin Infect Dis 2020; 73:e4141-e4151. [PMID: 32971532 PMCID: PMC7543323 DOI: 10.1093/cid/ciaa1459] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Indexed: 01/08/2023] Open
Abstract
Background Coronavirus disease (COVID-19) can cause severe illness and death. Predictors of poor outcome collected on hospital admission may inform clinical and public health decisions. Methods We conducted a retrospective observational cohort investigation of 297 adults admitted to eight academic and community hospitals in Georgia, United States, during March 2020. Using standardized medical record abstraction, we collected data on predictors including admission demographics, underlying medical conditions, outpatient antihypertensive medications, recorded symptoms, vital signs, radiographic findings, and laboratory values. We used random forest models to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CI) for predictors of invasive mechanical ventilation (IMV) and death. Results Compared with age <45 years, ages 65–74 years and ≥75 years were predictors of IMV (aOR 3.12, CI 1.47–6.60; aOR 2.79, CI 1.23–6.33) and the strongest predictors for death (aOR 12.92, CI 3.26–51.25; aOR 18.06, CI 4.43–73.63). Comorbidities associated with death (aORs from 2.4 to 3.8, p <0.05) included end-stage renal disease, coronary artery disease, and neurologic disorders, but not pulmonary disease, immunocompromise, or hypertension. Pre-hospital use vs. non-use of angiotensin receptor blockers (aOR 2.02, CI 1.03–3.96) and dihydropyridine calcium channel blockers (aOR 1.91, CI 1.03–3.55) were associated with death. Conclusions After adjustment for patient and clinical characteristics, older age was the strongest predictor of death, exceeding comorbidities, abnormal vital signs, and laboratory test abnormalities. That coronary artery disease, but not chronic lung disease, was associated with death among hospitalized patients warrants further investigation, as do associations between certain antihypertensive medications and death.
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Affiliation(s)
| | - Jeremy A W Gold
- CDC COVID-19 Emergency Response.,Epidemic Intelligence Service, CDC
| | | | - John Rossow
- CDC COVID-19 Emergency Response.,U.S. Public Health Service.,Epidemic Intelligence Service, CDC
| | | | | | - Karen K Wong
- CDC COVID-19 Emergency Response.,U.S. Public Health Service
| | - Sean D Browning
- CDC COVID-19 Emergency Response.,Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee
| | | | - Jessica Rogers-Brown
- CDC COVID-19 Emergency Response.,Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee
| | - Alfonso C Hernandez-Romieu
- CDC COVID-19 Emergency Response.,U.S. Public Health Service.,Epidemic Intelligence Service, CDC.,Emory University School of Medicine
| | - Christine M Szablewski
- CDC COVID-19 Emergency Response.,U.S. Public Health Service.,Epidemic Intelligence Service, CDC.,Georgia Department of Public Health, Atlanta, Georgia
| | | | | | | | | | | | - James M Blum
- Emory University School of Medicine.,Georgia Clinical & Translational Science Alliance, Atlanta, Georgia
| | | | - David W Wright
- Emory University School of Medicine.,Grady Health System, Atlanta, Georgia
| | | | - Jack D Owens
- Phoebe Putney Memorial Hospital, Albany, Georgia
| | | | - Frank W Brown
- Emory University School of Medicine.,Emory Decatur Hospital, Decatur, Georgia
| | - Deron C Burton
- CDC COVID-19 Emergency Response.,U.S. Public Health Service
| | | | | | - Priti R Patel
- CDC COVID-19 Emergency Response.,U.S. Public Health Service
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5
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Killerby ME, Link-Gelles R, Haight SC, Schrodt CA, England L, Gomes DJ, Shamout M, Pettrone K, O'Laughlin K, Kimball A, Blau EF, Burnett E, Ladva CN, Szablewski CM, Tobin-D'Angelo M, Oosmanally N, Drenzek C, Murphy DJ, Blum JM, Hollberg J, Lefkove B, Brown FW, Shimabukuro T, Midgley CM, Tate JE. Characteristics Associated with Hospitalization Among Patients with COVID-19 - Metropolitan Atlanta, Georgia, March-April 2020. MMWR Morb Mortal Wkly Rep 2020; 69:790-794. [PMID: 32584797 PMCID: PMC7316317 DOI: 10.15585/mmwr.mm6925e1] [Citation(s) in RCA: 250] [Impact Index Per Article: 62.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The first reported U.S. case of coronavirus disease 2019 (COVID-19) was detected in January 2020 (1). As of June 15, 2020, approximately 2 million cases and 115,000 COVID-19-associated deaths have been reported in the United States.* Reports of U.S. patients hospitalized with SARS-CoV-2 infection (the virus that causes COVID-19) describe high proportions of older, male, and black persons (2-4). Similarly, when comparing hospitalized patients with catchment area populations or nonhospitalized COVID-19 patients, high proportions have underlying conditions, including diabetes mellitus, hypertension, obesity, cardiovascular disease, chronic kidney disease, or chronic respiratory disease (3,4). For this report, data were abstracted from the medical records of 220 hospitalized and 311 nonhospitalized patients aged ≥18 years with laboratory-confirmed COVID-19 from six acute care hospitals and associated outpatient clinics in metropolitan Atlanta, Georgia. Multivariable analyses were performed to identify patient characteristics associated with hospitalization. The following characteristics were independently associated with hospitalization: age ≥65 years (adjusted odds ratio [aOR] = 3.4), black race (aOR = 3.2), having diabetes mellitus (aOR = 3.1), lack of insurance (aOR = 2.8), male sex (aOR = 2.4), smoking (aOR = 2.3), and obesity (aOR = 1.9). Infection with SARS-CoV-2 can lead to severe outcomes, including death, and measures to protect persons from infection, such as staying at home, social distancing (5), and awareness and management of underlying conditions should be emphasized for those at highest risk for hospitalization with COVID-19. Measures that prevent the spread of infection to others, such as wearing cloth face coverings (6), should be used whenever possible to protect groups at high risk. Potential barriers to the ability to adhere to these measures need to be addressed.
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6
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Gold JAW, Wong KK, Szablewski CM, Patel PR, Rossow J, da Silva J, Natarajan P, Morris SB, Fanfair RN, Rogers-Brown J, Bruce BB, Browning SD, Hernandez-Romieu AC, Furukawa NW, Kang M, Evans ME, Oosmanally N, Tobin-D'Angelo M, Drenzek C, Murphy DJ, Hollberg J, Blum JM, Jansen R, Wright DW, Sewell WM, Owens JD, Lefkove B, Brown FW, Burton DC, Uyeki TM, Bialek SR, Jackson BR. Characteristics and Clinical Outcomes of Adult Patients Hospitalized with COVID-19 - Georgia, March 2020. MMWR Morb Mortal Wkly Rep 2020; 69:545-550. [PMID: 32379729 PMCID: PMC7737948 DOI: 10.15585/mmwr.mm6918e1] [Citation(s) in RCA: 325] [Impact Index Per Article: 81.3] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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7
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Libby T, Clogher P, Wilson E, Oosmanally N, Boyle M, Eikmeier D, Nicholson C, McGuire S, Cieslak P, Golwalkar M, Geissler A, Vugia D. Disparities in Shigellosis Incidence by Census Tract Poverty, Crowding, and Race/Ethnicity in the United States, FoodNet, 2004-2014. Open Forum Infect Dis 2020; 7:ofaa030. [PMID: 32099844 PMCID: PMC7032626 DOI: 10.1093/ofid/ofaa030] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 01/29/2020] [Indexed: 11/12/2022] Open
Abstract
Background Shigella causes an estimated 500 000 enteric illnesses in the United States annually, but the association with socioeconomic factors is unclear. Methods We examined possible epidemiologic associations between shigellosis and poverty using 2004–2014 Foodborne Diseases Active Surveillance Network (FoodNet) data. Shigella cases (n = 21 246) were geocoded, linked to Census tract data from the American Community Survey, and categorized into 4 poverty and 4 crowding strata. For each stratum, we calculated incidence by sex, age, race/ethnicity, and FoodNet site. Using negative binomial regression, we estimated incidence rate ratios (IRRs) comparing the highest to lowest stratum. Results Annual FoodNet Shigella incidence per 100 000 population was higher among children <5 years old (19.0), blacks (7.2), and Hispanics (5.6) and was associated with Census tract poverty (incidence rate ratio [IRR], 3.6; 95% confidence interval [CI], 3.5–3.8) and household crowding (IRR, 1.8; 95% CI, 1.7–1.9). The association with poverty was strongest among children and persisted regardless of sex, race/ethnicity, or geographic location. After controlling for demographic variables, the association between shigellosis and poverty remained significant (IRR, 2.3; 95% CI, 2.0–2.6). Conclusions In the United States, Shigella infections are epidemiologically associated with poverty, and increased incidence rates are observed among young children, blacks, and Hispanics.
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Affiliation(s)
- Tanya Libby
- California Emerging Infections Program, Oakland, California, USA
| | - Paula Clogher
- Emerging Infections Program, Yale School of Public Health, New Haven, Connecticut, USA
| | - Elisha Wilson
- Emerging Infections Program, Colorado Department of Public Health and Environment, Denver, Colorado, USA
| | | | | | - Dana Eikmeier
- Minnesota Department of Health, St Paul, Minnesota, USA
| | - Cynthia Nicholson
- University of New Mexico Emerging Infections Program, Santa Fe, New Mexico, USA
| | - Suzanne McGuire
- Emerging Infections Program, New York State Department of Health, Albany, New York, USA
| | - Paul Cieslak
- Emerging Infections Program, Oregon Health Authority, Portland, Oregon, USA
| | | | - Aimee Geissler
- Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Duc Vugia
- California Department of Public Health, Richmond, California, USA
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8
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Hadler JL, Clogher P, Libby T, Wilson E, Oosmanally N, Ryan P, Magnuson L, Lathrop S, Mcguire S, Cieslak P, Fankhauser M, Ray L, Geissler A, Hurd S. Relationship Between Census Tract–Level Poverty and Domestically Acquired Salmonella Incidence: Analysis of Foodborne Diseases Active Surveillance Network Data, 2010–2016. J Infect Dis 2019; 222:1405-1412. [DOI: 10.1093/infdis/jiz605] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 11/21/2019] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
The relationships between socioeconomic status and domestically acquired salmonellosis and leading Salmonella serotypes are poorly understood.
Methods
We analyzed surveillance data from laboratory-confirmed cases of salmonellosis from 2010–2016 for all 10 Foodborne Disease Active Surveillance Network (FoodNet) sites, having a catchment population of 47.9 million. Case residential data were geocoded, linked to census tract poverty level, and then categorized into 4 groups according to census tract poverty level. After excluding those reporting international travel before illness onset, age-specific and age-adjusted salmonellosis incidence rates were calculated for each census tract poverty level, overall and for each of the 10 leading serotypes.
Results
Of 52 821geocodable Salmonella infections (>96%), 48 111 (91.1%) were domestically acquired. Higher age-adjusted incidence occurred with higher census tract poverty level (P < .001; relative risk for highest [≥20%] vs lowest [<5%] census tract poverty level, 1.37). Children <5 years old had the highest relative risk (2.07). Although this relationship was consistent by race/ethnicity and by serotype, it was not present in 5 FoodNet sites or among those aged 18–49 years.
Conclusion
Children and older adults living in higher-poverty census tracts have had a higher incidence of domestically acquired salmonellosis. There is a need to understand socioeconomic status differences for risk factors for domestically acquired salmonellosis by age group and FoodNet site to help focus prevention efforts.
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Affiliation(s)
- James L Hadler
- Emerging Infections Program, Yale School of Public Health, New Haven, Connecticut, USA
| | - Paula Clogher
- Emerging Infections Program, Yale School of Public Health, New Haven, Connecticut, USA
| | - Tanya Libby
- California Emerging Infections Program, Oakland, California, USA
| | - Elisha Wilson
- Emerging Infections Program, Colorado Department of Public Health and Environment, Denver, Colorado, USA
| | - Nadine Oosmanally
- Emerging Infections Program, Georgia Department of Public Health, Atlanta, Georgia, USA
| | - Patricia Ryan
- Emerging Infections Program, Maryland Department of Health, Baltimore, Maryland, USA
| | - Luke Magnuson
- Emerging Infections Program, Minnesota Department of Health, St Paul, Minnesota, USA
| | - Sarah Lathrop
- Emerging Infections Program, New Mexico Department of Health, Santa Fe, New Mexico, USA
| | - Suzanne Mcguire
- Emerging Infections Program, New York State Department of Health, Albany, New York, USA
| | - Paul Cieslak
- Emerging Infections Program, Oregon Health Authority, Portland, Oregon, USA
| | - Melissa Fankhauser
- Emerging Infections Program, Tennessee Department of Health, Nashville, Tennessee, USA
| | - Logan Ray
- Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Aimee Geissler
- Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Sharon Hurd
- Emerging Infections Program, Yale School of Public Health, New Haven, Connecticut, USA
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9
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Iwamoto M, Huang JY, Cronquist AB, Medus C, Hurd S, Zansky S, Dunn J, Woron AM, Oosmanally N, Griffin PM, Besser J, Henao OL. Bacterial enteric infections detected by culture-independent diagnostic tests--FoodNet, United States, 2012-2014. MMWR Morb Mortal Wkly Rep 2015; 64:252-7. [PMID: 25763878 PMCID: PMC5779603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
The increased availability and rapid adoption of culture-independent diagnostic tests (CIDTs) is moving clinical detection of bacterial enteric infections away from culture-based methods. These new tests do not yield isolates that are currently needed for further tests to distinguish among strains or subtypes of Salmonella, Campylobacter, Shiga toxin-producing Escherichia coli, and other organisms. Public health surveillance relies on this detailed characterization of isolates to monitor trends and rapidly detect outbreaks; consequently, the increased use of CIDTs makes prevention and control of these infections more difficult. During 2012-2013, the Foodborne Diseases Active Surveillance Network (FoodNet*) identified a total of 38,666 culture-confirmed cases and positive CIDT reports of Campylobacter, Salmonella, Shigella, Shiga toxin-producing E. coli, Vibrio, and Yersinia. Among the 5,614 positive CIDT reports, 2,595 (46%) were not confirmed by culture. In addition, a 2014 survey of clinical laboratories serving the FoodNet surveillance area indicated that use of CIDTs by the laboratories varied by pathogen; only CIDT methods were used most often for detection of Campylobacter (10%) and STEC (19%). Maintaining surveillance of bacterial enteric infections in this period of transition will require enhanced surveillance methods and strategies for obtaining bacterial isolates.
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Affiliation(s)
- Martha Iwamoto
- Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, CDC,Corresponding author: Martha Iwamoto, , 404-639-4745
| | - Jennifer Y. Huang
- Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, CDC
| | | | | | | | | | | | | | | | - Patricia M. Griffin
- Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, CDC
| | - John Besser
- Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, CDC
| | - Olga L. Henao
- Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, CDC
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10
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Ricotta EE, Palmer A, Wymore K, Clogher P, Oosmanally N, Robinson T, Lathrop S, Karr J, Hatch J, Dunn J, Ryan P, Blythe D. Epidemiology and antimicrobial resistance of international travel-associated Campylobacter infections in the United States, 2005-2011. Am J Public Health 2014; 104:e108-14. [PMID: 24832415 DOI: 10.2105/ajph.2013.301867] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
OBJECTIVES The objective of this study was to determine the role international travel plays in US Campylobacter epidemiology and antimicrobial resistance. METHODS In this study, epidemiological and antimicrobial resistance data, encompassing the years 2005 to 2011, from 10 sites participating in the Foodborne Diseases Active Surveillance Network were linked. The 10 sites are represented by 7 states that conducted surveillance on a statewide level, and 3 states which conducted county-level surveillance. Cases of Campylobacter among persons with history of international travel in the week prior to illness were compared with cases among individuals with no international travel. RESULTS Approximately 18% of Campylobacter infections were estimated to be associated with international travel, and 60% of international travel-associated infections had a quinolone-resistant Campylobacter isolate. CONCLUSIONS We confirm that international travel plays a significant role in campylobacteriosis diagnosed in the United States. Recognizing this is important to both medical management decisions and understanding burden and attribution estimates of US campylobacteriosis and antibiotic-resistant campylobacteriosis.
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Affiliation(s)
- Emily E Ricotta
- Emily E. Ricotta, Amanda Palmer, Patricia Ryan, and David Blythe are with the Maryland Department of Health and Mental Hygiene, Baltimore. Katie Wymore is with Public Health Foundation Enterprises, Oakland, CA. Paula Clogher is with the Yale School of Public Health, New Haven, CT. Nadine Oosmanally is with the Georgia Department of Public Health, Atlanta. Trisha Robinson is with the Minnesota Department of Health, St. Paul. Sarah Lathrop is with the University of New Mexico, Alburquerque. Jillian Karr is with the New York State Department of Health, Rochester. Julie Hatch is with the Oregon Health Authority, Public Health Division, Portland. John Dunn is with the Tennessee Department of Health, Nashville
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11
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Oosmanally N, Paul JE, Zanation AM, Ewend MG, Senior BA, Ebert CS. Comparative analysis of cost of endoscopic endonasal minimally invasive and sublabial-transseptal approaches to the pituitary. Int Forum Allergy Rhinol 2011; 1:242-9. [PMID: 22287427 DOI: 10.1002/alr.20048] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2010] [Revised: 12/09/2010] [Accepted: 01/04/2011] [Indexed: 11/10/2022]
Abstract
BACKGROUND Two surgical approaches to the pituitary are commonly used: the sublabial-transseptal (SLTS) approach using microscopy and the endonasal endoscopic minimally invasive (MIPS) approach. Although outcomes are similar for both procedures, MIPS has become increasingly prevalent over the last 15 years. Limited cost analysis data comparing the 2 alternatives are available. METHODS A retrospective analysis of cost and volume data was performed using data from the published literature and University of North Carolina at Chapel Hill (UNC) Hospitals. A sensitivity analysis of the parameters was used to evaluate the uncertainty in parameter estimates. RESULTS The total cost in real dollars ranges from $11,438 to $12,513 and $18,095 to $21,005 per patient per procedure for MIPS and SLTS, respectively, with a cost difference ranging between $5582 and $9567 per patient per procedure. The sensitivity analysis indicates that the total cost for MIPS is most sensitive to: (1) average length of stay, (2) nursing costs, and (3) number of total complications, whereas the total cost for SLTS is most sensitive to: (1) average length of stay, (2) nursing cost, and (3) operating time. MIPS is less costly than SLTS between 94% and 98% of the time. CONCLUSION The results indicate that MIPS is less costly than SLTS at a large academic center. Future research should compare the outcomes and quality of life (QoL) associated with the 2 surgeries to improve the data used to determine the cost-effectiveness of MIPS compared to SLTS.
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Affiliation(s)
- Nadine Oosmanally
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
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