Author
Kathy Angeles
Bio: Kathy Angeles is an academic researcher from University of New Mexico. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 3, co-authored 3 publications receiving 355 citations.
Topics: Population, Medicine, Pneumonia, Confidence interval, Diabetes mellitus
Papers
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National Center for Immunization and Respiratory Diseases1, Vanderbilt University2, Emory University3, Colorado Department of Public Health and Environment4, New York State Department of Health5, California Department of Public Health6, Oregon Health Authority7, University of New Mexico8, Johns Hopkins University9
TL;DR: The burden of invasive GAS infection in the United States remains substantial and vaccines under development could have a considerable public health impact.
Abstract: BACKGROUND Invasive group A Streptococcus (GAS) infections are associated with significant morbidity and mortality rates. We report the epidemiology and trends of invasive GAS over 8 years of surveillance. METHODS From January 2005 through December 2012, we collected data from the Centers for Disease Control and Prevention's Active Bacterial Core surveillance, a population-based network of 10 geographically diverse US sites (2012 population, 32.8 million). We defined invasive GAS as isolation of GAS from a normally sterile site or from a wound in a patient with necrotizing fasciitis (NF) or streptococcal toxic shock syndrome (STSS). Available isolates were emm typed. We calculated rates and made age- and race-adjusted national projections using census data. RESULTS We identified 9557 cases (3.8 cases per 100 000 persons per year) with 1116 deaths (case-fatality rate, 11.7%). The case-fatality rates for septic shock, STSS, and NF were 45%, 38%, and 29%, respectively. The annual incidence was highest among persons aged ≥65 years (9.4/100 000) or <1 year (5.3) and among blacks (4.7/100 000). National rates remained steady over 8 years of surveillance. Factors independently associated with death included increasing age, residence in a nursing home, recent surgery, septic shock, NF, meningitis, isolated bacteremia, pneumonia, emm type 1 or 3, and underlying chronic illness or immunosuppression. An estimated 10 649-13 434 cases of invasive GAS infections occur in the United States annually, resulting in 1136-1607 deaths. In a 30-valent M-protein vaccine, emm types accounted for 91% of isolates. CONCLUSIONS The burden of invasive GAS infection in the United States remains substantial. Vaccines under development could have a considerable public health impact.
258 citations
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TL;DR: WGS-based antimicrobial phenotype prediction was an informative alternative to BDT for invasive pneumococci and correctly predicted penicillin-binding protein types and common resistance determinants.
111 citations
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TL;DR: The WGS-based assignment of iGBS resistance features and serotypes is an accurate substitute for phenotypic testing.
100 citations
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TL;DR: Older adults with DM have higher rates of severe influenza-associated outcomes compared to those without DM, reinforcing the importance of preventing influenza virus infections through annual vaccination, and early treatment of influenza illness with antivirals in older adults withDM.
Abstract: Background
Diabetes mellitus (DM) is common among older adults hospitalized with influenza, yet data are limited on the impact of DM on risk of severe influenza-associated outcomes.
Methods
We included adults aged ≥65 years hospitalized with influenza during 2012-2013 through 2016-2017 from the Influenza Hospitalization Surveillance Network (FluSurv-NET), a population-based surveillance system for laboratory-confirmed influenza-associated hospitalizations conducted in defined counties within 13 states. We calculated population denominators using the Centers for Medicare and Medicaid Services county-specific DM prevalence estimates and National Center for Health Statistics population data. We present pooled rates and rate ratios (RRs) of intensive care unit (ICU) admission, pneumonia diagnosis, mechanical ventilation, and in-hospital death for persons with and without DM. We estimated RRs and 95% confidence intervals (CIs) using meta-analysis with site as a random effect in order to control for site differences in the estimates.
Results
Of 31 934 hospitalized adults included in the analysis, 34% had DM. Compared to those without DM, adults with DM had higher rates of influenza-associated hospitalization (RR, 1.57 [95% CI, 1.43-1.72]), ICU admission (RR, 1.84 [95% CI, 1.67-2.04]), pneumonia (RR, 1.57 [95% CI, 1.42-1.73]), mechanical ventilation (RR, 1.95 [95% CI, 1.74-2.20]), and in-hospital death (RR, 1.48 [95% CI, 1.23-1.80]).
Conclusions
Older adults with DM have higher rates of severe influenza-associated outcomes compared to those without DM. These findings reinforce the importance of preventing influenza virus infections through annual vaccination, and early treatment of influenza illness with antivirals in older adults with DM.
5 citations
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TL;DR: Older adults with DM have higher rates of severe influenza-associated outcomes compared to those without DM, which reinforces the importance of preventing influenza virus infections through annual vaccination, and early treatment of influenza illness with antivirals in older adults withDM.
Abstract:
Diabetes mellitus (DM) is common among older adults hospitalized with influenza, yet data are limited on the impact of DM on risk of severe influenza-associated outcomes.
We included adults aged ≥65 years hospitalized with influenza during 2012–13 through 2016–17 from the Influenza Hospitalization Surveillance Network (FluSurv-NET), a population-based surveillance system for laboratory-confirmed influenza-associated hospitalizations conducted in defined counties within 13 states. We calculated population denominators using the Centers for Medicare and Medicaid Services county-specific DM prevalence estimates and National Center for Health Statistics population data. We present pooled rates and rate ratios (RR) of intensive care unit (ICU) admission, pneumonia diagnosis, mechanical ventilation, and in-hospital death for persons with and without DM. We estimated RR and 95% confidence intervals (95%CI) using meta-analysis with site as a random effect in order to control for site differences in the estimates.
Of 31,934 hospitalized adults included in the analysis, 34% had DM. Compared to those without DM, adults with DM had higher rates of influenza-associated hospitalization (RR: 1.57; 95% CI: 1.43–1.72), ICU admission (RR: 1.84; 95% CI: 1.67–2.04), pneumonia (RR: 1.57; 95% CI: 1.42–1.73), mechanical ventilation (RR: 1.95; 95% CI: 1.74–2.20), and in-hospital death (RR: 1.48; 95% CI: 1.23–1.80).
Older adults with DM have higher rates of severe influenza-associated outcomes compared to those without DM. These findings reinforce the importance of preventing influenza virus infections through annual vaccination, and early treatment of influenza illness with antivirals in older adults with DM.
4 citations
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TL;DR: The hallmarks of necrotizing fasciitis are friable superficial fascia, gray exudate without pus, and widespread tissue destruction.
Abstract: The hallmarks of necrotizing fasciitis are friable superficial fascia, gray exudate without pus, and widespread tissue destruction. The infection is either polymicrobial or monomicrobial. Early surgical debridement and appropriate antibiotics are crucial for recovery.
373 citations
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TL;DR: Combined with addressing IAP implementation gaps, an effective vaccine covering the most common serotypes might further reduce EOD rates and help prevent LOD, for which there is no current public health intervention.
Abstract: Importance Invasive disease owing to group BStreptococcus(GBS) remains an important cause of illness and death among infants younger than 90 days in the United States, despite declines in early-onset disease (EOD; with onset at 0-6 days of life) that are attributed to intrapartum antibiotic prophylaxis (IAP). Maternal vaccines to prevent infant GBS disease are currently under development. Objective To describe incidence rates, case characteristics, antimicrobial resistance, and serotype distribution of EOD and late-onset disease (LOD; with onset at 7-89 days of life) in the United States from 2006 to 2015 to inform IAP guidelines and vaccine development. Design, Setting, and Participants This study used active population-based and laboratory-based surveillance for invasive GBS disease conducted through Active Bacterial Core surveillance in selected counties of 10 states across the United States. Residents of Active Bacterial Core surveillance areas who were younger than 90 days and had invasive GBS disease in 2006 to 2015 were included. Data were analyzed from December 2017 to April 2018. Exposures Group BStreptococcusisolated from a normally sterile site. Main Outcomes and Measures Early-onset disease and LOD incidence rates and associated GBS serotypes and antimicrobial resistance. Results The Active Bacterial Core surveillance program identified 1277 cases of EOD and 1387 cases of LOD. From 2006 to 2015, EOD incidence declined significantly from 0.37 to 0.23 per 1000 live births (P Conclusions and Relevance The rates of LOD among US infants are now higher than EOD rates. Combined with addressing IAP implementation gaps, an effective vaccine covering the most common serotypes might further reduce EOD rates and help prevent LOD, for which there is no current public health intervention.
205 citations
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TL;DR: A collection of 5,278 nontyphoidal Salmonella genomes was used to generate extreme gradient boosting (XGBoost)-based machine learning models for predicting MICs for 15 antibiotics, showing that highly accurate MIC prediction models can be generated with less than 500 genomes.
Abstract: Nontyphoidal Salmonella species are the leading bacterial cause of foodborne disease in the United States. Whole-genome sequences and paired antimicrobial susceptibility data are available for Salmonella strains because of surveillance efforts from public health agencies. In this study, a collection of 5,278 nontyphoidal Salmonella genomes, collected over 15 years in the United States, was used to generate extreme gradient boosting (XGBoost)-based machine learning models for predicting MICs for 15 antibiotics. The MIC prediction models had an overall average accuracy of 95% within ±1 2-fold dilution step (confidence interval, 95% to 95%), an average very major error rate of 2.7% (confidence interval, 2.4% to 3.0%), and an average major error rate of 0.1% (confidence interval, 0.1% to 0.2%). The model predicted MICs with no a priori information about the underlying gene content or resistance phenotypes of the strains. By selecting diverse genomes for the training sets, we show that highly accurate MIC prediction models can be generated with less than 500 genomes. We also show that our approach for predicting MICs is stable over time, despite annual fluctuations in antimicrobial resistance gene content in the sampled genomes. Finally, using feature selection, we explore the important genomic regions identified by the models for predicting MICs. To date, this is one of the largest MIC modeling studies to be published. Our strategy for developing whole-genome sequence-based models for surveillance and clinical diagnostics can be readily applied to other important human pathogens.
168 citations
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TL;DR: A WGS-based MIC prediction approach that allows reliable MIC prediction for five gonorrhoea antimicrobials is demonstrated and should allow reasonably precise prediction of MICs for a range of bacterial species.
Abstract: Background: Tracking the spread of antimicrobial-resistant Neisseria gonorrhoeae is a major priority for national surveillance programmes. / Objectives: We investigate whether WGS and simultaneous analysis of multiple resistance determinants can be used to predict antimicrobial susceptibilities to the level of MICs in N. gonorrhoeae. / Methods: WGS was used to identify previously reported potential resistance determinants in 681 N. gonorrhoeae isolates, from England, the USA and Canada, with phenotypes for cefixime, penicillin, azithromycin, ciprofloxacin and tetracycline determined as part of national surveillance programmes. Multivariate linear regression models were used to identify genetic predictors of MIC. Model performance was assessed using leave-one-out cross-validation. / Results: Overall 1785/3380 (53%) MIC values were predicted to the nearest doubling dilution and 3147 (93%) within ±1 doubling dilution and 3314 (98%) within ±2 doubling dilutions. MIC prediction performance was similar across the five antimicrobials tested. Prediction models included the majority of previously reported resistance determinants. Applying EUCAST breakpoints to MIC predictions, the overall very major error (VME; phenotypically resistant, WGS-prediction susceptible) rate was 21/1577 (1.3%, 95% CI 0.8%–2.0%) and the major error (ME; phenotypically susceptible, WGS-prediction resistant) rate was 20/1186 (1.7%, 1.0%–2.6%). VME rates met regulatory thresholds for all antimicrobials except cefixime and ME rates for all antimicrobials except tetracycline. Country of testing was a strongly significant predictor of MIC for all five antimicrobials. / Conclusions: We demonstrate a WGS-based MIC prediction approach that allows reliable MIC prediction for five gonorrhoea antimicrobials. Our approach should allow reasonably precise prediction of MICs for a range of bacterial species.
162 citations
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TL;DR: The Summary of Notifiable Infectious Diseases and Conditions - United States, 2015 (hereafter referred to as the summary) contains the official statistics, in tabular and graphical form, for the reported occurrence of nationally notifiable infectious diseases and conditions in the United States for 2015.
Abstract: The Summary of Notifiable Infectious Diseases and Conditions - United States, 2015 (hereafter referred to as the summary) contains the official statistics, in tabular and graphical form, for the reported occurrence of nationally notifiable infectious diseases and conditions in the United States for 2015. Unless otherwise noted, data are final totals for 2015 reported as of June 30, 2016. These statistics are collected and compiled from reports sent by U.S. state and territories, New York City, and District of Columbia health departments to the National Notifiable Diseases Surveillance System (NNDSS), which is operated by CDC in collaboration with the Council of State and Territorial Epidemiologists (CSTE). This summary is available at https://www.cdc.gov/MMWR/MMWR_nd/index.html. This site also includes summary publications from previous years.
155 citations