Document text
Principal Investigator: Julia Johnson
Organization: JOHNS HOPKINS UNIVERSITY
Fiscal Year: 2024
Award: $171,720
Funding agency: Eunice Kennedy Shriver National Institute of Child Health and Human Development
Project Summary/Abstract
Annually, 2.5 million babies die within the first four weeks of life, nearly a quarter due to infectious causes.
Newborns admitted to the Neonatal Intensive Care Unit (NICU) are especially vulnerable, due to such factors as
prematurity, an immature immune system, and need for life-sustaining invasive procedures and devices. In low
and middle income countries (LMIC), an increasing number of NICUs care for premature and critically ill
newborns. Healthcare-associated bloodstream infections (HA-BSI) in LMIC are more common due to inadequate
infection prevention and control (IPC) and more difficult to treat due to high rates of antimicrobial resistance
(AMR). Previous research in this setting focuses primarily on outbreak investigations and does not adequately
describe risk factors for HA-BSI. Healthcare facilities lack effective tools to assess maternal and neonatal IPC
and create improvement strategies. Preliminary data from the applicant's ongoing prospective cohort study that
has enrolled over 6600 neonates in three NICUs in Pune, India, reinforces the high incidence of HA-BSI in this
setting with a rate of 7.6 per 1000 patient-days, as well as high rates of AMR. Among Klebsiella pneumoniae
isolates, the most common BSI pathogen, 96% are resistant to third-generation cephalosporins and 38% to
carbapenems. Among neonates with BSI, mortality is 22%. Within the framework of this study, the following are
proposed: (1) To identify modifiable risk factors for HA-BSI in the NICU; (2) To develop a model for predicting
infection with carbapenem-resistant organisms (CRO); and (3) To develop and pilot a novel tool to assess IPC
practices in the NICU and Labor & Delivery. Identifying risk factors for HA-BSI in the NICU will promote
development of targeted IPC strategies. Creation of a prediction model using a decision tree algorithm will help
identify babies at highest risk of CRO infections. Such a model can support NICU clinicians in selecting the right
antibiotics when infection is suspected, reducing time to appropriate therapy and decreasing unnecessary use
of last resort antibiotics such as colistin. Development of an IPC assessment tool that incorporates human factors
engineering (HFE) principles will enable healthcare facilities to optimize IPC and reduce risk of hospital-acquired
infections and associated mortality. This mentored research will train the applicant in advanced epidemiologic
methods and application of IPC in LMIC. The applicant is a neonatologist at Johns Hopkins University committed
to patient-oriented research in resource-limited settings. Her long-term goals are to become a leader in neonatal
IPC in low resource settings and devise interventions to reduce global burden of HA-BSI and associated
mortality. This K23 will facilitate skill development in longitudinal data analysis, prediction models, survey
development, HFE, and qualitative data analysis. Training will include formal coursework, supervised data
analysis, and mentorship by a team with expertise in infectious diseases, IPC, biostatistics, epidemiology, patient
safety, and HFE. Collectively, the activities of this K23 will provide a pathway to an independent career as a
clinical investigator with expertise in healthcare epidemiology and IPC in low resource settings.
Terms: <0-4 weeks old><Address><Admission><Admission activity><Algorithms><Antibiotic Agents><Antibiotic Drugs><Antibiotic Resistance><Antibiotics><Antimicrobial Resistance><Assessment instrument><Assessment tool><Bacteria resistance><Bacteria resistant><Bacterial Infections><Bacterial resistant><Biometrics><Biometry><Biostatistics><Birth><Blood><Blood Reticuloendothelial System><Carbapenems><Caring><Cephalosporins><Characteristics><Clinical><Clinical Investigator><Cohort Studies><Colimycin><Colisticin><Colistin><Communicable Diseases><Communities><Concurrent Studies><Data><Data Analyses><Data Analysis><Death Rate><Decision Making><Decision Trees><Development><Devices><Disease Outbreaks><Engineering><Enrollment><Epidemiologic Methods><Epidemiological Methods><Epidemiological Techniques><Epidemiology><Future><Generations><Goals><Gram-Negative Bacteria><Hand><Health Facilities><Health care facility><Healthcare><Healthcare Facility><Hospital Admission><Hospital Infections><Hospital acquired infection><Hospitalization><Human><Hygiene><Immune system><Incidence><India><Infection><Infection Control><Infection prevention><Infectious Disease Pathway><Infectious Diseases><Infectious Disorder><Intensive Care><Intervention><Intervention Strategies><Investigation><Investigators><K pneumoniae><K. pneumoniae><Klebsiella pneumoniae><LMIC><Length of Stay><Life><Low-resource area><Low-resource community><Low-resource environment><Low-resource region><Low-resource setting><Measures><Mechanical ventilation><Mentors><Mentorship><Methodology><Methods><Methods Epidemiology><Miscellaneous Antibiotic><Modeling><Modern Man><Morbidity><Morbidity - disease rate><Neonatal><Neonatal Intensive Care Units><Neonatal Mortality><Newborn Infant><Newborn Intensive Care Units><Newborns><Nosocomial Infections><Number of Days in Hospital><Organism><Outbreaks><Parturition><Pathway interactions><Patients><Pneumonia><Polymyxin E><Position><Positioning Attribute><Prevalence><Prevent infection><Principal Investigator><Procedures><Prospective cohort><Prospective, cohort study><Recommendation><Rectum><Research><Research Personnel><Researchers><Resistance><Resistance to antibiotics><Resistance to infection><Resistant to antibiotics><Resource-constrained area><Resource-constrained community><Resource-constrained environment><Resource-constrained region><Resource-constrained setting><Resource-limited area><Resource-limited community><Resource-limited environment><Resource-limited region><Resource-limited setting><Resource-poor area><Resource-poor community><Resource-poor environment><Resource-poor region><Resource-poor setting><Risk Factors><Risk Reduction><Sepsis><Site><Survey Instrument><Surveys><Testing><Time><Training><Universities><Work><anti-microbial resistant><antibiotic drug resistance><antibiotic resistant><antibiotic resistant infections><bacteria infection><bacterial disease><bacterial resistance><biobank><biorepository><blood infection><bloodstream infection><carbapenem resistance><carbapenem resistant><care facilities><career><classification trees><clinical investigation><cohort><computer based prediction><critically ill newborn><data interpretation><death among neonates><death among newborns><death in neonates><death in newborn><developmental><enroll><epidemiologic><epidemiological><hands><health care><health care model><health care-associated infections><healthcare burden><healthcare model><healthcare-associated infections><high risk><hospital care><hospital days><hospital length of stay><hospital stay><improved><improved outcome><infected neonate><infected newborn><infection resistance><infection risk><institutional infection><interventional strategy><living system><low and middle-income countries><machine learning based model><machine learning model><malleable risk><mechanical respiratory assist><mechanically ventilated><modifiable risk><mortality><mortality among neonates><mortality among newborns><mortality in neonates><mortality in newborns><mortality rate><mortality ratio><neonatal ICU><neonatal care><neonatal death><neonatal demise><neonatal health><neonatal infection><neonatal sepsis><neonate><newborn child><newborn children><newborn death><newborn health><newborn infection><newborn mortality><novel><pathogen><pathway><patient oriented research><patient oriented study><patient safety><predictive modeling><premature><prematurity><prevent><preventing><prospective><reduce risk><reduce risks><reduce that risk><reduce the risk><reduce these risks><reduces risk><reduces the risk><reducing risk><reducing the risk><regression trees><resistance to Bacteria><resistance to Bacterial><resistance to anti-microbial><resistance to carbapenem><resistant><resistant to Bacteria><resistant to Bacterial><resistant to antimicrobial><resistant to carbapenem><risk-reducing><skill acquisition><skill development><skills><tertiary care><tool><treatment strategy>