Accepted Manuscript Analysing risk factors for urinary tract infection based on automated monitoring of hospital-acquired infection J.D. Redder, R.A. Leth, J.K. Møller PII:
S0195-6701(15)00523-X
DOI:
10.1016/j.jhin.2015.12.009
Reference:
YJHIN 4707
To appear in:
Journal of Hospital Infection
Received Date: 13 August 2015 Accepted Date: 8 December 2015
Please cite this article as: Redder JD, Leth RA, Møller JK, Analysing risk factors for urinary tract infection based on automated monitoring of hospital-acquired infection, Journal of Hospital Infection (2016), doi: 10.1016/j.jhin.2015.12.009. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
J.D. Redder et al. Short report
Analysing risk factors for urinary tract infection based on automated monitoring of hospital-acquired infection J.D. Reddera,b,*, R.A. Lethc, J.K. Møllera,b Department of Clinical Microbiology, Lillebaelt Hospital, Vejle, Denmark
b c
Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
RI PT
a
Department of Clinical Microbiology, Aarhus University Hospital, Aarhus, Denmark
____________________ *
Corresponding author. Address: Department of Clinical Microbiology, Vejle Hospital,
E-mail address: [email protected] (J.D. Redder).
M AN U
SUMMARY
SC
Kabbeltoft 25, DK-7100 Vejle, Denmark. Tel.: +45 7940 6526.
Urinary tract infections account for as much as one-third of all nosocomial infections. The aim of this study was to examine previously reported characteristics of patients with hospitalacquired urinary tract infections (HA-UTI) using an automated infection monitoring system (Hospital-Acquired Infection Registry: HAIR). A matched case‒control study was conducted to investigate the association of risk factors with HA-UTI. Patients with HA-UTI more
TE D
frequently had indwelling urinary catheters or a disease in the genitourinary or nervous system than the controls. Automated hospital-acquired infection monitoring enables documentation of key risk factors to better evaluate infection control interventions in general or for selected groups of patients.
EP
Keywords:
Automated monitoring
AC C
Hospital-acquired infection Risk factors
Urinary tract infection Introduction
Use of an indwelling urinary catheter (IUC) is the most well-known risk factor
for urinary tract infection (UTI) and is estimated to account for ~80% of all hospital-acquired (HA)-UTIs.1 Diabetes mellitus, advanced age, urinary tract obstructions, immunosuppression, and neurological disorders are also known risk factors associated with UTI.2‒6 We have recently evaluated a hospital-wide automated hospital-acquired infection (HAI) monitoring system (HAIR; Hospital-Acquired Infection Registry) at a Danish Hospital trust.7 Automated monitoring of HAI addresses the disadvantages of manual HAI Page 1 of 8
ACCEPTED MANUSCRIPT
surveillance and may also be used to investigate HAI risk factors to assist in reducing the burden of HA-UTI by targeted infection control measures.8 The aim of the present study was to provide ‘proof-of-concept’ data by identifying previously reported and well-known characteristics of patients with HA-UTI on a large sample of hospitalized patients within the framework of HAIR. Methods
RI PT
Study design, setting and population
A matched case‒control study was performed at Lillebaelt Hospital, a regional hospital trust in the Region of Southern Denmark. The source population was all patients admitted to Lillebaelt Hospital (N = 285,215 admissions) between January 2010 and
SC
December 2014. Study definitions
Cases were defined as patients who were classified by HAIR as having HA-
M AN U
UTI.7 Reinfection of the urinary tract with a new pathogen during the admission was included as a new HA-UTI case. The controls were patients who did not acquire UTI during admission. A total of 5966 cases and 279,249 controls were eligible for the study. Cases and controls were randomly matched 1:2 by belonging to the same five-year age group, sex, medical specialty, admission quarter and year, and time-to-infection (time from admission to culture
TE D
for the case). The length of hospital stay for controls had to be at least as long as the time-toinfection for the matched cases. Patients were excluded if the admission lasted
S0195-6701(15)00523-X
DOI:
10.1016/j.jhin.2015.12.009
Reference:
YJHIN 4707
To appear in:
Journal of Hospital Infection
Received Date: 13 August 2015 Accepted Date: 8 December 2015
Please cite this article as: Redder JD, Leth RA, Møller JK, Analysing risk factors for urinary tract infection based on automated monitoring of hospital-acquired infection, Journal of Hospital Infection (2016), doi: 10.1016/j.jhin.2015.12.009. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
J.D. Redder et al. Short report
Analysing risk factors for urinary tract infection based on automated monitoring of hospital-acquired infection J.D. Reddera,b,*, R.A. Lethc, J.K. Møllera,b Department of Clinical Microbiology, Lillebaelt Hospital, Vejle, Denmark
b c
Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
RI PT
a
Department of Clinical Microbiology, Aarhus University Hospital, Aarhus, Denmark
____________________ *
Corresponding author. Address: Department of Clinical Microbiology, Vejle Hospital,
E-mail address: [email protected] (J.D. Redder).
M AN U
SUMMARY
SC
Kabbeltoft 25, DK-7100 Vejle, Denmark. Tel.: +45 7940 6526.
Urinary tract infections account for as much as one-third of all nosocomial infections. The aim of this study was to examine previously reported characteristics of patients with hospitalacquired urinary tract infections (HA-UTI) using an automated infection monitoring system (Hospital-Acquired Infection Registry: HAIR). A matched case‒control study was conducted to investigate the association of risk factors with HA-UTI. Patients with HA-UTI more
TE D
frequently had indwelling urinary catheters or a disease in the genitourinary or nervous system than the controls. Automated hospital-acquired infection monitoring enables documentation of key risk factors to better evaluate infection control interventions in general or for selected groups of patients.
EP
Keywords:
Automated monitoring
AC C
Hospital-acquired infection Risk factors
Urinary tract infection Introduction
Use of an indwelling urinary catheter (IUC) is the most well-known risk factor
for urinary tract infection (UTI) and is estimated to account for ~80% of all hospital-acquired (HA)-UTIs.1 Diabetes mellitus, advanced age, urinary tract obstructions, immunosuppression, and neurological disorders are also known risk factors associated with UTI.2‒6 We have recently evaluated a hospital-wide automated hospital-acquired infection (HAI) monitoring system (HAIR; Hospital-Acquired Infection Registry) at a Danish Hospital trust.7 Automated monitoring of HAI addresses the disadvantages of manual HAI Page 1 of 8
ACCEPTED MANUSCRIPT
surveillance and may also be used to investigate HAI risk factors to assist in reducing the burden of HA-UTI by targeted infection control measures.8 The aim of the present study was to provide ‘proof-of-concept’ data by identifying previously reported and well-known characteristics of patients with HA-UTI on a large sample of hospitalized patients within the framework of HAIR. Methods
RI PT
Study design, setting and population
A matched case‒control study was performed at Lillebaelt Hospital, a regional hospital trust in the Region of Southern Denmark. The source population was all patients admitted to Lillebaelt Hospital (N = 285,215 admissions) between January 2010 and
SC
December 2014. Study definitions
Cases were defined as patients who were classified by HAIR as having HA-
M AN U
UTI.7 Reinfection of the urinary tract with a new pathogen during the admission was included as a new HA-UTI case. The controls were patients who did not acquire UTI during admission. A total of 5966 cases and 279,249 controls were eligible for the study. Cases and controls were randomly matched 1:2 by belonging to the same five-year age group, sex, medical specialty, admission quarter and year, and time-to-infection (time from admission to culture
TE D
for the case). The length of hospital stay for controls had to be at least as long as the time-toinfection for the matched cases. Patients were excluded if the admission lasted
