scholarly journals Development of risk prediction models to predict urine culture growth for patients with suspected urinary tract infection in the emergency department: protocol for an electronic health record study from a single UK hospital

2020 ◽  
Author(s):  
Patrick Rockenschaub ◽  
Martin J Gill ◽  
David McNulty ◽  
Orlagh Carroll ◽  
Nick Freemantle ◽  
...  
Keyword(s):  
Emergency Department ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Hospital Admission ◽  
Risk Prediction ◽  
Antibiotic Treatment ◽  
Prediction Models ◽  
Risk Prediction Models ◽  
Electronic Health

Abstract Background: Urinary tract infection (UTI) is a leading cause of hospital admissions and is diagnosed based on urinary symptoms and microbiological cultures. Due to lags in the availability of culture results of up to 72 hours, and the limitations of routine diagnostics, many patients with suspected UTI are started on antibiotic treatment unnecessarily. Predictive models based on routinely collected clinical information may help clinicians to rule out a diagnosis of bacterial UTI in low-risk patients shortly after hospital admission, providing additional evidence to guide antibiotic treatment decisions.Methods: Using electronic hospital records from Queen Elizabeth Hospital Birmingham (QEHB) collected between 2011 and 2017, we aim to develop a series of models that estimates the probability of bacterial UTI at presentation in the emergency department (ED) among individuals with suspected urinary tract infection syndromes. Predictions will be made during ED attendance and at different time points after hospital admission to assess whether predictive performance may be improved over time as more information becomes available about patient status. All models will be externally validated for expected future performance using QEHB data from 2018/19.Discussion: Risk prediction models using electronic health records offer a new approach to improve antibiotic prescribing decisions, integrating clinical and demographic data with test results to stratify patients according to their probability of bacterial infection. Used in conjunction with expert opinion, they may help clinicians to identify patients that benefit the most from early antibiotic cessation.

scholarly journals Development of risk prediction models to predict urine culture growth for adults with suspected urinary tract infection in the emergency department: protocol for an electronic health record study from a single UK university hospital

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Patrick Rockenschaub ◽  
Martin J. Gill ◽  
David McNulty ◽  
Orlagh Carroll ◽  
Nick Freemantle ◽  
...  
Keyword(s):  
Emergency Department ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Hospital Admission ◽  
Risk Prediction ◽  
Antibiotic Treatment ◽  
Prediction Models ◽  
Risk Prediction Models ◽  
Electronic Health

Abstract Background Urinary tract infection (UTI) is a leading cause of hospital admissions and is diagnosed based on urinary symptoms and microbiological cultures. Due to lags in the availability of culture results of up to 72 h, and the limitations of routine diagnostics, many patients with suspected UTI are started on antibiotic treatment unnecessarily. Predictive models based on routinely collected clinical information may help clinicians to rule out a diagnosis of bacterial UTI in low-risk patients shortly after hospital admission, providing additional evidence to guide antibiotic treatment decisions. Methods Using electronic hospital records from Queen Elizabeth Hospital Birmingham (QEHB) collected between 2011 and 2017, we aim to develop a series of models that estimate the probability of bacterial UTI at presentation in the emergency department (ED) among individuals with suspected UTI syndromes. Predictions will be made during ED attendance and at different time points after hospital admission to assess whether predictive performance may be improved over time as more information becomes available about patient status. All models will be externally validated for expected future performance using QEHB data from 2018/2019. Discussion Risk prediction models using electronic health records offer a new approach to improve antibiotic prescribing decisions, integrating clinical and demographic data with test results to stratify patients according to their probability of bacterial infection. Used in conjunction with expert opinion, they may help clinicians to identify patients that benefit the most from early antibiotic cessation.

scholarly journals Development of risk prediction models to predict urine culture growth for adults with suspected urinary tract infection in the emergency department: protocol for an electronic health record study from a single UK university hospital

2020 ◽  
Author(s):  
Patrick Rockenschaub ◽  
Martin J Gill ◽  
David McNulty ◽  
Orlagh Carroll ◽  
Nick Freemantle ◽  
...  
Keyword(s):  
Emergency Department ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Hospital Admission ◽  
Risk Prediction ◽  
Antibiotic Treatment ◽  
Prediction Models ◽  
Risk Prediction Models ◽  
Electronic Health

Abstract Background:Urinary tract infection (UTI) is a leading cause of hospital admissions and is diagnosed based on urinary symptoms and microbiological cultures. Due to lags in the availability of culture results of up to 72 hours, and the limitations of routine diagnostics, many patients with suspected UTI are started on antibiotic treatment unnecessarily. Predictive models based on routinely collected clinical information may help clinicians to rule out a diagnosis of bacterial UTI in low-risk patients shortly after hospital admission, providing additional evidence to guide antibiotic treatment decisions.Methods:Using electronic hospital records from Queen Elizabeth Hospital Birmingham (QEHB) collected between 2011 and 2017, we aim to develop a series of models that estimates the probability of bacterial UTI at presentation in the emergency department (ED) among individuals with suspected UTI syndromes. Predictions will be made during ED attendance and at different time points after hospital admission to assess whether predictive performance may be improved over time as more information becomes available about patient status. All models will be externally validated for expected future performance using QEHB data from 2018/19. Discussion:Risk prediction models using electronic health records offer a new approach to improve antibiotic prescribing decisions, integrating clinical and demographic data with test results to stratify patients according to their probability of bacterial infection. Used in conjunction with expert opinion, they may help clinicians to identify patients that benefit the most from early antibiotic cessation.

scholarly journals Development of risk prediction models to predict urine culture growth for adults with suspected urinary tract infection in the emergency department: protocol for an electronic health record study from a single UK university hospital

2020 ◽  
Author(s):  
Patrick Rockenschaub ◽  
Martin J Gill ◽  
David McNulty ◽  
Orlagh Carroll ◽  
Nick Freemantle ◽  
...  
Keyword(s):  
Emergency Department ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Hospital Admission ◽  
Risk Prediction ◽  
Antibiotic Treatment ◽  
Prediction Models ◽  
Risk Prediction Models ◽  
Electronic Health

Abstract Background: Urinary tract infection (UTI) is a leading cause of hospital admissions and is diagnosed based on urinary symptoms and microbiological cultures. Due to lags in the availability of culture results of up to 72 hours, and the limitations of routine diagnostics, many patients with suspected UTI are started on antibiotic treatment unnecessarily. Predictive models based on routinely collected clinical information may help clinicians to rule out a diagnosis of bacterial UTI in low-risk patients shortly after hospital admission, providing additional evidence to guide antibiotic treatment decisions.Methods: Using electronic hospital records from Queen Elizabeth Hospital Birmingham (QEHB) collected between 2011 and 2017, we aim to develop a series of models that estimates the probability of bacterial UTI at presentation in the emergency department (ED) among individuals with suspected UTI syndromes. Predictions will be made during ED attendance and at different time points after hospital admission to assess whether predictive performance may be improved over time as more information becomes available about patient status. All models will be externally validated for expected future performance using QEHB data from 2018/19. Discussion: Risk prediction models using electronic health records offer a new approach to improve antibiotic prescribing decisions, integrating clinical and demographic data with test results to stratify patients according to their probability of bacterial infection. Used in conjunction with expert opinion, they may help clinicians to identify patients that benefit the most from early antibiotic cessation.

scholarly journals Is stratification of antibiotic susceptibility of urinary pathogens useful in the Emergency Department?

2020 ◽  
Vol 33 (5) ◽  
pp. 379-382
Author(s):  
Yolanda Hernández-Hermida ◽  
Nerea López-Muñoz ◽  
Juan-Ignacio Alós ◽  
Keyword(s):  
Escherichia Coli ◽  
Emergency Department ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Antibiotic Treatment ◽  
Antibiotic Susceptibility ◽  
Demographic Data ◽  
Local Resistance ◽  
Treatment Results

Objective. The aim of the study wat to analyze the antibiotic susceptibility of the pathogens causing urinary tract infection (UTI) and to stratify the results in function of patient´s clinical and demographic dates. Material and methods. The susceptibility of the pathogens isolated in the urine of 144 patients with UTI randomly chosen was analyzed. The results were stratified in function of sex, age, type of UTI, previous UTI and previous antibiotic treatment. Results. The susceptibility of the all isolates and of the Escherichia coli isolates was analyzed. There were significant differences between groups in function of sex (fluoroquinolones), age (cefuroxime, ertapenem and gentamicin), type of UTI (cefuroxime, cefotaxime, ertapenem and fluoroquinolones), previous UTI and previous antibiotic treatment (cefotaxime, fluoroquinolones and fosfomycin). Conclusions. The use of clinical and demographic data according to population and local resistance epidemiology of the pathogen causing UTI may help to select an adequate empirical treatment for UTI.

scholarly journals Urinary Tract Infection Investigation and Treatment in Older Adults Presenting to the Emergency Department with Confusion: a Health Record Review of Local Practice Patterns

2021 ◽  
Vol 24 (4) ◽  
pp. 341-350
Author(s):  
Rhiannan Pinnell ◽  
Tim Ramsay ◽  
Han Wang ◽  
Pil Joo
Keyword(s):  
Emergency Department ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Antibiotic Treatment ◽  
Tertiary Care ◽  
Urinary Symptoms ◽  
Health Record ◽  
Indwelling Catheters ◽  
Record Review

Background  The rate of urinary tract infection (UTI) investigation and treatment in confused older emergency department (ED) patients has not been described in the literature. We aim to describe the pattern of practice in an academic tertiary care ED for this common presentation.  Methods  A health record review was conducted on 499 adults aged ≥65 presenting to academic EDs with confusion. Exclusion criteria: Glasgow Coma Scale < 13, current treatment for UTI, indwelling catheters, nephrostomy tubes, transfer from another hospital. Outcomes were the prevalence of UTI investigation, diagnosis and antibiotic treatment.  Results  64.9% received urine tests, 11.4% were diagnosed with UTI, and 35.2% were prescribed antibiotics. In the subgroup with no urinary symptoms, fever, or other obvious indication for antibiotics, these numbers were 58.2%, 7.6%, and 18.1%, respectively. Patients who had urine tests or received antibiotics were older than those who did not (p values < .01). Patients receiving antibiotics had higher admission rates and 30-day and six-month mortality (OR of 2.9 [2.0–4.3], 4.0 [1.6–11], and 2.8 [1.4–5.8], respectively).  Conclusion  Older patients presenting to ED with confusion were frequently investigated and treated for UTI, even in the absence of urinary symptoms. Antibiotic treatment was associated with higher hospitalization and mortality. 

The Benefits and Harms of Antibiotic Prophylaxis for Urinary Tract Infection in Older Adults

2021 ◽  
Author(s):  
Bradley J Langford ◽  
Kevin A Brown ◽  
Christina Diong ◽  
Alex Marchand-Austin ◽  
Kwaku Adomako ◽  
...  
Keyword(s):  
Older Adults ◽  
Urinary Tract Infection ◽  
Antibiotic Resistance ◽  
Urinary Tract ◽  
Tract Infection ◽  
Antibiotic Prophylaxis ◽  
Bloodstream Infection ◽  
Antibiotic Treatment ◽  
Positive Culture ◽  
Clostridioides Difficile

Abstract Background The role of antibiotics in preventing urinary tract infection (UTI) in older adults is unknown. We sought to quantify the benefits and risks of antibiotic prophylaxis among older adults. Methods We conducted a matched cohort study comparing older adults (≥66 years) receiving antibiotic prophylaxis, defined as antibiotic treatment for ≥30 days starting within 30 days of a positive culture, with patients with positive urine cultures who received antibiotic treatment but did not receive prophylaxis. We matched each prophylaxis recipient to 10 nonrecipients based on organism, number of positive cultures, and propensity score. Outcomes included (1) emergency department (ED) visit or hospitalization for UTI, sepsis, or bloodstream infection within 1 year; (2) acquisition of antibiotic resistance in urinary tract pathogens; and (3) antibiotic-related complications. Results Overall, 4.7% (151/3190) of UTI prophylaxis patients and 3.6% (n = 1092/30 542) of controls required an ED visit or hospitalization for UTI, sepsis, or bloodstream infection (hazard ratio [HR], 1.33; 95% confidence interval [CI], 1.12–1.57). Acquisition of antibiotic resistance to any urinary antibiotic (HR, 1.31; 95% CI, 1.18–1.44) and to the specific prophylaxis agent (HR, 2.01; 95% CI, 1.80–2.24) was higher in patients receiving prophylaxis. While the overall risk of antibiotic-related complications was similar between groups (HR, 1.08; 95% CI, .94–1.22), the risk of Clostridioides  difficile and general medication adverse events was higher in prophylaxis recipients (HR [95% CI], 1.56 [1.05–2.23] and 1.62 [1.11–2.29], respectively). Conclusions Among older adults with UTI, the harms of long-term antibiotic prophylaxis may outweigh their benefits.

National Trends in Emergency Department Antibiotic Prescribing for Elders with Urinary Tract Infection, 1996-2005

2009 ◽  
Vol 16 (6) ◽  
pp. 500-507 ◽  
Author(s):  
Jeffrey M. Caterino ◽  
Sarah Grace Weed ◽  
Janice A. Espinola ◽  
Carlos A. Camargo, Jr
Keyword(s):  
Emergency Department ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Antibiotic Prescribing ◽  
National Trends
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