Risk factors for healthcare-associated urinary tract infection and their applications in surveillance using hospital administrative data: a systematic review

A study on the risk stratification for patients within 24 hours of admission for risk of hospital-acquired urinary tract infection using Bayesian network models

Early identification of patients at risk of hospital-acquired urinary tract infections (HA-UTI) enables the initiation of timely targeted preventive and therapeutic strategies. Machine learning (ML) models have shown great potential for this purpose. However, existing ML models in infection control have demonstrated poor ability to support explainability, which challenges the interpretation of the result in clinical practice, limiting the adaption of the ML models into a daily clinical routine. In this study, we developed Bayesian Network (BN) models to enable explainable assessment within 24 h of admission for risk of HA-UTI. Our dataset contained 138,250 unique hospital admissions. We included data on admission details, demographics, lifestyle factors, comorbidities, vital parameters, laboratory results, and urinary catheter. Models developed from a reduced set of five features were characterized by transparency compared to models developed from a full set of 50 features. The expert-based clinical BN model over the reduced feature space showed the highest performance (area under the curve = 0.746) compared to the naïve- and tree-augmented-naïve BN models. Moreover, models developed from expert-based knowledge were characterized by enhanced explainability.

Clinical explainable machine learning models for early identification of patients at risk of hospital-acquired urinary tract infection

BACKGROUND

Machine learning (ML) models for early identification of patients at risk of hospital-acquired urinary tract infections (HA-UTI) may enable timely and targeted preventive and therapeutic strategies. However, clinicians are often challenged in the interpretation of the predictive outcomes provided by the ML models, which often reach different performances.

AIM

To train ML models for predicting patients at risk of HA-UTI using available data from electronic health records at the time of hospital admission. We focused on the performance of different ML models and clinical explainability.

METHODS

This retrospective study investigated patient data representing 138.560 hospital admissions in the North Denmark Region from 01.01.2017 to 31.12.2018. We extracted 51 health socio-demographic and clinical features in a full dataset and used the χ² test in addition to expert knowledge for feature selection, resulting in two reduced datasets. Seven different ML models were trained and compared between the three datasets. We applied the SHapley Additive exPlanation (SHAP) method to support population- and patient-level explainability.

FINDINGS

The best-performing ML model was a neural network based on the full dataset, reaching an area under the curve (AUC) of 0.758. The neural network was also the best-performing ML model based on the reduced datasets, reaching an AUC of 0.746. Clinical explainability was demonstrated with a SHAP summary- and forceplot.

CONCLUSION

Within 24h of hospital admission, the ML models were able to identify patients at risk of developing HA-UTI, providing new opportunities to develop efficient strategies for the prevention of HA-UTI. Using SHAP, we demonstrate how risk predictions can be explained at individual patient level and for the patient population in general.

Urinary tract infections in patients with renal insufficiency and dialysis - epidemiology, pathogenesis, clinical symptoms, diagnosis and treatment

Epidemiological studies show an increasing number of patients worldwide suffering from chronic kidney diseases (CKD), which are associated with a risk for progression to end-stage kidney disease (ESKD). CKD patients stage 2-5, patients with regular chronic dialysis treatment (hemo- or peritoneal dialysis), and patients suffering from kidney allograft dysfunction are at high risk to develop infections, e.g. urinary tract infections (UTI) and/or sepsis (urosepsis). These groups show metabolic disturbance, chronic inflammation, and impaired immunocompetence. Escherichia coli is still the most common pathogen in UTI. A wide variety of other pathogens may be involved in UTI. Urological interventions, catheterization, as well as repeated courses of antibiotics contribute to an increased challenge of antimicrobial resistance. The diagnosis of UTI in CKD is based on standard clinical and laboratory criteria. Pyuria (≥10 leucocytes/µl) is more often observed in patients with oligoanuria and low bacterial colony counts. The treatment strategies for this population are based on the same principles as in patients with normal renal function. However, drugs cleared by the kidney or by dialysis membranes need dose adjustment. Antimicrobials with potential systemic toxicity and nephrotoxicity should be administered with caution.

Bacterial Profile, Antimicrobial Susceptibility Pattern, and Associated Factors of Community- and Hospital-Acquired Urinary Tract Infection at Dessie Referral Hospital, Dessie, Northeast Ethiopia

Background

Bacterial urinary tract infection is among the most common community and hospital-acquired infections. Therefore, to know the status of the community and hospital-acquired urinary tract infection, antimicrobial susceptibility patterns, and associated factors among urinary tract infection profiles are essential to physicians and health workers to implement appropriate intervention.

Methods

An institution-based cross-sectional study was conducted among 422 urinary tract infection suspected patients. All isolates were identified by standard microbiological techniques, and their antibiotic susceptibility was done by the Kirby-Bauer disc diffusion method. Data were entered using EpiData version 3.1 and analyzed by SPSS software version 20. P value < 0.05 at 95% CI was considered statistically significant.

Result

Of 422 urine samples processed, 100 (23.7%) yielded bacterial isolates. About 50(30.7%) and 50(19.3%) were bacterial isolates from the community and hospitalized patients, respectively. E. coli 44/103(42.7%) predominated across the two groups, followed by S. aureus 25/103(24.3%), CONs, 14/103(13.5%), Klebsiella spp. 7/103(6.78), Proteus spp. 3/103(2.91), and Enterococcus spp. 3/103 (2.91%). Pseudomonas spp. 3/103 (2.91), Citrobacter spp. 2/103(1.94%), and Acinetobacter spp. 1/103(0.999), which were isolated from only the hospitalized patients. Meropenem susceptibly was 100% in both study groups and Ampicillin resistance was documented as 83.3% to 100% and 76.9% to 100% in hospitalized and community-acquired samples, respectively.

Conclusion

This study found a high prevalence of bacterial urinary tract infection in the study area and a high rate of bacterial resistance was observed to most antimicrobial drugs tested. Meropenem and nitrofurantoin were the most active drugs for urinary tract infections. Therefore, expanding routine bacterial culture and identification with antimicrobial susceptibility testing and strengthening regular surveillance systems are essential for appropriate patient care.

Personalized infection prevention and control: identifying patients at risk of healthcare-associated infection

BACKGROUND

Few healthcare-associated infection (HAI) studies focus on risk of HAI at the point of admission. Understanding this will enable planning and management of care with infection prevention at the heart of the patient journey from the point of admission.

AIM

To determine intrinsic characteristics of patients at hospital admission and extrinsic events, during the two years preceding admission, that increase risk of developing HAI.

METHODS

An incidence survey of adults within two hospitals in NHS Scotland was undertaken for one year in 2018/19 as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. The primary outcome measure was developing any HAI using recognized case definitions. The cohort was derived from routine hospital episode data and linkage to community dispensed prescribing data.

FINDINGS

The risk factors present on admission observed as being the most significant for the acquisition of HAI were: being treated in a teaching hospital, increasing age, comorbidities of cancer, cardiovascular disease, chronic renal failure and diabetes; and emergency admission. Relative risk of developing HAI increased with intensive care unit, high-dependency unit, and surgical specialties, and surgery <30 days before admission and a total length of stay of >30 days in the two years to admission.

CONCLUSION

Targeting patients at risk of HAI from the point of admission maximizes the potential for prevention, especially when extrinsic risk factors are known and managed. This study proposes a new approach to infection prevention and control (IPC), identifying those patients at greatest risk of developing a particular type of HAI who might be potential candidates for personalized IPC interventions.

Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study

Background

Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased morbidity, mortality and costs. Healthcare associated urinary tract infections (HA-UTI) accounts for about 20–30% of all HAI’s, and with the emergence of multi-resistant urinary tract pathogens, the total burden of HA-UTI will most likely increase.

Objective

The aim of the current study was to develop two predictive models, using data from the index admission as well as historic data on a patient, to predict the development of UTI at the time of entry to the hospital and after 48 hours of admission (HA-UTI). The ultimate goal is to predict the individual patient risk of acquiring HA-UTI before it occurs so that health care professionals may take proper actions to prevent it.

Methods

Retrospective cohort analysis of approx. 300 000 adult admissions in a Danish region was performed. We developed models for UTI prediction with five machine-learning algorithms using demographic information, laboratory results, data on antibiotic treatment, past medical history (ICD10 codes), and clinical data by transformation of unstructured narrative text in Electronic Medical Records to structured data by Natural Language Processing.

Results

The five machine-learning algorithms have been evaluated by the performance measures average squared error, cumulative lift, and area under the curve (ROC-index). The algorithms had an area under the curve (ROC-index) ranging from 0.82 to 0.84 for the entry model (T = 0 hours after admission) and from 0.71 to 0.77 for the HA-UTI model (T = 48 hours after admission).

Conclusion

The study is proof of concept that it is possible to create machine-learning models that can serve as early warning systems to predict patients at risk of acquiring urinary tract infections during admission. The entry model and the HA-UTI models perform with a high ROC-index indicating a sufficient sensitivity and specificity, which may make both models instrumental in individualized prevention of UTI in hospitalized patients. The favored machine-learning methodology is Decision Trees to ensure the most transparent results and to increase clinical understanding and implementation of the models.

Is Outpatient Management of Mandibular Fractures Associated With Inflammatory Complications? An ACS-NSQIP Study

PURPOSE

Timing of mandibular fracture repair has long been debated. The purpose of the present study was to assess the incidence of postoperative inflammatory complications (POICs) following open repair of mandibular fractures managed non-urgently in the outpatient setting versus urgently in the inpatient setting.

METHODS

The authors utilized the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database to enroll a sample of patients with mandibular fractures who underwent open repair. The primary independent variable was treatment protocol: outpatient (elective) versus inpatient (urgent/non-elective). The primary dependent variable was POIC (yes/no). Descriptive, bivariate, and multiple logistic regression statistics were utilized to evaluate the relationship between treatment protocol and POICs.

RESULTS

The study cohort was comprised of 1,848 subjects with 1,134 outpatients and 714 inpatients. The incidence of POICs was 6.53% for the outpatient group compared to 8.96% for the inpatient group, with no significant difference between groups (P= .052). However, subjects treated as inpatients were 1.51 times more likely to experience any complication (P = .008) due to an increase in non-POICs (P = .028), in particular urinary tract infections (P = .035). After adjusting for age, hypertension requiring medical treatment, and smoking, classification as ASA II (P = .046, OR = 2.21, 95% CI 1.01 to 4.83), ASA III (P = .020, OR = 2.88, 95% CI 1.18 to 7.02), diabetes (P = 0.004, OR = 3.11, 95% CI 1.43 to 6.74), and preoperative hematocrit (P = 0.010, OR = 0.950, 95% CI 0.913 to 0.988) were independent predictors of POICs. Length of stay was 0.83 ± 2.61 days compared to 2.36 ± 3.63 days for the outpatient and inpatient groups, respectively (P ≤ .001).

CONCLUSIONS

There was no significant difference in POICs between patients treated as outpatients versus inpatients, though outpatients had fewer non-POICs and a shorter length of hospital stay.

Critically Ill Health Care-Associated Urinary Tract Infection: Broad vs. Narrow Antibiotics in the Emergency Department Have Similar Outcomes

BACKGROUND

Urinary tract infection (UTI) is the second most common infection requiring intensive care unit (ICU) admission in emergency department (ED) patients. Optimal empiric management for health care-associated (HCA) UTI is unclear, particularly in the critically ill.

OBJECTIVE

To compare clinical failure of broad vs. narrow antibiotic selection in the ED for patients presenting with HCA UTI admitted to the ICU.

METHODS

Observational cohort of patients started on empiric antibiotic for UTI with at least one HCA risk factor (recurrent UTI, chronic urinary catheter or dialysis, urologic procedures, previous antibiotic exposure, hospitalization, or group facility residence). Broad antibiotics covered Pseudomonas spp. and extended-spectrum beta-lactamase. Clinical failure was a composite of multiorgan dysfunction (MODS) by day 2 and in-hospital mortality. Secondary outcomes were length of stay (LOS), readmission, recurrent infection, development of multidrug-resistant organisms, and Clostridium difficile infection. Associations were reported with odds ratios (OR) and 95% confidence intervals (CI).

RESULTS

There were 272 patients included; 196 (72.1%) received broad and 76 (27.9%) received narrow therapy. There was no association between antibiotic selection and clinical failure (OR 1.05, 95% CI 0.5-2.25, p = 0.89) or between antibiotic selection and number of HCA risk factors (OR 0.98, 95% CI 0.73-1.31, p = 0.87). There was an association between clinical failure and MODS on ICU admission (OR 9.14, 95% CI 4.70-17.78, p < 0.001). Hospital LOS and readmission did not differ between antibiotic groups.

CONCLUSION

Initial empiric broad or narrow antibiotic coverage in HCA UTI patients who presented to the ED and required ICU admission had similar clinical outcomes.

Management of hospital-acquired infections among patients hospitalized at Zewditu memorial hospital, Addis Ababa, Ethiopia: A prospective cross-sectional study

BACKGROUND

Hospital-Acquired Infections (HAIs) are acquired when the patient is hospitalized for more than 48 hours. In Ethiopia data are scarce in management appropriateness of HAIs. Hence, this study was aimed to assess the prevalence and management of HAIs among patients admitted at Zewditu Memorial Hospital.

METHOD

A facility based prospective cross sectional study was conducted from March 1, 2017 to August 30, 2017. The sample was proportionally allocated among (medical, pediatrics, gynecology and obstetrics and surgical) wards, based on patient flow. Data were collected using data abstraction format and supplemented by key informant interview. Interview was made on eight physicians and four microbiologists who have been working in the wards during study period. Management appropriateness was assessed using Infectious Disease Society of America guideline and experts opinion (Infectious disease specialist). A multivariate logistic regression was used to identify factors associated with HAIs.

RESULT

The prevalence of HAIs was 19.8%. Surgical Site Infection (SSI) and pneumonia accounted for 20 (24.7%) of the infections. Culture and sensitivity was done for 24 (29.6%) patients. Of the 81 patients who developed HAIs, 54 (66.67%) of them were treated inappropriately. Physicians' response for this variation was information gap, forgetfulness, affordability and availability issue of first line medications. Younger age (AOR (Adjusted odds ratio) = 8.53, 95% CI: 2.67-27.30); male gender (AOR = 2.06, 95% CI: 1.01-4.22); longer hospital stay (AOR = 0.17, 95% CI: 0.06-0.51); and previous hospital admission (AOR = 3.22, 95% CI: 1.76-5.89); were independent predictors of HAIs.

CONCLUSION

Prevalence of HAIs and inappropriate management were substantially high in this study. Pneumonia and SSI were the common types of HAIs. Locally conformable guidelines could help to correct such problems.

Profiles of the bacterial community in short-term indwelling urinary catheters by duration of catheterization and subsequent urinary tract infection

BACKGROUND

Urinary catheterization, even of short duration, increases the risk of subsequent urinary tract infection (UTI). Whether the bacteria found on the surface of catheters placed for <3 days are associated with UTI risk is unknown.

METHODS

We screened the biofilms found on the extraluminal surface of 127 catheters placed for <3 days in women undergoing elective gynecologic surgery, using targeted quantitative polymerase chain reaction and an untargeted 16S rRNA taxonomic screen.

RESULTS

Using quantitative polymerase chain reaction, Enterococcus spp were found on virtually all catheters and lactic acid bacteria in most catheters regardless of duration, but neither genus was associated with UTI development during follow-up. Enterococcus, Streptococcus, and Staphylococcus were the most commonly identified genera in the taxonomic screen but were not associated with subsequent UTIs. Although the most common cause of UTI following catheter removal was Escherichia coli, detectable E coli on the catheter surface was not associated with subsequent UTIs.

CONCLUSIONS

Our analysis does not suggest that the presence of bacteria on the surface of catheters placed for <3 days leads to subsequent UTIs. Other aspects of catheter care are likely more important than preventing bacterial colonization of the catheter surface for preventing UTIs following short-term catheter placement.

Epidemiology and health-economic burden of urinary-catheter-associated infection in English NHS hospitals: a probabilistic modelling study

BACKGROUND

Catheter-associated urinary tract infection (CAUTI) and bloodstream infection (CABSI) are leading causes of healthcare-associated infection in England's National Health Service (NHS), but health-economic evidence to inform investment in prevention is lacking.

AIMS

To quantify the health-economic burden and value of prevention of urinary-catheter-associated infection among adult inpatients admitted to NHS trusts in 2016/17.

METHODS

A decision-analytic model was developed to estimate the annual prevalence of CAUTI and CABSI, and their associated excess health burdens [quality-adjusted life-years (QALYs)] and economic costs (£ 2017). Patient-level datasets and literature were synthesized to estimate population structure, model parameters and associated uncertainty. Health and economic benefits of catheter prevention were estimated. Scenario and probabilistic sensitivity analyses were conducted.

FINDINGS

The model estimated 52,085 [95% uncertainty interval (UI) 42,967-61,360] CAUTIs and 7529 (UI 6857-8622) CABSIs, of which 38,084 (UI 30,236-46,541) and 2524 (UI 2319-2956) were hospital-onset infections, respectively. Catheter-associated infections incurred 45,717 (UI 18,115-74,662) excess bed-days, 1467 (UI 1337-1707) deaths and 10,471 (UI 4783-13,499) lost QALYs. Total direct hospital costs were estimated at £54.4M (UI £37.3-77.8M), with an additional £209.4M (UI £95.7-270.0M) in economic value of QALYs lost assuming a willingness-to-pay threshold of £20,000/QALY. Respectively, CABSI accounted for 47% (UI 32-67%) and 97% (UI 93-98%) of direct costs and QALYs lost. Every catheter prevented could save £30 (UI £20-44) in direct hospital costs and £112 (UI £52-146) in QALY value.

CONCLUSIONS

Hospital catheter prevention is poised to reap substantial health-economic gains, but community-oriented interventions are needed to target the large burden imposed by community-onset infection.

Magnitude of Biofilm Formation and Antimicrobial Resistance Pattern of Bacteria Isolated from Urinary Catheterized Inpatients of Jimma University Medical Center, Southwest Ethiopia

Biofilm formation is one of the features of most bacteria. Catheterization in medicine is a source of highly resistant bacterial infections, and those bacteria respond poorly to antimicrobial therapy. Bacterial biofilm features were not described from catheterized inpatients in Ethiopia as its formation is known to afford antimicrobial resistance and challenge patient management. The aim of this study was to isolate catheter-associated urinary bacterial pathogens, their biofilm formation, and antimicrobial susceptibility pattern among inpatients of Jimma University Medical Center (JUMC) in Southwest Ethiopia. A prospective cross-sectional study was conducted among urinary catheterized inpatients of JUMC from February to August 2016. A total of 143 study participants were enrolled consecutively in this study. Urine samples were collected from catheterized patients and processed using a standard bacteriological protocol for isolation and identification. Evaluation of in vitro biofilm formation and antimicrobial susceptibility pattern of uropathogenic bacteria was done using microtiter plates and disk diffusion method, respectively. Data were cleaned, coded, and entered into SPSS version 20 for analysis. All statistical test values of p < 0.05 were considered statistically significant. From all study participants, mean age was 44 years. Sixty bacterial strains were recovered from 57 urinary catheterized inpatients among which 54 of them were monomicrobial (94.7%). The remaining six bacterial strains were recovered from three study participants each with two bacterial isolates. The predominant bacterial isolates were Gram-negative bacteria with E. coli turning out first. About 80% of bacterial isolates were biofilm formers. The majority of the bacteria were resistant to commonly prescribed antimicrobial agents. In conclusion, the majority of bacterial uropathogen isolates were Gram-negative, biofilm formers, and resistant to commonly prescribed antimicrobial agents. Relatively ciprofloxacin, nitrofurantoin, and amikacin were highly effective against most isolated bacteria.

Supporting women with toileting in palliative care: use of the female urinal for bladder management

AIMS AND OBJECTIVES

This study explored whether a female urinal is an acceptable, safe and effective product to meet the toileting requirements of women receiving palliative care on oncology wards in hospitals.

BACKGROUND

There is minimal evidence on how urinary incontinence should be managed in women receiving palliative care. Female urinals may present an option. There have been two general reviews of products, but no formal evaluation since 1999.

METHODS

This qualitative interview study used semi-structured interviews. Eleven healthy volunteers, 9 patients and 7 staff members used (or assisted with) a VernaFem (Vernacare) female urinal and were subsequently interviewed. Directed content analysis was used to analyse the interviews.

RESULTS

User testing confirmed that the VernaFem is an acceptable, safe and effective product. Design improvements were suggested.

CONCLUSIONS

While unlikely to be suitable for all patients, hospitals should consider offering a female urinal to patients in receipt of palliative care.

The Impact of Catheter-Associated Urinary Tract Infection (CA-UTI) in Critically Ill Children in the Pediatric Intensive Care Unit

Objective Catheter-associated urinary tract infections (CA-UTIs) comprise a significant proportion of hospital-acquired infections. However, the impact of CA-UTIs on important outcome measures, such as length of stay (LOS) and hospital charges, has not been examined in the pediatric intensive care unit (PICU) setting. Design Single-center, retrospective, case-matched, cohort study and financial analysis. Setting PICU in a tertiary-care children's medical center. Patients A total of 41 critically ill children with CA-UTIs and 73 critically ill children without CA-UTI, matched for age, gender, severity of illness, and primary admission diagnosis. Interventions None. Measurements and Main Results We compared the length of hospital stay (LOS in PICU and in hospital), mortality, and hospital costs in critically ill children with CA-UTIs and their matched controls. Critically ill children experiencing CA-UTI had significantly longer PICU LOS, hospital LOS, duration of mechanical ventilation, and mortality compared with matched controls without CA-UTI. The longer LOS resulted in higher PICU and hospital charges in this group. Conclusion Critically ill children with CA-UTI experience worse outcomes in the PICU compared with those without CA-UTI. Further studies on the impact of CA-UTI in the PICU are warranted.

Risk Factors for Urinary Tract Infections in Cardiac Surgical Patients

BACKGROUND

Risk factors for catheter-associated urinary tract infections (CAUTIs) in patients undergoing non-cardiac surgical procedures have been well documented. However, the variables associated with CAUTIs in the cardiac surgical population have not been clearly defined. Therefore, the purpose of this study was to investigate risk factors associated with CAUTIs in patients undergoing cardiac procedures.

METHODS

All patients undergoing cardiac surgery at a single institution from 2006 through 2012 (4,883 patients) were reviewed. Patients with U.S. Centers for Disease Control (CDC) criteria for CAUTI were identified from the hospital's Quality Assessment database. Pre-operative, operative, and post-operative patient factors were evaluated. Univariate and multivariable analyses were used to identify significant correlations between perioperative characteristics and CAUTIs.

RESULTS

There were 55 (1.1%) documented CAUTIs in the study population. On univariate analysis, older age, female gender, diabetes mellitus, cardiogenic shock, urgent or emergent operation, packed red blood cell (PRBC) units transfused, and intensive care unit length of stay (ICU LOS) were all significantly associated with CAUTI [p<0.05]. On multivariable logistic regression, older age, female gender, diabetes mellitus, and ICU LOS remained significantly associated with CAUTI. Additionally, there was a significant association between CAUTI and 30-d mortality on univariate analysis. However, when controlling for common predictors of operative mortality on multivariable analysis, CAUTI was no longer associated with mortality.

CONCLUSIONS

There are several identifiable risk factors for CAUTI in patients undergoing cardiac procedures. CAUTI is not independently associated with increased mortality, but it does serve as a marker of sicker patients more likely to die from other comorbidities or complications. Therefore, awareness of the high-risk nature of these patients should lead to increased diligence and may help to improve peri-operative outcomes. Recognizing patients at high risk for CAUTI may lead to improved measures to decrease CAUTI rates within this population.

Use of Electronic Health-Related Datasets in Nursing and Health-Related Research

Datasets of gigabyte size are common in medical sciences. There is increasing consensus that significant untapped knowledge lies hidden in these large datasets. This review article aims to discuss Electronic Health-Related Datasets (EHRDs) in terms of types, features, advantages, limitations, and possible use in nursing and health-related research. Major scientific databases, MEDLINE, ScienceDirect, and Scopus, were searched for studies or review articles regarding using EHRDs in research. A total number of 442 articles were located. After application of study inclusion criteria, 113 articles were included in the final review. EHRDs were categorized into Electronic Administrative Health-Related Datasets and Electronic Clinical Health-Related Datasets. Subcategories of each major category were identified. EHRDs are invaluable assets for nursing the health-related research. Advanced research skills such as using analytical softwares, advanced statistical procedures, dealing with missing data and missing variables will maximize the efficient utilization of EHRDs in research.

Can't swallow, can't transfer, can't toilet: factors predicting infections in the first week post stroke

Post stroke infections are a significant clinical problem. Dysphagia occurs in approximately half of stroke patients and is associated with respiratory infections; however it is unclear what other factors contribute to an increased risk. This study aimed to determine which factors are most strongly predictive of infections in the first 7 days post stroke admission. A retrospective review of 536 stroke patients admitted to Australian hospitals in 2010 was conducted. Data were collected on 37 clinical and demographic parameters. Univariate and multivariate logistic regression analysis was performed. The overall incidence of infection was 21%. Full assistance with mobility and incontinence on admission were associated with increased odds of general infection. Nil by mouth and presence of a nasogastric tube were significantly associated with patients developing respiratory infections. Urinary incontinence was a significant predictor for a urinary tract infection. Incidence of infection was highest on day two post admission. This study found enteral feeding, requiring full assistance with mobility and incontinence were significantly associated with developing infections in acute stroke. It contributes valuable new data from a large cohort of stroke patients demonstrating a period of susceptibility to infection in the very acute post stroke period.

A point prevalence cross-sectional study of healthcare-associated urinary tract infections in six Australian hospitals

OBJECTIVES

Urinary tract infections (UTIs) account for over 30% of healthcare-associated infections. The aim of this study was to determine healthcare-associated UTI (HAUTI) and catheter-associated UTI (CAUTI) point prevalence in six Australian hospitals to inform a national point prevalence process and compare two internationally accepted HAUTI definitions. We also described the level and comprehensiveness of clinical record documentation, microbiology laboratory and coding data at identifying HAUTIs and CAUTIs.

SETTING

Data were collected from three public and three private Australian hospitals over the first 6 months of 2013.

PARTICIPANTS

A total of 1109 patients were surveyed. Records of patients of all ages, hospitalised on the day of the point prevalence at the study sites, were eligible for inclusion. Outpatients, patients in adult mental health units, patients categorised as maintenance care type (ie, patients waiting to be transferred to a long-term care facility) and those in the emergency department during the duration of the survey were excluded.

OUTCOME MEASURES

The primary outcome measures were the HAUTI and CAUTI point prevalence.

RESULTS

Overall HAUTI and CAUTI prevalence was 1.4% (15/1109) and 0.9% (10/1109), respectively. Staphylococcus aureus and Candida species were the most common pathogens. One-quarter (26.3%) of patients had a urinary catheter and fewer than half had appropriate documentation. Eight of the 15 patients ascertained to have a HAUTI based on clinical records (6 being CAUTI) were coded by the medical records department with an International Classification of Diseases (ICD)-10 code for UTI diagnosis. The Health Protection Agency Surveillance definition had a positive predictive value of 91.67% (CI 64.61 to 98.51) compared against the Centers for Disease Control and Prevention definition.

CONCLUSIONS

These study results provide a foundation for a national Australian point prevalence study and inform the development and implementation of targeted healthcare-associated infection surveillance more broadly.

Rate of positive urine culture and double-J catheters colonization on the basis of microorganism DNA analysis

Introduction

The aim of the trial was to estimate the relationship between colonization of the Double–J catheter, and the microorganisms cultured from urine.

Material and methods

60 patients, who had Double–J catheters inserted, participated in the study. All the subjects had their midstream urine samples taken prior to the stent insertion and removal. A negative urine culture before catheterization was mandatory to participate in the study. The patients were assigned into three subgroups, according to stenting duration: 1) 20 to 30 days (18 cases); 2) 30 to 90 days (30 cases); 3) longer than 90 days (12 cases). Bacterial and fungal DNA was identified using electrophoresis in polyacrylamide gel with a denaturing gradient (PCR–DGGE). The relationship between the genetic analysis of the catheter and the urine culture was estimated.

Results

Urine cultures were positive in only 8 patients, while Double–J catheter analyses were positive in all cases. In 2 cases one type of microorganism was isolated from the stent surface while the remaining 58 catheters were colonized by more than one pathogen. In three cases fungi were isolated. There were only three types of pathogens cultured from urine specimens. Urine and stent cultures were consistent in 5 cases. In 3 cases urine culture and stent analysis were not consistent.

Conclusions

Double–J catheter retention in the urinary tract is associated with an extremely high risk of bacterial colonization, while the risk of urine infection is about 8–fold lower. There is a great inconsistency between urine infection and catheter colonization, indicating a low predictive value of urine culture for estimating stent colonization.

Frequency and impact of intensive care unit complications on moderate-severe traumatic brain injury: early results of the Outcome Prognostication in Traumatic Brain Injury (OPTIMISM) Study

BACKGROUND

Known predictors of adverse outcomes in patients with moderate-severe TBI (msTBI) explain only a relatively small proportion of patient-related outcomes. The frequency and impact of intensive care unit complications (ICU-COMPL) on msTBI-associated outcomes are poorly understood.

METHODS

In 213 consecutive msTBI patients admitted to a Level I Trauma Center neuro trauma ICU, twenty-eight ICU-COMPL (21 medical and 7 neurological) were prospectively collected and adjudicated by group consensus, using pre-defined criteria. We determined frequencies, and explored associations of ICU-COMPL and hospital discharge outcomes using multivariable logistic regression.

RESULTS

The average age of the study sample was 53 years, and the median presenting Glasgow Coma Scale and Injury Severity Scores were 5 and 27, respectively. Hyperglycemia (79%), fever (62%), systemic inflammatory response syndrome (60%), and hypotension requiring vasopressors (42%) were the four most common medical ICU-COMPL. Herniation (39%), intracranial rebleed (39%), and brain edema requiring osmotherapy (37%) were the three most common neurological ICU-COMPL. After adjusting for admission variables, duration of ventilation, and ICU length-of-stay, patients with brain edema (OR 5.8; 95% CI 2, 16.7) had a significantly increased odds for dying during hospitalization whereas patients with hospital-acquired urinary tract infection (UTI) had a decreased odds (OR 0.05; 95% CI 0.005, 0.6). Sensitivity analysis revealed that UTI occurred later, suggesting a non-causal association with survival. Brain herniation (OR 15.7; 95% CI 2.6, 95.4) was associated with an unfavorable functional status (GOS 1-3).

CONCLUSION

ICU-COMPL are very common after msTBI, have a considerable impact on short-term outcomes, and should be considered in the prognostication of these high risk patients. Survival associations of time-dependent complications warrant cautious interpretation.