Comparison of Data Collection for Healthcare-Associated Infection Surveillance in Nursing Homes

2016 ◽  
Vol 37 (12) ◽  
pp. 1440-1445 ◽  
Author(s):  
Lauren Epstein ◽  
Nimalie D. Stone ◽  
Lisa LaPlace ◽  
Jane Harper ◽  
Ruth Lynfield ◽  
...  
Keyword(s):  
Risk Factors ◽  
Nursing Homes ◽  
Data Collection ◽  
Clinical Risk Factors ◽  
Healthcare Associated Infection ◽  
Screening Criteria ◽  
Clinical Risk ◽  
Level Data ◽  
Healthcare Associated ◽  
The Impact

OBJECTIVETo facilitate surveillance and describe the burden of healthcare-associated infection (HAI) in nursing homes (NHs), we compared the quality of resident-level data collected by NH personnel and external staff.DESIGNA 1-day point-prevalence surveySETTING AND PARTICIPANTSOverall, 9 nursing homes among 4 Centers for Disease Control and Prevention (CDC) Emerging Infection Program (EIP) sites were included in this study.METHODSNH personnel collected data on resident characteristics, clinical risk factors for HAIs, and the presence of 3 HAI screening criteria on the day of the survey. Trained EIP surveillance officers collected the same data elements via retrospective medical chart review for comparison; surveillance officers also collected available data to identify HAIs (using revised McGeer definitions). Overall agreement was calculated among residents identified by both teams with selected risk factors and HAI screening criteria. The impact of using NH personnel to collect screening criteria on HAI prevalence was assessed.RESULTSThe overall prevalence of clinical risk factors among the 1,272 residents was similar between NH personnel and surveillance officers, but the level of positive agreement (residents with factors identified by both teams) varied between 39% and 87%. Surveillance officers identified 253 residents (20%) with ≥1 HAI screening criterion, resulting in 67 residents with an HAI (5.3 per 100 residents). The NH personnel identified 152 (12%) residents with ≥1 HAI screening criterion; 42 residents had an HAI (3.5 per 100 residents).CONCLUSIONWe identified discrepancies in resident-level data collection between surveillance officers and NH personnel, resulting in varied estimates of the HAI prevalence. These findings have important implications for the design and implementation of future HAI prevalence surveys.Infect Control Hosp Epidemiol 2016;1440–1445

Clinical risk factors, phenomenology and the impact of clozapine induced obsessive compulsive symptoms

2021 ◽  
Vol 296 ◽  
pp. 113665
Author(s):  
Gamze Gürcan ◽  
Şevin Hun Şenol ◽  
A. Elif Anıl Yağcıoğlu ◽  
Aygün Ertuğrul
Keyword(s):  
Risk Factors ◽  
Clinical Risk Factors ◽  
Obsessive Compulsive ◽  
Obsessive Compulsive Symptoms ◽  
Clinical Risk ◽  
The Impact

scholarly journals Trends of Healthcare-associated Infections in a Tuinisian University Hospital and Impact of COVID-19 Pandemic

2021 ◽  
Vol 58 ◽  
pp. 004695802110679
Author(s):  
Hela Ghali ◽  
Asma Ben Cheikh ◽  
Sana Bhiri ◽  
Selwa Khefacha ◽  
Houyem Said Latiri ◽  
...  
Keyword(s):  
Risk Factors ◽  
Urinary Tract ◽  
Protective Factor ◽  
Bloodstream Infections ◽  
Point Prevalence ◽  
University Hospital ◽  
Healthcare Associated Infection ◽  
Tract Infections ◽  
Healthcare Associated ◽  
The Impact

Background Although efforts to manage coronavirus disease 2019 (COVID-19) pandemic have understandably taken immediate priority, the impacts on traditional healthcare-associated infection (HAI) surveillance and prevention efforts remain concerning. Aim To describe trends in HAIs in a Tunisian university hospital through repeated point prevalence surveys over 9 years, assess the impact of measures implemented for COVID-19 pandemic, and to identify associated factors of HAI. Methods The current study focused on data collected from annual point prevalence surveys conducted from 2012 to 2020. All types of HAIs as defined by the Centers for Disease Control and Prevention (CDC) were included. Data collection was carried out using NosoTun plug. Univariate and multivariate logistic analysis were used to identify HAI risk factors. Results Overall, 2729 patients were observed in the 9 surveys; the mean age was 48.3 ± 23.3 years and 57.5% were male. We identified 267 infected patients (9.8%) and 296 HAIs (10.8%). Pneumonia/lower respiratory tract infections were the most frequent HAI (24%), followed by urinary tract infection (20.9%).The prevalence of infected patients increased from 10.6% in 2012 to 14.9% in 2020. However, this increase was not statistically significant. The prevalence of HAIs increased significantly from 12.3% to 15.5% ( P =.003). The only decrease involved is bloodstream infections (from 2% to 1%). Independent risk factors significantly associated with HAI were undergoing surgical intervention (aOR = 1.7), the use of antibiotic treatment in previous 6 months (aOR = 1.8), peripheral line (aOR=2), parenteral nutrition (aOR=2.4), urinary tract within 7 days (aOR=2.4), central line (aOR = 6.3), and prosthesis (aOR = 12.8), length of stay (aOR = 3), and the year of the survey. Young age was found as protective factor (aOR = .98). Conclusion Contrary to what was expected, we noticed an increase in the HAIs rates despite the preventive measures put in place to control the COVID-19 pandemic. This was partly explained by the vulnerability of hospitalized patients during this period.

scholarly journals A Droplet Digital PCR Assay for Smoking Predicts All-Cause Mortality

2018 ◽  
Vol 47 (4) ◽  
pp. 220-229 ◽  
Author(s):  
Allan M. Andersen ◽  
Philip T. Ryan ◽  
Fredrick X. Gibbons ◽  
Ronald L. Simons ◽  
Jeffrey D. Long ◽  
...  
Keyword(s):  
Risk Factors ◽  
Polymerase Chain Reaction ◽  
Longitudinal Study ◽  
Clinical Risk Factors ◽  
Chain Reaction ◽  
Clinical Risk ◽  
Epigenetic Biomarkers ◽  
All Cause Mortality ◽  
Polymerase Chain ◽  
The Impact

Objectives.—Determine whether an epigenetic assay for smoking predicts all-cause mortality in adults participating in a longitudinal study of Iowa adoptees. Background.—Improved biomarkers for smoking are needed given its large public health impact and significant limitations of both self-report and current biomarkers, such as cotinine in detecting smoking. In the past 5 years, multiple epigenome-wide association studies of smoking have identified loci suitable for translation as epigenetic biomarkers for smoking, in particular the CpG cg05575921. Digital polymerase chain reaction methods hold promise for the development of this and other epigenetic biomarkers. Methods.—Participants in the Iowa Adoption Studies were interviewed regarding their smoking habits. DNA was prepared from whole blood and bisulfite-converted for methylation analysis and digital droplet polymerase chain reaction assay of methylation at cg05575921 was performed. National Death Index records were requested for 584 study participants, resulting in 24 complete matches, 210 partial matches and 350 non-matching records. Complete matches were coded as deceased while the remainder were coded as alive (ie, censored). In total, methylation data and vital status information were available for a total of N = 193 subjects, including 15 deceased and 178 non-deceased. Cox regression was used to examine the ability of cg05575921 methylation as a continuous value to predict the timing of mortality with and without the inclusion of age, sex, race, BMI, marital status, educational status, socioeconomic status, cardiovascular risk factors, and a history of cancer as covariates. Results.—Methylation at cg05575921 predicted the hazard of mortality as the sole predictor and after accounting for major demographic and clinical risk factors. The fitted model showed the hazard ratio increased by 3.5% for every 1% decrease in methylation. Conclusions.—Decreased methylation at cg05575921, an emerging epigenetic biomarker for smoking, was associated with early mortality in a longitudinal study of adults after accounting for the impact of major demographic and clinical risk factors for all-cause mortality. This approach may be useful in clinical research or actuarial assessments.

scholarly journals The prevalence of suspected ventilator-associated pneumonia in Scottish intensive care units

2019 ◽  
Vol 21 (2) ◽  
pp. 140-147
Author(s):  
Robert Hart ◽  
Scott McNeill ◽  
Sarah Maclean ◽  
Jamie Hornsby ◽  
Sarah Ramsay
Keyword(s):  
Data Collection ◽  
Ventilator Associated Pneumonia ◽  
Healthcare Associated Infection ◽  
Screening Process ◽  
Mechanically Ventilated ◽  
Endotracheal Tubes ◽  
Data Comparison ◽  
Healthcare Associated ◽  
The Impact ◽  
Meaningful Data

Ventilator-associated pneumonia is the most common healthcare-associated infection in mechanically ventilated patients. Despite this, accurate diagnosis of ventilator-associated pneumonia is difficult owing to the variety of criteria that exist. In this prospective national audit, we aim to quantify the existence of patients with suspected ventilator-associated pneumonia that would not be detected by our standard healthcare-associated infection screening process. Furthermore, we aim to assess the impact of tracheostomy insertion, subglottic drainage endotracheal tubes and chlorhexidine gel on ventilator-associated pneumonia rate. Of the 227 patients recruited, suspected ventilator-associated pneumonia occurred in 32 of these patients. Using the HELICS definition, 13/32 (40.6%) patients were diagnosed with ventilator-associated pneumonia (H-posVAP). Suspected ventilator-associated pneumonia rate was increased in our tracheostomy population, decreased in the subglottic drainage endotracheal tube group and unchanged in the chlorhexidine group. The diagnosis of ventilator-associated pneumonia remains a contentious issue. The formalisation of the HELICS criteria by the European CDC should allow standardised data collection throughout Europe, which will enable more consistent data collection and meaningful data comparison in the future. Our data add weight to the argument against routine oral chlorhexidine. The use of subglottic drainage endotracheal tubes in preventing ventilator-associated pneumonia is interesting and requires further investigation.

scholarly journals Identifying neurodevelopmental anomalies of white matter microstructure associated with high risk for psychosis in 22q11.2DS

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Joëlle Bagautdinova ◽  
Maria C. Padula ◽  
Daniela Zöller ◽  
Corrado Sandini ◽  
Maude Schneider ◽  
...  
Keyword(s):  
Risk Factors ◽  
White Matter ◽  
High Risk ◽  
Developmental Trajectories ◽  
Clinical Risk Factors ◽  
White Matter Tracts ◽  
Clinical Risk ◽  
White Matter Microstructure ◽  
White Matter Development ◽  
The Impact

AbstractDisruptions of white matter microstructure have been widely reported in schizophrenia. However, the emergence of these alterations during preclinical stages remains poorly understood. 22q11.2 Deletion Syndrome (22q11.2DS) represents a unique model to study the interplay of different risk factors that may impact neurodevelopment in premorbid psychosis. To identify the impact of genetic predisposition for psychosis on white matter development, we acquired longitudinal MRI data in 201 individuals (22q11.2DS = 101; controls = 100) aged 5–35 years with 1–3 time points and reconstructed 18 white matter tracts using TRACULA. Mixed model regression was used to characterize developmental trajectories of four diffusion measures—fractional anisotropy (FA), axial (AD), radial (RD), and mean diffusivity (MD) in each tract. To disentangle the impact of additional environmental and developmental risk factors on white matter maturation, we used a multivariate approach (partial least squares (PLS) correlation) in a subset of 39 individuals with 22q11.2DS. Results revealed no divergent white matter developmental trajectories in patients with 22q11.2DS compared to controls. However, 22q11.2DS showed consistently increased FA and reduced AD, RD, and MD in most white matter tracts. PLS correlation further revealed a significant white matter-clinical risk factors relationship. These results indicate that while age-related changes are preserved in 22q11.2DS, white matter microstructure is widely disrupted, suggesting that genetic high risk for psychosis involves early occurring neurodevelopmental insults. In addition, multivariate modeling showed that clinical risk factors further impact white matter development. Together, these findings suggest that genetic, developmental, and environmental risk factors may play a cumulative role in altering normative white matter development during premorbid stages of psychosis.

Healthcare-associated infections over an eight year period in a large university hospital in Sicily (Italy, 2011–2018)

2021 ◽  
pp. 175717742110124
Author(s):  
Giusy Russo Fiorino ◽  
Marialuisa Maniglia ◽  
Valentina Marchese ◽  
Luigi Aprea ◽  
Maria V Torregrossa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Data Entry ◽  
Antimicrobial Treatment ◽  
University Hospital ◽  
Healthcare Associated Infection ◽  
Fatal Disease ◽  
Klebsiella Species ◽  
Hospitalised Patients ◽  
Healthcare Associated ◽  
The Impact

Background: Up to 7% of hospitalised patients acquire at least one healthcare-associated infection (HAI). The aim of the present study was to quantify the burden of HAIs in an Italian hospital, identifying involved risk factors. Methods: Prevalence point study carried out from 2011 to 2018. For each recruited patient, a data entry form was compiled including information on demographics, hospital admission, risk factors, antimicrobial treatment, and infection if present. Results: A total of 2844 patients were included and 218 (7.03%) reported an infection. HAI prevalence rates showed a significant increase (average annual per cent change (AAPC) +33.9%; p=0.018) from 2011 to 2014 whereas from 2014 to 2018 a gradual decline was observed (AAPC –6.15%; p=0.35). Urinary tract infection was the most common HAI (25.2%) and a total of 166 (76.1%) pathogens were isolated from 218 infections. Enterococcus and Klebsiella species were the most prevalent pathogens, causing 15.1% and 14.5% of HAIs, respectively. A significant higher risk of HAIs was found in patients exposed to central catheter (adjusted odds ratio (adj-OR)=5.40), peripheral catheter (adj-OR=1.89), urinary catheter (adj-OR=1.46), National Healthcare Safety Network surgical intervention (adj-OR=1.48), ultimately fatal disease (adj-OR=2.19) or rapidly fatal disease (adj-OR=2.09) and in patients with longer hospital stay (adj-OR=1.01). Conclusion: Intervention programmes based on guidelines dissemination and personnel training can contribute to reduce the impact of HAI. Moreover, McCabe score can be a very powerful and efficient predictor of risk for HAI. Finally, an unexpected very high burden of disease due to Enterobacteriaceae and Gram positive cocci that could be related to the frequent use of carbapenems and third generation cephalosporins in this hospital was found.

scholarly journals On the Role of Length of Stay in Healthcare-Associated Bloodstream Infection

2012 ◽  
Vol 33 (12) ◽  
pp. 1213-1218 ◽  
Author(s):  
Christie Y. Jeon ◽  
Matthew Neidell ◽  
Haomiao Jia ◽  
Matt Sinisi ◽  
Elaine Larson
Keyword(s):  
Risk Factors ◽  
Length Of Stay ◽  
Hospital Stay ◽  
Bloodstream Infection ◽  
Negative Impact ◽  
Length Of Hospital Stay ◽  
Clinical Risk Factors ◽  
Clinical Risk ◽  
Increased Risk ◽  
Healthcare Associated

Design.We conducted a retrospective cohort study to examine the role played by length of hospital stay in the risk of healthcare-associated bloodstream infection (BSI), independent of demographic and clinical risk factors for BSI.Patients.We employed data from 113,893 admissions from inpatients discharged between 2006 and 2008.Setting.Large tertiary healthcare center in New York City.Methods.We estimated the crude and adjusted hazard of BSI by conducting logistic regression using a person-day data structure. The covariates included in the fully adjusted model included age, sex, Charlson score of comorbidity, renal failure, and malignancy as static variables and central venous catheterization, mechanical ventilation, and intensive care unit stay as time-varying variables.Results.In the crude model, we observed a nonlinear increasing hazard of BSI with increasing hospital stay. This trend was reduced to a constant hazard when fully adjusted for demographic and clinical risk factors for BSI.Conclusion.The association between longer length of hospital stay and increased risk of infection can largely be explained by the increased duration of stay among those who have underlying morbidity and require invasive procedures. We should take caution in attributing the association between length of stay and BSI to a direct negative impact of the healthcare environment.

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