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.

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

Surgical Site Infection in a Tertiary Neonatal Surgery Centre

2018 ◽  
Vol 29 (03) ◽  
pp. 260-265 ◽  
Author(s):  
Adiam Woldemicael ◽  
Sarah Bradley ◽  
Caroline Pardy ◽  
Justin Richards ◽  
Paolo Trerotoli ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Model ◽  
Surgical Site Infection ◽  
Hospital Stay ◽  
Logistic Regression Model ◽  
Length Of Hospital Stay ◽  
Neonatal Surgery ◽  
Site Infection ◽  
Increased Risk

Introduction Surgical site infection (SSI) is a key performance indicator to assess the quality of surgical care. Incidence and risk factors for SSI in neonatal surgery are lacking in the literature. Aim To define the incidence of SSI and possible risk factors in a tertiary neonatal surgery centre. Materials and Methods This is a prospective cohort study of all the neonates who underwent abdominal and thoracic surgery between March 2012 and October 2016. The variables analyzed were gender, gestational age, birth weight, age at surgery, preoperative stay in neonatal intensive care unit, type of surgery, length of stay, and microorganisms isolated from the wounds. Statistical analysis was done with chi-square, Student's t- or Mann–Whitney U-tests. A logistic regression model was used to evaluate determinants of risk for SSI; variables were analyzed both with univariate and multivariate models. For the length of hospital stay, a logistic regression model was performed with independent variables. Results A total of 244 neonates underwent 319 surgical procedures. The overall incidence of SSIs was 43/319 (13.5%). The only statistical differences between neonates with and without SSI were preoperative stay (<4 days vs. ≥4 days, p < 0.01) and length of hospital stay (<30 days vs. ≥30 days, p < 0.01). A pre-operative stay longer than 4 days was associated with almost three times increased risk of SSI (odds ratio [OR] 2.96, 95% confidence interval [CI] 1.05–8.34, p = 0.0407). Gastrointestinal procedures were associated with more than ten times the risk of SSI compared with other procedures (OR 10.17, 95% CI 3.82–27.10, p < 0.0001). Gastroschisis closure and necrotizing enterocolitis (NEC) laparotomies had the highest incidence SSI (54% and 62%, respectively). The risk of longer length of hospital stay after SSI was more than three times higher (OR = 3.36, 95%CI 1.63–6.94, p = 0.001). Conclusion This is the first article benchmarking the incidence of SSI in neonatal surgery in the United Kingdom. A preoperative stay ≥4 days and gastrointestinal procedures were independent risk factors for SSI. More research is needed to develop strategies to reduce SSI in selected neonatal procedures.

scholarly journals Identification of patients at increased risk of suicide in hepatobiliary and pancreatic cancer: an analysis of epidemiologic and clinical risk factors

HPB ◽  
2017 ◽  
Vol 19 ◽  
pp. S55
Author(s):  
P. Martinez Quinones ◽  
A. Talukder ◽  
N. Walsh ◽  
A. Lawson ◽  
A. Jones ◽  
...  
Keyword(s):  
Risk Factors ◽  
Pancreatic Cancer ◽  
Clinical Risk Factors ◽  
Clinical Risk ◽  
Increased Risk

scholarly journals Redefining osteoporosis treatment: who to treat and how long to treat

2006 ◽  
Vol 50 (4) ◽  
pp. 694-704 ◽  
Author(s):  
E. Michael Lewiecki ◽  
Stuart L. Silverman
Keyword(s):  
Risk Factors ◽  
Fracture Risk ◽  
Weight Bearing ◽  
Pharmacological Therapy ◽  
Clinical Risk Factors ◽  
Common Disease ◽  
Mineral Density ◽  
Clinical Risk ◽  
Increased Risk ◽  
Bmd Testing

Osteoporosis is a common disease that is associated with increased risk of fractures and serious clinical consequences. Bone mineral density (BMD) testing is used to diagnose osteoporosis, estimate the risk of fracture, and monitor changes in BMD over time. Combining clinical risk factors for fracture with BMD is a better predictor of fracture risk than BMD or clinical risk factors alone. Methodologies are being developed to use BMD and validated risk factors to estimate the 10-year probability of fracture, and then combine fracture probability with country-specific economic assumptions to determine cost-effective intervention thresholds. The decision to treat is based on factors that also include availability of therapy, patient preferences, and co-morbidities. All patients benefit from nonpharmacological lifestyle treatments such a weight-bearing exercise, adequate intake of calcium and vitamin D, fall prevention, avoidance of cigarette smoking and bone-toxic drugs, and moderation of alcohol intake. Patients at high risk for fracture should be considered for pharmacological therapy, which can reduce fracture risk by about 50%.

scholarly journals Clinical Application of a Novel Genetic Risk Score for Ischemic Stroke in Patients with Cardiometabolic Disease

Circulation ◽  
2020 ◽  
Author(s):  
Nicholas A. Marston ◽  
Parth N. Patel ◽  
Frederick K. Kamanu ◽  
Francesco Nordio ◽  
Giorgio M. Melloni ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Ischemic Stroke ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Clinical Risk Factors ◽  
Cardiometabolic Disease ◽  
Clinical Risk ◽  
Hazard Ratios ◽  
Increased Risk

Background: Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) that are associated with an increased risk of stroke. We sought to determine whether a genetic risk score (GRS) could identify subjects at higher risk for ischemic stroke after accounting for traditional clinical risk factors in five trials across the spectrum of cardiometabolic disease. Methods: Subjects who had consented for genetic testing and who were of European ancestry from the ENGAGE AF-TIMI 48, SOLID-TIMI 52, SAVOR-TIMI 53, PEGASUS-TIMI 54, and FOURIER trials were included in this analysis. A set of 32 SNPs associated with ischemic stroke was used to calculate a GRS in each patient and identify tertiles of genetic risk. A Cox model was used to calculate hazard ratios for ischemic stroke across genetic risk groups, adjusted for clinical risk factors. Results: In 51,288 subjects across the five trials, a total of 960 subjects had an ischemic stroke over a median follow-up period of 2.5 years. After adjusting for clinical risk factors, increasing genetic risk was strongly and independently associated with increased risk for ischemic stroke (p-trend=0.009). When compared to individuals in the lowest third of genetic risk, individuals in the middle and top tertiles of genetic risk had adjusted hazard ratios of 1.15 (95% CI 0.98-1.36) and 1.24 (95% CI 1.05-1.45) for ischemic stroke, respectively. Stratification into subgroups revealed the performance of the GRS appeared stronger in the primary prevention cohort with an adjusted HR for the top versus lowest tertile of 1.27 (95% CI 1.04-1.53), compared with an adjusted HR of 1.06 (95% CI 0.81-1.41) in subjects with prior stroke. In an exploratory analysis of patients with atrial fibrillation and CHA 2 DS 2 -VASc of 2, high genetic risk conferred a 4-fold higher risk of stroke and an absolute risk equivalent to those with CHA 2 DS 2 -VASc of 3. Conclusions: Across a broad spectrum of subjects with cardiometabolic disease, a 32-SNP GRS was a strong, independent predictor of ischemic stroke. In patients with atrial fibrillation but lower CHA 2 DS 2 -VASc scores, the GRS identified patients with risk comparable to those with higher CHA 2 DS 2 -VASc scores.

scholarly journals Associations Between Bone Impact Microindentation and Clinical Risk Factors for Fracture

Endocrinology ◽  
2019 ◽  
Vol 160 (9) ◽  
pp. 2143-2150 ◽  
Author(s):  
Pamela Rufus-Membere ◽  
Kara L Holloway-Kew ◽  
Adolfo Diez-Perez ◽  
Mark A Kotowicz ◽  
Julie A Pasco
Keyword(s):  
Risk Factors ◽  
Hip Fracture ◽  
Clinical Risk Factors ◽  
Material Strength ◽  
Mineral Density ◽  
Clinical Risk ◽  
Increased Risk ◽  
Vitamin D Levels ◽  
Prior Fracture ◽  
Impact Microindentation

Abstract Impact microindentation (IMI) measures bone material strength index (BMSi) in vivo. However, clinical risk factors that affect BMSi are largely unknown. This study investigated associations between BMSi and clinical risk factors for fracture in men. BMSi was measured using the OsteoProbe in 357 men (ages 33 to 96 years) from the Geelong Osteoporosis Study. Risk factors included age, weight, height, body mass index (BMI), femoral neck bone mineral density (BMD), parental hip fracture, prior fracture, type 2 diabetes mellitus (T2DM), secondary osteoporosis, smoking, alcohol consumption, sedentary lifestyle, medications, diseases, and low serum vitamin D levels. BMSi was negatively associated with age (r = −0.131, P = 0.014), weight (r = −0.109, P = 0.040), and BMI (r = −0.083, P = 0.001); no correlations were detected with BMD (r = 0.000, P = 0.998) or height (r = 0.087, P = 0.10). Mean BMSi values for men with and without prior fracture were 80.2 ± 6.9 vs 82.8 ± 6.1 (P = 0.024); parental hip fracture, 80.1 ± 6.1 vs 82.8 ± 6.9 (P = 0.029); and T2DM, 80.3 ± 8.5 vs 82.9 ± 6.6 (P = 0.059). BMSi did not differ in the presence vs absence of other risk factors. In multivariable models, mean (± SD) BMSi remained associated with prior fracture and parental hip fracture after adjusting for age and BMI: prior fracture (80.5 ± 1.1 vs 82.8 ± 0.4, P = 0.044); parental fracture (79.9 ± 1.2 vs 82.9 ± 0.4, P = 0.015). No other confounders were identified. We conclude that in men, BMSi discriminates prior fracture and parental hip fracture, which are both known to increase the risk for incident fracture. These findings suggest that IMI may be useful for identifying men who have an increased risk for fracture.

scholarly journals Prediction of Venous Thromboembolism Based on Clinical and Genetic Factors

2020 ◽  
Author(s):  
David A. Kolin ◽  
Scott Kulm ◽  
Olivier Elemento
Keyword(s):  
Risk Factors ◽  
Venous Thromboembolism ◽  
High Risk ◽  
Genetic Risk ◽  
Genetic Factors ◽  
Hazard Ratio ◽  
Low Risk ◽  
Clinical Risk Factors ◽  
Clinical Risk ◽  
Increased Risk

BACKGROUNDBoth clinical and genetic factors drive the risk of venous thromboembolism. However, whether clinically recorded risk factors and genetic variants can be combined into a clinically applicable predictive score remains unknown.METHODSUsing Cox proportional-hazard models, we analyzed the association of risk factors with the likelihood of venous thromboembolism in U.K. Biobank, a large prospective cohort. We created a novel ten point clinical score using seven established clinical risk factors for venous thromboembolism. We also generated a polygenic risk score of 21 single nucleotide polymorphisms to quantify genetic risk. The genetic score was categorized into high risk (top two deciles of scores), intermediate risk (deciles three to eight), and low risk (lowest two deciles). The discrete clinical score led to the following approximate decile categorizations: high risk (5 to 10 points), intermediate risk (3 to 4 points), and low risk (0 to 2 points).RESULTSAmongst the 502,536 participants in the U.K. Biobank, there were 4,843 events of venous thromboembolism. Analyses of established clinical risk factors and the most commonly used medications revealed that participants were at decreased risk of venous thromboembolism if they had ever used oral contraceptive pills (hazard ratio, 0.88; 95% confidence interval [CI], 0.79 to 0.99) or if they currently used bendroflumethiazide (hazard ratio, 0.84; 95% CI, 0.74 to 0.95), cod liver oil capsules (hazard ratio, 0.87; 95% CI, 0.77 to 0.99), or atenolol (hazard ratio, 0.79; 95% CI, 0.68 to 0.91). Participants were at significantly increased risk of venous thromboembolism if they were at high clinical risk (hazard ratio, 5.98; 95% CI, 5.43 to 6.59) or high genetic risk (hazard ratio, 2.28; 95% CI, 2.07 to 2.51) relative to participants at low clinical or genetic risk, respectively. Combining clinical risk factors with genetic risk factors produced a model that better predicted risk of venous thromboembolism than either model alone (P<0.001). Participants at high clinical and genetic risk in the combined score had over an eightfold increased risk of venous thromboembolism relative to participants at low risk (hazard ratio, 8.27; 95% CI 7.59 to 9.00).CONCLUSIONSBy assessing venous thromboembolic events in over 500,000 participants, we identified several known and novel associations between risk factors and venous thromboembolism. Participants in the high risk group of a combined score, consisting of clinical and genetic factors, were over eight times more likely to experience venous thromboembolism than participants in the low risk group.

scholarly journals Combining Clinical and Polygenic Risk Improves Stroke Prediction Among Individuals with Atrial Fibrillation

2021 ◽  
Author(s):  
Jack W. O'Sullivan ◽  
Anna Shcherbina ◽  
Johanne M. Justesen ◽  
Mintu Turakhia ◽  
Marco Perez ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Ischemic Stroke ◽  
Predictive Ability ◽  
Clinical Risk Factors ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Clinical Risk ◽  
Increased Risk ◽  
The Uk

Background - Atrial fibrillation (AF) is associated with a five-fold increased risk of ischemic stroke. A portion of this risk is heritable, however current risk stratification tools (CHA 2 DS 2 -VASc) don't include family history or genetic risk. We hypothesized that we could improve ischemic stroke prediction in patients with AF by incorporating polygenic risk scores (PRS). Methods - Using data from the largest available GWAS in Europeans, we combined over half a million genetic variants to construct a PRS to predict ischemic stroke in patients with AF. We externally validated this PRS in independent data from the UK Biobank, both independently and integrated with clinical risk factors. The integrated PRS and clinical risk factors risk tool had the greatest predictive ability. Results - Compared with the currently recommended risk tool (CHA 2 DS 2 -VASc), the integrated tool significantly improved net reclassification (NRI: 2.3% (95%CI: 1.3% to 3.0%)), and fit (χ2 P =0.002). Using this improved tool, >115,000 people with AF would have improved risk classification in the US. Independently, PRS was a significant predictor of ischemic stroke in patients with AF prospectively (Hazard Ratio: 1.13 per 1 SD (95%CI: 1.06 to 1.23)). Lastly, polygenic risk scores were uncorrelated with clinical risk factors (Pearson's correlation coefficient: -0.018). Conclusions - In patients with AF, there appears to be a significant association between PRS and risk of ischemic stroke. The greatest predictive ability was found with the integration of PRS and clinical risk factors, however the prediction of stroke remains challenging.

Prolongation of Hospital Stay and Additional Costs Due to Nosocomial Bloodstream Infection in an Algerian Neonatal Care Unit

2008 ◽  
Vol 29 (11) ◽  
pp. 1066-1070 ◽  
Author(s):  
Mohamed Lamine Atif ◽  
Fetta Sadaoui ◽  
Abdeldjallil Bezzaoucha ◽  
Chawki Ahmed Kaddache ◽  
Rachida Boukari ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Hospital Stay ◽  
Bloodstream Infection ◽  
Length Of Hospital Stay ◽  
Developed Countries ◽  
Neonatal Care ◽  
Additional Cost ◽  
University Hospital ◽  
Nosocomial Bloodstream Infection ◽  
The Mean

Background.Previous studies from developed countries reported that nosocomial bloodstream infection (BSI) in neonatal care units (NCUs) increases length of stay and costs. However, no such information is available for Algerian NCUs.Objective.To evaluate the influence of BSI in neonates on additional charges and length of hospital stay.Design.Prospective, nested case-control study.Setting.The 47-bed NCU of the University Hospital of Blida, Algeria.Patients and Methods.A total of 83 neonates with BSIs (case patients) and 166 neonates without BSIs (control patients), admitted to the NCU during the study period (April 2004 through December 2007), were matched for sex, birth weight, length of NCU stay, and year of hospital admission. Each patient's length of stay in the NCU was obtained prospectively on daily rounds. The estimated cost of each NCU-day was provided by the hospital's finance department. The cost of antibiotics prescribed was provided by the hospital's pharmacy department.Results.The mean additional length of NCU stay for case patients, compared with control patients, was 9.2 days (24.3 vs 15.1 days). The mean additional cost of antibiotics was $546. The mean cumulative additional cost was $1,315.Conclusion.This study highlights the effect of BSI on extra costs for NCU patients, especially costs due to prolongation of hospital stay and increased antibiotic use, and suggests that NCUs in Algeria have a financial interest in reducing the rate of BSI.

scholarly journals Lifestyle and clinical risk factors for incident rheumatoid arthritis-associated interstitial lung disease

2020 ◽  
pp. jrheum.200863
Author(s):  
Vanessa L. Kronzer ◽  
Weixing Huang ◽  
Paul F. Dellaripa ◽  
Sicong Huang ◽  
Vivi Feathers ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Functional Status ◽  
Area Under The Curve ◽  
Clinical Risk Factors ◽  
Logistic Regression Models ◽  
Clinical Risk ◽  
Increased Risk

Objective To determine the association between novel lifestyle factors on risk of rheumatoid arthritis-associated interstitial lung disease (RA-ILD), define the threshold at which smoking increases RA-ILD risk, and calculate the degree to which known lifestyle and clinical factors predict RA-ILD. Methods This nested case-control study matched incident RA-ILD cases to RA non-ILD controls on age, sex, RA duration, rheumatoid factor, and time from exposure assessment to RA-ILD. Exposures included education, body mass index (BMI), smoking, anti-cyclic citrullinated peptide, race, joint erosions, rheumatoid nodules, C-reactive protein (CRP), disease activity score, functional status, disease-modifying anti-rheumatic drug use, and glucocorticoid use. Odds ratios (OR) for each exposure on risk of RA-ILD were obtained from logistic regression models. Area under the curve (AUC) was calculated based all lifestyle and clinical exposures. Results We identified 84 incident RA-ILD cases and 233 matched controls. After adjustment, obesity, high-positive CRP (≥10 mg/L), and poor functional status (MDHAQ ≥1) were associated with increased risk of RA-ILD (OR 2.42, 95% confidence interval [CI] 1.11-5.24 vs. normal BMI; OR 2.61, 95% CI 1.21-5.64 vs. CRP <3mg/L; OR 3.10, 95% CI 1.32-7.26 vs. MDHAQ <0.2). Smoking 30 pack-years or more was strongly associated with risk of RA-ILD compared to nonsmokers (OR 6.06, 95% CI 2.72-13.5). Together, lifestyle and clinical risk factors for RA-ILD had an AUC of 0.79 (95% CI 0.73-0.85). Conclusion Obesity, CRP, functional status, and extensive smoking may be novel risk factors for RA-ILD, useful for RA-ILD risk assessment and prevention. The overall ability to predict RA-ILD remains modest.

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