Assessing length of stay and associated characteristics of geriatric patients in Northern Ireland

The effective provision of care for the elderly is becoming increasingly more difficult. This is due to the rising proportion of elderly in the population, increasing demands placed on the health services and the financial strain placed on an already stretched economy. The research presented in this paper uses three different models to represent the length of stay distribution of geriatric patients admitted to one of the six key acute hospitals in Northern Ireland and various patient characteristics associated with their respective length of stay. The accurate modelling of bed usage within wards would enable hospital managers to prepare patient discharge packages and rehabilitation services in advance. The models presented within the paper include a Cox proportional hazards model, a Bayesian network with a discrete variable to represent length of stay and a special conditional phase-type model (C-Ph) with a connecting outcome node. This research demonstrates the new efficient fitting algorithm employed for Coxian phase-type distributions while updating C-Ph models for recent elderly patient data.

The prognostic and therapeutic value of EpHA2 in early colorectal cancer (CRC).

Background: EpHA2 is a 130 kD transmembrane glycoprotein belonging to ephrin receptor subfamily and involved in angiogenesis/tumour neovascularisation. High EpHA2 mRNA level has recently been implicated in cetuximab resistance. Previously, we found high EpHA2 levels in a panel of invasive colorectal cancer (CRC) cells, which was associated with high levels of stem-cell marker CD44. Our aim was to investigate the prognostic value of EpHA2 and subsequently correlate expression levels to known clinico-pathological variables in early stage CRC. Methods: Tissue samples from 509 CRC patients were analysed. EpHA2 expression was measured using IHC. Kaplan-Meier graphs were used. Univariate and multivariate analyses employed Cox Proportional Hazards Ratio (HR) method. A backward selection method (Akaike’s information criterion) was used to determine a refined multivariate model. Results: EpHA2 was highly expressed in CRC adenocarcinoma compared to matched normal colon tissue. In support of our preclinical invasive models, strong correlation was found between EpHA2 expression and CD44 and Lgr5 staining (p<0.001). In addition, high EpHA2 expression significantly correlated with vascular invasion (p=0.03).HR for OS for stage II/III patients with high EpHA2 expression was 1.69 (95%CI: 1.164-2.439; p=0.003). When stage II/III was broken down into individual stages, there was significant correlation between high EpHA2 expression and poor 5-years OS in stage II patients (HR: 2.18; 95%CI: 1.28-3.71; p=0.005).HR in the stage III group showed a trend to statistical significance (HR: 1.48; 95%CI=0.87-2.51; p=0.05). In both univariate and multivariate analyses of stage II patients, high EpHA2 expression was the only significant factor and was retained in the final multivariate model. Higher levels of EpHA2 were noted in our RAS and BRAF mutant CRC cells, and silencing EpHA2 resulted in significant decreases in migration/invasion in parental and invasive CRC sublines. Correlation between KRAS/NRAS/BRAFmutational status and EpHA2 expression in clinical samples is ongoing. Conclusions: Taken together, our study is the first to indicate that EpHA2 expression is a predictor of poor clinical outcome and a potential novel target in early stage CRC.

Influence of noninjecting and injecting drug use on mortality, retention in the cohort, and antiretroviral therapy, in participants in the Swiss HIV Cohort Study.

OBJECTIVES: We studied the influence of noninjecting and injecting drug use on mortality, dropout rate, and the course of antiretroviral therapy (ART), in the Swiss HIV Cohort Study (SHCS). METHODS: Cohort participants, registered prior to April 2007 and with at least one drug use questionnaire completed until May 2013, were categorized according to their self-reported drug use behaviour. The probabilities of death and dropout were separately analysed using multivariable competing risks proportional hazards regression models with mutual correction for the other endpoint. Furthermore, we describe the influence of drug use on the course of ART. RESULTS: A total of 6529 participants (including 31% women) were followed during 31 215 person-years; 5.1% participants died; 10.5% were lost to follow-up. Among persons with homosexual or heterosexual HIV transmission, noninjecting drug use was associated with higher all-cause mortality [subhazard rate (SHR) 1.73; 95% confidence interval (CI) 1.07-2.83], compared with no drug use. Also, mortality was increased among former injecting drug users (IDUs) who reported noninjecting drug use (SHR 2.34; 95% CI 1.49-3.69). Noninjecting drug use was associated with higher dropout rates. The mean proportion of time with suppressed viral replication was 82.2% in all participants, irrespective of ART status, and 91.2% in those on ART. Drug use lowered adherence, and increased rates of ART change and ART interruptions. Virological failure on ART was more frequent in participants who reported concomitant drug injections while on opiate substitution, and in current IDUs, but not among noninjecting drug users. CONCLUSIONS: Noninjecting drug use and injecting drug use are modifiable risks for death, and they lower retention in a cohort and complicate ART.

Association of major and minor ECG abnormalities with coronary heart disease events.

CONTEXT: In populations of older adults, prediction of coronary heart disease (CHD) events through traditional risk factors is less accurate than in middle-aged adults. Electrocardiographic (ECG) abnormalities are common in older adults and might be of value for CHD prediction. OBJECTIVE: To determine whether baseline ECG abnormalities or development of new and persistent ECG abnormalities are associated with increased CHD events. DESIGN, SETTING, AND PARTICIPANTS: A population-based study of 2192 white and black older adults aged 70 to 79 years from the Health, Aging, and Body Composition Study (Health ABC Study) without known cardiovascular disease. Adjudicated CHD events were collected over 8 years between 1997-1998 and 2006-2007. Baseline and 4-year ECG abnormalities were classified according to the Minnesota Code as major and minor. Using Cox proportional hazards regression models, the addition of ECG abnormalities to traditional risk factors were examined to predict CHD events. MAIN OUTCOME MEASURE: Adjudicated CHD events (acute myocardial infarction [MI], CHD death, and hospitalization for angina or coronary revascularization). RESULTS: At baseline, 276 participants (13%) had minor and 506 (23%) had major ECG abnormalities. During follow-up, 351 participants had CHD events (96 CHD deaths, 101 acute MIs, and 154 hospitalizations for angina or coronary revascularizations). Both baseline minor and major ECG abnormalities were associated with an increased risk of CHD after adjustment for traditional risk factors (17.2 per 1000 person-years among those with no abnormalities; 29.3 per 1000 person-years; hazard ratio [HR], 1.35; 95% CI, 1.02-1.81; for minor abnormalities; and 31.6 per 1000 person-years; HR, 1.51; 95% CI, 1.20-1.90; for major abnormalities). When ECG abnormalities were added to a model containing traditional risk factors alone, 13.6% of intermediate-risk participants with both major and minor ECG abnormalities were correctly reclassified (overall net reclassification improvement [NRI], 7.4%; 95% CI, 3.1%-19.0%; integrated discrimination improvement, 0.99%; 95% CI, 0.32%-2.15%). After 4 years, 208 participants had new and 416 had persistent abnormalities. Both new and persistent ECG abnormalities were associated with an increased risk of subsequent CHD events (HR, 2.01; 95% CI, 1.33-3.02; and HR, 1.66; 95% CI, 1.18-2.34; respectively). When added to the Framingham Risk Score, the NRI was not significant (5.7%; 95% CI, -0.4% to 11.8%). CONCLUSIONS: Major and minor ECG abnormalities among older adults were associated with an increased risk of CHD events. Depending on the model, adding ECG abnormalities was associated with improved risk prediction beyond traditional risk factors.

Impact of early valve surgery on outcome of Staphylococcus aureus prosthetic valve infective endocarditis: analysis in the International Collaboration of Endocarditis-Prospective Cohort Study.

BACKGROUND: The impact of early valve surgery (EVS) on the outcome of Staphylococcus aureus (SA) prosthetic valve infective endocarditis (PVIE) is unresolved. The objective of this study was to evaluate the association between EVS, performed within the first 60 days of hospitalization, and outcome of SA PVIE within the International Collaboration on Endocarditis-Prospective Cohort Study. METHODS: Participants were enrolled between June 2000 and December 2006. Cox proportional hazards modeling that included surgery as a time-dependent covariate and propensity adjustment for likelihood to receive cardiac surgery was used to evaluate the impact of EVS and 1-year all-cause mortality on patients with definite left-sided S. aureus PVIE and no history of injection drug use. RESULTS: EVS was performed in 74 of the 168 (44.3%) patients. One-year mortality was significantly higher among patients with S. aureus PVIE than in patients with non-S. aureus PVIE (48.2% vs 32.9%; P = .003). Staphylococcus aureus PVIE patients who underwent EVS had a significantly lower 1-year mortality rate (33.8% vs 59.1%; P = .001). In multivariate, propensity-adjusted models, EVS was not associated with 1-year mortality (risk ratio, 0.67 [95% confidence interval, .39-1.15]; P = .15). CONCLUSIONS: In this prospective, multinational cohort of patients with S. aureus PVIE, EVS was not associated with reduced 1-year mortality. The decision to pursue EVS should be individualized for each patient, based upon infection-specific characteristics rather than solely upon the microbiology of the infection causing PVIE.

New statistical methods to assess the effect of time-dependent exposures in case-control studies

Contexte. Les études cas-témoins sont très fréquemment utilisées par les épidémiologistes pour évaluer l’impact de certaines expositions sur une maladie particulière. Ces expositions peuvent être représentées par plusieurs variables dépendant du temps, et de nouvelles méthodes sont nécessaires pour estimer de manière précise leurs effets. En effet, la régression logistique qui est la méthode conventionnelle pour analyser les données cas-témoins ne tient pas directement compte des changements de valeurs des covariables au cours du temps. Par opposition, les méthodes d’analyse des données de survie telles que le modèle de Cox à risques instantanés proportionnels peuvent directement incorporer des covariables dépendant du temps représentant les histoires individuelles d’exposition. Cependant, cela nécessite de manipuler les ensembles de sujets à risque avec précaution à cause du sur-échantillonnage des cas, en comparaison avec les témoins, dans les études cas-témoins. Comme montré dans une étude de simulation précédente, la définition optimale des ensembles de sujets à risque pour l’analyse des données cas-témoins reste encore à être élucidée, et à être étudiée dans le cas des variables dépendant du temps. Objectif: L’objectif général est de proposer et d’étudier de nouvelles versions du modèle de Cox pour estimer l’impact d’expositions variant dans le temps dans les études cas-témoins, et de les appliquer à des données réelles cas-témoins sur le cancer du poumon et le tabac. Méthodes. J’ai identifié de nouvelles définitions d’ensemble de sujets à risque, potentiellement optimales (le Weighted Cox model and le Simple weighted Cox model), dans lesquelles différentes pondérations ont été affectées aux cas et aux témoins, afin de refléter les proportions de cas et de non cas dans la population source. Les propriétés des estimateurs des effets d’exposition ont été étudiées par simulation. Différents aspects d’exposition ont été générés (intensité, durée, valeur cumulée d’exposition). Les données cas-témoins générées ont été ensuite analysées avec différentes versions du modèle de Cox, incluant les définitions anciennes et nouvelles des ensembles de sujets à risque, ainsi qu’avec la régression logistique conventionnelle, à des fins de comparaison. Les différents modèles de régression ont ensuite été appliqués sur des données réelles cas-témoins sur le cancer du poumon. Les estimations des effets de différentes variables de tabac, obtenues avec les différentes méthodes, ont été comparées entre elles, et comparées aux résultats des simulations. Résultats. Les résultats des simulations montrent que les estimations des nouveaux modèles de Cox pondérés proposés, surtout celles du Weighted Cox model, sont bien moins biaisées que les estimations des modèles de Cox existants qui incluent ou excluent simplement les futurs cas de chaque ensemble de sujets à risque. De plus, les estimations du Weighted Cox model étaient légèrement, mais systématiquement, moins biaisées que celles de la régression logistique. L’application aux données réelles montre de plus grandes différences entre les estimations de la régression logistique et des modèles de Cox pondérés, pour quelques variables de tabac dépendant du temps. Conclusions. Les résultats suggèrent que le nouveau modèle de Cox pondéré propose pourrait être une alternative intéressante au modèle de régression logistique, pour estimer les effets d’expositions dépendant du temps dans les études cas-témoins

A semi-Markov multistate model for estimation of the mean quality-adjusted survival for non-progressive processes

We discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models. We generalize an earlier work, considering the sojourn times in health states are not identically distributed, for a given vector of covariates. Approaches based on semiparametric and parametric (exponential and Weibull distributions) methodologies are considered. A simulation study is conducted to evaluate the performance of the proposed estimator and the jackknife resampling method is used to estimate the variance of such estimator. An application to a real data set is also included.

Estimation of the mean quality-adjusted survival using a multistate model for the sojourn times

In clinical trials, it may be of interest taking into account physical and emotional well-being in addition to survival when comparing treatments. Quality-adjusted survival time has the advantage of incorporating information about both survival time and quality-of-life. In this paper, we discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models for the sojourn times in health states. Semiparametric and parametric (with exponential distribution) approaches are considered. A simulation study is presented to evaluate the performance of the proposed estimator and the jackknife resampling method is used to compute bias and variance of the estimator. (C) 2007 Elsevier B.V. All rights reserved.

Does an evidence-based sedation protocol improve practice and patient outcomes in critical care?

Learning Objective 1: compare protocol-directed sedation management with traditional non-protocol-directed practice in mechanically ventilated patients in an Australian critical care.

Learning Objective 2: explain the contrasting international research findings on sedation protocol implementation.
Minimization of sedation in critical care patients has recently received widespread support. Professional organizations internationally have published sedation management guidelines for critically ill patients to improve the use of research in practice, decrease practice variability and shorten mechanical ventilation duration. Innovations in practice have included the introduction of decision making protocols, daily sedation interruptions and new drugs and monitoring technologies. The aim of this study was to compare protocol-directed sedation management with traditional non-protocol-directed practice in mechanically ventilated patients in an Australian critical care setting.

A randomized, controlled trial design was used to study 312 mechanically ventilated adult patients in a general critical care unit at an Australian metropolitan teaching hospital. Patients were randomly assigned to receive protocol directed sedation management developed from evidence based guidelines (n=153) or usual clinical practice (n=159).

The median (95% CI) duration of ventilation was 58 hrs (44–78 hrs) for patients in the non-protocol group and 79 hrs (56–93) for those patients in the protocol group (p=0.20). Results were not significant for length of stay in critical care or hospital, the frequency of tracheostomies, and unplanned extubations. A Cox proportional hazards model estimated that protocol directed sedation management was associated with a 22% decrease (95% CI: 40% decrease to 2% increase, p=0.07) in the occurrence of successful weaning from mechanical ventilation.

Few randomized controlled trials have evaluated the effectiveness of protocol-directed sedation outside of North America. This study highlights the lack of transferability between different settings and different models of care. Qualified, high intensity nursing in the Australian critical care setting facilitates rapid, responsive decisions for sedation management and an increased success rate for weaning from mechanical ventilation.

Psychosocial factors and survival of young women with breast cancer: a population-based prospective cohort study

Purpose: Most women with early-stage breast cancer believe that psychosocial factors are an important influence over whether their cancer will recur. Studies of the issue have produced conflicting results.

Patients and Methods: A population-based sample of 708 Australian women diagnosed before age 60 years with nonmetastatic breast cancer was observed for a median of 8.2 years. Depression and anxiety, coping style, and social support were assessed at a median of 11 months after diagnosis. Hazard ratios for distant disease-free survival (DDFS) and overall survival (OS) associated with psychosocial factors were estimated separately using Cox proportional hazards survival models, with and without adjustment for known prognostic factors.

Results: Distant recurrence occurred in 209 (33%) of 638 assessable patients, and 170 (24%) of 708 patients died during the follow-up period. There were no statistically significant associations between any of the measured psychosocial factors and DDFS or OS from the adjusted analyses. From unadjusted analyses, associations between greater anxious preoccupation and poorer DDFS and OS were observed (P = .02). These associations were no longer evident after adjustment for established prognostic factors; greater anxious preoccupation was associated with younger age at diagnosis (P = .03), higher tumor grade (P = .02), and greater number of involved axillary nodes (P = .008).

Conclusion: The findings do not support the measured psychosocial factors being an important influence on breast cancer outcomes. Interventions for adverse psychosocial factors are warranted to improve quality of life but should not be expected to improve survival.

Age at quitting smoking as a predictor of risk of cardiovascular disease incidence independent of smoking status, time since quitting and pack-years

Background: Risk prediction for CVD events has been shown to vary according to current smoking status, pack-years smoked over a lifetime, time since quitting and age at quitting. The latter two are closely and inversely related. It is not known whether the age at which one quits smoking is an additional important predictor of CVD events. The aim of this study was to determine whether the risk of CVD events varied according to age at quitting after taking into account current smoking status, lifetime pack-years smoked and time since quitting.
Findings. We used the Cox proportional hazards model to evaluate the risk of developing a first CVD event for a cohort of participants in the Framingham Offspring Heart Study who attended the fourth examination between ages 30 and 74 years and were free of CVD. Those who quit before the median age of 37 years had a risk of CVD incidence similar to those who were never smokers. The incorporation of age at quitting in the smoking variable resulted in better prediction than the model which had a simple current smoker/non-smoker measure and the one that incorporated both time since quitting and pack-years. These models demonstrated good discrimination, calibration and global fit. The risk among those quitting more than 5 years prior to the baseline exam and those whose age at quitting was prior to 44 years was similar to the risk among never smokers. However, the risk among those quitting less than 5 years prior to the baseline exam and those who continued to smoke until 44 years of age (or beyond) was two and a half times higher than that of never smokers.
Conclusions: Age at quitting improves the prediction of risk of CVD incidence even after other smoking measures are taken into account. The clinical benefit of adding age at quitting to the model with other smoking measures may be greater than the associated costs. Thus, age at quitting should be considered in addition to smoking status, time since quitting and pack-years when counselling individuals about their cardiovascular risk.

Epidemiologic merit of obese-years, the combination of degree and duration of obesity

This study aims to test the effect of combining the degree and the duration of obesity into a single variable-obese-years-and to examine whether obese-years is a better predictor of the risk of diabetes than simply body mass index (BMI) or duration of obesity. Of the original cohort of the Framingham Heart Study, 5,036 participants were followed up every 2 years for up to 48 years (from 1948). The variable, obese-years, was defined by multiplying for each participant the number of BMI units above 30 kg/m(2) by the number of years lived at that BMI. Associations with diabetes were analyzed by using time-dependent Cox proportional hazards regression models adjusted for potential confounders. The incidence of type-2 diabetes increased as the number of obese-years increased, with adjusted hazard ratios of 1.07 (95% confidence interval: 1.06, 1.09) per additional 10 obese-years. The dose-response relation between diabetes incidence and obese-years varied by sex and smoking status. The Akaike Information Criterion was lowest in the model containing obese-years compared with models containing either the degree or duration of obesity alone. A construct of obese-years is strongly associated with risk of diabetes and could be a better indicator of the health risks associated with increasing body weight than BMI or duration of obesity alone.

Influence functions of two families of robust estimators under proportional scatter matrices

In this paper, under a proportional model, two families of robust estimates for the proportionality constants, the common principal axes and their size are discussed. The first approach is obtained by plugging robust scatter matrices on the maximum likelihood equations for normal data. A projection- pursuit and a modified projection-pursuit approach, adapted to the proportional setting, are also considered. For all families of estimates, partial influence functions are obtained and asymptotic variances are derived from them. The performance of the estimates is compared through a Monte Carlo study. © 2006 Springer-Verlag.

The addition of depression to the Framingham Risk Equation model for predicting coronary heart disease risk in women

BACKGROUND: Depression is widely considered to be an independent and robust predictor of Coronary Heart Disease (CHD), however is seldom considered in the context of formal risk assessment. We assessed whether the addition of depression to the Framingham Risk Equation (FRE) improved accuracy for predicting 10-year CHD in a sample of women.

DESIGN: A prospective, longitudinal design comprising an age-stratified, population-based sample of Australian women collected between 1993 and 2011 (n=862).

METHODS: Clinical depressive disorder was assessed using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID-I/NP), using retrospective age-of-onset data. A composite measure of CHD included non-fatal myocardial infarction, unstable angina coronary intervention or cardiac death. Cox proportional-hazards regression models were conducted and overall accuracy assessed using area under receiver operating characteristic (ROC) curve analysis.

RESULTS: ROC curve analyses revealed that the addition of baseline depression status to the FRE model improved its overall accuracy (AUC:0.77, Specificity:0.70, Sensitivity:0.75) when compared to the original FRE model (AUC:0.75, Specificity:0.73, Sensitivity:0.67). However, when calibrated against the original model, the predicted number of events generated by the augmented version marginally over-estimated the true number observed.

CONCLUSIONS: The addition of a depression variable to the FRE equation improves the overall accuracy of the model for predicting 10-year CHD events in women, however may over-estimate the number of events that actually occur. This model now requires validation in larger samples as it could form a new CHD risk equation for women.

Shorter CAG repeat length in the AR gene is associated with poor outcome in head and neck cancer

Objective: Alterations in the size of the [CAG](n) repeats of the AR gene have been described in several types tumors. The purpose of this study was to evaluate if there is an association between the AR [CAG](n) repeat alleles and the relative risk for head and neck cancer and to analyse microsatellite instability (MSI) and loss of heterozygosity (LOH) in these tumors.Design: Matched samples of blood and head and neck tumors were evaluated using two methodologies, silver-stained gels to perform the analyses of MSI and LOH, and automated analysis to confirm these results and for genotyping of the AR [CAG](n), repeat length. Sixty-nine individuals without cancer were used as a control group for both procedures. The Log-rank test was used to compare overall survival and disease-free survival curves. The Cox proportional hazards regression models were performed to determine the [CAG], repeats as an independent prognostic factor.Results: Patients with alleles <= 20 in the male group showed a correlation with lower disease-free survival (P = 0.0325) and with recurrence or metastasis (RR 2.52, CI 95%). in the female group, the allele 2 (longer allele) showed a significant lower mean of [CAG](n), repeat when compared to the control group. Microsatellite instability was detected in nine cases in both procedures. In six out of these nine cases, we observed a reduction of the AR [CAG](n) repeat length. LOH was detected in one out of 17 women informative for oral cancer in both procedures.Conclusion: These results suggest that short [CAG](n) repeat length (: 20) polymorphism is associated with poor prognosis in a subset of male patients with head and neck cancer and that AR gene microsatellite instability is uncommon in these tumors. (C) 2007 Elsevier Ltd. All rights reserved.