Use of Cognitive Capacity in Reading: A Performance Operating Characteristic

The cognitive capacity used in cognitive tasks can be measured with a secondary task technique (also called the dual task technique). Interpretation of results obtained with this technique depends on the assumption that the primary and secondary tasks require the same limited-capacity cognitive processing system. The present experiment tested this assumption by constructing a performance operating characteristic, in which the allocation of processing resources for the primary and secondary tasks was varied by instructions, and performance on the two tasks was observed. As the quality of performance on one task increased, performance on the other task decreased. It was concluded that the primary and secondary tasks shared processing resources. This means that performance on one task can be used as an indicator of processing resources allocated to the other. Implications of performance operating characteristics for secondary task methodology were discussed.

Feeling angry about current health status: using a population survey to determine the association with demographic, health and social factors

BACKGROUND

Feeling angry about their health status may influence disease progression in individuals, creating a greater burden on the health care system. Identifying associations between different variables and feeling angry about health status may assist health professionals to improve health outcomes. This study used path analysis to explore findings from a population-based survey, informed by qualitative descriptions obtained from focus groups, to determine the prevalence of health-related anger within the community and variables associated with reporting health-related anger.

METHODS

A population-based Computer Assisted Telephone Interview (CATI) survey of 3003 randomly selected adults Australia-wide was conducted to examine the prevalence of health-related anger. A wide range of other covariates were included in the survey. Multivariable logistic regression and path analysis were undertaken to identify the relationships between different variables associated with feeling angry about the health status of people, to explore the direction of these associations and as a consequence of the results, consider implications for health service use and delivery.

RESULTS

Overall, 18.5 % of the population reported feeling angry about their health "some of the time", "most of the time" or "all of the time". People who felt angry about their health were more likely to have a severe health condition, at least one chronic condition, high psychological distress, fair to poor health status, and needed to adjust their daily lives because of a health condition. Having a tertiary level education was protective. Receiving some form of social support, usually from a support group, and not always doing as advised by a doctor, were also associated with a higher likelihood of being angry about their health.

CONCLUSIONS

People living with significant health problems are more likely to feel angry about their health. The path between illness and anger is, however, complex. Further research is needed to understand the extent that feeling angry influences the progression of health problems and, if necessary, how to minimise this progression. What also needs examining is whether identifying people who feel angry in the general population could be a predictor of persons most likely to develop significant health problems.

Cognitive Impairment Precedes and Predicts Functional Impairment in Mild Alzheimer's Disease

Background: The temporal relationship of cognitive deficit and functional impairment in Alzheimer’s disease (AD) is not well characterized. Recent analyses suggest cognitive decline predicts subsequent functional decline throughout AD progression.

Objective: To better understand the relationship between cognitive and functional decline in mild AD using autoregressive cross-lagged (ARCL) panel analyses in several clinical trials.

Methods: Data included placebo patients with mild AD pooled from two multicenter, double-blind, Phase 3 solanezumab (EXPEDITION/2) or semagacestat (IDENTITY/2) studies, and from AD patients participating in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Cognitive and functional outcomes were assessed using AD Assessment Scale-Cognitive subscale (ADAS-Cog), AD Cooperative Study-Activities of Daily Living instrumental subscale (ADCS-iADL), or Functional Activities Questionnaire (FAQ), respectively. ARCL panel analyses evaluated relationships between cognitive and functional impairment over time.

Results: In EXPEDITION, ARCL panel analyses demonstrated cognitive scores significantly predicted future functional impairment at 5 of 6 time points, while functional scores predicted subsequent cognitive scores in only 1 of 6 time points. Data from IDENTITY and ADNI programs yielded consistent results whereby cognition predicted subsequent function, but not vice-versa.

Conclusions: Analyses from three databases indicated cognitive decline precedes and predicts subsequent functional decline in mild AD dementia, consistent with previously proposed hypotheses, and corroborate recent publications using similar methodologies. Cognitive impairment may be used as a predictor of future functional impairment in mild AD dementia and can be considered a critical target for prevention strategies to limit future functional decline in the dementia process.

Cognitive and functional decline and their relationship in patients with mild Alzheimer's dementia

BACKGROUND

In patients with Alzheimer's disease (AD), the relationship between cognitive and functional progression is not fully understood; however, functional decline has been postulated to follow cognitive decline.

OBJECTIVE

To assess the relationship between cognitive and functional treatment effects in mild AD dementia patients.

METHODS

Data of patients with mild AD were pooled from two multicenter, double-blind, Phase 3 studies. Patients were randomized to infusions of 400-mg solanezumab (n = 654), or placebo (n = 660) every 4 weeks for 18 months. Cognitive and functional outcome measures were assessed using the AD Assessment Scale-Cognitive subscale (ADAS-Cog) and the AD Cooperative Study-Activities of Daily Living (ADCS-ADL), respectively. Analyses included comparisons among normalized scales, correlations between outcome measures, and path analyses to model the relationship of treatment effect on cognition and function.

RESULTS

Normalized ADAS-Cog and ADCS-ADL scales showed cognitive impairment was more evident than functional impairment in mild AD. The correlation between cognition and function increased over time. Path analyses demonstrated that 87% of the treatment effect on function was driven by the treatment effect on cognition, with the remaining 13% due to direct treatment effect.

CONCLUSION

Findings from this study are consistent with the hypothesis that functional impairment is primarily driven by and follows cognitive decline in mild AD dementia. The cognitive treatment effect appeared to explain the majority of the functional treatment effect. It is possible that a cognitive treatment effect may be considered as a leading indicator for functional outcomes in an 18-month clinical trial for milder stages of AD.

The efficacy of duloxetine, non-steroidal anti-inflammatory drugs, and opioids in osteoarthritis: a systematic literature review and meta-analysis

BACKGROUND

This meta-analysis assessed the efficacy of duloxetine versus other oral treatments used after failure of acetaminophen for management of patients with osteoarthritis.

METHODS

A systematic literature review of English language articles was performed in PUBMED, EMBASE, MedLine In-Process, Cochrane Library, and ClinicalTrials.gov between January 1985 and March 2013. Randomized controlled trials of duloxetine and all oral non-steroidal anti-inflammatory drugs and opioids were included if treatment was ≥12 weeks and the Western Ontario and McMaster Universities Index (WOMAC) total score was available. Studies were assessed for quality using the assessment tool from the National Institute for Health and Clinical Excellence guidelines for single technology appraisal submissions.WOMAC baseline and change from baseline total scores were extracted and standardized. A frequentist meta-analysis, meta-regression, and indirect comparison were performed using the DerSimonian-Laird and Bucher methods. Bayesian analyses with and without adjustment for study-level covariates were performed using noninformative priors.

RESULTS

Thirty-two publications reported 34 trials (2 publications each reported 2 trials) that met inclusion criteria. The analyses found all treatments except oxycodone (frequentist) and hydromorphone (frequentist and Bayesian) to be more effective than placebo. Indirect comparisons to duloxetine found no significant differences for most of the compounds. Some analyses showed evidence of a difference with duloxetine for etoricoxib (better), tramadol and oxycodone (worse), but without consistent results between analyses. Forest plots revealed positive trends in overall efficacy improvement with baseline scores. Adjusting for baseline, the probability duloxetine is superior to other treatments ranges between 15% to 100%.Limitations of this study include the low number of studies included in the analyses, the inclusion of only English language publications, and possible ecological fallacy associated with patient level characteristics.

CONCLUSIONS

This analysis suggests no difference between duloxetine and other post-first line oral treatments for osteoarthritis (OA) in total WOMAC score after approximately 12 weeks of treatment. Significant results for 3 compounds (1 better and 2 worse) were not consistent across performed analyses.

Lessons learnt from the first Australian ‘pop-up' HIV testing site

Lessons learnt from the first ‘pop-up’ HIV testing site in Australia suggest that highly visible testing activity was acceptable in the context of inner Sydney and that pop-up sites may be a useful adjunct to clinic-based models. Further evaluation of alternative testing models is needed to inform the scale up of HIV testing in Australia.

Evaluating the impact of unmeasured confounding with internal validation data: an example cost evaluation in type 2 diabetes

The quantitative assessment of the potential influence of unmeasured confounders in the analysis of observational data is rare, despite reliance on the "no unmeasured confounders" assumption. In a recent comparison of costs of care between two treatments for type 2 diabetes using a health care claims database, propensity score matching was implemented to adjust for selection bias though it was noted that information on baseline glycemic control was not available for the propensity model. Using data from a linked laboratory file, data on this potential "unmeasured confounder" were obtained for a small subset of the original sample. By using this information, we demonstrate how Bayesian modeling, propensity score calibration, and multiple imputation can utilize this additional information to perform sensitivity analyses to quantitatively assess the potential impact of unmeasured confounding. Bayesian regression models were developed to utilize the internal validation data as informative prior distributions for all parameters, retaining information on the correlation between the confounder and other covariates. While assumptions supporting the use of propensity score calibration were not met in this sample, the use of Bayesian modeling and multiple imputation provided consistent results, suggesting that the lack of data on the unmeasured confounder did not have a strong impact on the original analysis, due to the lack of strong correlation between the confounder and the cost outcome variable. Bayesian modeling with informative priors and multiple imputation may be useful tools for unmeasured confounding sensitivity analysis in these situations. Further research to understand the operating characteristics of these methods in a variety of situations, however, remains.

Clostridium difficile prevalence rates in a large healthcare system stratified according to patient population, age, gender, and specimen consistency

We evaluated Clostridium difficile prevalence rates in 2,807 clinically indicated stool specimens stratified by inpatient (IP), nursing home patient (NH), outpatient (OP), age, gender, and specimen consistency using bacterial culture, toxin detection, and polymerase chain reaction (PCR) ribotyping. Rates were determined based on the detection of toxigenic C. difficile isolates. We identified significant differences in the rates between patient populations and with age. Specimens from NH had a higher rate (46%) for toxigenic C. difficile than specimens from IP (18%) and OP (17%). There were no gender-related differences in the rates. Liquid specimens had a lower rate (15%) than partially formed and soft specimens (25%) and formed specimens (18%) for the isolation of toxigenic C. difficile. The nontoxigenic rate was lowest for NH (4%) and highest for patients<20 years of age (23%). We identified 31 different toxigenic ribotypes from a sampling of 190 isolates that showed the lowest diversity in NH. Fluoroquinolone resistance was observed in 93% of the 027 isolates, all of the 053 isolates, and in four other ribotypes. We observed different rates for toxigenic C. difficile in stratified patient populations, with the highest rate for NH, a low overall nontoxigenic rate, and fluoroquinolone resistance.

An integrated QSAR-PBPK modelling approach for predicting the inhalation toxicokinetics of mixtures of volatile organic chemicals in the rat

The objective of this study was to predict the inhalation toxicokinetics of chemicals in mixtures using an integrated QSAR-PBPK modelling approach. The approach involved: (1) the determination of partition coefficients as well as V(max) and K(m) based solely on chemical structure for 53 volatile organic compounds, according to the group contribution approach; and (2) using the QSAR-driven coefficients as input in interaction-based PBPK models in the rat to predict the pharmacokinetics of chemicals in mixtures of up to 10 components (benzene, toluene, m-xylene, o-xylene, p-xylene, ethylbenzene, dichloromethane, trichloroethylene, tetrachloroethylene, and styrene). QSAR-estimated values of V(max) varied compared with experimental results by a factor of three for 43 out of 53 studied volatile organic compounds (VOCs). K(m) values were within a factor of three compared with experimental values for 43 out of 53 VOCs. Cross-validation performed as a ratio of predicted residual sum of squares and sum of squares of the response value indicates a value of 0.108 for V(max) and 0.208 for K(m). The integration of QSARs for partition coefficients, V(max) and K(m), as well as setting the K(m) equal to K(i) (metabolic inhibition constant) within the mixture PBPK model allowed to generate simulations of the inhalation pharmacokinetics of benzene, toluene, m-xylene, o-xylene, p-xylene, ethylbenzene, dichloromethane, trichloroethylene, tetrachloroethylene and styrene in various mixtures. Overall, the present study indicates the potential usefulness of the QSAR-PBPK modelling approach to provide first-cut evaluations of the kinetics of chemicals in mixtures of increasing complexity, on the basis of chemical structure.