Sex differences in neurocognitive abilities have been extensively explored both in the healthy population and in many disorders. Until recently, however, little work has examined such differences in people with Alzheimer's disease (AD). This is despite clear evidence that AD is more prevalent in women, and converging lines of evidence from brain imaging, post-mortem analyses, hormone therapy and genetics suggesting that AD affects men and women differently. We provide an overview of evidence attesting to the poorer cognitive profiles in women than in men at the same stage of AD. Indeed, men significantly outperform women in several cognitive domains, including: Language and semantic abilities, visuospatial abilities and episodic memory. These differences do not appear to be attributable to any differences in age, education, or dementia severity. Reasons posited for this female disadvantage include a reduction of estrogen in postmenopausal women, greater cognitive reserve in men, and the influence of the apolipoprotein E ε4 allele. Assessment of cognitive abilities contributes to the diagnosis of the condition and thus, it is crucial to identify the role of sex differences if potentially more accurate diagnoses and treatments are to emerge.
Studies reporting on the cognitive abilities of men and women with Alzheimer's disease (AD) are surprisingly rare. We carried out a meta-analysis of neurocognitive data from 15 studies (n = 828 men; 1,238 women), which revealed a consistent male advantage on verbal and visuospatial tasks and tests of episodic and semantic memory. Moderator regression analyses showed that age, education level, and dementia severity did not significantly predict the male advantage. Reasons posited for this advantage include a reduction of estrogen in postmenopausal women, sex differences in AD pathology, and greater cognitive reserve in men.
Data-driven discovery in complex neurological disorders has potential to extract meaningful syndromic knowledge from large, heterogeneous data sets to enhance potential for precision medicine. Here we describe the application of topological data analysis (TDA) for data-driven discovery in preclinical traumatic brain injury (TBI) and spinal cord injury (SCI) data sets mined from the Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI) repository. Through direct visualization of inter-related histopathological, functional and health outcomes, TDA detected novel patterns across the syndromic network, uncovering interactions between SCI and co-occurring TBI, as well as detrimental drug effects in unpublished multicentre preclinical drug trial data in SCI. TDA also revealed that perioperative hypertension predicted long-term recovery better than any tested drug after thoracic SCI in rats. TDA-based data-driven discovery has great potential application for decision-support for basic research and clinical problems such as outcome assessment, neurocritical care, treatment planning and rapid, precision-diagnosis.
BackgroundMany patients demonstrate psychological distress and reduced physical activity before coronary artery bypass graft surgery (CABG). Here we evaluated the addition of a brief, cognitive-behavioural intervention (the HeartOp Programme) to routine nurse counselling for people waiting for CABG surgery.MethodsRandomised controlled trial comparing nurse counselling with the HeartOp programme to routine nurse counselling in 204 patients awaiting first time elective CABG. Primary outcome measures were: anxiety and length of hospital stay; secondary outcome measures were: depression, physical functioning, cardiac misconceptions and cost utility. Measures were collected prior to randomisation and after 8 weeks of their intervention prior to surgery, excepting length of hospital stay which was collected after discharge following surgery.Results100 patients were randomised to intervention, 104 to control. At follow-up there were no differences in anxiety or length of hospital stay. There were significant differences in depression (difference = 7.79, p = 0.008, 95% CI = 2.04–13.54), physical functioning (difference = 0.82, p = 0.001, 95%CI = 0.34–1.3) and cardiac misconceptions (difference = 2.56, p < 0.001, 95%CI = 1.64–3.48) in favour of the HeartOp Programme. The only difference to be maintained following surgery was in cardiac misconceptions. The HeartOp Programme was found to have an Incremental Cost Effectiveness Ratio (ICER) of £288.83 per Quality-Adjusted Life Year.ConclusionsNurse counselling with the HeartOp Programme reduces depression and cardiac misconceptions and improves physical functioning before bypass surgery significantly more than nurse counselling alone and meets the accepted criteria for cost efficacy.
Spinal cord injury (SCI) and other neurological disorders involve complex biological and functional changes. Well-characterized preclinical models provide a powerful tool for understanding mechanisms of disease; however managing information produced by experimental models represents a significant challenge for translating findings across research projects and presents a substantial hurdle for translation of novel therapies to humans. In the present work we demonstrate a novel ‘syndromic’ information-processing approach for capitalizing on heterogeneous data from diverse preclinical models of SCI to discover translational outcomes for therapeutic testing. We first built a large, detailed repository of preclinical outcome data from 10 years of basic research on cervical SCI in rats, and then applied multivariate pattern detection techniques to extract features that are conserved across different injury models. We then applied this translational knowledge to derive a data-driven multivariate metric that provides a common ‘ruler’ for comparisons of outcomes across different types of injury (NYU/MASCIS weight drop injuries, Infinite Horizons (IH) injuries, and hemisection injuries). The findings revealed that each individual endpoint provides a different view of the SCI syndrome, and that considering any single outcome measure in isolation provides a misleading, incomplete view of the SCI syndrome. This limitation was overcome by taking a novel multivariate integrative approach for leveraging complex data from preclinical models of neurological disease to identify therapies that target multiple outcomes. We suggest that applying this syndromic approach provides a roadmap for translating therapies for SCI and other complex neurological diseases.
Evidence is steadily and increasingly accumulating to confirm the poorer cognitive outcome for women than men with Alzheimer's disease. Although small in size, the effects occur across a broad range of cognitive domains including visuospatial, verbal, episodic memory, and semantic memory - some of which typically reveal a sex-related processing advantage for healthy women. Explanations have been linked to a variety of factors including differences in cognitive reserve, resilience, as well as genetics (apolipoprotein ε4) and functional and structural brain changes. Sex-related differences in risk factors, resilience, cognitive reserve, and rates of deterioration have implications for clinical practice.
The IBB scale is a recently developed forelimb scale for the assessment of fine control of the forelimb and digits after cervical spinal cord injury [SCI; (1)]. The present paper describes the assessment of inter-rater reliability and face, concurrent and construct validity of this scale following SCI. It demonstrates that the IBB is a reliable and valid scale that is sensitive to severity of SCI and to recovery over time. In addition, the IBB correlates with other outcome measures and is highly predictive of biological measures of tissue pathology. Multivariate analysis using principal component analysis (PCA) demonstrates that the IBB is highly predictive of the syndromic outcome after SCI (2), and is among the best predictors of bio-behavioral function, based on strong construct validity. Altogether, the data suggest that the IBB, especially in concert with other measures, is a reliable and valid tool for assessing neurological deficits in fine motor control of the distal forelimb, and represents a powerful addition to multivariate outcome batteries aimed at documenting recovery of function after cervical SCI in rats.
Efforts to understand spinal cord injury (SCI) and other complex neurotrauma disorders at the pre-clinical level have shown progress in recent years. However, successful translation of basic research into clinical practice has been slow, partly because of the large, heterogeneous data sets involved. In this sense, translational neurological research represents a "big data" problem. In an effort to expedite translation of pre-clinical knowledge into standards of patient care for SCI, we describe the development of a novel database for translational neurotrauma research known as Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI). We present demographics, descriptive statistics, and translational syndromic outcomes derived from our ongoing efforts to build a multi-center, multi-species pre-clinical database for SCI models. We leveraged archived surgical records, postoperative care logs, behavioral outcome measures, and histopathology from approximately 3000 mice, rats, and monkeys from pre-clinical SCI studies published between 1993 and 2013. The majority of animals in the database have measures collected for health monitoring, such as weight loss/gain, heart rate, blood pressure, postoperative monitoring of bladder function and drug/fluid administration, behavioral outcome measures of locomotion, and tissue sparing postmortem. Attempts to align these variables with currently accepted common data elements highlighted the need for more translational outcomes to be identified as clinical endpoints for therapeutic testing. Last, we use syndromic analysis to identify conserved biological mechanisms of recovery after cervical SCI between rats and monkeys that will allow for more-efficient testing of therapeutics that will need to be translated toward future clinical trials.
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