Impact of early vs delayed initiation of dual antimicrobial salvage therapy on clinical outcomes in MRSA bacteremia.

The global trend of population aging has led to a notable rise in dementia incidence, particularly Alzheimer's disease (AD), which has become a crucial public health concern. At present, dementia affects more than 50 million people around the world. In China alone, there are over 13 million cases, which is more than one-quarter of the global total. Estimates indicate that by 2050, the number of patients suffering from AD in China will exceed 30 million. Dementia is mainly caused by AD, accounting for approximately 60–80% of cases. Clinical trajectory models indicate that the pace of cognitive decline is expected to rise significantly starting from the mild cognitive impairment (MCI) stage. MCI, a vital intermediate stage between normal aging and dementia, impacts around 20% of the elderly population worldwide. Every year, 10% to 15% of those with MCI develop dementia, bringing significant economic and care giving pressures to individuals, families, and society. Consequently, identifying and dealing with problems during the MCI period or even earlier at the subjective cognitive decline (SCD) stage is an essential approach for decelerating disease development and lessening the incidence of dementia. Currently, the diagnosis and screening of MCI and SCD mainly rely on neuropsychological evaluations like the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). However, these instruments have substantial drawbacks: they consume a great deal of time, require trained staff for implementation, and their results can be affected by the educational and cultural backgrounds of the evaluated individuals. Furthermore, they might not possess the necessary sensitivity to detect extremely early and subtle cognitive alterations. Even though biomarkers, like cerebrospinal fluid Aβ/tau and amyloid positron emission tomography (PET) imaging, offer high diagnostic precision, their utilization is restricted by high expenses, invasive processes or radiation exposure, and limited availability, thus decreasing their practicality for extensive population screening. Hence, there is a critical demand for the creation of new screening devices that are objective, uncomplicated, cost-efficient, and easily expandable to fulfill the increasing need for early identification of cognitive risks among the aging population. The neural networks responsible for higher cognitive functions such as executive functioning, attention, and working memory exhibit considerable overlap with those that regulate gait and eye movement control. The neural substrate shared by cognitive and motor functions, which is involved in the relevant neural circuitry, mainly consists of the prefrontal cortex, parietal lobe, basal ganglia, and cerebellum. This shared neural basis offers a theoretical foundation for using behavioral metrics to explore early cognitive decline. Dual-task gait paradigms have been shown to more effectively reveal underlying deficits in executive function and divided attention compared to single-task walking. This is due to the increased cognitive load, which amplifies the competition for resources between motor and cognitive systems. A meta-analysis indicated that under single-task conditions, gait parameters such as speed, stride length, stride time, and its coefficient of variation were the most effective in distinguishing individuals with MCI from healthy controls. However, dual-task assessments further enhanced this discriminative capability. Notably, dual-task walking combined with a counting task demonstrated greater sensitivity (Cohen's d range 0.84–1.35) than verbal fluency tasks, such as fruit naming (d range 0.65–0.94). Another study found that the area under the receiver operating characteristic curve (AUC) for dual-task gait tests in distinguishing MCI ranged from 0.78 to 0.79, with high test-retest reliability, indicating their potential utility in MCI screening. Utilizing a one-versus-one support vector machine with majority voting and gait features extracted from an electronic walkway, Boettcher et al. achieved an accuracy of 86.0% in differentiating cognitively impaired individuals from healthy controls. Collectively, these findings underscore the efficacy of dual-task gait assessments in the early detection of cognitive impairments.