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Transcranial magnetic stimulation (TMS) is a non-invasive technique for focal brain stimulation based on electromagnetic induction where a fluctuating magnetic field induces a small intracranial electric current in the brain. For more than 35 years, TMS has shown promise in the diagnosis and treatment of neurological and psychiatric disorders in adults. In this review, we provide a brief introduction to the TMS technique with a focus on repetitive TMS (rTMS) protocols, particularly theta-burst stimulation (TBS), and relevant rTMS-derived metrics of brain plasticity. We then discuss the TMS-EEG technique, the use of neuronavigation in TMS, the neural substrate of TBS measures of plasticity, the inter- and intraindividual variability of those measures, effects of age and genetic factors on TBS aftereffects, and then summarize alterations of TMS-TBS measures of plasticity in major neurological and psychiatric disorders including autism spectrum disorder, schizophrenia, depression, traumatic brain injury, Alzheimer’s disease, and diabetes. Finally, we discuss the translational studies of TMS-TBS measures of plasticity and their therapeutic implications.

Background Delivering interventions is the main task of health systems whose accurate measurement is an essential input into tracking performance. Recently, the concept of effective coverage was introduced by World Health Organization to incorporate into health system performance assessment. The aim of present scoping review was mapping the key elements and steps of effective coverage assessment in practical efforts including kinds of interventions, criteria for selecting them and the need, use and quality estimation approaches and strategies of each intervention. Methods We conducted a scoping review of health system/program assessments which assessed effective coverage till May 2017. Seven databases were systematically searched with no time and language restriction through applying combined keyword of “effective coverage”. Results Eighteen studies contributed findings on monitoring effective coverage of health interventions and they all were included in the review. Only 4 contributed findings on health system and the others were related to specific intervention(s) assessment. The interventions monitored by effective coverage were mainly in child health, prenatal and antenatal care and delivery, and chronic conditions areas. Potential impact on the burden of disease, leading causes of mortality and morbidity, and high occurrence and prevalence rate were among the main intervention selection criteria. Availability of data was the critical prerequisite, especially, in all of the studies applied ex post approach in estimating effective coverage. Estimation based on a norm, self- reporting from surveys and biomarkers were the main strategies and methods of need, utilization and quality measurement, respectively. Conclusions More studies are needed to contribute to the ongoing improvement in the development of effective coverage concept and increasing practical efforts, especially through defining prospective approaches and strategies into estimation of composite measures based on the effective coverage framework. Also, further attention needs to be paid to quality measures of effective coverage in a manner that better conceptualizes and measures the connection between coverage rates and interventions’ effectiveness. At the administrative system level, more innovation is needed to develop data systems in order to enhance capacity of routine health service information.

Transcranial magnetic stimulation (TMS) can be used to assess neurophysiology and the mechanisms of cortical brain plasticity in humans . As the use of these measures in specific populations (e.g., Alzheimer's disease; AD) increases, it is critical to understand their reproducibility (i.e., test-retest reliability) in the populations of interest. Reproducibility of TMS measures was evaluated in older adults, including healthy, AD, and Type-2 diabetes mellitus (T2DM) groups. Participants received two identical neurophysiological assessments within a year including motor thresholds, baseline motor evoked potentials (MEPs), short- and long-interval intracortical inhibition (SICI, LICI) and intracortical facilitation (ICF), and MEP changes following intermittent theta-burst stimulation (iTBS). Cronbach's α coefficients were calculated to assess reproducibility. Multiple linear regression analyses were used to investigate factors related to intraindividual variability. Reproducibility was highest for motor thresholds, followed by baseline MEPs, SICI and LICI, and was lowest for ICF and iTBS aftereffects. The AD group tended to show higher reproducibility than T2DM or controls. Intraindividual variability of baseline MEPs was related to age and variability of RMT, while the intraindividual variability in post-iTBS measures was related to baseline MEP variability, intervisit duration, and Brain-derived neurotrophic factor ( ) polymorphism. Increased reproducibility in AD may reflect pathophysiological declines in the efficacy of neuroplastic mechanisms. Reproducibility of iTBS aftereffects can be improved by keeping baseline MEPs consistent, controlling for genotype, and waiting at least a week between visits. These findings provide the first direct assessment of reproducibility of TMS measures in older clinical populations. Reproducibility coefficients may be used to adjust effect- and sample size calculations for future studies.

Background Disease-modifying treatments for Alzheimer’s disease highlight the need for early detection of cognitive decline. However, at present, most primary care providers do not perform routine cognitive testing, in part due to a lack of access to practical cognitive assessments, as well as time and resources to administer and interpret the tests. Brief and sensitive digital cognitive assessments, such as the Digital Clock and Recall (DCR™), have the potential to address this need. Here, we examine the advantages of DCR over the Mini-Mental State Examination (MMSE) in detecting mild cognitive impairment (MCI) and mild dementia. Methods We studied 706 participants from the multisite Bio-Hermes study (age mean ± SD = 71.5 ± 6.7; 58.9% female; years of education mean ± SD = 15.4 ± 2.7; primary language English), classified as cognitively unimpaired (CU; n  = 360), mild cognitive impairment (MCI; n  = 234), or probable mild Alzheimer’s dementia (pAD; n  = 111) based on a review of medical history with selected cognitive and imaging tests. We evaluated cognitive classifications (MCI and early dementia) based on the DCR and the MMSE against cohorts based on the results of the Rey Auditory Verbal Learning Test (RAVLT), the Trail Making Test-Part B (TMT-B), and the Functional Activities Questionnaire (FAQ). We also compared the influence of demographic variables such as race (White vs. Non-White), ethnicity (Hispanic vs. Non-Hispanic), and level of education (≥ 15 years vs. < 15 years) on the DCR and MMSE scores. Results The DCR was superior on average to the MMSE in classifying mild cognitive impairment and early dementia, AUC = 0.70 for the DCR vs. 0.63 for the MMSE. DCR administration was also significantly faster (completed in less than 3 min regardless of cognitive status and age). Among 104 individuals who were labeled as “cognitively unimpaired” by the MMSE (score ≥ 28) but actually had verbal memory impairment as confirmed by the RAVLT, the DCR identified 84 (80.7%) as impaired. Moreover, the DCR score was significantly less biased by ethnicity than the MMSE, with no significant difference in the DCR score between Hispanic and non-Hispanic individuals. Conclusions DCR outperforms the MMSE in detecting and classifying cognitive impairment—in a fraction of the time—while being not influenced by a patient’s ethnicity. The results support the utility of DCR as a sensitive and efficient cognitive assessment in primary care settings. Trial registration ClinicalTrials.gov identifier NCT04733989.

The utility of continuous theta-burst stimulation (cTBS) as index of cortical plasticity is limited by inadequate characterization of its test-retest reliability. We thus evaluated the reliability of cTBS aftereffects, and explored the roles of age and common single-nucleotide polymorphisms in the brain-derived neurotrophic factor ( ) and apolipoprotein E ( ) genes. Twenty-eight healthy adults (age range 21-65) underwent two identical cTBS sessions (median interval = 9.5 days) targeting the motor cortex. Intraclass correlation coefficients (ICCs) of the log-transformed, baseline-corrected amplitude of motor evoked potentials (ΔMEP) at 5-60 min post-cTBS (T5-T60) were calculated. Adjusted effect sizes for cTBS aftereffects were then calculated by taking into account the reliability of each cTBS measure. ΔMEP at T50 was the most-reliable cTBS measure in the whole sample (ICC = 0.53). Area under-the-curve (AUC) of ΔMEPs was most reliable when calculated over the full 60 min post-cTBS (ICC = 0.40). cTBS measures were substantially more reliable in younger participants (< 35 years) and in those with Val66Val and ε4- genotypes. cTBS aftereffects are most reliable when assessed 50 min post-cTBS, or when cumulative ΔMEP measures are calculated over 30-60 min post-cTBS. Reliability of cTBS aftereffects is influenced by age, and and polymorphisms. Reliability coefficients are used to adjust effect-size calculations for interpretation and planning of cTBS studies.

By 2050, 1 in 4 people worldwide will be living with hearing impairment. We propose a digital Speech Hearing Screener (dSHS) using short nonsense word recognition to measure speech-hearing ability. The importance of hearing screening is increasing due to the anticipated increase in individuals with hearing impairment globally. We compare dSHS outcomes with standardized pure-tone averages (PTA) and speech-recognition thresholds (SRT). Fifty participants (aged 55 or older underwent pure-tone and speech-recognition thresholding. One-way ANOVA was used to compare differences between hearing impaired and hearing not-impaired groups, by the dSHS, with a clinical threshold of moderately impaired hearing at 35 dB and severe hearing impairment at 50 dB. dSHS results significantly correlated with PTAs/SRTs. ANOVA results revealed the dSHS was significantly different (F(1,47) = 38.1, p < 0.001) between hearing impaired and unimpaired groups. Classification analysis using a 35 dB threshold, yielded accuracy of 85.7% for PTA-based impairment and 81.6% for SRT-based impairment. At a 50 dB threshold, dSHS classification accuracy was 79.6% for PTA-based impairment (Negative Predictive Value (NPV)-93%) and 83.7% (NPV-100%) for SRT-based impairment. The dSHS successfully differentiates between hearing-impaired and unimpaired individuals in under 3 min. This hearing screener offers a time-saving, in-clinic hearing screening to streamline the triage of those with likely hearing impairment to the appropriate follow-up assessment, thereby improving the quality of services. Future work will investigate the ability of the dSHS to help rule out hearing impairment as a cause or confounder in clinical and research applications.

Dual task paradigms are thought to offer a quantitative means to assess cognitive reserve and the brain's capacity to allocate resources in the face of competing cognitive demands. The most common dual task paradigms examine the interplay between gait or balance control and cognitive function. However, gait and balance tasks can be physically challenging for older adults and may pose a risk of falls. We introduce a novel, digital dual-task assessment that combines a motor-control task (the \"ball balancing\" test), which challenges an individual to maintain a virtual ball within a designated zone, with a concurrent cognitive task (the backward digit span task [BDST]). The task was administered on a touchscreen tablet, performance was measured using the inertial sensors embedded in the tablet, conducted under both single- and dual-task conditions. The clinical use of the task was evaluated on a sample of 375 older adult participants (n=210 female; aged 73.0, SD 6.5 years). All older adults, including those with mild cognitive impairment (MCI) and Alzheimer disease-related dementia (ADRD), and those with poor balance and gait problems due to diabetes, osteoarthritis, peripheral neuropathy, and other causes, were able to complete the task comfortably and safely while seated. As expected, task performance significantly decreased under dual task conditions compared to single task conditions. We show that performance was significantly associated with cognitive impairment; significant differences were found among healthy participants, those with MCI, and those with ADRD. Task results were significantly associated with functional impairment, independent of diagnosis, degree of cognitive impairment (as indicated by the Mini Mental State Examination [MMSE] score), and age. Finally, we found that cognitive status could be classified with >70% accuracy using a range of classifier models trained on 3 different cognitive function outcome variables (consensus clinical judgment, Rey Auditory Verbal Learning Test [RAVLT], and MMSE). Our results suggest that the dual task ball balancing test could be used as a digital cognitive assessment of cognitive reserve. The portability, simplicity, and intuitiveness of the task suggest that it may be suitable for unsupervised home assessment of cognitive function.

Alzheimer's disease and related dementias (ADRD) represent a substantial global public health challenge with multifaceted impacts on individuals, families, and healthcare systems. Brief cognitive screening tools such as the Mini-Cog© can help improve recognition of ADRD in clinical practice, but widespread adoption continues to lag. We compared the Digital Clock and Recall (DCR), a next-generation process-driven adaptation of the Mini-Cog, with the original paper-and-pencil version in a well-characterized clinical trial sample. DCR was administered to 828 participants in the Bio-Hermes-001 clinical trial (age median ± SD = 72 ± 6.7, IQR = 11; 58% female) independently classified as cognitively unimpaired (  = 364) or as having mild cognitive impairment (MCI,  = 274) or dementia likely due to AD (DLAD,  = 190). MCI and DLAD cohorts were combined into a single impaired group for analysis. Two experienced neuropsychologists rated verbal recall accuracy and digitally drawn clocks using the original Mini-Cog scoring rules. Inter-rater reliability of Mini-Cog scores was computed for a subset of the data (  = 508) and concordance between Mini-Cog rule-based and DCR scoring was calculated. Inter-rater reliability of Mini-Cog scoring was good to excellent, but Rater 2's scores were significantly higher than Rater 1's due to variation in clock scores (  < 0.0001). Mini-Cog and DCR scores were significantly correlated (  = 0.71,  < 0.0001). However, using a Mini-Cog cut score of 4, the DCR identified more cases of cognitive impairment (  = 47;  = 13.26,  < 0.0005) and Mini-Cog missed significantly more cases of cognitive impairment (  = 87). In addition, the DCR correctly classified significantly more cognitively impaired cases missed by the Mini-Cog (  = 44) than vice versa (  = 4;  = 21.69,  < 0.0001). Our findings demonstrate higher sensitivity of the DCR, an automated, process-driven, and process-based digital adaptation of the Mini-Cog. Digital metrics capture clock drawing dynamics and increase detection of diagnosed cognitive impairment in a clinical trial cohort of older individuals.

BACKGROUND:The World Health Organization (WHO) considers a safe operating room as one of the necessities of hospitals that support patients. Achieving safety in surgical operations in all countries of the world is the basic goal of healthcare centers and organizations; hence, the present study investigated the challenges and prerequisites for the implementation of an active risk management program in the operating rooms of Iranian hospitals.MATERIALS AND METHODS:This qualitative-phenomenological study was conducted in 2022. Data were collected using semi-structured interviews, targeted sampling, and the participation of 20 experts (health policy and management experts and academic officials and faculty members of universities) and executive staff (nurses and operating room technicians, doctors and surgical specialists, and officials of surgical departments) and were analyzed using the framework analysis method.RESULTS:In the resulting qualitative study, the challenges and prerequisites for active risk management in the operating room from the point of view of experts and executive staff were divided into three sub-themes. These three themes include managerial challenges and prerequisites, organizational resources (financial resources, human resources, equipment, and facilities), and cultural issues.CONCLUSION:Considering managerial prerequisites, organizational resources (financial, human, equipment, and facilities), cultural issues, and removing challenges, an active risk management program in the operating room can be implemented correctly. With the correct implementation of this program, injuries in the operating room for personnel and patients will be greatly reduced, and the satisfaction of beneficiaries and the productivity of the hospital will be greatly increased.

Background Early identification of cognitive impairment and brain pathology associated with Alzheimer’s disease (AD) is essential to maximize benefits from lifestyle interventions and emerging pharmacologic disease-modifying treatments (DMT). Digital cognitive assessments (DCAs) can quickly capture an array of metrics that can be used to train machine-learning (ML) models to concurrently evaluate different outcomes. DCAs have the potential to optimize clinical workflows and enable efficient assessment of cognitive function and the likelihood of a given underlying pathology. Methods We assessed the ability of a multimodal ML-enabled DCA, the Digital Clock and Recall (DCR), to concurrently estimate brain amyloid-beta (Aβ) status and detect cognitive impairment, as compared with traditional cognitive assessments, including the MMSE, RAVLT, a DCA, Cognivue ® , and blood-based biomarkers in 930 participants from the Bio-Hermes-001 clinical study. Results Aβ42/40, p-tau181, APS, and p-tau217 poorly classified cognitive impairment (AUCs: 0.61; 0.63; 0.63; 0.70, respectively), but accurately classified Aβ status (AUCs: 0.81; 0.78; 0.85, 0.89, respectively). MMSE, RAVLT, and Cognivue poorly classified Aβ status (AUCs: 0.70, 0.73, 0.70, respectively). However, separate multimodal, DCR-based ML classification models, run in parallel, accurately classified both cognitive impairment (AUC = 0.83) and Aβ-PET status (AUC = 0.81). Conclusions DCAs that leverage digital technologies to generate advanced metrics, such as the DCR, enable accurate and efficient detection of cognitive impairment associated with AD pathology. They have the potential to empower health systems and primary care providers to help their patients make timely treatment decisions.