Faculty Bibliography

BACKGROUND:We have described the clinical stages of the brain aging and Alzheimer's disease (AD) continuum. In terms of the pre-dementia stages of AD, we introduced the terminology "mild cognitive impairment" (MCI) for the first pre-dementia stage and "subjective cognitive decline" (SCD) for the pre-MCI stage. We now report the characteristics of a pre-SCD condition eventuating in likely AD. OBJECTIVE:The aim of this study was to characterize a pre-SCD condition eventuating in AD. METHOD/METHODS:Sixty healthy persons with "no cognitive decline" (NCD) were recruited and 47 were followed (mean baseline age, 64.1 ± 8.9 years; mean follow-up time, 6.7 ± 3.1 years). Outcome was determined at the final assessment prior to 2002 as "decliner," if SCD or worse, or "nondecliner" if NCD. RESULTS:After controlling for age, gender, years of education, and follow-up time, there was a between-group difference in the decline rate (p < 0.001). Also, after controlling for demographic variables and follow-up time, the combinatorial psychometric score was lower at baseline in the future decliners (p = 0.035). Of the 9 psychometric variables, after controlling for demographic variables and follow-up time, 3 were significantly lower at baseline in future decliners. Since AD is known to be age related and all subjects in this study were otherwise healthy, we also did an analysis without controlling for age. The combinatorial psychometric score was highly significantly better at baseline in the future nondecliners than in the future decliners (p = 0.008). CONCLUSION/CONCLUSIONS:This is ostensibly the first study to link psychometric cognitive decline to the subsequent SCD stage of eventual AD.

BACKGROUND:Coronavirus (CoV) disease (COVID)-19 poses difficult situations in which the ethical course of action is not clear, or choices are made between equally unacceptable responses. METHODS:A web search was performed using the terms "bioethics; COVID-19; ethics; severe acute respiratory syndrome CoV-2; emergent care; pandemic; and public health emergencies." RESULTS:Protection from COVID-19 has resulted in the cancellation of necessary medical interventions, lengthened suffering, and potential non-COVID-19 deaths. Prolonged lockdown reduced well-being, triggering or aggravating mental illnesses and violence, and escalated medical risks. Collateral damage includes restrictions on visitations to hospitals, alienation from the deceased relative, or lack of warm caring of patients. Finally, in a public health crisis, public health interest overrides individual rights if it results in severe harm to the community. CONCLUSION:Balancing ethical dilemmas are one more challenge in the COVID-19 pandemic.

As all other aspects in times of the coronavirus disease (COVID)-19 pandemic, carrying-out quality clinical research has been challenging. Many well-established paradigms have shifted as a consequence of the rapid demand for new knowledge. New treatments are fast-moving, informed consent forms are difficult to obtain, a competitive invitation from researchers to participate in different studies is common, and non-COVID-19 research protocols are suffering continuity. However, these challenges should not imply taking shortcuts or accepting deficiencies in bioethical standards, but rather enhance the alertness for rigorous ethical approaches despite these less than ideal circumstances. In this manuscript, we point out some interrogates in COVID-19 research and outline possible strategies to overcome the difficult task to continue with high-quality research without violating the ethical principles.

Background There is growing recognition that positive health beliefs may promote blood pressure (BP) reduction, which is critical to stroke prevention but remains a persistent challenge. Yet, studies that examine the association between positive health beliefs and BP among stroke survivors are lacking. Methods and Results Data came from the DESERVE (Discharge Educational Strategies for Reduction of Vascular Events) study, a randomized controlled trial of a skills-based behavioral intervention to reduce vascular risk in a multiethnic cohort of 552 transient ischemic attack and mild/moderate stroke patients in New York City. The exposure was perception that people can protect themselves from having a stroke (ie, prevention self-efficacy) at baseline. The association between systolic BP (SBP) reduction at 12-month follow-up and self-efficacy was examined using linear regression adjusted for key confounders, overall and stratified by age, sex, race/ethnicity, and intervention trial arm. Approximately three quarters endorsed self-efficacy. These participants had, on average, 5.6 mm Hg greater SBP reduction compared with those who did not endorse it (95% CI, 0.5-10.7 mm Hg; P=0.032). Self-efficacy was significantly associated with greater SBP reduction, particularly among female versus male, younger versus older, and Hispanic versus non-Hispanic white patients. Sensitivity analysis adjusting for baseline SBP instead of elevated BP yielded no association between self-efficacy and SBP reduction, but showed sex differences in this association (women: β=5.3; 95% CI, -0.2 to 10.8; P=0.057; men: β=-3.3; 95% CI, -9.4 to 2.9; P=0.300; interaction P=0.064). Conclusions Self-efficacy was linked with greater SBP reduction among female stroke survivors. Targeted strategies to improve health beliefs after stroke may be important for risk factor management. REGISTRATION URL: https://www.clini​caltr​ials.gov; Unique identifier: NCT01836354.

The offline "replay" of neural firing patterns underlying waking experience, previously observed in non-human animals, is thought to be a mechanism for memory consolidation. Here, we test for replay in the human brain by recording spiking activity from the motor cortex of two participants who had intracortical microelectrode arrays placed chronically as part of a brain-computer interface pilot clinical trial. Participants took a nap before and after playing a neurally controlled sequence-copying game that consists of many repetitions of one "repeated" sequence sparsely interleaved with varying "control" sequences. Both participants performed repeated sequences more accurately than control sequences, consistent with learning. We compare the firing rate patterns that caused the cursor movements when performing each sequence to firing rate patterns throughout both rest periods. Correlations with repeated sequences increase more from pre- to post-task rest than do correlations with control sequences, providing direct evidence of learning-related replay in the human brain.

Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in medical imaging are often trained on public research cohorts with images acquired with a single scanner or with strict protocol harmonization, which is not representative of a clinical setting. The aim of this study was to investigate how well a DL model performs in unseen clinical datasets-collected with different scanners, protocols and disease populations-and whether more heterogeneous training data improves generalization. In total, 3117 MRI scans of brains from multiple dementia research cohorts and memory clinics, that had been visually rated by a neuroradiologist according to Scheltens' scale of medial temporal atrophy (MTA), were included in this study. By training multiple versions of a convolutional neural network on different subsets of this data to predict MTA ratings, we assessed the impact of including images from a wider distribution during training had on performance in external memory clinic data. Our results showed that our model generalized well to datasets acquired with similar protocols as the training data, but substantially worse in clinical cohorts with visibly different tissue contrasts in the images. This implies that future DL studies investigating performance in out-of-distribution (OOD) MRI data need to assess multiple external cohorts for reliable results. Further, by including data from a wider range of scanners and protocols the performance improved in OOD data, which suggests that more heterogeneous training data makes the model generalize better. To conclude, this is the most comprehensive study to date investigating the domain shift in deep learning on MRI data, and we advocate rigorous evaluation of DL models on clinical data prior to being certified for deployment.

Background/UNASSIGNED:Although the COVID-19 pandemic is affecting a relatively small proportion of the global population, its effects have already reached everyone. The pandemic has the potential to differentially disadvantage chronically ill patients, including those with Parkinson's disease (PD). The first health care reaction has been to limit access to clinics and neurology wards to preserve fragile patients with PD from being infected. In some regions, the shortage of medical staff has also forced movement disorders neurologists to provide care for patients with COVID-19. Objective/UNASSIGNED:To share the experience of various movement disorder neurologists operating in different world regions and provide a common approach to patients with PD, with a focus on those already on advanced therapies, which may serve as guidance in the current pandemic and for emergency situations that we may face in the future. Conclusion/UNASSIGNED:Most of us were unprepared to deal with this condition given that in many health care systems, telemedicine has been only marginally available or only limited to email or telephone contacts. In addition, to ensure sufficient access to intensive care unit beds, most elective procedures (including deep brain stimulation or the initiation of infusion therapies) have been postponed. We all hope there will soon be a time when we will return to more regular hospital schedules. However, we should consider this crisis as an opportunity to change our approach and encourage our hospitals and health care systems to facilitate the remote management of chronic neurological patients, including those with advanced PD.

Neck pain and headache are two of the most common complications of whiplash injury. Therefore, we performed a systematic literature search on PubMed and Embase for publications reporting on the prevalence of neck pain and headache following whiplash injury. The literature search identified 2,709 citations of which 44 contained relevant original data. Of these, 27 studies provided data for the quantitative analysis. For non-population-based studies, the present meta-analysis showed that a pooled relative frequency of neck pain was 84% CI (68-95%) and a pooled relative frequency of headache was 60% (46-73%), within 7 days following whiplash injury. At 12 months post-injury, 38% (32-45%) of patients with whiplash still experienced neck pain, while 38% (18-60%) of whiplash patients reported headache at the same time interval post-injury. However, we also found considerable heterogeneity among studies with I-values ranging from 89-98% for the aforementioned meta-analyses. We believe that the considerable heterogeneity among studies underscores the need for clear-cut definitions of whiplash injury and standardized reporting guidelines for post-whiplash sequelae such as neck pain and headache. Future studies should seek to optimize these aspects paving the way for a better understanding of the clinical characteristics and natural course of whiplash-associated sequelae.