Detection of SARS-coronavirus-2 in the central nervous system of patients with severe acute respiratory syndrome and seizures

This study was designed to evaluate whether severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) can directly target the central nervous system (CNS). We present four patients suffering from the loss of consciousness and seizure during the clinical course of COVID-19 infection. In addition to positive nasopharyngeal swab tests, SARS-CoV-2 has been detected in their cerebrospinal fluid. This report indicates the neuroinvasive potential of SARS-CoV-2, suggesting the ability of this virus to spread from the respiratory tract to the CNS. © 2021, Journal of NeuroVirology, Inc

National guidelines for cognitive assessment and rehabilitation of Iranian traumatic brain injury patients

Background: Individuals with moderate to severe traumatic brain injury (TBI) often have prolonged cognitive impairments, resulting in long-term problems with their real-life activities. Given the urgent need for evidence-based recommendations for neuropsychological management of Iranian TBI patients, the current work aimed to adapt eligible international guidelines for cognitive assessment and rehabilitation of the TBI patients in Iran. Methods: The project was led by an executive committee, under the supervision of the Iranian Ministry of Health and Medical Education (MOHME). Following a systematic literature search and selection process, four guidelines were included for adaptation. Clinical recommendations of the source guidelines were tabulated as possible clinical scenarios for 90 PICO clinical questions covering all relevant phases of care. After summing up the scenarios, our initial list of recommendations was drafted according to the Iranian patients� conditions. The final decision-making, with the contribution of a national interdisciplinary panel of 37 experts from across the country, was conducted in two rounds using online and offline survey forms (Round 1), and face-to-face and telephone meetings (Round 2). Results: A total of 63 recommendations in six sections were included in the final list of recommendations, among which 24 were considered as key recommendations. In addition, some of the recommendations were identified as fundamental, meaning that proper implementation of the other recommendations is largely dependent on their implementation. Conclusion: Iranian health policy makers and rehabilitation program managers are recommended to address some fundamental issues to provide the necessary infrastructure to set up an efficient cognitive rehabilitation service system. © 2020 Academy of Medical Sciences of I.R. Iran. All rights reserved

Analysis of respiratory events in obstructive sleep apnea syndrome: Inter-relations and association to simple nocturnal features

Objective: This study carefully evaluates the association of different respiration-related events to each other and to simple nocturnal features in obstructive sleep apneaâhypopnea syndrome (OSAS). The events include apneas, hypopneas, respiratory event-related arousals and snores. Methods: We conducted a statistical study on 158 adults who underwent polysomnography between July 2012 and May 2014. To monitor relevance, along with linear statistical strategies like analysis of variance and bootstrapping a correlation coefficient standard error, the non-linear method of mutual information is also applied to illuminate vague results of linear techniques. Results: Based on normalized mutual information weights (NMIW), indices of apnea are 1.3 times more relevant to AHI values than those of hypopnea. NMIW for the number of blood oxygen desaturation below 95% is considerable (0.531). The next relevant feature is ârespiratory arousals indexâ with NMIW of 0.501. Snore indices (0.314), and BMI (0.203) take the next place. Based on NMIW values, snoring events are nearly one-third (29.9%) more dependent to hypopneas than RERAs. Conclusion: 1. The more sever the OSAS is, the more frequently the apneic events happen. 2. The association of snore with hypopnea/RERA revealed which is routinely ignored in regression-based OSAS modeling. 3. The statistical dependencies of oximetry features potentially can lead to home-based screening of OSAS. 4. Poor ESS-AHI relevance in the database under study indicates its disability for the OSA diagnosis compared to oximetry. 5. Based on poor RERA-snore/ESS relevance, detailed history of the symptoms plus polysomnography is suggested for accurate diagnosis of RERAs. Keywords: Obstructive sleep apneaâhypopnea syndrome, Respiratory events, Polysomnography, Mutual information, Analysis of variance, Bootstrapping techniqu

Obstructive sleep apnea risk and psychological health among non-Hispanic blacks in the Metabolic Syndrome Outcome (MetSO) cohort study

INTRODUCTION: This study assessed associations of depression and anxiety with risk of OSA among Non-Hispanic Blacks in the Metabolic Syndrome Outcome (MetSO) study. METHOD: 1,035 patients provided data for the analysis. ARES™ score ≥ 6 defined high OSA risk. Moderate depression was defined by a CES-D score ≥ 16. Moderate anxiety was measured by a BAI score ≥ 16. RESULTS: The mean age was 62 ± 14 years; 70% were female. 93% were diagnosed with hypertension; 61%, diabetes; and 72%, dyslipidemia; 90% were overweight/obese; 33% had a history of heart disease and 10% had a stroke. Logistic regression analysis, adjusting for age and gender, showed that patients with depression had nearly a two-fold increased odds of being at risk for OSA (OR = 1.75, 95% CI = 1.02–2.98, p < .05). Patients with anxiety had a three-fold increased odds of being at risk for OSA (OR = 3.30, 95% CI = 2.11–5.15, p < .01). After adjusting for marital status and income, patients with anxiety had a 6% increase in OSA risk (OR=1.06, 95% CI= 1.04–1.09, p<.05) but depression was no longer significant. CONCLUSION: Our results suggest that Non-Hispanic Blacks with metabolic syndrome who experience anxiety and/or depression should be screened for OSA

Assessing the risk of obstructive sleep apnoea-hypopnoea syndrome in elderly home care patients with chronic multimorbidity: a cross-sectional screening study.

Obstructive sleep apnoea-hypopnea syndrome (OSAHS) and multimorbidity are common in elderly patients, but a potential link between the two conditions remains unclear. This study aimed to assess the prevalence of OSAHS, chronic multimorbidity and their relation in older adults in primary care settings. A screening study was performed in a cross-section of 490 elderly adults (mean age 77.5 years, 51 % male) receiving home care services in Thessaly, central Greece. The Berlin Questionnaire was employed to assess the likelihood for OSAHS and the Epworth Sleepiness Scale to assess daytime sleepiness. Multimorbidity was defined as a documented history of at least two chronic diseases. The prevalence of high risk for OSAHS, excessive daytime sleepiness and multimorbidity was 33.5, 11.6 and 63.9 %, respectively. None of the study subjects had a confirmed diagnosis for OSAHS prior to this study. A marked dose-response association between a high pre-test likelihood for OSAHS and multimorbidity was noted in patients with two [adjusted odds ratio (OR) 3.13; 95 % confidence interval (CI) 1.85-5.30) and three or more (adjusted OR 4.22; 95 % CI 2.55-6.96) chronic morbidities, independently of age, sex and smoking status. This association persisted across different levels for OSAHS risk in the Berlin questionnaire, was insensitive to varying definitions of multimorbidity and more pronounced in patients with excessive daytime sleepiness. These findings point out that primary care physicians who care for elderly patients who present with several, common and burdensome, chronic diseases should expect to find this multimorbidity often coinciding with undetected, and therefore untreated, OSAHS. Thus it is crucial to consider OSAHS as an important co-morbidity in older adults and systematically screen for OSAHS in primary care practice

Query-constraint-based mining of association rules for exploratory analysis of clinical datasets in the National Sleep Research Resource

Abstract Background Association Rule Mining (ARM) has been widely used by biomedical researchers to perform exploratory data analysis and uncover potential relationships among variables in biomedical datasets. However, when biomedical datasets are high-dimensional, performing ARM on such datasets will yield a large number of rules, many of which may be uninteresting. Especially for imbalanced datasets, performing ARM directly would result in uninteresting rules that are dominated by certain variables that capture general characteristics. Methods We introduce a query-constraint-based ARM (QARM) approach for exploratory analysis of multiple, diverse clinical datasets in the National Sleep Research Resource (NSRR). QARM enables rule mining on a subset of data items satisfying a query constraint. We first perform a series of data-preprocessing steps including variable selection, merging semantically similar variables, combining multiple-visit data, and data transformation. We use Top-k Non-Redundant (TNR) ARM algorithm to generate association rules. Then we remove general and subsumed rules so that unique and non-redundant rules are resulted for a particular query constraint. Results Applying QARM on five datasets from NSRR obtained a total of 2517 association rules with a minimum confidence of 60% (using top 100 rules for each query constraint). The results show that merging similar variables could avoid uninteresting rules. Also, removing general and subsumed rules resulted in a more concise and interesting set of rules. Conclusions QARM shows the potential to support exploratory analysis of large biomedical datasets. It is also shown as a useful method to reduce the number of uninteresting association rules generated from imbalanced datasets. A preliminary literature-based analysis showed that some association rules have supporting evidence from biomedical literature, while others without literature-based evidence may serve as the candidates for new hypotheses to explore and investigate. Together with literature-based evidence, the association rules mined over the NSRR clinical datasets may be used to support clinical decisions for sleep-related problems