Importance The outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, is serious and has the potential to become an epidemic worldwide. Several studies have described typical clinical manifestations including fever, cough, diarrhea, and fatigue. However, to our knowledge, it has not been reported that patients with COVID-19 had any neurologic manifestations. Objective To study the neurologic manifestations of patients with COVID-19. Design, Setting, and Participants This is a retrospective, observational case series. Data were collected from January 16, 2020, to February 19, 2020, at 3 designated special care centers for COVID-19 (Main District, West Branch, and Tumor Center) of the Union Hospital of Huazhong University of Science and Technology in Wuhan, China. The study included 214 consecutive hospitalized patients with laboratory-confirmed diagnosis of severe acute respiratory syndrome coronavirus 2 infection. Main Outcomes and Measures Clinical data were extracted from electronic medical records, and data of all neurologic symptoms were checked by 2 trained neurologists. Neurologic manifestations fell into 3 categories: central nervous system manifestations (dizziness, headache, impaired consciousness, acute cerebrovascular disease, ataxia, and seizure), peripheral nervous system manifestations (taste impairment, smell impairment, vision impairment, and nerve pain), and skeletal muscular injury manifestations. Results Of 214 patients (mean [SD] age, 52.7 [15.5] years; 87 men [40.7%]) with COVID-19, 126 patients (58.9%) had nonsevere infection and 88 patients (41.1%) had severe infection according to their respiratory status. Overall, 78 patients (36.4%) had neurologic manifestations. Compared with patients with nonsevere infection, patients with severe infection were older, had more underlying disorders, especially hypertension, and showed fewer typical symptoms of COVID-19, such as fever and cough. Patients with more severe infection had neurologic manifestations, such as acute cerebrovascular diseases (5 [5.7%] vs 1 [0.8%]), impaired consciousness (13 [14.8%] vs 3 [2.4%]), and skeletal muscle injury (17 [19.3%] vs 6 [4.8%]). Conclusions and Relevance Patients with COVID-19 commonly have neurologic manifestations. During the epidemic period of COVID-19, when seeing patients with neurologic manifestations, clinicians should suspect severe acute respiratory syndrome coronavirus 2 infection as a differential diagnosis to avoid delayed diagnosis or misdiagnosis and lose the chance to treat and prevent further transmission.
Tryptophan is an essential amino acid critical for protein synthesis in humans that has emerged as a key player in the microbiota-gut-brain axis. It is the only precursor for the neurotransmitter serotonin, which is vital for the processing of emotional regulation, hunger, sleep, and pain, as well as colonic motility and secretory activity in the gut. Tryptophan catabolites from the kynurenine degradation pathway also modulate neural activity and are active in the systemic inflammatory cascade. Additionally, tryptophan and its metabolites support the development of the central and enteric nervous systems. Accordingly, dysregulation of tryptophan metabolites plays a central role in the pathogenesis of many neurologic and psychiatric disorders. Gut microbes influence tryptophan metabolism directly and indirectly, with corresponding changes in behavior and cognition. The gut microbiome has thus garnered much attention as a therapeutic target for both neurologic and psychiatric disorders where tryptophan and its metabolites play a prominent role. In this review, we will touch upon some of these features and their involvement in health and disease.
Huntington's disease (HD) is an inherited neurodegenerative disorder characterized by both neurological and systemic abnormalities. We examined the peripheral immune system and found widespread evidence of innate immune activation detectable in plasma throughout the course of HD. Interleukin 6 levels were increased in HD gene carriers with a mean of 16 years before the predicted onset of clinical symptoms. To our knowledge, this is the earliest plasma abnormality identified in HD. Monocytes from HD subjects expressed mutant huntingtin and were pathologically hyperactive in response to stimulation, suggesting that the mutant protein triggers a cell-autonomous immune activation. A similar pattern was seen in macrophages and microglia from HD mouse models, and the cerebrospinal fluid and striatum of HD patients exhibited abnormal immune activation, suggesting that immune dysfunction plays a role in brain pathology. Collectively, our data suggest parallel central nervous system and peripheral pathogenic pathways of immune activation in HD.
Shannon Gwin Mitchell, Jan Gryczynski, Donald C. Worley
et al.
Background De-implementing non-effective or even harmful practices in healthcare is sometimes necessary, as has been the case with opioid prescribing in dentistry over the past decade. One approach to practice transformation is to deploy clinical decision support (CDS) tools. This qualitative study examined barriers to CDS use as part of a cluster randomized trial that aimed to decrease opioid prescribing for pain management following tooth extractions across a large dental practice. Method Twenty dental providers who took part in the larger randomized trial were purposively selected to complete a semi-structured qualitative interview. Participants represented a broad range in terms of years of practice, dental specialization, and CDS use patterns. Interviews were conducted via Zoom, audio recorded, transcribed, and analyzed using a content analysis approach in ATLAS.ti following participation in the cluster randomized trial. Results Reasons for not using the CDS fell generally into two broad categories: unintentional (i.e., forgetting to use the CDS) and intentional. Providers who forgot to use the CDS after training and implementation either were not sure where to look for the alert on the screen or did not remember to look for it because its use was never incorporated into their workflow. Reasons for deciding not to use the CDS included feeling that it slowed down their workflow, thinking that the information it provided would not be useful, and not trusting the functionality of the system. Conclusions There were numerous, interdependent human, organizational, and technological factors that influenced the intentionally and unintentionally low CDS use rates observed in the study. Findings highlight issues to be aware of and address in future implementation efforts that utilize CDS. Trial registration Clinicaltrials.gov NCT03584789.
Abstract Background Posttraumatic stress symptoms are prevalent mental phenomenon in women with previous perinatal loss due to high grief, high perinatal depression and anxiety or low social support. Although posttraumatic stress symptoms are known to have serious negative implications for women with previous perinatal loss, families and society, the mechanism through which it functions is less clear. Objective The aim of this study was to examine the moderated mediating effect of social support on perinatal anxiety and depression and its associations with grief and posttraumatic stress symptoms in women with previous perinatal loss. We hypothesized that perinatal depression and anxiety would mediate relationships between grief and posttraumatic stress symptoms and that its mediating effects would differ depending on social support. Methods This study was a multicentre cross-sectional survey conducted from December 2021 to October 2022, involving 346 women during hospitalization for perinatal loss as participants from two public hospitals in China. Self-reported scales were used to measure the level of perinatal depression and anxiety, grief, posttraumatic stress symptoms and social support. The Pearson’s correlation analysis, the PROCESS Macro Model 4 and Model 14 on SPSS were used to analyse the available data. Results The positive effect of perinatal grief on posttraumatic stress symptoms was found to be mediated by perinatal depression and anxiety, and this mediating effect was moderated according to social support: the more social support, the weaker the mediating effect of perinatal depression and anxiety was between perinatal grief and posttraumatic stress symptoms. The positive effect of perinatal depression and anxiety on posttraumatic stress symptoms was lowest in the high social support group. Conclusions Healthcare providers should closely monitor the psychological well-being of pregnant individuals and implement targeted interventions-such as antenatal education course, group-based prenatal care models, and mindfulness-based therapies (e.g., cognitive behaviour therapy) -to mitigate perinatal anxiety and depression. These measures may also significantly reduce post-traumatic stress symptoms in women with previous perinatal loss and high perinatal grief, particularly among those with insufficient social support.
How does the threat of infectious disease influence sociality among generative agents? We used generative agent-based modeling (GABM), powered by large language models, to experimentally test hypotheses about the behavioral immune system. Across three simulation runs, generative agents who read news about an infectious disease outbreak showed significantly reduced social engagement compared to agents who received no such news, including lower attendance at a social gathering, fewer visits to third places (e.g., cafe, store, park), and fewer conversations throughout the town. In interview responses, agents explicitly attributed their behavioral changes to disease-avoidance motivations. A validity check further indicated that they could distinguish between infectious and noninfectious diseases, selectively reducing social engagement only when there was a risk of infection. Our findings highlight the potential of GABM as an experimental tool for exploring complex human social dynamics at scale.
Large-scale models pre-trained on Electroencephalography (EEG) have shown promise in clinical applications such as neurological disorder detection. However, the practical deployment of EEG-based large-scale models faces critical challenges such as limited labeled EEG data and suboptimal performance in clinical scenarios. To address these issues, we propose NeuroDx-LM, a novel large-scale model specifically designed for detecting EEG-based neurological disorders. Our key contributions include (i) a Selective Temporal-Frequency Embedding mechanism that adaptively captures complex temporal and spectral patterns in EEG signals; and (ii) a Progressive Feature-Aware Training strategy that refines feature representation in a two-stage process. In the first stage, our model learns the fundamental discriminative features of EEG activities; in the second stage, the model further extracts more specialized fine-grained features for accurate diagnostic performance. We evaluated NeuroDx-LM on the CHB-MIT and Schizophrenia datasets, achieving state-of-the-art performance in EEG-based seizure and schizophrenia detection, respectively. These results demonstrate the great potential of EEG-based large-scale models to advance clinical applicability. Our code is available at https://github.com/LetItBe12345/NeuroDx-LM.
Objective: To assess the influence of clinical and imaging characteristics on the outcome of microsurgery treatment for cerebellopontine angle (CPA) epidermoid cyst (EC) presenting only with trigeminal neuralgia (TN). Methods: A retrospective observational study describing 42 cases of CPA epidermoid cyst presenting only with TN n CPA for 10 years from 2011 to 2021 with the mean follow-up period was 37 months (range, 6–60 months). This study is the largest research with a long follow-up period reported so far worldwide for ECs with only TN symptom. We analyzed the clinical-radiological records of all the patients who met the rigorous requirements to find the distinct features of these tumors. Results: The mean age was 40.1 ± 4.7 years. The time from symptom onset to surgery was 8.6 ± 3.9 months. Symptoms of multiple branches of the 5th nerve appeared in 71.4 %, the most common was V2V3 accounting for 42.9 %. Most of the tumors were located limited in the CPA, accounting for 66.7 %. Total resection reached 90.5 %. The effectiveness of pain relief of microsurgery reached 97.6 %, Barrow Neurological Institute (BNI) score I reached 73.8 % and pain relief was 23.8 %. The postoperative neurologic deficit was 14.3 %. Conclusion: CPA epidermoid cysts presenting with TN as the sole symptom have favorable characteristics for total removing the tumor compared with other tumors in the remaining group. Total removing the tumor with the support of continuous intraoperative electromyography monitoring and decompressing the 5th nerve was ideal; it will not only increase the symptom improvement but also have a low rate of postoperative complications.
Surgery, Neurology. Diseases of the nervous system
Petra Baeumler, Margherita Schäfer, Luise Möhring
et al.
IntroductionPreviously, we had observed that immediate pain reduction after one acupuncture treatment was associated with high temporal summation of pain (TS) at a pain free control site and younger age in a mixed population of chronic pain patients. The aim of the present study was to verify these results in chronic non-specific low back pain (LBP) and to collect pilot data on the association between TS and the response to an acupuncture series.MethodsTS at a pain free control site (back of dominant hand) and at the pain site was quantified by the pin-prick induced wind-up ratio (WUR) in 60 LBP patients aged 50 years or younger. Response to one acupuncture treatment was assessed by change in pain intensity and pressure pain threshold (PPT) at the pain site. The primary hypothesis was that a high TS (WUR > 2.5) would be associated with a clinically relevant reduction in pain intensity of at least 30%. In study part two, 26 patients received nine additional treatments. Response to the acupuncture series was assessed by the pain intensity during the last week, the PPT and the Hannover functional ability questionnaire (FFbH-R).ResultsAn immediate reduction in pain intensity of at least 30% was frequent irrespective of TS at the control site (low vs. high TS 58% vs. 72%, p = 0.266). High TS at the pain site was also not significantly associated with a clinically relevant immediate reduction in pain intensity (low vs. high TS 46% vs. 73%, p = 0.064). The PPT was not changed after one acupuncture treatment. Study part two did not reveal a consistent association between TS at the control site and any of the outcome measures but also a trend toward a higher chance for a clinically relevant response along with low TS at the pain site.ConclusionOur results do not suggest an important role of TS for predicting a clinically important acupuncture effect or the response to a series of 10 acupuncture treatments in patients with chronic non-specific LBP. Overall high response rates imply that acupuncture is a suitable treatment option for LBP patients irrespective of their TS.
Laura Carnevali, Irene Valori, Irene Valori
et al.
IntroductionInterpersonal motor synchrony (IMS) is the spontaneous, voluntary, or instructed coordination of movements between interacting partners. Throughout the life cycle, it shapes social exchanges and interplays with intra- and inter-individual characteristics that may diverge in Autism Spectrum Disorder (ASD). Here we perform a systematic review and meta-analysis to summarize the extant literature and quantify the evidence about reduced IMS in dyads including at least one participant with a diagnosis of ASD. MethodsEmpirical evidence from sixteen experimental studies was systematically reviewed, encompassing spontaneous and instructed paradigms as well as a paucity of measures used to assess IMS. Of these, thirteen studies (n = 512 dyads) contributed measures of IMS with an in situ neurotypical partner (TD) for ASD and control groups, which could be used for meta-analyses. ResultsReduced synchronization in ASD-TD dyads emerged from both the systematic review and meta-analyses, although both small and large effect sizes (i.e., Hedge’s g) in favor of the control group are consistent with the data (Hedge’s g = .85, p < 0.001, 95% CI[.35, 1.35], 95% PI[-.89, 2.60]). DiscussionUncertainty is discussed relative to the type of task, measures, and age range considered in each study. We further discuss that sharing similar experiences of the world might help to synchronize with one another. Future studies should not only assess whether reduced IMS is consistently observed in ASD-TD dyads and how this shapes social exchanges, but also explore whether and how ASD-ASD dyads synchronize during interpersonal exchanges.
Christof Naumzik, Alice Kongsted, Werner Vach
et al.
Clinical data informs the personalization of health care with a potential for more effective disease management. In practice, this is achieved by subgrouping, whereby clusters with similar patient characteristics are identified and then receive customized treatment plans with the goal of targeting subgroup-specific disease dynamics. In this paper, we propose a novel mixture hidden Markov model for subgrouping patient trajectories from chronic diseases. Our model is probabilistic and carefully designed to capture different trajectory phases of chronic diseases (i.e., "severe", "moderate", and "mild") through tailored latent states. We demonstrate our subgrouping framework based on a longitudinal study across 847 patients with non-specific low back pain. Here, our subgrouping framework identifies 8 subgroups. Further, we show that our subgrouping framework outperforms common baselines in terms of cluster validity indices. Finally, we discuss the applicability of the model to other chronic and long-lasting diseases.
Nowadays, individuals do yoga as a way to improve their physical and psychological health with the pursuit of feeling good. Therefore, examining yoga in terms of psychological factors is very important in literature and life. This study aimed to examine psychological well-being, happiness, and mindfulness according to yoga and non-yoga practitioners and the sequential mediating role of happiness and mindfulness in the relationship between yoga and psychological well-being. The sample group of this study consists of 263 participants (129 yoga practitioners and 134 non-yoga practitioners). Participants completed the Demographic Information Form, Psychological Well-Being Scale, Oxford Happiness Scale, and Conscious Awareness Scale online. The data obtained in the study were analyzed by applying the Pearson correlation coefficient and Serial Multi-Mediator Variable Analysis (PROCESS Model 6). According to the study results, it was seen that between psychological well-being and happiness .56, between psychological well-being and mindfulness .34, and between happiness and mindfulness .30 correlations are positive and significant relationships. In conclusion, the results remark on the significant sequential mediating role of happiness and mindfulness in the relationship between yoga and psychological well-being.
Introduction
Mental Health Knowledge specific to symptom recognition, treatment efficacy, help-seeking, and employment can facilitate understanding when communicating with clinicians and reduce personal stigma. Better knowledge of mental illness has also been shown to decrease fear and embarrassment when interacting with people with mental illnesses. Thus, knowledge can play a key role in influencing behaviors and attitudes associated with stigma.
Objectives
The objective of this study was to evaluate mental health knowledge among Tunisian students
Methods
This cross-sectional study was conducted on 2501 Tunisian students from different academic institutions. They anonymously filled in a questionnaire circulated online through social networks in pages and groups of each university. The validated Arabic version of the “Mental Health Knowledge Schedule” (MAKS) was used to assess the knowledge about mental illnesses.
Results
The median MAKS score was equal to 45 out of 60, ranging from 30 to 56. In our study, 60.2% of the participants answered “don’t know” or “neither agree nor disagree” to item 1 indicating that “Most people with mental health problems want to have paid employment.”. Exactly 83.7% of the participants thought they knew what advice to give a friend to get professional help and 90% thought that psychotherapy could be effective in treating a person with a mental illness. In addition, 57.1% of participants thought that medication could be effective and 68.8% thought that people with severe mental health problems could make a full recovery. People with mental health problems do not seek professional help according to 39% of participants. About 90% were considering depression, schizophrenia, and bipolar disorder as mental illnesses. Stress and drug addiction were considered mental illnesses according to 71% and 63% of participants respectively. Finally, 52.9% answered that grief was a mental illness.
Conclusions
In Tunisia, anti-stigma programs are almost nonexistent. Our results would allow us to take a baseline assessment of mental health knowledge and could be the starting point for anti-stigma interventions. We should combine these findings with a behavioral and attitudinal assessment to better address stigma.
Disclosure of InterestNone Declared
BackgroundGrowing evidence suggests that gait training can improve stroke patients’ balance outcomes. However, it remains unclear which type of gait training is more effective in improving certain types of balance outcomes in patients with stroke. Thus, this network meta-analysis (NMA) included six types of gait training (treadmill, body-weight-supported treadmill, virtual reality gait training, robotic-assisted gait training, overground walking training, and conventional gait training) and four types of balance outcomes (static steady-state balance, dynamic steady-state balance, proactive balance, and balance test batteries), aiming to compare the efficacy of different gait training on specific types of balance outcomes in stroke patients and determine the most effective gait training.MethodWe searched PubMed, Embase, Medline, Web of Science, and Cochrane Library databases from inception until 25 April 2022. Randomized controlled trials (RCTs) of gait training for the treatment of balance outcomes after stroke were included. RoB2 was used to assess the risk of bias in the included studies. Frequentist random-effects network meta-analysis (NMA) was used to evaluate the effect of gait training on four categories of balance outcomes.ResultA total of 61 RCTs from 2,551 citations, encompassing 2,328 stroke patients, were included in this study. Pooled results showed that body-weight-support treadmill (SMD = 0.30, 95% CI [0.01, 0.58]) and treadmill (SMD = 0.25, 95% CI [0.00, 0.49]) could improve the dynamic steady-state balance. Virtual reality gait training (SMD = 0.41, 95% CI [0.10, 0.71]) and body-weight-supported treadmill (SMD = 0.41, 95% CI [0.02, 0.80]) demonstrated better effects in improving balance test batteries. However, none of included gait training showed a significant effect on static steady-state balance and proactive balance.ConclusionGait training is an effective treatment for improving stroke patients’ dynamic steady-state balance and balance test batteries. However, gait training had no significant effect on static steady-state balance and proactive balance. To achieve maximum efficacy, clinicians should consider this evidence when recommending rehabilitation training to stroke patients. Considering body-weight-supported treadmill is not common for chronic stroke patients in clinical practice, the treadmill is recommended for those who want to improve dynamic steady-state balance, and virtual reality gait training is recommended for those who want to improve balance test batteries.LimitationMissing evidence in relation to some types of gait training is supposed to be taken into consideration. Moreover, we fail to assess reactive balance in this NMA since few included trials reported this outcome.Systematic Review RegistrationPROSPERO, identifier CRD42022349965.
Oral diseases such as periodontal (gum) diseases and dental caries (cavities) affect billions of people across the world today. However, previous state-of-the-art models have relied on X-ray images to detect oral diseases, making them inaccessible to remote monitoring, developing countries, and telemedicine. To combat this overuse of X-ray imagery, we propose a lightweight machine learning model capable of detecting calculus (also known as hardened plaque or tartar) in RGB images while running efficiently on low-end devices. The model, a modified MobileNetV3-Small neural network transfer learned from ImageNet, achieved an accuracy of 72.73% (which is comparable to state-of-the-art solutions) while still being able to run on mobile devices due to its reduced memory requirements and processing times. A ResNet34-based model was also constructed and achieved an accuracy of 81.82%. Both of these models were tested on a mobile app, demonstrating their potential to limit the number of serious oral disease cases as their predictions can help patients schedule appointments earlier without the need to go to the clinic.