Post-acute COVID-19 neuropsychiatric symptoms are not associated with ongoing nervous system injury

A proportion of patients infected with severe acute respiratory syndrome coronavirus 2 experience a range of neuropsychiatric symptoms months after infection, including cognitive deficits, depression and anxiety. The mechanisms underpinning such symptoms remain elusive. Recent research has demonstrated that nervous system injury can occur during COVID-19. Whether ongoing neural injury in the months after COVID-19 accounts for the ongoing or emergent neuropsychiatric symptoms is unclear. Within a large prospective cohort study of adult survivors who were hospitalized for severe acute respiratory syndrome coronavirus 2 infection, we analysed plasma markers of nervous system injury and astrocytic activation, measured 6 months post-infection: neurofilament light, glial fibrillary acidic protein and total tau protein. We assessed whether these markers were associated with the severity of the acute COVID-19 illness and with post-acute neuropsychiatric symptoms (as measured by the Patient Health Questionnaire for depression, the General Anxiety Disorder assessment for anxiety, the Montreal Cognitive Assessment for objective cognitive deficit and the cognitive items of the Patient Symptom Questionnaire for subjective cognitive deficit) at 6 months and 1 year post-hospital discharge from COVID-19. No robust associations were found between markers of nervous system injury and severity of acute COVID-19 (except for an association of small effect size between duration of admission and neurofilament light) nor with post-acute neuropsychiatric symptoms. These results suggest that ongoing neuropsychiatric symptoms are not due to ongoing neural injury.</p

Modifiable risk factors for dementia, and awareness of brain health behaviors: Results from the Five Lives Brain Health Ireland Survey (FLBHIS)

Up to 40% of dementias globally are attributable to modifiable risk factors. Many existing studies examining attitudes to brain health are limited by a failure to consider a range of pertinent risk factors and associated barriers to protective behaviors. In Ireland, self-reported knowledge of dementia is poor compared to other conditions. In this context, the current study aimed to explore exposure to and awareness of specific modifiable risk factors for dementia. We also aimed to investigate whether exposure to these risk factors is associated with demographic and socioeconomic factors. A cross-sectional survey was administered to 555 voluntary participants in February 2022. The survey captured the following information: (1) Sociodemographic factors; (2) Exposure to, as well as knowledge of modifiable risk factors for dementia, namely diet, social interaction, exercise, hypertension, sleep, depression, smoking, alcohol consumption, cognitive stimulation, hearing impairment, diabetes, air pollution, and head injury. The study population comprised 551 participants (50.3% male; 49.6% female). Mean age was 59.7 years. Modifiable risk factors for dementia were prevalent. Relative to females, male gender was significantly associated with multiple risk factors. Whilst 65.6% of participants believed that lifestyle improvements can decrease a person’s risk of developing dementia, only 31.4% believed that dementia could be prevented. Head injury (90.9%, n = 500), low mental stimulation (85.3%, n = 469), and alcohol consumption (77.8%, n = 428) were the three most commonly recognized risk factors. Awareness was significantly greater in both university groups (undergraduate and postgraduate) for multiple risk factors. Our findings demonstrate that the distribution of exposure to modifiable risk factors for dementia is unequal across gender and age groups, and that awareness levels vary across risk factors. These findings highlight that focus surrounding dementia prevention should shift toward individual risk profiling and should be tailored toward an individual’s specific needs

The choice of the medium sanation in the treatment of acute widespread purulent peritonitis by the method of laparostomy in combination with programmed of the abdominal cavity sanitation

The accumulated clinical experience and analysis of our own results of treatment of patients with severe forms of acute widespread purulent peritonitis, speaks about the growing urgency of this problem. The aim of this study was determination of the most optimal medium sanation during execution programs of the abdominal cavity sanitation in acute diffuse purulent peritonitis.Was studied the treatment results of 79 patients with severe forms of acute widespread purulent peritonitis. After laparotomy and performing a biopsy was conducted qualitative and quantitative morphological study of the inflammatory process in the peritoneum on the background of the landmark of the abdominal cavity sanitation of  two groups of patients with acute widespread purulent peritonitis before and after carrying out the programmatic sanitation of the abdominal cavity, using a solution of octenidine dihydrochloride and saline solution.In the result of study, authors came to the conclusion, that the application, as it seemed different sanation mediums do not affect on the basic morphometric parameters of the studied biopsies of the peritoneum after sanitation of abdominal cavity.This confirms the theory of "mechanical purification" of the abdominal cavity, and sanitation of the abdominal cavity does not depend on the qualitative composition of the sanation medium

Personalised treatment for cognitive impairment in dementia : development and validation of an artificial intelligence model

Background Donepezil, galantamine, rivastigmine and memantine are potentially effective interventions for cognitive impairment in dementia, but the use of these drugs has not been personalised to individual patients yet. We examined whether artificial intelligence-based recommendations can identify the best treatment using routinely collected patient-level information. Methods Six thousand eight hundred four patients aged 59–102 years with a diagnosis of dementia from two National Health Service (NHS) Foundation Trusts in the UK were used for model training/internal validation and external validation, respectively. A personalised prescription model based on the Recurrent Neural Network machine learning architecture was developed to predict the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores post-drug initiation. The drug that resulted in the smallest decline in cognitive scores between prescription and the next visit was selected as the treatment of choice. Change of cognitive scores up to 2 years after treatment initiation was compared for model evaluation. Results Overall, 1343 patients with MMSE scores were identified for internal validation and 285 [21.22%] took the drug recommended. After 2 years, the reduction of mean [standard deviation] MMSE score in this group was significantly smaller than the remaining 1058 [78.78%] patients (0.60 [0.26] vs 2.80 [0.28]; P = 0.02). In the external validation cohort (N = 1772), 222 [12.53%] patients took the drug recommended and reported a smaller MMSE reduction compared to the 1550 [87.47%] patients who did not (1.01 [0.49] vs 4.23 [0.60]; P = 0.01). A similar performance gap was seen when testing the model on patients prescribed with AChEIs only. Conclusions It was possible to identify the most effective drug for the real-world treatment of cognitive impairment in dementia at an individual patient level. Routine care patients whose prescribed medications were the best fit according to the model had better cognitive performance after 2 years

Real-world effectiveness, its predictors and onset of action of cholinesterase inhibitors and memantine in dementia: retrospective health record study

Background The efficacy of acetylcholinesterase inhibitors and memantine in the symptomatic treatment of Alzheimer's disease is well-established. Randomised trials have shown them to be associated with a reduction in the rate of cognitive decline. Aims To investigate the real-world effectiveness of acetylcholinesterase inhibitors and memantine for dementia-causing diseases in the largest UK observational secondary care service data-set to date. Method We extracted mentions of relevant medications and cognitive testing (Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores) from de-identified patient records from two National Health Service (NHS) trusts. The 10-year changes in cognitive performance were modelled using a combination of generalised additive and linear mixed-effects modelling. Results The initial decline in MMSE and MoCA scores occurs approximately 2 years before medication is initiated. Medication prescription stabilises cognitive performance for the ensuing 2–5 months. The effect is boosted in more cognitively impaired cases at the point of medication prescription and attenuated in those taking antipsychotics. Importantly, patients who are switched between agents at least once do not experience any beneficial cognitive effect from pharmacological treatment. Conclusions This study presents one of the largest real-world examination of the efficacy of acetylcholinesterase inhibitors and memantine for symptomatic treatment of dementia. We found evidence that 68% of individuals respond to treatment with a period of cognitive stabilisation before continuing their decline at the pre-treatment rate

Clinical case of recurrent syndrome of pseudoobstruction of large intestine in a patient suffering from Parkinson’s disease

В статье описан случай рецидивирующего течения синдрома острой псевдообструкции толстой кишки (ОПТК) у 64-летнего мужчины на фоне болезни Паркинсона, который был госпитализирован с классической клинической картиной острой толстокишечной непроходимости, подтвержденной рентгенологически. Пациент был ургентно оперирован после проведения предоперационной подготовки, выполнена цекостомия. При дообследовании — выполнении фиброколоноскопии, спиральной компьютерной томографии патология органов брюшной полости и забрюшинного пространства исключена. Причинами развития острой псевдообструктивной толстокишечной непроходимости в данном случае были признаны ишемия толстой кишки на фоне наличия сопутствующей сердечной патологии, а также прием антипаркинсонических препаратов. После планового восстановления толстокишечной непрерывности пациент был выписан на амбулаторный этап наблюдения и лечения. В течение последующих трех лет пациент был дважды госпитализирован в хирургическое отделение с рецидивом ОПТК, чему предшествовали самостоятельные изменения дозы принимаемых противосудорожных препаратов и грубое нарушение диеты.A case of recurrent course of syndrome of acute pseudoobstruction of large intestine (APLI) in a 64-year-old man against a background of Parkinson’s disease, which was hospitalized with the classic clinical picture of the acute large intestine impassability, confirmed roentgenologic is described in article. A patient was urgentlty operated after conducting preoperation preparation, cecostomy was executed. With next examination — phybrocolonoscopy implementation, Spiral CT pathology of organs of abdominal and retroperitonial space was excluded. The causes of development of acute pseudoobstructive large intestine impassability were intestinal ischemia with concomitant cardiac pathology, and also administration of antiparkinsonian drugs. After the planned restoration of intstinal continuity a patient was discharged for the ambulatory stage of observation and medical treatment. During subsequent three years a patient was twice hospitalized in the surgical department with the APLI relapse, which were caused by change of dose of administered anti-seizure drugs and diet. In both cases of disease relapse it was succeeded to recover an adequate intestinal peristalsis during 24–48 hours, its timely emptying and improvement of state of patient, which confirmed the correctness of the chosen treatment management, and saved a patient and surgeon from the forced surgical decompression of the large intestine

Aβ₄₂/Aβ₄₀ and Aβ₄₂/Aβ₃₈ Ratios Are Associated with Measures of Gait Variability and Activities of Daily Living in Mild Alzheimer’s Disease: A Pilot Study

Gait disturbances are some of the earliest changes in dementia and their monitoring presents an opportunity for early diagnosis. The exact relationship between gait and well-established biomarkers of Alzheimer’s disease (AD) remains to be clarified. In this study we compared gait-related measures with cerebrospinal fluid (CSF) markers of AD pathology. We recruited seventeen participants with mild AD in a multi-site study and performed gait assessment as well as lumbar punctures to obtain CSF. CSF Aβ₄₂/Aβ₄₀ and Aβ₄₂/Aβ₃₈ correlated positively with measures of variability (step time and step length) in the clinic-based assessments. This was driven by a negative relationship between gait variability and Aβ₄₀ and Aβ₃₈ but not Aβ₄₂. The amyloid ratios and gait variability measures were also associated with more severe functional impairment. We interpret these data as an indication that increasing amyloid production (i.e., increasing Aβ₄₀ and Aβ₃₈) is associated with diminishing cognitive-motor control of gait. These preliminary results suggest that the two amyloid ratios may be a marker of the earliest disturbances in the interplay between cognitive and motor control which characterize dementia

Neurology and neuropsychiatry of COVID-19: a systematic review and meta-analysis of the early literature reveals frequent CNS manifestations and key emerging narratives

There is accumulating evidence of the neurological and neuropsychiatric features of infection with SARS-CoV-2. In this systematic review and meta-analysis, we aimed to describe the characteristics of the early literature and estimate point prevalences for neurological and neuropsychiatric manifestations.We searched MEDLINE, Embase, PsycINFO and CINAHL up to 18 July 2020 for randomised controlled trials, cohort studies, case-control studies, cross-sectional studies and case series. Studies reporting prevalences of neurological or neuropsychiatric symptoms were synthesised into meta-analyses to estimate pooled prevalence.13 292 records were screened by at least two authors to identify 215 included studies, of which there were 37 cohort studies, 15 case-control studies, 80 cross-sectional studies and 83 case series from 30 countries. 147 studies were included in the meta-analysis. The symptoms with the highest prevalence were anosmia (43.1% (95% CI 35.2% to 51.3%), n=15 975, 63 studies), weakness (40.0% (95% CI 27.9% to 53.5%), n=221, 3 studies), fatigue (37.8% (95% CI 31.6% to 44.4%), n=21 101, 67 studies), dysgeusia (37.2% (95% CI 29.8% to 45.3%), n=13 686, 52 studies), myalgia (25.1% (95% CI 19.8% to 31.3%), n=66 268, 76 studies), depression (23.0% (95% CI 11.8% to 40.2%), n=43 128, 10 studies), headache (20.7% (95% CI 16.1% to 26.1%), n=64 613, 84 studies), anxiety (15.9% (5.6% to 37.7%), n=42 566, 9 studies) and altered mental status (8.2% (95% CI 4.4% to 14.8%), n=49 326, 19 studies). Heterogeneity for most clinical manifestations was high.Neurological and neuropsychiatric symptoms of COVID-19 in the pandemic's early phase are varied and common. The neurological and psychiatric academic communities should develop systems to facilitate high-quality methodologies, including more rapid examination of the longitudinal course of neuropsychiatric complications of newly emerging diseases and their relationship to neuroimaging and inflammatory biomarkers

Streaming histogram sketching for rapid microbiome analytics

Background: The growth in publically available microbiome data in recent years has yielded an invaluable resource for genomic research, allowing for the design of new studies, augmentation of novel datasets and reanalysis of published works. This vast amount of microbiome data, as well as the widespread proliferation of microbiome research and the looming era of clinical metagenomics, means there is an urgent need to develop analytics that can process huge amounts of data in a short amount of time. To address this need, we propose a new method for the compact representation of microbiome sequencing data using similarity-preserving sketches of streaming k-mer spectra. These sketches allow for dissimilarity estimation, rapid microbiome catalogue searching and classification of microbiome samples in near real time. Results: We apply streaming histogram sketching to microbiome samples as a form of dimensionality reduction, creating a compressed ‘histosketch’ that can efficiently represent microbiome k-mer spectra. Using public microbiome datasets, we show that histosketches can be clustered by sample type using the pairwise Jaccard similarity estimation, consequently allowing for rapid microbiome similarity searches via a locality sensitive hashing indexing scheme. Furthermore, we use a ‘real life’ example to show that histosketches can train machine learning classifiers to accurately label microbiome samples. Specifically, using a collection of 108 novel microbiome samples from a cohort of premature neonates, we trained and tested a random forest classifier that could accurately predict whether the neonate had received antibiotic treatment (97% accuracy, 96% precision) and could subsequently be used to classify microbiome data streams in less than 3 s. Conclusions: Our method offers a new approach to rapidly process microbiome data streams, allowing samples to be rapidly clustered, indexed and classified. We also provide our implementation, Histosketching Using Little K-mers (HULK), which can histosketch a typical 2 GB microbiome in 50 s on a standard laptop using four cores, with the sketch occupying 3000 bytes of disk space