Abstract Background South Africa has experienced two waves of COVID-19 infections, the second of which was inter alia attributed to the emergence of a novel SARS-CoV2 variant, 501Y.V2. This variant possibly has increased virulence and may be associated with increased mortality. The objective of this study was to determine if patients admitted in the second wave had more severe illness and higher mortality than those admitted in the first. Methods We analysed and compared the characteristics, biological severity markers, treatments, level of care and outcomes of patients hospitalised in a private hospital in the Eastern Cape Province, South Africa. Results Compared to the first wave, patients admitted in the second were older and less likely to have co-morbidities. In contrast, the D-dimer and interleukin-6 (IL-6) levels were significantly higher. Despite this, significantly less patients were admitted to ICU and/or were mechanically ventilated. The total length of hospital stay was identical in both groups. Whereas the overall mortality was not significantly higher during the second wave, the ICU mortality was. Those that died in the second wave were older than those in the first wave. Multivariable logistic regression showed that being admitted during the second wave was an independent risk factor for mortality. Conclusion This study appears to confirm previous reports that the 501Y.V2 variant is possibly more virulent as indicated by the higher levels of D-dimer and IL-6, the slight increase in mortality of hospitalised patients and the higher ICU mortality in the second wave.
Background: Few longitudinal data on COVID-19 symptoms across the full spectrum of disease severity are available. We evaluated symptom onset, severity and recovery up to nine months after illness onset. Methods: The RECoVERED Study is a prospective cohort study based in Amsterdam, the Netherlands. Participants aged>18 years were recruited following SARS-CoV-2 diagnosis via the local Public Health Service and from hospitals. Standardised symptom questionnaires were completed at recruitment, at one week and month after recruitment, and monthly thereafter. Clinical severity was defined according to WHO criteria. Kaplan-Meier methods were used to compare time from illness onset to symptom recovery, by clinical severity. We examined determinants of time to recovery using multivariable Cox proportional hazards models. Results: Between 11 May 2020 and 31 January 2021, 301 COVID-19 patients (167[55%] male) were recruited, of whom 99/301(32.9%) had mild, 140/301(46.5%) moderate, 30/301(10.0%) severe and 32/301(10.6%) critical disease. The proportion of participants reporting at least one persistent symptom at 12 weeks after illness onset was greater in those with severe/critical disease (81.7%[95%CI=68.7-89.7%]) compared to those with mild or moderate disease (33.0%[95%CI=23.0-43.3%] and 63.8%[95%CI=54.8-71.5%]). At nine months after illness onset, almost half of all participants (42.1%[95%CI=35.6-48.5]) continued to report [≥]1 symptom. Recovery was slower in participants with BMI[≥]30kg/m2 (HR 0.51[95%CI=0.30-0.87]) compared to those with BMI<25kg/m2, after adjusting for age, sex and number of comorbidities. Conclusions: COVID-19 symptoms persisted for nine months after illness onset, even in those with mild disease. Obesity was the most important determinant of time to recovery from symptoms.
Background: SARS-CoV-2 mutations appeared recently and can lead to conformational changes in the spike protein and probably induce modifications in antigenicity. In this study, we wanted to assess the neutralizing capacity of antibodies to prevent cell infection, using a live virus neutralisation test. Methods: Sera samples were collected from different populations: two-dose vaccinated COVID-19-naive healthcare workers (HCWs; Pfizer-BioNTech BNT161b2), 6-months post mild COVID-19 HCWs, and critical COVID-19 patients. We tested various clades such as 19A (initial one), 20B (B.1.1.241 lineage), 20I/501Y.V1 (B.1.1.7 lineage), and 20H/501Y.V2 (B.1.351 lineage). Results: No significant difference was observed between the 20B and 19A isolates for HCWs with mild COVID-19 and critical patients. However, a significant decrease in neutralisation ability was found for 20I/501Y.V1 in comparison with 19A isolate for critical patients and HCWs 6-months post infection. Concerning 20H/501Y.V2, all populations had a significant reduction in neutralising antibody titres in comparison with the 19A isolate. Interestingly, a significant difference in neutralisation capacity was observed for vaccinated HCWs between the two variants whereas it was not significant for the convalescent groups. Conclusion: Neutralisation capacity was slightly reduced for critical patients and HCWs 6-months post infection. No neutralisation escape could be feared concerning the two variants of concern in both populations. The reduced neutralising response observed towards the 20H/501Y.V2 in comparison with the 19A and 20I/501Y.V1 isolates in fully immunized subjects with the BNT162b2 vaccine is a striking finding of the study.
Background Recent reports demonstrate robust serological responses to a single dose of messenger RNA (mRNA) vaccines in individuals previously infected with SARS-CoV-2. Data on immune responses following a single-dose adenovirus-vectored vaccine expressing the SARS-CoV-2 spike protein (ChAdOx1 nCoV-19) in individuals with previous SARS-CoV-2 infection are however limited, and current guidelines recommend a two-dose regime regardless of preexisting immunity. Methods We compared spike-specific IgG and pseudo-neutralizing spike-ACE2 blocking antibodies against SARS-CoV-2 wild type and variants B.1.1.7, B.1.351, and P1 following two doses of the mRNA vaccine BNT162b2 and a single dose of the adenovector vaccine ChAdOx1 nCoV-19 in 232 healthcare workers with and without previous COVID-19. Findings The post-vaccine levels of spike-specific IgG and neutralizing antibodies against the SARS-CoV-2 wild type and all three variants of concern were similar or higher in participants receiving a single dose of ChAdOx1 nCoV-19 vaccine post SARS-CoV-2 infection (both < 11 months post infection (n=37) and [≥] 11 months infection (n=46)) compared to participants who received two doses of BNT162b2 vaccine (n=149). Interpretation Our data support that a single dose ChAdOx1 nCoV-19 vaccine serves as an effective immune booster after priming with natural SARS-CoV-2 infection up to at least 11 months post infection.
Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete understanding of potentially druggable immune mediators of disease. To advance this, we present a comprehensive multi-omic blood atlas in patients with varying COVID-19 severity and compare with influenza, sepsis and healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity revealed cells, their inflammatory mediators and networks as potential therapeutic targets, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Tensor and matrix decomposition of the overall dataset revealed feature groupings linked with disease severity and specificity. Our systems-based integrative approach and blood atlas will inform future drug development, clinical trial design and personalised medicine approaches for COVID-19.
When quantitative longitudinal traits are risk factors for disease progression, endogenous, and/or subject to random errors, joint model specification of multiple time-to-event and multiple longitudinal traits can effectively identify direct and/or indirect genetic association of single nucleotide polymorphisms (SNPs) with time-to-event traits. Here, we present a joint model that integrates: i) a linear mixed model describing the trajectory of each longitudinal trait as a function of time, SNP effects and subject-specific random effects, and ii) a frailty Cox survival model that depends on SNPs, longitudinal trajectory effects, and a subject-specific frailty term accounting for unexplained dependency between time-to-event traits. Inference is based on a two-stage approach with bootstrap joint covariance estimation. We develop a hypothesis testing procedure to identify direct and/or indirect SNP association with each time-to-event trait. Motivated by complex genetic architecture of type 1 diabetes complications (T1DC) observed in the Diabetes Control and Complications Trial (DCCT), we show by realistic simulation study that joint modelling of two time-to-T1DC (retinopathy, nephropathy) and two longitudinal risk factors (HbA1c, systolic blood pressure) reduces bias and improves identification of direct and/or indirect SNP associations, compared to alternative methods ignoring measurement errors in intermediate risk factors. Through analysis of DCCT, we identify two SNPs with indirect associations with multiple time-to-T1DC traits and obtain similar conclusions using alternative formulations of time-dependent HbA1c effects on T1DC. In total, joint analysis of multiple longitudinal and multiple time-to-event traits provides insight into etiology of complex traits.
Accurate identification of seizure activity, both clinical and subclinical, has important implications in the management of epilepsy. Accurate recognition of seizure activity is essential for diagnostic, management and forecasting purposes, but patient-reported seizures have been shown to be unreliable. Earlier work has revealed accurate capture of electrographic seizures and forecasting is possible with an implantable intracranial device, but less invasive electroencephalography (EEG) recording systems would be optimal. Here, we present preliminary results of seizure detection and forecasting with a minimally invasive sub-scalp device that continuously records EEG. Five participants with refractory epilepsy who experience at least two clinically identifiable seizures monthly have been implanted with sub-scalp devices (Minder TM), providing two channels of data from both hemispheres of the brain. Data is continuously captured via a behind-the-ear system, which also powers the device, and transferred wirelessly to a mobile phone, from where it is accessible remotely via cloud storage. EEG recordings from the sub-scalp device were compared to data recorded from a conventional system during a 1-week ambulatory video-EEG monitoring session. Suspect epileptiform activity (EA) was detected using machine learning algorithms and reviewed by trained neurophysiologists. Seizure forecasting was demonstrated retrospectively by utilising cycles in EA and previous seizure times. The procedures and devices were well tolerated and no significant complications have been reported. Seizures were accurately identified on the sub-scalp system, as confirmed by periods of concurrent conventional scalp EEG recordings. The data acquired also allowed seizure forecasting to be successfully undertaken. The area under the receiver operating characteristic curve (AUC score) achieved (0.88) is comparable to the best score in recent, state-of-the-art forecasting work using intracranial EEG.
Background Fertility testing using urinary hormones has been used to improve the likelihood of pregnancy effectively. To provide fertility scores, the existing home-use systems measure one or two hormones. However, the hormone profiles vary depending on cycle duration, fertility-related disorders, drugs and other treatments. Here we introduce Inito, a mobile-phone connected reader that is scalable to multiple hormone tests. In this report, we assess the accuracy of the quantitative home-based fertility monitor, Inito Fertility Monitor (IFM), and suggest using IFM as a device to monitor and analyse female hormone patterns. We further show that Inito can be used as a tool to decipher novel hormone patterns in a more profound way than the existing knowledge in the field. Methods There were two aspects to our analysis: i. Evaluation of Inito Fertility Monitor efficiency characteristics for urinary Estrone-3-glucuronide (E3G), Pregnanediol glucuronide (PdG) and Luteinizing hormone (LH) assessment, and ii. A retrospective study of patients' hormone profiles using IFM. For the performance assessment, the recovery percentage of the three hormones from IFM was evaluated using standard spiked solutions, the reproducibility of re-prediction and the correlation between re-predicted values from IFM and ELISA. The first urine sample of the day was collected from 100 women who volunteered for the study and IFM was provided to 52 more women to use it at home to track their fertile days. Finding We observed that with all three hormones, IFM had an accurate recovery percentage and had a CV of less than 10 percent for separate test strips through tests of the same dosage making it a reliable tool to monitor hormone patterns of patients. Furthermore, in predicting the concentration of E3G, PdG and LH in urine samples, we show that IFM has a high correlation with ELISA. We show that certain hormone trends associated with urinary E3G, PdG and LH could be accurately captured using IFM. In addition, we report a novel criterion for earlier confirmation of ovulation compared to existing criteria. Finally, we present a novel hormone pattern associated with most of the menstrual cycles by examining hormone profiles from the volunteers recruited for the clinical trial. Interpretation The Inito Fertility Monitor is an effective tool for calculating the urinary concentrations of E3G, PdG and LH and can also be used to provide accurate fertility scores and confirm ovulation. In addition, the sensitivity of IFM facilitates the monitoring of menstrual cycle-related hormone patterns, therefore also making it a great tool for physicians to track the hormones of their patients.
Objectives To describe the presentation and outcome of SARS-CoV2 infection in an African setting of high non-communicable co-morbidity and also HIV-1 and tuberculosis prevalence. Design Case control analysis with cases stratified by HIV-1 and tuberculosis status. Setting A single-centre observational case-control study of adults admitted to a South African hospital with proven SARS-CoV-2 infection or alternative diagnosis. Participants 104 adults with RT-PCR-proven SARS-CoV2 infection of which 55 (52.9%) were male and 31 (29.8%) HIV-1 co-infected. 40 adults (35.7% male, 30.9% HIV-1 co-infected) admitted during the same period with no RT-PCR or serological evidence of SARS-CoV2 infection and assigned alternative diagnoses. Additional in vitro data from prior studies of 72 healthy controls and 118 HIV-1 uninfected and infected persons participants enrolled to a prior study with either immune evidence of tuberculosis sensitization but no symptoms or microbiologically confirmed pulmonary tuberculosis. Results Two or more co-morbidities were present in 57.7% of 104 RT-PCR proven COVID-19 presentations, the commonest being hypertension (48%), type 2 diabetes mellitus (39%), obesity (31%) but also HIV-1 (30%) and active tuberculosis (14%). Amongst patients dually infected by tuberculosis and SARS-CoV-2, clinical features could be dominated by either SARS-CoV-2 or tuberculosis: lymphopenia was exacerbated, and some markers of inflammation (D-dimer and ferritin) elevated in singly SARS-CoV-2 infected patients were even further elevated (p less than 0.05). HIV-1 and SARS-CoV2 co-infection resulted in lower absolute number and proportion of CD4 lymphocytes, with those in the lowest peripheral CD4 percentage strata exhibiting absent or lower antibody responses against SARS-CoV2. Death occurred in 30/104 (29%) of all COVID-19 patients and in 6/15 (40%) of patients with coincident SARS-CoV-2 and tuberculosis. Conclusions In this South African setting, HIV-1 and tuberculosis are common co-morbidities in patients presenting with COVID-19. In environments in which tuberculosis is common, SARS-CoV-2 and tuberculosis may co-exist with clinical presentation being typical of either disease. Clinical suspicion of exacerbation of co-existent tuberculosis accompanying SARS-CoV-2 should be high.
Background. Accurate brain meningioma detection, segmentation and volumetric assessment are critical for serial patient follow-up, surgical planning and monitoring response to treatment. Current gold standard of manual labeling is a time-consuming process, subject to inter-user variability. Fully-automated algorithms for meningioma detection and segmentation have the potential to bring volumetric analysis into clinical and research workflows by increasing accuracy and efficiency, reducing inter-user variability and saving time. Previous research has focused solely on segmentation tasks without assessment of impact and usability of deep learning solutions in clinical practice. Methods. We developed a three-dimensional convolutional neural network (3D-CNN) to perform expert-level, automated meningioma segmentation and volume estimation on MRI scans. A 3D-CNN was initially trained by segmenting entire brain volumes using a dataset of 10,099 healthy brain MRIs. Using transfer learning, the network was then specifically trained on meningioma segmentation using 806 expert-labeled MRIs. The algorithm tumor-labeling performance was assessed with standard metrics of tumor segmentation performance (i.e., Dice score). To evaluate clinical applicability, we compared volume estimation accuracy and segmentation time based on current practice versus the use of our automated algorithm. Findings. The final model achieved a median performance of 88.2% reaching the spectrum of current inter-expert variability (82.6% - 91.6%). Compared to current workflows, the use of the algorithm reduced processing time by 99% and produced tumor volume calculations with an almost perfect correlation with the expert manual segmentations (r=0.98, p<0.001), significantly more accurate compared to volume estimation techniques used in practice. Conclusions. We demonstrate through a prospective trial conducted in a simulated setting that a deep learning approach to meningioma segmentation is feasible, highly accurate and can substantially improve current clinical practice.
Background: Since December 2019, the novel coronavirus, SARS-CoV-2, has garnered global attention due to its rapid transmission, which has infected more than twenty nine million people worldwide. World is facing enormous stress and anxiety as there is no effective medicine or vaccine to treat or prevent COVID-19 till date. Experts are recommending self-care like social distancing, respiratory etiquette, hand washing, using face mask to prevent corona virus infection. Materials and methods: This descriptive cross-sectional study was designed to assess the prevalence of self-care practice among the undergraduate medical students (4th year) of 14 medical colleges of Bangladesh during COVID-19 pandemic. A structured questionnaire survey linked in the google form was used as study instrument and was distributed among study population through email, messenger, whatsapp and other social media during the month of October 2020. Total 916 students were participated in the study. Results: 79.8% of students reported self-care practice in study period. 44.98% of students went outside once in a week. 90.5%, 70.96% and 52.62% of respondents always used face mask, followed 20 seconds hand washing principle and maintained social distancing. Face masks (97.8%), sanitizers (76.7%) and gloves (71.9%) are most common items purchased as protective mesures. Most of the students (76.9%) follow their hobbies as a coping strategy to overcome phychological stress, while 6% of students took professional help. Conclusion: Suboptimal practice of self-care was found among the undergraduate medical students of Bangladesh.
Objectives: The rapid pace, high volume, and limited quality of mental health evidence being generated during COVID-19 poses a barrier to effective decision-making. The objective of the present report is to compare mental health outcomes assessed during COVID-19 to outcomes prior to COVID-19 in the general population and other population groups. Design: Living systematic review. Data Sources: MEDLINE (Ovid), PsycINFO (Ovid), CINAHL (EBSCO), EMBASE (Ovid), Web of Science Core Collection: Citation Indexes, China National Knowledge Infrastructure, Wanfang, medRxiv (preprints), and Open Science Framework Preprints (preprint server aggregator). The initial search was conducted on April 13, 2020 with ongoing weekly updates. Eligibility criteria for selecting studies: For this report, we included studies that compared general mental health, anxiety symptoms, or depression symptoms, assessed January 1, 2020 or later, to the same outcomes collected between January 1, 2018 and December 31, 2019. We required [≥] 90% of participants pre-COVID-19 and during COVID-19 to be the same or the use of statistical methods to address missing data. For population groups with continuous outcomes for at least three studies in an outcome domain, we conducted restricted maximum-likelihood random-effects meta-analyses. Results: As of March 22, 2021, we had identified 36 unique eligible studies with data from 33 cohorts. All reported COVID-19 outcomes between March and June 2020, and 3 studies also reported outcomes between September and November 2020. Estimates of changes in general mental health were close to zero in the general population (standardized mean difference [SMD] = 0.02, 95% CI -0.11 to 0.16, I2 = 94.6%; 4 studies, N = 19,707) and among older adults (SMD = 0.02, 95% CI -0.11 to 0.16, I2 = 90.4%; 4 studies, N = 5,520) and university students (SMD = -0.01, 95% CI -0.33 to 0.30, I2 = 92.0%; 3 studies, N = 3,372). Changes in anxiety symptoms were close to zero and not statistically significant in university students (SMD = 0.00, 95% CI -0.35 to 0.36, I2 = 95.4%; 5 studies, N = 1,537); women or females (SMD = 0.02, 95% CI -0.35 to 0.39, I2 = 92.3%; 3 studies, N = 2,778); and men or males (SMD = 0.07, 95% CI -0.01 to 0.15; I2 = 0.01%; 3 studies, N = 1,250); anxiety symptoms increased, however, among people with pre-existing medical conditions (SMD = 0.27, 95% CI 0.01 to 0.54, I2 = 91.0%; 3 studies, N = 2,053). Changes in depression symptoms were close to zero or small and not statistically significant among university students (SMD = 0.19, 95% CI -0.08 to 0.45, I2 = 91.8%; 5 studies, N = 1,537); people with pre-existing medical conditions (SMD = 0.01, 95% CI -0.15 to 0.17, I2 = 14.9%; 3 studies, N = 2,006); women or females (SMD = 0.21, 95% CI -0.14 to 0.55, I2 = 91.2%; 3 studies, N = 2,843); and men or males (SMD = 0.00, 95% CI -0.21 to 0.22; I2 = 92.3%; 4 studies, N = 3,661). In 3 studies with data from both March to June 2020 and September to November 2020, symptoms were unchanged from pre-COVID-19 at both time points or there were increases at the first assessment that had largely dissipated by the second assessment. Conclusions: Evidence does not suggest a widespread negative effect on mental health symptoms in COVID-19, although it is possible that gaps in data have not allowed identification of changes in some vulnerable groups. Continued updating is needed as evidence accrues.
Aims: The aim of this study was prediction of blood sugar regulation based on ego boundary, healthy boundary and post trauma growth in patient with Diabetes. Methods: For this purpose 50 people with diabetes were selected by multistage cluster sampling. The questionnaires used in this study were the post trauma growth inventory (PGI), the ego strength (PIES), and Healthy Boundaries (HB) Questionnaire. Results: Stepwise regression analysis showed that there were a significant positive relationship between blood sugar level (HbA1c) and ego strength, health boundaries and post-trauma growth (PTG). Conclusion: The findings indicate a significant correlation between hyperglycemia and health boundaries, ego strength and post-traumatic growth. This means that controlling and recognizing the boundaries of mental health and post-traumatic emotions prevents high blood (HbA1c) sugar and Type 2 diabetes.
Background: A meaningful part of schizophrenia patients suffer from physiosomatic symptoms (formerly named psychosomatic) which are reminiscent of chronic fatigue syndrome and fibromyalgia (FF) and are associated with signs of immune activation and increased levels of tryptophan catabolites (TRYCATs). Aims: To examine whether FF symptoms in schizophrenia are associated with breakdown of the paracellular pathway, zonulin, lowered natural IgM responses to oxidative specific epitopes (OSEs); and whether FF symptoms belong to the behavioral-cognitive-physical-psychosocial-(BCPS)-worsening index consisting of indices of a general cognitive decline (G-CoDe), symptomatome of schizophrenia, and quality of life (QoL)-phenomenome. Methods: FF symptoms were assessed using the Fibromyalgia and Chronic Fatigue Rating scale in 80 schizophrenia patients and 40 healthy controls and serum cytokines/chemokines, IgA levels to TRYCATs, IgM to OSEs, zonulin and transcellular/paracellular (TRANS/PARA) molecules were assayed using ELISA methods. Results: A large part (42.3%) of the variance in the total FF score was explained by the regression on the PARA/TRANS ratio, pro-inflammatory cytokines, IgM to zonulin, IgA to TRYCATs (all positively) and IgM to OSEs (inversely). There were highly significant correlations between the total FF score and G-CoDe, symtopmatome, QoL phenomenome and BCPS-worsening score. FF symptoms belong to a common core shared by G-CoDe, symtopmatome, and QoL phenomenome. Discussion: The physio-somatic symptoms of schizophrenia are driven by various pathways including increased zonulin, breakdown of the paracellular tight-junctions pathway, immune activation with induction of the TRYCAT pathway, and consequent neurotoxicity. It is concluded that FF symptoms are part of the phenome of schizophrenia and BCPS-worsening as well.
Background: With up to 70% of adverse drug reactions (ADRs) having high genetic associations, the clinical utility of pharmacogenomics (PGx) has been gaining traction. Nala PGx Core is a multi-gene qPCR-based panel that comprises 18 variants and 2 CYP2D6 Copy Number markers across 4 pharmacogenes - CYP2C9, CYP2C19, CYP2D6 and SLCO1B1. Objectives: In this study, we validated the performance of Nala PGx Core against benchmark methods, on the Singaporean and Indonesian populations. Additionally, we examined the allele and diplotype frequencies across 5 major ethnic groups present in these populations namely, Indonesians, Chinese, Malays, Indians and Caucasians. Methods: Human gDNA samples, extracted from the buccal swabs of 246 participants, were tested on Nala PGx Core and two chosen benchmarks, Agena VeriDose Core and CYP2D6 Copy Number Variation (CNV) Panel, and TaqMan DME Genotyping Assays. Performance was evaluated based on assay robustness, precision and accuracy at the genotype- and diplotype-level. Results: Nala PGx Core demonstrated high genotype- and diplotype-level call rates of >97% and >95% respectively in CYP2D6, and 100% for CYP2C9, CYP2C19 and SLCO1B1. A precision rate of 100% was observed on both intra- and inter-precision studies. Variant-level concordance to the benchmark methods was >96.9% across all assays, which consequently resulted in a diplotype-level concordance of >94.7% across CYP2C9, CYP2C19 and CYP2D6. Overall, the allele frequencies of CYP2D6*10 and CYP2D6*36 were higher in our cohort as compared to previous records. Notably, CYP2D6 copy number variation (CNV) analysis demonstrated a CYP2D6 *10/*36 frequency of 26.5% amongst the Indonesian cohort. Conclusion: Nala PGx Core produced robust and accurate genotyping when compared to other established benchmarks. Furthermore, the panel successfully characterized alleles of clinical relevance in the Singaporean and Indonesian populations such as CYP2D6*10 and CYP2D6*36, suggesting its potential for adoption in clinical workflows regionally.
Background: Increasingly more children and young people (CYP) present in mental health crises, many being hospitalised due to concerns around illness severity and lack of community services. To release the burden of admission, we systematically reviewed the literature on the effects of proposed alternatives to CYP in crises. Methods: Three databases (PsychInfo, PubMed and Web of Science) were searched for peer-reviewed papers in October 2020, with an updated search in May 2021. Results: We identified 19 papers of interventions delivered in the emergency department, the home, outside of home but outside of clinics and in hospital clinics. The best evidence came from in-home interventions, in particular multisystemic therapy (MST), which proved to be promising alternatives by improving psychological outcomes and decreasing length of inpatient stay. The quality of included studies was low, with less than half being randomised controlled trials and only half of these at low risk of bias. Conclusions: We could not recommend a particular intervention as an alternative to inpatient admission, however our review describes benefits across a range of types of inteventions that might be considered in multi-modal treatments. We also provide recommendations for future research, in particular the evaluation of new interventions as they emerge.
In order to identify the temporal change in the possible risk of superspreading events (SSE), we estimated the overdispersion parameter in two different periods of COVID-19 pandemic. We identified the possible risk of SSE was reduced 34% during the second epidemic period in South Korea.
Severe acute respiratory syndrome coronavirus has infected over 114 million people worldwide as of March 2021, with worldwide mortality rates ranging between 1-10%. We use information on up to 421,111 UK Biobank participants to identify possible predictors for long-term susceptibility to severe COVID-19 infection (N =1,088) and mortality (N =376). We include 36,168 predictors in our analyses and use a gradient boosting decision tree (GBDT) algorithm and feature attribution based on Shapley values, together with traditional epidemiological approaches to identify possible risk factors. Our analyses show associations between socio-demographic factors (e.g. age, sex, ethnicity, education, material deprivation, accommodation type) and lifestyle indicators (e.g. smoking, physical activity, walking pace, tea intake, and dietary changes) with risk of developing severe COVID-19 symptoms. Blood (cystatin C, C-reactive protein, gamma glutamyl transferase and alkaline phosphatase) and urine (microalbuminuria) biomarkers measured more than 10 years earlier predicted severe COVID-19. We also confirm increased risks for several pre-existing disease outcomes (e.g. lung diseases, type 2 diabetes, hypertension, circulatory diseases, anemia, and mental disorders). Analyses on mortality were possible within a sub-group testing positive for COVID-19 infection (N =1,953) with our analyses confirming association between age, smoking status, and prior primary diagnosis of urinary tract infection.
Objective: To characterize heart rate (HR) changes during autonomic dysreflexia (AD) in daily life for individuals with chronic spinal cord injury (SCI). Design: Data analysis of two prospective clinical studies and one cross-sectional study. Setting: Single-center study. Participants: Forty-five individuals (including 8 females) with a chronic SCI at or above the sixth thoracic spinal segment with confirmed AD, and a median age and time since injury of 43 years (interquartile range [IQR] 36 - 50) and 17 years (IQR 6 - 23) respectively, were included for analysis. Interventions: Not applicable. Main outcome measure: Any systolic blood pressure (SBP) increase > 20mmHg from baseline from a 24-hour ambulatory surveillance period was identified and categorized as either confirmed (i.e. known AD trigger), unknown (i.e. no diary entry), and unlikely (i.e. potential physical activity driven SBP increase). SBP-associated HR changes were categorized as either unchanged, increased or decreased compared to baseline. Results: A total of 797 episodes of SBP increase above AD threshold were identified and classified as confirmed (n = 250, 31.4%), unknown (n = 472, 59.2%) or unlikely (n = 75, 9.4%). Median SBP changes and median SBP-related HR changes were 37 mmHg and -8 bpm, 28 mmHg and -6 bpm, or 30 mmHg and -4 bpm for confirmed, unknown, or unlikely episodes, respectively. HR-decrease/increase ratio was 3:1 for confirmed and unknown, and 1.5:1 for unlikely episodes. HR changes resulting in brady-/tachycardia were 34.4% / 2.8% for confirmed, 39.6% / 3.4% unknown, and 26.7% / 9.3% for unlikely episodes, respectively. Conclusions: Our findings suggest that the majority of confirmed AD episodes are associated with a HR decrease. Further improvements, such as more precise participant diaries combined with the use of 24-hour Holter electrocardiogram and wearable-sensors-derived measures of physical activity could provide a better, more detailed characterization of HR changes during AD.
The SARS-CoV-2 coronavirus is a respiratory virus whose primary route of transmission is airborne. However, it has been shown that the virus can replicate in gastrointestinal cells, can be excreted in feces, and can reach sewage systems. Although viral RNA is known to be found in patient feces and sewage, little is known about the possible fecal-oral transmission of the coronavirus. Determining the presence of infective viral particles in feces and sewage is necessary to take adequate control measures and to discover new routes of coronavirus transmission. Here, we analyzed feces and urine of COVID-19 patients and wastewater samples at the time of high prevalence in the region under study, both by molecular methods and cell culture. The results obtained do not evidence the presence of infective viral particles, although larger-scale efforts are needed to elucidate whether the fecal-oral transmission should be considered as a route of SARS-CoV-2 transmission.