title: Machine Learning Prediction of Food Processing

abstract: Despite the accumulating evidence that increased consumption of ultra-processed food has adverse health implications, it remains difficult to decide what constitutes processed food. Indeed, the current processing-based classification of food has limited coverage and does not differentiate between degrees of processing, hindering consumer choices and slowing research on the health implications of processed food. Here we introduce a machine learning algorithm that accurately predicts the degree of processing for any food, indicating that over 73% of the U.S. food supply is ultra-processed. We show that the increased reliance of an individuals diet on ultra-processed food correlates with higher risk of metabolic syndrome, diabetes, angina, elevated blood pressure and biological age, and reduces the bio-availability of vitamins. Finally, we find that replacing foods with less processed alternatives can significantly reduce the health implications of ultra-processed food, suggesting that access to information on the degree of processing, currently unavailable to consumers, could improve population health.


title: Improving dengue case confirmation by combining rapid diagnostic test, clinical, and laboratory variables

abstract:
BackgroundDengue is the most widely distributed arboviral disease in tropical and subtropical countries. Early diagnosis is difficult, and most of the suspected cases are diagnosed according to clinical criteria. In underdeveloped countries, laboratory tests are done on a proportion of dengue with warning signs or severe dengue suspect cases. This study aimed to design a diagnostic algorithm using rapid diagnostic tests (RDT), ELISA tests together with clinical and hematology variables to confirm dengue cases in febrile patients from an endemic area in Colombia.

Methods and resultsA total of 505 samples were collected from patients with acute febrile syndrome (<7 days) assisted to the Municipal Hospital in Girardot (Colombia). Serum samples were evaluated by rapid diagnostic tests -RDT- (IgM and IgG antibodies and NS1 antigen immunochromatographic assay), capture ELISAs (IgM, IgG, and NS1 antigen), and by RT-PCR. We analyzed individual tests performance to determine which were the most useful to confirm dengue cases. Individual results for IgM, IgG, and NS1 RDT yield low sensitivity and specificity values than the reference standard. A high sensitivity (96.3%) and specificity (96.4%) were obtained after combining the IgM and NS1 ELISAs results. The analysis using the combined NS1 RDT and IgM ELISA results showed 90.3% sensitivity and 96.2% specificity. Adjusted odd ratios (aOR) were calculated including data from symptoms, signs, and diagnostic laboratory tests to differentiate dengue from other febrile illnesses (OFI). Myalgia (aOR: 1.87, CI95%: 1.04-3.38), abdominal tenderness (aOR: 1.89, CI95%: 1.14-3.10), platelets count <140.000/mm3 (aOR: 2.19 CI95%: 1.31-3.67). The analysis using the results of the diagnostic test yields significant ratios for IgM RDT (aOR:2.63 CI95%: 1.59-4.33) and NS1 RDT also differentiate dengue cases from OFI. Combined positive IgM or NS1 RDT and the one that combined positive NS1 RDT or IgM ELISA detect dengue cases in 81.6% and 90.6%, respectively (p<0.001).

ConclusionOur findings showed that only clinical diagnosis does not confirm true dengue cases dengue and needs to be complemented by laboratory diagnostic tests to stablish the diagnosis. We also demonstrate the usefulness of rapid tests in diagnosis, suggesting their implementation with IgM ELISA test to better confirm dengue cases.

Author SummaryDengue infections are considered the main mosquito-borne viral disease and a considerable concern in public health in tropical countries. Transmission has been associated with population growth, globalization (rapid urbanization, increasing movement of people), and environmental changes. Dengue diagnosis is difficult because of clinical variability in population of different age groups, with different degrees of severity that can have a fatal outcome. Diagnosis must consider clinical and laboratory criteria to improve early case confirmation particularly in endemic areas, where there is a need to support health services and improve treatment and management of the disease.

category: infectious diseases


title: Psychological factors underpinning vaccine willingness in Israel, Japan and Hungary

abstract: The rapid international spread of the SARS-CoV-2 virus 19 led to unprecedented attempts to develop and administer an effective vaccine. However, there is considerable vaccine hesitancy in some countries. We investigated willingness to vaccinate in three nations with historically different levels of vaccine willingness and attitudes: Israel, Japan and Hungary. Employing an ecological-systems approach we analysed associations between demographic factors and health status, individual cognitions, normative pressures, trust in government, belief in COVID-19 myths and willingness to be vaccinated, using data from three nationally representative samples (Israel, N=1011 (Jan 2021); Japan, N= 997 (Feb 2021); Hungary, N=1131 (Apr 2021)). In Israel 74% indicated a willingness to vaccinate, but only 51% in Japan and 31% in Hungary. Multigroup regression analyses indicated greater vaccine willingness amongst those who perceived benefits to vaccination, anticipated regret if not vaccinated and trusted the government. Multi-group latent class analysis of ten COVID-19 (mis)beliefs identified three classes of myths, with concerns about the alteration of DNA (Israel), allergies (Hungary) and catching COVID-19 from the vaccine (Japan) specific to vaccine willingness for each culture. Intervention campaigns should focus on increasing trust and addressing culturally specific myths while emphasising the individual and social group benefits of vaccination.


title: COVID-19 vaccination hesitancy model: The impact of vaccine education on controlling the outbreak in the United States

abstract: The coronavirus outbreak continues to pose a significant challenge to human lives globally. Many efforts have been made to develop vaccines to combat this virus. However, with the arrival of the COVID-19 vaccine, there is hesitancy and a mixed reaction toward getting the vaccine. We develop a mathematical model to analyze and investigate the impacts of education on individuals hesitant to get vaccinated. The findings indicate that vaccine education can substantially minimize the daily cumulative cases and deaths of COVID-19 in the United States. The results also show that vaccine education significantly increases the number of willing susceptible individuals, and with a high vaccination rate and vaccine effectiveness, the outbreak can be controlled in the US.


title: Transdiagnostic connectome-based prediction of craving

abstract: Craving is a central construct in the study of motivation and human behavior and is also a clinical symptom of substance and non-substance-related addictive disorders. Thus, craving represents a target for transdiagnostic modeling. We applied connectome-based predictive modeling (CPM) to functional connectivity data in a large (N=274) transdiagnostic sample of individuals with and without substance-use-related conditions, to predict self-reported craving. CPM is a machine-learning approach used to identify neural  signatures in functional connectivity data related to a specific phenotype. Functional connectomes were derived from three guided imagery conditions of personalized appetitive, stress, and neutral-relaxing experiences. Craving was rated before and after each imagery condition. CPM successfully predicted craving, thereby identifying a transdiagnostic  craving network comprised primarily of the posterior cingulate cortex, hippocampus, visual cortex, and primary sensory areas. Findings suggest that craving may be associated with difficulties directing attention away from internal self-related processing, represented in the default mode network.

category: addiction medicine


title: Mask mandate and use efficacy in state-level COVID-19 containment

abstract:
BackgroundCOVID-19 pandemic mitigation requires evidence-based strategies. Because COVID-19 can spread via respired droplets, most US states mandated mask use in public settings. Randomized control trials have not clearly demonstrated mask efficacy against respiratory viruses, and observational studies conflict on whether mask use predicts lower infection rates. We hypothesized that statewide mask mandates and mask use were associated with lower COVID-19 case growth rates in the United States.

MethodsWe calculated total COVID-19 case growth and mask use for the continental United States with data from the Centers for Disease Control and Prevention and Institute for Health Metrics and Evaluation. We estimated post-mask mandate case growth in non-mandate states using median issuance dates of neighboring states with mandates.

ResultsEarlier mask mandates were not associated with lower total cases or lower maximum growth rates. Earlier mandates were weakly associated with lower minimum COVID-19 growth rates. Mask use predicted lower minimum but not lower maximum growth rates. Growth rates and total growth were comparable between US states in the first and last mask use quintiles during the Fall-Winter wave. These observations persisted for both natural logarithmic and fold growth models and when adjusting for differences in US state population density.

ConclusionsWe did not observe association between mask mandates or use and reduced COVID-19 spread in US states. COVID-19 mitigation requires further research and use of existing efficacious strategies, most notably vaccination.

category: epidemiology


title: Mask mandate and use efficacy for COVID-19 containment in US States


title: A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases

abstract: Starting February 2020, COVID-19 was confirmed in 11,946 people worldwide, with a mortality rate of almost 2%. A significant number of epidemic diseases including human Coronavirus display patterns. In this study with the benefit of data analytic, we develop regression models and a Susceptible-Infected-Recovered (SIR) model for the contagion to compare the performance of models to predict number of cases. first, we implement a good understanding of data and perform Exploratory Data Analysis (EDA). Then, we derive the parameters of the model from the available data corresponding to the top 4 regions based on the history of infections and the most infected people as of the end of August 2020. Then models are compared and further research are introduced.


title: Monitoring of SARS-CoV-2 B.1.1.7 variant early-phase spreading in South-Moravian Region in the Czech Republic and evaluation of its pathogenicity

abstract:
SARS-CoV-2 emerged in Wuhan, China, in December 2019. Starting in January 2020, over a period of several months, the initial virus (Wuhan-Hu-1/2019; Wu et al. 2020) diverged in a descendant strain carrying D614G amino acid mutation in spike protein. By summer 2020 this novel coronavirus (nCoV) became the most dominant form of the virus circulating worldwide and raised serious international concern. Currently (April 2021), there are 3598 subsequent PANGO branched lineages recognized that carry numerous mutations. To date, the most emerging lineages of SARS-CoV-2 worldwide include B.1.1.7 lineage with a frequency of 48% followed by several dozens of others with frequencies 7.5% or less, such as B.1.351, B.1.1.28, B.1.2, B.1.1.519, P.1, R.1, etc. (www.nextrain.org, Centers for Disease Control and Prevention; CDC 2020 www.cdc.gov).

In this study, we monitored the spreading of B.1.1.7 lineage from the early phase of its appearance until it became predominant in the South-Moravian region of the Czech Republic. We measured significantly associated clinical marker (Ct; cycle threshold) correlating with viral load in B.1.1.7 lineage. Interestingly, we found that the spreading of B.1.1.7 strain was associated with a shift in patients average age, as compared to the former predominant lineage. Finally, we calculated the impact of the B.1.1.7 lineage on hospitalization and case fatality of the patients on the intensive care unit in the central South-Moravian faculty hospital.


title: Adverse events and their association with comorbidities after first and second doses of Covishield vaccination among healthcare workers of Government owned medical colleges in Kerala

abstract:
BackgroundA bridging study in the population was not existing at the time of introduction of Covishield vaccine in the state of Kerala A monitoring network for adverse events which was already in place ensured the reporting of serious adverse events following vaccination, but the recording of symptom profile and timeline of symptoms along with the comorbidity status of the individual recipients needed a further database.

AimsTo find the proportion of vaccine recipients with adverse events following the first and second doses of Covishield vaccination along with assessment of the symptom profile and timeline of appearance of symptoms following vaccination with each dose along with association of adverse events with comorbidity status of the respondents.

Materials & MethodsCross-sectional study with secondary data taken from the AEFI database of the Covid Cell, Directorate of Medical Education of the Kerala state.The database is formed with responses collected as online self-reporting forms collected from the health workers (doctors, nurses, students, paramedical, housekeeping and clerical staff) who received vaccination from vaccination centres in government owned Medical Colleges in Kerala for a period of three months from the date of rolling out vaccination in the state.

ResultsA total of 4402 healthworkers submitted the forms after taking the vaccination,either first dose or second dose.Out of this 3656(83.1%)responders were after first dose and 746(16.9%)participants responded after second dose 63.3% respondents after first dose & 24.3% after second dose reported they had experienced adverse events following vaccination with first or second dose of the vaccine respectively.The first symptom to be noticed in those who reported the adverse event after first dose was body ache (17.9%) followed by headache in 15.1 % of participants. 11% (403 out of 3656)of the responders after first dose were having comorbidities and 8.3 % were taking concomitant medications. History of being an asthmatic was found to be of increased risk for developing symptoms following first dose of vaccination(p value 0.004, OR-1.269,95% CI 1.127-1.429) whereas diabetes mellitus is not identified as a risk factor for development of adverse events though a significant association is found,might be due to a decreased reactogenicity.Among those who responded after receiving second dose of vaccination,24.3% reported they had adverse events(at least one post vaccination symptom),of which the first symptom experienced was headache (25.5%),followed by fever(20.9%) as compared to bodyache and headache after the first dose.

Conclusions56.7% of those who responded after receiving either first or second dose of the vaccine developed at least one symptom afterwards (63.3% after first and 24.3% after second dose of the vaccine respectively)with mean duration of appearance of symptoms being 8.5 hours and for majority of respondents the symptoms lasted for a day only.The first symptom to appear was bodyache (first dose),fever(in second dose) Though 8.5% respondents had a history of previous Covid infection it had no association with adverse events.Symptoms like chestpain,dry mouth, breathing difficulty which are not being spelled out in Covishield factsheet, has also been reported by the study respondents.Seizures were also reported as an adverse event by the responders

category: public and global health


title: How COVID-19 challenged care for women and their newborns: a qualitative case study of the experience of Belgian midwives during the first wave of the pandemic

abstract: In this article, we describe the results of a rapid qualitative study conducted between May 19 and June 25, 2020 on the work experience of midwives during the first wave of the COVID-19 pandemic in Brussels and Wallonia (Belgium). Using semi-structured interviews conducted with fifteen midwives working in hospitals or practicing privately, we investigated the impact of the first COVID-19 wave on their work experience, the woman-midwife relationship, and midwife-perceived changes in quality of care. Findings include high levels of stress and insecurity related to the lack of resources and personal protective equipment, feelings of distrust from midwives towards the Belgian State and public health authorities, as well as structural and organizational challenges within maternity wards which negatively affected quality of care. Moreover, based on the midwives experiences, we demonstrate the need to recognise the views of all stakeholders involved in maternal and newborn care provision, and share five essential lessons learned from this study: 1) it is crucial to acknowledge the central role of midwives for maintaining maternal and newborn care amidst the pandemic and beyond; 2) creating unified national guidelines could support ensuring best practice; 3) efforts must be put in place to diminish the climate of mistrust towards health authorities and to repair the relationship between midwives and decision-makers which was damaged during the pandemic; 4) caring for front-line healthcare workers mental health is critical, and 5) quality of maternal care can be improved, even in the midst of a pandemic, through team effort and creative solutions tailored to the needs and demands of each setting.


title: Low-field thoracic magnetic stimulation increases peripheral oxygen saturation levels in coronavirus disease (COVID-19) patients: a single-blind, sham-controlled, crossover study

abstract:
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may cause low oxygen saturation (SpO2) and respiratory failure in coronavirus disease (COVID-19) patients. Hence the increase of SpO2 levels could be crucial for the quality of life and recovery of these patients. Here we introduce an electromagnetic device termed low-field thoracic magnetic stimulation (LF-ThMS) system. This device was designed to non-invasively deliver a pulsed magnetic field from 100 to 118 Hz and 10.5 to 13.1 mT (i.e., 105 to 131 Gauss) to the dorsal thorax. We show that these frequencies and magnetic flux densities are safe for the patients. We also present a proof-of-concept that a single session of LF-ThMS applied for 30 minutes to the dorsal thorax of 17 COVID-19 patients significantly increases their SpO2 levels. We designed a single-blind, sham-controlled, crossover study on 5 COVID-19 patients who underwent two sessions of the study (real and sham LF-ThMS) and 12 COVID-19 patients who underwent only the real LF-ThMS. We found a statistically significant correlation between magnetic flux density, frequency, or temperature associated with the real LF-ThMS and SpO2 levels in all COVID-19 patients. However, the five patients of the sham-controlled study did not exhibit a significant change in their SpO2 levels during sham stimulation. All the patients did not present adverse events after the LF-ThMS intervention.

Trial registrationClinicalTrials.gov

IdentifierNCT04895267

category: respiratory medicine


title: Using kinematics to re-define the pull test as a quantitative biomarker of the postural response

abstract:
BackgroundQuantitative biomarkers are needed for the diagnosis, monitoring and therapeutic assessment of postural instability.

ObjectiveCreate a practical and objective measure of postural instability using kinematic measurement of the pull test to incorporate into clinical practice.

MethodsTwenty patients evaluated and treated for normal pressure hydrocephalus were tested over a number of sessions. Patients were fitted with 15 inertial measurement units during each session. At each session, the patient underwent 10-20 pull tests performed by a trained clinician. The clinician purposefully induced a range of perturbations during each session to assess the patients step response. Kinematic data was extracted for each pull test and aggregated.

ResultsPatients participated in 57 sessions for a total of 860 trials and were separated into groups by pull test score. The center of mass velocity profile easily distinguished between groups such that score increases correlated with decreases in peak velocity and later peak velocity onset. All patients except those scored as "3" demonstrated an increase in step length and decrease in reaction time with increasing pull intensity. Groups were distinguished by differences in overall step length or reaction time regardless of pull intensity (y-intercept). A logistic regression model including only kinematic variables identified three kinematic factors that could be used to identify trials in which patients needed to be caught (i.e. "fell").

ConclusionAn instrumented, purposefully varied pull test produces kinematic metrics useful for distinguishing clinically meaningful differences between and within NPH patients. These metrics should be followed prospectively to examine fall risk.

category: neurology


title: Childhood body composition and BMI as a predictor of cardiometabolic non-communicable diseases in adulthood: A systematic review

abstract: There is growing evidence that childhood malnutrition is associated with non-communicable diseases (NCDs) in adulthood and that body composition mediates some of this association. This review aims to determine: if childhood body composition can be used to predict later-life cardiometabolic NCDs; which measures of body composition best predict future NCDs. Three electronic databases were searched for studies where: children aged under 5 year had body composition measured; cardiometabolic health outcomes were measured a minimum of 10 years later. 29 studies met the inclusion criteria. Though a poor proxy measure of body composition, Body mass index (BMI) was commonly reported (n=28, 97%). 25% of these studies included an additional measure (Ponderal Index or skinfold thickness). Only some studies adjusted for current body size (n=11, 39%). Many studies reported that low infant BMI and high childhood BMI increased the risk of NCD-related outcomes in later life but no conclusions can be made about exact timing of child malnutrition and consequent impact on NCD. Because studies focused on BMI rather than direct measures of body composition, nothing can be said about which measures of body composition in childhood are most useful. Future research on child nutrition and long-term outcomes is urgently needed and should include validated body composition assessments as well as standard anthropometric and BMI measurements.

category: nutrition


title: Association of Intravenous Bamlanivimab Use with Reduced Hospitalization, Intensive Care Unit Admission, and Mortality in Patients with Mild to Moderate COVID-19

abstract:
BackgroundClinical data to support the use of bamlanivimab for the treatment of outpatients with mild to moderate coronavirus disease-19 (COVID-19) is needed.

Methods2,335 patients who received single-dose bamlanivimab infusion between November 12, 2020 to February 17, 2021 were compared with a propensity-matched control of 2,335 untreated patients with mild to moderate COVID-19 at Mayo Clinic facilities across 4 states. The primary outcome was the rate of hospitalization at days 14, 21 and 28.

ResultsThe median age of the population was 63; 47.3% of the bamlanivimab-treated cohort were [≥]65 years; 49.3% were female. High-risk characteristics included hypertension (54.2%), body mass index [≥]35 (32.4%), diabetes mellitus (26.5%), chronic lung disease (25.1%), malignancy (16.6%), and renal disease (14.5%). Patients who received bamlanivimab had lower all-cause hospitalization rates at days 14 (1.5% vs 3.5%; Odds Ratio [OR], 0.38), 21 (1.9% vs 3.9%; OR, 0.46), and 28 (2.5% vs 3.9%; OR, 0.61). Secondary exploratory outcomes included lower intensive care unit admission rates at days 14 (0.14% vs 1%; OR, 0.12), 21 (0.25% vs 1%; OR: 0.24) and 28 (0.56% vs 1.1%; OR: 0.52), and lower all-cause mortality at days 14 (0% vs 0.33%), 21 (0.05% vs 0.4%; OR,0.08) and 28 (0.11% vs 0.44%; OR, 0.01). Adverse events were uncommon with bamlanivimab, occurring in 19/2355, most commonly fever (n=6), nausea (n=5), and lightheadedness (n=3).

ConclusionsAmong high-risk patients with mild to moderate COVID-19, treatment with bamlanivimab was associated with a statistically significant lower rate of hospitalization compared with usual care.

FundingMayo Clinic.


title: Estimating the contribution of HIV-infected adults to household pneumococcal transmission in South Africa, 2016-2018: A hidden Markov modelling study.

abstract:
Human immunodeficiency virus (HIV) infected adults are at a higher risk of pneumococcal colonisation and disease, even while receiving antiretroviral therapy (ART). To help evaluate potential indirect effects of vaccination of HIV-infected adults, we assessed whether HIV-infected adults disproportionately contribute to household transmission of pneumococci. We constructed a hidden Markov model to capture the dynamics of pneumococcal carriage acquisition and clearance observed during a longitudinal household-based nasopharyngeal swabbing study, while accounting for sample misclassifications. Households were followed-up twice weekly for 10 months for nasopharyngeal carriage detection via real-time PCR. We estimated the effect of participants age, HIV status, presence of a HIV-infected adult within the household and other covariates on pneumococcal acquisition and clearance probabilities. Of 1,684 individuals enrolled, 279 (16.6%) were younger children (<5 years-old) of whom 4 (1.5%) were HIV-infected and 726 (43.1%) were adults ([≥]18 years-old) of whom 214 (30.4%) were HIV-infected, most (173, 81.2%) with high CD4+ count. The observed range of pneumococcal carriage prevalence across visits was substantially higher in younger children (56.9-80.5%) than older children (5-17 years-old) (31.7-50.0%) or adults (11.5-23.5%). We estimate that 14.4% (95% Confidence Interval [CI]: 13.7-15.0) of pneumococcal-negative swabs were false negatives. Daily carriage acquisition probabilities among HIV-uninfected younger children were similar in households with and without HIV-infected adults (hazard ratio: 0.95, 95%CI: 0.91-1.01). Longer average carriage duration (11.4 days, 95%CI: 10.2-12.8 vs 6.0 days, 95%CI: 5.6 - 6.3) and higher median carriage density (622 genome equivalents per millilitre, 95%CI: 507-714 vs 389, 95%CI: 311.1-435.5) were estimated in HIV-infected vs HIV-uninfected adults. The use of ART and antibiotics substantially reduced carriage duration in all age groups, and acquisition rates increased with household size. Although South African HIV-infected adults on ART have longer carriage duration and density than their HIV-uninfected counterparts, they show similar patterns of pneumococcal acquisition and onward transmission.

Author summaryWe assessed the contribution of HIV-infected adults to household pneumococcal transmission by applying a hidden Markov model to pneumococcal cohort data comprising 115,595 nasopharyngeal samples from 1,684 individuals in rural and urban settings in South Africa. We estimated 14.4% of sample misclassifications (false negatives), representing 85.6% sensitivity of a test that was used to detect pneumococcus. Pneumococcal carriage prevalence and acquisition rates, and average duration were usually higher in younger or older children than adults. The use of ART and antibiotics reduced the average carriage duration across all age and HIV groups, and carriage acquisition risks increased in larger household sizes. Despite the longer average carriage duration and higher median carriage density in HIV-infected than HIV-uninfected adults, we found similar carriage acquisition and onward transmission risks in the dual groups. These findings suggest that vaccinating HIV-infected adults on ART with PCV would reduce their risk for pneumococcal disease but may add little to the indirect protection against carriage of the rest of the population.


title: Monoclonal Antibody Treatment, Prophylaxis and Vaccines Combined to Reduce SARS CoV-2 Spread

abstract:
BackgroundAntiviral monoclonal antibodies (mAbs) developed for treatment of COVID-19 reduce the magnitude and duration of viral shedding and can thus potentially contribute to reducing transmission of the causative virus, severe acute respiratory coronavirus 2 (SARS-CoV-2). However, use of these mAbs in combination with a vaccine program has not been considered in public health strategic planning.

MethodsWe developed an agent-based model to characterize SARS-CoV-2 transmission in the US population during an aggressive phase of the pandemic (October 2020 to April 2021), and simulated the effects on infections and mortality of combining mAbs as treatment and post-exposure prophylaxis (PEP) with a vaccine program plus non-pharmaceutical interventions. We also interrogated the impact of rapid diagnostic testing, increased mAb supply, and vaccine rollout.

FindingsAllocation of mAbs as PEP or targeting those [≥]65 years provided the greatest incremental benefits relative to vaccine in averting infections and deaths, by up to 17% and 41%, respectively. Rapid testing, facilitating earlier diagnosis and mAb use, amplified these benefits. The model was sensitive to mAb supply; doubling supply further reduced infections and mortality, by up to two-fold, relative to vaccine. mAbs continued to provide incremental benefits even as proportion of the vaccinated population increased.

InterpretationUse of anti-viral mAbs as treatment and PEP in combination with a vaccination program would substantially reduce SARS-CoV-2 transmission and pandemic burden. These results may help guide resource allocation and patient management decisions for COVID-19 and can also be used to inform public health policy for current and future pandemic preparedness.

FundingRegeneron Pharmaceuticals.


title: Detecting COVID-19 Related Pneumonia on CT Scans using Hyperdimensional Computing

abstract: Pneumonia is a common complication associated with COVID-19 infections. Unlike common versions of pneumonia spread quickly through large lung regions, COVID-19 related pneumonia starts in small localized pockets before spreading over the course of several days. This makes the infection more resilient and with a high probability of developing acute respiratory distress syndrome. Because of the peculiar spread pattern, the use of pulmonary computerized tomography (CT) scans was key in identifying COVID-19 infections. Identifying uncommon pulmonary diseases could be a strong line of defense in early detection of new respiratory infection-causing viruses. In this paper we describe a classification algorithm based on hyperdimensional computing for the detection of COVID-19 pneumonia in CT scans. We test our algorithm using three different datasets. The highest reported accuracy is 95.2% with an F1 score of 0.90, and all three models had a precision of 1 (0 false positives).

category: health informatics


title: COVID-19 gender difference pattern in Iranian population, compared to the global pattern; a systematic review and meta-analysis

abstract: The coronavirus disease 2019 (COVID-19) pandemic has highlighted Sex-related immune responses. In this review, gender differences in seroprevalence, severity, mortality, and recovery in the Iranian population were systematically compared to the COVID-19 global pattern. This compressive meta-analysis was conducted on studies published up to April 1, 2021, examining seroprevalence in the general population as well as disease outcomes in hospitalized patients. Data were analyzed based on gender to determine differences between men and women in COVID-19. The PubMed, Scopus, Google Scholar, WOS, medRxiv, and bioRxiv were searched. The odds ratio (OR) was calculated based on the random-effects model, with a corresponding 95% confidence interval (CI), according to the number of participants reported in papers. Subgroup analyses were performed according to the age, antibody isotype, and detection assay. Overall, 61 studies with 225799 males and 237017 females were eligible for meta-analysis. Seroprevalence was 1.13 times higher (95% CI: 1.03, 1.24), mortality was 1.45 times higher (95% CI: 1.19, 1.77), and severity was up to 1.37 times higher (95% CI: 1.13, 1.67) in males than those of females in the general population across the globe. Mortality was higher in Iranian patients up to 26% in men (95% CI: 1.20, 1.33), but no significant difference was observed between disease severity and serum prevalence between men and women. Besides, the rate of recovery was 29% (global pattern) and 21% (Iran pattern) lower in males than in females. The results of subgroup analyses for seroprevalence were not significant for the age, antibody isotype, and detection methods. The results of our meta-analyses showed that the patient mortality and recovery patterns are similar in Iran and other countries in the context of gender differences, and the disease is more fatal in men.


title: Age- and airway disease related gene expression patterns of key SARS-CoV-2 entry factors in human nasal epithelia

abstract: The global COVID-19 pandemic caused by SARS-CoV-2 predominantly affects the elderly. Differential expression of SARS-CoV-2 entry genes may underlie the variable susceptibility in different patient groups. Here, we examined the gene expression of key SARS-CoV-2 entry factors in mucosal biopsies to delineate the roles of age and existing chronic airway disease. A significant inverse correlation between ACE2 and age and a downregulation of NRP1 in patients with airway disease were noted. These results indicate that the interplay between various factors may influence susceptibility and the disease course.


title: A random forest model for forecasting regional COVID-19 cases utilizing reproduction number estimates and demographic data

abstract: AO_SCPLOWBSTRACTC_SCPLOWDuring the COVID-19 pandemic, predicting case spikes at the local level is important for a precise, targeted public health response and is generally done with compartmental models. The performance of compartmental models is highly dependent on the accuracy of their assumptions about disease dynamics within a population; thus, such models are susceptible to human error, unexpected events, or unknown characteristics of a novel infectious agent like COVID-19. We present a relatively non-parametric random forest model that forecasts the number of COVID-19 cases at the U.S. county level. Its most prioritized training features are derived from easily accessible, standard epidemiological data (i.e., regional test positivity rate) and the effective reproduction number (Rt) from compartmental models. A novel input training feature is case projections generated by aligning estimated effective reproduction number (pre-computed by COVIDActNow.org) with real time testing data until maximally correlated, helping our model fit better to the epidemics trajectory as ascertained by traditional models. Poor reliability of Rt is partially mitigated with dynamic population mobility and prevalence and mortality of non-COVID-19 diseases to gauge population disease susceptibility. The model was used to generate forecasts for 1, 2, 3, and 4 weeks into the future for each reference week within 11/01/2020 - 01/10/2021 for 3068 counties. Over this time period, it maintained a mean absolute error (MAE) of less than 300 weekly cases/100,000 and consistently outperformed or performed comparably with gold-standard compartmental models. Furthermore, it holds great potential in ensemble modeling due to its potential for a more expansive training feature set while maintaining good performance and limited resource utilization.


title: Symptoms of common mental disorders and adherence to antiretroviral therapy among adults living with HIV in rural Zimbabwe: a cross-sectional study

abstract:
ObjectivesTo examine the proportion of people living with HIV who screen positive for common mental disorders (CMD) and the associations between CMD and self-reported adherence to antiretroviral therapy (ART).

SettingSixteen government-funded health facilities in the rural Bikita district of Zimbabwe.

DesignCross-sectional survey.

ParticipantsHIV-positive non-pregnant adults, aged 18 years or older, who lived in Bikita district and had received ART for at least six months.

Outcome measuresThe primary outcome was the proportion of participants screening positive for CMD defined as a Shona Symptoms Questionnaire (SSQ-14) score of 9 or greater. Secondary outcomes were the proportion of participants reporting suicidal ideation, perceptual symptoms, and suboptimal ART adherence and adjusted prevalence ratios (aPR) for factors associated with CMD, suicidal ideation, perceptual symptoms, and suboptimal ART adherence.

ResultsOut of 3,480 adults, 18.8% (95% confidence interval [CI] 14.8-23.7) screened positive for CMD, 2.7% (95% CI 1.5-4.7) reported suicidal ideations, and 1.5% (95% 0.9-2.6) reported perceptual symptoms. Positive CMD screens were more common in women (adjusted prevalence ratio [aPR] 1.67, 95% CI 1.19-2.35) than in men and were more common in adults aged 40-49 years (aPR 1.47 95% CI 1.16-1.85) or aged 50-59 years (20.3%; aPR 1.51 95% CI 1.05-2.17) than in those 60 years or older. Positive CMD screen was associated with suboptimal adherence (aPR 1.53; 95% CI 1.37-1.70).

ConclusionsA substantial proportion of people living with HIV in rural Zimbabwe are affected by CMD. There is a need to integrate mental health services and HIV programs in rural Zimbabwe.

Strengths and limitations of this studyO_LIInclusion of a large sample of people living with HIV recruited at 16 government-funded primary and secondary care facilities in a rural district of Zimbabwe.
C_LIO_LIUse of a locally developed screening tool that showed good psychometric properties for detecting common mental disorders in Zimbabwe in HIV-positive urban populations.
C_LIO_LIThe screening tool was not validated for the rural setting, and the cutoff score was selected based on data from the urban setting.
C_LIO_LIAdherence to antiretroviral therapy was self-reported.
C_LI


title: A statistical model of COVID-19 testing in populations: effects of sampling bias and testing errors

abstract: We develop a statistical model for the testing of disease prevalence in a population. The model assumes a binary test result, positive or negative, but allows for biases in sample selection and both type I (false positive) and type II (false negative) testing errors. Our model also incorporates multiple test types and is able to distinguish between retesting and exclusion after testing. Our quantitative framework allows us to directly interpret testing results as a function of errors and biases. By applying our testing model to COVID-19 testing data and actual case data from specific jurisdictions, we are able to estimate and provide uncertainty quantification of indices that are crucial in a pandemic, such as disease prevalence and fatality ratios.


title: Racial disparities in prevalence, determinants, and impacts of COVID-19 in pregnancy: Protocol for a study using data from New Jersey hospitals

abstract:
IntroductionRacial and ethnic disparities in COVID-19 related infections, hospitalizations, and deaths have been well-documented. However, little research has examined racial and ethnic disparities in COVID-19 prevalence, determinants, and impacts among pregnant women. Within the United States, New Jersey was an early epicenter of the pandemic and experienced high rates of disease in the fall of 2020.

MethodsThis study uses data from two New Jersey hospitals, which implemented universal testing of COVID-19 of pregnant women admitted for labor and delivery starting in March 2020. We will estimate prevalence of COVID-19 between March 2020 and November 2020 and compare prevalence rates across race and ethnicity. We will conduct multivariable logistic regression analysis to examine the associations of COVID-19 infection with patient demographic and health status predictors. We will also use multivariable linear and logistic regressions to examine the impact of COVID-19 symptomatic and asymptomatic infection on maternal and infant birth outcomes.

DiscussionThis study will generate important policy implications on birth equity in the time of COVID-19 and guide future research studies related to COVID-19 in pregnant women. Results of this study will help to guide interventions and policies to center safe, accessible, and equitable maternity care within the strategic response to the pandemic.


title: ENRIch: Exploiting Image Similarity to Maximize Efficient Machine Learning in Medical Imaging

abstract: Deep learning (DL) requires labeled data. Labeling medical images requires medical expertise, which is often a bottleneck. It is therefore useful to prioritize labeling those images that are most likely to improve a models performance, a practice known as instance selection. Here we introduce ENRICH, a method that selects images for labeling based on how much novelty each image adds to the growing training set. In our implementation, we use cosine similarity between autoencoder embeddings to measure that novelty. We show that ENRICH achieves nearly maximal performance on classification and segmentation tasks using only a fraction of available images, and outperforms the default practice of selecting images at random. We also present evidence that instance selection may perform categorically better on medical vs. non-medical imaging tasks. In conclusion, ENRICH is a simple, computationally efficient method for prioritizing images for expert labeling for DL.

category: radiology and imaging


title: Variants of concern are overrepresented among post-vaccination breakthrough infections of SARS-CoV-2 in Washington State

abstract: Across 20 vaccine breakthrough cases detected at our institution, all 20 (100%) infections were due to variants of concern (VOC) and had a median Ct of 20.2 (IQR=17.1-23.3). When compared to 5174 contemporaneous samples sequenced in our laboratory, VOC were significantly enriched among breakthrough infections (p < .05).


title: Business as Un-usual: Access to mental health and primary care services for people with severe mental illness during the COVID-19 restrictions

abstract:
AimsTo explore: how satisfied people with severe mental illness (SMI) are with the support received during the pandemic; understand any difficulties encountered when accessing both mental health and primary care services; consider ways to mitigate these difficulties; and assess the perceived need for future support from mental health services.

Materials and MethodsA representative sample was drawn from a large transdiagnostic clinical cohort of people with SMI, which was recruited between April 2016 and March 2020. The sample was re-surveyed a few months after the beginning of the restrictions. Descriptive frequency statistics were used to analyse the quantitative data. The free text responses were analysed thematically.

Results367 participants responded to the survey. Two thirds were receiving support from mental health services with the rest supported in primary care or self-managing. A quarter thought they would need more mental health support in the coming year. Half had needed to used community mental health services during the pandemic and the majority had been able to get support. A minority reported that their mental health had deteriorated but they had either not got the supported they wanted or had not sought help. The biggest service change was the reduction in face-to-face appointments and increasing use of phone and video call support. Nearly half of those using mental health services found this change acceptable or even preferred it; acceptability was influenced by several factors. Participants were more likely to be satisfied with support received when seen in person.

DiscussionAlthough most participants were satisfied with the mental health support they had received, a minority were not. This, couple with findings on future need for mental health support has implications for post pandemic demand on services. Remote care has brought benefits but also risks that it could increase inequalities in access to services.

category: psychiatry and clinical psychology


title: Use of traditional medicine in treatment of migraine during coronavirus disease 2019 (COVID-19) pandemic: an online survey

abstract: Since the declaration of coronavirus disease 2019 (COVID-19) pandemic, patients with migraine were specifically vulnerable to worsening of their headaches. Traditional medicine (TM) has been used to treat headache disorders for centuries, especially during times of a healthcare emergencies, similar to the current pandemic. We aimed to assess the use of TM in treatment of migraine amid COVID-19 pandemic in Kuwait, using an online, self-administered questionnaire. A total of 1018 patients completed the survey. TM was used by 39.9% respondents. The greatest users of TM were those with older age (p =0.04), and longer disease duration (p =0.005). TM users were found to be more compliant to treatments than non-TM users (p<0.02). However, they reported significantly less communication with their physicians (p <0.001) during the pandemic. This study showed higher rates of TM use, as a way of self-treatment, among patients with migraine during COVID-19 pandemic. Neurologists should prepare their patients with "rescue" strategies for headache management, and new means of communication, to face these "new normal" challenges.


title: Description and clinical validation of a real-time AI diagnostic companion for fetal ultrasound examination

abstract:
ObjectiveTo describe a real-time decision support system (DSS), named SONIO, to assist ultrasound-based prenatal diagnosis and to assess its performance using a clinical database of precisely phenotyped postmortem examinations.

Population and MethodsThis DSS is knowledge-based and comprises a dedicated thesaurus of 294 syndromes and diseases. It operates by suggesting, at each step of the ultrasound examination, the best next symptom to check for in order to optimize the diagnostic pathway to the smallest number of possible diagnoses. This assistant was tested on a single-center database of 251 cases of postmortem phenotypes with a definite diagnosis. Adjudication of discordant diagnoses was made by a panel of external experts. The primary outcome was a target concordance rate >90% between the postmortem diagnosis and the top-7 diagnoses given by SONIO when providing the full phenotype as input. Secondary outcomes included concordance for the top-5 and top-3 diagnoses; We also assessed a "1-by-1" model, providing only the anomalies sequentially prompted by the system, mimicking the use of the software in a real-life clinical setting.

ResultsThe validation database covered 96 of the 294 (32.65%) syndromes and 79% of their overall prevalence in the SONIO thesaurus. The adjudicators discarded 42/251 cases as they were not amenable to ultrasound based diagnosis. SONIO failed to make the diagnosis on 7/209 cases. On average, each case displayed 6 anomalies, 3 of which were considered atypical for the condition. Using the  full-phenotype model, the success rate of the top-7 output of Sonio was 96.7% (202/209). This was 91.9% and 87.1% for the top-5 and top-3 outputs respectively. Using the "1-by-1" model, the correct diagnosis was within the top-7, top-5 and top-3 of SONIOs output in 72.4%, 69.3% and 63.1%.

ConclusionSonio is a robust DSS with a success-rate >95% for top-7 ranking diagnoses when the full phenotype is provided, using a large database of noisy real data. The success rate over 70% using the  1-by-1 model was understandably lower, given that SONIOs sequential queries may not systematically cover the full phenotype.

category: genetic and genomic medicine


title: Class-Modeling of Septic Shock With Hyperdimensional Computing

abstract: Sepsis arises when a patients immune system has an extreme reaction to an infection. This is followed by septic shock if damage to organ tissue is so extensive that it causes a total systemic failure. Early detection of septic shock among septic patients could save critical time for preparation and prevention treatment. Due to the high variance in symptoms and patient state before shock, it is challenging to create a protocol that would be effective across patients. However, since septic shock is an acute change in patient state, modeling patient stability could be more effective in detecting a condition that departs from it. In this paper we present a one-class classification approach to septic shock using hyperdimensional computing. We built various models that consider different contexts and can be adapted according to a target priority. Among septic patients, the models can detect septic shock accurately with 90% sensitivity and overall accuracy of 60% of the cases up to three hours before the onset of septic shock, with the ability to adjust predictions according to incoming data. Additionally, the models can be easily adapted to prioritize sensitivity (increase true positives) or specificity (decrease false positives).


title: Statistical Analysis Plan for the Stepped-wedge Cluster Randomized Controlled Trial of Electronic Early Notification of Sepsis in Hospitalized Ward Patients (SCREEN): a study protocol for a stepped-wedge cluster randomized controlled trial

abstract:
BackgroundIt is unclear whether screening for sepsis using an electronic alert in hospitalized ward patients improves outcomes. The objective of the SCREEN (Stepped-wedge Cluster Randomized Controlled Trial of Electronic Early Notification of Sepsis in Hospitalized Ward Patients) trial is to evaluate whether an electronic screening for sepsis compared to no screening among hospitalized ward patients reduces all-cause 90-day in-hospital mortality.

Methods and designThis study is designed as a stepped-wedge cluster randomized controlled trial in which the unit of randomization or cluster is the hospital ward. An electronic alert for sepsis was developed in the electronic medical record (EMR), with the feature of being active (visible to treating team) or masked (inactive in EMR frontend for the treating team but active in the backend of the EMR). Forty-five clusters in 5 hospitals are randomized into 9 sequences of 5 clusters each to receive the intervention (active alert) over 10 periods, 2-months each, the first being the baseline period. Data are extracted from EMR and are compared between the intervention (active alert) and control group (masked alert). The primary outcome of all-cause hospital mortality by day 90 will be compared using a generalized linear mixed model with a binary distribution and a log-link function to estimate the relative risk as a measure of effect. We will include two levels of random effects to account for nested clustering within wards and periods and two levels of fixed effects; hospitals and COVID-19 ward status. Results will be expressed as relative risk with a 95% confidence interval (CI).

ConclusionThe SCREEN trial provides an opportunity for a novel trial design and analysis of routinely collected and entered data to evaluate the effectiveness of an intervention (alert) for a common medical problem (sepsis in ward patients). In this statistical analysis plan, we outline details of the planned analyses in advance of trial completion. Prior specification of the statistical methods and outcomes analysis will facilitate unbiased analyses of these important clinical data.

Trial registrationClinicalTrials.gov NCT04078594. Registered on September 6, 2019, https://clinicaltrials.gov/ct2/show/NCT04078594

category: health systems and quality improvement


title: Immunogenic Amino Acid Motifs and Linear Epitopes of COVID-19 mRNA Vaccines

abstract: Reverse vaccinology is an evolving approach for improving vaccine effectiveness and minimizing adverse responses by limiting immunizations to critical epitopes. Towards this goal, we sought to identify immunogenic amino acid motifs and linear epitopes of the SARS-CoV-2 spike protein that elicit IgG in COVID-19 mRNA vaccine recipients. Paired pre/post vaccination samples from N=20 healthy adults, and post-vaccine samples from an additional N=13 individuals were used to immunoprecipitate IgG targets expressed by a bacterial display random peptide library, and preferentially recognized peptides were mapped to the spike primary sequence. The data identify several distinct amino acid motifs recognized by vaccine-induced IgG, a subset of those targeted by IgG from natural infection, which may mimic 3-dimensional conformation (mimotopes). Dominant linear epitopes were identified in the C-terminal domains of the S1 and S2 subunits (aa 558-569, 627-638, and 1148-1159) which have been previously associated with SARS-CoV-2 neutralization in vitro and demonstrate identity to bat coronavirus and SARS-CoV, but limited homology to non-pathogenic human coronavirus. The identified COVID-19 mRNA vaccine epitopes should be considered in the context of variants, immune escape and vaccine and therapy design moving forward.

category: allergy and immunology


title: Fast raster-scan optoacoustic mesoscopy enables assessment of human melanoma microvasculature in vivo

abstract: The development and progression of melanoma tumors is associated with angiogenesis, manifesting as changes in vessel density, morphology, and architecture that may extend through the entire skin depth. Three-dimensional imaging of vascular characteristics in skin lesions could allow diagnostic insights not available to the conventional visual inspection. Raster-scan optoacoustic mesoscopy (RSOM) has emerged as a unique modality to image microvasculature through the entire skin depth with resolutions of tens of micrometers, offering new possibilities to assess angiogenetic processes. However, current RSOM implementations are slow, exacerbating motion artifacts and reducing image quality, particularly when imaging melanoma lesions that often appear on the upper torso where breathing motion is strongest. To visualize for the first time melanoma vasculature in humans, in high-resolution, we accelerated RSOM scanning using an illumination scheme that is co-axial with a high-sensitivity ultrasound detector path, yielding 15 second single-breath-hold scans that minimize motion artifacts. Applied to 10 melanomas and 10 benign nevi in humans, we demonstrate visualization of microvasculature with performance never before shown in vivo. We show marked differences between malignant and benign lesions, supporting the possibility to use vasculature as a biomarker for lesion characterization. The study points to promising clinical potential for Fast-RSOM (FRSOM) as a three dimensional visualization method that can enable the complete assessment of microvascular parameters of melanoma and improve diagnostics.

category: dermatology


title: Multiple drug arrests reported to the Maine Diversion Alert Program more frequently involved carisoprodol, amitriptyline, or quetiapine

abstract:
BackgroundMuch of the blame of the increasing death toll by drug overdoses has justifiably been attributed to the United States current opioid epidemic. However, nearly 80% of overdoses related to opioids involve another drug substance or alcohol. The objective of this study was to elucidate overrepresentation of drugs in polypharmacy arrests by identifying drugs that were more likely to be found in conjunction with other substances, using the drug arrest data provided by the Maine Diversion Alert Program (DAP).

MethodsSingle drug arrest and multiple drug arrest totals reported to the DAP were examined. Drugs involved in the arrests were classified by Drug Enforcement Administration Schedule (I-V or non-controlled prescription) and categorized into five drug families: hallucinogens, opioids, sedatives, stimulants, and miscellaneous. Multiple drug arrest totals were compared to single drug arrest totals to create a Multiple-to-Single Ratio (MSR) specific to each drug family and each drug. Chi-square approximations without Yates correction and two-tailed P values were used to determine statistical significance through GraphPads 2x2 contingency tables.

ResultsOver three-fifths (63.8%) of all arrests involved a single drug. Opioids accounted for over-half (53.5%) of single arrests, followed by stimulants (27.7%) and hallucinogens (7.7%). Similarly, nearly two-fifths (39.6%) of multiple arrests were opioids, followed by stimulants (30.8%) and miscellaneous (13.0%). Miscellaneous family drugs were recorded with the highest Multiple-to-Single Ratio (1.51), followed by sedatives (1.09), stimulants (0.63), opioids (0.42), and hallucinogens (0.35). Carisoprodol (8.80), amitriptyline (6.34), and quetiapine (4.69) had the highest MSR values and therefore were the three most overrepresented drugs in polysubstance arrests.

ConclusionThe abuse of opioids, both alone and in conjunction with another drug, deserves continued surveillance in public health. In addition, common prescription drugs with lesser-known misuse potential, especially carisoprodol, amitriptyline, and quetiapine, require more attention by medical providers for their ability to enhance the effects of other drugs or to compensate for undesired drug effects.

category: forensic medicine


title: Reduced Intrinsic Neural Timescales in Schizophrenia along Posterior Parietal and Occipital Areas

abstract: We computed intrinsic neural timescales (INT) based on resting state functional magnetic resonance imaging (rsfMRI) data of healthy controls (HC) and patients with schizophrenia spectrum disorder (SZ) from three independently collected samples. Five clusters showed decreased INT in SZ compared to HC in all three samples: Right occipital fusiform gyrus (rOFG), Left superior occipital gyrus (lSOG), Right superior occipital gyrus (rSOG), Left lateral occipital cortex (lLOC), and Right postcentral gyrus (rPG). In other words, it appears that sensory information in visual and posterior parietal areas is stored for reduced lengths of time in SZ compared to HC. We also found some evidence that symptom severity modulates INT of these areas in SZ.


title: Fear among Syrians: a Proposed Cutoff Score and Validation of the Arabic Fear of COVID-19 Scale- A National Survey

abstract: COVID-19 pandemic has led to psychological health issues one of which is fear. This study validates the Arabic version of the fear of COVID-19 scale and suggests a new cutoff score to measure fear of COVID-19 among the Syrian Population. A total of 3989 participants filled an online survey consisting of socio-demographic information, the fear of COVID-19 scale, the patient health questionnaire 9-item, and the generalized anxiety disorder 7-item. Receiver operating characteristic analysis was used to define cutoff scores for the fear of COVID-19 scale in relation to generalized anxiety disorder 7-item and the patient health questionnaire 9-item. The Cronbach  value of the Arabic fear of COVID-19 scale was 0.896, revealing good stability and internal consistency. The inter-item correlations were between [0.420 - 0.868] and the corrected item-total correlations were between [0.614 - 0.768]. A cutoff point of 17.5 was deduced from analysis. According to the deduced cutoff point, 2111(52.9%) were classified as cases with extreme fear. This cutoff score deduced from this study can be used for screening purposes to identify individuals that may be most vulnerable towards developing extreme fear of COVID-19. Therefore, early preventive and supportive measures can then be delivered.


title: Engagement with daily testing instead of self-isolating in contacts of confirmed cases of SARS-CoV-2: A qualitative analysis

abstract:
IntroductionIn December 2020 and January 2021 Public Health England (PHE) with NHS Test and Trace conducted a study to explore the feasibility and acceptability of daily testing as an alternative to self-isolation following close contact with a confirmed COVID-19 case. This qualitative paper aims to identify factors influencing uptake among those offered daily testing, and the subsequent impact on behaviour.

MethodsWe conducted in-depth interviews with 52 participants who had taken part in the feasibility study. Participants were asked about their experiences of daily testing or self-isolating, their reasons for choosing to test or isolate, and their behaviour during the study period. Data were analysed using inductive thematic analysis.

ResultsResults are presented under two main headings: 1) factors influencing acceptance of testing and 2) impact of test results. Participants appeared highly motivated to engage in behaviours that would protect others from the virus. Factors influencing the decision to accept testing included 1) needing to avoid self-isolation 2) concerns about test sensitivity and 3) perceived benefits of detecting infection. Participants who were taking tests reported:1) positive consequences following confirmation of COVID status 2) engaging in essential activities 3) uncertainty and 4) self-isolating whilst testing.

ConclusionsThis study has identified a range of factors that appear to influence the decision to engage in daily testing or to self-isolate following close contact with a positive case, many of which could be addressed by clear communications. Covid-19 infection rates and government restrictions influenced experiences, and so further research is needed to explore perceptions of daily testing and behaviour following close contact with a positive case among a wider range of individuals, in the context of lower rates of COVID-19, few government restrictions on general population behaviour and more widespread testing.


title: SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from functional annotations of SNPs, MNPs and InDels

abstract:
BackgroundFaced to the ongoing global pandemic of coronavirus disease, the  National Reference Centre for Whole Genome Sequencing of microbial pathogens: database and bioinformatic analysis (GENPAT) formally established at the  Istituto Zooprofilattico Sperimentale dellAbruzzo e del Molise (IZSAM) in Teramo (Italy) supports the genomic surveillance of the SARS-CoV-2. In a context of SARS-CoV-2 surveillance needed proper and fast assessment of epidemiological clusters from large amount of samples, the present manuscript proposes a workflow for identifying accurately the PANGOLIN lineages of SARS-CoV-2 samples and building of discriminant minimum spanning trees (MST) bypassing the usual time consuming phylogenomic inferences based on multiple sequence alignment (MSA) and substitution model.

ResultsGENPAT constituted two collections of SARS-CoV-2 samples. The samples of the first collection were isolated by IZSAM in the Abruzzo region (Italy), then shotgun sequenced and analyzed in GENPAT (n = 1 592), while those of the second collection were isolated from several Italian provinces and retrieved from the reference Global Initiative on Sharing All Influenza Data (GISAID) (n = 17 201). The main outcomes of the present study showed that (i) GENPAT and GISAID identified identical PANGOLIN lineages, (ii) the PANGOLIN lineages B.1.177 (i.e. historical in Italy) and B.1.1.7 (i.e.  UK variant) are major concerns today in several Italian provinces, and the new MST-based method (iii) clusters most of the PANGOLIN lineages together, (iv) with a higher dicriminatory power than PANGOLIN, (v) and faster that the usual phylogenomic methods based on MSA and substitution model.

ConclusionsThe shotgun sequencing efforts of Italian provinces, combined to a structured national system of metagenomics data management, provided support for surveillance SARS-CoV-2 in Italy. We recommend to infer phylogenomic relationships of SARS-CoV-2 variants through an accurate, discriminant and fast MST-based method bypassing the usual time consuming steps related to MSA and substitution model-based phylogenomic inference.


title: Quantitative susceptibility mapping captures chronic multiple sclerosis rim lesions with greater myelin damage: Comparison with high-pass filtered phase MRI

abstract:
BackgroundChronic active MS lesions with paramagnetic rim can be identified by high-pass filtered (HPF) phase imaging or quantitative susceptibility mapping (QSM).

PurposeThe objective was to compare the ability of HPF and QSM to identify MS lesions with greater myelin damage and to distinguish MS patients with increased clinical disability.

Material and MethodsEighty-six patients were scanned with gradient echo sequence for lesion rim detection and FAST-T2 sequence for myelin water fraction (MWF) mapping. Chronic lesions were classified based on the presence/absence of rim on HPF and QSM images (HPF rim+/QSM rim+, HPF rim+/QSM rim-, HPF rim-/QSM rim+, HPF rim-/QSM rim-). A lesion-level linear mixed-effects model with MWF as outcome was used to compare myelin damage among the lesion groups. A multivariate patient-level linear regression model was fit to establish the association between Expanded Disease Status Scale (EDSS) and the number of rim lesions (zero vs. one or more).

ResultsOf 2229 lesions, 96 (8.8%) were HPF rim+/QSM rim+, 211 (9.5%) were HPF rim+/QSM rim-, and the remainder had no rim. Adjusting for other factors, HPF rim+/QSM rim+ lesions had on average significantly lower MWF than both HPF rim+/QSM rim-(p<0.001) and HPF rim-/QSM rim-(p<0.001) lesions, while the MWF difference between HPF rim+/QSM rim- and HPF rim-/QSM rim-lesions was not statistically significant (p=0.309). Having at least one QSM rim+ lesion was associated with an increase in EDSS compared to having no QSM rim+ lesions, holding all other factors constant (p=0.026). The relationship between having one or more HPF rim+ lesions vs. having no HPF rim+ lesions and EDSS was not statistically significant.

ConclusionQSM identifies chronic MS lesions with paramagnetic rim that on average have greater myelin damage. QSM may be a valuable tool for studying the impact of rim lesions on clinical disability in MS.


title: Nursing students' attitudes, knowledge, and willingness to receive the COVID-19 vaccine: A cross-sectional study

abstract:
AimTo investigate nursing students konwledge, attitudes and willingness to receive the COVID-19 vaccine, and the influencing factors.

BackgroundVaccination is one of the effective measures to prevent COVID-19, but the vaccination acceptance varies across countries and populations. As reserve nurses, nursing students have both the professionalism of medical personnel and the special characteristics of school students, their attitudes, knowledge, and willingness to receive the COVID-19 vaccine may greatly affect the vaccine acceptance of the population now and in the future. But little research has been done on vaccine acceptance among nursing students.

DesignA cross-sectional survey of nursing students was conducted via online questionnaires in March 2021.

MethodsDescriptive statistics, independent sample t tests/one-way ANOVA (normal distribution), Mann-Whitney U tests/Kruskal-Wallis H tests (skewness distribution) and multivariate linear regression were performed.

ResultsThe score rate of attitude, knowledge and vaccination willingness were 70.07%, 80.70% and 84.38% respectively. Attitude was significantly influenced by family economic conditions and whether a family member had been vaccinated. The main factors influencing knowledge were gender, grade and academic background. In terms of willingness, gender, academic background, visits to risk areas, whether family members were vaccinated, and whether they had side effects were significant influencing factors.

ConclusionsThe vaccine acceptance of nursing students was fair. Greater focus needed to be placed on the males, those of younger age, with a science background, and having low grades, as well as on students whose family members had not received the COVID-19 vaccine or had side effects from the vaccine. Targeted intervention strategies were recommended to improve vaccination rates.

category: nursing


title: Cardiovascular Disease in the Peruvian Highlands: Local Perceptions, Barriers, and Paths to Preventing Chronic Diseases in Andean Adults

abstract:
ObjectivesPublic health interventions can be improved by understanding peoples explanatory models of disease. We explore awareness and perceptions of cardiovascular diseases (CVD) and options for preventive actions in young rural adults highlanders.

Methods46 men and women from communities in Cajamarca, Peru were purposively selected to participate in eight focus groups, where participants discussed their understanding and perceived causes of CVD as well as barriers and pathways to healthy lifestyles.

ResultsFresh foods, physical activity, unpleasant emotions, and healthcare access were cited as important determinants of healthy lifestyles. Barriers to healthy diets included lacking nutritional knowledge, fluctuating food prices, and limited access to foodstuffs. Women felt particularly vulnerable to CVD and identified gendered barriers to manage stress and engage in leisure sports. Low health literacy, distance and poor doctor-patient relationships prevented participants from fully accessing healthcare.

ConclusionsCVD prevention should consider local knowledge of these diseases and of healthy lifestyles and harness ongoing programmes that have successfully promoted good nutrition in children and pregnant women. In concert with public-private parterships, governments should include health prevention for the entire family.


title: Addressing anti-syncytin antibody levels, and fertility and breastfeeding concerns, following BNT162B2 COVID-19 mRNA vaccination

abstract:
ObjectiveTo determine whether antibodies against the SARS-CoV-2 spike protein following BNT162B2 (Pfizer-BioNTech) COVID-19 mRNA vaccination cross-react with human syncytin-1 protein, and if BNT162B2 mRNA enters breast milk.

MethodsIn this observational cohort study of female front-line workers with no history of COVID-19 infection, we amplified BNT162B2 mRNA in plasma and breast milk and assayed anti-SARS-CoV-2 neutralising antibodies and anti-human syncytin-1 binding antibodies in plasma, at early (1-4 days) and late (4-7 weeks) time points following first-dose vaccination.

ResultsFifteen consented participants (mean age 40.4 years, various ethnicities) who received at least one dose of BNT162B2, including five breast-feeding women and two women who were inadvertently vaccinated in early pregnancy, were recruited. BNT162B2 mRNA, detected by amplifying part of the spike-encoding region, was detected in plasma 1-4 days following the first dose (n=13), but not 4-5 weeks later (n=2), nor was the mRNA isolated from aqueous or lipid breast milk fractions collected 0-7 days post-vaccination (n=5). Vaccine recipients demonstrated strong SARS-CoV-2 neutralising activity by at least four weeks after the first dose (n=15), including the two pregnant women. None had placental anti-syncytin-1 binding antibodies at either time-point following vaccination.

ConclusionsBNT162B2-vaccinated women did not transmit vaccine mRNA to breast milk, and did not produce a concurrent humoral response to syncytin-1, suggesting that cross-reactivity to syncytin-1 on the developing trophoblast, or other adverse effects in the breast-fed infant from vaccine mRNA ingestion, are unlikely.

What are the novel findings of this work?COVID-19 vaccination with BNT162B2 did not elicit a cross-reacting humoral response to human syncytin-1 despite robust neutralising activity to the SARS-CoV2 spike protein, and while vaccine mRNA was isolated from plasma, it was not found in breast milk.

What are the clinical implications of this work?Our work directly addresses the fertility and breastfeeding concerns fuelling vaccine hesitancy among reproductive-age women, by suggesting that BNT162B2 vaccination is unlikely to cause adverse effects on the developing trophoblast, via cross-reacting anti-syncytin-1 antibodies, or to the breastfed neonate, via mRNA breast milk transmission.

category: obstetrics and gynecology


title: Single-dose SARS-CoV-2 vaccine in a prospective cohort of COVID-19 patients

abstract:
BackgroundThe urgent need for, but limited availability of, SARS-CoV-2 vaccines worldwide has led to widespread consideration of dose sparing strategies, particularly single vaccine dosing of individuals with prior SARS-CoV-2 infection.

MethodsWe evaluated SARS-CoV-2 specific antibody responses following a single-dose of BNT162b2 (Pfizer-BioNTech) mRNA vaccine in 155 previously SARS-CoV-2-infected individuals participating in a population-based prospective cohort study of COVID-19 patients.

Participants varied widely in age, comorbidities, COVID-19 severity and time since infection, ranging from 1 to 15 months. Serum antibody titers were determined at time of vaccination and one week after vaccination. Responses were compared to those in SARS-CoV-2-naive health care workers after two BNT162b2 mRNA vaccine doses.

ResultsWithin one week of vaccination, IgG antibody levels to virus spike and RBD proteins increased 27 to 29-fold and neutralizing antibody titers increased 12-fold, exceeding titers of fully vaccinated SARS-CoV-2-naive controls (95% credible interval (CrI): 0.56 to 0.67 v. control 95% CrI: -0.16 to -0.02). Pre-vaccination neutralizing antibody titers had the largest positive mean effect size on titers following vaccination (95% CrI (0.16 to 0.45)). COVID-19 severity, the presence of comorbidities and the time interval between infection and vaccination had no discernible impact on vaccine response.

ConclusionA single dose of BNT162b2 mRNA vaccine up to 15 months after SARS-CoV-2 infection provides neutralizing titers exceeding two vaccine doses in previously uninfected individuals. These findings support wide implementation of a single-dose mRNA vaccine strategy after prior SARS-CoV-2 infection.

category: infectious diseases


title: Projecting the impact of nutrition policy to improve child stunting: A case study in Guatemala using the Lives Saved Tool

abstract:
BackgroundChild stunting is a critical global health issue. Guatemala has one of the worlds highest levels of stunting despite sustained commitment to international nutrition policy best-practices endorsed by the Scaling Up Nutrition movement (SUN). Our objective was to use Guatemala as a case study by projecting the impact of a recently published national nutrition policy, the Great Crusade, that is consistent with SUN principles.

MethodsWe used the Lives Saved Tool (LiST) to project the scaling-up of nutrition interventions proposed in the Great Crusade and recommended by SUN. Our outcomes were changes in stunting prevalence, number of stunting cases averted, and number of cases averted by intervention in children under five years of age from 2020-2030. We considered four scenarios: (1) intervention coverage continues based on historical trends, (2) coverage targets in the Great Crusade are achieved, (3) coverage targets in the Great Crusade are achieved with reduced fertility risk, and (4) coverage reaches an aspirational level.

ResultsAll scenarios led to modest reductions in stunting prevalence. In 2024, stunting prevalence was estimated to change by -0.1% (95% CI 0.0% to -0.2%) if historical trends continue, -1.1% (95% CI -0.8% to -1.5%) in the Great Crusade scenario, and -2.2% (95% CI - 1.6% to -3.0%) in the aspirational scenario. In 2030, we projected a stunting prevalence of -0.4% (95% CI -0.2% to -0.8%) and -3.7% (95% CI -2.8% to -5.1%) in the historical trends and aspirational scenario, respectively. Complementary feeding, sanitation, and breastfeeding were the most impactful interventions across models.

ConclusionsTargeted reductions in child stunting prevalence in Guatemala are unlikely to be achieved solely based on increases in intervention coverage. Our results show the limitations of current paradigms recommended by the international nutrition community. Policies and strategies are needed that address the broader structural drivers of stunting.


title: Plitidepsin has a positive therapeutic index in adult patients with COVID-19 requiring hospitalization.

abstract:
Plitidepsin is a marine-derived cyclic-peptide that inhibits SARS-CoV-2 replication at low nanomolar concentrations by the targeting of host protein eEF1A (eukaryotic translation-elongation-factor-1A). We evaluated a model of intervention with plitidepsin in hospitalized COVID-19 adult patients where three doses were assessed (1.5, 2 and 2.5 mg/day for 3 days, as a 90-minute intravenous infusion) in 45 patients (15 per dose-cohort). Treatment was well tolerated, with only two Grade 3 treatment-related adverse events observed (hypersensitivity and diarrhea). The discharge rates by Days 8 and 15 were 56.8% and 81.8%, respectively, with data sustaining dose-effect. A mean 4.2 log10 viral load reduction was attained by Day 15. Improvement in inflammation markers was also noted in a seemingly dose-dependent manner. These results suggest that plitidepsin impacts the outcome of patients with COVID-19.

One-Sentence SummaryPlitidepsin, an inhibitor of SARS-Cov-2 in vitro, is safe and positively influences the outcome of patients hospitalized with COVID-19.


title: Blood-based epigenome-wide analyses of cognitive abilities

abstract: Using blood-based epigenome-wide analyses of general cognitive function (g; n=9,162) we show that individual differences in DNA methylation (DNAm) explain 35.0% of the variance in g. A DNAm predictor explains [~]4% of the variance in g, independently of a polygenic score, in two external cohorts. It also associates with circulating levels of neurology- and inflammation-related proteins, global brain imaging metrics, and regional cortical volumes. As sample sizes increase, our ability to assess cognitive function from DNAm data may be informative in settings where cognitive testing is unreliable or unavailable.


title: Metabolomics and a Breath Sensor Identify Acetone as a Biomarker for Heart Failure

abstract:
BackgroundMultiomics delivers more biological insight than targeted investigations. We applied multiomics to patients with heart failure with reduced ejection fraction (HFrEF).

Methods46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography mass spectrometry (LCMS/GCMS) and solid-phase microextraction (SPME) volatilomics in plasma and urine. HFrEF was defined using left ventricular global longitudinal strain, ejection fraction and NTproBNP. A consumer breath acetone (BrACE) sensor validated results in n=73.

Results28 metabolites were identified by GCMS, 35 by LCMS and 4 volatiles by SPME in plasma and urine. Alanine, aspartate and glutamate, citric acid cycle, arginine biosynthesis, glyoxylate and dicarboxylate metabolism were altered in HFrEF. Plasma acetone correlated with NT-proBNP (r = 0.59, 95% CI 0.4 to 0.7), 2-oxovaleric and cis-aconitic acid, involved with ketone metabolism and mitochondrial energetics. BrACE> 1.5 ppm discriminated HF from other cardiac pathology (AUC 0.8, 95% CI 0.61 to 0.92, P < 0.0001).

ConclusionBreath acetone discriminated HFrEF from other cardiac pathology using a consumer sensor, but was not cardiac specific.

category: cardiovascular medicine


title: Exploiting Molecular Basis of Age and Gender Differences in Outcomes of SARS-CoV-2 Infections.

abstract:
MotivationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease, 2019; COVID-19) is associated with adverse outcomes in patients. It has been observed that lethality seems to be related to the age of patients. Moreover, it has been demonstrated that ageing causes some modifications at a molecular level.

ObjectiveThe study aims to shed out light on a possible link between the increased COVID-19 lethality and the molecular changes that occur in elderly people.

MethodsWe considered public datasets on ageing-related genes and their expression at tissue level. We selected interactors that are known to be related to ageing process. Then, we performed a network-based analysis to identify interactors significantly related to both SARS-CoV-2 and ageing. Finally, we investigated changes on the expression level of coding genes at tissue, gender and age level.

ResultsWe observed a significant intersection between some SARS-CoV-2 interactors and ageing-related genes suggesting that those genes are particularly affected by COVID-19 infection. Our analysis evidenced that virus infection particularly affects ageing molecular mechanisms centred around proteins EEF2, NPM1, HMGA1, HMGA2, APEX1, CHEK1, PRKDC, and GPX4. We found that HMGA1, and NPM1 have a different expression in lung of males, while HMGA1, APEX1, CHEK1, EEF2, and NPM1 present changes in expression in males due to aging effects.

ConclusionOur study generated a mechanistic framework to explaining the correlation between COVID-19 incidence in elderly patients and molecular mechanisms of ageing. This will provide testable hypotheses for future investigation and pharmacological solutions tailored on specific age ranges.


title: Pooled Surveillance Testing Program for Asymptomatic SARS-CoV-2 Infections in K-12 Schools and Universities

abstract: The negative impact of continued school closures during the height of the COVID-19 pandemic warrants the establishment of new cost-effective strategies for surveillance and screening to safely reopen and monitor for potential in-school transmission. Here, we present a novel approach to increase the availability of repetitive and routine Covid-19 testing that may ultimately reduce the overall viral burden in the community. We describe implementation of a testing program that included students, faculty and staff from K-12 schools and universities participating in the SalivaClear pooled surveillance method (Mirimus Clinical Labs, Brooklyn, NY). Over 400,000 saliva specimens were self-collected from students, faculty and staff from 93 K-12 schools and 18 universities and tested in pools of up to 24 samples over a 20-week period during this pandemic. Peaks of positive cases were seen in the days following the Halloween, Thanksgiving and New Year holidays. Pooled testing did not significantly alter the sensitivity of the molecular assay in terms of both qualitative (100% detection rate on both pooled and individual samples) and quantitative (comparable cycle threshold (CT) values between pooled and individual samples) measures. Pooling samples substantially reduced the costs associated with PCR testing and allowed schools to rapidly assess transmission and adjust prevention protocols as necessary. By establishing low-cost, weekly testing of students and faculty, pooled saliva analysis enabled schools to determine whether transmission had occurred, make data-driven decisions, and adjust safety protocols. Pooled testing is a fundamental component to the reopening of schools, minimizing transmission among students and faculty.


title: Modelling gambiense human African trypanosomiasis infection in villages of the Democratic Republic of Congo using Kolmogorov forward equations

abstract: Stochastic methods for modelling disease dynamics enables the direct computation of the probability of elimination of transmission (EOT). For the low-prevalence disease of human African trypanosomiasis (gHAT), we develop a new mechanistic model for gHAT infection that determines the full probability distribution of the gHAT infection using Kolmogorov forward equations. The methodology allows the analytical investigation of the probabilities of gHAT elimination in the spatially-connected villages of the Kwamouth and Mosango health zones of the Democratic Republic of Congo, and captures the uncertainty using exact methods. We predict that, if current active and passive screening continue at current levels, local elimination of infection will occur in 2029 for Mosango and after 2040 in Kwamouth, respectively. Our method provides a more realistic approach to scaling the probability of elimination of infection between single villages and much larger regions, and provides results comparable to established models without the requirement of detailed infection structure. The novel flexibility allows the interventions in the model to be implemented specific to each village, and this introduces the framework to consider the possible future strategies of test-and-treat or direct treatment of individuals living in villages where cases have been found, using a new drug.

category: epidemiology


title: High-resolution within-sewer SARS-CoV-2 surveillance facilitates informed intervention

abstract:
To assist in the COVID-19 public health guidance on a college campus, daily composite wastewater samples were withdrawn at 20 manhole locations across the University of Colorado Boulder campus. Low-cost autosamplers were fabricated in-house to enable an economical approach to this distributed study. These sample stations operated from August 25th until November 23rd during the fall 2020 semester, with 1,512 samples collected. The concentration of SARS-CoV-2 in each sample was quantified through two comparative reverse transcription quantitative polymerase chain reactions (RT-qPCRs). These methods were distinct in the utilization of technical replicates and normalization to an endogenous control. (1) Higher temporal resolution compensates for supply chain or other constraints that prevent technical or biological replicates. (2) The endogenous control normalized data agreed with the raw concentration data, minimizing the utility of normalization. The raw wastewater concentration values reflected SARS-CoV-2 prevalence on campus as detected by clinical services. Overall, combining the low-cost composite sampler with a method that quantifies the SARS-CoV-2 signal within six hours enabled actionable and time-responsive data delivered to key stakeholders. With daily reporting of the findings, wastewater surveillance assisted in decision making during critical phases of the pandemic on campus, from detecting individual cases within populations ranging from 109 to 2,048 individuals to monitoring the success of on-campus interventions.

SynopsisTracking SARS-CoV-2 in on-campus wastewater informs and monitors public health decisions and actions.

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category: public and global health


title: Behaviour of smokers and their influencers in the UK during COVID-19 pandemic

abstract:
PurposeThe COVID-19 pandemic has resulted in unprecedented circumstances and changes in behaviour. This research sought to better understand the impact of the COVID-19 pandemic, and lockdown, on smoking behaviour in the UK from the perspectives of consumers (current and former smokers) and some of their smoking-related behaviour-influencers.

Design/methodology/approachThis research project encompassed two surveys, one for current and former smokers (Consumers) and one for those individuals in professions with the potential to influence smoking behaviours (Influencers). Both surveys were conducted online and were infield for approximately two weeks during UKs first COVID-19 lockdown. Because of the unprecedented times the society was experiencing, several questions relating directly to COVID-19 were added to the survey and this paper is based only on findings only from those questions and not the whole project. The results were analysed descriptively.

FindingsA total of 954 consumers and 1027 influencers participated in the surveys. Increased smoking was reported by 67% of the consumers mainly due to stress and boredom arising out of COVID-19 lockdown. Consumers under 45 years of age, those in professional and managerial occupations, and among dual users reported increased smoking in lockdown. The COVID-19 situation changed the plans to quit smoking in 36% of consumers, with only 6% deciding to quit. Only 40% of healthcare professionals (HCPs) documented patient smoking status in over half their interactions.

Originality/ valueThis research among current and former smokers and their influencers highlights important changes in behaviour during the COVID-19 times and underscores urgent measures to be taken by HCPs and policymakers for staying on course of achieving smokefree goals despite challenges posed by COVID-19.


title: Internal Neurolysis for the Treatment of Trigeminal Neuralgia: Systematic Review

abstract:
IntroductionTrigeminal neuralgia remains a challenging disease with significant debilitating symptoms and variable efficacy in terms of treatment options, namely microvascular decompression (MVD), stereotactic radiosurgery (SRS), and percutaneous rhizotomy. Internal neurolysis (IN) is an alternative treatment that may be provide patient benefit but has limited understanding. We performed a systematic review of IN treatment of trigeminal neuralgia.

MethodsStudies from 2000 to 2021 that assessed IN in trigeminal neuralgia were aggregated and independently reviewed. Weighted averages for demographics, outcomes and complications were generated.

ResultsA total of 520 patients in 12 studies were identified with 384 who underwent IN (mean age 53.8 years, range 46-61.4 years). A mean follow-up time of 36.5 months (range 12-90 months) was seen. Preoperative symptoms were present for about 55.0 months before treatment and pain was predominantly in V2/3 (26.8%) followed by other distributions. An excellent to good outcome (Barrow Neurological Institute Pain Score [BNI-PS] I-III) was seen in 83.7% of patients (range 72-93.8%). Pain outcomes at 1 year were excellent in 58-78.4%, good or better in 77-93.75% and fair or better in 80-93.75% of patients. On average facial numbness following IN was seen in 96% of patients however at follow-up remained in only 1.75-10%. The vast majority of remaining numbness was not significantly distressing to patients. Subgroup comparisons of IN vs. recurrent MVD, IN vs. radiofrequency ablation, the impact of IN during the absence of vascular compression as well as IN with and without MVD were also evaluated.

ConclusionsIN represents a promising approach for surgical treatment of trigeminal neuralgia in the absence of vascular compression or in potential cases of recurrence. Complications were limited in general. Further study is required to evaluate the impact of IN via higher quality prospective studies.

category: surgery


title: Forecasting seizure likelihood with wearable technology

abstract:
The unpredictability of epileptic seizures exposes people with epilepsy to potential physical harm, restricts day-to-day activities, and impacts mental well-being. Accurate seizure forecasters would reduce the uncertainty associated with seizures but need to be feasible and accessible in the long-term. Wearable devices are perfect candidates to develop non-invasive, accessible forecasts but are yet to be investigated in long-term studies. We hypothesized that machine learning models could utilize heart rate as a biomarker for well-established cycles of seizures and epileptic activity, in addition to other wearable signals, to forecast high and low risk seizure periods.

This feasibility study tracked participants (n = 11) heart rates, sleep, and step counts using wearable smartwatches and seizure occurrence using mobile seizure diaries for at least 6 months (mean = 14.6 months, SD = 3.8 months). Eligible participants had a diagnosis of refractory epilepsy and reported at least 20 seizures (mean = 135, SD = 123) during the recording period. An ensembled machine learning and neural network model estimated seizure risk either daily or hourly, with retraining occurring on a weekly basis as additional data was collected. Performance was evaluated retrospectively against a rate-matched random forecast using the area under the receiver operating curve. A pseudo-prospective evaluation was also conducted on a held-out dataset.

Of the 11 participants, seizures were predicted above chance in all (100%) participants using an hourly forecast and in ten (91%) participants using a daily forecast. The average time spent in high risk (prediction time) before a seizure occurred was 37 minutes in the hourly forecast and 3 days in the daily forecast. Cyclic features added the most predictive value to the forecasts, particularly circadian and multiday heart rate cycles.

Wearable devices can be used to produce patient-specific seizure forecasts, particularly when biomarkers of seizure and epileptic activity cycles are utilized.

category: neurology


title: Systematic Review and Meta-Analysis Protocol: Beta adrenoreceptor drugs and risk of Parkinsons disease

abstract: Parkinsons disease (PD) is a progressive nervous system disorder characterised by the loss of dopaminergic neurons leading to motor and non-motor symptoms. Accumulation of -synuclein protein (SNCA) in the form of Lewy bodies has been observed in dopaminergic neurons of PD patients. Potential relationships between {beta}-adrenergic drugs (agonists and antagonist) and SNCA synthesis in PD have been recently suggested. This study aims to systematically review the evidence from various epidemiological studies that analysed the association between beta-adrenoceptors (agonists and antagonists) and the risk of PD. Biomedical databases such as PubMed and Embase will be searched to identify the individual studies that reported the relationship between beta-adrenoceptors and the risk of PD. JBI critical appraisal tool scale will be used to assess the quality of included studies. The primary outcome will be to compute the pooled risk of PD among beta-agonist and antagonist users. Furthermore, we will consider the pooled risk of PD based on study design, types of beta-agonist or antagonist exposure under secondary outcomes. RevMan 5, STATA 16, and ProMeta 3.0 will be used to conduct the statistical analysis.


title: Patient-level detection of grade group >=2 prostate cancer using quantitative diffusion MRI

abstract:
PurposeMultiparametric MRI (mpMRI) improves detection of clinically significant prostate cancer (csPCa), but the qualitative PI-RADS system and quantitative apparent diffusion coefficient (ADC) yield inconsistent results. An advanced Restrictrion Spectrum Imaging (RSI) model may yield a better quantitative marker for csPCa, the RSI restriction score (RSIrs). We evaluated RSIrs for patient-level detection of csPCa.

Materials and MethodsRetrospective analysis of men who underwent mpMRI with RSI and prostate biopsy for suspected prostate cancer from 2017-2019. Maximum RSIrs within the prostate was assessed by area under the receiver operating characteristic curve (AUC) for discriminating csPCa (grade group [≥]2) from benign or grade group 1 biopsies. Performance of RSIrs was compared to minimum ADC and PI-RADS v2-2.1via bootstrap confidence intervals and bootstrap difference (two-tailed =0.05). We also tested whether the combination of PI-RADS and RSIrs (PI-RADS+RSIrs) was superior to PI-RADS, alone.

Results151 patients met criteria for inclusion. AUC values for ADC, RSIrs, and PI-RADS were 0.50 [95% confidence interval: 0.41, 0.60], 0.76 [0.68, 0.84], and 0.78 [0.71, 0.85], respectively. RSIrs (p=0.0002) and PI-RADS (p<0.0001) were superior to ADC for patient-level detection of csPCa. The performance of RSIrs was comparable to that of PI-RADS (p=0.6). AUC for PI-RADS+RSIrs was 0.84 [0.77, 0.90], superior to PI-RADS or RSIrs, alone (p=0.008, p=0.009).

ConclusionsRSIrs was superior to conventional ADC and comparable to (routine, clinical) PI-RADS for patient-level detection of csPCa. The combination of PI-RADS and RSIrs was superior to either alone. RSIrs is a promising quantitative marker worthy of prospective study in the setting of csPCa detection.

DisclosuresMEH reports honoraria from Multimodal Imaging Services Corporation and research funding from General Electric Healthcare. AMD is a Founder of and holds equity in CorTechs Labs, Inc, and serves on its Scientific Advisory Board. He is a member of the Scientific Advisory Board of Human Longevity, Inc. and receives funding through research agreements with General Electric Healthcare. The terms of these arrangements have been reviewed and approved by the University of California San Diego in accordance with its conflict-of-interest policies. TMS reports honoraria from Multimodal Imaging Services Corporation, Varian Medical Systems, and WebMD; he has an equity interest in CorTechs Labs, Inc. and also serves on its Scientific Advisory Board. These companies might potentially benefit from the research results. The terms of this arrangement have been reviewed and approved by the University of California San Diego in accordance with its conflict-of-interest policies.

category: oncology