title: Implementation of an in-house real-time reverse transcription-PCR assay for the rapid detection of the SARS-CoV-2 Marseille-4 variant

abstract:
IntroductionThe SARS-CoV-2 pandemic has been associated with the occurrence since summer 2020 of several viral variants that overlapped or succeeded each other in time. Those of current concern harbor mutations within the spike receptor binding domain (RBD) that may be associated with viral escape to immune responses. In our geographical area a viral variant we named Marseille-4 harbors a S477N substitution in this RBD.

Materials and methodsWe aimed to implement an in-house one-step real-time reverse transcription-PCR (qPCR) assay with a hydrolysis probe that specifically detects the SARS-CoV-2 Marseille-4 variant.

ResultsAll 6 cDNA samples from Marseille-4 variant strains identified in our institute by genome next-generation sequencing (NGS) tested positive using our Marseille-4 specific qPCR, whereas all 32 cDNA samples from other variants tested negative. In addition, 39/42 (93%) respiratory samples identified by NGS as containing a Marseille-4 variant strain and 0/26 samples identified as containing non-Marseille-4 variant strains were positive. Finally, 1,585/2,889 patients SARS-CoV-2-diagnosed in our institute, 10/277 (3.6%) respiratory samples collected in Algeria, and none of 207 respiratory samples collected in Senegal, Morocco, or Lebanon tested positive using our Marseille-4 specific qPCR.

DiscussionOur in-house qPCR system was found reliable to detect specifically the Marseille-4 variant and allowed estimating it is involved in more than half of our SARS-CoV-2 diagnoses since December 2020. Such approach allows the real-time surveillance of SARS-CoV-2 variants, which is warranted to monitor and assess their epidemiological and clinical characterics based on comprehensive sets of data.


title: Investigation of association of rare, functional genetic variants with heavy drinking and problem drinking in exome sequenced UK Biobank participants

abstract:
AimsThe study aimed to identify specific genes and functional genetic variants affecting susceptibility to two alcohol related phenotypes: heavy drinking and problem drinking.

MethodsPhenotypic and exome sequence data was downloaded from the UK Biobank. Reported drinks in the last 24 hours was used to define heavy drinking while responses to a mental health questionnaire defined problem drinking. Gene-wise weighted burden analysis was applied, with genetic variants which were rarer and/or had a more severe functional effect being weighted more highly. Additionally, previously reported variants of interest were analysed inidividually.

ResultsOf exome sequenced subjects, for heavy drinking there were 8,166 cases and 84,461 controls while for problem drinking there were 7,811 cases and 59,606 controls. No gene was formally significant after correction for multiple testing but three genes possibly related to autism were significant at p < 0.001, FOXP1, ARHGAP33 and CDH9, along with VGF which may also be of psychiatric interest. Well established associations with rs1229984 in ADH1B and rs671 in ALDH2 were confirmed but previously reported variants in ALDH1B1 and GRM3 were not associated with either phenotype.

ConclusionsThis large study fails to conclusively implicate any novel genes or variants. It is possible that more definitive results will be obtained when sequence data for the remaining UK Biobank participants becomes available and/or if data can be obtained for a more extreme phenotype such as alcohol dependence disorder. This research has been conducted using the UK Biobank Resource.

Short summaryTests for association of rare, functional genetic variants with heavy drinking and problem drinking confirm the known effects of variants in ADH1B and ALDH2 but fail to implicate novel variants or genes. Results for three genes potentially related to autism suggest they might exert a protective effect.

category: addiction medicine


title: TOP-Plus is a Versatile Biosensor Platform for Monitoring SARS-CoV-2 Antibody Durability

abstract:
BackgroundThere is a concern that low initial SARS-CoV-2 antibody titers in individuals may drop to undetectable levels within months after infection. Although this may raise concerns over long term immunity, both the antibody levels and avidity of the antibody-antigen interaction should be examined to understand the quality of the antibody response.

MethodsA testing-on-a-probe "plus" panel (TOP-Plus) was developed, which included a newly developed avidity assay built into the previously described SARS-CoV-2 TOP assays that measured total antibody (TAb), surrogate neutralizing antibody (SNAb), IgM and IgG on a versatile biosensor platform. TAb and SNAb levels were compared with avidity in previously infected individuals at 1.3 and 6.2 months post-infection in paired samples from 80 COVID-19 patients.

ResultsThe newly designed avidity assay in this TOP panel correlated well with a reference Bio-Layer Interferometry avidity assay (R=0.88). The imprecision of the TOP avidity assay was less than 9%. Although TAb and neutralization activity (by SNAb) decreased between 1.3 and 6.2 months post infection, the antibody avidity increased significantly (P < 0.0001).

ConclusionThis highly precise and versatile TOP-Plus panel with the ability to measure SARS-CoV-2 TAb, SNAb, IgG and IgM antibody levels and avidity of individual sera on one sensor can become a valuable asset in monitoring not only SARS-CoV-2-infected patients, but also the status of individuals COVID-19 vaccination response.

category: allergy and immunology


title: COVID-19 transmission in educational institutions August to December 2020, Rhineland-Palatinate, Germany: a study of index cases and close contact cohorts

abstract:
BackgroundThe lack of precise estimates on transmission risk hampers rational decisions on closure of educational institutions during the COVID-19 pandemic.

MethodsSecondary attack rates (SARs) for schools and day-care centres were calculated using data from state-wide mandatory notification of SARS-CoV-2 index cases in educational institutions and information on routine contact tracing and PCR-testing.

FindingsFrom August to December 2020, every sixth of overall 784 independent index cases caused a transmission in educational institutions (risk 0{middle dot}17, 95% CI 0{middle dot}14-0{middle dot}19). In a subgroup, monitoring of 14,594 institutional high-risk contacts (89% PCR-tested) of 441 index cases revealed 196 secondary cases (SAR 1{middle dot}34%, 1{middle dot}16-1{middle dot}54). Transmission was more likely from teachers than from students/children (incidence risk ratio [IRR] 3{middle dot}17, 1{middle dot}79-5{middle dot}59), and from index cases in day-care centres (IRR 3{middle dot}23, 1{middle dot}76-5{middle dot}91) than from those in secondary schools. In 748 index cases, teachers caused four times more secondary cases than children (1{middle dot}08 vs. 0{middle dot}25 secondary cases per index, IRR 4{middle dot}39, 2{middle dot}67-7{middle dot}21). This difference was mainly due to a large number of teacher-to-teacher transmissions in day-care centres (mean number of secondary cases 0.66) and a very low number of student/child-to-teacher transmissions in schools (mean number of secondary cases 0.004).

InterpretationIn educational institutions, the risk of infection for contacts to a confirmed COVID-19 case is one percent, but varies depending on type of institution and index case. Hygiene measures and vaccination targeting the day-care setting and teacher-to-teacher transmission are priorities in reducing the burden of infection and may promote educational justice during the pandemic.

FundingNo particular funding was received for this study.

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed on Jan 27, 2021, without any language restrictions for all articles in which the title or abstract contained the search terms "COVID 19" or "corona", and "school", "education*", or "daycare", and "transmission", and "risk", "attack rate", or "SAR", and screened 175 results for original research or reviews on COVID-19 transmission risk in the educational setting. Following a similar strategy, we also searched Google Scholar, SSRN, medRxiv, and the reference lists of identified literature. We found five cohort studies on transmission risk looking at overall 171 index cases and their 6,910 contact persons in Australian, Italian, Irish, Singaporean, and German schools and reporting attack rates between 0% and 3% percent. These five studies were conducted before October 2020 and thus looked at COVID-19 transmission risk in schools before the second wave in Europe.

A number of modelling studies from the first wave of COVID-19 provide inconclusive guidance to policy makers. While two publications, one from several countries and one from Switzerland, concluded that school closures contributed markedly to the reduction of SARS-CoV-2 transmission and individual mobility, two other studies, one using cross-country data and one from Japan rated school closures among the least effective measures to reduce COVID-19 incidence rates.

Added value of this studyBased on a large data set that emerged from the current public health practice in Germany, which incorporates routine PCR-testing during active follow-up of asymptomatic high-risk contacts to index cases, this study provides a precise estimate of the true underlying SARS-CoV-2 transmission risk in schools and day-care centres. Its analysis also allows for a meaningful examination of differences in the risk of transmission with respect to the characteristics of the index case. We found that the individual risk of acquiring SARS-CoV-2 among high-risk contacts in the educational setting is 1.3%, but that this risk rises to 3.2% when the index case is a teacher and to 2.5% when the index case occurs in a day-care centre. Furthermore, we could show that, on average, teacher index cases produced about four times as many secondary cases as student/child index cases. Despite the relatively small proportion of teachers among index cases (20%), our study of transmission pathways revealed that the majority of all secondary cases (54%), and the overwhelming majority of secondary cases in teachers (78%) were caused by teacher index cases. Of note, most cases of teacher-to-teacher transmission (85%) occurred in day-care centres.

Implications of all the available evidenceIn this setting, where preventative measures are in place and COVID-19 incidence rates were rising sharply in the population, we found a low and stable transmission risk in educational institutions over time, which provides evidence for the effectiveness of current preventative measures to control the spread of COVID-19 in schools. The identification of a substantial teacher-to-teacher transmission risk in day-care, but a clearly mitigated child/student-to-teacher transmission risk in schools, indicates the need to shift the focus to hygiene among day-care teachers, including infection prevention during staff-meetings and in break rooms. These findings also strongly support the re-prioritization of vaccination against SARS-CoV-2 to educational staff in day-care.

category: epidemiology


title: COVID-19 transmission in educational institutions August to December 2020 in Germany: a study of index cases and close contact cohorts


title: Is the Association Between Smoking and Depression Mediated by Inflammation? A Mendelian Randomization Study.

abstract: Smoking, inflammation and depression commonly co-occur and may be mechanistically linked. However, key questions remain around the direction of association and the influence of residual confounding. We aimed to characterize the association between lifetime smoking and depression, as well as to assess the role that genetically-predicted C-reactive protein (CRP) level, an archetypal inflammatory marker, as a potential mediator for this association. We performed inverse variance weighted Mendelian randomization (MR) analyses using recently published summary-level GWAS data for lifetime smoking index, CRP levels, and depression. A subset of inflammatory-related genetic variants from the lifetime smoking GWAS were also used to assess the potential inflammatory causal pathways between smoking and depression. The analysis indicated significant reciprocal relationships between lifetime smoking and both depression (ORSmk-Dep = 2.01, 95% CI 1.71-2.37, p < 0.001; O RDep-Smk = 1.09, 95% CI 1.06-1.13, p < 0.001) and CRP levels (ORSmk-CRP = 1.40, 95% CI 1.21-1.55, p < 0.001; ORCRP-Smk = 1.03, 95% CI 1.02-1.05, p < 0.001). These significant and positive associations were also supported by the majority of the robust MR methods performed. The reciprocal relationships between CRP levels (using >500 genetic instruments for CRP) and depression were not significant (ORCRP-Dep = 1.01, 95% CI 0.99-1.04; ORDep-CRP = 1.03, 95% CI 0.99-1.07). We observed little variation in the IVW estimates between smoking and depression when we limited the genetic variants assessed to those related to inflammation or when we adjusted the analysis by CRP-levels in multivariable analysis. Our study supports potential causal associations between lifetime smoking and depression, as well as between lifetime smoking and CRP levels, but not between CRP and depression. No evidence was found that CRP mediates the relationship between smoking and depression.


title: Modeling Influenza Seasonality in the Tropics and Subtropics

abstract: Climate drivers such as humidity and temperature may play a key role in influenza seasonal transmission dynamics. Such a relationship has been well defined for temperate regions. However, to date no models capable of capturing the diverse seasonal pattern in tropical and subtropical climates exist. In addition, multiple influenza viruses could cocirculate and shape epidemic dynamics. Here we construct seven mechanistic epidemic models to test the effect of two major climate drivers (humidity and temperature) and multi-strain co-circulation on influenza transmission in Hong Kong, an influenza epidemic center located in the subtropics. Based on model fit to long-term influenza surveillance data from 1998 to 2018, we found that a simple model incorporating the effect of both humidity and temperature best recreated the influenza epidemic patterns observed in Hong Kong. The model quantifies a bimodal effect of absolute humidity on influenza transmission where both low and very high humidity levels facilitate transmission quadratically; the model also quantifies the monotonic but nonlinear relationship with temperature. In addition, model results suggest that, at the population level, a shorter immunity period can approximate the co-circulation of influenza virus (sub)types. The basic reproductive number R0 estimated by the best-fit model is also consistent with laboratory influenza survival and transmission studies under various combinations of humidity and temperature levels. Overall, our study has developed a simple mechanistic model capable of quantifying the impact of climate drivers on influenza transmission in (sub)tropical regions. This model can be applied to improve influenza forecasting in the (sub)tropics in the future.


title: Emergence of SARS-CoV-2 stains harbouring the signature mutations of both A2a and A3 clade

abstract: SARS-CoV-2 strains with both high transmissibility and potential to cause asymptomatic infection is expected to gain selective advantage over other circulating strains having either high transmissibility or ability to trigger asymptomatic infection. The D614G mutation in spike glycoprotein, the characteristic mutation A2a clade, has been associated with high transmissibility, whereas the A3 clade specific mutation L37F in NSP6 protein has been linked with asymptomatic infection. In this study, we performed a comprehensive mutational analysis of 3,77,129 SARS-CoV-2 genomes collected during January, 2020 to December, 2020 from all across the world for the presence of D614G and L37F mutations. Out of 3,77,129 SARS-CoV-2 strains analysed, 14, 598 (3.87%) were found to harbour both the D614G and L37F mutations. Majority of these double mutant SARS-CoV-2 strains were identified in Europe (11097) followed by North America (1915), Asia (980), Oceania (242), Africa (219), and South America (145). Geographical root surveillance revealed their first emergence during February-March in all the six continents. Temporal prevalence analysis from February, 2020 to December, 2020 showed a gradual upsurge in their frequencies worldwide, which strongly demonstrated the adaptive selection of these double mutants. Evolutionary analysis depicted that these double mutants emerged as a new clade in the dendrogram (named as A2a/3), and were sub-divided into four distinct clusters (Cluster I, II, III and IV) according to different sets of coexisting mutations. The frequency distribution pattern showed the global predominance of cluster III (41.42%), followed by cluster IV (23.31%), cluster II (21.02%) and cluster I (14.25%). Overall, our study highlighted the emergence of a unique phylogenetic clade encompassing the double-mutant SARS-CoV-2 strains which may provide a fitness advantage during course of virus evolution.


title: A Cross-Sectional Study Evaluating Tick-borne Encephalitis Vaccine Uptake and Timeliness Among Adults in Switzerland

abstract:
ObjectivesThe goal of this study was to evaluate timeliness of Tick-borne Encephalitis vaccination uptake among adults in Switzerland.

MethodsIn this cross-sectional survey, we collected vaccination records from randomly selected adults 18-79 throughout Switzerland. Of 4,626 participants, data from individuals receiving at least 1 TBE vaccination (n=1875) were evaluated. We determined year and age of first vaccination and vaccine compliance, evaluating dose timeliness. Participants were considered "on time" if they received doses according to the recommended schedule {+/-} a 15% tolerance period.

Results45% of participants received their first TBE vaccination between 2006 and 2009. 25% were first vaccinated aged 50+ (mean age 37). More than 95% of individuals receiving the first dose also received the second; [~]85% of those receiving the second dose received the third. For individuals completing the primary series, 30% received 3 doses of Encepur, 58% received 3 doses of FSME-Immun, and 12% received a combination. According to conventional schedules, 88% and 79% of individuals received their second and third doses "on time", respectively. 20% of individuals receiving Encepur received their third dose "too early". Of individuals completing primary vaccination, 19% were overdue for a booster. Among the 31% of subjects receiving a booster, mean time to first booster was 7.1 years.

ConclusionsWe estimate that a quarter of adults in Switzerland were first vaccinated for TBE aged 50+. Approximately 80% of participants receiving at least one vaccine dose completed the primary series. We further estimate that 66% of individuals completing the primary series adhered to an "ideal" TBE vaccination schedule.


title: SARS-CoV-2 Seroprevalence in Tamil Nadu in October-November 2020

abstract: A population-representative serological study was conducted in all districts of the state of Tamil Nadu (population 72 million), India, in October-November 2020. State-level seroprevalence was 31.6%. However, this masks substantial variation across the state. Seroprevalence ranged from just 11.1% in The Nilgris to 51.0% in Perambalur district. Seroprevalence in urban areas (36.9%) was higher than in rural areas (26.9%). Females (30.8%) had similar seroprevalence to males (30.3%). However, working age populations (age 40-49: 31.6%) have significantly higher seroprevalence than the youth (age 18-29: 30.7%) or elderly (age 70+: 25.8%). Estimated seroprevalence implies that at least 22.6 million persons were infected by the end of November, roughly 36 times the number of confirmed cases. Estimated seroprevalence implies an infection fatality rate of 0.052%.


title: Understanding the pattern of symptoms for pancreatic neuroendocrine neoplasms (PNENs) to improve the early diagnosis of pancreatic cancer: analysis of the QResearch database

abstract: This article is the study protocol and statistical analysis plan for the project. This study is set up to identify and quantify "red flag" symptoms associated with the diagnosis of Pancreatic Neuroendocrine Neoplasm (PNEN) and compare these with the symptoms associated with Pancreatic Ductal Adenocarcinoma (PDAC). The results of this study will inform the evidence base for the refinement of the QCancer (Pancreas) tools, which have been integrated into the UK NHS primary care computer systems, to improve the early recognition of PNEN.


title: Inhaled budesonide in the treatment of early COVID-19 illness: a randomised controlled trial

abstract:
BackgroundMultiple early hospital cohorts of coronavirus disease 2019 (COVID-19) showed that patients with chronic respiratory disease were significantly under-represented. We hypothesised that the widespread use of inhaled glucocorticoids was responsible for this finding and tested if inhaled glucorticoids would be an effective treatment for early COVID-19 illness.

MethodsWe conducted a randomised, open label trial of inhaled budesonide, compared to usual care, in adults within 7 days of the onset of mild Covid-19 symptoms. The primary end point was COVID-19-related urgent care visit, emergency department assessment or hospitalisation. The trial was stopped early after independent statistical review concluded that study outcome would not change with further participant enrolment.

Results146 patients underwent randomisation. For the per protocol population (n=139), the primary outcome occurred in 10 participants and 1 participant in the usual care and budesonide arms respectively (difference in proportion 0.131, p=0.004). The number needed to treat with inhaled budesonide to reduce COVID-19 deterioration was 8. Clinical recovery was 1 day shorter in the budesonide arm compared to the usual care arm (median of 7 days versus 8 days respectively, logrank test p=0.007). Proportion of days with a fever and proportion of participants with at least 1 day of fever was lower in the budesonide arm. Fewer participants randomised to budesonide had persistent symptoms at day 14 and day 28 compared to participants receiving usual care.

ConclusionEarly administration of inhaled budesonide reduced the likelihood of needing urgent medical care and reduced time to recovery following early COVID-19 infection.

(Funded by Oxford NIHR Biomedical Research Centre and AstraZeneca; ClinicalTrials.gov number, NCT04416399)

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThe majority of interventions studied for the COVID-19 pandemic are focused on hospitalised patients. Widely available and broadly relevant interventions for mild COVID-19 are urgently needed.

Added value of this studyIn this open label randomised controlled trial, inhaled budesonide, when given to adults with early COVID-19 illness, reduces the likelihood of requiring urgent care, emergency department consultation or hospitalisation. There was also a quicker resolution of fever, a known poor prognostic marker in COVID-19 and a faster self-reported and questionnaire reported symptom resolution. There were fewer participants with persistent COVID-19 symptoms at 14 and 28 days after budesonide therapy compared to usual care.

Implications of all the available evidenceThe STOIC trial potentially provides the first easily accessible effective intervention in early COVID-19. By assessing health care resource utilisation, the study provides an exciting option to help with the worldwide pressure on health care systems due to the COVID-19 pandemic. Data from this study also suggests a potentially effective treatment to prevent the long term morbidity from persistent COVID-19 symptoms.

category: primary care research


title: Skin cancer high-risk patient screening from dermoscopic images via Artificial Intelligence: an online study

abstract:
ObjectivesTo evaluate a novel Artificial Intelligence (AI) method for the detection of malignant skin lesions from dermoscopic images.

Methods58,457 dermoscopic images available online from the International Skin Imaging Collaboration (ISIC) Archive were downloaded. These images were acquired from different centers worldwide by recognized dermatologists and show varied clinical outcomes belonging to different types of benign and malign skin lesions. A state-of-the-art AI skin lesion classifier based on Deep Learning was designed. The method, fully automated, first locates and segments the nevus in the image and then classifies it into either benign or malign type.

Results1,631 images (2.8%) were discarded due to bad quality. A total of 56,826 images were finally used. Two thirds of the images (37,688) were used to train the classifier, leaving the remaining 19,138 images for validation. In this set, malignant lesions had a prevalence of 15.4% (2,956/19,138). The AI skin lesion classifier reached an area under the curve (AUC) of 87.4%. Optimal cut-off point in terms of accuracy resulted in an 85.9% accuracy (16,439/19,138) and sensibility of 89.6% (2,648/ 2,956) at 85.2% (13,791/16,182) specificity. Negative predictive value (NPV) was 97.8% (13,791/14,099). Other training/validation splits were also evaluated, showing similar results.

ConclusionsA novel AI method showed promising results as skin lesion classifier from dermoscopic images. Its high NPV value could make it suited for high-risk patient screening. A large clinical study to confirm these results is needed and will be pursued.

category: radiology and imaging


title: Tau-PET and in vivo Braak-staging as a prognostic marker in Alzheimer's disease

abstract:
INTRODUCTIONTau pathology in Alzheimers disease tracks clinical status more closely than beta-amyloid. Thus, tau-PET may be a promising prognostic marker for cognitive decline. Here, we systematically compared tau-PET and Braak-staging vs. amyloid-PET as predictors of cognitive decline.

METHODSWe included 396 cognitively normal to dementia subjects with 18F-Flutemetamol/18F-Florbetapir-amyloid-PET, 18F-Flortaucipir-tau-PET and ~2-year cognitive assessments. Annual cognitive change rates were calculated via linear-mixed models. We determined global amyloid-PET, global tau-PET, and tau-PET-based Braak-stage (Braak0/BraakI+/BraakI-IV+/BraakI-VI+/Braakatypical+). In bootstrapped linear regression, we assessed whether tau-PET outperformed amyloid-PET in predicting cognitive decline. Using ANCOVAs, we tested whether later Braak-stage predicted accelerated cognitive decline and determined Braak-stage-specific conversion risk to MCI or dementia.

RESULTSGlobal tau-PET was a better predictor of cognitive decline than global amyloid-PET (p<0.001). Advanced Braak-stage was associated with faster cognitive decline (p<0.001) and elevated clinical conversion risk.

DISCUSSIONTau-PET and Braak-staging show promise for predicting patient-specific risk of clinical AD progression.

category: neurology


title: Neuromotor Prosthetic to Treat Stroke-Related Paresis

abstract:
AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSFunctional recovery of independent arm movement typically plateaus within six months following a stroke, leaving chronic motor deficits. This feasibility study tested whether a wearable, powered exoskeletal orthosis, driven by a percutaneous, implanted brain-computer interface (BCI), using the activity of neurons in the precentral gyrus in the affected cortical hemisphere, could restore voluntary upper extremity function in a person with chronic hemiparetic subsequent to a cerebral hemispheric stroke of subcortical gray and white matter and cortical gray matter.

MethodsOne person with chronic hemiparetic stroke with upper-limb motor impairment used a powered elbow-wrist-hand orthosis that opened and closed the affected hand using cortical activity, recorded from four 64-channel microelectrode arrays implanted in the ipsilesional precentral gyrus, based on decoding of spiking patterns and high frequency field potentials generated by imagined hand movements using technology and decoding methods used for people with other causes of paralysis. The system was evaluated in a home setting daily for 12 weeks.

ResultsRobust single unit activity, modulating with attempted or imagined movement, was present throughout the precentral gyrus areas. The participant was able to acquire voluntary control over a hand-orthosis BCI, with a score of 10 points on the Action Research Arm Test (out of 53) using the BCI, compared to 0 without any device, and 5 using myoelectric control. Orthosis-powered hand-opening was faster with BCI control compared to myoelectric control, on a standardized object-movement task.

ConclusionsThe findings demonstrate the therapeutic potential of an implantable BCI system coupled to a brace to "electrically bypass" the stroke and promote neurally driven limb function. The participants ability to rapidly acquire voluntary control over otherwise paralyzed hand opening, more than 18 months after a subcortical stroke, lays the foundation for a fully implanted movement restoration system.


title: High-throughput splicing assays identify missense and silent splice-disruptive POU1F1 variants underlying pituitary hormone deficiency

abstract: Pituitary hormone deficiency occurs in [~]1:4,000 live births. Approximately 3% of the cases are due to mutations in the alpha isoform of POU1F1, a pituitary-specific transcriptional activator. We found four separate heterozygous missense variants in unrelated hypopituitarism patients that were predicted to affect a minor isoform, POU1F1 beta, which can act as a transcriptional repressor. These variants retain repressor activity, but they shift splicing to favor the expression of the beta isoform, resulting in dominant negative loss of function. Using a high throughput splicing reporter assay, we tested 1,080 single nucleotide variants in POU1F1. We identified 113 splice disruptive variants, including 23 synonymous variants. We evaluated separate cohorts of hypopituitarism patients and found two different synonymous splice disruptive variants that co-segregate with hypopituitarism. This study underlines the importance of evaluating the impact of variants on splicing and provides a catalog for interpretation of variants of unknown significance in the POU1F1 gene.

category: genetic and genomic medicine


title: Staff-Pupil SARS-CoV-2 Infection Pathways in Schools: A Population Level Linked Data Approach

abstract:
BackgroundBetter understanding of the role that children and school staff play in the transmission of SARS-CoV-2 is essential to guide policy development on controlling infection whilst minimising disruption to childrens education and wellbeing.

MethodsOur national e-cohort (n=500,779) study used anonymised linked data for pupils, staff and associated households linked via educational settings. We estimated the risk of testing positive for SARS-CoV-2 infection for staff and pupils over the period August - December 2020, dependent on measures of recent exposure to known cases linked to their educational settings.

ResultsThe total number of cases in a school was not associated with a subsequent increase in the risk of testing positive (Staff OR per case 0.92, 95%CI 0.85, 1.00; Pupils OR per case 0.98, 95%CI 0.93, 1.02). Amongst pupils, the number of recent cases within the same year group was significantly associated with subsequent increased risk of testing positive (OR per case 1.12, 95%CI 1.08 - 1.15). These effects were adjusted for a range of demographic covariates, and in particular any known cases within the same household, which had the strongest association with testing positive (Staff OR 39.86, 95%CI 35.01, 45.38, pupil OR 9.39, 95%CI 8.94 - 9.88).

ConclusionsIn a national school cohort, the odds of staff testing positive for SARS-CoV-2 infection were not significantly increased in the 14-day period after case detection in the school. However, pupils were found to be at increased risk, following cases appearing within their own year group, where most of their contacts occur. Strong mitigation measures over the whole of the study period may have reduced wider spread within the school environment.

O_TEXTBOXWhat is knownO_LIEvidence of the role schools play in the transmission of SARS-CoV-2 is limited
C_LIO_LIHigher positivity rates are observed in school staff compared to pupils
C_LIO_LILack of evidence on transmission pathways transmission into and within schools
C_LI

What this study addsO_LIFirst UK national level study of transmission between pupils and staff in a school environment during the SARS-CoV-2 pandemic.
C_LIO_LISchools opening September-December 2020 was not associated with an increased subsequent risk of testing positive in staff
C_LIO_LIPupils were found to be at increased risk of testing positive, following cases appearing within their own year group
C_LI

C_TEXTBOX

category: health informatics


title: DrugWAS: Leveraging drug-wide association studies to facilitate drug repurposing for COVID-19

abstract:
ImportanceThere is an unprecedented need to rapidly identify safe and effective treatments for the novel coronavirus disease 2019 (COVID-19).

ObjectiveTo systematically investigate if any of the available drugs in Electronic Health Record (EHR), including prescription drugs and dietary supplements, can be repurposed as potential treatment for COVID-19.

Design, Setting, and ParticipantsBased on a retrospective cohort analysis of EHR data, drug-wide association studies (DrugWAS) were performed on COVID-19 patients at Vanderbilt University Medical Center (VUMC). For each drug study, multivariable logistic regression with overlap weighting using propensity score was applied to estimate the effect of drug exposure on COVID-19 disease outcomes.

ExposuresPatient exposure to a drug during 1-year prior to the pandemic and COVID-19 diagnosis was chosen as exposure of interest. Natural language processing was employed to extract drug information from clinical notes, in addition to the prescription drug data available in structured format.

Main Outcomes and MeasuresAll-cause of death was selected as primary outcome. Hospitalization, admission to the intensive care unit (ICU), and need for mechanical ventilation were identified as secondary outcomes.

ResultsThe study included 7,768 COVID-19 patients, of which 509 (6.55%) were hospitalized, 82 (1.06%) were admitted to ICU, 64 (0.82%) received mechanical ventilation, and 90 (1.16%) died. Overall, 15 drugs were significantly associated with decreased COVID-19 severity. Previous exposure to either Streptococcus pneumoniae vaccines (adjusted odds ratio [OR], 0.38; 95% CI, 0.14-0.98), diphtheria toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98), and tetanus toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98) were significantly associated with a decreased risk of death (primary outcome). Secondary analyses identified several other significant associations showing lower risk for COVID-19 outcomes: 2 vaccines (acellular pertussis, Streptococcus pneumoniae), 3 dietary supplements (turmeric extract, flaxseed extract, omega-3 fatty acids), methylprednisolone acetate, pseudoephedrine, ethinyl estradiol, estradiol, ibuprofen, and fluticasone.

Conclusions and RelevanceThis cohort study leveraged EHR data to identify a list of drugs that could be repurposed to improve COVID-19 outcomes. Further randomized clinical trials are needed to investigate the efficacy of the proposed drugs.

Key PointsO_ST_ABSQuestionC_ST_ABSCan Electronic Health Records (EHRs) be used to search for drug candidates that could be repurposed to treat the coronavirus disease 2019 (COVID-19)?

FindingsDrug-wide association studies (DrugWAS) of COVID-19 severity outcomes were conducted on a cohort of 7,768 COVID-19 patients. The study found 15 drug ingredients that are significantly associated with a decreased risk of death and other severe COVID-19 outcomes.

MeaningThe list of drugs proposed by this study could provide additional insights into developing new candidates for COVID-19 treatment.

category: infectious diseases


title: Using Machine Learning to Predict Mortality for COVID-19 Patients on Day Zero in the ICU

abstract:
RationaleGiven the expanding number of COVID-19 cases and the potential for upcoming waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.

ObjectivesEarly prediction of mortality using machine learning based on typical laboratory results and clinical data registered on the day of ICU admission.

MethodsWe studied retrospectively 263 COVID-19 ICU patients. To find parameters with the highest predictive values, Kolmogorov-Smirnov and Pearson chi-squared tests were used. Logistic regression and random forest (RF) algorithms were utilized to build classification models. The impact of each marker on the RF model predictions was studied by implementing the local interpretable model-agnostic explanation technique (LIME-SP).

ResultsAmong 66 documented parameters, 15 factors with the highest predictive values were identified as follows: gender, age, blood urea nitrogen (BUN), creatinine, international normalized ratio (INR), albumin, mean corpuscular volume, white blood cell count, segmented neutrophil count, lymphocyte count, red cell distribution width (RDW), and mean cell hemoglobin along with a history of neurological, cardiovascular, and respiratory disorders. Our RF model can predict patients outcomes with a sensitivity of 70% and a specificity of 75%.

ConclusionsThe most decisive variables in our model were increased levels of BUN, lowered albumin levels, increased creatinine, INR, and RDW along with gender and age. Complete blood count parameters were also crucial for some patients. Considering the importance of early triage decisions, this model can be a useful tool in COVID-19 ICU decision-making.


title: Symptoms of COVID-19 infection and magnitude of antibody response in a large community-based study

abstract:
BackgroundThe majority of COVID-19 cases are asymptomatic, or minimally symptomatic with management in the home. Little is known about the frequency of specific symptoms in the general population, and how symptoms predict the magnitude of antibody response to SARS-CoV-2 infection.

MethodsWe quantified IgG antibodies against the SARS-CoV-2 receptor binding domain (RBD) in home-collected dried blood spot samples from 3,365 adults participating in a community-based seroprevalence study in the city of Chicago, USA, collected between June 24 and November 11, 2020.

Results17.8% of the sample was seropositive for SARS-CoV-2. A cluster of symptoms (loss of sense of smell or taste, fever, shortness of breath, muscle or body aches, cough, fatigue, diarrhea, headache) was associated with stronger anti-RBD IgG responses among the seropositives. 39.2% of infections were asymptomatic, and 2 or fewer symptoms were reported for 66.7% of infections. Total number of symptoms was positively but weakly associated with IgG response: Median anti-RBD IgG was 0.95 ug/mL for individuals with 3 or more symptoms, in comparison with 0.61 ug/mL for asymptomatic infections.

ConclusionWe document high rates of asymptomatic and mild infection in a large community-based cohort, and relatively low levels of anti-SARS-CoV-2 IgG antibody in the general population of previously exposed individuals.


title: Longitudinal serology in SARS-CoV-2 infected individuals in India - a prospective cohort study

abstract:
Clinical and epidemiological characteristics of SARS-CoV-2 infection are now widely available, but there are few data on longitudinal serology in large cohorts, particularly from low-and middle-income countries. We established an ongoing prospective cohort of 3840 SARS-CoV-2 RT-PCR positive individuals in the Delhi-National Capital Region of India, to document clinical and immunological characteristics during illness and convalescence. The IgG responses to the receptor binding domain (RBD) and nucleocapsid were assessed at 0-7, 10-28 days and 6-10 weeks after infection. The clinical predictors of seroconversion were identified by multivariable regression analysis. The seroconversion rates in the post-infection windows of 0-7 days, 10-28 days and 6-10 weeks were 46%, 84.7% and 85.3% respectively (n=782). The proportion with a serological response increased with severity of COVID-19 disease. All participants with severe disease, 89.6% with mild to moderate infection and 77.3% of asymptomatic participants had IgG antibodies to the RBD antigen. The threshold values in the nasopharyngeal viral RNA RT-PCR in a subset of asymptomatic and symptomatic seroconverters were comparable (p value: 0.48), with similar results among non-seroconverters (p value: 0.16) (n=169). This is the first report of longitudinal humoral immune responses to SARS-CoV-2 infection over a period of ten weeks from South Asia. The low seropositivity in asymptomatic participants and differences between assays highlight the importance of contextualizing the understanding of population serosurveys.

SummaryWe measured anti-SARS-CoV-2 RBD and NC protein IgG in a multi-hospital-based prospective cohort from northern India up to ten weeks post-infection. The lower seroconversion rate among asymptomatic RT-PCR positive participants has public health significance particularly for interpreting community seroprevalence estimates.


title: Prediction Model for Severe Community-acquired Pneumonia Development among Patients with Diabetes Mellitus

abstract:
IntroductionDiabetes is an independent risk factor for the development of severe community-acquired pneumonia (CAP) and associated with pneumonia-related hospitalization as well as mortality. Here, we assessed several selected biomarkers to determine their predictive value for progression to severe CAP among diabetic patients.

Research design and methodsA retrospective cohort study of diabetic patients with CAP was conducted at a tertiary teaching hospital. The prediction model group (N=100) comprised patients registered between January 2015 to December 2016. Multivariate analysis was performed to identify predictive biomarkers from this cohort. The validation group (N=108) comprised the patients between January 2017 to February 2019. Predictive performance was assessed in the validation group.

ResultsA total of 208 diabetic inpatients with CAP were recruited. Further multivariate analysis showed that C-reactive protein (CRP), absolute lymphocyte count (ALC), immunoglobulin (IgM), and HbA1C at admission were independently associated with progression to severe CAP in diabetic patients during hospitalization. The prediction model =0.0179555*CRP+1.975918* HbA1C-2.879364* ALC -0.026255* IgM - 8.220555. The area under ROC (AUROC) curve in the validation group was 0.851 (0.781-0.921) with statistical significance (P<.05).

ConclusionsIn diabetic patients with CAP, a combination of CRP, ALC, IgM, and HbA1C at admission could be used to predict the progression to severe CAP.

O_TEXTBOXSignificance of this studyO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIDiabetes is an independent risk factor for the development of severe community-acquired pneumonia (CAP) and associated with pneumonia-related hospitalization as well as mortality.
C_LIO_LIIt is essential to identify these patients early and prevent them from progressing to SCAP to improve clinical outcomes.
C_LI

What are the new findings?O_LIC-reactive protein (CRP), absolute lymphocyte count (ALC), immunoglobulin (IgM), and HbA1C at admission were independently associated with progression to severe CAP in diabetic patients during hospitalization.
C_LIO_LIThe prediction model = 0.0179555*CRP+1.975918* HbA1C-2.879364* ALC -0.026255* IgM - 8.220555.
C_LIO_LIThe area under ROC (AUROC) curve in the validation group was 0.851 (0.781-0.921) with statistical significance (P<.05).
C_LI

How might these results change the focus of research or clinical practice?O_LIIn patients with diabetes and CAP, HbA1C, CRP, ALC, IgM at admission, and their combination could be used to predict the progression to severe CAP during hospitalization with good accuracy.
C_LIO_LIDue to the included biomarkers are common, our finding may be performed well in clinical practice and then improve the early management of diabetic patients with CAP.
C_LI

C_TEXTBOX

category: intensive care and critical care medicine


title: Introduction of a hand dermatitis clinic to reduce occupational dermatoses during the covid-19 pandemic.

abstract:
BackgroundThe SARS-Co-V pandemic has necessitated strict hand hygiene practices in healthcare settings. An increased incidence of staff presentations of occupational dermatitis in our institutions prompted the establishment of a drop-in access daily hand dermatitis clinic.

Objectiveto document the incidence and severity of cases of occupational dermatitis arising in healthcare workers during the first wave of the pandemic, and to reduce the impact of this with early assessment and treatment.

Methodsan open-access daily staff clinic run by dermatologists was established, and demographic and clinical data collected from each clinical encounter.

Results532 staff attended the clinic over a 6 week period. This compared to 7 staff presenting to occupational health over the same period in 2019. The majority were females 81%,and ward based 51%. ITU and A&E staff represented 15%. The prevalence of occupational hand dermatitis was 88%. 52% were classed as mild, 26% as moderate 26% and 9% severe/very severe.

Conclusionsthe pandemic and associated hand hygiene practices have led to a substantial increase in presentations of occupational hand dermatitis. A drop-in clinic proved an effective way of allowing staff to access treatment in a timely fashion.

category: dermatology


title: Assessment of Vaccination and Underreporting on COVID-19 Infections in Turkey Based On Effective Reproduction Number

abstract:
In this paper, we introduce a SEIR type COVID-19 model where the infected class is further divided into subclasses with individuals in intensive care (ICUs) and ventilation units. The model is validated with the symptomatic COVID-19 cases, deaths, and the number of patients in ICUs and ventilation units as reported by Republic of Turkey, Ministry of Health for the period March 11, 2020 through May 30, 2020 when the nationwide lockdown is in order. COVID-19 interventions in Turkey are incorporated into the model to detect the future trend of the outbreak accurately. We tested the effect of underreporting and we found that the peaks of the disease differ significantly depending on the rate of underreporting, however, the timing of the peaks remains constant.

The lockdown is lifted on June 1, and the model is modified to include a time dependent transmission rate which is linked to the effective reproduction number [R]t through basic reproduction number [R]0. The modified model captures the changing dynamics and peaks of the outbreak successfully. With the onset of vaccination on 13 January 2021, we augment the model with the vaccination class to investigate the impact of vaccination rate and efficacy. We observe that vaccination rate is a more critical parameter than the vaccine efficacy to eliminate the disease successfully.


title: Evolution and emergence of multidrug-resistant Mycobacterium tuberculosis in Chisinau, Moldova

abstract:
1.BackgroundDrug-resistant tuberculosis is a high priority threat to global public health. There are still critical gaps in understanding how novel drug-resistant M. tuberculosis strains emerge and, once emergent, what drives the differential propagation of certain epidemiologically-successful strains over others. This study sought to describe the joint evolutionary and epidemiological histories of a novel multidrug-resistant M. tuberculosis strain recently identified in the capital city of the Republic of Moldova (MDR Ural/4.2).

MethodsUsing whole genome sequence data and Bayesian phylogenomic methods, we reconstruct the stepwise acquisition of drug-resistance mutations in the MDR Ural/4.2 strain, estimate its historical bacterial population size over time, and infer the migration history of this strain between Eastern European countries.

ResultsWe infer that MDR Ural/4.2 likely evolved (via acquisition of rpoB S450L, which confers resistance to rifampin) in the early 1990s, during a period of social turmoil following Moldovan independence from the Soviet Union. This strain subsequently underwent substantial population size expansion in the early 2000s, at a time when national guidelines encouraged in hospital treatment of TB patients. We infer exportation of this strain and its INH-resistant ancestral precursor from Moldova to neighboring countries starting as early as 1985.

ConclusionsOur findings underscore how public health practice and social determinants of health shape the conditions under which M. tuberculosis evolves, and demonstrates how historical changes in these conditions shape present-day challenges in TB control. These findings underscore the need for regional coordination in TB control across Eastern Europe.


title: Continuity of Care by Primary Care Provider in Young Children with Chronic Conditions

abstract:
Objectives(1) To assess continuity of care by primary-care provider (CoC), an established quality indicator, in children with asthma, autism spectrum disorder (ASD), and no chronic conditions, and (2) to determine patient factors that influenced CoC.

MethodsRetrospective cohort study of electronic health records from all office visits of children under 9 years, seen [≥]4 times between 2015 and 2019 in 10 practices of a community-based primary healthcare network in California. Three cohorts were constructed: (1)Asthma: [≥]2 visits with asthma visit diagnoses; (2)ASD: same method; (3)Controls: no chronic conditions. CoC, using the Usual Provider of Care measure (range >0-1), was calculated for (1)total visits and (2)well-care visits only. Fractional regression models examined CoC adjusting for patient age, medical insurance, practice affiliation, and number of visits.

ResultsOf 30,678 eligible children, 1875 (6.1%) were classified as Asthma, 294 (1.0%) as ASD, and 15,465 (50.4%) as Controls. Asthma and ASD had lower total CoC than Controls (Mean=0.58, SD 0.21, M=0.57, SD 0.20, M=0.66, SD 0.21). Differences among well-care CoC were smaller (Asthma M=0.80, ASD M=0.78, Controls M=0.82). In regression models, lower total CoC was found for Asthma (aOR 0.90, 95% CI 0.85-0.94). Lower total and well-care CoC were associated with public insurance (aOR 0.77, CI 0.74-0.81; aOR 0.64, CI 0.59-0.69).

ConclusionChildren with asthma in this primary-care network had lower CoC compared to children without chronic conditions. Public insurance was the most prominent patient factor associated with low CoC. Quality initiatives should address disparities in CoC for children with chronic conditions.

Table of Contents SummaryContinuity of care by primary care provider is an established quality indicator. We compared continuity in young children with asthma, autism, and no chronic conditions.

Whats Known on This SubjectContinuity of care has emerged as an important component of care in the patient-centered medical home, especially for children with chronic medical conditions. However, it has been minimally studied across chronic conditions, especially in neurodevelopmental disorders.

What This Study AddsChildren with asthma, but not those with autism spectrum disorder, had lower continuity of care compared to children without chronic conditions. Public insurance was associated with lower care continuity for children with and without chronic conditions, highlighting important sociodemographic disparities.

Contributors Statement PageDr. Bannett conceptualized and designed the study, defined and coordinated data extraction, carried out the data analyses, drafted the manuscript, and reviewed and revised the manuscript.

Ms. Gardner participated in study design, extensively reformatted the data for analysis, performed statistical data analysis, and critically reviewed and revised the manuscript.

Dr. Feldman participated in study design, supervised data analysis and critically reviewed and revised the manuscript.

Drs. Huffman and Sanders supervised the conceptualization and design of the study, supervised data analysis, and critically reviewed and revised the manuscript.

All authors approved the final manuscript as submitted and are responsible for all aspects of the work.

category: pediatrics


title: Development of the NeuroFlow Severity Score and Comparison With Validated Measures for Depression and Anxiety

abstract:
PurposeAlthough depression and anxiety are the leading causes of disability in the United States, respectively, fewer than half of people diagnosed with these conditions receive appropriate treatment, and fewer than 10% receive measurement-based care (MBC), which is defined as behavioral health care based on and adapted in response to patient outcomes data collected throughout treatment. The NeuroFlow platform was developed with the goal of making MBC easier to deliver and more accessible within integrated behavioral health care. Data from over 3,000 users of the NeuroFlow platform were used to develop the NeuroFlow Severity Score (NFSS), a potential new measure for depression and anxiety. To begin evaluating the potential usefulness of this new measure, NFSSs were compared with validated measures for depression and anxiety, the Personal Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) scale, and clinician assessment.

MethodsThe NFSS platform is used to record patient-reported and passively collected data related to behavioral health. An artificial-intelligence derived algorithm was developed that condenses this large number of measurements into a single score for longitudinal tracking of an individuals depression and anxiety symptoms. Linear regression and Bland-Altman analyses were used to evaluate relationships and differences between NFSS and PHQ-9 or GAD-7 scores from over 35,000 NeuroFlow users. The NFSS was also compared to assessment by a panel of expert clinicians for a subset of 250 individuals.

ResultsLinear regression results showed a strong correlation between NFSS and PHQ-9 (r=.74, P<.001) and GAD-7 (r=.80, P<.001) changes. There was also a strong positive correlation between the NFSS and expert panel clinical assessment (r=.80-.84, P<.001). Bland-Altman analysis and evaluation of outliers on regression analysis, however, show that the NFSS has significant differences from the PHQ-9.

ConclusionsClinicians can reliably use the NFSS as a proxy measure for monitoring symptoms of depression and anxiety longitudinally. The NFSS may identify at-risk individuals who are not identified by the PHQ-9. Further research is warranted to evaluate the sensitivity and specificity of the NFSS.

category: psychiatry and clinical psychology


title: Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

abstract: Psychiatric disorders show heterogeneous clinical manifestations and disease trajectories, with current classification systems not accurately reflecting their molecular etiology. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify diagnostically mixed psychiatric patient clusters that share clinical and genetic features and may profit from similar therapeutic interventions. We used unsupervised high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N=1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, was characterized by general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. MDD patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N=622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction AUC=81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatment regimes.


title: COVID-19 prevention behaviour over time in Australia: Patterns and long-term predictors from April to July 2020

abstract:
BackgroundIn Australia in March 2020 a national public health directive required that non-essential workers stay at home, except for essential activities. These restrictions began easing in May 2020 as community transmission slowed.

PurposeThis study investigated changes in COVID-19 prevention behaviours from April-July 2020, and psychosocial predictors of these behaviours.

Methods1,843 participants in Australia completed a national COVID-19 survey in April, with monthly follow-up over four months. Principal components analysis (PCA) combined self-reported adherence across seven prevention behaviours. Multivariable regression models explored baseline (April) correlates of behaviour in June (a period of low community transmission) and July (a period of increasing community transmission).

ResultsOn average, participants agreed with statements of adherence for all behaviours (means all above 4 out of 7). PCA identified two behaviour types:  distancing (e.g. staying 1.5m away) and  hygiene (e.g. washing hands), explaining 28.3% and 24.2% of variance, respectively. Distancing declined each month (ps<.001), whereas hygiene remained relatively stable. For distancing, stronger perceptions of societal risk, self-efficacy to maintain distancing, and greater perceived social obligation at baseline were associated with adherence in June and July (ps<0.05). For hygiene, the only significant correlate of adherence in June and July was belief that ones actions could prevent infection of family members (p<.001).

ConclusionsHigh adherence to COVID-19 prevention behaviours were reported; however, distancing behaviours tended to decrease over time. Belief in social responsibility may be an important aspect to consider in encouraging distancing behaviours. Different policy approaches may be needed for different behavioural categories.

category: public and global health


title: Impact of school closures on the health and well-being of primary school children in Wales UK; a routine data linkage study using the HAPPEN survey (2018-2020).

abstract:
IntroductionIn response to the COVID-19 pandemic, school closures were implemented across the United Kingdom. This study aimed to explore the impact of school closures on childrens health by comparing health and wellbeing outcomes collected during school closures (April - June 2020) with data from the same period in 2019 and 2018.

MethodsData were collected online via the  HAPPEN At Home survey, which captured the typical health behaviours of children aged 8 - 11 years between April - June 2020. These data were compared with data in 2018 and 2019 also collected between April-June, from HAPPEN. Free school meal (FSM) status was used as a proxy for socio-economic deprivation. Analyses were repeated stratifying by FSM.

ResultsComparing responses between April - June in 2020 (n=1068), 2019 (n=1150) and 2018 (n=475), there were improvements in physical activity levels, sleep time, happiness and general wellbeing for children during school closures compared to previous years. However, children on FSM ate less fruit and vegetables (21% (95%CI (5.7% to 37%)) and had lower self-assessed school competence compared to 2019. Compared to those not on FSM they also spent less time doing physical activity (13.03% (95%CI: 3.3% to 21.7%) and consumed more takeaways (16.3% (95%CI: 2%-30%)) during school closures.

ConclusionThis study suggests that schools play an important role in reducing inequalities in physical health. The physical health (e.g. physical activity and diet) of children eligible for FSM may be impacted by prolonged school closures.

What is already known on this subject?In response to the COVID-19 pandemic, by mid-March 2020, 138 countries had implemented national school closures to reduce the number of social contacts between pupils, therefore interrupting the transmission of COVID-19 as part of pandemic plans. UNESCO warned that the global scale and speed of the educational disruption would be unparalleled. There is an ongoing debate with regard to the effectiveness of schools closures on transmission rates, but the fact schools are closed for a long period of time could have detrimental impacts on pupils physical and mental health.

This study provides evidence of any differences in the health and wellbeing of children prior to and during the COVID-19 enforced lockdown and school closures between March and June 2020. These findings could have a significant impact for the future and support schools to better understand their pupils physical, psychological, emotional and social health. It also contributes to a significant literature gap regarding the impact of school closures on school-aged children.

What this study adds?Improvements in physical activity levels, sleep time, happiness and general wellbeing were observed in general for children during school closures compared to previous years. However, children on FSM reported eating less fruit and vegetables and had lower self-assessed school competence compared to 2019. Compared to those not on FSM they also spent less time doing physical activity and consumed more takeaways during school closures. These trends are not evident among children not on FSM. All children reported improvements in wellbeing during lockdown especially on the happiness with family measure.

Overall, findings suggest schools help to reduce inequalities in physical health for socio-economically deprived children. During school closures children from deprived backgrounds are likely to have poorer physical health (e.g. less time spent doing physical activities and poorer diet) and this is not observed in children who are not in receipt of FSM. This research suggests that school closures will result in widening health inequalities and when schools return measures will need to be in place to readdress the widened gap in physical health.


title: Enhancing Food Security for Families Vulnerable to COVID-19

abstract: The COVID-19 pandemic has exposed some of the underlying inequities in our society. Vulnerable and low-income communities who have typically struggled with food insecurity have been further impacted by the COVID-19 pandemic. To make matters worse, transit dependent households in the City of Detroit that rely on SNAP benefits from the government have a 54% probability of not having internet access, reducing the possibility of online food delivery. Thus, the motivation for the Detroit Food Delivery Pilot Program, a prepared meal delivery service for food insecure households during the COVID-19 pandemic. Through this program, the City had aided 350 households; over 1,000 unique individuals and has served over 90,000 meals. This had all been made possible through the engagement of 575 volunteers, volunteering over 6,850 delivery miles. Our team helped to identify the magnitude and the needs of the Citys food insecure population; then partnered with the City of Detroit to modify existing food programs to address the crisis, and finally, assessed the impact of the program on the target population. Our analysis revealed that approximately 20,800 households will be classified as food insecure in Detroit and only a fraction of this population is benefitting from the food delivery pilot program. However, on average, the concerns about food sufficiency have abated appreciably from the surveys analyzed. Responses from the beneficiaries of the food delivery pilot program were positive though concerns about the travel behavior of individuals, particularly those from COVID-19 positive households remain.


title: SOUTH AMERICAN INDIGENOUS COMMUNITIES AND BODY MASS INDEX: A SYSTEMATIC REVIEW AND META-ANALYSIS

abstract: Obesity is an increasing new pandemic. Currently more than 1.9 billion adults are overweight and at least 700 million of them are obese. Obesity is the result of a positive energy balance, which is conditioned by both environmental and genetic factors. Interestingly, individuals from similar ethnic-based ancestry communities, share both environmental and genetic features. Here, we described the relationship between indigenous Chilean groups and body mass Index. We conducted a Systematic review and Meta-analysis on Pubmed, LILACS, Scielo, Web of Science and Scopus databases. Our results showed that Indigenous Children present a lower BMI than Non-Indigenous Children. However, no difference within BMI was identified in adults. The gender affected the BMI as well. Aymara and Mapuche Women presented higher BMI than Indigenous Men. In the other hand, Indigenous people living in rural environment showed lower BMI than those whose live-in urban areas. Finally, Indigenous communities presented no difference in the risk to suffer Obesity when compared with Non-Indigenous communities. Here suggest that ethnicity could be a health determinant as well as a risk factor for obesity. Then, targeted prevention strategies with ethnic-based focus would be developed.


title: Remote-Management of COPD: Evaluating Implementation of Digital Innovation to Enable Routine Care (RECEIVER) - protocol for a feasibility and service adoption observational cohort study

abstract:
IntroductionReduction in exacerbations and hospitalisations are the outcomes rated as most important by COPD patients. Patient self-management and evidence-based healthcare interventions that reduce exacerbations and hospital admissions do exist but there are considerable barriers to their uptake and delivery. Patient and clinician engagement is often not consistent. Data which could potentially predict exacerbations and treatment success are not acquired systematically and is not reliably visible or actionable at key time points of patient-clinician interaction. Most COPD management is currently based on a reactive approach, and delays in recognising treatable opportunities underpin COPD care-quality gaps. Innovations which can empower patient self-management, facilitate integrated clinical care and support delivery of evidence-based treatment interventions are urgently required.

We have developed a digital service model for COPD patients, designed to integrate current routine clinical care within a digitally enabled remote-monitoring service infrastructure. This digital platform will capture relevant routinely acquired patient-reported outcomes, continuous physiology data and clinical event/episode data in a patient and clinician co-designed interface.

Methods and analysisThe remote management of COPD: evaluating implementation of digital innovations to enable routine care (RECEIVER) trial is a prospective observational cohort hybrid implementation and effectiveness study that will test the adoption of this digital service model for  high-risk COPD patients and evaluate the performance of this approach versus current standards of care. Patients with a recent severe exacerbation and/or COPD-OSA overlap or chronic hypercapnic respiratory failure requiring home NIV or CPAP, with access to smartphone, tablet or computer will be recruited into the study and enrolled into the digital service.

In our endpoints will determine patient engagement, clinical service impact and clinical outcomes that will be compared with historical and contemporary COPD control patient data, acquired from NHS GG&C SafeHaven. The digital innovations will be iterated throughout the study to optimize them, based on the user experience accrued. The digital infrastructure for this support of routine clinical care will also provide a foundation to explore the feasibility of approaches to predict outcomes and exacerbations in COPD patients, for testing in future prospective clinical and regulatory trials through machine-learning analysis.

Ethics and disseminationEthical approval for this clinical trial has been obtained from the West of Scotland Research Ethics Service (WoSRES). The trial will commence in September 2019 for a duration of 2 years. Key results will be presented at local, national and international meetings, including those with patient representation. All data obtained will be submitted for publication to peer reviewed journals.

Trial registration numberNCT04240353

category: respiratory medicine


title: A mechanistic and data-driven reconstruction of the time-varying reproduction number: Application to the COVID-19 epidemic

abstract:
The effective reproduction number Reff is a critical epidemiological parameter that characterizes the transmissibility of a pathogen. However, this parameter is difficult to estimate in the presence of silent transmission and/or significant temporal variation in case reporting. This variation can occur due to the lack of timely or appropriate testing, public health interventions and/or changes in human behavior during an epidemic. This is exactly the situation we are confronted with during this COVID-19 pandemic.

In this work, we propose to estimate Reff for the SARS-CoV-2 (the etiological agent of the COVID-19), based on a model of its propagation considering a time-varying transmission rate. This rate is modeled by a Brownian diffusion process embedded in a stochastic model. The model is then fitted by Bayesian inference (particle Markov Chain Monte Carlo method) using multiple well-documented hospital datasets from several regions in France and in Ireland. This mechanistic modeling framework enables us to reconstruct the temporal evolution of the transmission rate of the COVID-19 based only on the available data. Except for the specific model structure, it is non-specifically assumed that the transmission rate follows a basic stochastic process constrained by the observations. This approach allows us to follow both the course of the COVID-19 epidemic and the temporal evolution of its Reff(t). Besides, it allows to assess and to interpret the evolution of transmission with respect to the mitigation strategies implemented to control the epidemic waves in France and in Ireland. We thus can estimate a reduction of more than 80% for the first wave in all the studied regions but a smaller reduction for the second wave when the epidemic was less active. For the third wave in Ireland the reduction was again significant (>70%).

Author SummaryIn the early stages of any new epidemic, one of the first steps to design a control strategy is to estimate pathogen transmissibility in order to provide information on its potential to spread in the population. Among the different epidemiological indicators that characterize the transmissibility of a pathogen, the effective reproduction number Reff is commonly used for measuring time-varying transmissibility. It measures how many additional people can be infected by an infected individual during the course of an epidemic. However, Reff is difficult to estimate in the presence of silent transmission and/or significant temporal variation in case reporting. This is exactly the situation we are confronted with during this COVID-19 pandemic.

The statistical methods classically used for the estimation of Reff have some shortcomings in the rigorous consideration of the transmission characteristics of SARS-CoV-2. We propose here to use an original approach based on a stochastic model whose parameters vary in time and are inferred in a Bayesian framework from reliable hospital data. This enables us to reconstruct both the COVID-19 epidemic and its Reff. The Reff time evolution allows us to get information regarding the potential effects of mitigation measures taken during and between epidemics waves.

This approach, based on a stochastic model that realistically describes the hospital multiple datasets and which overcomes many of the biases associated with Reff estimates, appears to have some advantage over previously developed methods.


title: Mapping internet activity in Australian cities during COVID-19 lockdown: how occupational factors drive inequality

abstract: During the COVID-19 pandemic, evidence has accumulated that movement restrictions enacted to combat virus spread produce disparate consequences along socioeconomic lines. We investigate the hypothesis that people engaged in financially secure employment are better able to adhere to mobility restrictions, due to occupational factors that link the capacity for flexible work arrangements to income security. We use high-resolution spatial data on household internet traffic as a surrogate for adaptation to home-based work, together with the geographical clustering of occupation types, to investigate the relationship between occupational factors and increased internet traffic during work hours under lockdown in two Australian cities. By testing our hypothesis based on the observed trends, and exploring demographic factors associated with divergences from our hypothesis, we are left with a picture of unequal impact dominated by two major influences: the types of occupations in which people are engaged, and the composition of households and families. During lockdown, increased internet traffic was correlated with income security and, when school activity was conducted remotely, to the proportion of families with children. Our findings suggest that response planning and provision of social and economic support for residents within lockdown areas should explicitly account for income security and household structure. Overall, the results we present contribute to the emerging picture of the impacts of COVID-19 on human behaviour, and will help policy makers to understand the balance between public health and social impact in making decisions about mitigation policies.


title: Uncorrected cardiac malformation is the major risk factor for death in patients with dextrocardia

abstract:
Background/ObjectivesDextrocardia is rare in the general population. We aimed to analyze the clinical characteristics and risk factors for survival rate of dextrocardia patients during 2013 to 2018 in our hospital, through a specialized Hospital Information System.

MethodsA retrospective study of patients with dextrocardia was performed through Hospital Information System. International Classification of Diseases 10 was searched to identify eligible cases from January 2013 to December 2018 in our hospital. Medical records were reviewed to acquire the basic information of dextrocardia patients.

ResultsAmong 9304 patients diagnosed with congenital heart disease in past six years, 48 (0.51%) had dextrocardia. Among 48 dextrocardia patients, 28 (58.33%) had situs inversus viscerum, 20 (41.67%) had cardiac malformation, nine (18.75%) had other malformations and 16 (33.33%) had no malformation. Compared with patients with uncorrected cardiac malformation, patients without cardiac malformation were older (43.5000 vs 0.4583 years, P<0.001). The dextrocardia patients age of onset correlated significantly with cardiac malformation. Multivariable logistic model showed the significant risk factor for survival rate was uncorrected cardiac malformation (odds ratio, 22.2391; P <0.001). However, situs inversus (odds ratio, 1.9750; P= 0.4399) or pneumonia (odds ratio, 4.2610; P= 0.0849) itself was not a significant risk factor for survival rate. Kaplan-Meier plot shown that dextrocardia patients with uncorrected cardiac malformation had lower survival rate than those without cardiac malformation (P<0.0001), and there is no significant difference between healthy cohort and patients with pure dextrocardia with or without situs inversus (P=0.25).

ConclusionsDextrocardia remains a rare finding in population, even in the group of patients with known congenital heart disease. Dextrocardia was associated with various malformations besides cardiac malformation. Uncorrected cardiac malformation, which should be paid high attention in the developing countries, is the main risk factor for death in patients with dextrocardia, and pure dextrocardia with or without situs inversus has no effect on survival rate of dextrocardia patients.

category: cardiovascular medicine


title: Ventilation rate assessment by carbon dioxide levels in dental treatment rooms

abstract:
ObjectivesThe purpose of the present study was to monitor and evaluate CO2 levels in dental operatories using a consumer-grade CO2 sensor and determine the utility and accuracy of various methods using CO2 levels to assess ventilation rate in dental clinics. We aim to find a practical tool for dental practitioners to conveniently and accurately monitor CO2 levels and assess the ventilation rates in their office in order to devise a pragmatic and effective strategy for ventilation improvement in their work environment.

MethodsMechanical ventilation rate in air change per hour (ACHVENT) of 10 dental operatories was first measured with an air velocity sensor and air flow balancing hood. CO2 levels were measured in these rooms to analyze the effects of ventilation rate and number of persons in the room on CO2 accumulation. Ventilation rates were estimated using natural steady state CO2 levels during dental treatments and experimental CO2 concentration decays by dry ice or mixing baking soda and vinegar. We compared the differences and assessed the correlations between ACHVENT and ventilation rates estimated by steady states CO2 model with low (0.3 L/min, ACHSS30) or high (0.46 L/min, ACHSS46) CO2 generation rates, by CO2 decay constants using dry ice (ACHDI) or baking soda (ACHBV), and by time needed to remove 63% of excess CO2 generated by dry ice (ACHDI63%) or baking soda (ACHBV63%).

ResultsACHVENT varied from 3.9 to 35.0 with a mean of 13.2 ({+/-}10.6) in the 10 dental operatories. CO2 accumulation occurred in rooms with low ventilation (ACHVENT[≤]6) and more persons (n>3) but not in those with higher ventilation and less persons. ACHSS30 and ACHSS46 correlated well with ACHVENT (r=0.83, p=0.003), but ACHSS30 was more accurate for rooms with low ACHVENT. Ventilation rates could be reliably estimated using CO2 released from dry ice or baking soda. ACHVENT was highly correlated with ACHDI (r=0.99), ACHBV(r=0.98), ACHDI63%(r=0.98), and ACHBV63% (r=0.98). There were no statistically significant differences between ACHVENT and ACHDI63% or ACHBV63%.

ConclusionsDental operatories with low ventilation rates and overcrowding facilitate CO2 accumulations. Ventilation rates could be reliably calculated by observing the changes in CO2 levels after a simple mixing of household baking soda and vinegar in dental settings. Time needed to remove 63% of excess CO2 generated by baking soda could be used to accurately assess the ventilation rates using a consumer-grade CO2 sensor and a basic calculator.

category: dentistry and oral medicine


title: Distinct microRNA expression signatures of primary and secondary central nervous system lymphomas

abstract: Central nervous system (CNS) lymphoma is a rare and aggressive non-Hodgkin lymphoma that might arise in the CNS (primary CNS lymphoma, PCNSL) or disseminates from a systemic lymphoma to the CNS (secondary CNS lymphoma, SCNSL). Dysregulated expression of microRNAs (miRNAs) is associated with various pathological processes and miRNA expression patterns may have diagnostic, prognostic and therapeutic implications. However, miRNA expression is understudied in CNS lymphomas. Here, we performed expression analysis of 798 miRNAs in 73 CNS lymphoma samples using the NanoString platform, followed by a detailed statistical analysis to identify potential novel biomarkers characterizing subgroups and to examine differences based on their primary and secondary nature, molecular subtype, mutational patterns and survival. We describe the general expression patterns of miRNAs across CNS lymphoma samples and identified 31 differentially expressed miRNAs between primary and secondary groups. Additionally, we identified 7 more miRNAs associated with a molecular subtype and 25 associated with mutation status. Using unsupervised clustering methods, we defined a small but distinct primary CNS lymphoma subgroup, with characteristically different expression patterns compared to the rest of the cases. Finally, we identified differentially regulated pathways in the above comparisons and assessed the utility of miRNA expression patterns in predicting survival. Our study identifies a novel CNS lymphoma subgroup defined by distinct miRNAs, proves the importance of specific miRNAs and pathways in their pathogenesis, and provides the basis for future research.

category: pathology


title: Development and validation of an algorithm to estimate the risk of severe complications of COVID-19 to prioritise vaccination

abstract:
ObjectiveTo develop an algorithm (sCOVID) to predict the risk of severe complications of COVID- 19 in a community-dwelling population to optimise vaccination scenarios.

DesignPopulation based cohort study

Setting264 Dutch general practices contributing to the NL-COVID database

Participants6074 people aged 0-99 diagnosed with COVID-19

Main outcome measuresSevere complications (hospitalisation, institutionalisation, death). The algorithm was developed from a training dataset comprising 70% of the patients and validated in the remaining 30%. Potential predictor variables included age, sex, a chronic co-morbidity score (CCS) based on risk factors for COVID-19 complications as defined by the National Institute of Public Health and the Environment (RIVM), obesity, neighborhood deprivation score (NDS), first or second COVID wave, and confirmation test. Six different population vaccination scenarios were explored: 1) random (naive), 2) random for persons above 60 years (60plus), 3) oldest patients first in age bands of five years (oldest first), 4) target population of the annual influenza vaccination program (influenza) and 5) those 25-65 years of age first (worker), and 6) risk-based using the prediction algorithm (sCOVID). For each vaccination strategy the amount of vaccinations needed to reach a 50% reduction of severe complications was calculated.

ResultsSevere complications were reported in 243 (4.8%) people with 59 (20.3%) nursing home admissions, 181 (62.2%) hospitalisations and 51 (17.5%) deaths. The algorithm included age, sex, CCS, NDS, wave, and confirmation test with a c statistic of 0.91 (95% CI 0.88-0.94) in the validation set. Applied to different vaccination scenarios, the proportion of people needed to be vaccinated to reach a 50% reduction of severe complications was 67.5%, 50.0%, 26.1%, 16.0%, 10.0%, and 8.4% for the worker, naive, infuenza, 60plus, oldest first, and sCOVID scenarios respectively.

ConclusionCOVID-19 related severe complications will be reduced most efficiently when vaccinations are risk-based, prioritizing the highest risk group using the sCOVID algorithm. The vaccination scenario, prioritising oldest people in age bands of 5 years down to 60 years of age, performed second best. The sCOVID algorithm can readily be applied to identify persons with highest risks from data in the electronic health records of GPs.

What is already known on this topic?O_LISevere COVID-19 complications may be reduced when persons at the highest risk will be vaccinated first.
C_LIO_LITo identify persons at a high risk for hospitalization or death in the general population, a limited number of prediction algorithms have been developed.
C_LIO_LIMost of these algorithms were based on data from the first wave of infections (spring 2020) when widespread testing was not always possible, limiting the usefulness of these algorithms.
C_LI

What this study addsO_LIIncluding data up to January 2021, we developed and validated a prediction algorithm (sCOVID) with a c-statistic of 0.91 (95% CI 0.88-0.94) based on age, sex, chronic comorbidity score, economic status, wave, and a confirmation test to identify patients in the general population that are at risk of severe COVID-19 complication.
C_LIO_LIUsing the algorithm, a 50% reduction of patients with severe complications could be obtained with a vaccination coverage of only 8%. This vaccination scenario based on this algorithm was superior to other calculated vaccination scenarios.
C_LIO_LIThe sCOVID algorithm can readily be implemented in the electronic health records of general practitioners.
C_LI


title: Short-term functional outcome in psychotic patients. Results of the Turku Early Psychosis Study (TEPS).

abstract:
BackgroundFunctional recovery of patients with clinical and sub-clinical psychosis is associated with clinical, neuropsychological and developmental factors. Less is known how these factors predict functional outcome in same models.

AimWe investigated functional outcome and its predictors in patients with first-episode psychosis (FEP) or confirmed vs. non-confirmed clinical high risk to psychosis (CHR-P vs. CHR-N).

MethodsAltogether, 130 FEP, 60 CHR-P and 47 CHR-N patients were recruited and extensively examined at baseline (T0) and at 9 (T1) and 18 (T2) months after baseline. Global Assessment of Functioning (GAF) at T0, T1 and T2, and psychotic, depression and anxiety symptoms at T1 and T2 were assessed. Functional outcome was predicted in multivariate repeated ANOVA.

ResultsDuring follow-up, GAF improved significantly in FEP and CHR-P but not in CHR-N patients. In FEP, single marital status, low basic education, poor work situation, disorganised symptoms, perceptual deficits and poor premorbid adjustment, in CHR-P, disorganised symptoms and poor premorbid adjustment and in CHR-N, low basic education, poor work situation and general symptoms predicted poor functional outcome. In FEP, psychotic symptoms at T1 and in CHR-P, psychotic and depression symptoms at T1 and anxiety symptoms at T2 associated with poor functioning.

DiscussionIn FEP and CHR-P patients, poor premorbid adjustment and disorganised symptomatology are common predictors for functional outcome, while poor education and work situation predict poor functional outcome in FEP and CHR-N patients. Interventions aimed to improve studying and ability to work are most important in improving functioning of patients with clinical or subclinical psychosis.


title: Endometrial microbiota composition is associated with reproductive outcome in infertile patients.

abstract:
BackgroundPrevious evidence indicates associations between the female reproductive tract microbiome composition and reproductive outcome in infertile patients undergoing assisted reproduction. We aimed to determine whether the endometrial microbiota composition is associated with reproductive outcomes of live birth, biochemical pregnancy, clinical miscarriage, or no pregnancy.

MethodsHere we present a multicentre prospective observational study using 16S rRNA gene sequencing to analyse endometrial fluid and biopsy samples before embryo transfer in a cohort of 342 infertile patients asymptomatic for infection undergoing assisted reproductive treatments.

ResultsA dysbiotic endometrial microbiota profile composed of Atopobium, Bifidobacterium, Chryseobacterium, Gardnerella, Haemophilus, Klebsiella, Neisseria, Staphylococcus and Streptococcus was associated with unsuccessful outcomes. In contrast, Lactobacillus was consistently enriched in patients with live birth outcomes.

ConclusionsOur findings indicate that endometrial microbiota composition before embryo transfer is a useful biomarker to predict reproductive outcome, offering an opportunity to further improve diagnosis and treatment strategies.

category: obstetrics and gynecology


title: Maximum likelihood perimetric progression analysis: Using raw (trial-by-trial) response data to estimate progression more robustly

abstract:
PurposeTo describe and demonstrate a more efficient (Maximum Likelihood) method for quantifying visual field progression.

DesignMonte Carlo simulation.

MethodsTrial-by-trial response data were simulated using a stochastic psychometric model (a "simulated observer"). Simulated Differential Light Sensitivity (DLS) decreased between tests to mimic long-term visual field progression. Progression slopes were fitted, either by fitting a regression slope to independent DLS estimates from each test (conventional method), or by fitting all the raw data combined in a single model (proposed maximum likelihood method).

ResultsThe proposed ML method seldom performed worse than a conventional, regression-based approach, and often performed better. For an idealized observer with a lapse (false negative) rate of 0 and a guess (false positive) rate of 0, both methods were equally precise. However, as lapse rate increased, the ML method exhibited less random measurement error. For small numbers of trials this increase in precision translated to a negative progression slope being detected with 95% confidence at least one year/assessment sooner. The only time the ML method was observed to perform worse was when very few trials (N = 4) were combined with very high lapse rates ({lambda} = 0.3): an unlikely but not inconceivable scenario.

ConclusionsCombining raw, trial-by-trial response data in a single ML model can provide a more robust estimate of visual field progression than conventional methods (e.g., linear regression), at no additional cost to the patient or clinician (i.e., no additional trials).

category: ophthalmology


title: High-resolution portability of 240 polygenic scores when derived and applied in the same cohort

abstract: The low portability of polygenic scores (PGS) across global populations is a major concern that must be addressed before PGS can be used for everyone in the clinic. Indeed, prediction accuracy has been shown to decay as a function of the genetic distance between the training and test cohorts. However, such cohorts differ not only in their genetic distance but also in their geographical distance and their data collection and assaying, conflating multiple factors. In this study, we examine the extent to which PGS are transferable between ancestries by deriving polygenic scores for 245 curated traits from the UK Biobank data and applying them in nine ancestry groups from the same cohort. By restricting both training and testing to the UK Biobank data, we reduce the risk of environmental and genotyping confounding from using different cohorts. We define the nine ancestry groups at a high-resolution, country-specific level, based on a simple, robust and effective method that we introduce here. We then apply two different predictive methods to derive polygenic scores for all 245 phenotypes, and show a systematic and dramatic reduction in portability of PGS trained in the inferred ancestral UK population and applied to the inferred ancestral Polish - Italian - Iranian - Indian - Chinese - Caribbean - Nigerian - Ashkenazi populations, respectively. These analyses, performed at a finer scale than the usual continental scale, demonstrate that prediction already drops off within European ancestries and reduces globally in proportion to PC distance, even when all individuals reside in the same country and are genotyped and phenotyped as part of the same cohort. Our study provides high-resolution and robust insights into the PGS portability problem.


title: High-resolution portability of 245 polygenic scores when derived and applied in the same cohort


title: Neighborhood Disadvantage and Active, Disabled and Total Life Expectancy Among Community-living Older Persons

abstract:
BackgroundNeighborhood disadvantage is a novel social determinant of health that could adversely affect the functional well-being and longevity of older persons. We evaluated whether estimates of active, disabled and total life expectancy differ on the basis of neighborhood disadvantage after accounting for individual-level socioeconomic characteristics and other prognostic factors.

MethodsWe used data on 754 community-living older persons from South Central Connecticut, who completed monthly assessments of disability from 1998 to 2020. Scores on the area deprivation index were dichotomized at the 80th state percentile to distinguish neighborhoods that were disadvantaged (81-100) from those that were not (1-80).

ResultsWithin 5-year age increments from 70 to 90, active and total life expectancy were consistently lower in participants from neighborhoods that were disadvantaged versus not disadvantaged, and these differences persisted and remained statistically significant after adjustment for individual-level race/ethnicity, education, income, and other prognostic factors. At age 70, adjusted estimates (95% CI) for active and total life expectancy (in years) were 12.3 (11.5-13.1) and 15.0 (13.8-16.1) in the disadvantaged group and 14.2 (13.5-14.7) and 16.7 (15.9-17.5) in the non-disadvantaged group. At each age, participants from disadvantaged neighborhoods spent a greater percentage of their projected remaining life disabled, relative to those from non-disadvantaged neighborhoods, with adjusted values (SE) ranging from 17.7 (0.8) vs. 15.3 (0.5) at age 70 to 55.0 (1.7) vs. 48.1 (1.3) at age 90.

ConclusionsLiving in a disadvantaged neighborhood is associated with lower active and total life expectancy and a greater percentage of projected remaining life disabled.

category: geriatric medicine


title: Longitudinal Metabolomics of Human Plasma Reveals Robust Prognostic Markers of COVID-19 Disease Severity

abstract: There is an urgent need to identify which COVID-19 patients will develop life-threatening illness so that scarce medical resources can be optimally allocated and rapid treatment can be administered early in the disease course, when clinical management is most effective. To aid in the prognostic classification of disease severity, we performed untargeted metabolomics profiling of 341 patients with plasma samples collected at six longitudinal time points. Using the temporal metabolic profiles and machine learning, we then built a predictive model of disease severity. We determined that the levels of 25 metabolites measured at the time of hospital admission successfully predict future disease severity. Through analysis of longitudinal samples, we confirmed that these prognostic markers are directly related to disease progression and that their levels are restored to baseline upon disease recovery. Finally, we validated that these metabolites are also altered in a hamster model of COVID-19. Our results indicate that metabolic changes associated with COVID-19 severity can be effectively used to stratify patients and inform resource allocation during the pandemic.


title: Loss of Factor H family proteins associates with meningococcal disease severity

abstract: Neisseria meningitidis, the causative agent of meningococcal disease (MD), evades complement-mediated clearance upon infection by  hijacking the human complement regulator factor H (FH). The FH protein family also comprises the homologous FH-related (FHR) proteins, hypothesized to act as antagonists of FH, and FHR-3 has recently been implicated to play a major role in MD susceptibility. Here, we show that, next to FH and FHR-3, the circulating levels of all FH family proteins are equally decreased during pediatric MD. We did not observe a specific consumption of FH or FHR-3 by N. meningitidis during the first days of infection and the levels recovered over time. MD severity associated predominantly with a loss of FH. Strikingly, loss of FH and FHRs associated strongly with renal failure, suggesting insufficient protection of host tissue by the FH protein family. Retaining higher levels of FH family proteins may thus limit tissue injury during MD.


title: The kinetic variations of anti-nucleocapsid antibody in SARS-CoV-2 infection

abstract:
The humoral immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays a pivotal role in controlling coronavirus disease 2019 (COVID-19) infections. However, little is known about the persistence of the antibody response.

We evaluated that the kinetics of anti-nucleocapsid protein antibody of SARS-CoV2 infected healthcare workers in COVID-19 cluster occurred hospital. The long-term kinetics of anti-N antibody was classified high and keep pattern, high and decay pattern, and low and keep pattern. COVID-19 contact and symptomaticity was not related to kinetic patterns.

The reason of kinetic difference was still unclear. However natural anti-SARS-CoV-2 antibody persistence was not uniform, suggesting inter-individual difference of SARS-CoV2 vaccine efficacy.