ISARIC COVID-19 Clinical Data Report: 8 April 2021 ISARIC (International Severe Acute Respiratory and emerging Infections Consortium) partnerships and outbreak preparedness initiatives enabled the rapid launch of standardised clinical data collection on COVID-19 in Jan 2020. Extensive global participation has resulted in a large, standardised collection of comprehensive clinical data from hundreds of sites across dozens of countries. Data are analysed regularly and reported publicly to inform patient care and public health response. This report, our 17th report, is a part of a series published over the past 2 years. Data have been entered for 800,459 individuals from 1701 partner institutions and networks across 60 countries.

The comprehensive analyses detailed in this report includes hospitalised individuals of all ages for whom data collection occurred between 30 January 2020 and up to and including 5 January 2022, AND who have laboratory-confirmed SARS-COV-2 infection or clinically diagnosed COVID-19.

For the 699,014 cases who meet eligibility criteria for this report, selected findings include: O_LImedian age of 58 years, with an approximately equal (50/50) male:female sex distribution
C_LIO_LI29% of the cohort are at least 70 years of age, whereas 4% are 0-19 years of age
C_LIO_LIthe most common symptom combination in this hospitalised cohort is shortness of breath, cough, and history of fever, which has remained constant over time
C_LIO_LIthe five most common symptoms at admission were shortness of breath, cough, history of fever, fatigue/malaise, and altered consciousness/confusion, which is unchanged from the previous reports
C_LIO_LIage-associated differences in symptoms are evident, including the frequency of altered consciousness increasing with age, and fever, respiratory and constitutional symptoms being present mostly in those 40 years and above
C_LIO_LI16% of patients with relevant data available were admitted at some point during their illness into an intensive care unit (ICU), which is slightly lower than previously reported (19%)
C_LIO_LIantibiotic agents were used in 35% of patients for whom relevant data are available (669,630), a significant reduction from our previous reports (80%) which reflects a shifting proportion of data contributed by different institutions; in ICU/HDU admitted patients with data available (50,560), 91% received antibiotics
C_LIO_LIuse of corticosteroids was reported in 24% of all patients for whom data were available (677,012); in ICU/HDU admitted patients with data available (50,646), 69% received corticosteroids
C_LIO_LIoutcomes are known for 632,518 patients and the overall estimated case fatality ratio (CFR) is 23.9% (95%CI 23.8-24.1), rising to 37.1% (95%CI 36.8-37.4) for patients who were admitted to ICU/HDU, demonstrating worse outcomes in those with the most severe disease
C_LI To access previous versions of ISARIC COVID-19 Clinical Data Report please use the link below: https://isaric.org/research/covid-19-clinical-research-resources/evidence-reports/
MAGNITUDE AND DURABILITY OF THE EFFECT OF VACCINATION ON THE CASE FATALITY RATE FOR COVID-19 ObjectiveTo evaluate the benefits of vaccination on the case fatality rate (CFR) for COVID-19 infections.

DesignMultivariate modeling of data from electronic medical records

Setting130 medical centers of the United States Department of Veterans Affairs

Participants339,772 patients with COVID-19 confirmed by nucleic acid amplification testing as of September 30, 2021

MethodsThe primary outcome was death within 60 days of the diagnosis. Patients were considered vaccinated if they had completed a full series >= 14 days prior to diagnosis. Cases presenting in July - September of 2021 were considered to have the delta variant. Logistic regression was used to derive adjusted odds ratios (OR) for vaccination and infection with delta versus earlier variants. Models were adjusted for demographic traits, standard comorbidity indices, selected clinical terms, and 3 novel parameters representing all prior diagnoses, all prior vital signs/ baseline laboratory tests, and current outpatient treatment. Patients with a delta infection were divided into 8 cohorts based upon the time from vaccination to diagnosis (in 4-week blocks). A common model was used to estimate the odds of death associated with vaccination for each cohort relative that of all unvaccinated patients.

Results9.1% of subjects had been fully vaccinated, and 21.5% were presumed to have the delta variant. 18,120 patients (5.33%) died within 60 days of their diagnoses. The adjusted OR for delta infection was 1.87 +/- 0.05 which corresponds to a relative risk of 1.78. The overall adjusted OR for prior vaccination was 0.280 +/- 0.011 corresponding to a relative risk of 0.291. The study of vaccine cohorts with a delta infection showed that the raw CFR rose steadily after 10-14 weeks. However, the OR for vaccination remained stable for 10-34 weeks.

ConclusionsOur study confirms that delta is substantially more lethal than earlier variants and that vaccination is an effective means of preventing COVID death. After adjusting for major selection biases, we found no evidence that the benefits of vaccination on CFR declined over 34 weeks.
A general computational framework for COVID-19 modelling with applications to testing varied interventions in education environments We construct a spatially-compartmental individual-based model of the spread of Covid-19 in indoor spaces. The model can be used to predict the infection rates in a variety of locations when various non-pharmaceutical interventions (NPIs) are introduced. Tasked by the Welsh Government, we apply the model to secondary schools and Further and Higher Education environments. Specifically, we consider student populations mixing in a classroom and in halls of residence. We focus on assessing the potential efficacy of Lateral Flow Devices (LFDs) when used in broad-based screens for asymptomatic infection or in  test-to-release scenarios in which individuals who have been exposed to infection are released from isolation given a negative result. LFDs are also compared to other NPIs; we find that, although LFD testing can be used to mitigate the spread of Covid-19, it is more effective to invest in personal protective equipment, e.g. masks, and in increasing ventilation quality. In addition, we provide an open-access and user-friendly online applet that simulates the individual-based model, complete with user tutorials to encourage the use of the model to aid educational policy decisions as input infection data evolves (https://bit.ly/CV19_INTER_IBM). Three-dimensional cephalometric landmarking and Frankfort horizontal plane construction: reproducibility of conventional and novel landmarks ObjectivesTo assess manual landmarking repeatability and reproducibility (R&R) of a set of three-dimensional (3D) landmarks and to evaluate R&R of vertical cephalometric measurements using two Frankfort Horizontal (FH) planes as references for horizontal 3D imaging reorientation.

MethodsThirty-three landmarks, divided into "conventional", "foraminal" and "dental", were manually located twice by 3 experienced operators on 20 computed tomography (CT) scans of orthognathic surgery patients. R&R of the landmark localization were computed according to the ISO 5725 standard. These landmarks were then used to construct 2 FH planes: a conventional FH plane (orbitale left, porion right and left) and a newly proposed FH plane (midinternal acoustic foramen, orbitale right and left). R&R of vertical cephalometric measurements were computed using these 2 FH planes as horizontal references for CT reorientation.

ResultsLandmarks showing a 95% confidence interval (CI) of repeatability and/or reproducibility > 2mm were found exclusively in the "conventional" landmarks group. Vertical measurements showed excellent R&R (95% CI < 1mm) with either FH plane as horizontal reference. However, the 2 FH planes were not found to be parallel (absolute angular difference of 2.41{degrees}, SD 1.27{degrees}). The average time needed to landmark one CT scan was 14 {+/-} 3 minutes.

ConclusionsThe "dental" and "foraminal" landmarks tended to be more reliable than the "conventional" landmarks. Despite the poor overall reliability of the landmarks orbitale and porion, the construction of the conventional FH plane using 3 landmarks provided a reliable horizontal reference for 3D craniofacial CT scan reorientation. The Addiction Risk Factor: A Unitary Genetic Vulnerability Characterizes Substance Use Disorders and Their Associations with Common Correlates Substance use disorders commonly co-occur with one another and with other psychiatric disorders. They share common features including high impulsivity, negative affect, and lower executive function. We tested whether a common genetic factor undergirds liability to problematic alcohol use (PAU), problematic tobacco use (PTU), cannabis use disorder (CUD), and opioid use disorder (OUD) by applying genomic structural equation modelling to genome-wide association study summary statistics for individuals of European ancestry (Total N = 1,019,521; substance specific Ns range: 82,707-435,563), while adjusting for the genetics of substance use (Ns = 184,765-632,802). We also tested whether shared liability across SUDs is associated with behavioral constructs (risk taking, executive function, neuroticism; Ns = 328,339-427,037) and non-substance use psychopathology (psychotic, compulsive, and early neurodevelopmental disorders). Shared genetic liability to PAU, PTU, CUD, and OUD was characterized by a unidimensional addiction risk factor (termed The Addiction-Risk-Factor, independent of substance use. OUD and CUD demonstrated the largest loadings, while problematic tobacco use showed the lowest loading. The Addiction-Risk-Factor was associated with risk taking, neuroticism, executive function, and non-substance psychopathology, but retained specific variance before and after accounting for genetics of substance use. Thus, a common genetic factor partly explains susceptibility for alcohol, tobacco, cannabis, and opioid use disorder. The Addiction-Risk-Factor has a unique genetic architecture that is not shared with normative substance use or non-substance psychopathology, suggesting that addiction is not the linear combination of substance use and psychopathology. Decoding Neural Activity in Sulcal and White Matter Areas of the Brain to Accurately Predict Individual Finger Movement and Tactile Stimuli of the Human Hand Millions of people worldwide suffer motor or sensory impairment due to stroke, spinal cord injury, multiple sclerosis, traumatic brain injury, diabetes, and motor neuron diseases such as ALS (amyotrophic lateral sclerosis). A brain-computer interface (BCI), which links the brain directly to a computer, offers a new way to study the brain and potentially restore these losses in patients living with debilitating conditions. One of the challenges currently facing BCI technology, however, is how to minimize surgical risk. Minimally invasive techniques, such as stereoelectroencephalography (SEEG) have become more widely used in clinical applications since they can lead to fewer complications. SEEG electrodes also give access to sulcal and white matter areas of the brain but have not been widely studied in brain-computer interfaces. We therefore investigated the viability of using SEEG electrodes in a BCI for recording and decoding neural signals related to movement and the sense of touch and compared its performance to electrocorticography electrodes (ECoG) placed on gyri. Initial poor decoding performance and the observation that most neural modulation patterns were highly variable trial-to-trial and transient (significantly shorter than the sustained finger movements studied), led to the development of a feature selection method based on a repeatability metric using temporal correlation. An algorithm based on temporal correlation was developed to isolate features that consistently repeated (required for accurate decoding) and possessed information content related to movement or touch-related stimuli. We subsequently used these features, along with deep learning methods, to automatically classify various motor and sensory events for individual fingers with high accuracy. Repeating features were found in sulcal, gyral, and white matter areas and were predominantly phasic or phasic-tonic across a wide frequency range for both HD (high density) ECoG and SEEG recordings. These findings motivated the use of long short-term memory (LSTM) recurrent neural networks (RNNs) which are well-suited to handling both transient and sustained input features. Combining temporal correlation-based feature selection with LSTM yielded decoding accuracies of up to 92.04 +/-1.51% for hand movements, up to 91.69 +/-0.49% for individual finger movements, and up to 80.64 +/-1.64% for focal tactile stimuli to the finger pads and palm while using a relatively small number of SEEG electrodes. These findings may lead to a new class of minimally invasive brain-computer interface systems in the future, increasing its applicability to a wider variety of conditions. Association of preference and frequency of teleworking with work functioning impairment: a nationwide cross-sectional study of Japanese full-time employees ObjectiveWe examined whether teleworking preference and frequency were associated with work functioning impairment.

MethodsThis online cross-sectional study was conducted using a self-administered questionnaire among 27,036 full-time Japanese workers. The Work Functioning Impairment Scale was used to measure work functioning impairment, and we performed multilevel logistic regression analysis.

ResultsHigher odds ratios for work functioning impairment were observed among employees who preferred to telework compared with those who preferred working in the workplace. A similar trend was observed among employees who teleworked 4 or more days a week compared with those who almost never teleworked. When teleworking preference and frequency were adjusted, only teleworking preference was associated with work functioning impairment.

ConclusionsA preference for teleworking was associated with work functioning impairment and one factor that increased the teleworking frequency. Survey of Contaminated Percutaneous Injuries in Anesthesia Practitioners BackgroundAnesthesia practitioners are at inherent risk for percutaneous injuries by blood-contaminated needles and sharp objects. These exposures may result in transmission of HIV and hepatitis viruses. Data about this occupational hazard from contaminated needles and sharp devices is limited and decades old. We conducted a web-based survey to assess the occurrence, reporting, characteristics, and outcome of contaminated percutaneous injuries (CPI) in anesthesia residents, fellows, and attendings.

MethodsAfter institutional research board approval, an email was sent to 217 anesthesia practitioners requesting their participation in an online survey about contaminated percutaneous injuries. Responses were collected from February through March 2020. Results are reported as absolute numbers and proportions with 95% confidence interval (CI).

ResultsThe overall survey response rate was 51% (110/217). 59% (65/110) (95% CI, 50-68) of participants reported having one or more contaminated percutaneous injury during their years of anesthesia practice (42% (21/50) of residents, 50% (4/8) of fellows, 77% (40/52) of anesthesia attendings). Prevalence of injuries related to attendings years of anesthesia practice was 69% (95% CI, 44-94) for 5-10 years, 62.5% (95% CI, 29-96) for 10-15 years, and 79% (95% CI, 63- 95) for greater than 15 years of practice.

35% (95% CI, 26-44) of participants reported having one or more CPI within the last 5 years (40% of residents, 50% of fellows, 29% of attendings). Occurrence of CPI within the last 5 years based on attending anesthesiologist years of practice was 57% for less than 5 years, 37.5% for 10-15 years, and 20% for 15-20 years of practice. 75% (95% CI, 65-85) reported the incident at the time of injury. 59% (95% CI, 48-70) of injuries were due to hollow bore needles. 50% (95% CI, 39-61) of total injuries were high risk. 26% of injured anesthesia practitioners received post-exposure prophylaxis and there were zero seroconversions.

ConclusionMost anesthesiologists will sustain a contaminated percutaneous injury during their careers. Incidence of these injuries decreases with years of practice. Occurrence of these injuries is high among anesthesia residents, with the majority reporting their injuries. Half of the injuries are high risk with a quarter requiring postexposure prophylaxis. More education and interventions are needed to reduce percutaneous injuries and improve reporting. Deaths from cardiovascular disease involving anticoagulants: a systematic synthesis of coroners' case reports BackgroundThe global burden of cardiovascular disease (CVD) is forecast to increase, and anticoagulants will remain important medicines for its management. Coroners Prevention of Future Death reports (PFDs) provide valuable insights that may enable safer and more effective use of these agents.

AimTo identify CVD-related PFDs involving anticoagulants.

Design and SettingRetrospective observational study of coronial case reports in England and Wales between 2013 and 2019.

MethodWe screened 3037 PFDs for eligibility and included PFDs where CVD and an anticoagulant caused or contributed to the death. We descriptively analysed included cases and used content analysis to assess concerns raised by coroners and who responded to them.

ResultsWe identified 113 cardiovascular disease-related PFDs involving anticoagulants. Warfarin (36%), enoxaparin (11%), and rivaroxaban (11%) were the most common anticoagulants reported. Concerns most frequently raised by coroners included poor systems (31%), poor communication (25%), and failures to keep accurate medical records (25%). These concerns were most often directed to NHS trusts (29%), hospitals (10%), and general practices (8%). Nearly two-thirds (60%) of PFDs had not received responses from such organisations, which are mandatory under regulation 28 of the Coroners (Investigations) Regulations 2013. We created a publicly available tool, https://preventabledeathstracker.net/, which displays coroners reports in England and Wales to streamline access and identify important lessons to prevent future deaths.

ConclusionNational organisations, healthcare professionals, and prescribers should take actions to address the concerns of coroners in PFDs to improve the safe use of anticoagulants in patients with cardiovascular disease.

How this fits inA previous assessment of 500 PFDs identified anticoagulants as the class of drugs most often involved in fatal medication errors. This study uses innovative methods to automatically collect all available PFDs between 2013 and 2019 to identify deaths from cardiovascular disease when the use of or lack of anticoagulants caused or contributed to the death. Coroners raised hundreds of coroners in their reports, including issues with communication, following protocols, education and training, access to resources, and safety. Despite repeat concerns with national relevance being identified, most CVD-anticoagulant PFDs were sent locally to NHS Trusts, hospitals, and general practices, limiting their ability to reduce harms and prevent premature deaths. Hyperreflective foci, OCT progression indicators in age-related macular degeneration, include transdifferentiated retinal pigment epithelium PurposeBy optical coherence tomography (OCT) imaging, hyperreflective foci (HRF) indicate progression risk for advanced age-related macular degeneration (AMD) and are in part attributable to ectopic retinal pigment epithelium (RPE). We hypothesized that ectopic RPE are molecularly distinct from in-layer cells and that their cross-retinal course follows Muller glia.

MethodIn clinical OCT (61 eyes, 44 AMD patients, 79.4 {+/-} 7.7 years; 29 female; follow-up = 4.7 {+/-} 0.9 years) one HRF type, RPE plume, was reviewed. Twenty eyes of 20 donors characterized by ex vivo OCT were analyzed by histology (normal, 4; early/intermediate AMD, 7; geographic atrophy (GA), 6; 3 neovascular AMD (nvAMD). Cryosections were stained with antibodies to retinoid (RPE65, CRALPB) and immune (CD68, CD163) markers. In published RPE cellular phenotypes, red immunoreactivity was assessed semi-quantitatively by one observer (none, some cells, all cells).

ResultsTrajectories of RPE plume and cellular debris paralleled Muller glia, whether ordered or subsident, near atrophy borders. RPE corresponding to HRF lost immunoreactivity for retinoid markers and gained immunoreactivity for immune markers. Aberrant immunoreactivity appeared in individual in-layer RPE cells and extended to all abnormal phenotypes. Muller glia remained CRALBP-positive. Plume cells approached and contacted retinal capillaries.

ConclusionGain- and loss-of-function starts with individual in-layer RPE cells and extends to all abnormal phenotypes. Down-regulated RPE retinoid handling may impair rod vision while Muller glia sustain cone vision. Evidence for RPE transdifferentiation, possibly due to ischemia, supports a proposed process of epithelial-mesenchyme transition. Data can propel new biomarkers and therapeutic strategies for AMD.

PrecisHyperreflective foci (HRF) are OCT progression risk indicators in age-related macular degeneration. Abnormal RPE cells including some that correspond to HRF lose immunoreactivity for retinoid markers and gain immunoreactivity for immune markers, indicating molecular transdifferentiation. PENet: Continuous-Valued Pulmonary Edema Severity Prediction On Chest X-ray Using Siamese Convolutional Networks For physicians to take rapid clinical decisions for patients with congestive heart failure, the assessment of pulmonary edema severity in chest radiographs is vital. While deep learning has been promising in detecting the presence or absence, or even discrete grades of severity, of such edema, prediction of the continuous-valued severity yet remains a challenge. Here, we propose PENet, a deep learning framework to assess the continuous spectrum of pulmonary edema severity from chest X-rays. We present different modes of implementing this network, and demonstrate that our best model outperforms that of earlier work (mean area under the curve of 0.91 over 0.87, for nine comparisons), while saving training data and computation. Efficacy and Safety of FLOT regimen vs DCF, FOLFOX, and ECF regimens as Perioperative Chemotherapy Treatments for Resectable Gastric Cancer Patients PurposeThis study aimed to compare the efficacy and toxicity of perioperative chemotherapy regimens including ECF, DCF, FOLFOX, and FLOT to identify the most effective chemotherapy regimen with less toxicity.

MethodThis retrospective cohort study(2014-2021) was based on 152 eligible resectable gastric cancer patients who had received one of the perioperative chemotherapy regimens including ECF, DCF, FOLFOX, or FLOT, and followed for at least two years. The primary endpoint of this study was Overall Survival (OS), Progression-Free Survival (PFS), Overall Response Rate (ORR), and R0 resection. We also considered toxicity according to CTCAE (v.4.0) criteria as a secondary endpoint.

ResultsOf included patients, 32(21%), 51(33.7%), 37(24.3%), and 32(21%) had received ECF, DCF, FOLFOX and FLOT, respectively. After the median 30 months follow-up, overall survival was higher with the FLOT regimen in comparison with other regimens (hazard ratio [HR] = 0. 276). The median OS of the FLOT regimen was 39 months. Besides, the median OS was 28, 25, and 21 months for DCF, FOLOFX, and ECF regimens, respectively. Moreover, a median PFS of 24, 18, 17, and 14 months was observed for FLOT, DCF, FOLFOX, and ECF regimens, respectively (Log-rank <0.001). FLOT regimen showed 84. 4% ORR, was notably higher than other groups (p-value<0. 01).

ConclusionsFor resectable gastric cancer patients, the perioperative FLOT regimen led to a significant improvement in patients OS and PFS in comparison with ECF, DCF, and FOLFOX regimens. As such, the FLOT regimen could be considered the optimal option for managing resectable gastric cancer patients. The CT Scan Lung Severity Score and Vaccination Status in COVID-19 patients in India: Perspective of an Independent Radiology Practice BackgroundThe COVID-19 patients often undergo a high-resolution CT scan to determine extent of their lung involvement. The aim of this study was to determine lung involvement in confirmed/suspected COVID-19 patients (encountered at an independent radiology practice) and its correlation to vaccination status amidst the second COVID-19 wave in India.

MethodsWe retrospectively queried our data since April 2021 to identify adult patients (>17 years) who had confirmed (positive RT-PCR or antigen test) or suspected COVID-19 (classic symptoms but negative RT-PCR) and received a high-resolution CT scan to determine the extent of their lung involvement using the CT severity (CT-SS) score. Patients were classified in 3 groups based on their vaccination status to determine its correlation with the CT-SS score: fully vaccinated, partially vaccinated, and unvaccinated. Basic descriptive statistics, univariate tests and multivariate linear regression analysis were used.

ResultsWe identified 229 patients (median age 45 years, 60% male) of which 205 (89%) had confirmed COVID-19 (positive RT-PCR) and 24 had suspected disease (negative RT-PCT but classic symptoms). Of the 229 patients 29 (13%) had complete vaccination, 38 (17%) had partial vaccination and 162 (70%) had no vaccination. The CT score of the completely vaccinated patients was significantly lower compared to partially or unvaccinated patients (median 0 v. 3.5 v. 10, respectively p<.01). A multivariate linear regression model showed that partial or fully vaccinated patients had lower CT severity score compared to unvaccinated patients (adjusted R squared = 0.47).

ConclusionWe present here the real-world findings from an independent radiology practice (a unique and common practice model), in India amid the second COVID-19 wave showing significantly lower CT severity score in fully or partially vaccinated patients compared to unvaccinated patients. Complete vaccination in patients could be critical in preventing severe lung disease. Impact of natural selection on global patterns of genetic variation, and association with clinical phenotypes, at genes involved in SARS-CoV-2 infection. We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection (ACE2, TMPRSS2, DPP4, and LY6E). We analyzed novel data from 2,012 ethnically diverse Africans and 15,997 individuals of European and African ancestry with electronic health records, and integrated with global data from the 1000GP. At ACE2, we identified 41 non-synonymous variants that were rare in most populations, several of which impact protein function. However, three non-synonymous variants were common among Central African hunter-gatherers from Cameroon and are on haplotypes that exhibit signatures of positive selection. We identify strong signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2, we identified 13 amino acid changes that are adaptive and specific to the human lineage. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19. A Randomised Trial of a Wearable UV dosimeter for Skin Cancer Prevention BackgroundNon-melanoma skin cancer (NMSC) is the most prevalent cancer in the United States, affecting 5 million people and costing $8.1 billion per year. Despite well-defined guidelines on ultraviolet radiation (UVR) avoidance, it remains difficult for people to assess their individual exposure, as UVR is invisible and the onset of symptoms due to UVR damage are delayed.

MethodsIn a prospective, randomized-controlled trial, 97 patients with a history of actinic keratoses were enrolled from March 2018 to July 2018 and followed over 6 months. 50 patients were given a wearable device that measured UV exposure and a smartphone application that provided both real-time and cumulative UV exposure information, and 47 patients were provided with UV protection counseling by a dermatologist.

ResultsWe observed a significant decrease in the incidence rate of NMSC in the intervention group compared to the control group over 3 months (p = 0.02). We did not observe a significant decrease in the incidence rate of actinic keratoses (AK) in the intervention group compared to the control group. The observed clinical benefit was not accompanied by psychological side effects such as anxiety and depression.

ConclusionsThis study suggests that providing real-time UV exposure data using a wearable UV dosimeter is a safe and effective behavioral change strategy to prevent NMSC. (Funded by the National Cancer Institute, contract HHSN261201700005C; ClinicalTrials.gov number NCT03315286.) Dental biofilm microbiota dysbiosis is associated with the risk of acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation Acute graft-versus-host disease (aGVHD) is one of the major causes of death after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Recently, aGVHD onset was linked to intestinal microbiota (IM) dysbiosis. However, other bacterial-rich gastrointestinal sites, such as the mouth, which hosts several distinctive microbiotas, may also impact the risk of GVHD. The dental biofilm microbiota (DBM) is highly diverse and, like the IM, interacts with host cells and modulates immune homeostasis. We characterized changes in the DBM of patients during allo-HSCT and evaluated whether the DBM could be associated with the risk of aGVHD. DBM dysbiosis during allo-HSCT was marked by a gradual loss of bacterial diversity and changes in DBM genera composition, with commensal genera reductions and potentially pathogenic bacteria overgrowths. High Streptococcus and high Corynebacterium relative abundance at preconditioning were associated with a higher risk of aGVHD (67% vs. 33%; HR = 2.89, P = 0.04 and 73% vs. 37%; HR = 2.74, P = 0.04, respectively), while high Veillonella relative abundance was associated with a lower risk of aGVHD (27% vs. 73%; HR = 0.24, P < 0.01). Enterococcus faecalis bloom during allo-HSCT was observed in 20% of allo-HSCT recipients and was associated with a higher risk of aGVHD (100% vs. 40%; HR = 4.07, P < 0.001) and severe aGVHD (60% vs. 12%; HR = 6.82, P = 0.01). To the best of our knowledge, this is the first study demonstrating that DBM dysbiosis is associated with the aGVHD risk after allo-HSCT. The kidney releases a non-polymerizing form of Uromodulin in the urine and circulation that retains the external hydrophobic patch domain Uromodulin (Tamm-Horsfall protein, THP) is a glycoprotein uniquely produced in the kidney. It is released by cells of the thick ascending limbs (TAL) apically in the urine, and basolaterally in the renal interstitium and systemic circulation. Processing of mature urinary THP, which polymerizes into supra-molecular filaments, requires cleavage of an external hydrophobic patch (EHP) at the C terminus. However, THP in the circulation is not polymerized, and it remains unclear if non-aggregated forms of THP exist natively in the urine. We propose that an alternative processing path, which retains the EHP domain, can lead to a non-polymerizing form of THP. We generated an antibody that specifically recognizes THP with retained EHP (THP+EHP) and established its presence in the urine in a non-polymerized native state. Proteomic characterization of urinary THP+EHP revealed its C-terminus to end at F617. In the human kidney, THP+EHP was not only detected in TAL cells, but also diffusely in the renal parenchyma. Using immunoprecipitation followed by proteomic sequencing and immunoblotting, we then demonstrated that serum THP has also retained EHP. In a small cohort of patients at risk for acute kidney injury (AKI), admission urinary THP+EHP was significantly lower in patients who subsequently developed AKI during hospitalization. Our findings uncover novel insights into uromodulin biology by establishing the presence of an alternative path for cellular processing, which could explain the release of non-polymerizing THP in the circulation. Larger studies are needed to establish the utility of urinary THP+EHP as a sensitive biomarker of kidney health and susceptibility to injury. The impact of social and environmental extremes on cholera time varying reproduction number in Nigeria Nigeria currently reports the second highest number of cholera cases in Africa, with numerous socioeconomic and environmental risk factors. Less investigated are the role of extreme events, despite recent work showing their potential importance. To address this gap, we estimated time varying reproductive number (R) from cholera incidence in Nigeria and used a machine learning approach to evaluate its association with extreme events (conflict, flood, drought) and pre-existing vulnerabilities (poverty, sanitation, healthcare). We then created a traffic-light system for cholera outbreak risk, using three hypothetical traffic-light scenarios (Red, Amber and Green) and used this to predict R. The system highlighted potential extreme events and socioeconomic thresholds for outbreaks to occur. We found that reducing poverty and increasing access to sanitation lessened vulnerability to increased cholera risk caused by extreme events (monthly conflicts and the Palmers Drought Severity Index). The work presented here shows the need for sustainable development for disaster prevention and mitigation and to improve health and quality of life. A User Preference Analysis Of Commercial Breath Ketone Sensors To Inform The Development Of Portable Breath Ketone Sensors For Diabetes Management In Young People BackgroundPortable breath ketone sensors may help people with Type 1 Diabetes Mellitus (T1DM) avoid episodes of diabetic ketoacidosis; however the design features preferred by users have not been studied. We aimed to elucidate breath analysis and design preferences associated with commercial breath ketone devices among young people with T1DM aged 12-16 years and their parents in order to inform the development of a breath ketone sensor prototype for diabetes management.

Research Designs and MethodsTwo commercially available breath ketone sensors, designed for ketogenic diet monitoring, were explored over one week by ten young people with T1DM to get an insight into breath measurements. Participants interacted with the devices at least twice daily for five days, taking breath ketone, blood ketone and blood glucose measurements. Semi-structured interviews were conducted post-testing with the young participants and their caregivers to elicit preferences related to breath analysis and to inform the co-design of a diabetes breath ketone sensor prototype. To validate the results from a professional healthcare perspective, we interviewed two diabetes educators working in pediatric care about their perspective of young people using breath ketone sensors.

ResultsParticipants acknowledged the non-invasiveness of breath sensors as compared to blood testing. Affordability, reliability and accuracy were identified as prerequisites for breath ketone sensors used for diabetes management. Design features valued by young people included portability, ease of use, sustainability, readability and suitability for use in public. The time required to use breath sensors was similar to that for blood testing. The requirement to maintain a 10-second breath exhalation posed a challenge for users. Diabetes educators highlighted the ease of use of breath devices especially for young people with insufficient blood ketone testing.

ConclusionsBreath ketone sensors for diabetes management bear potential to facilitate ketone testing in young people. Our study affirms features for young people that drive usability of breath sensors among this population, and provides a model of user preference assessment.

Highlights/new findingsO_LIPortable breath ketone sensors potentially offer a non-invasive alternative to blood ketone testing in diabetes management, especially for young people with diabetes.
C_LIO_LIA user preference assessment of portable non-medical breath ketone devices among young people with Type 1 Diabetes Mellitus demonstrates the key values associated with breath ketone devices for diabetes management.
C_LIO_LIThe time to test for breath ketones was similar to that of blood ketone testing.
C_LIO_LIYoung people can and should be engaged in co-creation of medical devices that they will use.
C_LI Prospectively validated disease-agnostic predictive medicine with augmented intelligence Despite numerous superhuman achievements in complex challenges1,2, standalone AI does not free life science from the long-term bottleneck of linearly extracting new knowledge from exponentially growing new data3, severely limiting the success rate of drug discovery4. Inspired by the state-of-the-art AI training methods, we trained a human-centric hybrid augmented intelligence5 (HAI) to learn a foundation model6 that extracts all-encompassing knowledge of human physiology and diseases. To evaluate the quality of HAIs extracted knowledge, we designed the public, prospective prediction of pivotal ongoing clinical trial outcomes at large scale (PROTOCOLS) challenge to benchmark HAIs real-world performance of predicting drug clinical efficacy without access to human data. HAI achieved a 10.5-fold improvement from the baseline with 99% confidence7 in the PROTOCOLS validation, readily increasing the average clinical success rate of investigational new drugs from 7.9%8 to 90% for almost any human diseases9,10. The validated HAI confirms that exponentially extracted knowledge alone is sufficient for accurately predicting drug clinical efficacy, effecting a total reversal of Erooms law4. HAI is also the worlds first clinically validated model of human aging that could substantially speed up the discovery of preventive medicine for all age-related diseases11. Our results demonstrate that disruptive breakthroughs necessitate the smallest team size to attain the largest HAI for optimal knowledge extraction from high-dimensional low-quality data space, thus establishing the first prospective proof of the previous discovery that small teams disrupt12. The global adoption of training HAI provides a well-beaten economic path to mass-produce scientific and technological breakthroughs via exponential knowledge extraction and better designs of data labels for training better-performing AI13. Molecular analysis suggests oligoclonality and metastasis of endometriosis lesions across anatomically defined subtypes. Endometriosis symptoms are heterogeneous with controversy on whether it constitutes a single disease or multiple distinct types. Our previous work found recurrent somatic cancer-driver alterations in endometriosis; however, these have not been found ubiquitously. A handful of cases spread across studies also suggest mutations might be shared (clonal) between lesions of the same type. As current classification systems correlate poorly with symptoms or outcomes, somatic genomics may improve the current system. Here, we investigate heterogeneity of somatic cancer-driver mutations within patients and across endometriosis types. We examined anatomically distinct types of endometriosis (ovarian, deep infiltrating, and superficial endometriosis) in 27 individual patients all of whom had at least two types of endometriosis. Specimens were analyzed using high-sensitivity targeted sequencing with orthogonal validation from droplet digital PCR and mutation-surrogate immunohistochemistry. Results found 13/27 patients had informative somatic driver mutation in endometriosis, 9/13 had identical mutations across distinct lesions. Endometriomas tended to have a higher mutational complexity, with functionally redundant driver mutations in same gene and within the same lesions.

Our data are consistent with clonality across endometriosis lesions regardless of subtype. Further the finding of redundancy in mutations with the same gene and lesions is also consistent with endometriosis representing an oligoclonal disease with dissemination likely to consist of multiple epithelial clones travelling together. This suggests the current anatomically defined classification of endometriosis does not fully recognize the etiology of the disease. A novel classification should take into account genomic and other molecular features. These findings could further contribute to development of a more personalized endometriosis diagnosis and care. An Accurate Model for SARS-CoV-2 Pooled RT-PCR Test Errors PCR testing is an important tool to mitigate outbreaks of infectious diseases. One way of increasing testing throughput is by simultaneously testing multiple samples for the presence of a pathogen, a technique known as pooling. During the current COVID-19 pandemic, rapidly testing individuals for the presence of SARS-CoV-2 is conducted in large amounts. Since testing is often a bottleneck in mitigating the spread of SARS-CoV-2, pooling is increasing in popularity. Most analyses of the error rates of pooling schemes assume that including more than a single infected sample in a pooled test does not increase the probability of a positive outcome. We challenge this assumption with experimental data and suggest a novel probabilistic model for the outcomes of pooled tests. As an application, we analyze the false-negative rates of one common pooling scheme known as Dorfman pooling. We show that the false-negative rates of Dorfman pooling increase when the prevalence of infection decreases. However, low infection prevalence is exactly the condition under which Dorfman pooling achieves highest throughput. We therefore implore the cautious use of pooling and development of pooling schemes that consider correctly accounting for tests error rates. Variability in proteoglycan biosynthetic genes reveals new facets of heparan sulfates diversity. A systematic review and analysis Proteoglycans are complex macromolecules formed of glycosaminoglycan chains covalently linked to core proteins through a linker tetrasaccharide common to heparan sulfate proteoglycans (HSPG) and chondroitin sulfate proteoglycans (CSPG). Biosynthesis of a single proteoglycan requires the expression of dozens of genes, which together create the large structural and functional diversity reflected by the numerous diseases or syndromes associated to their genetic variability. Among proteoglycans, HSPG are the most structurally and functionally complex. To decrease this complexity, we retrieved and linked information on pathogenic variants, polymorphism, expression, and literature databases for 50 genes involved in the biosynthesis of HSPG core proteins, heparan sulfate (HS) chains, and their linker tetrasaccharide. This resulted in a new gene organization and biosynthetic pathway representation in which the phenotypic continuum of disorders as linkeropathies and other pathologies could be predictable. Moreover, ubiquitous NDST1, GLCE, HS2ST1, and HS6ST1 appeared to generate ubiquitous heparan sulfate (HS) sequences essential for normal development and homeostasis, whereas the tissue restricted NDST2-4, HS6ST2-3, and HS3ST1-6 appeared to generate specialized HS sequences mainly involved in responsiveness to stimuli. Supported by data on genetic polymorphism and clinical variants, we afford a new vision of HSPG involvement in homeostasis, disease, vulnerability to disease, and behavioral disorders. What delirium detection tools are used in routine clinical practice in the United Kingdom? Survey results from 91% of acute healthcare organisations. PurposeOur aim was to collect information on delirium assessment processes and pathways in non-intensive care settings in the United Kingdom (UK).

MethodsWe sent a Freedom of Information request to 169 UK National Health Service (NHS) hospitals, trusts and health boards (units) in July 2020 to obtain data on usage of delirium assessment tools in clinical practice and delirium pathways or guidelines.

ResultsWe received responses from 154/169 units (91% response rate). Of these, 146/154 (95%) units reported use of formal delirium assessment processes and 131/154 (85%) units had guidelines or pathways in place. The 4  As Test (4AT) was the most widely used tool, with 117/146 (80%) units reporting use. The Confusion Assessment Method was used in 65/146 (45%) units, and the Single Question to identify Delirium (SQiD) in 52/146 (36%) units.

ConclusionsOur findings show that the 4AT is the most commonly used tool in the UK, with 80% of units reporting use. This study adds to our knowledge of real-world uptake of delirium detection methods at scale. Future studies should evaluate real-world implementation of delirium assessment tools further via (i) tool completion rates and (ii) rates of positive scores against the expected prevalence delirium in the clinical population concerned.

KEY SUMMARY POINTSO_ST_ABSAimC_ST_ABSTo seek information on delirium assessment processes and pathways in non-intensive clinical care settings in the United Kingdom (UK), and to assess usage of specific delirium assessment tools: the 4  As Test (4AT), Confusion Assessment Method and Single Question to identify Delirium (SQiD).

FindingsIn total, 95% of National Health Service (NHS) units (hospitals, trusts and health boards) reported use of formal delirium assessment processes and 85% of units had guidelines or pathways in place. The 4AT was the most widely used tool, with 80% of units reporting use; the Confusion Assessment Method was reportedly used in 45% of units and the SQiD in 36% of units.

MessageThis study shows real-world, large-scale uptake of delirium detection methods and delirium guidelines in UK hospitals, which contributes to ongoing efforts to improve delirium care. Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine Diffusion Kurtosis Imaging (DKI) has undisputed advantages over more classical diffusion Magnetic Resonance Imaging (dMRI), as witnessed by a fast-increasing number of clinical applications and software packages widely adopted in brain imaging. However, in the neonatal setting, DKI is still largely underutilized in Spinal Cord (SC) imaging because of its inherently demanding technological requirements.

Due to its extreme sensitivity to non-gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, and not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between SC region and the above brain, managing to apply such a method to neonatal cohort becomes of utmost importance.

This study will (i) review the current methodological challenges associated with application of advanced dMRI methods like DKI in early infancy, (ii) illustrate the first semi-automated pipeline built on Spinal Cord Toolbox (SCT) for handling with DKI data of neonatal SC, from acquisition setting to estimation of diffusion measures, through accurate adjustment of processing algorithms customized for adult SC, and (iii) present preliminary results of its application in a pilot clinical case study.

Results of this application agree with findings achieved in a corresponding adult survey, thus confirming validity of adopted pipeline and diagnostic value of DKI in pediatrics.