The second wave of SARS-CoV-2 infections and COVID-19 deaths in Germany - driven by values, social status and migration background? A county-scale explainable machine learning approach There is a general consensus that SARS-CoV-2 infections and COVID-19 deaths have hit lower social groups the hardest, however, for Germany individual level information on socioeconomic characteristics of infections and deaths does not exist. The aim of this study was to identify the key features explaining SARS-CoV-2 infections and COVID-19 deaths during the upswing of the second wave in Germany.

We considered information on COVID-19 diagnoses and deaths from 1. October to 15. December 2021 on the county-level, differentiating five two-week time periods. We used 155 indicators to characterize counties in nine geographic, social, demographic, and health domains. For each period, we calculated directly age-standardized COVID-19 incidence and death rates on the county level. We trained gradient boosting models to predict the incidence and death rates with the 155 characteristics of the counties for each period. To explore the importance and the direction of the correlation of the regional indicators we used the SHAP procedure. We categorized the top 20 associations identified by the Shapley values into twelve categories depicting the correlation between the feature and the outcome.

We found that counties with low SES were important drivers in the second wave, as were those with high international migration and a high proportion of foreigners and a large nursing home population. During the period of intense exponential increase in infections, the proportion of the population that voted for the Alternative for Germany (AfD) party in the last federal election was among the top characteristics correlated with high incidence and death rates.

We concluded that risky working conditions with reduced opportunities for social distancing and a high chronic disease burden put populations in low-SES counties at higher risk of SARS-CoV-2 infections and COVID-19 deaths. In addition, noncompliance with Corona measures and spill-over effects from neighbouring counties increased the spread of the virus. To further substantiate this finding, we urgently need more data at the individual level.
Contact tracing can explain counter-intuitive COVID-19 trajectories, mitigate disease transmission and provide an early warning indicator - a mathematical modeling study The COVID-19 trajectories worldwide have shown several surprising features which are outside the purview of classical epidemiological models. These include (a) almost constant and low daily case rates over extended periods of time, (b) sudden waves emerging from the above solution despite no or minimal change in the level of non-pharmaceutical interventions (NPI), and (c) reduction or flattening of case counts even after relaxation of NPI. To explain these phenomena, we add contact tracing to our recently developed cluster seeding and transmission (CST) model, which is predicated on heterogeneous rather than homogeneous mixing of people in society. With this addition, we find no fewer than four effects which make prediction of epidemic trajectories uncertain. These are (a) cryptogenic instability, where a small increase in population-averaged contact rate causes a large increase in cases, (b) critical mass effect, where a wave can manifest after weeks of quiescence with no change in parameter values, (c) knife-edge effect, where a small change in parameter across a critical value can cause a huge change in the response of the system, and (d) hysteresis effect, where the timing and not just the strength of a particular NPI determines the subsequent evolution of the epidemic. Despite these effects however, it is a robust conclusion that a good contact tracing program can effectively substitute for much more invasive measures. We further find that the contact tracing capacity ratio - a metric of the stress to which the tracers are subject - can act as a reliable early warning indicator of an imminent epidemic wave. Extensive simulations demonstrate that whenever there is a drop in capacity ratio during a period of low daily infections, there is a very high probability of the case counts rising significantly in the immediate future.

Author summaryClose to two years into the pandemic, the trajectories of COVID-19 in different places and at different times have shown wild variations and confounded modeling and forecasting efforts. Our new mathematical model can help to explain these variations. Some solutions of our model are non-standard but realistic. For example, we find an epidemic curve where daily cases remain on a plateau for a long time before suddenly exploding into a wave, despite interventions remaining constant throughout. We also find solutions showing that a specific intervention, for example capacity reduction at public gatherings, is very effective if implemented early on in a wave but useless if implemented a little later. Our proposed early warning indicator can be a game-changer for epidemic forecasting and model-based intervention strategies. Current forecasting algorithms have the weakest performance at the inflection points where there is an abrupt change in trend in the daily infection rates. The early warning indicator can give us advance notice of an approaching inflection point, and enable the authorities to take preventive measures before a wave actually arrives. Our results indicate that close communication between contact tracing personnel and public health authorities can achieve synergistic mitigation of the pandemic.
Diagnostic Model of in-Hospital Mortality in Patients with Acute ST-Segment Elevation Myocardial Infarction Used Artificial Intelligence Methods BackgroundPreventing in-hospital mortality in Patients with ST-segment elevation myocardial infarction (STEMI) is a crucial step.

ObjectivesThe objective of our research was to to develop and externally validate the diagnostic model of in-hospital mortality in acute STEMI patients used artificial intelligence methods.

MethodsWe divide non-randomly the American population with acute STEMI into a training set, a test set,and a validation set. We converted the unbalanced data into balanc ed data. We used artificial intelligence methods to develop and externally validate the dia gnostic model of in-hospital mortality in acute STEMI patients. We used confusion matrix combined with the area under the receiver operating characteristic curve (AUC) to evaluat e the pros and cons of the above models.

ResultsThe strongest predictors of in-hospital mortality were age, gender, cardiogenic shock, atrial fibrillation(AF), ventricular fibrillation(VF),third degree atrioventricular block,in-hospital bleeding, underwent percutaneous coronary intervention(PCI) during hospitalization, underwent coronary artery bypass grafting (CABG) during hospitalization, hypertension history, diabetes history, and myocardial infarction history.The F2 score of logistic regression in the training set, the test set, and the validation data set were 0.81, 0.6, and 0.59 respectively.The AUC of logistic regression in the training set, the test set, and the validation data set were 0.77, 0.78, and 0.8 respectively. The diagnostic model built by logistic regression was the best.

ConclusionWe had used artificial intelligence methods developed and externally validated the diagnostic model of in-hospital mortality in acute STEMI patients.

We registered this study with WHO International Clinical Trials Registry Platform (ICTRP) (registration number: ChiCTR1900027129; registered date: 1 November 2019). Hyperactive immature state and differential CXCR2 expression of neutrophils in severe COVID-19 Neutrophils are vital in defence against pathogens but excessive neutrophil activity can lead to tissue damage and promote acute respiratory distress syndrome (ARDS). COVID-19 is associated with systemic expansion of immature neutrophils but the functional consequences of this shift to immaturity are not understood. We used flow cytometry to investigate activity and phenotypic diversity of circulating neutrophils in COVID-19. First, we demonstrate hyperactivation of immature CD10- subpopulations in severe disease, with elevated degranulation of secondary granule markers. Partially activated immature neutrophils are detectable three months post symptom onset, indication long term myeloid dysregulation in convalescent COVID-19 patients. Second, we demonstrate that neutrophils from moderately ill patients downregulate the chemokine receptor CXCR2, while neutrophils from severely ill individuals failed to do so, suggesting altered ability for organ trafficking. CD10- and CXCR2hi neutrophil subpopulations were enriched in severe disease and may represent biomarkers for early identification of individuals at high risk of progressing to severe COVID-19. Stability of the stroke code during the COVID-19 pandemic in the region of Madrid: a retrospective cohort study Acute Stroke (AS) is the most common time-dependent disease attended in the Emergency Medicine Service (EMS) of Madrid (SUMMA 112). Community of Madrid has been one of the most affected regions in Spain by the coronavirus disease 2019 (COVID19) pandemic. A significant reduction in AS hospital admissions has been reported during the COVID-19 pandemic compared to the same period one year before. As international clinical practice guidelines support those patients with suspected acute stroke should be accessed via EMS, it is important to know whether the pandemic has jeopardized urgent pre-hospital stroke care, the first medical contact for most patients. We aimed to examine the impact of the COVID-19 in stroke codes (SC) in our EMS among three periods of time: the COVID-19 period, the same period the year before, and the 2019-2020 seasonal influenza period. Methods: We compared the SC frequency among the periods with high cumulative infection rate (above the median of the series) of the first wave of COVID-19, seasonal influenza, and also with the same period of the year before. Results: 1,130 SC were attended during the three periods. No significant reduction in SC was found during the COVID-19 pandemic. The reduction of hospital admissions might be attributable to patients attending the hospital by their means. The maximum SC workload seen during seasonal influenza has not been reached during the pandemic. We detected a non-significant deviation from the SC protocol, with a slight increase in hospitals transfers to hospitals without stroke units. The Preventive Treatment of Migraine with Low-Dose naltrexone and acetaminophen Combination: Findings of a Small, Randomized, Double-Blind, and Placebo-Controlled Clinical Trial with an Open-Label Extension for None-Responders We tested a low-dose naltrexone and acetaminophen combination for episodic migraine prevention. We randomly assigned patients to naltrexone and acetaminophen combination (n=6) or placebo (n=6) for a 12-week double-blind treatment. Non-responders continued into open-label treatment with naltrexone and acetaminophen combination (n=5) for additional 12 weeks. Patients were adults who experienced 5 to 17 (average 9.7) migraine days at baseline. The primary endpoint was the mean change in the monthly migraine days during the last 4 weeks of the double-blind treatment period. The key secondary endpoint was the mean change in the monthly migraine days from the 4-week double-blind follow-up (2nd baseline) to the last 4 weeks of the open-label treatment period.

The magnitude of the treatment effect for the naltrexone and acetaminophen combination observed in the double-blind period was 2.2 fewer monthly migraine days than placebo (p=0.43). Four out of 6 (66.7%) naltrexone and acetaminophen-treated patients experienced 75% reduction in migraine days compared to 1 out of 6 (16.7%) placebo-treated patients (p=0.09).

In the open-label phase, treatment with the naltrexone and acetaminophen combination (n=5) led to 8.2 fewer mean monthly migraine days (from 11.8 to 3.6), representing 69.5% improvement (p=0.03), and 100% of the patients experienced a 50% reduction in monthly migraine days. Adverse events were mild to moderate and transient, included dry mouth, fatigue, sedation, nausea, and feeling jittery.

We postulate that naltrexones toll-like receptor (TLR4) antagonism properties prevent pro-inflammatory cytokines production in the trigeminal ganglion averting "overactive nerves" (laymans term) and migraine. Although this trial used low-dose naltrexone (defined as 1 - 5 mg/day), in future phase 3 studies we will test a range of naltrexone and acetaminophen combination doses. Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs BackgroundPalliative care (PC) has demonstrated benefits for life-limiting illnesses. Cancer patients have mainly accessed these services, but there is growing consensus about the importance of promoting access for patients with non-malignant disease. Bad survival prognosis and patients frailty are usual dimensions to decide PC inclusion.

ObjectivesThe main aim of this work is to design and evaluate three quantitative models based on machine learning approaches to predict frailty and mortality on older patients in the context of supporting PC decision making: one-year mortality, survival regression and one-year frailty classification.

MethodsThe dataset used in this study is composed of 39,310 hospital admissions for 19,753 older patients (age >= 65) from January 1st, 2011 to December 30th, 2018. All prediction models were based on Gradient Boosting Machines. From the initial pool of variables at hospital admission, 20 were selected by a recursive feature elimination algorithm based on the random forests GINI importance criterion. Besides, we run an independent grid search to find the best hyperparameters in each model. The evaluation was performed by 10-fold cross-validation and area under the receiver operating characteristic curve and mean absolute error were reported. The Cox proportional-hazards model was used to compare our proposed approach with classical survival methods.

ResultsThe one-year mortality model achieved an AUC ROC of 0.87 {+/-} 0.01; the mortality regression model achieved an MAE of 329.97 {+/-} 5.24 days. The one-year frailty classification reported an AUC ROC of 0.9 {+/-} 0.01. The Spearmans correlation between the admission frailty index and the survival time was -0.1, while the point-biserial correlation between one-year frailty index and survival time was -0.16.

ConclusionsOne-year mortality model performance is at a state-of-the-art level. Frailty Index used in this study behaves coherently with other works in the literature. One-year frailty classifier demonstrated that frailty status within the year could be predicted accurately. To our knowledge, this is the first study predicting one-year frailty status based on a frailty index. We found mortality and frailty as two weakly correlated and complementary PC needs assessment criteria. Predictive models are available online at http://demoiapc.upv.es. Serum Vitamin D levels are associated with increased COVID-19 severity and mortality independent of whole-body and visceral adiposity INTRODUCTIONCoronavirus disease (COVID-19) is a global pandemic. Vitamin D deficiency has been associated with susceptibility to infectious disease. In this study, the association between COVID-19 outcomes and vitamin D levels in patients attending a COVID-19 reference center in Mexico City are examined.

METHODSConsecutive patients with confirmed COVID-19 were evaluated. All patients underwent clinical evaluation and follow-up, laboratory measurements and a thoracic computerized tomography, including the measurement of epicardial fat thickness. Low vitamin D was defined as levels <20ng/mL (<50nmol/L) and deficient Vitamin D as a level [&le;]12ng/mL (<30nmol/L)

RESULTSOf the 551 patients included, low vitamin D levels were present in 45.6% and deficient levels in 10.9%. Deficient Vitamin D levels were associated with mortality (HR 2.11, 95%CI 1.24-3.58, p=0.006) but not with critical COVID-19, adjusted for age, sex, body-mass index and epicardial fat. Using model-based causal mediation analyses the increased risk of COVID-19 mortality conferred by low vitamin D levels was partly mediated by its effect on D-dimer and cardiac ultrasensitive troponins. Notably, increased risk of COVID-19 mortality conferred by low vitamin D levels was independent of BMI and epicardial fat.

CONCLUSIONVitamin D deficiency ([&le;]12ng/mL or <30nmol/L), is independently associated with COVID-19 mortality after adjustment for visceral fat (epicardial fat thickness). Low vitamin D may contribute to a pro-inflammatory and pro-thrombotic state, increasing the risk for adverse COVID-19 outcomes. Covid-19 Associated Hepatitis in children (CAH-C) during the second wave of SARS-CoV-2 infections in Central India: Is it a complication or transient phenomenon. Objective: While pediatric population has largely remained free of severe COVID-19, in some cases SARS-CoV-2 infection has been associated with complications like Multiple Inflammatory Syndrome in children (MIS-C). We mention another unique presentation subsequent to asymptomatic infection of SARS-CoV-2, a unique form of hepatitis designated by us as COVID-19 Associated Hepatitis in Children (CAH-C). The contrasting clinical presentations, temporal association and viral parameters of CAH-C cases, to the MIS-C cases are presented here. Methods: As a retrospective and follow-up observational study we reviewed all children testing positive for SARS-CoV-2 during study period. Children presenting with sudden onset of hepatitis, elevated transaminases, non-obstructive jaundice, lacking marked inflammatory responses and without evidence of (a) other known causes of acute hepatitis or previous underlying liver disease (b) multi-system involvement were classified as CAH-C, are described here. Results: Among 475 children who tested positive, 47 patients presented with hepatitis, 37 patients who had features of CAH-C, having symptoms of hepatitis only, with un-elevated inflammatory markers and uneventful recovery following supportive treatment. Whereas remaining 10 MIS-C hepatitis had protracted illness, multiple system involvement, required admission to critical care, and had mortality of 30%. Conclusion: With the emergence of newer variants of concern (VOC) including the Delta variant which predominated the second wave of infections in India and has now spread to more than 142 countries with changing presentations, CAH-C might be one of them. Cases of such new entities need to be identified early and differentiated from other emerging syndromes in children during the ongoing pandemic for preventing adversities by timely intervention. The effect of D-cycloserine on brain processing of breathlessness over pulmonary rehabilitation - an experimental medicine study BackgroundPulmonary rehabilitation is the best treatment for chronic breathlessness in COPD but there remains an unmet need to improve efficacy. Pulmonary rehabilitation has strong parallels with exposure-based cognitive behavioural therapies (CBT), both clinically and in terms of brain activity patterns. The partial NMDA-receptor agonist, D-cycloserine has shown promising results in enhancing efficacy of CBT, thus we hypothesised that it would similarly augment the effects of pulmonary rehabilitation in the brain. Positive findings would support further development in phase 3 clinical trials.

Methods72 participants with mild-to-moderate COPD were recruited to a double-blind pre-registered (ID: NCT01985750) experimental medicine study running parallel to a pulmonary rehabilitation course. Participants were randomised to 250mg D-cycloserine or placebo, administered immediately prior to the first four sessions of pulmonary rehabilitation. Primary outcome measures were differences between D-cycloserine and placebo in brain activity in the anterior insula, posterior insula, anterior cingulate cortices, amygdala and hippocampus following completion of pulmonary rehabilitation. Secondary outcomes included the same measures at an intermediate time point and voxel-wise difference across wider brain regions.

ResultsNo difference between D-cycloserine and placebo groups was observed across the primary or secondary outcome measures. Questionnaire and measures of respiratory function showed no group difference.

ConclusionsThis is the first study testing brain-active drugs in pulmonary rehabilitation. Rigorous trial methodology and validated surrogate end-points maximised statistical power. Although increasing evidence supports therapeutic modulation of NMDA pathways to treat symptoms, we conclude that a phase 3 clinical trial of D-cycloserine would not be worthwhile.

Key MessagesO_ST_ABSWhat is the key question?C_ST_ABSDoes the partial NMDA-receptor agonist, D-cycloserine, augment the effects of pulmonary rehabilitation on breathlessness related brain activity?

What is the bottom line?Rigorous trial methodology and validated surrogate end-points revealed no effect of D-cycloserine on breathlessness related brain activity across pulmonary rehabilitation.

Why read on?This study highlights both the value of functional magnetic resonance imaging in "de-risking" expensive clinical trials and provides detailed investigation of brain-targeted points for pharmacological treatments of breathlessness. Statistical modeling for quality risk assessment of clinical trials: follow-up at the era of remote auditing BackgroundAs investigator site audits have largely been conducted remotely during the COVID-19 pandemic, remote quality monitoring has gained some momentum. To further facilitate the conduct of remote Quality Assurance (QA) activities for clinical trials, we developed new quality indicators, building on a previously published statistical modeling methodology.

MethodsWe modeled the risk of having an audit or inspection finding using historical audits and inspections data from 2011 - 2019. We used logistic regression to model finding risk for 4 clinical impact factor (CIF) categories: Safety Reporting, Data Integrity, Consent and Protecting Endpoints.

ResultsWe could identify 15 interpretable factors influencing audit finding risk of 4 out of 5 CIF categories. They can be used to realistically predict differences in risk between 25 and 43% for different sites which suffice to rank sites by audit and inspection finding risk.

ConclusionContinuous surveillance of the identified risk factors and resulting risk estimates could be used to complement remote QA strategies for clinical trials and help to manage audit targets and audit focus also in post-pandemic times. Chemosensory dysfunctions induced by COVID-19 can persist up to 7 months: A study of over 700 healthcare workers Several studies have revealed either self-reported chemosensory alterations in large groups or objective quantified chemosensory impairments in smaller populations of patients diagnosed with COVID-19. However, due to the great variability in published results regarding COVID-19-induced chemosensory impairments and their follow-up, prognosis for chemosensory functions in patients with such complaints remains unclear. Our objective is to describe the various chemosensory alterations associated with COVID-19 and their prevalence and evolution after infection. A cross-sectional study of 704 healthcare workers with a RT-PCR confirmed SARS-CoV-2 infection between 28/2/2020 and 14/6/2020 was conducted 3 to 7 months after onset of symptoms. Data were collected with an online questionnaire. Outcomes included differences in reported chemosensory self-assessment of olfactory, gustatory, and trigeminal functions across time points and Chemosensory Perception Test scores from an easy-to-use at-home self-administered chemosensory test. Among the 704 participants, 593 (84.2%) were women, the mean (SD) age was 42 (12) years, and the questionnaire was answered on average 4.8 (0.8) months after COVID-19. During COVID-19, a decrease in olfactory, gustatory, and trigeminal sensitivities were reported by 81.3%, 81.5% and 48.0% respectively. Three to seven months later, reduced sensitivity was still reported by 52.0%, 41.9% and 23.3% respectively. Chemosensory Perception Test scores indicate that 19.5% of participants had objective olfactory impairment. These data suggest a significant proportion of COVID-19 cases have persistent chemosensory impairments at 3 to 7 months after their infection but the majority of those who had completely lost their olfactory, gustatory, and trigeminal sensitivity have improved. USING PHYLOGENETICS TO INFER HIV-1 TRANSMISSION DIRECTION BETWEEN KNOWN TRANSMISSION PAIRS Inferring the transmission direction between linked individuals living with HIV provides unparalleled power to understand the epidemiology that determines transmission. Phylogenetic ancestral state reconstruction approaches infer the transmission direction by identifying the individual in whom the most recent common ancestor of the virus populations originated. However, these methods vary in their accuracy but it is unclear why. To evaluate the performance of phylogenetic ancestral state reconstruction, we inferred the transmission direction for 112 HIV transmission pairs where transmission direction was known and detailed additional information was available. We then fit a statistical model to evaluate the extent to which epidemiological, sampling, genetic and phylogenetic factors influenced the outcome of the inference. We repeated the analysis under real-life conditions with only routinely-collected data. We found that the inference of transmission direction depends principally on the topology class and branch length characteristics of the phylogeny. Under real-life conditions, the probability of identifying the correct transmission direction increases from 52%--when a monophyletic-monophyletic or paraphyletic-polyphyletic tree topology is observed, when the sample size in both partners is small and when the tip closest to the root does not agree with the state at the root--to 93% when a paraphyletic-monophyletic topology is observed, when the sample size is large and when the tip closest to the root agrees with root state. Our results suggest that discordance between previous studies in inferring the transmission direction can be explained by differences in key phylogenetic properties that arise due to different evolutionary, epidemiological and sampling processes.

Significance StatementIdentifying the direction of infectious disease transmission between individuals provides unparalleled power to understand infectious disease epidemiology. With epidemiological and clinical information typically unable to distinguish the direction, phylogenetic analysis of pathogen sequence data is an alternative approach. However, when these phylogenetic methods have been implemented, their accuracy is highly variable, and the reasons for this discordance is unknown. Here we analyse sequence data from over 100 pairs of individuals for whom both the direction of transmission of HIV is known and detailed epidemiological and sampling information is available. We find that easily quantifiable phylogenetic characteristics discriminate whether a phylogenetically-inferred transmission direction is correct. Our analysis highlights that phylogenetic approaches are unsuitable for individual-level analysis such as forensic investigations. Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level BackgroundForecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources.

MethodsWe made weekly forecasts of daily COVID-19 hospital admissions for National Health Service (NHS) Trusts in England between August 2020 and April 2021 using three disease-agnostic forecasting models: a mean ensemble of autoregressive time series models, a linear regression model with 7-day-lagged local cases as a predictor, and a scaled convolution of local cases and a delay distribution. We compared their point and probabilistic accuracy to a mean-ensemble of them all, and to a simple baseline model of no change from the last day of admissions. We measured predictive performance using the Weighted Interval Score (WIS) and considered how this changed in different scenarios (the length of the predictive horizon, the date on which the forecast was made, and by location), as well as how much admissions forecasts improved when future cases were known.

ResultsAll models outperformed the baseline in the majority of scenarios. Forecasting accuracy varied by forecast date and location, depending on the trajectory of the outbreak, and all individual models had instances where they were the top- or bottom-ranked model. Forecasts produced by the mean-ensemble were both the most accurate and most consistently accurate forecasts amongst all the models considered. Forecasting accuracy was improved when using future observed, rather than forecast, cases, especially at longer forecast horizons.

ConclusionsAssuming no change in current admissions is rarely better than including at least a trend. Using confirmed COVID-19 cases as a predictor can improve admissions forecasts in some scenarios, but this is variable and depends on the ability to make consistently good case forecasts. However, ensemble forecasts can make forecasts that make consistently more accurate forecasts across time and locations. Given minimal requirements on data and computation, our admissions forecasting ensemble could be used to anticipate healthcare needs in future epidemic or pandemic settings. Macular vascular complexity analysis of diabetes mellitus by swept-source optical coherence tomographic angiography PurposeTo evaluate the associations of retinal vascular complexity features, including fractal dimension (FD) and blood vessel tortuosity (BVT), with the severity of diabetic retinopathy (DR) by using noninvasive optical coherence tomographic angiography (OCTA).

MethodsThis prospective cross-sectional study recruited ocular-treatment-naive patients with type 2 diabetes mellitus (DM) registered in the community of Guangzhou, China. OCTA was used to obtain the measurements of FD and BVT in the superficial capillary plexus (SCP) and the deep capillary plexus (DCP). Univariate and multivariate linear regression was used to analyse the correlation of FD and BVT in different layers with DR severity.

ResultsA total of 1282 patients with DM (1282 eyes), with a mean age of 64.2{+/-}7.8 years, were included. FD in the DCP decreased and BVT in the DCP increased in DR patients compared to non-DR patients, even after adjusting for confounding factors (P< 0.05). Trend analysis showed a significant decrease in the FD values as the DR progressed, while the BVT progressively increased with worsening DR severity (P< 0.01). The FD in DCP had a statistically significant positive correlation with FD in SCP and a negative correlation with BVT in SCP and BVT in DCP in all of the participants, including the non-DR group, moderate DR group and severe DR group (P< 0.01).

ConclusionFD and BVT determined using OCTA might be useful parameters for objectively distinguishing DR from non-DR and indicating DR progression. Airway management, procedural data, and mortality records of patients undergoing surgery for mucormycosis associated with coronavirus disease (COVID-19) In India, the second wave of coronavirus disease (COVID -19) was associated with a distinct surge in cases of invasive fungal infection with mucormycosis. This disease was seen typically in the sinonasal form in COVID-19 patients. Uncontrolled diabetes, steroid use in COVID-19 treatment, etc. were some of the postulated risk factors for the association of COVID 19 and Mucormycosis. The management plan of these cases included surgical debridement, systemic antifungal therapy, sugar control, and management of antifungal related systemic adverse effects. In this retrospective case record review, we aimed to evaluate the airway management plan, demographics, and overall outcomes in patients undergoing surgical resection for COVID-19 associated mucormycosis. Forty-one (71.9 %) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) had a diagnosis of rhino-orbital mucormycosis, and 2 patients (3.5%) were diagnosed with palatal mucormycosis. Total 44 (77.19 %) patients had co-morbidities. The most common co-morbidity was Diabetes Mellitus 42 (73.6%), followed by hypertension 21 (36.84%) and Acute kidney injury 14 (28.07%). We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 out of 57 patients. In our study, mortality occurred in 7 (12.28 %) patients. The median mortality time was 60 (range, 27-74) days. The median time to hospital discharge was 53.5 (range,10-85) days. Managing COVID-19 on its own is challenging and additional mucormycosis can lead to increased morbidity and mortality. Despite challenges and risks, timely and meticulous interventions can reduce complications. Grey and white matter micro-structure is associated with polygenic risk for schizophrenia BackgroundRecent discovery of approximately 270 common genetic variants associated with schizophrenia has enabled polygenic risk scores (PRS) to be measured in the population. We hypothesized that normal variation in PRS would be associated with magnetic resonance imaging (MRI) phenotypes of brain morphometry and tissue composition.

MethodsWe used the largest extant genome-wide association dataset (N = 69,369 cases and N = 236,642 healthy controls) to measure PRS for schizophrenia in a large sample of adults from the UK Biobank (Nmax = 29,878) who had multiple micro- and macro-structural MRI metrics measured at each of 180 cortical areas, seven subcortical structures, and 15 major white matter tracts. Linear mixed effect models were used to investigate associations between PRS and brain structure at global and regional scales, controlled for multiple comparisons.

ResultsPolygenic risk was significantly associated with reduced neurite density index (NDI) at global brain scale, at 149 cortical regions, five subcortical structures and 14 white matter tracts. Other micro-structural parameters, e.g., fractional anisotropy, that were correlated with NDI were also significantly associated with PRS. Genetic effects on multiple MRI phenotypes were co-located in temporal, cingulate and prefrontal cortical areas, insula, and hippocampus. Post-hoc bidirectional Mendelian randomization analyses provided preliminary evidence in support of a causal relationship between (reduced) thalamic NDI and (increased) risk of schizophrenia.

ConclusionsRisk-related reduction in NDI is plausibly indicative of reduced density of myelinated axons and dendritic arborization in large-scale cortico-subcortical networks. Cortical, subcortical and white matter micro-structure may be linked to the genetic mechanisms of schizophrenia. Generalized Prediction of Hemodynamic Shock in Intensive Care Units Early prediction of hemodynamic shock in the ICU can save lives. Several studies have leveraged a combination of vitals, lab investigations, and clinical data to construct early warning systems for shock. However, these have a limited potential of generalization to diverse settings due to reliance on non-real-time data. Monitoring data from vitals can provide an early real-time prediction of Hemodynamic shock which can precede the clinical diagnosis to guide early therapy decisions. Generalization across age and geographical context is an unaddressed challenge. In this retrospective observational study, we built real-time shock prediction models generalized across age groups (adult and pediatric), ICU-types, and geographies. We trained, validated, and tested a shock prediction model on the publicly available eICU dataset on 208 ICUs across the United States. Data from 156 hospitals passed the eligibility criteria for cohort building. These were split hospital-wise in a five-fold training-validation-test set. External validation of the model was done on a pediatric ICU in New Delhi and MIMIC-III database with more than 0.23 million and one million patient-hours vitals data, respectively. Our models identified 92% of all the shock events more than 8 hours in advance with AUROC of 86 %(SD= 1.4) and AUPRC of 93% (SD =1.2) on the eICU testing set. An AUROC of 87 % (SD =1.8), AUPRC 92 % (SD=1.6) were obtained in external validation on the MIMIC-III cohort. The New Delhi Pediatric SafeICU data achieved an AUROC of 87 % (SD =4) AUPRC 91% (SD=3), despite being completely different geography and age group. In this first, we demonstrate a generalizable model for predicting shock, and algorithms are publicly available as a pre-configured Docker environment at https://github.com/tavlab-iiitd/ShoQPred. 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). Early prediction of preeclampsia in pregnancy with circulating cell-free RNA Liquid biopsies that measure circulating cell-free RNA (cfRNA) offer an unprecedented opportunity to noninvasively study the development of pregnancy-related complications and to bridge gaps in clinical care. Here, we used 404 blood samples from 199 pregnant mothers to identify and validate cfRNA transcriptomic changes that are associated with preeclampsia (PE), a multi-organ syndrome which is the second largest cause of maternal death globally. We find that changes in cfRNA gene expression between normotensive (NT) and preeclamptic mothers are striking and stable early in gestation, well before the onset of symptoms. These changes are enriched for genes specific to neuromuscular, endothelial, and immune cell types and tissues that reflect important aspects of PE physiology and suggest new hypotheses for disease progression. This enabled identification and independent validation of a panel of 18 genes whose measurement between 5-16 weeks of gestation can form the basis of a liquid biopsy test that would identify mothers at risk of PE well before the clinical symptoms manifest themselves. Finally, we demonstrate that cfRNA changes reflect the multifactorial nature of PE and provide a means to non-invasively monitor maternal organ health. Tests based on these observations could help predict and manage who is at risk for PE, an important and until now unachieved objective for obstetric care. The effects of modifiable maternal pregnancy exposures on offspring molar-incisor hypomineralisation: A negative control study ObjectivesO_LITo explore the associations between modifiable maternal pregnancy exposures: pre-pregnancy body mass index (BMI), pregnancy smoking and alcohol consumption with offspring molar-incisor hypomineralisation (MIH).
C_LIO_LITo explore for the presence of residual confounding using negative control analyses.
C_LI

MethodsThis study used data from Avon Longitudinal Study of Parents and Children (ALSPAC), a UK prospective birth cohort. We defined offspring MIH using prospectively collected questionnaire data. We used logistic regression to explore confounder adjusted associations between maternal pre-pregnancy BMI and smoking and alcohol consumption during pregnancy with MIH. We included negative control exposure (paternal BMI, smoking and alcohol around the time of pregnancy) and outcome (offspring dental trauma) analyses to explore for the presence of residual confounding.

Results5536 mother/offspring pairs were included (297 MIH cases [5.4%]). We found a positive association between maternal mean BMI and offspring MIH (OR per 1-kg/m2 difference in maternal BMI: 1.04, 95% CI: 1.00, 1.08). In subsequent analyses, we found evidence that this effect was non-linear and being driven by women in the highest BMI quintiles. In negative control analyses, we found no evidence of association between paternal BMI and offspring MIH (OR: 0.94, 95% CI: 0.89, 1.00) and maternal BMI and offspring dental trauma (OR: 0.99, 95% CI: 0.96, 1.02). There was no clear evidence of an association for maternal pregnancy smoking (OR: 0.76, 95%CI: 0.46, 1.22) and alcohol consumption (OR: 0.79, 95% CI: 0.56, 1.21) with offspring MIH with results imprecisely estimated.

ConclusionIn summary we found evidence of a possible intrauterine effect of high maternal pre-pregnancy BMI on offspring MIH. We did not find robust evidence for an intrauterine effect of maternal pregnancy smoking or alcohol consumption on offspring MIH. Our findings provide further support for women of reproductive age to maintain a healthy weight. Future studies are warranted to explore possible mechanisms on how the pregnancy environment may relate to offspring MIH. Deceased donor kidney degradomics indicates cytoskeletal proteolytic alterations impacting post-transplant function. BackgroundIn brain death, cerebral injury contributes to systemic biological dysregulation, causing significant cellular stress in donor kidneys that adversely impacts the quality of grafts. Here, we hypothesized that DBD kidneys may undergo proteolytic processes that renders grafts susceptible to post-transplant dysfunction.

Material & MethodsUsing mass spectrometry and immunoblotting analyses, we profiled degradation patterns of cytoskeletal proteins in deceased (n=55) and living (n=10) donor kidneys.

ResultsWe found that in DBD kidneys, key podocyte cytoskeletal proteins had been proteolytically cleaved. Generated degradation profiles were not associated to donor related demographic and clinical factors but were associated to suboptimal post-transplant function. Strikingly, -actinin -4 and Talin-1 degradation profiles were not observed in circulatory-death or living-donor kidneys. As Talin-1 is a specific proteolytic target of Calpain-1, we investigated a potential trigger of Calpain activation and Talin-1 degradation using ex-vivo precision-cut human kidney slices and in-vitro immortalised human podocytes. Notably, we found that Transforming-Growth Factor-{beta} (TGF-{beta}) activated Calpain-1 and proteolytically cleaved Talin-1 to generate distinct peptide fragments. These peptide fragments were of similar size and matched the degradation patterns observed in DBD kidneys. Talin-1 degradation was prevented in vitro by Calpain-1 inhibition.

ConclusionsHere, we provide initial evidence that DBD kidneys are susceptible to cytoskeletal protein degradation that impacts posttransplant kidney function. Subsequent studies should aim to further investigate the link between brain death and activation of proteolytic pathways exploring new therapeutic opportunities. Ultra-rare and common genetic variant analysis converge to implicate negative selection and neuronal processes in the aetiology of schizophrenia Both common and rare genetic variants (minor allele frequency > 1% and < 0.1% respectively) have been implicated in the aetiology of schizophrenia. In this study, we integrate single-cell gene expression data with publicly available Genome-Wide Association Study (GWAS) and exome sequenced data in order to investigate in parallel, the enrichment of common and (ultra-)rare variants related to schizophrenia in several functionally relevant gene-sets. Four types of gene-sets were constructed 1) protein-truncating variant (PTV)-intolerant (PI) genes 2) genes expressed in brain cell types and neurons ascertained from mouse and human brain tissue 3) genes defined by synaptic function and location and 4) intersection genes, i.e., PI genes that are expressed in the human and mouse brain cell gene-sets. We show that common as well as ultra-rare schizophrenia-associated variants are overrepresented in PI genes, in excitatory neurons from the prefrontal cortex and hippocampus, medium spiny neurons, and genes enriched for synaptic processes. We also observed stronger enrichment in the intersection genes. Our findings suggest that across the allele frequency spectrum, genes and genetic variants likely to be under stringent selection, and those expressed in particular brain cell types, are involved in the same biological pathways influencing the risk for schizophrenia. Short Practical Regimen of Acupuncture for Melasma: A Prospective Cohort Study in a Tertiary Hospital in Thailand BackgroundMelasma is a common skin pigmentation disorder. Acupuncture shows benefits for patients with melasma, although no standardized method or optimal number of sessions have been determined.

ObjectiveTo comparatively assess clinical outcomes of melasma between five vs ten standard acupuncture sessions.

MethodsWe performed a prospective observational cohort study in all melasma patients at the Acupuncture Clinic, King Chulalongkorn Memorial Hospital, Bangkok, Thailand. All patients were treated with standard acupuncture procedure twice a week and were evaluated after the fifth and the tenth sessions of acupuncture, with a follow-up one week after the last session. Participants were divided into two treatment groups: Groups A and B received five and ten acupuncture sessions respectively. Melasma outcomes were assessed by using the Melanin Index (MI), Melasma Area and Severity Index (MASI), patient-reported improvement scores and acupuncture-related adverse events.

ResultsOf 113 participants, 67 received five sessions of acupuncture treatment while 39 received ten sessions. 7 participants did not finish treatment. After five sessions of acupuncture in Group A, the mean MI decreased by 28.7 (95%CI -38.5 to -18.8), whereas the median MASI decreased by 3.4 (-6.9, -1.2) points. After ten sessions of acupuncture in Group B, the mean MI decreased by 31.3 (95%CI -45.0 to -17.6), whereas the median MASI decreased by 5.4 (-9.9, - 3.0) points. The first five sessions of acupuncture had a higher effect on the change in magnitude than the last five sessions, although there was no statistically significant difference. However, ten-session of acupuncture, had not reached the peak benefit on melasma yet. Further studies should be done with a higher number of sessions to determine the optimal rounds of treatment. Twenty-nine participants reported minor side effects, mostly consisting of persistent pain and small hematoma. Group B had RR of having adverse events 1.8 times (95% CI 1.0-3.4) compared to group A.

ConclusionAcupuncture has a potential dose-response effect on clinical and patient-reported melasma outcomes with minor side effects.