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This article presents a framework for semi-automated building damage assessment due to earthquakes from remote-sensing data and other supplementary datasets, while also leveraging recent advances in machine-learning algorithms. The framework integrates high-resolution building inventory data with earthquake ground shaking intensity maps and surface-level changes detected by comparing pre- and post-event InSAR (interferometric synthetic aperture radar) images. We demonstrate the use of ensemble models in a machine-learning approach to classify the damage state of buildings in the area affected by an earthquake. Both multi-class and binary damage classification are attempted for four recent earthquakes, and we compare the predicted damage labels with ground truth damage grade labels reported in field surveys. For three out of the four earthquakes studied, the model is able to identify over 50 % or nearly half of the damaged buildings successfully when using binary classification. Multi-class damage grade classification using InSAR data has rarely been attempted previously, and the case studies presented in this report represent one of the first such attempts using InSAR data.

Aim: To evaluate the clinical efficacy of subgingivally delivered SMV and Placebo gel and compare in the treatment of stage II periodontitis when used as an adjunct to SRP and their antimicrobial effect on the Porphyromonas gingivalis bacteria. Materials & Methods: In a split mouth study design, 10 systemically healthy patients with stage II periodontitis were included in this study based on the inclusion and exclusion criteria. Two sites with deepest pockets were selected. Plaque samples were collected from these pockets at baseline followed by full mouth scaling and root planning, In Group I 1,2% SMV gel and in Group II Placebo gel was placed in the subgingival pockets. Microbiological analysis for Colony Forming Units of P.g was done at baseline after 3 months, Clinical parameters (GI, PI, PD, CAL, mSBI) were evaluated at baseline (before SRP), 1 month and 3 months. Result: Both the groups showed significant reduction in GI, PI, PD, CAL, mSBI and CFU of Pg but Group I showed more significant reduction than Group II.

Infrastructures are critical for the functioning of society. Due to globalization, damages between different components of infrastructure systems can cross international boundaries, resulting in broad economic and social impacts. Hence, it is fundamental to develop powerful tools for the assessment of infrastructure risk, considering a wide spectrum of uncertainties. Past studies covering infrastructure risk assessment are limited to a few countries, partly because for assessing the infrastructure risk, issues due to the complexity of the systems, like paucity and heterogeneity of the data and methods, the consideration of dependencies between components and systems, modeling of ground shaking in terms of scenario and probabilistic approach, taking into account site effects, spatial variability and cross correlation of ground motion at the urban scale, as well as consideration of risk metrics tailored to infrastructure, still remain partially or not properly answered. Moreover, the presently available infrastructure risk assessment tools are not sufficiently illustrative, user-friendly, and comprehensive to meet actual needs. To this end, the paper making an overview of these issues proposes a comprehensive approach that leverages the main strength of existing infrastructure risk methodologies, integrating them into a powerful open-source tool and providing common platform from hazard to risk analysis that will serve for global and easy usage. The methodology and its implementation are illustrated through a test-bed study of the water supply network of the city of Thessaloniki in Greece, considering an Mw 6.5 scenario of the 1978 Thessaloniki earthquake and an event based probabilistic approach and, simultaneously evaluating the sensitivity of cross spatial correlation.

IntroductionWe evaluated the long-term outcomes of recurrent glomerulonephritis (RGN) using clinical, histopathological, and demographic predictors.MethodsA retrospective cohort study of kidney transplant recipients (KTR) in two renal centers between 2005 and 2020. Clinical and native kidney histological data were analyzed. The risk factors and outcomes of each primary glomerulonephritis subtype were assessed using Cox methods.Result336 recipients with primary glomerulonephritis were analyzed. RGN was diagnosed in 17%, 20%, 25%, and 13% of recipients with IgA nephropathy (IgAN), focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN) and membranoproliferative glomerulonephritis (MPGN), respectively. Median time to recurrence was shortest in FSGS (.6 years IQR .2-2.9) and longest in MN (6.3 years IQR 3.3-8.0) whereas time to graft loss after diagnosis was shortest in MPGN (.3 years IQR .1-1.7) and longest in IgAN (2.9 year IQR 1.3-4.3). Recipients with recurrent IgAN were likely to be younger, have higher proteinuria at diagnosis, receive living donor allografts, receive cyclosporine treatment, have a history of acute rejection, and have segmental sclerosis in native glomeruli. Younger age of the donors, higher proteinuria at diagnosis, alemtuzumab, proteinuria within the first 12 months, acute rejection, low baseline eGFR, mesangial proliferation, and IgG and IgA deposits were associated with FSGS recurrence. MPGN recurrence was predicted by lower BMI at transplantation, and crescentic native disease. Death-censored graft survival at 5-, 10-, and 15-years was 83%, 51%, and 29% in the RGN group and 95%, 93%, and 84%, respectively in the non-RGN group. Over 15 years, recipients with RGN are nine times more likely than those without RGN to lose their grafts, regardless of donor type, acute rejection, and baseline eGFR. Transplant recipients of related donor allograft were not more likely to have recurrent GN than non-related donors.

Best practices for left ventricular assist devices (LVADs) deactivation at end-of-life (EOL) have yet to be elucidated. We conducted a single-institution retrospective review of patients who died following LVAD deactivation between January 2017 and March 2020. Data were obtained from institutional databases and electronic health record and were analyzed using descriptive statistics. Fifty-eight patients (70% male, 70% African American, median age 62 years) were categorized by implant strategy: bridge therapy (BT, N = 22, 38%) or destination therapy (DT, N = 36, 62%). Clinical events leading to deactivation were categorized either acute ( e.g. , stroke [ N = 31, 53%]), gradual decline ( N = 12, 21%), or complications during index hospitalization ( N = 15, 26%). Implant strategy was not associated with clinical trajectory leading to EOL ( p = 0.67), hospital unit of death ( p = 0.13), or use of mechanical ventilation ( p = 0.69) or renal replacement therapy ( p = 0.81) during terminal hospitalization. Overall time from admission to code status change was mean 27.0 days (SD 30.3 days). Compared with BT patients, DT experienced earlier do-not-resuscitate (DNR) orders ( p ≤ 0.01) and shorter survival post-deactivation ( p ≤ 0.01). Deactivations after gradual decline tended to occur outside ICUs, compared with acute events or index implant-related complications ( p = 0.04). Implant strategy was not associated with differences in EOL experience except regarding timing of DNR order and survival post-deactivation.

Background Members of racial and ethnic minority groups have been disproportionately impacted by coronavirus-2019 (COVID-19). The objective of the study is to describe associations between race and ethnicity on clinical outcomes such as need for mechanical ventilation and mortality. Methods Retrospective cohort study of patients with severe COVID-19 infection admitted within a large, not-for-profit healthcare system in the mid-Atlantic region between March and July, 2020. Patient demographic data and clinical outcomes were abstracted from the electronic health record. Logistic regressions were performed to estimate associations between race and ethnicity and the clinical outcomes. Results The study population (N = 2931) was stratified into 1 of 3 subgroups: non-Hispanic White (n = 466), non-Hispanic Black (n = 1611), and Hispanic (n = 654). The average age of White, Black, and Hispanic patients was 69 ± 17.06, 64 ± 15.9, and 50 ± 15.53 years old, respectively ( P Conclusion Our analysis demonstrated that Hispanic patients were more likely require mechanical ventilation but had lower mortality when compared to White patients, with lower average age likely mediating this association. These findings emphasize the importance of outreach efforts to communities of color to increase prevention measures and vaccination uptake to reduce infection with COVID-19.

Background Many patients with American College of Cardiology/American Heart Association Stage D (advanced) heart failure are discharged home on chronic intravenous inotropic support (CIIS) as bridge to surgical therapy or as palliative therapy. This study analyzed the clinical trajectory of patients with advanced heart failure who were on home CIIS. Methods We conducted a single-institution, retrospective cohort study of patients on CIIS between 2010 and 2016 (n = 373), stratified by indication for initiation of inotropic support. Study outcomes were time from initiation of CIIS to cessation of therapy, time to death for patients who did not receive surgical therapy and rates of involvement with palliative care. Results Overall, patients received CIIS therapy for an average of 5.9 months (standard deviation [SD] 7.3). Patients on CIIS as palliative therapy died in an average of 6.2 months (SD 6.6) from the time of initiation of CIIS, and those on CIIS as bridge therapy who did not ultimately receive surgical therapy died after an average of 8.6 months (SD 9.3). Patients who received CIIS as bridge therapy were significantly less likely to receive palliative-care consultation than those on inotropes as palliative therapy, whether or not they underwent surgery. Conclusions In this large cohort of patients with advanced HF, patients who on CIIS as palliative therapy survived for 6.2 months, on average, with wide variation among patients. Patients who were on CIIS as bridge therapy but did not ultimately receive surgical therapy received less palliative care despite the high mortality rate in this subgroup.

The exposure model is a key component of a seismic risk model, which captures the spatial distribution of population and built assets along with their structural characteristics and valuation that are required for seismic risk assessment. Current and available exposure models for China have various limitations that make them less suitable for use in risk assessment, including low spatial resolution of building inventory and the limited identification of key structural characteristics. This study describes the development of a residential buildings’ township-level exposure model for mainland China, containing information about the geographical distribution, structural characteristics, age, ductility, number of stories, number of dwellings, average built-up area, and replacement cost at the township level. This exposure model is intended to be used for risk assessment and to support emergency planning, risk management, and decisions. The geographical distribution’s detailed analysis of the building typologies, heights, and construction vintage at the national, regional, and provincial levels is provided to better aid in understanding country exposure. The results indicate that based on the method, flow, and data from the 6th National Population Census of the People's Republic of China, we can generate key information used for seismic risk analysis, representing a significant step toward a better understanding of risk due to seismic hazards in mainland China.

Over 140,000 people in the United States have died as a result of infection with COVID-19. These patients have varying death experiences based on their location of death, the availability and utilization of various medical technologies, the amount of strain on the local health care system, the involvement of specialist palliative care (PC) teams, and access to essential medications to alleviate symptoms at the end of life. The objective of this report is to describe the death experiences of four patients cared for in an urban academic medical center who received very different degrees of medical interventions and to examine the interventions of our interdisciplinary PC team. We conclude that PC teams must adapt to this new landscape by creating best practices for ensuring adequate symptom control, modifying approaches for withdrawal of life-sustaining medical technologies, and gaining facility with communication through teleconferencing platforms to meet the challenge of alleviating suffering for people dying from COVID-19.

This study presents a comprehensive open probabilistic seismic risk model for India. The proposed model comprises a nationwide residential and non-residential building exposure model, a selection of analytical seismic vulnerability functions tailored for Indian building classes, and the open implementation of an existing probabilistic seismic hazard model for India. The vulnerability of the building exposure is combined with the seismic hazard using the stochastic (Monte Carlo) event-based calculator of the OpenQuake engine to estimate probabilistic seismic risk metrics such as average annual economic losses and the exceedance probability curves at the national, state, district, and subdistrict levels. The risk model and the underlying datasets, along with the risk metrics calculated at different scales, are intended to be used as tools to quantitatively assess the earthquake risk across India and also compare with other countries to develop risk-informed building design guidelines, for more careful land-use planning, to optimize earthquake insurance pricing, and to enhance general earthquake risk awareness and preparedness.

Probabilistic earthquake loss models are widely used in the (re)insurance industry to assess the seismic risk of portfolios of assets and to inform pricing mechanisms for (re)insurance contracts, as well as by international and national organizations with the remit to assess and reduce disaster risk. Such models include components characterizing the seismicity of the region, the ground motion intensity, the building inventory, and the vulnerability of the assets exposed to ground shaking. Each component is characterized by a large uncertainty, which can be classified as aleatory or epistemic. Modern seismic risk assessment models often neglect some sources of uncertainty, which can lead to biased loss estimates or to an underestimation of the existing uncertainty. This study focuses on exploring and quantifying the impact of a number of sources of uncertainties from each component of an earthquake loss model to the loss estimates. To this end, the residential exposure of Guatemala and Guatemala City were used as case studies. Moreover, a comparison of the predicted losses for an insured portfolio in the country between OpenQuake-engine and a vendor catastrophe platform was performed, assessing the potential application of OpenQuake in the (re)insurance industry. The findings from this study suggest that the uncertainty in the hazard component has the most significant effect on the loss estimates.

This article presents a framework for semi-automated building damage assessment due to earthquakes from remote sensing data and other supplementary datasets, while also leveraging recent advances in machine-learning algorithms. The framework integrates high-resolution building inventory data with earthquake ground shaking intensity maps and surface-level changes detected by comparing pre- and post-event InSAR (interferometric synthetic aperture radar) images. We demonstrate the use of ensemble models in a machine-learning approach to classify the damage state of buildings in the area affected by an earthquake. Both multi-class and binary damage classification are attempted for four recent earthquakes and we compare the predicted damage labels with ground truth damage grade labels reported in field surveys. For three out of the four earthquakes studied, the model is able to identify over fifty percent or nearly half of the damaged buildings successfully when using binary classification. Multi-class damage grade classification using InSAR data has rarely been attempted previously, and the case studies presented in this report represent one of the first such attempts using InSAR data.

The global prevalence of heart failure (HF) is increasing. Advancements in guideline-directed medical and device therapy have resulted in improved survival. Thus, there are more patients living - and living longer - with advanced HF. Only a small proportion of these patients are deemed appropriate for advanced surgical intervention (mechanical circulatory support or heart transplantation), and even if offered, some may decline such interventions if not aligned with their overall goals and values. Therefore, a growing number of patients with advanced HF receive chronic intravenous inotropic support (CIIS) for palliation of symptoms. Despite increased use, clinical evidence supporting use of palliative inotropes remains limited. However, available data suggest improvements in functional class, health-related quality of life (HRQoL) indicators, symptom burden, hemodynamic parameters, and possibly rehospitalization. While initial concerns regarding increased mortality have been assuaged in the modern era of guideline-directed medical therapy, palliative inotropes are certainly not without burden. Risks of infection and medication-related adverse effects, need for routine laboratory monitoring, frequent dressing changes, and presence of a reliable caregiver must be carefully considered prior to initiation. This review addresses pharmacology, guideline recommendations, benefits and burdens, considerations related to hospice and end-of-life care, and future directions of CIIS in advanced HF care.

Use of continuous intravenous inotropic support (CIIS) strictly as palliative therapy for patients with ACC/AHA Stage D (end-stage) Heart Failure (HF) has increased significantly. The harms of CIIS therapy may detract from its benefits. To describe benefits (improvement in NYHA functional class) and harms (infection, hospitalization, days-spent-in-hospital) of CIIS as palliative therapy. Methods: Retrospective analysis of patients with end-stage HF initiated on CIIS as palliative therapy at an urban, academic center in the United States between 2014-2016. Clinical outcomes were extracted, and data were analyzed using descriptive statistics. Seventy-five patients, 72% male, 69% African American/Black, with a mean age 64.5 years ( SD = 14.5) met study criteria. Mean duration of CIIS was 6.5 months ( SD = 7.7). Most patients (69.3%) experienced improvement in NYHA functional class from class IV to class III. Sixty-seven patients (89.3%) were hospitalized during their time on CIIS, with a mean of 2.7 hospitalizations per patient ( SD = 3.3). One-third of patients (n = 25) required at least one intensive care unit (ICU) admission while on CIIS therapy. Eleven patients (14.7%) experienced catheter-related blood stream infection. Patients spent an average of 20.6% ( SD = 22.8), approximately 40 days, of their time on CIIS admitted to the study institution. Patients on CIIS as palliative therapy report improvement in functional class, survive 6.5 months following initiation, but spend a significant number of days in the hospital. Prospective studies quantifying the symptomatic benefit and the direct and indirect harms of CIIS as palliative therapy are warranted.

Kidney transplantation has evolved over the years from transplants between identically matched donors and recipients to successfully transplanting allografts across virtually any degree of donor-recipient human leukocyte antigen mismatch and ABO-incompatibility. Integral to these improved outcomes has been the development and deployment of a range of immunosuppressive agents. The addition of monoclonal and polyclonal antibodies as a standard part of overall immunosuppression has led to the improved outcomes by providing a robust and focused protection during the first few months of transplantation when allografts are most vulnerable to immune-mediated injury. Alemtuzumab is a recombinant anti-CD52 pan-lymphocyte depleting monoclonal antibody that has been in use for kidney transplantation since the late 1990s. Despite the many years of experience with alemtuzumab, its utilisation in the UK has remained relatively restrained. This may be due to a lack of high-level evidence to support its safety and efficacy in transplantation. Also, long-term outcomes have not been addressed by existing studies. Nevertheless, available evidence suggests that alemtuzumab is associated with a lower risk of acute rejection within the first year of transplantation while exhibiting a comparable safety profile to non-lymphocyte depleting agents. Despite the current economic advantages of alemtuzumab (available free of cost on a named transplant recipient basis), its use in UK transplant centres has remained limited, variating from non-use, through usage in selected high immunologic risk subjects, to use as routine induction immunosuppression. This review discusses the current use of alemtuzumab for immunosuppression induction in kidney transplantation. It describes its evolution from development to its present application in kidney transplantation and reviews the evidence underpinning its utilisation. The role of alemtuzumab in the immunosuppressive protocols individual UK kidney transplant centres is also described.

BACKGROUND Urinary tract infection is the most frequent infectious complication in allograft recipients with poor outcomes. The study aimed to assess the effect of self-testing urine dipsticks at home, with the assistance of smartphone technology, on the occurrence of urinary tract infection (UTI)-associated complications and frequency and length of hospital admissions. METHOD We performed a retrospective cohort study of kidney transplant recipients with a history of recurrent UTI who used a newly introduced smartphone-assisted dipsticks urinalysis test for self-monitoring. Participants self-administered the home urinalysis test with symptom onset. Antibiotics were prescribed if an infection was suspected, and home urinalysis was positive. The incidence of urinary infections, hospitalisations, and complications was evaluated before and during the home urinalysis period. Remote and face-to-face interactions with healthcare personnel were also assessed (cases acted as their controls). RESULTS Nineteen participants were included in the study. A total of 89.5% were females. Ninety home urinalysis tests were conducted over a mean period of 7 months. Sixty-one of these were pre-antibiotic. A total of 42.2% of all tests and 47.5% of the pre-antibiotic tests were positive. UTI-related hospitalisations were lower by 75% during the home urinalysis period; mean 1.26 (0.8-1.6) versus 0.32 (-0.01-0.6). The incidence of infection-related complications was also 65% lower; mean 1.52 (0.8-2.2) versus 0.52 (-0.2-1.2) during the same period. The number of face-to-face interactions was slightly lower; mean 1.9 (1.1-2.2) versus 1.7 (0.6-2.8), with more remote interactions; mean 6.0 (3.7-8.5) versus 10.4 (6.5-14.3), during smartphone urinalysis. Fifty per cent of antibiotic-treated UTI episodes had antibiotics within 24 h, rising to 82% within 48 h of a test. CONCLUSION Smartphone-assisted home urinalysis enabled remote management of UTI in a high-risk population. Outcomes point to a reduction in UTI complications and hospitalisations.

BACKGROUND Patients with neurocysticercosis (NCC) may have an increased frequency of migraine. We studied the characteristics of migraine attacks in patients with calcified NCC on brain imaging. METHODS Of 350 migraine patients who visited our outpatient department from January 2016 through June 2018, 166 had undergone brain imaging. Seventy-two patients with migraines had calcified NCC. The migraine attacks of the patients with calcification (MiC) were compared with those of 94 patients without calcification (MiNC). RESULTS Side-locked headaches were seen in 48.6% of the MiC patients. Aura preceding the migraine attack was more common in the MiC group than in the MiNC group (22.22% vs 7.4%; p=0.001). The MiC group had fewer headache episodes per month (5 vs 6; p

There is a bidirectional relationship between atrial fibrillation (AF) and chronic kidney disease (CKD), with multiple shared risk factors. This article discusses an integrated care approach toward the management of patients with AF, including those with CKD. There is an increasing risk of both ischemic stroke and bleeding with progressive deterioration of renal function, complicating the decision of optimal stroke prevention strategies among patients with AF and CKD. The optimal stroke prevention strategy in patients with AF and severe CKD remains uncertain. An individualized approach incorporating stroke and bleeding risk stratification is needed, especially in those with end-stage renal disease.

A compound disaster defines a situation with adverse consequences resulting from different, but related, disaster‐agents (ICLA 1996). These low probability extreme events can correspond to events with multiple concurrent or consecutive drivers, resulting in major financial or physical loss (Sadegh et al., 2018). In this study, disaster scenarios involving natural hazards and pandemics were developed to assess the risk and implications of a compound event to member countries of the Central Asia Regional Economic Cooperation (CAREC) area.A partnership of 11 countries (Afghanistan, Azerbaijan, China (Inner Mongolia Autonomous Region; Xinjiang Uyghur Autonomous Region), Georgia, Kazakhstan, Kyrgyz Republic, Mongolia, Pakistan, Tajikistan, Turkmenistan and Uzbekistan) across Asia, the CAREC countries work together to promote sustainable development, economic growth and reduce poverty. High exposure to flooding and earthquake coupled with low insurance penetration means natural catastrophes are significantly material to the public sector balance sheet. This collaborative study involving multiple hazard modelling agencies assesses the potential impact of natural perils concurrent to pandemic/epidemic outbreaks.The compound events developed represent Realistic Disaster Scenarios (RDS) for the specific areas they represent and are based on plausible low-probability, high-consequence events such as the 2015 floods in Tbilisi and the 1905 Bolnai earthquake in Mongolia. The impact of the natural events is then further compounded by modelled infectious disease outbreaks for each given scenario.High resolution fluvial and pluvial flood hazard scenario footprints (30m x 30m), earthquake hazard intensity maps and gridded population data (Worldpop) are modelled alongside outbreaks including respiratory (including flu), Nipah and Crimean-Congo haemorrhagic fever, to assess the compounded impact. The humanitarian and financial loss potential of these events are then presented in the context of alternative disaster risk financing measures and adaptation strategies aimed at increased resilience. ICLA (1996), International Conference on Local Authorities Confronting Disasters and Emergencies, Background Documents, Amsterdam.Sadegh, M., Moftakhari, H., Gupta, H. V., Ragno, E., Mazdiyasni, O., Sanders, B., ... & AghaKouchak, A. (2018). Multihazard scenarios for analysis of compound extreme events. Geophysical Research Letters, 45(11), 5470-5480.

Background Cohort studies are among the most robust of observational studies but have issues with external validity. This study assesses threats to external validity (generalizability) in the European QUALity (EQUAL) study, a cohort study of people >65 years of age with Stage 4/5 chronic kidney disease. Methods Patients meeting the EQUAL inclusion criteria were identified in The Health Improvement Network database and stratified into those attending renal units, a secondary care cohort (SCC) and a not primary care cohort (PCC). Survival, progression to renal replacement therapy (RRT) and hospitalization were compared. Results The analysis included 250, 633 and 2464 patients in EQUAL, PCC and SCC. EQUAL had a higher proportion of men compared with PCC and SCC (60.0% versus 34.8% versus 51.4%). Increasing age ≥85 years {odds ratio [OR] 0.25 [95% confidence interval (CI) 0.15–0.40]} and comorbidity [Charlson Comorbidity Index ≥4, OR 0.69 (95% CI 0.52–0.91)] were associated with non-participation in EQUAL. EQUAL had a higher proportion of patients starting RRT at 1 year compared with SCC (8.1% versus 2.1%; P Conclusions This study provides evidence of how participants in a cohort study can differ from the broader population of patients, which is essential when considering external validity and application to local practice.

Background: Critically ill patients with COVID-19 infection on extracorporeal membrane oxygenation (ECMO) face high morbidity and mortality. Palliative care consultation may benefit these patients and their families. Prior to the pandemic, our institution implemented a policy of automatic palliative care consultation for all patients on ECMO due to the high mortality, medical complexity, and psychosocial distress associated with these cases. Objectives: The main objective was to describe the role of the palliative care team for patients on ECMO for COVID-19 infection. The secondary objective was to describe the clinical outcomes for this cohort. Design: Case series. Settings/Subjects: All patients age 18 or older infected by the novel coronavirus who required cannulation on ECMO from March through July of 2020, at an urban, academic medical center in the United States. Inter-disciplinary palliative care consultation occurred for all patients. Results: Twenty-three patients (median age 43 years [range 28-64], mean body mass index 34.9 kg/m2 [SD 9.2], 65% Hispanic ethnicity) were cannulated on ECMO. Eleven patients died during the hospitalization (48%). Patients older than 50 years of age demonstrated a trend toward increased odds of death compared to those younger than 50 years of age (OR 9.1, P = 0.07). Patients received an average of 6.8 (SD 3.7) palliative clinical encounters across all disciplines. The actions provided by the palliative care team included psychosocial support and counseling, determination of surrogate decision maker (for 100% of patients), pain management (83%), and non-pain symptom management (83%). Conclusions: Here, we present one of the first studies describing the patient characteristics, outcomes, and palliative care actions for critically ill patients with COVID-19 on ECMO. Almost half of the patients in this cohort died during their hospitalization. Given the high morbidity and mortality of this condition, we recommend involvement of palliative care for patients/families with COVID-19 infection who are on ECMO. The impact of palliative care on patient and family outcomes, such as symptom control, satisfaction with communication, rates of anxiety, and grief experience merits further investigation.

Machine learning (ML) can help in analyzing xray images to assist human doctors. ML algorithms are not perfect and when a ML algorithm makes a diagnostic error, it is often unclear why - were the features genuinely confusing or was it a badly trained algorithm. In this work, we first compare the accuracy of four well-known ML algorithms (KNN, Decision Tree, Logistic Regression and Convolutional Neural network) to detect pneumonia from chest X-rays of pediatric patients. We show that an algorithm based on Convolutional Neural Networks (CNN) gave the best accuracy of 90.7%. We then present a small test set of the X-rays which were wrongly diagnosed by the CNN algorithm to a panel of 14 doctors to investigate why the algorithm may have failed. We analyze the gap between ML algorithms and real doctors. The panel of doctors was able to diagnose 37% of the images correctly, while it was confused on the remaining 63% of images. This shows that better ML algorithms and training methods can improve the accuracy up to 94%. For the truly confusing images, the doctors identified the following additional features that could be included to help in the diagnosis: Oxygen saturation level (SPO2), Age, Respiratory Rate, and Body Temperature.

Disaster risk reduction relies on quantitative estimates of the future impacts and consequences of known hazard threats in order to evaluate proposed mitigation and adaptation measures. Natural Res...

Talaromycosis is a fungal infection endemic in Southeast Asia. We report a case of a renal transplant recipient who developed infection after a trip to South China. She presented with constitutional symptoms and was found to have an FDG-avid lung mass. Histopathology demonstrated small yeast cells and the culture grew Talaromyces marneffei. The patient was treated with 2 weeks of liposomal amphotericin B followed by itraconazole. The dose of tacrolimus was significantly reduced because of the interaction with itraconazole. Mycophenolate mofetil was discontinued. After 12 months of treatment, the mass had completely resolved. Talaromycosis has mainly been reported in patients with AIDS and is uncommon among solid organ transplant recipients. The immune response against T. marneffei infection is mediated predominantly by T-cells and macrophages. The diagnosis may not be suspected outside of endemic areas. We propose a therapeutic approach in transplant patients by extrapolating the evidence from the HIV literature and following practices applied to other endemic mycoses.

Background and Aims Membranous nephropathy (MN) is among the most common causes of nephrotic syndrome in adults worldwide. Despite this, there is currently no robust data on the epidemiology of MN in the UK population. The Health Improvement Network (THIN) is an electronic medical record database that holds longitudinal anonymised patient records for over 17 million patients and has shown to be generalisable to the UK regarding demographics and crude prevalence’s of major conditions. To our knowledge, accuracy of the read codes for glomerular disease is yet to be validated. This will be the first study into MN validating the diagnostic accuracy using the THIN database. Method THIN database was interrogated for patients with MN using read codes. Two cohorts were considered: Definite cohort, defined as read codes expected to correspond to a diagnosis of MN, and Probable cohort, defined as read codes that could correspond to a diagnosis of MN. In order to confirm the diagnosis of MN, a short questionnaire was sent to the GP practice of a randomly selected cohort of patients asking if the diagnosis of MN was correct, and that the diagnosis had been confirmed by a specialist renal centre, with or without a renal biopsy. Results 267 patients with a record of MN were identified from the THIN database. 235 of the patients had Definite cohort read codes, with a mean age at diagnosis of 57 years. There were 155 (66.2%) male and 79 (33.8%) female patients. 32 patients were identified in the Probable cohort. GP questionnaires were sent to 71 randomly selected patients with 61 responses (85.9% response rate). This represented 23% (n=53) of the total Definite cohort and 25% (n=8) of the total Probable cohort. Of the 61 returned questionnaires, an MN diagnosis was confirmed in 96% (n=51) of patients with a definite read code and 25% (n=2) with a probable read code. Amongst the confirmed MN diagnoses in the Definite cohort, 88% (n=45) of the patients had primary MN. Conclusion The THIN database is a valid data resource for studying MN in patients with a read code from the Definite cohort list. Read codes from the Probable cohort list cannot be used unless confirmed on a case by case basis such as through the GP. The results of this study will feed into a larger project with an aim to describe accurately the epidemiology of MN in the UK population, and report the incidence and prevalence of specific secondary associations of MN. Once these factors are fully understood, diagnostic and care pathways for MN can be developed.

Purpose As more patients live with advanced heart failure, use of continuous intravenous inotropic support (CIIS) as palliative therapy has increased over the last decade. However, in-depth analysis of symptom benefits provided by CIIS and its associated risks merit further investigation. We aimed to study health-related quality of life outcomes for patients receiving CIIS as palliative therapy. Methods Retrospective analysis of patients with advanced heart failure at an urban, academic center who were started on CIIS as palliative therapy between 2014-2016. Patients prescribed CIIS as bridge to surgical therapies were excluded. Data collected from the EHR included demographics, length of time on CIIS, change in functional status at first clinic appointment, and complications of therapy (e.g. ICD shocks, infections, hospitalizations, ER visits, ICU admissions). Data were analyzed using descriptive statistics. Results Seventy-six patients meeting study criteria received CIIS for palliation for an average of 6.2 months. The majority experienced improvement in functional status (69.7%) and changed code status to DNR/DNI after inotrope initiation (57.8%). Rates of ICD shocks and central line infection were 4.4 and 1.3 per 100 person-months of CIIS therapy, respectively. The rate of all cause- hospitalization was 43.6 per 100 person-months of follow up. More specifically, rate of hospitalization due to acute decompensated heart failure (ADHF), bacteremia, ICD shock, or other were 12.9, 1.1, 0, and 1.3 per 100 person-months of follow-up, respectively. Reasons for ED visits due to HF compared to non-HF related were 11.2 and 3.4 per 100 person-months, respectively. The rate of ICU admission during palliative CIIS was 5.5 per 100 person-months. Overall, patients spent 20.1% (SD 21.7%) of their time on inotropes admitted to our hospital. Conclusion Patients in this cohort reported an improvement in functional status after the initiation of CIIS. All-cause hospitalization rate was quite high in this patient cohort, with ADHF being the primary reason for hospitalization, followed by bacteremia. ICD shocks do not appear to be a major burden for these patients with respect to both rate of shocks observed and reason for hospitalization. Patients on CIIS as palliative therapy spent, on average, one out of five days in the hospital while on inotropic therapy.