Sturge-Weber Syndrome Associated with Bilateral Angle-closure Glaucoma in a Young Adult

Sturge-Weber syndrome (SWS) is a phakomatosis involving the eyelids, conjunctiva, choroid and retina. The mechanism ofglaucoma in SWS involves developmental anomaly of the anterior chamber angle and elevated episcleral venous pressure.Here, we present a case of Roach’s type II SWS with bilateral angle-closure glaucoma (ACG) in a young adult, which to thebest of our knowledge, is the first-of-its-kind report in the literature. Though unusual, ACG may occur in young adults too.However, the underlying causes that make them develop the ACG are poorly understood. We also highlight the importanceof comprehensive clinical examination and appropriate investigations for early detection and proper treatment of such youngpatients with ACG

PCA based health indicator for remaining useful life prediction of wind turbine gearbox

Fault prognosis of wind turbine gearbox has received considerable attention as it predicts the remaining useful life which further allows the scheduling of maintenance strategies. However, the studies related towards the RUL prediction of wind turbine gearbox are limited, because of the complexity of gearbox, acute changes in the operating conditions and non-linear nature of the acquired vibration signals. In this study, a health indicator is constructed in order to predict the remaining useful life of the wind turbine gearbox. Run to fail experiments are performed on a laboratory scaled wind turbine gearbox of overall gear ratio 1:100. Vibration signals are acquired and decomposed through continuous wavelet transform to obtain the wavelet coefficients. Various statistical features are computed from the wavelet coefficients which return form high-dimensional input feature set. Principal component analysis is performed to reduce the dimensionality and principal components (PCs) are computed from the input feature set. PC1 is considered as the health indicator and subjected to further smoothening by linear rectification technique. Exponential degradation model is fit to the considered health indicator and the model is able to predict the RUL of the gearbox with an error percentage of 2.73 %

Impact of Second Primary Malignancy Post–Autologous Transplantation on Outcomes of Multiple Myeloma: A CIBMTR Analysis

The overall survival (OS) has improved significantly in multiple myeloma (MM) over the last decade with the use of proteasome inhibitor and immunomodulatory drug-based combinations, followed by high-dose melphalan and autologous hematopoietic stem cell transplantation (auto-HSCT) and subsequent maintenance therapies in eligible newly diagnosed patients. However, clinical trials using auto-HSCT followed by lenalidomide maintenance have shown an increased risk of second primary malignancies (SPM), including second hematological malignancies (SHM). We evaluated the impact of SPM and SHM on progression-free survival (PFS) and OS in patients with MM after auto-HSCT using CIBMTR registry data. Adult patients with MM who underwent first auto-HSCT in the United States with melphalan conditioning regimen from 2011 to 2018 and received maintenance therapy were included (n = 3948). At a median follow-up of 37 months, 175 (4%) patients developed SPM, including 112 (64%) solid, 36 (20%) myeloid, 24 (14%) SHM, not otherwise specified, and 3 (2%) lymphoid malignancies. Multivariate analysis demonstrated that SPM and SHM were associated with an inferior PFS (hazard ratio [HR] 2.62, P \u3c .001 and HR 5.01, P \u3c .001, respectively) and OS (HR 3.85, P \u3c .001 and HR 8.13, P \u3c .001, respectively). In patients who developed SPM and SHM, MM remained the most frequent primary cause of death (42% vs 30% and 53% vs 18%, respectively). We conclude the development of SPM and SHM leads to a poor survival in patients with MM and is an important survivorship challenge. Given the median survival for MM continues to improve, continued vigilance is needed to assess the risks of SPM and SHM with maintenance therapy post-auto-HSCT

The Mutational Landscape in Chronic Myelomonocytic Leukemia and Its Impact on Allogeneic Hematopoietic Cell Transplantation Outcomes: A Center for Blood and Marrow Transplantation Research (CIBMTR) Analysis

Somatic mutations are recognized as an important prognostic factor in chronic myelomonocytic leukemia (CMML). However, limited data are available regarding their impact on outcomes after allogeneic hematopoietic cell transplantation (HCT). In this registry analysis conducted in collaboration with the Center for International Blood and Marrow Transplantation Registry database/sample repository, we identified 313 adult patients with CMML (median age: 64 years, range, 28- 77) who underwent allogeneic HCT during 2001-2017 and had an available biospecimen in the form of a peripheral blood sample obtained prior to the start of conditioning. In multivariate analysis, a CMML-specific prognostic scoring system (CPSS) score of intermediate-2 (HR=1.46, P=0.049) or high (HR=3.22, P=0.0004) correlated significantly with overall survival. When the molecularly informed CPSS-Mol prognostic model was applied, a high CPSS-Mol score (HR=2 P=0.0079) correlated significantly with overall survival. The most common somatic mutations were in ASXL1 (62%), TET2 (35%), KRAS/NRAS (33% combined), and SRSF2 (31%). DNMT3A and TP53 mutations were associated with decreased overall survival (HR=1.70 [95% CI: 1.11-2.60], P=0.0147 and HR=2.72 [95% CI: 1.37-5.39], P=0.0042, respectively) while DNMT3A, JAK2, and TP53 mutations were associated with decreased disease-free survival (HR=1.66 [95% CI: 1.11-2.49], P=0.0138, HR=1.79 [95% CI: 1.06-3.03], P=0.0293, and HR=2.94 [95% CI: 1.50-5.79], P=0.0018, respectively). The only mutation associated with increased relapse was TP53 (HR=2.94, P=0.0201). Nonetheless, the impact of TP53 mutations specifically should be interpreted cautiously given their rarity in CMML. We calculated the goodness of fit measured by Harrell\u27s C-index for both the CPSS and CPSS-Mol, which were very similar. In summary, via registry data we have determined the mutational landscape in patients with CMML who underwent allogeneic HCT, and demonstrated an association between CPSS-Mol and transplant outcomes although without major improvement in the risk prediction beyond that provided by the CPSS

Allogeneic Hematopoietic Cell Transplantation for Blastic Plasmacytoid Dendritic Cell Neoplasm: A CIBMTR Analysis

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematological malignancy with a poor prognosis and considered incurable with conventional chemotherapy. Small observational studies reported allogeneic hematopoietic cell transplantation (allo-HCT) offers durable remissions in patients with BPDCN. We report an analysis of patients with BPDCN who received an allo-HCT, using data reported to the Center for International Blood and Marrow Transplant Research (CIBMTR). We identified 164 patients with BPDCN from 78 centers who underwent allo-HCT between 2007 and 2018. The 5-year overall survival (OS), disease-free survival (DFS), relapse, and nonrelapse mortality (NRM) rates were 51.2% (95% confidence interval [CI], 42.5-59.8), 44.4% (95% CI, 36.2-52.8), 32.2% (95% CI, 24.7-40.3), and 23.3% (95% CI, 16.9-30.4), respectively. Disease relapse was the most common cause of death. On multivariate analyses, age of ≥60 years was predictive for inferior OS (hazard ratio [HR], 2.16; 95% CI, 1.35-3.46; P = .001), and higher NRM (HR, 2.19; 95% CI, 1.13-4.22; P = .02). Remission status at time of allo-HCT (CR2/primary induction failure/relapse vs CR1) was predictive of inferior OS (HR, 1.87; 95% CI, 1.14-3.06; P = .01) and DFS (HR, 1.75; 95% CI, 1.11-2.76; P = .02). Use of myeloablative conditioning with total body irradiation (MAC-TBI) was predictive of improved DFS and reduced relapse risk. Allo-HCT is effective in providing durable remissions and long-term survival in BPDCN. Younger age and allo-HCT in CR1 predicted for improved survival, whereas MAC-TBI predicted for less relapse and improved DFS. Novel strategies incorporating allo-HCT are needed to further improve outcomes

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation