HAPLOIDENTICAL TRANSPLANT WITH POST-TRANSPLANT CYCLOPHOSPHAMIDE FOR ACUTE MYELOID LEUKAEMIA AND MYELODYSPLASTIC SYNDROMES PATIENTS: THE ROLE OF PREVIOUS LINES OF THERAPY.

Background: Allogeneic haematopoietic stem-cell transplant is a potentially curative option for high-risk acute myeloid leukaemia (AML) and myelodysplastic syndrome (MDS) patients. Post-transplant cyclophosphamide administration allows for selection of haploidentical donors in patients who are eligible for the procedure, but do not have a fully matched donor, since it can overcome the HLA barrier. There is still an active debate on whether intensification of the conditioning regimen is necessary with haploidentical donors when peripheral blood stem cells are used as the source of the graft.   Herein we report our decennial experience of haploidentical stem-cell transplant using peripheral blood stem cells at King’s College Hospital. Objectives: The primary objective was to evaluate overall survival (OS) for patients with less than two previous lines of therapy. Secondary objectives were total OS, OS according to cytomegalovirus (CMV) reactivation, incidence of transplant-related mortality (TRM), graft-versus-host disease (GVHD) and GVHD-relapse-free survival (GRFS). Results: One-year and three-year total OS were 62% and 43%, respectively, with a median OS of 22 months. One-year and three-year OS for patients with ≤2 and in patients with >2 previous lines of therapy were 72% and 55%, and 60% and 22%, respectively (p-value=0.04). The median OS in patients with >2 previous lines of therapy and ≤2 lines of therapy was 16 and 49 months, respectively. Cumulative incidence (CI) of relapse was 25% with a median time to relapse of 5 months (range 1 – 38 months). Conclusions: Haploidentical haematopoietic stem-cell transplant is potentially curative in chemo-sensitive AML and MDS and offers a high rate of prolonged remission. Our cohort further confirms the role of consolidative haploidentical transplant in patients in complete remission and highlights that patients with heavily pre-treated disease may not benefit from this strategy.

Performance of the beta-glucan test for the diagnosis of invasive fusariosis and scedosporiosis: a meta-analysis

The (1→3)-β-D-glucan (BDG) is a component of the fungal cell wall that can be detected in serum and used as an adjunctive tool for the diagnosis of invasive mold infections (IMI) in patients with hematologic cancer or other immunosuppressive conditions. However, its use is limited by modest sensitivity/specificity, inability to differentiate between fungal pathogens, and lack of detection of mucormycosis. Data about BDG performance for other relevant IMI, such as invasive fusariosis (IF) and invasive scedosporiosis/lomentosporiosis (IS) are scarce. The objective of this study was to assess the sensitivity of BDG for the diagnosis of IF and IS through systematic literature review and meta-analysis. Immunosuppressed patients diagnosed with proven or probable IF and IS, with interpretable BDG data were eligible. A total of 73 IF and 27 IS cases were included. The sensitivity of BDG for IF and IS diagnosis was 76.7% and 81.5%, respectively. In comparison, the sensitivity of serum galactomannan for IF was 27%. Importantly, BDG positivity preceded the diagnosis by conventional methods (culture or histopathology) in 73% and 94% of IF and IS cases, respectively. Specificity was not assessed because of lacking data. In conclusion, BDG testing may be useful in patients with suspected IF or IS. Combining BDG and galactomannan testing may also help differentiating between the different types of IMI

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

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

Estimating the value of demand-side management in low-cost, solar micro-grids

Demand-side management has the potential to reduce the cost of solar based community micro-grids and solar home systems for electricity access. This paper presents a methodology for optimal least-cost sizing of generation assets while meeting explicit reliability constraints in micro-grids that are capable of active demand management. The battery management model considers kinetic constraints on battery operation and represents dispatch in the field to regulate the depth of discharge. The model allows consideration of the trade-off between depth of discharge, cycle life, and calendar lifetime in lead-acid batteries. Separate reliability targets for disaggregated, residential load profiles at hourly timesteps are considered to evaluate the performance and cost reduction potential of demand-side management capabilities — with economic results and sensitivity analyses around key input assumptions subsequently presented. We find that demand-side management can reduce the number and cost of requisite solar panels and batteries with the integration of real-time management and controls – a key result for justifying next generation micro-grids for electricity access. Keywords: Micro-grids, Electricity access, Demand-side management, Reliability, Asset selection, Off-grid, Techno-economic model, CostMassachusetts Institute of Technology. Tata Center for Technology and Desig

Optimal sizing of solar and battery assets in decentralized micro-grids with demand-side management

Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2017.Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.Cataloged from PDF version of thesis.Includes bibliographical references (pages 199-209).Solar-based community micro-grids and individual home systems have been recognized as key enablers of electricity provision to the over one billion people living without energy access to-date. Despite significant cost reductions in solar panels, these options can still be cost-prohibitive mainly due over-sizing of generation assets corresponding with a lack of ability to actively manage electricity demand. The main contribution shared is the methodology and optimization approach of least-cost combinations of generation asset sizes, in solar panels and batteries, subject to meeting reliability constraints; these results are based on a techno-economic modeling approach constructed for assessing decentralized micro-grids with demand-side management capabilities. The software model constructed is implemented to represent the technical characteristics of a low-voltage, direct current network architecture and computational capabilities of a power management device. The main use-case of the model presented is based on serving representative, aggregated, household-level load profiles combined with simulated power output from solar photovoltaic modules and the kinetic operating constraints of lead-acid batteries at hourly timesteps over year-long simulations. The state-space for solutions is based on available solar module and battery capacities from distributors in Jharkhand, India. Additional work presented also extends to real-time operation of such isolated micro-grids with requisite local computation. First, for load disaggregation and forecasting purposes, clustering algorithms and statistical learning techniques are applied on quantitative results from inferred load profiles based on data logged from off-grid solar home systems. Second, results from an optimization approach to accurately parametrize a lead-acid battery model for potential usage in real-time field implementation are also shared. Economic results, sensitivity analyses around key technical and financial input assumptions, and comparisons in cost reductions due to the optimization of solar and battery assets for decentralized micro-grids with demand-side management capabilities are subsequently presented. The work concludes with insights and policy implications on establishing differentiated willingness-to-pay, tiers of service, and dynamic price-setting in advanced micro-grids.by Varun Mehra.S.M. in Technology and PolicyS.M