Development of a life expectancy table for individuals with type 1 diabetes

Aims/hypothesis:Tables reporting life expectancies by common risk factors are available for individuals with type 2 diabetes; however, there is currently no published equivalent for individuals with type 1 diabetes. We aimed to develop a life expectancy table using a recently published simulation model for individuals with type 1 diabetes.Methods: The simulation model was developed using data from a real-world population of patients with type 1 diabetes selected from the Swedish National Diabetes Register. The following six important risk factors were included in the life table: sex; age; current smoking status; BMI; eGFR; and HbA1c. For each of 1024 cells in the life expectancy table, a synthetic cohort containing 1000 individuals was created, with other risk factors assigned values representative of the real-world population. The simulations were executed for all synthetic cohorts and life expectancy for each cell was calculated as mean survival time of the individuals in the respective cohort.Results: There was a substantial variation in life expectancy across patients with different risk factor levels. Life expectancy of 20-year-old men varied from 29.3 years to 50.6 years, constituting a gap of 21.3 years between those with worst and best risk factor levels. In 20-year-old women, this gap was 18.9 years (life expectancy range 35.0-53.9 years). The variation in life expectancy was a function of the combination of risk factor values, with HbA1c and eGFR consistently showing a negative and positive correlation, respectively, with life expectancy at any level combination of other risk factors. Individuals with the lowest level (20 kg/m2) and highest level of BMI (35 kg/m2) had a lower life expectancy compared with those with a BMI of 25 kg/m2. Non-smokers and women had a higher life expectancy than smokers and men, respectively, with the difference in life expectancy ranging from 0.4 years to 2.7 years between non-smokers and smokers, and from 1.9 years to 5.9 years between women and men, depending on levels of other risk factors.Conclusions/interpretation: The life expectancy table generated in this study shows a substantial variation in life expectancy across individuals with different modifiable risk factors. The table allows for rapid communications of risk in an easily understood format between healthcare professionals, health economists, researchers, policy makers and patients. Particularly, it supports clinicians in their discussion with patients about the benefits of improving risk factors

Development and use of prediction models for classification of cardiovascular risk of remote indigenous Australians

Background: Cardiovascular disease (CVD) is the leading cause of death for Indigenous Australians. There is widespread belief that current tools have deficiencies for assessing CVD risk in this high-risk population. We sought to develop a 5-year CVD risk score using a wide range of known risk factors to further improve CVD risk prediction in this population.Methods: We used clinical and demographic information on Indigenous people aged between 30 and 74 years without a history of CVD events who participated in the Well Person's Health Check (WPHC), a community-based survey. Baseline assessments were conducted between 1998 and 2000, and data were linked to administrative hospitalisation and death records for identification of CVD events. We used Cox proportional hazard models to estimate the 5-year CVD risk, and the Harrell's c-statistic and the modified Hosmer-Lemeshow (mH-L) χ2 statistic to assess the model discrimination and calibration, respectively.Results: The study sample consisted of 1,583 individuals (48.1% male; mean age 45.0 year). The risk score consisted of sex, age, systolic blood pressure, diabetes mellitus, waist circumference, triglycerides, and albumin creatinine ratio. The bias-corrected c-statistic was 0.72 and the bias-corrected mH-L χ2 statistic was 12.01 (p-value, 0.212), indicating good discrimination and calibration, respectively. Using our risk score, the CVD risk of the Indigenous Australians could be stratified to a greater degree compared to a recalibrated Framingham risk score.Conclusions: A seven-factor risk score could satisfactorily stratify 5-year risk of CVD in an Indigenous Australian cohort. These findings inform future research targeting CVD risk in Indigenous Australians

Chemical tagging with APOGEE: discovery of a large population of N-rich stars in the inner Galaxy

Formation of globular clusters (GCs), the Galactic bulge, or galaxy bulges in general is an important unsolved problem in Galactic astronomy. Homogeneous infrared observations of large samples of stars belonging to GCs and the Galactic bulge field are one of the best ways to study these problems. We report the discovery by APOGEE (Apache Point Observatory Galactic Evolution Experiment) of a population of field stars in the inner Galaxy with abundances of N, C, and Al that are typically found in GC stars. The newly discovered stars have high [N/Fe], which is correlated with [Al/Fe] and anticorrelated with [C/Fe]. They are homogeneously distributed across, and kinematically indistinguishable from, other field stars within the same volume. Their metallicity distribution is seemingly unimodal, peaking at [Fe/H] ∼ −1, thus being in disagreement with that of the Galactic GC system. Our results can be understood in terms of different scenarios. N-rich stars could be former members of dissolved GCs, in which case the mass in destroyed GCs exceeds that of the surviving GC system by a factor of ∼8. In that scenario, the total mass contained in so-called ‘first-generation’ stars cannot be larger than that in ‘second-generation’ stars by more than a factor of ∼9 and was certainly smaller. Conversely, our results may imply the absence of a mandatory genetic link between ‘second-generation’ stars and GCs. Last, but not least, N-rich stars could be the oldest stars in the Galaxy, the by-products of chemical enrichment by the first stellar generations formed in the heart of the Galaxy

Quality of life among people living with hypertension in a rural Vietnam community

Background - To respond to growing prevalence of hypertension in Vietnam, it is critical to have an in-depth understanding about quality of life (QOL) among people living with hypertension and related factors. This study aimed to measure QOL among hypertensive people in a rural community in Vietnam, and its association with socio-demographic characteristics and factors related to treatment. Methods - This study was conducted in a rural community located 60 km from Ho Chi Minh City. Face-to-face interviews were conducted among 275 hypertensive people aged 50 years and above using WHOQOL-BREF questionnaire. Descriptive statistics were used to examine mean scores of quality of life. Cronbach’s alpha coefficient and Pearson’s correlation coefficient were applied to estimate the internal consistency, and the level of agreement between different domains of WHOQOL-BREF, respectively. Independent T-test and ANOVA test followed by multiple linear regression analyses were used to measure the association between QOL domains and independent variables. Results - Both overall WHOQOL-BREF and each domain had a good internal consistency, ranging from 0.65 to 0.88. The QOL among hypertensive patients was found moderate in all domains, except for psychological domain that was fairly low (mean = 49.4). Backward multiple linear regressions revealed that being men, married, attainment of higher education, having physical activities at moderate level, and adherence to treatment were positively associated with QOL. However, older age and presence of co-morbidity were negatively associated with QOL. Conclusion - WHOQOL-BREF is a reliable instrument to measure QOL among hypertensive patients. The results revealed low QOL in psychological domain and inequality in QOL across socio-demographic characteristics. Given the results, encouraging physical activities and strengthening treatment adherence should be considered to improve QOL of hypertensive people, especially for psychological aspect. Actions to improve QOL among hypertensive patients targeted towards women, lower educated and unmarried patients are needed in the setting

The transcriptional architecture of early human hematopoiesis identifies multilevel control of lymphoid commitment.

Understanding how differentiation programs originate from the gene-expression 'landscape' of hematopoietic stem cells (HSCs) is crucial for the development of new clinical therapies. We mapped the transcriptional dynamics underlying the first steps of commitment by tracking transcriptome changes in human HSCs and eight early progenitor populations. We found that transcriptional programs were extensively shared, extended across lineage-potential boundaries and were not strictly lineage affiliated. Elements of stem, lymphoid and myeloid programs were retained in multilymphoid progenitors (MLPs), which reflected a hybrid transcriptional state. By functional single cell analysis, we found that the transcription factors Bcl-11A, Sox4 and TEAD1 (TEF1) governed transcriptional networks in MLPs, which led to B cell specification. Overall, we found that integrated transcriptome approaches can be used to identify previously unknown regulators of multipotency and show additional complexity in lymphoid commitment

Product and process innovation in manufacturing firms: a 30-year bibliometric analysis

Built upon a thirty-year dataset collected from the Web of Science database, the present research aims to offer a comprehensive overview of papers, authors, streams of research, and the most influential journals that discuss product and process innovation in the manufacturing environment. The dataset is composed of 418 papers from more than 150 journals from the period between 1985 and 2015. Homogeneity analysis by means of alternating least squares (HOMALS) and Social Network Analysis (SNA) are used to accomplish the objectives listed above through the keywords given by authors. Initially, the paper highlights and discusses the similarity between the topics debated by the main journals in this field. Subsequently, a wide-range map of topics is presented highlighting five main areas of interests; namely, performance, patent, small firm, product development, and organization. A SNA is also performed in order to validate the results that emerged from HOMALS. Finally, several insights about future research avenues in the manufacturing field are provided

Phylogeographical analysis of the dominant multidrug-resistant H58 clade of Salmonella Typhi identifies inter- and intracontinental transmission events.

The emergence of multidrug-resistant (MDR) typhoid is a major global health threat affecting many countries where the disease is endemic. Here whole-genome sequence analysis of 1,832 Salmonella enterica serovar Typhi (S. Typhi) identifies a single dominant MDR lineage, H58, that has emerged and spread throughout Asia and Africa over the last 30 years. Our analysis identifies numerous transmissions of H58, including multiple transfers from Asia to Africa and an ongoing, unrecognized MDR epidemic within Africa itself. Notably, our analysis indicates that H58 lineages are displacing antibiotic-sensitive isolates, transforming the global population structure of this pathogen. H58 isolates can harbor a complex MDR element residing either on transmissible IncHI1 plasmids or within multiple chromosomal integration sites. We also identify new mutations that define the H58 lineage. This phylogeographical analysis provides a framework to facilitate global management of MDR typhoid and is applicable to similar MDR lineages emerging in other bacterial species

The comparative mortality of an elite group in the long run of history: an observational analysis of politicians from 11 countries

This study aims to compare the mortality rate and life expectancy of politicians with those of the age and gender-matched general populations. This was an observational analysis of mortality rates of politicians (i.e. members of national parliaments with available data on dates of birth, death and election, gender, and life tables) in 11 developed countries. Politicians were followed from date of first election until either death or the last available year with life table data. Relative mortality differences were estimated using standardised mortality ratios (SMRs). Absolute inequalities were quantified as the difference in survival by deducting a population’s remaining life expectancy from politicians’ remaining life expectancy at age 45, estimated using Gompertz parametric proportional hazards models. We included 57,561 politicians (with follow-up ranging from 1816–2016 for France to 1949–2017 for Germany). In almost all countries politicians had similar rates of mortality to the general population in the early part of the twentieth century. Relative mortality and survival differences (favouring politicians) increased considerably over the course of the twentieth century, with recent SMRs ranging from 0.45 (95%CI 0.41–0.50) in Italy to 0.82 (95%CI 0.69–0.95) in New Zealand. The peak life expectancy gaps ranged from 4.4 (95% CI, 3.5–5.4) years in the Netherlands to 7.8 (95% CI, 7.2–8.4) years in the US. Our results show large relative and absolute inequalities favouring politicians in every country. In some countries, such as the US, relative inequalities are at the greatest level in over 150 years

A patient-level model to estimate lifetime health outcomes of patients with type 1 diabetes

Objective: To develop a patient-level simulation model for predicting lifetime health outcomes of patients with type 1 diabetes and as a tool for economic evaluation of type 1 diabetes treatment based on data from a large, longitudinal cohort. Research design and methods: Data for model development were obtained from the Swedish National Diabetes Register. We derived parametric proportional hazards models predicting the absolute risk of diabetes complications and death based on a wide range of clinical variables and history of complications. We used linear regression models to predict risk factor progression. Internal validation was performed, estimates of life expectancies for different age-sex strata were computed, and the impact of key risk factors on life expectancy was assessed. Results: The study population consisted of 27,841 patients with type 1 diabetes with a mean duration of follow-up of 7 years. Internal validation showed good agreement between the predicted and observed cumulative incidence of death and 10 complications. Simulated life expectancy was ∼13 years lower than that of the sex- and age-matched general population, and patients with type 1 diabetes could expect to live with one or more complications for ∼40% of their remaining life. Sensitivity analysis showed the importance of preventing renal dysfunction, hypoglycemia, and hyperglycemia as well as lowering HbA1c in reducing the risk of complications and death. Conclusions: Our model was able to simulate risk factor progression and event histories that closely match the observed outcomes and to project events occurring over patients' lifetimes. The model can serve as a tool to estimate the impact of changing clinical risk factors on health outcomes to inform economic evaluations of interventions in type 1 diabetes