Lack of Association Between Dietary Inflammatory Index and Low Impact Fractures in the Brazilian Population: the Brazilian Osteoporosis Study (BRAZOS)

Introduction: Adequate nutrition, including intake of dietary calcium and vitamin D, is important to maintain bone health. Evidence suggests that a deficiency in micronutrients may contribute to bone loss during aging and exert generalized effects on chronic inflammation. Recently, the Dietary Inflammatory Index (DII) was developed to assess the inflammatory potential of individual diets. Our aim was to evaluate the DII in a representative sample and verify its association with low-impact fractures. Methods: Individuals from The Brazilian Osteoporosis Study (BRAZOS) database had their DII calculated. BRAZOS is an important cross-sectional epidemiological study carried out with a representative sample of men and women ≥40 years old. The research was conducted through in-home interviews administered by a trained team. Nutrition Database System for Research (NDSR) software was used to analyze data on the intake of nutrients, which were employed to calculate the DII using Statistical Analysis Software (SAS®) and Statistical Package for the Social Sciences (SPSS®) to assess its association with low-impact fractures. Results: A total of 2269 subjects had their DII score calculated using information from 24-h recall data. Males had lower DII than females (DII = 1.12 ± 1.04 vs DII = 1.24 ± 0.99, p = 0.012). Women taking statins had lower DII (DII = 0.65 ± 1.14 vs DII + 1.26 ± 0.98, p = 0.002), indicating a greater potential for diet-related anti-inflammatory effects. Conclusion: Our findings suggest that women might have a pro-inflammatory diet pattern compared to men. However, we did not find any association between DII scores and low-impact fractures

The Association of the Metabolic Syndrome with PAI-1 and t-PA Levels

Background. We used a random sample (n = 2, 495) from the population-based Prevention of Renal and Vascular End-stage Disease (PREVEND) study population to examine the association of the metabolic syndrome (Met S) with plasminogen activator inhibitor type 1 (PAI-1) and tissue plasminogen activator (t-PA) antigen levels. Results. The overall prevalence of the Met S was 18%, was dependent on age and gender, and was positively associated with higher antigen levels of both PAI-1 and t-PA. These significant effects were maintained after adjustment for age, gender, BMI, elevated C-reactive protein, smoking status, urinary albumin excretion, and insulin levels. We found no significant interactions between the Met S and other covariates on PAI-1 and t-PA levels. Conclusions. Our study demonstrates that those with the Met S have significantly higher levels of PAI-1 and t-PA antigen, factors known to increase the risk of cardiovascular disease

An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene Interactions on risk of myocardial infarction: The importance of model validation

BACKGROUND: To examine interactions among the angiotensin converting enzyme (ACE) insertion/deletion, plasminogen activator inhibitor-1 (PAI-1) 4G/5G, and tissue plasminogen activator (t-PA) insertion/deletion gene polymorphisms on risk of myocardial infarction using data from 343 matched case-control pairs from the Physicians Health Study. We examined the data using both conditional logistic regression and the multifactor dimensionality reduction (MDR) method. One advantage of the MDR method is that it provides an internal prediction error for validation. We summarize our use of this internal prediction error for model validation. RESULTS: The overall results for the two methods were consistent, with both suggesting an interaction between the ACE I/D and PAI-1 4G/5G polymorphisms. However, using ten-fold cross validation, the 46% prediction error for the final MDR model was not significantly lower than that expected by chance. CONCLUSIONS: The significant interaction initially observed does not validate and may represent a type I error. As data-driven analytic methods continue to be developed and used to examine complex genetic interactions, it will become increasingly important to stress model validation in order to ensure that significant effects represent true relationships rather than chance findings

The SXS Collaboration catalog of binary black hole simulations

Accurate models of gravitational waves from merging black holes are necessary for detectors to observe as many events as possible while extracting the maximum science. Near the time of merger, the gravitational waves from merging black holes can be computed only using numerical relativity. In this paper, we present a major update of the Simulating eXtreme Spacetimes (SXS) Collaboration catalog of numerical simulations for merging black holes. The catalog contains 2018 distinct configurations (a factor of 11 increase compared to the 2013 SXS catalog), including 1426 spin-precessing configurations, with mass ratios between 1 and 10, and spin magnitudes up to 0.998. The median length of a waveform in the catalog is 39 cycles of the dominant $\ell=m=2$ gravitational-wave mode, with the shortest waveform containing 7.0 cycles and the longest 351.3 cycles. We discuss improvements such as correcting for moving centers of mass and extended coverage of the parameter space. We also present a thorough analysis of numerical errors, finding typical truncation errors corresponding to a waveform mismatch of $\sim 10^{-4}$. The simulations provide remnant masses and spins with uncertainties of 0.03% and 0.1% ($90^{\text{th}}$ percentile), about an order of magnitude better than analytical models for remnant properties. The full catalog is publicly available at https://www.black-holes.org/waveforms .Comment: 33+18 pages, 13 figures, 4 tables, 2,018 binaries. Catalog metadata in ancillary JSON file. v2: Matches version accepted by CQG. Catalog available at https://www.black-holes.org/waveform

A randomized clinical trial of a peri-operative behavioral intervention to improve physical activity adherence and functional outcomes following total knee replacement

<p>Abstract</p> <p>Background</p> <p>Total knee replacement (TKR) is a common and effective surgical procedure to relieve advanced knee arthritis that persists despite comprehensive medical treatment. Although TKR has excellent technical outcomes, significant variation in patient-reported functional improvement post-TKR exists. Evidence suggests that consistent post-TKR exercise and physical activity is associated with functional gain, and that this relationship is influenced by emotional health. The increasing use of TKR in the aging US population makes it critical to find strategies that maximize functional outcomes.</p> <p>Methods/Design</p> <p>This randomized clinical trial (RCT) will test the efficacy of a theory-based telephone-delivered Patient Self-Management Support intervention that seeks to enhance adherence to independent exercise and activity among post- TKR patients. The intervention consists of 12 sessions, which begin prior to surgery and continue for approximately 9 weeks post-TKR. The intervention condition will be compared to a usual care control condition using a randomized design and a probabilistic sample of men and women. Assessments are conducted at baseline, eight weeks, and six- and twelve- months. The project is being conducted at a large healthcare system in Massachusetts. The study was designed to provide greater than 80% power for detecting a difference of 4 points in physical function (SF36/Physical Component Score) between conditions (standard deviation of 10) at six months with secondary outcomes collected at one year, assuming a loss to follow up rate of no more than 15%.</p> <p>Discussion</p> <p>As TKR use expands, it is important to develop methods to identify patients at risk for sub-optimal functional outcome and to effectively intervene with the goal of optimizing functional outcomes. If shown efficacious, this peri-TKR intervention has the potential to change the paradigm for successful post-TKR care. We hypothesize that Patient Self-Management Support to enhance adherence to independent activity and exercise will enhance uniform, optimal improvement in post-TKR function and patient autonomy, the ultimate goals of TKR.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00566826">NCT00566826</a></p

Cardiovascular Risk Associated with Interactions among Polymorphisms in Genes from the Renin-Angiotensin, Bradykinin, and Fibrinolytic Systems

Vascular fibrinolytic balance is maintained primarily by interplay of tissue plasminogen activator (t-PA) and plasminogen activator inhibitor type 1 (PAI-1). Previous research has shown that polymorphisms in genes from the renin-angiotensin (RA), bradykinin, and fibrinolytic systems affect plasma concentrations of both t-PA and PAI-1 through a set of gene-gene interactions. In the present study, we extend this finding by exploring the effects of polymorphisms in genes from these systems on incident cardiovascular disease, explicitly examining two-way interactions in a large population-based study

Updated international tuberous sclerosis complex diagnostic criteria and surveillance and management recommendations

Background Tuberous sclerosis complex (TSC) is an autosomal dominant genetic disease affecting multiple body systems with wide variability in presentation. In 2013, Pediatric Neurology published articles outlining updated diagnostic criteria and recommendations for surveillance and management of disease manifestations. Advances in knowledge and approvals of new therapies necessitated a revision of those criteria and recommendations. Methods Chairs and working group cochairs from the 2012 International TSC Consensus Group were invited to meet face-to-face over two days at the 2018 World TSC Conference on July 25 and 26 in Dallas, TX, USA. Before the meeting, working group cochairs worked with group members via e-mail and telephone to (1) review TSC literature since the 2013 publication, (2) confirm or amend prior recommendations, and (3) provide new recommendations as required. Results Only two changes were made to clinical diagnostic criteria reported in 2013: “multiple cortical tubers and/or radial migration lines” replaced the more general term “cortical dysplasias,” and sclerotic bone lesions were reinstated as a minor criterion. Genetic diagnostic criteria were reaffirmed, including highlighting recent findings that some individuals with TSC are genetically mosaic for variants in TSC1 or TSC2. Changes to surveillance and management criteria largely reflected increased emphasis on early screening for electroencephalographic abnormalities, enhanced surveillance and management of TSC-associated neuropsychiatric disorders, and new medication approvals. Conclusions Updated TSC diagnostic criteria and surveillance and management recommendations presented here should provide an improved framework for optimal care of those living with TSC and their families

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