Osteoporosis and increased risk of fractures

Osteoporosis is a common condition in older people. This condition leads to increased risk of fractures and is associated with morbidity and mortality. The number of patients with osteoporosis will increase significantly in the years to come due to the increasing numbers of older people and increasing life expectancy. This will be accompanied by increasing demand for care and clinical practice will be faced with questions about therapeutic options and the optimal treatment duration for patients with osteoporosis or increased risk of fractures. In this educational article, we are using practical questions to provide an overview of pathophysiology, diagnostics and treatment of osteoporosis and increased risk of fractures

Rate control drugs differ in the prevention of progression of atrial fibrillation

AIMS: We hypothesize that in patients with paroxysmal atrial fibrillation (AF), verapamil is associated with lower AF progression compared to beta blockers or no rate control. METHODS AND RESULTS: In this pre-specified post hoc analysis of the RACE 4 randomized trial, the effect of rate control medication on AF progression in paroxysmal AF was analysed. Patients using Vaughan-Williams Class I or III antiarrhythmic drugs were excluded. The primary outcome was a composite of first electrical cardioversion (ECV), chemical cardioversion (CCV), or atrial ablation. Event rates are displayed using Kaplan–Meier curves and multivariable Cox regression analyses are used to adjust for baseline differences. Out of 666 patients with paroxysmal AF, 47 used verapamil, 383 used beta blockers, and 236 did not use rate control drugs. The verapamil group was significantly younger than the beta blocker group and contained more men than the no rate control group. Over a mean follow-up of 37 months, the primary outcome occurred in 17% in the verapamil group, 33% in the beta blocker group, and 33% in the no rate control group (P = 0.038). After adjusting for baseline characteristics, patients using verapamil have a significantly lower chance of receiving ECV, CCV, or atrial ablation compared to patients using beta blockers [hazard ratio (HR) 0.40, 95% confidence interval (CI) 0.19–0.83] and no rate control (HR 0.64, 95% CI 0.44–0.93). CONCLUSION: In patients with newly diagnosed paroxysmal AF, verapamil was associated with less AF progression, as compared to beta blockers and no rate control

Osteoporosis and increased risk of fractures

Osteoporosis is a common condition in older people. This condition leads to increased risk of fractures and is associated with morbidity and mortality. The number of patients with osteoporosis will increase significantly in the years to come due to the increasing numbers of older people and increasing life expectancy. This will be accompanied by increasing demand for care and clinical practice will be faced with questions about therapeutic options and the optimal treatment duration for patients with osteoporosis or increased risk of fractures. In this educational article, we are using practical questions to provide an overview of pathophysiology, diagnostics and treatment of osteoporosis and increased risk of fractures

A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting

Background The COVID-19 pandemic has a large impact worldwide and is known to particularly affect the older population. This paper outlines the protocol for external validation of prognostic models predicting mortality risk after presentation with COVID-19 in the older population. These prognostic models were originally developed in an adult population and will be validated in an older population (≥ 70 years of age) in three healthcare settings: the hospital setting, the primary care setting, and the nursing home setting. Methods Based on a living systematic review of COVID-19 prediction models, we identified eight prognostic models predicting the risk of mortality in adults with a COVID-19 infection (five COVID-19 specific models: GAL-COVID-19 mortality, 4C Mortality Score, NEWS2 + model, Xie model, and Wang clinical model and three pre-existing prognostic scores: APACHE-II, CURB65, SOFA). These eight models will be validated in six different cohorts of the Dutch older population (three hospital cohorts, two primary care cohorts, and a nursing home cohort). All prognostic models will be validated in a hospital setting while the GAL-COVID-19 mortality model will be validated in hospital, primary care, and nursing home settings. The study will include individuals ≥ 70 years of age with a highly suspected or PCR-confirmed COVID-19 infection from March 2020 to December 2020 (and up to December 2021 in a sensitivity analysis). The predictive performance will be evaluated in terms of discrimination, calibration, and decision curves for each of the prognostic models in each cohort individually. For prognostic models with indications of miscalibration, an intercept update will be performed after which predictive performance will be re-evaluated. Discussion Insight into the performance of existing prognostic models in one of the most vulnerable populations clarifies the extent to which tailoring of COVID-19 prognostic models is needed when models are applied to the older population. Such insight will be important for possible future waves of the COVID-19 pandemic or future pandemics

Processes Underlying Glycemic Deterioration in Type 2 Diabetes: An IMI DIRECT Study

Objective We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D). Research Design and Methods 732 recently diagnosed T2D patients from the IMI-DIRECT study were extensively phenotyped over three years, including measures of insulin sensitivity (OGIS), β-cell glucose sensitivity (GS) and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA1c deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression. Results Faster HbA1c progression was independently associated with faster deterioration of OGIS and GS, and increasing CLIm; visceral or liver fat, HDL-cholesterol and triglycerides had further independent, though weaker, roles (R2=0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from AUROC=0.94). The proportion of fast progressors was reduced from 56% to 8-10% in subgroups in which only one trait among OGIS, GS and CLIm was relatively stable (odds ratios 0.07 to 0.09). T2D polygenic risk score and baseline pancreatic fat, GLP-1, glucagon, diet, and physical activity did not show an independent role. Conclusions Deteriorating insulin sensitivity and β-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of T2D patients in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, β-cell function, and insulin clearance may be relevant to prevent progression

Preparing for future pandemics:frailty associates with mortality in hospitalised older people during the entire COVID-19 pandemic, a Dutch multicentre cohort study

Purpose: Viral mutations and improved prevention or treatment options may have changed the association of frailty with mortality throughout the COVID-19 pandemic. We investigated how associations of frailty with in-hospital mortality changed throughout the pandemic in older people hospitalised for COVID-19. Methods: The COVID-OLD study included COVID-19 patients aged ≥ 70 years hospitalised during the first (early 2020), second (late 2020), third (late 2021) or fourth wave (early 2022). Based on the clinical frailty scale, patients were categorised as fit (1–3), pre-frail (4–5) or frail (6–9). Associations of frailty with in-hospital mortality were assessed with pairwise comparisons with fit as reference category and modelled using binary logistic regression adjusted for age and sex. Results: This study included 2362 patients (mean age 79.7 years, 60% men). In the first wave, in-hospital mortality was 46% in patients with frailty and 27% in fit patients. In-hospital mortality decreased in each subsequent wave to 25% in patients with frailty and 11% in fit patients in the fourth wave. After adjustments, an overall higher risk of in-hospital mortality was found in frail (OR 2.26, 95% CI: 1.66–3.07) and pre-frail (OR 1.73, 95% CI: 1.27–2.35) patients compared to fit patients, which did not change over time (p for interaction = 0.74). Conclusions: Frailty remained associated with a higher risk of in-hospital mortality throughout the entire COVID-19 pandemic, although overall in-hospital mortality rates decreased. Frailty therefore remains a relevant risk factor in all stages of a pandemic and is important to consider in prevention and treatment guidelines for future pandemics.</p

A meta-analysis of previous falls and subsequent fracture risk in cohort studies

NC Harvey acknowledges funding from the UK Medical Research Council (MC_PC_21003; MC_PC_21001). The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through 75N92021D00001, 75N92021D00002, 75N92021D00003, 75N92021D00004, and 75N92021D00005. Funding for the MrOS USA study comes from the National Institute on Aging (NIA), the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), the National Center for Advancing Translational Sciences (NCATS), and NIH Roadmap for Medical Research under the following grant numbers: U01 AG027810, U01 AG042124, U01 AG042139, U01 AG042140, U01 AG042143, U01 AG042145, U01 AG042168, U01 AR066160, and UL1 TR000128. Funding for the SOF study comes from the National Institute on Aging (NIA), and the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), supported by grants (AG05407, AR35582, AG05394, AR35584, and AR35583). Funding for the Health ABC study was from the Intramural research program at the National Institute on Aging under the following contract numbers: NO1-AG-6–2101, NO1-AG-6–2103, and NO1-AG-6–2106.Peer reviewedPostprin

Previous fracture and subsequent fracture risk : a meta-analysis to update FRAX

A large international meta-analysis using primary data from 64 cohorts has quantified the increased risk of fracture associated with a previous history of fracture for future use in FRAX. The aim of this study was to quantify the fracture risk associated with a prior fracture on an international basis and to explore the relationship of this risk with age, sex, time since baseline and bone mineral density (BMD). We studied 665,971 men and 1,438,535 women from 64 cohorts in 32 countries followed for a total of 19.5 million person-years. The effect of a prior history of fracture on the risk of any clinical fracture, any osteoporotic fracture, major osteoporotic fracture, and hip fracture alone was examined using an extended Poisson model in each cohort. Covariates examined were age, sex, BMD, and duration of follow-up. The results of the different studies were merged by using the weighted β-coefficients. A previous fracture history, compared with individuals without a prior fracture, was associated with a significantly increased risk of any clinical fracture (hazard ratio, HR = 1.88; 95% CI = 1.72-2.07). The risk ratio was similar for the outcome of osteoporotic fracture (HR = 1.87; 95% CI = 1.69-2.07), major osteoporotic fracture (HR = 1.83; 95% CI = 1.63-2.06), or for hip fracture (HR = 1.82; 95% CI = 1.62-2.06). There was no significant difference in risk ratio between men and women. Subsequent fracture risk was marginally downward adjusted when account was taken of BMD. Low BMD explained a minority of the risk for any clinical fracture (14%), osteoporotic fracture (17%), and for hip fracture (33%). The risk ratio for all fracture outcomes related to prior fracture decreased significantly with adjustment for age and time since baseline examination. A previous history of fracture confers an increased risk of fracture of substantial importance beyond that explained by BMD. The effect is similar in men and women. Its quantitation on an international basis permits the more accurate use of this risk factor in case finding strategies

World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions

BACKGROUND: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. METHODS: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40-80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. FINDINGS: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629-0·741) to 0·833 (0·783-0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40-64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. INTERPRETATION: We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. FUNDING: World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk