Vertebral fractures assessed by dual-energy X-ray absorptiometry and all-cause mortality. The Tromsø Study 2007-2020

Vertebral fractures have been associated with increased mortality, but findings are inconclusive, and many vertebral fractures avoid clinical attention. We investigated this association in a general population of 2,476 older adults aged ≥55 years from Tromsø, Norway, who were followed over 2007–2020, using dual-energy x-ray absorptiometry (DXA) at baseline to evaluate vertebral fractures (mild, moderate, or severe). We used multiple Cox regression models to estimate hazard ratios (HRs) for all-cause mortality, adjusted for age, sex, body mass index, education, smoking, alcohol intake, cardiovascular disease, and respiratory disease. Mean follow-up in the cohort was 11.2 (standard deviation, 2.7) years; 341 participants (13.8%) had ≥1 vertebral fracture at baseline, and 636 participants (25.7%) died between baseline and follow-up. Full-adjustment models showed a nonsignificant association between vertebral fracture status (yes/no) and mortality. Participants with ≥3 vertebral fractures (HR = 2.43, 95% confidence interval: 1.57, 3.78) or ≥1 severe vertebral fracture (HR = 1.65, 95% confidence interval: 1.26, 2.15) had increased mortality compared with those with no vertebral fractures. Dual-energy x-ray absorptiometry–based screening could be a potent and feasible tool in detecting vertebral fractures that are often clinically silent yet independently associated with premature death. Our data indicated that detailed vertebral assessment could be warranted for a more accurate survival estimation

Validating risk models versus age alone for atrial fibrillation in a young Dutch population cohort:should atrial fibrillation risk prediction be expanded to younger community members?

BACKGROUND: Advancing age is the primary selection criterion for community screening for atrial fibrillation (AF), with selection often restricted to those aged ≥65 years. If multivariable models were shown to have considerable additional value over age alone in predicting AF risk among younger individuals, AF screening could be expanded to patients with lower age, but with high AF risk as per a validated risk model. METHODS: We validated risk models CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology model for AF) and FHS-AF (Framingham Heart Study model for AF), and risk scores CHA(2)DS(2)-VASc and CHA(2)DS(2)-VA, and presented their predictive abilities for 5-year and 10-year AF risk versus that of age alone in a young Dutch population cohort (PREVEND) free from AF at baseline. We assessed discrimination by the C-statistic and calibration by the calibration plot and stratified Kaplan-Meier plot using survey-weighted Cox models. RESULTS: During 5-year and 10-year follow-up there were n=98 (2.46/1000 person-years) and n=249 (3.29/1000 person-years) new AF cases, respectively, among 8265 participants with mean age 49±13 years. CHARGE-AF and FHS-AF both showed good discrimination for 5-year and 10-year AF (C-statistic range 0.83–0.86) with accurate calibration for 5-year AF, but overestimation of 10-year AF risk in highest-risk individuals. CHA(2)DS(2)-VASc and CHA(2)DS(2)-VA relatively underperformed. Age alone showed similar discrimination to that of CHARGE-AF and FHS-AF both in the overall, young PREVEND cohort and in subgroups for lower age and lower stroke risk. CONCLUSION: Multivariable models accurately discriminate for 5-year and 10-year AF risk among young European community-dwelling individuals. However, their additional discriminatory value over age alone was limited. Selection strategies for primary AF screening using multivariable models should not be expanded to younger individuals

Cardiovascular and renal multimorbidity increase risk of atrial fibrillation in the PREVEND cohort

Objective: Atrial fibrillation (AF) is a condition that occurs in the presence of comorbidities. With the accumulation of comorbidities (multimorbidity), some combinations may more often occur together than others. Information on the impact of clustering of these on incident AF is sparse. We aimed to investigate clustering of cardiovascular and renal comorbidities and study the association between comorbidity clusters and incident AF.Methods: We used the community-based Prevention of Renal and Vascular ENd-stage Disease (PREVEND) cohort in which 8592 individuals participated. Latent class analysis was performed to assess clustering of 10 cardiovascular and renal comorbidities.Results: We excluded individuals with prior AF or missing ECG data, leaving 8265 individuals for analysis (mean age 48.9±12.6 years, 50.2% women). During 9.2±2.1 years of follow-up, 251 individuals (3.0%) developed AF. A model with three clusters was the optimal model, with one cluster being young (44.5±10.8 years) and healthy, carrying a low (1.0%) risk of incident AF; one cluster being older (63.0±8.4 years) and multimorbid, carrying a high (16.2%) risk of incident AF and a third middle-aged (57.0±11.3 years), obese and hypertensive cluster carrying an intermediate risk (5.9%) of incident AF. While the prevalence of the comorbidities differed between classes, no clear combination(s) of comorbidities was observed within the classes.Conclusions: We identified three clusters of comorbidities in individuals in the community-based PREVEND cohort. The three clusters contained different amount of comorbidities carrying different risks of incident AF. However, there were no differences between the clusters regarding specific combination(s) of comorbidities.</p

Cardiovascular and renal multimorbidity increase risk of atrial fibrillation in the PREVEND cohort

Objective: Atrial fibrillation (AF) is a condition that occurs in the presence of comorbidities. With the accumulation of comorbidities (multimorbidity), some combinations may more often occur together than others. Information on the impact of clustering of these on incident AF is sparse. We aimed to investigate clustering of cardiovascular and renal comorbidities and study the association between comorbidity clusters and incident AF.Methods: We used the community-based Prevention of Renal and Vascular ENd-stage Disease (PREVEND) cohort in which 8592 individuals participated. Latent class analysis was performed to assess clustering of 10 cardiovascular and renal comorbidities.Results: We excluded individuals with prior AF or missing ECG data, leaving 8265 individuals for analysis (mean age 48.9±12.6 years, 50.2% women). During 9.2±2.1 years of follow-up, 251 individuals (3.0%) developed AF. A model with three clusters was the optimal model, with one cluster being young (44.5±10.8 years) and healthy, carrying a low (1.0%) risk of incident AF; one cluster being older (63.0±8.4 years) and multimorbid, carrying a high (16.2%) risk of incident AF and a third middle-aged (57.0±11.3 years), obese and hypertensive cluster carrying an intermediate risk (5.9%) of incident AF. While the prevalence of the comorbidities differed between classes, no clear combination(s) of comorbidities was observed within the classes.Conclusions: We identified three clusters of comorbidities in individuals in the community-based PREVEND cohort. The three clusters contained different amount of comorbidities carrying different risks of incident AF. However, there were no differences between the clusters regarding specific combination(s) of comorbidities.</p

Atrial fibrillation detected at screening is not a benign condition:Outcomes in screen-detected versus clinically detected atrial fibrillation. Results from the Prevention of Renal and Vascular End-stage Disease (PREVEND) study

AIMS: It is unknown whether screen-detected atrial fibrillation (AF) carries cardiovascular risks similar to clinically detected AF. We aimed to compare clinical outcomes between individuals with screen-detected and clinically detected incident AF. METHODS: We studied 8265 participants (age 49 ± 13 years, 50% women) without prevalent AF from the community-based Prevention of Renal and Vascular End-stage Disease (PREVEND) study. By design of the PREVEND study, 70% of participants had a urinary albumin concentration >10 mg/L. Participants underwent 12-lead ECG screening at baseline and every 3 years. AF was considered screen-detected when first diagnosed during a study visit and clinically detected when first diagnosed during a hospital visit. We analysed data from the baseline visit (1997–1998) up to the third follow-up visit (2008). We used Cox regression with screen-detected and clinically detected AF as time-varying covariates to study the association of screen-detected and clinically detected AF with all-cause mortality, incident heart failure (HF) and vascular events. RESULTS: During a follow-up of 9.8 ± 2.3 years, 265 participants (3.2%) developed incident AF, of whom 60 (23%) had screen-detected AF. The majority of baseline characteristics were comparable between individuals with screen-detected and clinically detected AF. Unadjusted, both screen-detected and clinically detected AF were strongly associated with mortality, incident HF, and vascular events. After multivariable adjustment, screen-detected and clinically detected AF remained significantly associated with mortality (HR 2.21 (95% CI 1.09 to 4.47) vs 2.95 (2.18 to 4.00), p for difference=0.447) and incident HF (4.90 (2.28 to 10.57) vs 3.98 (2.49 to 6.34), p for difference=0.635). After adjustment, screen-detected AF was not significantly associated with vascular events, whereas clinically detected AF was (1.12 (0.46 to 2.71) vs 1.92 (1.21 to 3.06), p for difference=0.283). CONCLUSION: Screen-detected incident AF was associated with an increased risk of adverse outcomes, especially all-cause mortality and incident HF. The risk of outcomes was not significantly different between screen-detected AF and clinically detected AF