Mortality and ventricular arrhythmias in patients on d,l-sotalol for rhythm control of atrial fibrillation: A nationwide cohort study.

BACKGROUND: Use of d,l-sotalol for rhythm control in patients with atrial fibrillation (AF) has raised safety concerns. Previous randomized studies are few and not designed for mortality outcome. OBJECTIVE: The purpose of this study was to compare the incidences of mortality and ventricular arrhythmias in AF patients treated with d,l-sotalol for rhythm control vs matched control patients treated with cardioselective beta-blockers. METHODS: This population-based cohort study included AF patients from the Swedish National Patient Registry (2006-2017) who underwent rhythm control after a second cardioversion. Incidence rates (IRs) and adjusted hazard ratios (aHRs) for mortality and a composite endpoint of cardiac arrest/death and ventricular arrhythmias were calculated for the overall cohort and a 1:1 propensity score matched cohort of d,l-sotalol vs beta-blocker treatment. RESULTS: Among patient treated with d,l-sotalol (n = 4987) and beta-blocker (n = 27,078) (mean follow-up 458 days), all-cause mortality was lower in patients treated with d,l-sotalol: IR 1.21; 95% confidence interval 0.95-1.52 vs 2.42 (2.26-2.60) deaths per 100 patient-years; aHR 0.66 (0.52-0.83). The difference in mortality persisted in the propensity score matched comparison (n = 4953 in each group): aHR 0.63 (0.48-0.86). No differences were observed in the composite outcome: IR in propensity cohorts 2.13 (1.78-2.52) vs 2.07 (1.73-2.53) events per 100 years; aHR 1.01 (0.78-1.29). CONCLUSION: There was no excess mortality with d,l-sotalol compared with cardioselective beta-blockers in patients undergoing rhythm control treatment for AF after a second cardioversion. Our results indicate that the risk associated with d,l-sotalol treatment for AF can be mitigated by careful patient selection and strict adherence to follow-up protocols.

Estimating biomass and soil carbon change at the level of forest stands using repeated forest surveys assisted by airborne laser scanner data.

BACKGROUND: Under the growing pressure to implement mitigation actions, the focus of forest management is shifting from a traditional resource centric view to incorporate more forest ecosystem services objectives such as carbon sequestration. Estimating the above-ground biomass in forests using airborne laser scanning (ALS) is now an operational practice in Northern Europe and is being adopted in many parts of the world. In the boreal forests, however, most of the carbon (85%) is stored in the soil organic (SO) matter. While this very important carbon pool is "invisible" to ALS, it is closely connected and feeds from the growing forest stocks. We propose an integrated methodology to estimate the changes in forest carbon pools at the level of forest stands by combining field measurements and ALS data. RESULTS: ALS-based models of dominant height, mean diameter, and biomass were fitted using the field observations and were used to predict mean tree biophysical properties across the entire study area (50 km2) which was in turn used to estimate the biomass carbon stocks and the litter production that feeds into the soil. For the soil carbon pool estimation, we used the Yasso15 model. The methodology was based on (1) approximating the initial soil carbon stocks using simulations; (2) predicting the annual litter input based on the predicted growing stocks in each cell; (3) predicting the soil carbon dynamics of the annual litter using the Yasso15 soil carbon model. The estimated total carbon change (standard errors in parenthesis) for the entire area was 0.741 (0.14) Mg ha-1 yr-1. The biomass carbon change was 0.405 (0.13) Mg ha-1 yr-1, the litter carbon change (e.g., deadwood and leaves) was 0.346 (0.027) Mg ha-1 yr-1, and the change in SO carbon was - 0.01 (0.003) Mg ha-1 yr-1. CONCLUSIONS: Our results show that ALS data can be used indirectly through a chain of models to estimate soil carbon changes in addition to changes in biomass at the primary level of forest management, namely the forest stands. Having control of the errors contributed by each model, the stand-level uncertainty can be estimated under a model-based inferential approach.