Outcomes and drivers of inappropriate dosing of non-vitamin K antagonist oral anticoagulants (NOACs) in patients with atrial fibrillation: a systematic review and meta-analysis.

OBJECTIVE: There has been limited systematic evaluation of outcomes and drivers of inappropriate non-vitamin K antagonist oral anticoagulants (NOACs) dosing among patients with atrial fibrillation (AF). This review identified and systematically evaluated literature on clinical and economic outcomes of inappropriate NOAC dosing and associated patient characteristics. METHODS: MEDLINE, Embase, Cochrane Library, International Pharmaceutical Abstracts, Econlit, PubMed and NHS EEDs databases were searched for English language observational studies from all geographies published between 2008 and 2020, examining outcomes of, or factors associated with, inappropriate NOAC dosing in adult patients with AF. RESULTS: One hundred and six studies were included in the analysis. Meta-analysis showed that compared with recommended NOAC dosing, off-label underdosing was associated with a null effect on stroke outcomes (ischaemic stroke and stroke/transient ischaemic attack (TIA), stroke/systemic embolism (SE) and stroke/SE/TIA). Meta-analysis of 15 studies examining clinical outcomes of inappropriate NOAC dosing found a null effect of underdosing on bleeding outcomes (major bleeding HR=1.04, 95% CI 0.90 to 1.19; p=0.625) but an increased risk of all-cause mortality (HR=1.28, 95% CI 1.10 to 1.49; p=0.006). Overdosing was associated with an increased risk of major bleeding (HR=1.41, 95% CI 1.07 to 1.85; p=0.013). No studies were found examining economic outcomes of inappropriate NOAC dosing. Narrative synthesis of 12 studies examining drivers of inappropriate NOAC dosing found that increased age, history of minor bleeds, hypertension, congestive heart failure and low creatine clearance (CrCl) were associated with an increased risk of underdosing. There was insufficient evidence to assess drivers of overdosing. CONCLUSIONS: Our analysis suggests that off-label underdosing of NOACs does not reduce bleeding outcomes. Patients prescribed off-label NOAC doses are at an increased risk of all-cause mortality. These data underscore the importance of prescriber adherence to NOAC dosing guidelines to achieve optimal clinical outcomes for patients with AF. PROSPERO REGISTRATION NUMBER: CRD42020219844.

The hemispheric contrast in cloud microphysical properties constrains aerosol forcing.

The change in planetary albedo due to aerosol-cloud interactions during the industrial era is the leading source of uncertainty in inferring Earth's climate sensitivity to increased greenhouse gases from the historical record. The variable that controls aerosol-cloud interactions in warm clouds is droplet number concentration. Global climate models demonstrate that the present-day hemispheric contrast in cloud droplet number concentration between the pristine Southern Hemisphere and the polluted Northern Hemisphere oceans can be used as a proxy for anthropogenically driven change in cloud droplet number concentration. Remotely sensed estimates constrain this change in droplet number concentration to be between 8 cm-3 and 24 cm-3 By extension, the radiative forcing since 1850 from aerosol-cloud interactions is constrained to be -1.2 W⋅m-2 to -0.6 W⋅m-2 The robustness of this constraint depends upon the assumption that pristine Southern Ocean droplet number concentration is a suitable proxy for preindustrial concentrations. Droplet number concentrations calculated from satellite data over the Southern Ocean are high in austral summer. Near Antarctica, they reach values typical of Northern Hemisphere polluted outflows. These concentrations are found to agree with several in situ datasets. In contrast, climate models show systematic underpredictions of cloud droplet number concentration across the Southern Ocean. Near Antarctica, where precipitation sinks of aerosol are small, the underestimation by climate models is particularly large. This motivates the need for detailed process studies of aerosol production and aerosol-cloud interactions in pristine environments. The hemispheric difference in satellite estimated cloud droplet number concentration implies preindustrial aerosol concentrations were higher than estimated by most models.

Publisher Correction: Critical Southern Ocean climate model biases traced to atmospheric model cloud errors.

'In the original HTML version of this Article, ref.12 was incorrectly cited in the first sentence of the first paragraph of the Introduction. The correct citation is ref. 2. This has now been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.'

Critical Southern Ocean climate model biases traced to atmospheric model cloud errors.

The Southern Ocean is a pivotal component of the global climate system yet it is poorly represented in climate models, with significant biases in upper-ocean temperatures, clouds and winds. Combining Atmospheric and Coupled Model Inter-comparison Project (AMIP5/CMIP5) simulations, with observations and equilibrium heat budget theory, we show that across the CMIP5 ensemble variations in sea surface temperature biases in the 40-60°S Southern Ocean are primarily caused by AMIP5 atmospheric model net surface flux bias variations, linked to cloud-related short-wave errors. Equilibration of the biases involves local coupled sea surface temperature bias feedbacks onto the surface heat flux components. In combination with wind feedbacks, these biases adversely modify upper-ocean thermal structure. Most AMIP5 atmospheric models that exhibit small net heat flux biases appear to achieve this through compensating errors. We demonstrate that targeted developments to cloud-related parameterisations provide a route to better represent the Southern Ocean in climate models and projections.

Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles.

Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions.

Verification of mid-ocean ballast water exchange using naturally occurring coastal tracers.

We examined methods for verifying whether or not ships have performed mid-ocean ballast water exchange (BWE) on four commercial vessels operating in the Pacific and Atlantic Oceans. During BWE, a ship replaces the coastal water in its ballast tanks with water drawn from the open ocean, which is considered to harbor fewer organisms capable of establishing in coastal environments. We measured concentrations of several naturally occurring chemical tracers (salinity, six trace elements, colored dissolved organic matter fluorescence and radium isotopes) along ocean transects and in ballast tanks subjected to varying degrees of BWE (0-99%). Many coastal tracers showed significant concentration changes due to BWE, and our ability to detect differences between exchanged and unexchanged ballast tanks was greatest under multivariate analysis. An expanded dataset, which includes additional geographic regions, is now needed to test the generality of our results.