The Feasibility of Deriving the Electronic Frailty Index from Australian General Practice Records

Purpose: Frailty is a prevalent condition in older adults. Identification of frailty using an electronic Frailty Index (eFI) has been successfully implemented across general practices in the United Kingdom. However, in Australia, the eFI remains understudied. Therefore, we aimed to (i) examine the feasibility of deriving an eFI from Australian general practice records and (ii) describe the prevalence of frailty as measured by the eFI and the prevalence with socioeconomic status and geographic remoteness. Participants and Methods: This retrospective analysis included patients (≥70 years) attending any one of >700 general practices utilizing the Australian MedicineInsight data platform, 2017–2018. A 36-item eFI was derived using standard methodology, with frailty classified as mild (scores 0.13–0.24); moderate (0.25–0.36) or severe (≥0.37). Socioeconomic status (Socio-Economic Indexes for Areas (SEIFA) index)) and geographic remoteness (Australian Statistical Geography Standard (ASGC) remoteness areas) were also examined. Results: In total, 79,251 patients (56% female) were included, mean age 80.0 years (SD 6.5); 37.4% (95% CI 37.0–37.7) were mildly frail, 16.7% (95% CI 16.4–16.9) moderately frail, 4.8% (95% CI 4.7–5.0) severely frail. Median eFI score was 0.14 (IQR 0.08 to 0.22); maximum eFI score was 0.69. Across all age groups, moderate and severe frailty was significantly more prevalent in females (P < 0.001). Frailty severity increased with increasing age (P < 0.001) and was strongly associated with socioeconomic disadvantage (P < 0.001) but not with geographic remoteness. Conclusion: Frailty was identifiable from routinely collected general practice data. Frailty was more prevalent in socioeconomically disadvantaged groups, women and older patients and existed in all levels of remoteness. Routine implementation of an eFI could inform interventions to prevent or reduce frailty in all older adults, regardless of location

Evidence for the existence of powder sub-populations in micronized materials : Aerodynamic size-fractions of aerosolized powders possess distinct physicochemical properties

This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.Purpose: To investigate the agglomeration behaviour of the fine ( 12.8 µm) particle fractions of salmeterol xinafoate (SX) and fluticasone propionate (FP) by isolating aerodynamic size fractions and characterising their physicochemical and re-dispersal properties. Methods: Aerodynamic fractionation was conducted using the Next Generation Impactor (NGI). Re-crystallized control particles, unfractionated and fractionated materials were characterized for particle size, morphology, crystallinity and surface energy. Re-dispersal of the particles was assessed using dry dispersion laser diffraction and NGI analysis. Results: Aerosolized SX and FP particles deposited in the NGI as agglomerates of consistent particle/agglomerate morphology. SX particles depositing on Stages 3 and 5 had higher total surface energy than unfractionated SX, with Stage 5 particles showing the greatest surface energy heterogeneity. FP fractions had comparable surface energy distributions and bulk crystallinity but differences in surface chemistry. SX fractions demonstrated higher bulk disorder than unfractionated and re-crystallized particles. Upon aerosolization, the fractions differed in their intrinsic emission and dispersion into a fine particle fraction (< 5.0 µm). Conclusions: Micronized powders consisted of sub-populations of particles displaying distinct physicochemical and powder dispersal properties compared to the unfractionated bulk material. This may have implications for the efficiency of inhaled drug deliveryPeer reviewe

Calculating the surface energies of crystals on a face-specific and whole particle basis: Case study of the α- and β-polymorphic forms of L-glutamic acid

Molecular-scale modelling for predicting surface energies on a face-specific and whole particle basis is applied to all the crystallographically-independent surfaces of L-glutamic acid forms. The predicted data is found to be in good general agreement with measured surface energies using inverse gas chromatography and Washburn capillary rise techniques with the former revealing higher values compared to the prediction, perhaps consistent with the polar (zwitterionic) nature of this material. This fusion of experimental and computational data provides a high-fidelity definition of the face-by-face breakdown of the energetic anisotropy of the crystals. There is increasing industrial interest in defining the potential impact of whole particle properties on the performance of formulated drug product and their manufacturability especially as the community accelerates the molecule to medicine journey. The overall molecular modelling approach highlights its application in designing ingredients for optimising face-specific particle surface energies for product formulatability particularly in early phase process development

Measurement of the 1S0^{1}S_{0} neutron-neutron effective range in neutron-deuteron breakup

We report the most precise determination of the $^{1}S_{0}$ neutron-neutron effective range parameter $(r_{nn})$ from neutron-neutron quasifree scattering in neutron-deuteron breakup. The experiment setup utilized a collimated beam of 15.5 MeV neutrons and an array of eight neutron detectors positioned at angles sensitive to several quasifree scattering kinematic configurations. The two neutrons emitted from the breakup reaction were detected in coincidence and time-of-flight techniques were used to determine their energies. The beam-target luminosity was measured in-situ with the yields from neutron-deuteron elastic scattering. Rigorous Faddeev-type calculations using the CD Bonn nucleon-nucleon potential were fit to our cross-section data to determine the value of $r_{nn}$. The analysis was repeated using a semilocal momentum-space regularized $N^{4}LO^{+}$ chiral interaction potential. We obtained values of $r_{nn}=2.86 \pm 0.01 (stat) \pm 0.10 (sys)$ fm and $r_{nn}=2.87 \pm 0.01 (stat) \pm 0.10 (sys)$ fm using the CD Bonn and $N^{4}LO^{+}$ potentials, respectively. Our results are consistent with charge symmetry and previously reported values of $r_{nn}$

Hepatitis C in HIV-infected individuals: cure and control, right now

For persons living with HIV, hepatitis C is a major public health problem that must be controlled and could be eliminated. The challenge arises because the hepatitis C virus (HCV) is prevalent among HIV-infected persons in most parts of the world, because HIV worsens all HCV outcomes, and because HCV may add additional individual economic and psychosocial complications to HIV disease. Despite the major benefits of antiretroviral therapy on HIV outcomes, antiretroviral therapy is not sufficient to halt the complications of HCV. Nonetheless, HCV can be controlled at all stages, including prevention of infection and cure. Thus, HCV is an eradicable disease. There are significant inequalities worldwide in HCV control that could markedly constrain the impact of these measures

Formulation Pre-screening of Inhalation Powders Using Computational Atom–Atom Systematic Search Method

The synthonic modeling approach provides a molecule-centered understanding of the surface properties of crystals. It has been applied extensively to understand crystallization processes. This study aimed to investigate the functional relevance of synthonic modeling to the formulation of inhalation powders by assessing cohesivity of three active pharmaceutical ingredients (APIs, fluticasone propionate (FP), budesonide (Bud), and salbutamol base (SB)) and the commonly used excipient, α-lactose monohydrate (LMH). It is found that FP (−11.5 kcal/mol) has a higher cohesive strength than Bud (−9.9 kcal/mol) or SB (−7.8 kcal/mol). The prediction correlated directly to cohesive strength measurements using laser diffraction, where the airflow pressure required for complete dispersion (CPP) was 3.5, 2.0, and 1.0 bar for FP, Bud, and SB, respectively. The highest cohesive strength was predicted for LMH (−15.9 kcal/mol), which did not correlate with the CPP value of 2.0 bar (i.e., ranking lower than FP). High FP–LMH adhesive forces (−11.7 kcal/mol) were predicted. However, aerosolization studies revealed that the FP–LMH blends consisted of agglomerated FP particles with a large median diameter (∼4–5 μm) that were not disrupted by LMH. Modeling of the crystal and surface chemistry of LMH identified high electrostatic and H-bond components of its cohesive energy due to the presence of water and hydroxyl groups in lactose, unlike the APIs. A direct comparison of the predicted and measured cohesive balance of LMH with APIs will require a more in-depth understanding of highly hydrogen-bonded systems with respect to the synthonic engineering modeling tool, as well as the influence of agglomerate structure on surface–surface contact geometry. Overall, this research has demonstrated the possible application and relevance of synthonic engineering tools for rapid pre-screening in drug formulation and design

Capturing Ecosystem Services, Stakeholders' Preferences and Trade-Offs in Coastal Aquaculture Decisions : A Bayesian Belief Network Application

Aquaculture activities are embedded in complex social-ecological systems. However, aquaculture development decisions have tended to be driven by revenue generation, failing to account for interactions with the environment and the full value of the benefits derived from services provided by local ecosystems. Trade-offs resulting from changes in ecosystem services provision and associated impacts on livelihoods are also often overlooked. This paper proposes an innovative application of Bayesian belief networks - influence diagrams - as a decision support system for mediating trade-offs arising from the development of shrimp aquaculture in Thailand. Senior experts were consulted (n = 12) and primary farm data on the economics of shrimp farming (n = 20) were collected alongside secondary information on ecosystem services, in order to construct and populate the network. Trade-offs were quantitatively assessed through the generation of a probabilistic impact matrix. This matrix captures nonlinearity and uncertainty and describes the relative performance and impacts of shrimp farming management scenarios on local livelihoods. It also incorporates export revenues and provision and value of ecosystem services such as coastal protection and biodiversity. This research shows that Bayesian belief modeling can support complex decision-making on pathways for sustainable coastal aquaculture development and thus contributes to the debate on the role of aquaculture in social-ecological resilience and economic development