Prescriber decision-making on antithrombotic therapy after endovascular intervention for peripheral artery disease: a protocol for a discrete choice experiment.

INTRODUCTION: Peripheral artery disease (PAD) is a major risk factor for cardiovascular morbidity and mortality, despite surgical and endovascular treatments. Emerging evidence supports the use of immediate antithrombotic medications after endovascular intervention for PAD, however, there is a lack of consensus regarding choice and duration of antithrombotic therapy. Prescriber decision-making is a complex process, with prior studies demonstrating patient factors can influence variability in antithrombotic therapy for PAD. However, it remains unclear the relative contribution of these factors. This paper describes a planned study that aims to (1) determine the influence of patient factors on clinician preference for antithrombotic therapy following endovascular intervention and (2) compare differences in prescribing preferences between consultant vascular surgeons and trainees. METHODS AND ANALYSIS: This cross-sectional survey will evaluate antithrombotic prescribing choices using a discrete choice experiment (DCE) that has been developed and piloted for this study. A list of attributes and levels was generated using a mixed-methods approach. This included an extensive literature review and semistructured interviews with prescribing clinicians. Following final selection of included attributes, specialised software was used to construct a D-efficient design for the DCE questionnaire. The electronic questionnaire will be administered to vascular trainees and consultant surgeons across Australia. These data will be analysed using multinomial logistic regression, treating the decision to prescribe antithrombotic therapy as a function of both the attributes of the two alternatives, as well as characteristics of the respondent. Latent class analysis will be used to explore heterogeneity of responses. ETHICS AND DISSEMINATION: Ethics approval was obtained from the University of Sydney Human Ethics committee (2023/474). The results of this study will be published in peer-reviewed journals and presented at national vascular surgical conferences. These results will be used to improve understanding how clinicians make prescribing decisions and to inform future strategy to enhance guideline-directed prescribing.

Frail patients having vascular surgery during the early COVID-19 pandemic experienced high rates of adverse perioperative events and amputation.

BACKGROUND: Frailty predicts adverse perioperative outcomes and increased mortality in patients having vascular surgery. Frailty assessment is a potential tool to inform resource allocation, and shared decision-making about vascular surgery in the resource constrained COVID-19 pandemic environment. This cohort study describes the prevalence of frailty in patients having vascular surgery and the association between frailty, mortality and perioperative outcomes. METHODS: The COVID-19 Vascular Service in Australia (COVER-AU) prospective cohort study evaluates 30-day and six-month outcomes for consecutive patients having vascular surgery in 11 Australian vascular units, March-July 2020. The primary outcome was mortality, with secondary outcomes procedure-related outcomes and hospital utilization. Frailty was assessed using the nine-point visual Clinical Frailty Score, scores of 5 or more considered frail. RESULTS: Of the 917 patients enrolled, 203 were frail (22.1%). The 30 day and 6 month mortality was 2.0% (n = 20) and 5.9% (n = 35) respectively with no significant difference between frail and non-frail patients (OR 1.68, 95%CI 0.79-3.54). However, frail patients stayed longer in hospital, had more perioperative complications, and were more likely to be readmitted or have a reoperation when compared to non-frail patients. At 6 months, frail patients had twice the odds of major amputation compared to non-frail patients, after adjustment (OR 2.01; 95% CI 1.17-3.78), driven by a high rate of amputation during the period of reduced surgical activity. CONCLUSION: Our findings highlight that older, frail patients, experience potentially preventable adverse outcomes and there is a need for targeted interventions to optimize care, especially in times of healthcare stress.

Chronic occlusion of the thoracic aorta: a novel cause of pleuropericardial effusions and pancytopenia.

A 57-year-old man had presented with a 6-month history of worsening dyspnea, renal failure, hypertension, pancytopenia, and a continuous machinery murmur. Imaging studies revealed pleuropericardial effusions that recurred despite aspiration and suprarenal mid-thoracic aortic occlusion (AO) with extensive collateral vessels to the chest wall, rectus sheath, and diaphragm. A right axillofemoral bypass transformed his clinical course. The murmurs, renal failure, pleuropericardial drainage, and pancytopenia resolved, and his hypertension had markedly improved. The association of chronic AO with pleuropericardial effusions without peripheral edema or ascites was most likely due to increased supradiaphragmatic interstitial pressure, and the bone marrow hypoperfusion likely explains the pancytopenia. In addition to posing diagnostic challenges, chronic AO reveals unique insights into the pathogenesis of pleuropericardial effusions and pancytopenia.

Understanding the Role and Value of Process Quality Indicators in Older Vascular Surgery Inpatients.

BACKGROUND: Despite the development of geriatrics surgery process quality indicators (QIs), few studies have reported on these QIs in routine surgical practice. Even less is known about the links between these QIs and clinical outcomes, and patient characteristics. We aimed to measure geriatrics surgery process QIs, and investigate the association between process QIs and outcomes, and QIs and patient characteristics, in hospitalized older vascular surgery patients. METHODS: This was a prospective cohort study of 150 consecutive patients aged ≥ 65 years admitted to a tertiary vascular surgery unit. Occurrence of geriatrics surgery process QIs as part of routine vascular surgery care was measured. Associations between QIs and high-risk patient characteristics, and QIs and clinical outcomes were assessed using clustered heatmaps. RESULTS: QI occurrence rate varied substantially from 2% to 93%. Some QIs, such as cognition and delirium screening, documented treatment preferences, and geriatrician consultation were infrequent and clustered with high-risk patient characteristcs. There were two major process-outcome clusters: (a) multidisciplinary consultations, communication and screening-based process QIs with multiple adverse outcomes, and (b) documentation and prescribing-related QIs with fewer adverse outcomes. CONCLUSIONS: Clustering patterns of process QIs with clinical outcomes are complex, and there is a differential occurrence of QIs by patient characteristics. Prospective intervention studies that report on implemented QIs, outcomes and patient characteristics are needed to better understand the causal pathways between process QIs and outcomes, and to help prioritize targets for quality improvement in the care of older surgical patients.

Five-year lung cancer mortality risk analysis and topography in Xuan Wei: a spatiotemporal correlation analysis.

BACKGROUND: In Xuan Wei, China, the lung cancer mortality rate is rising significantly more than that of the nation overall. However, it remains unclear 1) if improved diagnosis can just partially explain this observation and how other local risk factors may be correlated with the lung cancer mortality rate and 2) how the lung cancer mortality rates differ within Xuan Wei and how these spatiotemporal patterns are linked with local risk factors. To increase etiological knowledge, this study evaluated the spatial and temporal distributions of the health effects (the lung cancer mortality rates) from 2011 to 2015. METHODS: Four steps of spatial analysis were applied, as follows: 1) hotspot analysis to determine the geographical patterns of lung cancer mortality, 2) spatially-weighted sum to identify areas with higher health risks, 3) bivariate statistical analysis to assess the overall correlation between coal mines and lung cancer mortality, and 4) geographically-weighted regression to test for correlations among different towns within Xuan Wei. RESULTS: Women had higher lung cancer mortality rates than those in men, with an increasing trend in both sexes over time. The incidence rates in Laibin Town were the highest in Xuan Wei every year. Over the 5-year study period, the lung cancer mortality was increasingly concentrated in Laibin, Shuanglong, and Longchang, where the smoky coal mines are most concentrated. The population-level health risks from the coal mine in Xuan Wei were mapped and divided into five types of risk areas (Type I - Type IV). Correlation analysis revealed that there was no significant correlation between lung cancer mortality as a whole and coal mine distribution during the 5-year study period. However, the geographically-weighted regression revealed a stronger correlation in medium (Type III) and second-lowest (Type IV) health risks. CONCLUSIONS: Xuan Wei lung cancer mortality has increased continuously since the third national retrospective surveys on the causes of death by the Ministry of Health of the People's Republic of China (2004-2005), especially for local women and residents over 35 years of age. Geographically, lung cancer in Xuan Wei showed unique spatiotemporal clustering. The local lung cancer mortality was significantly correlated with the smoky coal mine geographically. Some specific towns (Laibin, Shuanglong, and Longchang) within Xuan Wei manifested high correlations between lung cancer mortality and coal mines. The effects of coal mines on lung cancer mortality rates also spread geographically outward from these areas. Public health concern regarding lung cancer in Xuan Wei should prioritize higher-risk towns surrounded by smoking coal mines. Intervention strategies for particular toxic coal types require further studies on their chemical characteristics and mechanisms of carcinogenesis. Additional studies are also warranted to systematically examine the local environmental health risks related to coal industries and combustion air pollution and eventually to conduct early screening of lung cancer for local people who are more exposed to smoky coal in high-risk areas.

Land use regression modelling of air pollution in high density high rise cities: A case study in Hong Kong.

Land use regression (LUR) is a common method of predicting spatial variability of air pollution to estimate exposure. Nitrogen dioxide (NO2), nitric oxide (NO), fine particulate matter (PM2.5), and black carbon (BC) concentrations were measured during two sampling campaigns (April-May and November-January) in Hong Kong (a prototypical high-density high-rise city). Along with 365 potential geospatial predictor variables, these concentrations were used to build two-dimensional land use regression (LUR) models for the territory. Summary statistics for combined measurements over both campaigns were: a) NO2 (Mean=106µg/m3, SD=38.5, N=95), b) NO (M=147µg/m3, SD=88.9, N=40), c) PM2.5 (M=35µg/m3, SD=6.3, N=64), and BC (M=10.6µg/m3, SD=5.3, N=76). Final LUR models had the following statistics: a) NO2 (R2=0.46, RMSE=28µg/m3) b) NO (R2=0.50, RMSE=62µg/m3), c) PM2.5 (R2=0.59; RMSE=4µg/m3), and d) BC (R2=0.50, RMSE=4µg/m3). Traditional LUR predictors such as road length, car park density, and land use types were included in most models. The NO2 prediction surface values were highest in Kowloon and the northern region of Hong Kong Island (downtown Hong Kong). NO showed a similar pattern in the built-up region. Both PM2.5 and BC predictions exhibited a northwest-southeast gradient, with higher concentrations in the north (close to mainland China). For BC, the port was also an area of elevated predicted concentrations. The results matched with existing literature on spatial variation in concentrations of air pollutants and in relation to important emission sources in Hong Kong. The success of these models suggests LUR is appropriate in high-density, high-rise cities.

Model predictions for the wide-angle x-ray scatter signals of healthy and malignant breast duct biopsies.

Wide-angle x-ray scatter (WAXS) could potentially be used to diagnose ductal carcinoma in situ (DCIS) in breast biopsies. The regions of interest were assumed to consist of fibroglandular tissue and epithelial cells and the model assumed that biopsies with DCIS would have a higher concentration of the latter. The scattered number of photons from a 2-mm diameter column of tissue was simulated using a 110-kV beam and selectively added in terms of momentum transfer. For a 1-min exposure, specificities and sensitivities of unity were obtained for biopsies 2- to 20-mm thick. The impact of sample and tumor cell layer thicknesses was studied. For example, a biopsy erroneously estimated to be 8 mm would be correctly diagnosed if its actual thickness was between 7.3 and 8.7 mm. An 8-mm thick malignant biopsy can be correctly diagnosed provided the malignant cell layer thickness is [Formula: see text]. WAXS methods could become a diagnostic tool for DCIS within breast biopsies.

A method to estimate the fractional fat volume within a ROI of a breast biopsy for WAXS applications: animal tissue evaluation.

PURPOSE: To develop a method to estimate the mean fractional volume of fat (ν¯fat) within a region of interest (ROI) of a tissue sample for wide-angle x-ray scatter (WAXS) applications. A scatter signal from the ROI was obtained and use of ν¯fat in a WAXS fat subtraction model provided a way to estimate the differential linear scattering coefficient µs of the remaining fatless tissue. METHODS: The efficacy of the method was tested using animal tissue from a local butcher shop. Formalin fixed samples, 5 mm in diameter 4 mm thick, were prepared. The two main tissue types were fat and meat (fibrous). Pure as well as composite samples consisting of a mixture of the two tissue types were analyzed. For the latter samples, νfat for the tissue columns of interest were extracted from corresponding pixels in CCD digital x-ray images using a calibration curve. The means ν¯fat were then calculated for use in a WAXS fat subtraction model. For the WAXS measurements, the samples were interrogated with a 2.7 mm diameter 50 kV beam and the 6° scattered photons were detected with a CdTe detector subtending a solid angle of 7.75 × 10(-5) sr. Using the scatter spectrum, an estimate of the incident spectrum, and a scatter model, µs was determined for the tissue in the ROI. For the composite samples, a WAXS fat subtraction model was used to estimate the µs of the fibrous tissue in the ROI. This signal was compared to µs of fibrous tissue obtained using a pure fibrous sample. RESULTS: For chicken and beef composites, ν¯fat=0.33±0.05 and 0.32 ± 0.05, respectively. The subtractions of these fat components from the WAXS composite signals provided estimates of µs for chicken and beef fibrous tissue. The differences between the estimates and µs of fibrous obtained with a pure sample were calculated as a function of the momentum transfer x. A t-test showed that the mean of the differences did not vary from zero in a statistically significant way thereby validating the methods. CONCLUSIONS: The methodology to estimate ν¯fat in a ROI of a tissue sample via CCD x-ray imaging was quantitatively accurate. The WAXS fat subtraction model allowed µs of fibrous tissue to be obtained from a ROI which had some fat. The fat estimation method coupled with the WAXS models can be used to compare µs coefficients of fibroglandular and cancerous breast tissue.

WAXS fat subtraction model to estimate differential linear scattering coefficients of fatless breast tissue: phantom materials evaluation.

PURPOSE: Develop a method to subtract fat tissue contributions to wide-angle x-ray scatter (WAXS) signals of breast biopsies in order to estimate the differential linear scattering coefficients µ(s) of fatless tissue. Cancerous and fibroglandular tissue can then be compared independent of fat content. In this work phantom materials with known compositions were used to test the efficacy of the WAXS subtraction model. METHODS: Each sample 5 mm in diameter and 5 mm thick was interrogated by a 50 kV 2.7 mm diameter beam for 3 min. A 25 mm(2) by 1 mm thick CdTe detector allowed measurements of a portion of the θ = 6° scattered field. A scatter technique provided means to estimate the incident spectrum N(0)(E) needed in the calculations of µ(s)[x(E, θ)] where x is the momentum transfer argument. Values of [Formula: see text] for composite phantoms consisting of three plastic layers were estimated and compared to the values obtained via the sum [Formula: see text], where ν(i) is the fractional volume of the ith plastic component. Water, polystyrene, and a volume mixture of 0.6 water + 0.4 polystyrene labelled as fibphan were chosen to mimic cancer, fat, and fibroglandular tissue, respectively. A WAXS subtraction model was used to remove the polystyrene signal from tissue composite phantoms so that the µ(s) of water and fibphan could be estimated. Although the composite samples were layered, simulations were performed to test the models under nonlayered conditions. RESULTS: The well known µ(s) signal of water was reproduced effectively between 0.5 < x < 1.6 nm(-1). The [Formula: see text] obtained for the heterogeneous samples agreed with [Formula: see text]. Polystyrene signals were subtracted successfully from composite phantoms. The simulations validated the usefulness of the WAXS models for nonlayered biopsies. CONCLUSIONS: The methodology to measure µ(s) of homogeneous samples was quantitatively accurate. Simple WAXS models predicted the probabilities for specific x-ray scattering to occur from heterogeneous biopsies. The fat subtraction model can allow µ(s) signals of breast cancer and fibroglandular tissue to be compared without the effects of fat provided there is an independent measurement of the fat volume fraction ν(f). Future work will consist of devising a quantitative x-ray digital imaging method to estimate ν(f) in ex vivo breast samples.