https://nova.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:45171 Wed 26 Oct 2022 14:18:49 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:51144 Wed 23 Aug 2023 12:29:49 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:51660 Wed 21 Feb 2024 15:03:53 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:22258 Wed 11 Apr 2018 16:35:43 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:39962 Wed 01 Mar 2023 10:26:05 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:36809 Tue 07 Jul 2020 11:40:42 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:25914 Thu 17 Mar 2022 14:37:50 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:42694 Thu 01 Sep 2022 09:27:20 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:1882 Sat 24 Mar 2018 08:31:19 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:19181 Sat 24 Mar 2018 07:52:17 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:5505 Sat 24 Mar 2018 07:47:02 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:5665 Sat 24 Mar 2018 07:44:05 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:5351 Sat 24 Mar 2018 07:43:53 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:4918 Sat 24 Mar 2018 07:21:12 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:39018 2DS₂-VA scheme, were calculated. Factors associated with AF were assessed using logistic regression. Results: From 2000 to 2015, a total of 1827 women with AF were identified. AF prevalence increased every year as women aged from 2.71% (95% CI 1.62%–3.80%) in 2000 among women aged 74–79 years to 24.83% (95% CI = 23.23%–26.44%) in 2015 among women aged 89–94 years. The incidence proportion remained constant (between 3% and 5%) throughout the study period. Sedentary lifestyle (OR = 1.24, 95% CI = 1.04–1.49), hypertension (OR = 1.24, 95% CI = 1.09–1.42), arthritis (OR = 1.24, 95% CI = 1.09–1.41), heart attack (OR = 1.62, 95% CI = 1.18–2.24), and angina (OR = 1.39, 95% CI = 1.14–1.70) were independently associated with AF. Mean CHA₂DS₂-VA score for women with AF was 3.43 (SD ± 1.23). Conclusions: The prevalence of AF reported in Australian women is among the highest compared to previous estimations from other countries and regions. According to the findings, about one in four women over the age of 90 years had AF. These women were also at high risk of stroke. This has significant public health implications especially with changing demographics of increase in the aging population. Further research is required on understanding how women with AF are treated in Australia and their health outcomes.]]> Mon 29 Jan 2024 17:43:06 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:42374 P < 0.05). Age, gender, number of outpatient visits, and specialist consultation were not associated with PIM prescription. Polypharmacy (adjusted odds ratio [aOR] =2.11) and hyperpolypharmacy (aOR = 5.55) had independent association with PIM prescription (P < 0.05). Conclusion: PIM prescription appears to be common in teaching hospitals in Kerala. Polypharmacy and hyperpolypharmacy in older people should trigger a review of medication to reduce the use of PIM.]]> Mon 22 Aug 2022 14:22:23 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:46241 N = 1432 women diagnosed with AF from 2000 to 2015 of the old cohort (born 1921–26) of the Australian Longitudinal Study on Women’s Health (ALSWH) who remained alive for at least 12 months post first recorded AF diagnosis. Self-reported data on demographics, health behaviours, health conditions, and SF-36 were obtained from the ALSWH surveys, corresponding to within three years of the date of the first record of AF diagnosis. Linked Pharmaceutical Benefits Scheme (PBS) data determined the use of oral anticoagulants and comorbid conditions, included in CHA₂DS₂-VA (Congestive heart failure, Hypertension, Age ≥ 75 years, Diabetes, Stroke or TIA, Vascular disease and Age 65–74 years) score calculation, were assessed using state-based hospital admissions data. Utility scores were calculated for every woman from their SF-36 responses using the SF-6D algorithm with Australian population norms. Mean utility scores were then calculated for women with various demographic, health behaviours, and clinical characteristics. Ordinary Least Square (OLS) regression modelling was performed to determine factors associated with these utility scores. Two different scenarios were used for the analysis: (1) complete-case, for women with complete data on all the SF-36 items required to estimate SF-6D (N = 584 women), and (2) Multiple Imputation (MI) for missing data, applied to missing values on SF-36 items (N = 1432 women). MI scenario was included to gauge the potential bias when using complete data only. Results: The mean health utility was estimated to be 0.638 ± 0.119 for the complete dataset and 0.642 ± 0.120 for the dataset where missing values were handled using MI. Using the MI technique, living in regional and remote areas (β=0.016±0.007) and the use of oral anticoagulants (β=0.021±0.007) were positively associated with health utility compared to living in major cities and no use of anticoagulants, respectively. Difficulty to manage on available income (β=−0.027±0.009), no/low physical activity (β=−0.069±0.011), disability (β=−0.097±0.008), history of stroke (β=−0.025±0.013) and history of arthritis (β=−0.024±0.007) were negatively associated with health utility. Conclusion: This study presents health utility estimates for older women with AF. These estimates can be used in future clinical and economic research. The study also highlights better health utilities for women living in regional and remote areas, which requires further exploration.]]> Mon 14 Nov 2022 13:17:50 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:44215 85% for most of the latent statuses. All factors but diabetes mellitus among the CHA2DS2-VA scoring scheme were independently associated with latent status membership at the time of AF diagnosis. Conclusions: Evaluation of pharmacological treatment indicates that prevention of thromboembolism is inadequate among women with AF. There exists wide variations in medication patterns. However, once in a particular pattern, women are likely to continue the same medications long-term. This underscores the importance of initial assessment of patient profile and stroke risk score in determining the treatment for AF. Failure to assess risk makes women susceptible to devastating AF complications.]]> Mon 10 Oct 2022 16:52:36 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:49848 Mon 05 Jun 2023 15:49:02 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:50078 Fri 30 Jun 2023 15:18:13 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:48100 Fri 24 Feb 2023 15:31:10 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:33223 Fri 14 Sep 2018 09:19:07 AEST ]]>