Browsing by Author "O'Beirne, Maeve"
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- ItemOpen AccessThe Alberta Pregnancy Outcomes and Nutrition (APrON) cohort study: rationale and methods(Maternal & Child Nutrition, 2014-01) Kaplan, Bonnie; Giesbrecht, Gerald; Leung, Brenda; Field, Catherine; Dewey, Deborah; Bell, Rhonda; Manca, Donna; O'Beirne, Maeve; Johnston, David; Pop, Victor; Singhal, Nalini; Gagnon, Lisa; Bernier, Francois; Eliasziw, Misha; McCargar, Linda; Kooistra, Libbe; Farmer, Anna; Cantell, Marja; Goonewardene, Laki; Casey, Linda; Letourneau, Nicole; Martin, Jonathan; APrON Study TeamThe Alberta Pregnancy Outcomes and Nutrition (APrON) study is an ongoing prospective cohort study that recruits pregnant women early in pregnancy and, as of 2012, is following up their infants to 3 years of age. It has currently enrolled approximately 5000 Canadians (2000 pregnant women, their offspring and many of their partners).The primary aims of the APrON study were to determine the relationships between maternal nutrient intake and status, before, during and after gestation, and (1) maternal mood; (2) birth and obstetric outcomes; and (3) infant neurodevelopment. We have collected comprehensive maternal nutrition, anthropometric, biological and mental health data at multiple points in the pregnancy and the post-partum period, as well as obstetrical, birth, health and neurodevelopmental outcomes of these pregnancies. The study continues to follow the infants through to 36 months of age.The current report describes the study design and methods, and findings of some pilot work. The APrON study is a significant resource with opportunities for collaboration.
- ItemOpen AccessDevelop a comprehensive hypertension prediction model and risk score in population-based data applying conventional statistical and machine learning approaches(2021-04-01) Chowdhury, Mohammad Ziaul Islam; Chowdhury, Tanvir; Quan, Hude; Leung, Alexander; O'Beirne, Maeve; Sikdar, Khokan; Hagel, Brent; Hu, XiaoqiongHypertension is a common medical condition and is a significant risk factor for heart attack, stroke, kidney disease, and mortality. Developing a risk prediction model for hypertension incidence incorporating its risk factors can help identify high-risk individuals who should be targeted for healthy behavioral changes or medical treatment to prevent hypertension onset. This research aims to develop a robust hypertension prediction model for the general population. More specifically, we aimed to 1) conduct a comprehensive systematic review to identify risk factors and prediction models for hypertension incidence and perform a meta-analysis to evaluate the current model’s predictive performance. 2) develop a risk prediction model for incident hypertension in a Canadian cohort using a traditional modeling approach. 3) develop machine learning algorithms to predict hypertension incidence and compare their predictive performance with a traditional statistical model. We systematically searched MEDLINE, EMBASE, Web of Science, Scopus, and the grey literature for studies predicting the risk of hypertension among the general adult population. We identified 52 studies that presented 117 models, of which 75 were developed using traditional regression-based modeling and 42 using machine learning algorithms. No studies were from Canada where a hypertension prediction model was developed or validated. Meta-analysis showed the overall pooled C-statistics 0.75 [0.73 – 0.77] for the traditional regression-based models and 0.76 [0.72 – 0.79] for the machine learning-based models. The lack of a hypertension prediction model in a Canadian context motivated us to develop a new model. We used the data of 18,322 participants on 29 candidate variables from the large Alberta’s Tomorrow Project (ATP) to develop traditional Cox proportional hazards (PH) model. Age, sex, body mass index (BMI), systolic blood pressure (SBP), diabetes, total physical activity time, and cardiovascular disease were used as significant risk factors in the model. Our model showed good discrimination (Harrel’s C-statistic 0.77) and calibration (Grønnesby and Borgan test, χ^2 statistic = 8.75, p = 0.07; calibration slope 1.006). A risk score table to estimate hypertension risks at 2-, 3-, 5-, and 6-year were derived from the model to favor the model’s clinical implementation and workability. Five machine learning algorithms were also developed to predict hypertension incidence: penalized regression Ridge, Lasso, Elastic Net (EN), random survival forest (RSF), and gradient boosting (GB). The performance of machine learning algorithms was observed, similar to the traditional Cox PH model. Average C-indexes were 0.78, 0.78, 0.78, 0.76, 0.76, for Ridge, Lasso, Elastic Net, RSF, GB, respectively. Important features associated with each machine learning algorithms were also presented. We developed a simple yet practical prediction model to estimate the risk of incident hypertension for the Canadian population that relies on readily available variables. Our results showed little predictive performance difference between machine learning algorithms and the traditional Cox PH model in predicting hypertension incidence. Our newly developed model may help clinicians, and the general population assess their risks of new-onset hypertension and facilitate discussions on preventing this risk more effectively.
- ItemOpen AccessEnhancing Person-Centred Practice in Primary Care: Co-designing Strategies to Implement Quality Indicators Informed by the Patient Perspective(2022-03) Manalili, Kimberly; Santana, Maria Jose; Scott, Catherine; O'Beirne, Maeve; Hemmelgarn, BrendaPerson-Centred Care (PCC) promotes engagement with patients and caregivers to improve patient experiences and outcomes. Person-Centred Quality Indicators (PC-QIs) are quality improvement (QI) tools that support healthcare providers and organizations to identify gaps in the delivery of PCC and improve the quality of care for patients. Little is known about how to implement PC-QIs effectively so that they are adopted and used to create meaningful change in practice. We aimed to address these knowledge gaps by applying a person-centred and implementation science lens to QI and collaborate with stakeholders to inform the future implementation of PC-QIs for primary care in Alberta, Canada. The first study of this thesis was a systematic review and meta-analysis on the effectiveness of person-centred QI strategies on the management of hypertension in primary care. Our findings suggest that consistent features of person-centered QI interventions that were effective for improving hypertension outcomes included tailored communication with patients, use of health information technology, and multidisciplinary collaboration. The second and third studies of this thesis were mixed methods studies focussed on co-designing the implementation of the PC-QIs for future use in primary care in Alberta. In study two, our findings from an organizational readiness survey and interviews conducted with participants representing both Canadian system-level and Alberta clinical primary care perspectives shed light on key factors that may influence implementation. These factors included: the organization or clinics’ interest and motivation to implement the PC-QIs, resources and capacity to collect and use data for improvements, and the organizational climate for implementation of the PC-QIs, related to PCC and QI. In the third study, we conducted a consensus process with primary care stakeholders to prioritize the PC-QIs for implementation and implementation strategies that were identified, which emerged from our second study. Consensus panelists prioritized PC-QIs related to: patient and caregiver involvement in decisions about care, having a trusting relationship with the healthcare provider, health information technology to support PCC, co-designing care in partnership with communities, and overall experience. The strategies prioritized included: developing partnerships among stakeholder groups, obtaining QI resources, conducting a needs assessment, aligning measurement efforts provincially, and engaging champions.
- ItemOpen AccessModulation of dye and electrotonic coupling in the hippocampus(1991) O'Beirne, Maeve; MacVicar, Brian A.
- ItemOpen AccessThe role of maternal cardiac vagal control in the association between depressive symptoms and gestational hypertension.(Elsevier, 2016-05) Giesbrecht, Gerald; Rouleau, Codie, R.; Tomfohr- Madsen, Lianne, M.; Campbell, Tavis, S.; Letourneau, Nicole; O'Beirne, MaeveReduced cardiac vagal control, indexed by relatively lower high-frequency heart rate variability (HF-HRV), is implicated in depressed mood and hypertensive disorders among non-pregnant adults whereas research in pregnancy is limited. This study examined whether maternal HF-HRV during pregnancy mediates the association between depressed mood and gestational hypertension. Depressive symptoms (Edinburgh Depression Scale) and HF-HRV were measured during early (M = 14.9 weeks) and late (M = 32.4 weeks) pregnancy in 287 women. Gestational hypertension was determined by chart review. Depressive symptoms were associated with less HF-HRV (b = -0.02, p =.001). There was an indirect effect of depressed mood on gestational hypertension through late pregnancy HF-HRV (b = 0.04, 95% CI 0.0038, 0.1028) after accounting for heart rate. These findings suggest cardiac vagal control is a possible pathway through which prenatal depressed mood is associated with gestational hypertension, though causal ordering remains uncertain.
- ItemOpen AccessThe Seamless Transfer-of-Care Protocol: a randomized controlled trial assessing the efficacy of an electronic transfer-of-care communication tool(BioMed Central, 2012-11-21) Okoniewska, Barbara M.; Santana, Maria J.; Holroyd-Leduc, Jayna M.; Flemons, W. Ward; O'Beirne, Maeve; White, Deborah; Clement, Fiona M.; Forster, Alan; Ghali, William A.
- ItemOpen AccessVitamin D during Pregnancy(2016) Aghajafari, Fariba; Ross, Susan; O'Beirne, Maeve; Field, Catherine; Eliasziw, Misha; Dewey, DeborahVitamin D plays an important role in promoting healthy pregnancy and fetal development. There is a lack of knowledge on (1) the effect of vitamin D deficiency/ insufficiency on pregnancy and neonatal outcomes, (2) the association between maternal plasma vitamin D concentration and dietary intake, and (3) the prevalence of vitamin D deficiency/ insufficiency during pregnancy and the contribution of vitamin D metabolites to estimate vitamin D. This dissertation attempts to address these knowledge gaps about vitamin D during pregnancy. In a systematic review and meta-analysis of observational studies, low maternal 25(OH)D concentrations were found to be associated with higher risks of gestational diabetes (pooled OR 1.49, 95% CI: 1.18 to 1.89), preeclampsia (pooled OR 1.79, 95% CI: 1.25 to 2.58), small for gestational age (SGA) (pooled OR 1.85, 95% CI: 1.52 to 2.26) and lower birth weight (weighted mean difference: -130.92 g (95% CI: -186.69 to -75.14). However, that quality of individual studies was not always optimal due to inconsistent reporting on confounding factors. The two studies in this work involved pregnant women from a large Alberta cohort study to measure vitamin D. 3-epi-25(OH)D3 was found in all of the pregnant women’s blood in mid-pregnancy, at the time of delivery and in cord blood. When the 3-epimer was included in the estimation of status, the prevalence of vitamin D <75 nmol/L was significantly lower (P<0.005). A significant relationship between maternal reported dietary vitamin D intake and plasma 25(OH)D and 3-epi-25(OH)D3 concentration were identified. Consuming the Recommended Dietary Allowance (RDA) (600 IU/ day) was found to be insufficient to achieve vitamin D <75 nmol/L in half of participants. This research highlighted the potentially important association between maternal vitamin D status and pregnancy health and the variability that can arise in study results when different measures of vitamin D status are used. In addition, it extends the literature suggesting that current RDA may not be adequate to ensure that Canadian pregnant women achieving vitamin D status. Furthermore, this research showed that the method employed to measure vitamin D in pregnant women and cord blood can influence the estimates of status.