Search

Your search keyword '"Sajobi, Tolulope T."' showing total 531 results
Start Over Author "Sajobi, Tolulope T."
531 results on '"Sajobi, Tolulope T."'

102. Primary care electronic medical records can be used to predict risk and identify potentially modifiable factors for early and late death in adult onset epilepsy

Author

Hrabok, Marianne, primary, Engbers, Jordan D. T., additional, Wiebe, Samuel, additional, Sajobi, Tolulope T., additional, Subota, Ann, additional, Almohawes, Amal, additional, Federico, Paolo, additional, Hanson, Alexandra, additional, Klein, Karl Martin, additional, Peedicail, Joseph, additional, Pillay, Neelan, additional, Singh, Shaily, additional, and Josephson, Colin B., additional

Published
2020
Full Text
View/download PDF

103. Genetic Risk, Vascular Function, and Subjective Cognitive Complaints Predict Objective Cognitive Function in Healthy Older Adults: Results From the Brain in Motion Study

Author

Tyndall, Amanda V., primary, Longman, R. Stewart, additional, Sajobi, Tolulope T., additional, Parboosingh, Jillian S., additional, Drogos, Lauren L., additional, Davenport, Margie H., additional, Eskes, Gail A., additional, Hogan, David B., additional, Hill, Michael D., additional, and Poulin, Marc J., additional

Published
2020
Full Text
View/download PDF

105. Repeated measures discriminant analysis using multivariate generalized estimation equations.

Author

Brobbey, Anita, Wiebe, Samuel, Nettel-Aguirre, Alberto, Josephson, Colin Bruce, Williamson, Tyler, Lix, Lisa M, and Sajobi, Tolulope T.

Subjects
MONTE Carlo method, DISCRIMINANT analysis, REPEATED measures design, MULTIVARIATE analysis, GENERALIZED estimating equations, MAXIMUM likelihood statistics
Abstract

Discriminant analysis procedures that assume parsimonious covariance and/or means structures have been proposed for distinguishing between two or more populations in multivariate repeated measures designs. However, these procedures rely on the assumptions of multivariate normality which is not tenable in multivariate repeated measures designs which are characterized by binary, ordinal, or mixed types of response distributions. This study investigates the accuracy of repeated measures discriminant analysis (RMDA) based on the multivariate generalized estimating equations (GEE) framework for classification in multivariate repeated measures designs with the same or different types of responses repeatedly measured over time. Monte Carlo methods were used to compare the accuracy of RMDA procedures based on GEE, and RMDA based on maximum likelihood estimators (MLE) under diverse simulation conditions, which included number of repeated measure occasions, number of responses, sample size, correlation structures, and type of response distribution. RMDA based on GEE exhibited higher average classification accuracy than RMDA based on MLE especially in multivariate non-normal distributions. Three repeatedly measured responses namely severity of epilepsy, current number of anti-epileptic drugs, and parent-reported quality of life in children with epilepsy were used to demonstrate the application of these procedures. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

106. Association between antiseizure medications and quality of life in epilepsy: A mediation analysis.

Author

Wang, Meng, Perera, Kevin, Josephson, Colin B., Lamidi, Mubasiru, Lawal, Oluwaseyi A., Awosoga, Oluwagbohunmi, Roach, Pamela, Patten, Scott B., Wiebe, Samuel, and Sajobi, Tolulope T.

Subjects
EPILEPSY, PROPENSITY score matching, PEOPLE with epilepsy, QUALITY of life, DRUGS
Abstract

Objective: The relationship between antiseizure medications (ASMs), which improve health outcomes by controlling seizures, and health‐related quality of life (HRQOL) is poorly understood and may involve intermediate variables. We evaluated the potential mediators of the association between ASMs and HRQOL. Methods: Data are from an outpatient registry of adult patients with epilepsy seen at the Foothills Medical Center, Calgary, Alberta, Canada. Quality of life was measured using the 10‐item Quality of Life in Epilepsy, and depression was measured using the Neurological Disorders Depression Inventory for Epilepsy. Propensity score matching was used to adjust for covariate imbalance between patients who received a single ASM (monotherapy) and those who received two or more ASMs (polytherapy) due to confounding. Mediation analysis was used to estimate the mediating effects of depression and ASM side effects on the association between patients' ASM polytherapy and HRQOL. Results: Of 778 patients included in this analysis, 274 (35.2%) were on two or more ASMs. Patient‐reported depression and ASM side effects jointly mediated the association between ASMs and HRQOL; these mediators accounted for 42% of the total average effect of ASM polytherapy (β = −13.6, 95% confidence interval = −18.2 to −8.6) on HRQOL. Significance: These findings highlight the importance of managing depression and ASM side effects for improving health outcomes of patients requiring treatment with ASMs. Intervention programs aimed at improving HRQOL of patients with epilepsy need to target these potential mediators. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

107. White matter tract microstructure and cognitive performance after transient ischemic attack

Author

Tariq, Sana, primary, Tsang, Adrian, additional, Wang, Meng, additional, Reaume, Noaah, additional, Carlson, Helen, additional, Sajobi, Tolulope T., additional, Longman, Richard Stewart, additional, Smith, Eric E., additional, Frayne, Richard, additional, d’Esterre, Christopher D., additional, Coutts, Shelagh B., additional, and Barber, Philip A., additional

Published
2020
Full Text
View/download PDF

108. Development and validation of the Epilepsy Surgery Satisfaction Questionnaire (ESSQ‐19)

Author

Wiebe, Samuel, primary, Wahby, Sandra, additional, Lawal, Oluwaseyi A., additional, Sajobi, Tolulope T., additional, Keezer, Mark R., additional, Nguyen, Dang K., additional, Malmgren, Kristina, additional, Tellez‐Zenteno, Jose, additional, Atkinson, Mark J., additional, Hader, Walter J., additional, Josephson, Colin B., additional, Macrodimitris, Sophia, additional, Patten, Scott B., additional, Pillay, Neelan, additional, Sharma, Ruby, additional, Singh, Shaily, additional, and Starreveld, Yves, additional

Published
2020
Full Text
View/download PDF

114. A pragmatic dementia risk score for patients with mild cognitive impairment in a memory clinic population: Development and validation of a dementia risk score using routinely collected data.

Author

Meng Wang, Sajobi, Tolulope T., Ismail, Zahinoor, Seitz, Dallas, Chekouo, Thierry, Forkert, Nils D., Fischer, Karyn, Mackie, Aaron, Pearson, Dawn, Patry, David, Cieslak, Alicja, Menon, Bijoy, Barber, Philip, McLane, Brienne, Granger, Robert, Hogan, David B., and Smith, Eric E.

Subjects
DISEASE risk factors, MEMORY disorders, MILD cognitive impairment, ALZHEIMER'S disease, DEMENTIA patients, DATABASES
Abstract

Introduction: This study aimed to develop and validate a 3-year dementia risk score in individuals with mild cognitive impairment (MCI) based on variables collected in routine clinical care. Methods: The prediction score was trained and developed using data from the National Alzheimer's Coordinating Center (NACC). Selection criteria included aged 55 years and older with MCI. Cox models were validated externally using two independent cohorts from the Prospective Registry of Persons with Memory Symptoms (PROMPT) registry and the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Results: Our Mild Cognitive Impairment to Dementia Risk (CIDER) score predicted dementia risk with c-indices of 0.69 (95% confidence interval [CI] 0.66-0.72), 0.61 (95% CI 0.59-0.63), and 0.72 (95% CI 0.69-0.75), for the internally validated and the external validation PROMPT, and ADNI cohorts, respectively. Discussion: The CIDER score could be used to inform clinicians and patients about the relative probabilities of developing dementia in patients with MCI. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

118. Trimodal prehabilitation for colorectal surgery attenuates post-surgical losses in lean body mass: A pooled analysis of randomized controlled trials

Author

Gillis, Chelsia, primary, Fenton, Tanis R., additional, Sajobi, Tolulope T., additional, Minnella, Enrico Maria, additional, Awasthi, Rashami, additional, Loiselle, Sarah-Ève, additional, Liberman, A Sender, additional, Stein, Barry, additional, Charlebois, Patrick, additional, and Carli, Francesco, additional

Published
2019
Full Text
View/download PDF

120. Prediction Tools for Psychiatric Adverse Effects After Levetiracetam Prescription

Author

Josephson, Colin B., primary, Engbers, Jordan D. T., additional, Jette, Nathalie, additional, Patten, Scott B., additional, Singh, Shaily, additional, Sajobi, Tolulope T., additional, Marshall, Deborah, additional, Agha-Khani, Yahya, additional, Federico, Paolo, additional, Mackie, Aaron, additional, Macrodimitris, Sophie, additional, McLane, Brienne, additional, Pillay, Neelan, additional, Sharma, Ruby, additional, and Wiebe, Samuel, additional

Published
2019
Full Text
View/download PDF

122. A comparison of meta-analytic methods for synthesizing evidence from explanatory and pragmatic trials

Author

Sajobi, Tolulope T., Li, Guowei, Awosoga, Olu A., Wang, Meng, Menon, Bijoy K., Hill, Michael D., Thabane, Lehana, Sajobi, Tolulope T., Li, Guowei, Awosoga, Olu A., Wang, Meng, Menon, Bijoy K., Hill, Michael D., and Thabane, Lehana

Abstract

Background: The pragmatic–explanatory continuum indicator summary version 2 (PRECIS-2) tool has recently been developed to classify randomized clinical trials (RCTs) as pragmatic or explanatory based on their design characteristics. Given that treatment effects in explanatory trials may be greater than those obtained in pragmatic trials, conventional meta-analytic approaches may not accurately account for the heterogeneity among the studies and may result in biased treatment effect estimates. This study investigates if the incorporation of PRECIS-2 classification of published trials can improve the estimation of overall intervention effects in meta-analysis. Methods: Using data from 31 published trials of intervention aimed at reducing obesity in children, we evaluated the utility of incorporating PRECIS-2 ratings of published trials into meta-analysis of intervention effects in clinical trials. Specifically, we compared random-effects meta-analysis, stratified meta-analysis, random-effects meta-regression, and mixture random-effects meta-regression methods for estimating overall pooled intervention effects. Results: Our analyses revealed that mixture meta-regression models that incorporate PRECIS-2 classification as covariate resulted in a larger pooled effect size (ES) estimate (ES=−1.01, 95%CI=[−1.52, −0.43]) than conventional random-effects meta-analysis (ES=−0.15, 95%CI=[−0.23, −0.08]). Conclusions: In addition to the original intent of PRECIS-2 tool of aiding researchers in their choice of trial design, PRECIS2 tool is useful for explaining between study variations in systematic review and meta-analysis of published trials. We recommend that researchers adopt mixture meta-regression methods when synthesizing evidence from explanatory and pragmatic trials.

Published
2018

123. Primary care electronic medical records can be used to predict risk and identify potentially modifiable factors for early and late death in adult onset epilepsy.

Author

Hrabok, Marianne, Engbers, Jordan D. T., Wiebe, Samuel, Sajobi, Tolulope T., Subota, Ann, Almohawes, Amal, Federico, Paolo, Hanson, Alexandra, Klein, Karl Martin, Peedicail, Joseph, Pillay, Neelan, Singh, Shaily, and Josephson, Colin B.

Subjects
ELECTRONIC health records, EARLY death, PRIMARY care, RECEIVER operating characteristic curves, PARTIAL epilepsy, EPILEPSY
Abstract

Objective: To use clinically informed machine learning to derive prediction models for early and late premature death in epilepsy. Methods: This was a population‐based primary care observational cohort study. All patients meeting a case definition for incident epilepsy in the Health Improvement Network database for inclusive years 2000‐2012 were included. A modified Delphi process identified 30 potential risk factors. Outcome was early (within 4 years of epilepsy diagnosis) and late (4 years or more from diagnosis) mortality. We used regularized logistic regression, support vector machines, Gaussian naive Bayes, and random forest classifiers to predict outcomes. We assessed model calibration, discrimination, and generalizability using the Brier score, mean area under the receiver operating characteristic curve (AUC) derived from stratified fivefold cross‐validation, plotted calibration curves, and extracted measures of association where possible. Results: We identified 10 499 presumed incident cases from 11 194 182 patients. All models performed comparably well following stratified fivefold cross‐validation, with AUCs ranging from 0.73 to 0.81 and from 0.71 to 0.79 for early and late death, respectively. In addition to comorbid disease, social habits (alcoholism odds ratio [OR] for early death = 1.54, 95% confidence interval [CI] = 1.12‐2.11 and OR for late death = 2.62, 95% CI = 1.66‐4.16) and treatment patterns (OR for early death when no antiseizure medication [ASM] was prescribed at baseline = 1.33, 95% CI = 1.07‐1.64 and OR for late death after receipt of enzyme‐inducing ASM at baseline = 1.32, 95% CI = 1.04‐1.66) were significantly associated with increased risk of premature death. Baseline ASM polytherapy (OR = 0.55, 95% CI = 0.36‐0.85) was associated with reduced risk of early death. Significance: Clinically informed models using routine electronic medical records can be used to predict early and late mortality in epilepsy, with moderate to high accuracy and evidence of generalizability. Medical, social, and treatment‐related risk factors, such as delayed ASM prescription and baseline prescription of enzyme‐inducing ASMs, were important predictors. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

124. Psychosocial profiles and their predictors in epilepsy using patient‐reported outcomes and machine learning.

Author

Josephson, Colin B., Engbers, Jordan D. T., Wang, Meng, Perera, Kevin, Roach, Pamela, Sajobi, Tolulope T., Wiebe, Samuel, Federico, Paolo, Klein, Karl Martin, Murphy, William, Pillay, Neelan, Salmon, Andrea, and Singh, Shaily

Subjects
MACHINE learning, EPILEPSY, DISABILITIES, PEOPLE with epilepsy
Abstract

Objective: To apply unsupervised machine learning to patient‐reported outcomes to identify clusters of epilepsy patients exhibiting unique psychosocial characteristics. Methods: Consecutive outpatients seen at the Calgary Comprehensive Epilepsy Program outpatient clinics with complete patient‐reported outcome measures on quality of life, health state valuation, depression, and epilepsy severity and disability were studied. Data were acquired at each patient's first clinic visit. We used k‐means++ to segregate the population into three unique clusters. We then used multinomial regression to determine factors that were statistically associated with patient assignment to each cluster. Results: We identified 462 consecutive patients with complete patient‐reported outcome measure (PROM) data. Post hoc analysis of each cluster revealed one reporting elevated measures of psychosocial health on all five PROMs ("high psychosocial health" cluster), one with intermediate measures ("intermediate" cluster), and one with poor overall measures of psychosocial health ("poor psychosocial health" cluster). Failing to achieve at least 1 year of seizure freedom (relative risk [RR] = 4.34, 95% confidence interval [CI] = 2.13‐9.09) predicted placement in the "intermediate" cluster relative to the "high" cluster. In addition, failing to achieve seizure freedom, social determinants of health, including the need for partially or completely subsidized income support (RR = 6.10, 95% CI = 2.79‐13.31, P <.001) and inability to drive (RR = 4.03, 95% CI = 1.6‐10.00, P =.003), and a history of a psychiatric disorder (RR = 3.16, 95% CI = 1.46‐6.85, P =.003) were associated with the "poor" cluster relative to the "high" cluster. Significance: Seizure‐related factors appear to drive placement in the "intermediate" cluster, with social determinants driving placement in the "poor" cluster, suggesting a threshold effect. Precision intervention based on cluster assignment, with an initial emphasis on improving social support and careful titration of medications for those reporting the worst psychosocial health, could help optimize health for patients with epilepsy. [ABSTRACT FROM AUTHOR]

Published
2020
Full Text
View/download PDF

126. Patient satisfaction with epilepsy surgery: what is important to patients

Author

Lunney, Meaghan, primary, Wahby, Sandra, additional, Sauro, Khara M., additional, Atkinson, Mark J., additional, Josephson, Colin B., additional, Girgis, Fady, additional, Singh, Shaily, additional, Patten, Scott B., additional, Jetté, Nathalie, additional, Sajobi, Tolulope T., additional, Hader, Walter, additional, and Wiebe, Samuel, additional

Published
2018
Full Text
View/download PDF

138. Latent variable mixture models to test for differential item functioning: a population-based analysis

Author

Wu, Xiuyun, primary, Sawatzky, Richard, additional, Hopman, Wilma, additional, Mayo, Nancy, additional, Sajobi, Tolulope T., additional, Liu, Juxin, additional, Prior, Jerilynn, additional, Papaioannou, Alexandra, additional, Josse, Robert G., additional, Towheed, Tanveer, additional, Davison, K. Shawn, additional, and Lix, Lisa M., additional

Published
2017
Full Text
View/download PDF

139. Longitudinal Brain Atrophy Rates in Transient Ischemic Attack and Minor Ischemic Stroke Patients and Cognitive Profiles.

Author

Munir, Muhammad, Ursenbach, Jake, Reid, Meaghan, Gupta Sah, Rani, Wang, Meng, Sitaram, Amith, Aftab, Arooj, Tariq, Sana, Zamboni, Giovanna, Griffanti, Ludovica, Smith, Eric E., Frayne, Richard, Sajobi, Tolulope T., Coutts, Shelagh B., d'Esterre, Christopher D., and Barber, Philip A.

Subjects
CEREBRAL atrophy, TRANSIENT ischemic attack, STROKE patients, COGNITION disorders, DEMENTIA, COGNITIVE testing
Abstract

Introduction: Patients with transient ischemic attack (TIA) and minor stroke demonstrate cognitive impairment, and a four-fold risk of late-life dementia. Aim: To study the extent to which the rates of brain volume loss in TIA patients differ from healthy controls and how they are correlated with cognitive impairment. Methods: TIA or minor stroke patients were tested with a neuropsychological battery and underwent T1 weighted volumetric magnetic resonance imaging scans at fixed intervals over a 3 years period. Linear mixed effects regression models were used to compare brain atrophy rates between groups, and to determine the relationship between atrophy rates and cognitive function in TIA and minor stroke patients. Results: Whole brain atrophy rates were calculated for the TIA and minor stroke patients; n = 38 between 24 h and 18 months, and n = 68 participants between 18 and 36 months, and were compared to healthy controls. TIA and minor stroke patients demonstrated a significantly higher whole brain atrophy rate than healthy controls over a 3 years interval (p = 0.043). Diabetes (p = 0.012) independently predicted higher atrophy rate across groups. There was a relationship between higher rates of brain atrophy and processing speed (composite P = 0.047 and digit symbol coding P = 0.02), but there was no relationship with brain atrophy rates and memory or executive composite scores or individual cognitive tests for language (Boston naming, memory recall, verbal fluency or Trails A or B score). Conclusion: TIA and minor stroke patients experience a significantly higher rate of whole brain atrophy. In this cohort of TIA and minor stroke patients changes in brain volume over time precede cognitive decline. [ABSTRACT FROM AUTHOR]

Published
2019
Full Text
View/download PDF

142. Cardiometabolic risk factors predict cerebrovascular health in older adults: results from theBrain in Motionstudy

Author

Tyndall, Amanda V., primary, Argourd, Laurie, additional, Sajobi, Tolulope T., additional, Davenport, Margie H., additional, Forbes, Scott C., additional, Gill, Stephanie J., additional, Parboosingh, Jillian S., additional, Anderson, Todd J., additional, Wilson, Ben J., additional, Smith, Eric E., additional, Hogan, David B., additional, Hill, Michael D., additional, and Poulin, Marc J., additional

Published
2016
Full Text
View/download PDF

143. Differential Item Functioning in the SF-36 Physical Functioning and Mental Health Sub-Scales: A Population-Based Investigation in the Canadian Multicentre Osteoporosis Study

Author

Lix, Lisa M., primary, Wu, Xiuyun, additional, Hopman, Wilma, additional, Mayo, Nancy, additional, Sajobi, Tolulope T., additional, Liu, Juxin, additional, Prior, Jerilynn C., additional, Papaioannou, Alexandra, additional, Josse, Robert G., additional, Towheed, Tanveer E., additional, Davison, K. Shawn, additional, and Sawatzky, Richard, additional

Published
2016
Full Text
View/download PDF

145. Abstract TP45: One Threshold Does not Fit All: Hounsfield Unit Thresholds to Segment Clot on NCCT are Patient Specific

Author

Qazi, Emmad, primary, Wilson, Alexis T, additional, McDougall, Connor, additional, Boesen, Mari, additional, Al-Ajlan, Fahad S, additional, Pordeli, Pooneh, additional, Batchelor, Connor, additional, Khan, Khayam, additional, Sajobi, Tolulope T, additional, Lee, Ting-Yim, additional, Hill, Michael D, additional, Demchuk, Andrew M, additional, Goyal, Mayank, additional, d'Esterre, Christopher D, additional, Menon, Bijoy K, additional, and Forkert, Nils D, additional

Published
2016
Full Text
View/download PDF

149. Association between Lifetime Physical Activity and Cognitive Functioning in Middle-Aged and Older Community Dwelling Adults: Results from theBrain in MotionStudy

Author

Gill, Stephanie J., primary, Friedenreich, Christine M., additional, Sajobi, Tolulope T., additional, Longman, R. Stewart, additional, Drogos, Lauren L., additional, Davenport, Margie H., additional, Tyndall, Amanda V., additional, Eskes, Gail A., additional, Hogan, David B., additional, Hill, Michael D., additional, Parboosingh, Jillian S, additional, Wilson, Ben J., additional, and Poulin, Marc J., additional

Published
2015
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results