Browsing by Subject "Trajectories"

Now showing 1 - 4 of 4
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    Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years
    (Wiley, 2022-01) Frangou, Sophia; Modabbernia, Amirhossein; Williams, Steven C.R.; Papachristou, Efstathios; Doucet, Gaelle E.; Agartz, Ingrid; Aghajani, Moji; Akudjedu, Theophilus N.; Albajes-Eizagirre, Anton; Alnæs, Dag; Alpert, Kathryn I.; Andersson, Micael; Andreasen, Nancy C.; Andreassen, Ole A.; Asherson, Philip; Banaschewski, Tobias; Bargallo, Nuria; Baumeister, Sarah; Baur-Streubel, Ramona; Bertolino, Alessandro; Bonvino, Aurora; Boomsma, Dorret I.; Borgwardt, Stefan; Bourque, Josiane; Brandeis, Daniel; Breier, Alan; Brodaty, Henry; Brouwer, Rachel M.; Buitelaar, Jan K.; Busatto, Geraldo F.; Buckner, Randy L.; Calhoun, Vincent; Canales-Rodríguez, Erick J.; Cannon, Dara M.; Caseras, Xavier; Castellanos, Francisco X.; Cervenka, Simon; Chaim-Avancini, Tiffany M.; Ching, Christopher R.K.; Chubar, Victoria; Clark, Vincent P.; Conrod, Patricia; Conzelmann, Annette; Crespo-Facorro, Benedicto; Crivello, Fabrice; Crone, Eveline A.; Dale, Anders M.; Dannlowski, Udo; Davey, Christopher; de Geus, Eco J.C.; de Haan, Lieuwe; de Zubicaray, Greig I.; den Braber, Anouk; Dickie, Erin W.; Di Giorgio, Annabella; Doan, Nhat Trung; Dørum, Erlend S.; Ehrlich, Stefan; Erk, Susanne; Espeseth, Thomas; Fatouros-Bergman, Helena; Fisher, Simon E.; Fouche, Jean-Paul; Franke, Barbara; Frodl, Thomas; Fuentes-Claramonte, Paola; Glahn, David C.; Gotlib, Ian H.; Grabe, Hans-Jörgen; Grimm, Oliver; Groenewold, Nynke A.; Grotegerd, Dominik; Gruber, Oliver; Gruner, Patricia; Gur, Rachel E.; Gur, Ruben C.; Hahn, Tim; Harrison, Ben J.; Hartman, Catharine A.; Hatton, Sean N.; Heinz, Andreas; Heslenfeld, Dirk J.; Hibar, Derrek P.; Hickie, Ian B.; Ho, Beng-Choon; Hoekstra, Pieter J.; Hohmann, Sarah; Holmes, Avram J.; Hoogman, Martine; Hosten, Norbert; Howells, Fleur M.; Hulshoff Pol, Hilleke E.; Huyser, Chaim; Jahanshad, Neda; James, Anthony; Jernigan, Terry L.; Jiang, Jiyang; Jönsson, Erik G.; Joska, John A.; Kahn, Rene; Kalnin, Andrew; Kanai, Ryota; Klein, Marieke; Klyushnik, Tatyana P.; Koenders, Laura; Koops, Sanne; Krämer, Bernd; Kuntsi, Jonna; Lagopoulos, Jim; Lázaro, Luisa; Lebedeva, Irina; Lee, Won Hee; Lesch, Klaus-Peter; Lochner, Christine; Machielsen, Marise W.J.; Maingault, Sophie; Martin, Nicholas G.; Martínez-Zalacaín, Ignacio; Mataix-Cols, David; Mazoyer, Bernard; McDonald, Colm; McDonald, Brenna C.; McIntosh, Andrew M.; McMahon, Katie L.; McPhilemy, Genevieve; Meinert, Susanne; Menchón, José M.; Medland, Sarah E.; Meyer-Lindenberg, Andreas; Naaijen, Jilly; Najt, Pablo; Nakao, Tomohiro; Nordvik, Jan E.; Nyberg, Lars; Oosterlaan, Jaap; Ortiz-García de la Foz, Víctor; Paloyelis, Yannis; Pauli, Paul; Pergola, Giulio; Pomarol-Clotet, Edith; Portella, Maria J.; Potkin, Steven G.; Radua, Joaquim; Reif, Andreas; Rinker, Daniel A.; Roffman, Joshua L.; Rosa, Pedro G.P.; Sacchet, Matthew D.; Sachdev, Perminder S.; Salvador, Raymond; Sánchez-Juan, Pascual; Sarró, Salvador; Satterthwaite, Theodore D.; Saykin, Andrew J.; Serpa, Mauricio H.; Schmaal, Lianne; Schnell, Knut; Schumann, Gunter; Sim, Kang; Smoller, Jordan W.; Sommer, Iris; Soriano-Mas, Carles; Stein, Dan J.; Strike, Lachlan T.; Swagerman, Suzanne C.; Tamnes, Christian K.; Temmingh, Henk S.; Thomopoulos, Sophia I.; Tomyshev, Alexander S.; Tordesillas-Gutiérrez, Diana; Trollor, Julian N.; Turner, Jessica A.; Uhlmann, Anne; van den Heuvel, Odile A.; van den Meer, Dennis; van der Wee, Nic J.A.; van Haren, Neeltje E.M.; van't Ent, Dennis; van Erp, Theo G.M.; Veer, Ilya M.; Veltman, Dick J.; Voineskos, Aristotle; Völzke, Henry; Walter, Henrik; Walton, Esther; Wang, Lei; Wang, Yang; Wassink, Thomas H.; Weber, Bernd; Wen, Wei; West, John D.; Westlye, Lars T.; Whalley, Heather; Wierenga, Lara M.; Wittfeld, Katharina; Wolf, Daniel H.; Worker, Amanda; Wright, Margaret J.; Yang, Kun; Yoncheva, Yulyia; Zanetti, Marcus V.; Ziegler, Georg C.; Karolinska Schizophrenia Project (KaSP); Thompson, Paul M.; Dima, Danai; Radiology and Imaging Sciences, School of Medicine
    Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
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    Dynamic Delirium Severity Trajectories and Their Association With 2-Year Healthcare Utilization and Mortality Outcomes
    (Wolters Kluwer, 2021-09-10) Lindroth, Heidi; Mohanty, Sanjay; Ortiz, Damaris; Gao, Sujuan; Perkins, Anthony J.; Khan, Sikandar H.; Boustani, Malaz A.; Khan, Babar A.; Surgery, School of Medicine
    Delirium severity has been associated with a higher risk of mortality and an increasing morbidity burden. Recently defined delirium severity trajectories were predictive of 30-day mortality in a critically ill patient population. No studies to date have examined associations between delirium severity trajectories and 2-year mortality and healthcare utilization outcomes. Objectives: To examine the associations between recently defined delirium severity trajectories and 2-year healthcare utilization outcomes of emergency department visits, rehospitalizations, and mortality. Design setting and participants: This is a secondary analysis using data from the randomized controlled clinical trial Pharmacological Management of Delirium in the Intensive Care Unit and Deprescribing in the Pharmacologic Management of Delirium trial conducted from 2009 to 2015. Patients who were greater than or equal to 18 years old, were in the ICU for greater than or equal to 24 hours, and had a positive delirium assessment (Confusion Assessment Method for the ICU) were included in the original trial. Participants were included in the secondary analysis if 2-year healthcare utilization and mortality data were available (n = 431). Main outcomes and measures: Healthcare utilization data within 2 years of the initial discharge date were pulled from the Indiana Network for Patient Care. Data over a 2-year period on emergency department visits (days to first emergency department visit, number of emergency department visits), inpatient hospitalizations (days to first hospitalizations, number of hospitalizations), and mortality (time to death) were extracted. Univariate relationships, Cox proportional hazard models, and competing risk modeling were used to examine statistical relationships in SAS v9.4. Results: The overall sample (n = 431) had a mean age of 60 (sd, 16), 56% were females, and 49% African-Americans. No significant associations were identified between delirium severity trajectories and time to event for emergency department visit, mortality, or rehospitalization within 2 years of the index hospital discharge. Conclusions and relevance: This secondary analysis did not identify a significant relationship between delirium severity trajectories and healthcare utilization or mortality within 2 years of hospital discharge.
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    Predictors of trajectories of child neurodevelopment in the first 2 years of life in LMICs: A systematic review and meta-analysis protocol
    (Research Square, 2025-04-16) Nyakato, Mary; Nakasujja, Noeline; Idro, Richard; Akena, Dickens; Naggayi, Shubaya Kasule; Ssemata, Andrew Sentoogo; Nakitende, Anne Jacqueline; Nyangoma, Betty; Ouma, Simple; Ssenkusu, John Mbaziira; Chandy, John C.; Bangirana, Paul; Pediatrics, School of Medicine
    Background: In low-and-middle-income countries (LMICs), children are exposed to multiple risks that may compromise their neurodevelopment, especially during the early years. Early childhood developmental trajectories are crucial, especially in such at-risk populations as they help predict future neurocognitive potential. In LMICs where numerous factors shape child neurodevelopment, describing neurodevelopment trajectories and understanding the predictors that shape them is imperative for early intervention. The systematic review and meta-analysis will determine the predictors of trajectories of child neurodevelopment during the first 2 years of life in LMICs. Methods and analysis: The Preferred Reporting Items for Systematic Review and meta-analysis protocols (PRISMA-P) guidelines will be followed while performing this review. PubMed, Psych INFO, EMBASE, and Google Scholar databases and reference lists of relevant articles will be searched for articles. Selected publications will be uploaded to Endnote to remove duplicates and reviewed by title, abstract, and full text to identify those meeting the eligibility criteria. Longitudinal studies on child neurodevelopment and associated predictors among children aged ≤ 24 months in LMICs will be included. Screening, data extraction, and critical appraisal will be done by two autonomous reviewers. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) will evaluate the risk of bias and funnel plot asymmetry, publication bias. The I 2 statistics will be used to test for heterogeneity in the selected studies and STATA-18 and EPPI-reviewer software for statistical analysis. A random-effects meta-analysis will be undertaken. Discussion: The protocol describes a systematic review and meta-analysis aimed at identifying factors influencing neurodevelopment trajectories during the first 2 years of life in LMICs. The review findings may provide a comprehensive understanding of the factors that influence child neurodevelopment, particularly in the first 2 years of life in LMICs, help identify critical windows of opportunity for intervention, and potentially guide the design of age and contextually appropriate interventions for optimizing neurodevelopmental outcomes, especially in this context.
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    Research Needs for Prognostic Modeling and Trajectory Analysis in Patients with Disorders of Consciousness
    (Springer, 2021) Hammond, Flora M.; Katta-Charles, Sheryl; Russell, Mary Beth; Zafonte, Ross D.; Claassen, Jan; Wagner, Amy K.; Puybasset, Louis; Egawa, Satoshi; Laureys, Steven; Diringer, Michael; Stevens, Robert D.; Curing Coma Campaign and its Contributing Members; Physical Medicine and Rehabilitation, School of Medicine
    Background: The current state of the science regarding the care and prognosis of patients with disorders of consciousness is limited. Scientific advances are needed to improve the accuracy, relevance, and approach to prognostication, thereby providing the foundation to develop meaningful and effective interventions. Methods: To address this need, an interdisciplinary expert panel was created as part of the Coma Science Working Group of the Neurocritical Care Society Curing Coma Campaign. Results: The panel performed a gap analysis which identified seven research needs for prognostic modeling and trajectory analysis ("recovery science") in patients with disorders of consciousness: (1) to define the variables that predict outcomes; (2) to define meaningful intermediate outcomes at specific time points for different endotypes; (3) to describe recovery trajectories in the absence of limitations to care; (4) to harness big data and develop analytic methods to prognosticate more accurately; (5) to identify key elements and processes for communicating prognostic uncertainty over time; (6) to identify health care delivery models that facilitate recovery and recovery science; and (7) to advocate for changes in the health care delivery system needed to advance recovery science and implement already-known best practices. Conclusion: This report summarizes the current research available to inform the proposed research needs, articulates key elements within each area, and discusses the goals and advances in recovery science and care anticipated by successfully addressing these needs.