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Marieke S Velema, Evie J M Linssen, Ad R M M Hermus, Hans J M M Groenewoud, Gert-Jan van der Wilt, Antonius E van Herwaarden, Jacques W M Lenders, Henri J L M Timmers and Jaap Deinum

development and validation of prediction models ( 5 ). Patients Our cohort consisted of adult patients who underwent an SLT for clinically suspected PA at the Radboud Adrenal Center, a tertiary center of expertise for patients with adrenal disorders in

Open access

Huguette S Brink, Aart Jan van der Lely and Joke van der Linden

) identify potential predictive biomarkers in GD and ( 2 ) discuss the role of incorporating predictive biomarkers into clinical risk prediction models, for the stratification of high-risk patients. Epigenetic footprint Metabolic alterations such as

Open access

Emmanuel K Fai, Cheryl Anderson and Victor Ferreros

The purpose of this quantitative study was to investigate the extent to which patient attitudes and intentions predict adherence to the use of oral antihyperglycemic regimens in African Americans. This cross-sectional study of 115 participants used correlation analysis to establish relationships among patient attitudes, intentions and adherence. Data analyses showed significant correlations between the variables. Multiple regression analysis was used to establish predictions between the variables. A prediction model containing attitudes, subjective norms and perceived behavioral control (PBC) explained 37% of the variance to behavioral intention. Intentions accounted for 8.5% of the variance to adherence. Attitudes predicted behavioral intentions. The findings support the theory of planned behavior model and identify important correlations between attitudes, intentions and behaviors. In addition, the results underscore the need for promoting positive attitudes and positive intentions in effective adherence to the use of oral antihyperglycemic regimens. Achieving adequate adherence through behavioral counseling can effect positive social change by reducing the mortality and morbidity that are associated with inadequate adherence to the use of oral diabetic agents.

Open access

Urszula Smyczyńska, Joanna Smyczyńska, Maciej Hilczer, Renata Stawerska, Ryszard Tadeusiewicz and Andrzej Lewiński

, significant variability in its effectiveness in different patients is observed ( 1 , 2 ). Taking into account the inconsistent and sometimes disappointing effects of treatment, the need to create prediction models of growth response to GH therapy has been

Open access

Nidan Qiao

into four stages when developing a prediction model. The first step is to bring out the clinical question, which is summarized as ‘predicting Outcome using Predictors in a Cohort’. A study should choose the appropriate outcome, predictors and the data

Open access

Werner F Blum, Abdullah Alherbish, Afaf Alsagheir, Ahmed El Awwa, Walid Kaplan, Ekaterina Koledova and Martin O Savage

particularly in non-GH deficiency disorders such as Turner syndrome, short stature related to birth size small for gestational age (SGA) and idiopathic short stature ( 5 ), has led to development of prediction models of growth response ( 6 ) and a recognition

Open access

Yang Lv, Ning Pu, Wei-lin Mao, Wen-qi Chen, Huan-yu Wang, Xu Han, Yuan Ji, Lei Zhang, Da-yong Jin, Wen-Hui Lou and Xue-feng Xu

NEC staging systems. Because NET is heterogeneous with respect to survival of individual patients, prediction just using the TNM staging system or WHO classification is imprecise ( 2 ). For those with rectal NEC disease, a prognostic prediction model

Open access

Mélanie Rouleau, Francis Lemire, Michel Déry, Benoît Thériault, Gabriel Dubois, Yves Fradet, Paul Toren, Chantal Guillemette, Louis Lacombe, Laurence Klotz, Fred Saad, Dominique Guérette and Frédéric Pouliot

ignoring the values <0.416 nM as given by the IA apparatus for which an MS value ≥0.1 nM was available and to use a prediction model instead. We have fitted a linear regression model using a maximum likelihood method to estimate the testosterone values when

Open access

Gudmundur Johannsson, Martin Bidlingmaier, Beverly M K Biller, Margaret Boguszewski, Felipe F Casanueva, Philippe Chanson, Peter E Clayton, Catherine S Choong, David Clemmons, Mehul Dattani, Jan Frystyk, Ken Ho, Andrew R Hoffman, Reiko Horikawa, Anders Juul, John J Kopchick, Xiaoping Luo, Sebastian Neggers, Irene Netchine, Daniel S Olsson, Sally Radovick, Ron Rosenfeld, Richard J Ross, Katharina Schilbach, Paulo Solberg, Christian Strasburger, Peter Trainer, Kevin C J Yuen, Kerstin Wickstrom, Jens O L Jorgensen and on behalf of the Growth Hormone Research Society

correlated with growth rates in subsequent years and adult height. Prediction models using auxology, bone age and other variables have been advocated as tools for individual patient management ( 10 , 11 , 12 ). Measurement of body proportions can be helpful

Open access

Lang Qin, Xiaoming Zhu, Xiaoxia Liu, Meifang Zeng, Ran Tao, Yan Zhuang, Yiting Zhou, Zhaoyun Zhang, Yehong Yang, Yiming Li, Yongfei Wang and Hongying Ye

analysis Data are presented as median (range), unless otherwise indicated. Pearson correlation coefficients were used for correlation analyses. Linear regression was used to build prediction models of SBP from each predictor of interest respectively