Faculty Opinions recommendation of Predicting major outcomes in type 1 diabetes: a model development and validation study.

Author(s):  
Giuseppe Penno
Diabetologia ◽  
2014 ◽  
Vol 57 (11) ◽  
pp. 2304-2314 ◽  
Author(s):  
Sabita S. Soedamah-Muthu ◽  
Yvonne Vergouwe ◽  
Tina Costacou ◽  
Rachel G. Miller ◽  
Janice Zgibor ◽  
...  

2017 ◽  
Vol 21 (4) ◽  
pp. 392-403 ◽  
Author(s):  
Stefan Nilsson ◽  
Lena Hanberger ◽  
Anna Lindholm Olinder ◽  
Maria Forsner

The aim of this study was to determine the concurrent and content validity, sensitivity and inter-rater reliability of the Faces Emotional Coping Scale (FECS) to evaluate the children’s anticipation of the level of emotional coping in conjunction with a venepuncture. A total of 153 children with type 1 diabetes and 86 of their parents participated in the study. The age of the children, 76 of whom were boys, ranged from 7 to 18 years. The child and his or her parent reported the child’s coping ability, and the child reported the pain intensity and unpleasantness of a venepuncture. The child also wrote a short narrative about his or her experience of the needle procedure. The FECS correlated negatively with the Coloured Analogue Scale and the Facial Affective Scale and positively with the FECS by proxy. The narratives of 90 children correlated negatively with the FECS. Younger children reported significantly lower scores than older children did regarding their ability to cope with a venepuncture. The children’s scores on the FECS showed good agreement with the parents’ scores. In this study, the FECS was deemed valid for measuring children’s ability to cope with their emotions when undergoing needle-related procedures like venepuncture.


Diabetes Care ◽  
2009 ◽  
Vol 33 (3) ◽  
pp. 457-462 ◽  
Author(s):  
M. B. Koontz ◽  
L. Cuttler ◽  
M. R. Palmert ◽  
M. O'Riordan ◽  
E. A. Borawski ◽  
...  

Diabetologia ◽  
2009 ◽  
Vol 53 (2) ◽  
pp. 254-262 ◽  
Author(s):  
Y. Vergouwe ◽  
S. S. Soedamah-Muthu ◽  
J. Zgibor ◽  
N. Chaturvedi ◽  
C. Forsblom ◽  
...  

2020 ◽  
Author(s):  
Muhammad Faisal ◽  
Mohammed A Mohammed ◽  
Donald Richardson ◽  
Ewout W. Steyerberg ◽  
Massimo Fiori ◽  
...  

AbstractObjectivesTo consider the potential of the National Early Warning Score (NEWS2) for COVID-19 risk prediction on unplanned admission to hospital.DesignLogistic regression model development and validation study using a cohort of unplanned emergency medical admission to hospital.SettingYork Hospital (YH) as model development dataset and Scarborough Hospital (SH) as model validation dataset.ParticipantsUnplanned adult medical admissions discharged over 3 months (11 March 2020 to 13 June 2020) from two hospitals (YH for model development; SH for external model validation) based on admission NEWS2 electronically recorded within ±24 hours of admission. We used logistic regression modelling to predict the risk of COVID-19 using NEWS2 (Model M0’) versus enhanced cNEWS models which included age + sex (model M1’) + subcomponents (including diastolic blood pressure + oxygen flow rate + oxygen scale) of NEWS2 (model M2’). The ICD-10 code ‘U071’ was used to identify COVID-19 admissions. Model performance was evaluated according to discrimination (c statistic), calibration (graphically), and clinical usefulness at NEWS2 ≥5.ResultsThe prevalence of COVID-19 was higher in SH (11.0%=277/2520) than YH (8.7%=343/3924) with higher index NEWS2 (3.2 vs 2.8) but similar in-hospital mortality (8.4% vs 8.2%). The c-statistics for predicting COVID-19 for cNEWS models (M1’,M2’) was substantially better than NEWS2 alone (M0’) in development (M2’: 0.78 (95%CI 0.75-0.80) vs M0’ 0.71 (95%CI 0.68-0.74)) and validation datasets (M2’: 0.72 (95%CI 0.69-0.75) vs M0’ 0.65 (95%CI 0.61-0.68)). Model M2’ had better calibration than Model M0’ with improved sensitivity (M2’: 57% (95%CI 51%-63%) vs M0’ 44% (95%CI 38%-50%)) and similar specificity (M2’: 76% (95%CI 74%-78%) vs M0’ 75% (95%CI 73%-77%)) for validation dataset at NEWS2≥5.ConclusionsModel M2’ is reasonably accurate for predicting the on-admission risk of COVID-19. It may be clinically useful for an early warning system at the time of admission especially to triage large numbers of unplanned hospital admissions.


2021 ◽  
Vol 45 (7) ◽  
pp. S4-S5
Author(s):  
Peter Senior ◽  
Kate Farnsworth ◽  
Joseph Cafazzo ◽  
Madison Taylor ◽  
Melanie Yeung

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