Long-term Evaluation of Hair Transplantation into Various Recipient Sites

2006 ◽  
Vol 16 (2) ◽  
pp. 37-45
Author(s):  
Sungjoo “Tommy” Hwang
Keyword(s):  
Hair Transplantation ◽  
Term Evaluation

Respiratory rehabilitation with heat moisture exchanger after total laryngectomy: long-term evaluation

2019 ◽  
Vol 69 (2) ◽  
Author(s):  
Eugenia Allegra ◽  
Ignazio La Mantia ◽  
Maria R. Bianco ◽  
Nicolò Marino ◽  
Alessio Fallica ◽  
...  
Keyword(s):  
Total Laryngectomy ◽  
Moisture Exchanger ◽  
Term Evaluation ◽  
Respiratory Rehabilitation

scholarly journals A 16-year prospective cohort study to evaluate effects of long-term fluctuations in obesity indices of prediabetics on the incidence of future diabetes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shahla Safari ◽  
Maryam Abdoli ◽  
Masoud Amini ◽  
Ashraf Aminorroaya ◽  
Awat Feizi
Keyword(s):  
High Risk ◽  
Transition Probabilities ◽  
Clinical Settings ◽  
High Tendency ◽  
Mean Values ◽  
Latent Markov Model ◽  
Term Evaluation ◽  
Obesity Indices

AbstractThis study aimed to evaluate the patterns of changes in obesity indices over time in prediabetic subjects and to classify these subjects as either having a low, moderate, and high risk for developing diabetes in the future. This study was conducted among 1228 prediabetics. The patterns of changes in obesity indices based on three measurements including first, mean values during the follow-up period, and last visit from these indices were evaluated by using the latent Markov model (LMM). The mean (standard deviation) age of subjects was 44.0 (6.8) years and 73.6% of them were female. LMM identified three latent states of subjects in terms of change in all anthropometric indices: a low, moderate, and high tendency to progress diabetes with the state sizes (29%, 45%, and 26%), respectively. LMM showed that the probability of transitioning from a low to a moderate tendency to progress diabetes was higher than the other transition probabilities. Based on a long-term evaluation of patterns of changes in obesity indices, our results reemphasized the values of all five obesity indices in clinical settings for identifying high-risk prediabetic subjects for developing diabetes in future and the need for more effective obesity prevention strategies.

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