Optimization of clinical risk‐factor interpretation and radiological findings with machine learning for PIRADS category 3 patients

The Prostate ◽  
2021 ◽  
Author(s):  
Pubordee Aussavavirojekul ◽  
Apirak Hoonlor ◽  
Sittiporn Srinualnad
Keyword(s):  
Machine Learning ◽  
Risk Factor ◽  
Clinical Risk Factor ◽  
Radiological Findings ◽  
Clinical Risk

scholarly journals Male gender is an important clinical risk factor for iron deficiency in healthy infants

2012 ◽  
Vol 7 (6) ◽  
pp. e219-e222 ◽  
Author(s):  
Henedina Antunes ◽  
Cristina Santos ◽  
Susana Carvalho ◽  
Sónia Gonçalves ◽  
Altamiro Costa-Pereira
Keyword(s):  
Risk Factor ◽  
Iron Deficiency ◽  
Male Gender ◽  
Clinical Risk Factor ◽  
Clinical Risk ◽  
Healthy Infants

Epidemiology of Coronary Atherosclerosis: Postmortem vs Clinical Risk Factor Correlations. The Framingham Study

1980 ◽  
pp. 54-56 ◽  
Author(s):  
W. B. Kannel ◽  
Paul Sorlie ◽  
Frederick Brand ◽  
W. P. Castelli ◽  
P. M. McNamara ◽  
...  
Keyword(s):  
Risk Factor ◽  
Coronary Atherosclerosis ◽  
Clinical Risk Factor ◽  
Framingham Study ◽  
Clinical Risk

Can the trabecular bone score (TBS) be considered as a major clinical risk factor (CRF) of osteoporotic fractures? A meta-like analysis

Bone ◽  
2012 ◽  
Vol 50 ◽  
pp. S151 ◽  
Author(s):  
D. Hans ◽  
R. Winzenrieth⁎ ◽  
B. Aubry-Rozier ◽  
D. Stoll ◽  
O. Lamy ◽  
...  
Keyword(s):  
Risk Factor ◽  
Trabecular Bone ◽  
Trabecular Bone Score ◽  
Osteoporotic Fractures ◽  
Clinical Risk Factor ◽  
Clinical Risk

scholarly journals P1.16-33 From a Systematic Review to Real World Evidence: Integrating Gender as a Clinical Risk Factor in NSCLC

2019 ◽  
Vol 14 (10) ◽  
pp. S600
Author(s):  
N. Alsaadoun ◽  
K. Kopciuk ◽  
D. Hao ◽  
F. Hao ◽  
A. Elegbede ◽  
...  
Keyword(s):  
Systematic Review ◽  
Risk Factor ◽  
Real World ◽  
Clinical Risk Factor ◽  
Clinical Risk ◽  
Real World Evidence

scholarly journals Clinical risk factor assessment had better discriminative ability than bone mineral density in identifying subjects with vertebral fracture

2010 ◽  
Vol 22 (2) ◽  
pp. 667-674 ◽  
Author(s):  
S. W. Y. Tsang ◽  
C. H. Bow ◽  
E. Y. W. Chu ◽  
S. C. Yeung ◽  
C. C. Soong ◽  
...  
Keyword(s):  
Bone Mineral Density ◽  
Risk Factor ◽  
Vertebral Fracture ◽  
Bone Mineral ◽  
Clinical Risk Factor ◽  
Mineral Density ◽  
Discriminative Ability ◽  
Risk Factor Assessment ◽  
Clinical Risk

scholarly journals AB1290-HPR UTILITY OF FRAX IN THE RISK DETECTION OF FRACTURE IN SPONDYLOARTHRITIS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1935.2-1935
Author(s):  
D. Palma Sanchez ◽  
A. Haro ◽  
M. J. Moreno ◽  
E. Peñas ◽  
M. Mayor ◽  
...  
Keyword(s):  
Risk Factor ◽  
High Risk ◽  
Osteoporotic Fracture ◽  
Clinical Risk Factor ◽  
Intermediate Risk ◽  
Mineral Density ◽  
Risk Of Fracture ◽  
Additional Information ◽  
Clinical Risk ◽  
Asas Criteria

Background:Axial spondyloarthritis (SpAax) presents an increased risk of vertebral fracture not fully detected by Dual energy X-ray absorptiometry (DXA). The FRAX algorithms give the 10-year probability of hip fracture and of mayor osteoporotic fracture (clinical spine, forearm, hip or shoulder fracture), taking into account 11 clinical risk factors.Objectives:To analyze the suitability of FRAX to detect the risk of fracture in patients with SpAax. To assess whether the incorporation of SpAax as a clinical risk factor to conventional FRAX provides additional information.Methods:Cross-sectional study in which SpAax patients (ASAS criteria) were included. Clinical-demographic and related to the disease variables were collected. FRIDEX model for Spanish population was used to determine low, intermediate or high risk of mayor fracture by FRAX. These results were compared with those obtained by DXA and trabecular bone score (TBS). In the statistical analysis we used mean and standard deviation (SD) in quantitative variables and frequency in qualitative ones. To compare means among 3 groups, ANOVA test was used.Results:The characteristics of the patients are shown in Table 1. According to FRIDEX, no patient had high risk of fracture and 2.4% had intermediate risk. When SpAax was added as a risk factor, no patient had high risk of fracture and 6.1% presented intermediate risk. According to DXA, 7.3% had high risk of fracture and 41.3% intermediate risk. TBS detected high risk of fracture in 18.3% and intermediate risk also in 18.3% of patients.Table 1.Sociodemographic, clinical and related characteristics with the disease (BMD: bone mineral density, BMI: index of body mass)Gender (Male), n (%)61 (74.4)Age, mean ± SD49.48 ± 12.47BMI, mean ± SD27.13 ± 4.42Smoking, n (%)26 (31.7)Diabetes mellitus, n (%)9 (11)Osteoporotic fracture, n (%)1 (1.2)Disease duration (years), mean ± SD11.77 ± 10syndesmophytes, n (%)38 (46.3)ASDAS-PCR, mean ± SD2.55 ± 1.07Lumbar BMD (g / cm2), mean ± SD1.032 ± 0.180BMD femoral neck (g / cm2), mean ± SD0.816 ± 0.140Lumbar TBS, mean ± SD1.383 ± 0.133Conclusion:FRAX does not seem an adequate tool to detect the risk of fracture in patients with SpAax since it did not improve the results obtained by DXA meanwhile TBS did. The incorporation of SpAax as a clinical risk factor to conventional FRAX did not provide additional information in most casesDisclosure of Interests:None declared

scholarly journals Preventing early-onset group B streptococcal sepsis: clinical risk factor-based screening or culture-based screening?

2019 ◽  
Author(s):  
J Lee ◽  
K Naiduvaje ◽  
KL Chew ◽  
N Charan ◽  
YH Chan ◽  
...  
Keyword(s):  
Risk Factor ◽  
Early Onset ◽  
Clinical Risk Factor ◽  
Clinical Risk ◽  
Streptococcal Sepsis ◽  
Group B ◽  
Onset Group ◽  
Early Onset Group
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