scholarly journals Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8793
Author(s):  
Yi-sheng Chen ◽  
Yan-xian Cai ◽  
Xue-ran Kang ◽  
Zi-hui Zhou ◽  
Xin Qi ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Elderly Patients ◽  
Prediction Model ◽  
Predictive Model ◽  
Body Mass ◽  
Curve Analysis ◽  
Advanced Age ◽  
Decision Curve Analysis ◽  
Low Body Mass Index ◽  
Patellar Fractures

Purpose To develop a risk prediction model for postoperative sarcopenia in elderly patients with patellar fractures in China. Patients and methods We conducted a community survey of patients aged ≥55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (lasso analysis) as well as the Support Vector Machine (SVM) algorithm. The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We also conducted internal sampling methods for qualitative assessment. Result We recruited 137 participants (53 male; mean age, 65.7 years). Various risk factors were assessed, and low body mass index and advanced age were identified as the most important risk factor (P < 0.05). The prediction rate of the model was good (C-index: 0.88; 95% CI [0.80552–0.95448]), with a satisfactory correction effect. The C index is 0.97 in the validation queue and 0.894 in the entire cohort. Decision curve analysis suggested good clinical practicability. Conclusion Our prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, less outdoor exercise, no postoperative rehabilitation, different surgical methods, diabetes, open fracture, and removal of internal fixation.

scholarly journals Predicting the risk of sarcopenia in elderly patients with patellar fracture: Development and assessment of a new predictive nomogram

2019 ◽  
Author(s):  
Chen Yisheng ◽  
Tao Jie
Keyword(s):  
Risk Factors ◽  
Body Mass Index ◽  
Elderly Patients ◽  
Prediction Model ◽  
Predictive Model ◽  
Body Mass ◽  
Curve Analysis ◽  
Decision Curve Analysis ◽  
Low Body Mass Index ◽  
Patellar Fractures

AbstractPurposeThis study was aimed at developing a risk prediction model for postoperative dysplasia in elderly patients with patellar fractures in China.Patients and methodsWe conducted a community survey of patients aged ≥55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (Lasso analysis). The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We conducted internal sampling methods for qualitative assessment.ResultWe recruited 61 participants (males: 20, mean age: 68.1 years). Various risk factors were assessed, and low body mass index and diabetes mellitus were identified as the most important risk factors (P<0.05). The model showed a good prediction rate (C-index: 0.909; 95% confidence interval: 0.81–1.00) and good correction effect. The C-index remained high (0.828) even after internal sample verification. Decision curve analysis showed that the risk of sarcopenia was 8.3–80.0%, suggesting good clinical practicability.ConclusionOur prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, longer postoperative hospital stay, no higher education, no postoperative rehabilitation, removal of internal fixation, and less outdoor exercise.

Sex-Associated Differences in the Handgrip Strength of Elderly Individuals

2019 ◽  
Vol 42 (4) ◽  
pp. 262-268 ◽  
Author(s):  
Yeunhee Kwak ◽  
Yoonjung Kim ◽  
Haekyung Chung
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Handgrip Strength ◽  
Low Frequency ◽  
Advanced Age ◽  
Related Factors ◽  
Elderly Individuals ◽  
Muscle Strengthening ◽  
Factors Associated ◽  
Low Body Mass Index

This study aimed to identify sex-specific factors associated with handgrip strength in elderly individuals. The analysis cohort comprised 1,197 men and 1,384 women aged ≥65 years. In men, factors associated with low handgrip strength included advanced age; low body mass index; low frequency of performing flexibility exercises; limited self-care ability (which is a measure of the health-related quality of life); and the presence of diabetes, stroke, or osteoporosis ( R² = 0.285, F = 7.52, p < .001). In women, the factors included advanced age, low body mass index, low frequency of performing muscle strengthening exercises, stress, and osteoarthritis ( R² = 0.225, F = 4.17, p < .001). Effective health-promoting interventions for elderly individuals require the development of individualized programs that enhance handgrip strength while considering sex-related factors.

scholarly journals A prediction modeling based on SNOT-22 score for endoscopic nasal septoplasty: a retrospective study

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9890
Author(s):  
Xue-ran Kang ◽  
Bin Chen ◽  
Yi-sheng Chen ◽  
Bin Yi ◽  
Xiaojun Yan ◽  
...  
Keyword(s):  
Prediction Model ◽  
Predictive Model ◽  
Surgical Outcome ◽  
Middle Turbinate ◽  
Multivariate Logistic Regression Analysis ◽  
Preoperative Assessment ◽  
Curve Analysis ◽  
Decision Curve Analysis ◽  
Nasal Septoplasty ◽  
Snot 22

Background To create a nomogram prediction model for the efficacy of endoscopic nasal septoplasty, and the likelihood of patient benefiting from the operation. Methods A retrospective analysis of 155 patients with nasal septum deviation (NSD) was performed to develop a predictive model for the efficacy of endoscopic nasal septoplasty. Quality of life (QoL) data was collected before and after surgery using Sinonasal Outcome Test-22 (SNOT-22) scores to evaluate the surgical outcome. An effective surgical outcome was defined as a SNOT-22 score change ≥ 9 points after surgery. Multivariate logistic regression analysis was then used to establish a predictive model for the NSD treatment. The predictive quality and clinical utility of the predictive model were assessed by C-index, calibration plots, and decision curve analysis. Results The identified risk factors for inclusion in the predictive model were included. The model had a good predictive power, with a AUC of 0.920 in the training group and a C index of 0.911 in the overall sample. Decision curve analysis revealed that the prediction model had a good clinical applicability. Conclusions Our prediction model is efficient in predicting the efficacy of endoscopic surgery for NSD through evaluation of factors including: history of nasal surgery, preoperative SNOT-22 score, sinusitis, middle turbinate plasty, BMI, smoking, follow-up time, seasonal allergies, and advanced age. Therefore, it can be cost-effective for individualized preoperative assessment.

Clinical effects of low body mass index on geriatric status in elderly patients

2018 ◽  
Vol 110 ◽  
pp. 86-91 ◽  
Author(s):  
Koji Naruishi ◽  
Hiromichi Yumoto ◽  
Jun-ichi Kido
Keyword(s):  
Body Mass Index ◽  
Elderly Patients ◽  
Body Mass ◽  
Clinical Effects ◽  
Low Body Mass Index

scholarly journals Association between cardiovascular disease and dementia

2009 ◽  
Vol 3 (4) ◽  
pp. 308-314 ◽  
Author(s):  
Claudia Kimie Suemoto ◽  
Renata Eloah Ferretti ◽  
Lea Tenenholz Grinberg ◽  
Kátia Cristina de Oliveira ◽  
José Marcelo Farfel ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Body Mass Index ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Body Mass ◽  
Physical Inactivity ◽  
Circle Of Willis ◽  
Advanced Age ◽  
Low Body Mass Index

Abstract Longitudinal studies have shown association between cardiovascular risk factors and dementia. However, these studies are not capable of detecting asymptomatic cardiovascular alterations and thus may provide erroneous estimates of association. Autopsy studies could be more useful in elucidating these questions. The present clinicopathological study sought to examine the relationship between dementia, cardiovascular risk factors and disease. Methods: 603 subjects, who underwent autopsy, were classified regarding the presence of dementia, according to post mortem cognitive classification. Demographics, cardiovascular risk factors, and anatomically-proven cardiovascular disease (myocardial hypertrophy, cerebral and carotid atherosclerosis) were compared among cognitively normal persons and individuals with dementia. Results: Cognitive deficit was associated with advanced age, stroke, physical inactivity and low body mass index (p<0.05). Circle of Willis atherosclerosis was greater in patients with dementia than in controls on univariate analysis (p=0.01). However, this association lost significance when adjusted by age and gender (p=0.61). Heart failure and anatomopathological cardiac parameters were more severe in the control group than in demented individuals (p<0.05). Carotid artery atherosclerosis and intima-media thickness were similar in both groups. Conclusion: Advanced age, stroke, physical inactivity and low body mass index were linked to dementia. Circle of Willis atherosclerosis was associated with dementia only when age was not considered. Our results suggest that cerebral artery atherosclerosis was not directly associated with clinical expression of dementia.

scholarly journals P5669Prognostic impact of low body-mass index in elderly patients with heart failure

2018 ◽  
Vol 39 (suppl_1) ◽  
Author(s):  
Y Okuma ◽  
H Motoki ◽  
M Minamisawa ◽  
S Suzuki ◽  
W Shoin ◽  
...  
Keyword(s):  
Heart Failure ◽  
Body Mass Index ◽  
Elderly Patients ◽  
Body Mass ◽  
Patients With Heart Failure ◽  
Low Body Mass Index

The biopsychosocial assessment of people with low body mass index

2016 ◽  
Vol 20 (2) ◽  
pp. 64-71
Author(s):  
Funda Yıldırım Baş ◽  
Bahriye Arslan ◽  
Yasemin Türker
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Low Body Mass Index ◽  
Biopsychosocial Assessment
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