scholarly journals Grip strength as a predictor of depressive symptoms among vulnerable elderly Europeans with musculoskeletal conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Priscila Marconcin ◽  
Adilson Marques ◽  
Duarte Henriques-Neto ◽  
Élvio R. Gouveia ◽  
Gerson Ferrari ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Grip Strength ◽  
Receiver Operating Characteristics ◽  
Operating Characteristics ◽  
Men And Women ◽  
Elderly Individuals ◽  
Musculoskeletal Conditions ◽  
Receiver Operating Characteristics Curve ◽  
Health Aging ◽  
Vulnerable Elderly

AbstractThe present study aimed to investigate the grip strength (GS) discrimination capacity and cutoffs points for depressive symptoms among vulnerable elderly individuals with musculoskeletal conditions. The Survey of Health, Aging, and Retirement in Europe wave 6 was analyzed. GS was measured by a handgrip dynamometer, and EURO-D scale was used to assess depressive symptoms. GS cutoff values for depressive symptoms were calculated using the receiver operating characteristics curve. 2206 participants, mean age 74.0 (73.7–74.3), 78.8% with osteoarthritis/other rheumatism, enrolled in the study. Sensitivity varies between 0.44 (men, ≥ 85 years) and 0.82 (men, 75–84 years), and specificity varying between 0.35 (women, 75–84 years) and 0.70 (men 75–84 years). GS is associated with depressive symptoms just for women and it is not possible to use a GS cutoff point for screening depressive symptoms for vulnerable men and women with musculoskeletal conditions over the age of 65 years.

scholarly journals qTICI: Quantitative assessment of brain tissue reperfusion on digital subtraction angiograms of acute ischemic stroke patients

2020 ◽  
pp. 174749302090963
Author(s):  
Haryadi Prasetya ◽  
Lucas A Ramos ◽  
Thabiso Epema ◽  
Kilian M Treurniet ◽  
Bart J Emmer ◽  
...  
Keyword(s):  
Functional Outcome ◽  
Digital Subtraction Angiography ◽  
Quantitative Measure ◽  
Receiver Operating Characteristics ◽  
Binary Logistic Regression Analysis ◽  
Digital Subtraction ◽  
Operating Characteristics ◽  
Vessel Occlusion ◽  
Receiver Operating Characteristics Curve ◽  
Receiver Operating

Background The Thrombolysis in Cerebral Infarction (TICI) scale is an important outcome measure to evaluate the quality of endovascular stroke therapy. The TICI scale is ordinal and observer-dependent, which may result in suboptimal prediction of patient outcome and inconsistent reperfusion grading. Aims We present a semi-automated quantitative reperfusion measure (quantified TICI (qTICI)) using image processing techniques based on the TICI methodology. Methods We included patients with an intracranial proximal large vessel occlusion with complete, good quality runs of anteroposterior and lateral digital subtraction angiography from the MR CLEAN Registry. For each vessel occlusion, we identified the target downstream territory and automatically segmented the reperfused area in the target downstream territory on final digital subtraction angiography. qTICI was defined as the percentage of reperfused area in target downstream territory. The value of qTICI and extended TICI (eTICI) in predicting favorable functional outcome (modified Rankin Scale 0–2) was compared using area under receiver operating characteristics curve and binary logistic regression analysis unadjusted and adjusted for known prognostic factors. Results In total, 408 patients with M1 or internal carotid artery occlusion were included. The median qTICI was 78 (interquartile range 58–88) and 215 patients (53%) had an eTICI of 2C or higher. qTICI was comparable to eTICI in predicting favorable outcome with area under receiver operating characteristics curve of 0.63 vs. 0.62 (P = 0.8) and 0.87 vs. 0.86 (P = 0.87), for the unadjusted and adjusted analysis, respectively. In the adjusted regression analyses, both qTICI and eTICI were independently associated with functional outcome. Conclusion qTICI provides a quantitative measure of reperfusion with similar prognostic value for functional outcome to eTICI score.

scholarly journals Evaluating and comparing biomarkers with respect to the area under the receiver operating characteristics curve in two-phase case–control studies

Biostatistics ◽  
2016 ◽  
Vol 17 (3) ◽  
pp. 499-522 ◽  
Author(s):  
Ying Huang
Keyword(s):  
Case Control ◽  
Receiver Operating Characteristics ◽  
Biased Sampling ◽  
Second Phase ◽  
Operating Characteristics ◽  
Case Control Studies ◽  
Two Phase ◽  
Receiver Operating Characteristics Curve ◽  
The Impact ◽  
Receiver Operating

Abstract Two-phase sampling design, where biomarkers are subsampled from a phase-one cohort sample representative of the target population, has become the gold standard in biomarker evaluation. Many two-phase case–control studies involve biased sampling of cases and/or controls in the second phase. For example, controls are often frequency-matched to cases with respect to other covariates. Ignoring biased sampling of cases and/or controls can lead to biased inference regarding biomarkers' classification accuracy. Considering the problems of estimating and comparing the area under the receiver operating characteristics curve (AUC) for a binary disease outcome, the impact of biased sampling of cases and/or controls on inference and the strategy to efficiently account for the sampling scheme have not been well studied. In this project, we investigate the inverse-probability-weighted method to adjust for biased sampling in estimating and comparing AUC. Asymptotic properties of the estimator and its inference procedure are developed for both Bernoulli sampling and finite-population stratified sampling. In simulation studies, the weighted estimators provide valid inference for estimation and hypothesis testing, while the standard empirical estimators can generate invalid inference. We demonstrate the use of the analytical variance formula for optimizing sampling schemes in biomarker study design and the application of the proposed AUC estimators to examples in HIV vaccine research and prostate cancer research.

scholarly journals Overweight in Young Athletes: New Predictive Model of Overfat Condition

2019 ◽  
Vol 16 (24) ◽  
pp. 5128 ◽  
Author(s):  
Gabriele Mascherini ◽  
Cristian Petri ◽  
Elena Ermini ◽  
Vittorio Bini ◽  
Piergiuseppe Calà ◽  
...  
Keyword(s):  
Fat Mass ◽  
Weight Status ◽  
Low Cost ◽  
Normal Weight ◽  
Receiver Operating Characteristics ◽  
Operating Characteristics ◽  
Young Athletes ◽  
Receiver Operating Characteristics Curve ◽  
Calculated Probability ◽  
Correct Weight

The aim of the study is to establish a simple and low-cost method that, associated with Body Mass Index (BMI), differentiates overweight conditions due to a prevalence of lean mass compared to an excess of fat mass during the evaluation of young athletes. 1046 young athletes (620 male, 426 female) aged between eight and 18 were enrolled. Body composition assessments were performed with anthropometry, circumferences, skinfold, and bioimpedance. Overweight was established with BMI, while overfat was established with the percentage of fat mass: 3.5% were underweight, 72.8% were normal weight, 20.1% were overweight, and 3.5% were obese according to BMI; according to the fat mass, 9.5% were under fat, 63.6% were normal fat, 16.2% were overfat, and 10.8% were obese. Differences in overfat prediction were found using BMI alone or with the addition of the triceps fold (area under the receiver operating characteristics curve (AUC) for BMI = 0.867 vs. AUC for BMI + TRICEPS = 0.955, p < 0.001). These results allowed the creation of a model factoring in age, sex, BMI, and triceps fold that could provide the probability that a young overweight athlete is also in an overfat condition. The calculated probability could reduce the risk of error in establishing the correct weight status of young athletes.

Higher Baseline Cortical Score Predicts Good Outcome in Patients With Low Alberta Stroke Program Early Computed Tomography Score Treated with Endovascular Treatment

Neurosurgery ◽  
2020 ◽  
Author(s):  
Peng-fei Xing ◽  
Yong-wei Zhang ◽  
Lei Zhang ◽  
Zi-fu Li ◽  
Hong-jian Shen ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Endovascular Treatment ◽  
Receiver Operating Characteristics ◽  
Operating Characteristics ◽  
Good Outcome ◽  
Poor Outcome ◽  
Poor Outcome Group ◽  
Outcome Group ◽  
Receiver Operating Characteristics Curve ◽  
Receiver Operating

Abstract BACKGROUND Patients with large vessel occlusion and noncontrast computed tomography (CT) Alberta Stroke Program Early CT Score (ASPECTS) &lt;6 may benefit from endovascular treatment (EVT). There is uncertainty about who will benefit from it. OBJECTIVE To explore the predicting factors for good outcome in patients with ASPECTS &lt;6 treated with EVT. METHODS We retrospectively reviewed 60 patients with ASPECTS &lt;6 treated with EVT in our center between March 2018 and June 2019. Patients were divided into 2 groups because of the modified Rankin Score (mRS) at 90 d: good outcome group (mRS 0-2) and poor outcome group (mRS ≥3). Baseline and procedural characteristics were collected for unilateral variate and multivariate regression analyses to explore the influent variates for good outcome. RESULTS Good outcome (mRS 0-2) was achieved in 24 (40%) patients after EVT and mortality was 20% for 90 d. Compared with the poor outcome group, higher baseline cortical ASPECTS (c-ASPECTS), lower intracranial hemorrhage, and malignant brain edema after thrombectomy were noted in the good outcome group (all P &lt; .01). Multivariate logistic regression showed that only baseline c-ASPECTS (≥3) was positive factor for good outcome (odds ratio = 4.29; 95% CI, 1.21-15.20; P = .024). The receiver operating characteristics curve indicated a moderate value of c-ASPECTS for predicting good outcome, with the area under receiver operating characteristics curve 0.70 (95% CI, 0.56-0.83; P = .011). CONCLUSION Higher baseline c-ASPECTS was a predictor for good clinical outcome in patients with ASPECTS &lt;6 treated with EVT, which could be helpful to treatment decision.

Sign in / Sign up

Export Citation Format

Share Document