MATERIALS AND METHODS: We conducted a cross-sectional study of men aged above 40 years with no history of prostate cancer, prostate surgery, or 5α-reductase inhibitor treatment. Serum prostate-specific antigen (PSA) and total PV were measured in each subject. Potential sociodemographic and clinical variables including age, weight, comorbidities, and International Prostate Symptom Score (IPSS) were collected. Of 1034 subjects, 837 were used in building the PV calculator using regression analysis. The remaining 1/5 (n = 197) was used for model validation.
RESULTS: There were 1034 multiethnic Asian men (Chinese 52.9%, Malay 35.4%, and Indian 11.7%) with mean age of 60 ± 7.6 years. Average PV was 29.4 ± 13.0 mL while the overall mean of PSA was 1.7 ± 1.7 ng/mL. We identified age, IPSS, weight, and PSA (all P
METHODS: A cross sectional study by adopting European Quality of Life scale (EQ-5D) for the assessment of HRQoL was conducted. All registered HB patients attending two public hospitals in Quetta, Pakistan were approached for study. Descriptive statistics were used to describe demographic and disease related characteristics of the patients. HRQoL was scored using values adapted from the United Kingdom general population survey. EQ-5D scale scores were compared with Mann-Whitney and Kruskal-Wallis test. Standard multiple regression analysis was performed to identify predictors of HRQoL. All analyses were performed using SPSS v 16.0.
RESULTS: Three hundred and ninety HB patients were enrolled in the study. Majority of the participants (n = 126, 32.3%) were categorized in the age group of 18-27 years (36.07 ± 9.23). HRQoL was measured as poor in the current study patients (0.3498 ± 0.31785). The multivariate analysis revealed a significant model (F(10, 380) = 40.04, P
METHODS: The derivation cohort included 90 Malaysian GBS patients with two sets of NCS performed early (1-20days) and late (3-8 weeks). Potential predictors of AIDP were considered in univariate and multivariate logistic regression models to develop a predictive model. The model was externally validated in 102 Japanese GBS patients.
RESULTS: Median motor conduction velocity (MCV), ulnar distal motor latency (DML) and abnormal ulnar/normal sural pattern were independently associated with AIDP at both timepoints (median MCV: p = 0.038, p = 0.014; ulnar DML: p = 0.002, p = 0.003; sural sparing: p = 0.033, p = 0.009). There was good discrimination of AIDP (area under the curve (AUC) 0.86-0.89) and this was valid in the validation cohort (AUC 0.74-0.94). Scores ranged from 0 to 6, and corresponded to AIDP probabilities of 15-98% at early NCS and 6-100% at late NCS.
CONCLUSION: The probabilities of AIDP could be reliably predicted based on median MCV, ulnar DML and ulnar/sural sparing pattern that were determined at early and late stages of GBS.
SIGNIFICANCE: A simple and valid model was developed which can accurately predict the probability of AIDP.
SUBJECTS AND METHODS: This cross-sectional study was conducted among all (n = 361) consented dental undergraduate students of our dental school. A twenty-item Lay's Procrastination Scale for student population and a ten-item General Self-Efficacy Scale were used for the study after getting institutional ethical approval. The quantitative data were explained using descriptive statistics. Independent sample t-test and ANOVA were used to determine the association between self-efficacy, academic procrastination, and genders and academic years. Pearson correlation coefficient was used to determine the association between self-efficacy and procrastination. Multiple linear regression analysis was performed to determine the related factors to academic procrastination.
RESULTS: High procrastination (score ≥62) was seen among 28.5% of students. The mean self-efficacy score was 29.5. There was no significant difference between genders for procrastination scores (P = 0.835) and between academic years (P = 0.226). Males showed significantly more self-efficacy (P < 0.001), and self-efficacy did not show any significant difference (P = 0.204) between academic years though a tendency for year 5 students to have lower self-efficacy scores was observed. Academic procrastination was negatively correlated with self-efficacy (r = -0.238 and P < 0.001).
CONCLUSIONS: For dental undergraduates who have cognitive load as well as work associated with patients, procrastination and self-efficacy are negatively correlated.