Approaches to study in higher education portuguese students: a portuguese version of the Approaches and Study Skills Inventory for Students (ASSIST)

This paper examines the validity of the Approaches and Study Skills Inventory for Students—short version (ASSIST; Tait et al. in Improving student learning: Improving students as learners, 1998), to be used with Portuguese undergraduate students. The ASSIST was administrated to 566 students, in order to analyse a Portuguese version of this inventory. Exploratory factor analysis (principal axis factor analysis followed by direct oblimin rotation) reproduced the three main factors that correspond to the original dimensions of the inventory (deep, surface apathetic and strategic approaches to learning). The results are consistent with the background theory on approaches to learning. Additionally, the reliability analysis revealed acceptable internal consistency indexes for the main scales and subscales. This inventory might represent a valuable research tool for the assessment of approaches to learning among Portuguese higher education students

Quantifying atherogenic lipoproteins for lipid-lowering strategies: consensus-based recommendations from EAS and EFLM

The joint consensus panel of the European Atherosclerosis Society (EAS) and the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) recently addressed present and future challenges in the laboratory diagnostics of atherogenic lipoproteins. Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), LDL cholesterol (LDLC), and calculated non-HDLC (=total - HDLC) constitute the primary lipid panel for estimating risk of atherosclerotic cardiovascular disease (ASCVD) and can be measured in the nonfasting state. LDLC is the primary target of lipid-lowering therapies. For on-treatment follow-up, LDLC shall be measured or calculated by the same method to attenuate errors in treatment decisions due to marked between-method variations. Lipoprotein(a) [Lp(a)]-cholesterol is part of measured or calculated LDLC and should be estimated at least once in all patients at risk of ASCVD, especially in those whose LDLC declines poorly upon statin treatment. Residual risk of ASCVD even under optimal LDL-lowering treatment should be also assessed by non-HDLC or apolipoprotein B (apoB), especially in patients with mild-to-moderate hypertriglyceridemia (2-10 mmol/L). Non-HDLC includes the assessment of remnant lipoprotein cholesterol and shall be reported in all standard lipid panels. Additional apoB measurement can detect elevated LDL particle (LDLP) numbers often unidentified on the basis of LDLC alone. Reference intervals of lipids, lipoproteins, and apolipoproteins are reported for European men and women aged 20-100 years. However, laboratories shall flag abnormal lipid values with reference to therapeutic decision thresholds

Adrenal Incidentaloma: Prevalence and Referral Patterns From Routine Practice in a Large UK University Teaching Hospital.

Context: Adrenal incidentalomas (AIs) are increasingly being identified during unrelated imaging. Unlike AI clinical management, data on referral patterns in routine practice are lacking. Objective: This work aimed to identify factors associated with AI referral. Methods: We linked data from imaging reports and outpatient bookings from a large UK teaching hospital. We examined (i) AI prevalence and (ii) pattern of referral to endocrinology, stratified by age, imaging modality, scan anatomical site, requesting clinical specialty, and temporal trends. Using key radiology phrases to identify scans reporting potential AI, we identified 4097 individuals from 479 945 scan reports (2015-2019). Main outcome measures included prevalence of AI and referral rates. Results: Overall, AI lesions were identified in 1.2% of scans. They were more prevalent in abdomen computed tomography and magnetic resonance imaging scans (3.0% and 0.6%, respectively). Scans performed increased 7.7% year-on-year from 2015 to 2019, with a more pronounced increase in the number with AI lesions (14.7% per year).Only 394 of 4097 patients (9.6%) had a documented endocrinology referral code within 90 days, with medical (11.8%) more likely to refer than surgical (7.2%) specialties (P < .001). Despite prevalence increasing with age, older patients were less likely to be referred (P < .001). Conclusion: While overall AI prevalence appeared low, scan numbers are large and rising; the number with identified AI are increasing still further. The poor AI referral rates, even in centers such as ours where dedicated AI multidisciplinary team meetings and digital management systems are used, highlights the need for new streamlined, clinically effective systems and processes to appropriately manage the AI workload