The perceived and measured difficulty of texts and tasks in L1 and L2

The study investigates the effect of the perception of text and task difficulty on adults’ performance in reading tests in L1 and L2. The relationship between the following variables is studied: (a) readers’ perception of text and task difficulty in L1 and L2 measured in a self-reported post-task questionnaire, (b) the number of correct answers to the reading tasks, (c) time spent on the task in each language, (d) the number and mean duration of fixations on areas of interest assigned to texts and each of four different task instructions as measured by an eye tracker. The study shows that for readers at an intermediate level of L2, the perceived and measured text and task difficulty is higher for L2, which results in longer mean fixation durations and a higher number of fixation counts. Tasks placed lower on the difficulty scale based on the 7-point scale of reading ability by Khalifa and Weir (2009) are prone to be treated by readers as typical of a specific task format and receive less attention, which often leads to incorrect answers

Diagnostic yield is dependent on monitoring duration. Insights from a full-disclosure mobile cardiac telemetry system

Background: Despite the advancement of electrocardiogram (ECG) monitoring methods, the most important factor influencing diagnostic yield (DY) may still be monitoring duration. Ambulatory ECG monitoring, typically with 24–48 hours duration, is widely used but may result in underdiagnosis of rare arrhythmias.Aims: This study aimed to examine the relationship between the DY and monitoring duration in a large patient cohort and investigate sex and age differences in the presentation of arrhythmias. Methods: The study population consisted of 25 151 patients (57.8% women; median [interquartile range, IQR], 71 [64–78] years), who were examined with mobile cardiac telemetry during 2017 in the United States, using the PocketECGTM that continuously transmits a signal on a beat-to-beat basis. We investigated the occurrence of atrial fibrillation at a burden of both ≤1% (atrial fibrillation [AF], ≤1%) and ≤10% (AF ≤10%), premature ventricular contractions (PVC; >10 000 per 24 hours), non-sustained ventricular tachycardias (nsVT), sustained ventricular tachycardias (VT ≥30 seconds), atrioventricular blocks (AVB), pauses of >3 seconds duration, and bradycardia  (heart rate <40 beats per minute for ≥60 seconds).Results: The median (IQR) recording duration was 15.4, 8.2–28.2) days. The DY increased gradually with monitoring duration for all types of investigated arrhythmias. Compared to DY after up to 30 days of monitoring, a standard 24 hours monitoring resulted in DY for males/females of 20%/18% for AF ≤1%, 29%/28% for AF ≤10%, 45%/40% for PVCs, 17%/11% for nsVT, 17%/11% for VT ≥30 seconds, 49%/42 for AVB, 27%/20% for pauses, 36%/29% for bradycardia. Conclusion: A substantial number of patients suffering from arrhythmias may remain undiagnosed due to insufficient ECG monitoring time

Diagnostic yield is dependent on monitoring duration. Insights from a full-disclosure mobile cardiac telemetry system

Background: Despite the advancement of electrocardiogram (ECG) monitoring methods, the most important factor influencing diagnostic yield (DY) may still be monitoring duration. Ambulatory ECG monitoring, typically with 24–48 hours duration, is widely used but may result in underdiagnosis of rare arrhythmias. Aims: This study aimed to examine the relationship between the DY and monitoring duration in a large patient cohort and investigate sex and age differences in the presentation of arrhythmias. Methods: The study population consisted of 25 151 patients (57.8% women; median [interquartile range, IQR], 71 [64–78] years), who were examined with mobile cardiac telemetry during 2017 in the United States, using the PocketECGTM that continuously transmits a signal on a beat-to-beat basis. We investigated the occurrence of atrial fibrillation at a burden of both ≤1% (atrial fibrillation [AF], ≤1%) and ≤10% (AF ≤10%), premature ventricular contractions (PVC; >10 000 per 24 hours), non-sustained ventricular tachycardias (nsVT), sustained ventricular tachycardias (VT ≥30 seconds), atrioventricular blocks (AVB), pauses of >3 seconds duration, and bradycardia (heart rate <40 beats per minute for ≥60 seconds). Results: The median (IQR) recording duration was 15.4, 8.2–28.2) days. The DY increased gradually with monitoring duration for all types of investigated arrhythmias. Compared to DY after up to 30 days of monitoring, a standard 24 hours monitoring resulted in DY for males/females of 20%/18% for AF ≤1%, 29%/28% for AF ≤10%, 45%/40% for PVCs, 17%/11% for nsVT, 17%/11% for VT ≥30 seconds, 49%/42 for AVB, 27%/20% for pauses, 36%/29% for bradycardia. Conclusion: A substantial number of patients suffering from arrhythmias may remain undiagnosed due to insufficient ECG monitoring time

Can 24 h of ambulatory ECG be used to triage patients to extended monitoring?

Abstract Background Access to long‐term ambulatory recording to detect atrial fibrillation (AF) is limited for economical and practical reasons. We aimed to determine whether 24 h ECG (24hECG) data can predict AF detection on extended cardiac monitoring. Methods We included all US patients from 2020, aged 17–100 years, who were monitored for 2–30 days using the PocketECG device (MEDICALgorithmics), without AF ≥30 s on the first day (n = 18,220, mean age 64.4 years, 42.4% male). The population was randomly split into equal training and testing datasets. A Lasso model was used to predict AF episodes ≥30 s occurring on days 2–30. Results The final model included maximum heart rate, number of premature atrial complexes (PACs), fastest rate during PAC couplets and triplets, fastest rate during premature ventricular couplets and number of ventricular tachycardia runs ≥4 beats, and had good discrimination (ROC statistic 0.7497, 95% CI 0.7336–0.7659) in the testing dataset. Inclusion of age and sex did not improve discrimination. A model based only on age and sex had substantially poorer discrimination, ROC statistic 0.6542 (95% CI 0.6364–0.6720). The prevalence of observed AF in the testing dataset increased by quintile of predicted risk: 0.4% in Q1, 2.7% in Q2, 6.2% in Q3, 11.4% in Q4, and 15.9% in Q5. In Q1, the negative predictive value for AF was 99.6%. Conclusion By using 24hECG data, long‐term monitoring for AF can safely be avoided in 20% of an unselected patient population whereas an overall risk of 9% in the remaining 80% of the population warrants repeated or extended monitoring

Metabolic syndrome is associated with similar long-term prognosis in non-obese and obese patients. An analysis of 45 615 patients from the nationwide LIPIDOGRAM 2004-2015 cohort studies

Aims We aimed to evaluate the association between metabolic syndrome (MetS) and long-term all-cause mortality. Methods The LIPIDOGRAM studies were carried out in the primary care in Poland in 2004, 2006 and 2015. MetS was diagnosed based on the National Cholesterol Education Program, Adult Treatment Panel III (NCEP/ATP III) and Joint Interim Statement (JIS) criteria. The cohort was divided into four groups: non-obese patients without MetS, obese patients without MetS, non-obese patients with MetS and obese patients with MetS. Differences in all-cause mortality was analyzed using Kaplan-Meier and Cox regression analyses. Results 45,615 participants were enrolled (mean age 56.3, standard deviation: 11.8 years; 61.7% female). MetS was diagnosed in 14,202 (31%) by NCEP/ATP III criteria, and 17,216 (37.7%) by JIS criteria. Follow-up was available for 44,620 (97.8%, median duration 15.3 years) patients. MetS was associated with increased mortality risk among the obese (hazard ratio, HR: 1.88 [95% CI, 1.79-1.99] and HR: 1.93 [95% CI 1.82-2.04], according to NCEP/ATP III and JIS criteria, respectively) and non-obese individuals (HR: 2.11 [95% CI 1.85-2.40] and 1.7 [95% CI, 1.56-1.85] according to NCEP/ATP III and JIS criteria respectively). Obese patients without MetS had a higher mortality risk than non-obese patients without MetS (HR: 1.16 [95% CI 1.10-1.23] and HR: 1.22 [95%CI 1.15-1.30], respectively in subgroups with NCEP/ATP III and JIS criteria applied). Conclusions MetS is associated with increased all-cause mortality risk in non-obese and obese patients. In patients without MetS obesity remains significantly associated with mortality. The concept of metabolically healthy obesity should be revised