Exploring break-points and interaction effects among predictors of the international digital divide

Cataloged from PDF version of article.The deepening of the digital divide between countries has prompted international organizations and governments to work together toward reducing the problem over the next 15 years. However, such efforts will likely succeed only if they are based on a firm grasp of the divide's underlying causes. In this paper we report the results of a comprehensive analysis of the determinants of the international digital divide. Our results confirm many findings of past research, but also extend existing knowledge in important ways. By employing Multivariate Adaptive Regression Splines (MARS), we discover non-linearities and interaction effects among the predictors. We then articulate significant policy implications based upon these findings

Optimal Use of the Non-Inferiority Trial Design

Superiority trials are conducted to test the hypothesis that a treatment or strategy A is superior to (i.e., better than) treatment strategy B in reducing the impact of disease. However, A may be considerably safer, more convenient, or cheaper than B. These features may make A more attractive than B even if the burden of disease is reduced comparably by the two treatments, or even a bit worse by A over B. In this context, non-inferiority trials have become increasingly popular to test the hypothesis that a new treatment is not \u2018unacceptably worse\u2019 than an active comparator by more than a predefined non-inferiority margin. Non-inferiority trials have unique design features and methodology and require a different analysis than traditional superiority trials. The main aim of this overview is to analyze the role of non-inferiority trials in the development of new treatments, involving some scientific, statistical, and practical considerations. We elucidate some aspects of non-inferiority trials that contribute to the validity of the results. The unique design features and methodology of non-inferiority trials are summarized and key findings to consider when evaluating a non-inferiority trial are illustrated

Combined use of electrocardiography and ultrasound to detect cardiac and pulmonary involvement after recovery from COVID-19 pneumonia: A case series

Background: Although severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may cause an acute multiorgan syndrome (coronavirus disease 2019 (COVID-19)), data are emerging on mid-and long-term sequelae of COVID-19 pneumonia. Since no study has hitherto investigated the role of both cardiac and pulmonary ultrasound techniques in detecting such sequelae, this study aimed at evaluating these simple diagnostic tools to appraise the cardiopulmonary involvement after COVID-19 pneumonia. Methods: Twenty-nine patients fully recovered from COVID-19 pneumonia were considered at our centre. On admission, all patients underwent 12-lead electrocardiogram (ECG) and transthoracic echocardiography (TTE) evaluation. Compression ultrasound (CUS) and lung ultrasound (LUS) were also performed. Finally, in each patient, pathological findings detected on LUS were correlated with the pulmonary involvement occurring after COVID-19 pneumonia, as assessed on thoracic computed tomography (CT). Results: Out of 29 patients (mean age 70 \ub1 10 years; males 69%), prior cardiovascular and pulmonary comorbidities were recorded in 22 (76%). Twenty-seven patients (93%) were in sinus rhythm and two (7%) in atrial fibrillation. Persistence of ECG abnormalities from the acute phase was common, and nonspecific repolarisation abnormalities (93%) reflected the high prevalence of pericardial involvement on TTE (86%). Likewise, pleural abnormalities were frequently observed (66%). TTE signs of left and right ventricular dysfunction were reported in two patients, and values of systolic pulmonary artery pressure were abnormal in 16 (55%, despite the absence of prior comorbidities in 44% of them). Regarding LUS evaluation, most patients displayed abnormal values of diaphragmatic thickness and excursion (93%), which correlated well with the high prevalence (76%) of pathological findings on CT scan. CUS ruled out deep vein thrombosis in all patients. Conclusions: Data on cardiopulmonary involvement after COVID-19 pneumonia are scarce. In our study, simple diagnostic tools (TTE and LUS) proved clinically useful for the detection of cardiopulmonary complications after COVID-19 pneumonia