PC program for comparing tracking indices in several independent groups

A method for computing a measure of tracking based on Cohen's kappa statistic for one-sample longitudinal data sets was previously described and implemented. This paper shows how one may test the equality of several kappas, each computed from an independent longitudinal sample. Thus, it is possible to formally compare groups of individuals with regard to stability in growth (or adaptive) patterns. Relative assessments of predictability in growth outcomes in different populations can be made with this approach. Also, when a common value of kappa is not contradicted by the data, a method to estimate this value and obtain a confidence interval for it is shown. A menu-driven GAUSS program for carrying out the procedure is described and made available. The method and program are illustrated with three samples of Guatemalan children. © 1992 Wiley-Liss, Inc.     

A GAUSS program for computing an index of tracking from longitudinal observations

Tracking can be defined as the tendency of individuals or collections of individuals to stay within a particular course of growth over time relative to other individuals. Thus, tracking describes stability in growth patterns. This paper outlines a statistical procedure for examining tracking in a single sample of measurements made on humans or other animals. This nonparametric procedure, based on Cohen's (1960) kappa statistic, is suitable for equally or unequally spaced serial data that is complete and is appropriate for questions concerning growth as well as other time-dependent phenomena. It is a conceptually simple longitudinal method that affords insight regarding the predictability of growth within a population. For example, by tracking, one can ask if young children who are in the lowest height for age category are likely to end up in that category at an older age. A user-friendly GAUSS program is provided that generates overall as well as individual and track-specific statistics. High-resolution graphic representations of the data are also generated by the program. Examples are presented, including a tracking analysis of Guatemalan Indian children using quartiles.     

Wide QRS Complex and Lateral ST-T Segment Abnormality Are Associated With Worse Clinical Outcomes in COVID-19 Patients

BackgroundThe information on electrocardiographic features of patients with coronavirus disease 2019 (COVID-19) is limited. Our aim was to determine if baseline electrocardiographic features of hospitalized COVID-19 patients are associated with markers of myocardial injury and clinical outcomes.MethodsIn this retrospective, single center cohort study, we included 223 hospitalized patients with laboratory-confirmed COVID-19. Clinical, electrocardiographic and laboratory data were collected and analyzed. Primary composite endpoint of mortality, need for invasive mechanical ventilation, or admission to the intensive care unit was assessed.ResultsForty patients (17.9%) reached the primary composite endpoint. Patients with the primary composite endpoint were more likely to have wide QRS complex (>120 ms) and lateral ST-T segment abnormality. The multivariable Cox regression showed increasing odds of the primary composite endpoint associated with acute respiratory distress syndrome (odds ratio 7.76, 95% CI 2.67–22.59; p < 0.001), acute cardiac injury (odds ratio 3.14, 95% CI 1.26–7.99; p = 0.016), high flow oxygen therapy (odds ratio 2.43, 95% CI 1.05–5.62; p = 0.037) and QRS duration longer than >120 ms (odds ratio 3.62, 95% CI 1.39–9.380; p = 0.008) Patients with a wide QRS complex (>120 ms) had significantly higher median level of troponin T and pro-BNP than those without it. Patients with abnormality of lateral ST-T segment had significantly higher median level of troponin T and pro-BNP than patients without.ConclusionsThe presence of QRS duration longer than 120 ms and lateral ST-T segment abnormality were associated with worse clinical outcomes and higher levels of myocardial injury biomarkers.