Objectives Patients who underwent corrective surgery for tetralogy of Fallot (TOF) have increased long-term risk of cardiovascular morbidity and mortality. Yet, limited information is available on how to evaluate the risk in this population. Therefore, the aim of this study was to investigate the prognostic value of aerobic exercise capacity, along with other related parameters, at medium-term follow-up in adult patients with tetralogy of Fallot. Methods and results Between 2000 and 2003, 92 adults (age 26.2 ± 7.8 years; 63 male) with corrected TOF or TOF-type morphology underwent a cardiopulmonary exercise test (CPET) until exhaustion and echocardiography. During a mean follow-up of 7.3 ± 1.2 years (range 0.9 to 9.3 years), 2 patients died and 26 patients required at least 1 cardiac-related intervention at a mean age of 28.9 ± 7.9 years. Event-free survival tended to be higher in patients with the classical type of TOF (P = 0.061). At multivariate Cox analysis, age at CPET [hazard ratio (HR): 1.13, P = 0.006], age at correction (HR: 0.82, P = 0.037), right ventricular (RV) function (HR: 4.94, P = 0.001), QRS duration (HR: 1.02, P = 0.007), percentage of predicted peak oxygen uptake (peak VO2%) (HR: 0.96, P = 0.029) and ventilatory effi ciency slope (VE/VCO2 slope) (HR: 1.13, P = 0.021) were signifi cantly related to the incidence of death/cardiac-related intervention during medium follow-up. Conclusions Early corrective surgery and a well-preserved RV are associated with a better outcome in adults with corrected TOF. Furthermore, CPET provides important prognostic information; peak VO2% and VE/VCO2 slope are independent predictors for event-free survival in patients with corrected TOF.
Housing stability is an important focus in research on homeless people. Although definitions of stable housing differ across studies, the perspective of homeless people themselves is generally not included. Therefore, this study explored the inclusion of satisfaction with the participant's current housing status as part of the definition of housing stability and also examined predictors of housing stability with and without the inclusion of homeless person's perspective. Of the initial cohort consisting of 513 homeless participants who were included at baseline in 2011, 324 (63.2%) were also interviewed at 2.5-year follow-up. To determine independent predictors of housing stability, we fitted multivariate logistic regression models using stepwise backward regression. At 2.5-year follow-up, 222 participants (68.5%) were stably housed and 163 participants (51.1%) were stably housed and satisfied with their housing status. Having been arrested (OR = 0.36, 95% CI: 0.20-0.63), a high level of somatisation (physical manifestations of psychological distress) (OR = 0.52, 95% CI: 0.30-0.91) and having unmet care needs (OR = 0.77, 95% CI: 0.60-0.99) were negative predictors of housing stability. Having been arrested (OR = 0.43, 95% CI: 0.25-0.75), high debts (OR = 0.45, 95% CI: 0.24-0.84) and a high level of somatisation (OR = 0.49, 95% CI: 0.28-0.84) were negative predictors of stable housing when satisfaction with the housing status was included. Because inclusion of a subjective component revealed a subgroup of stably housed but not satisfied participants and changed the significant predictors, this seems a relevant addition to the customary definition of housing stability. Participants with characteristics negatively associated with housing stability should receive more extensive and individually tailored support services to facilitate achievement of housing stability.
This research focuses on exit choices within SMEs. In this study, “exit choice” refers to the decision to opt for either liquidation or sale of the firm. The predictions focus on human-capital and firm-resource variables. The hypotheses are tested on a set of 158 owners of small firms, the majority of which are micro-firms with 0–9 employees. The results of a series of binominal logistic regression analyses show that firm-resource characteristics (previous sales turnover, the firm’s independence from its owner, and firm size), together with one aspect of the owner’s specific human capital (the owner’s acquisition experience), predict exit choice. The conclusions have been made with caution, as the dataset is relatively small and the number of predictors is limited.
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