Citations

Risk factors contributing to institutionalization after inpatient rehabilitation for people with traumatic brain injury (TBI) have not been well studied and need to be better understood to guide clinicians during rehabilitation. We aimed to develop a prognostic model that could be used at admission to inpatient rehabilitation facilities to predict discharge disposition. The model could be used to provide the interdisciplinary team with information regarding aspects of patients' functioning and/or their living situation that need particular attention during inpatient rehabilitation if institutionalization is to be avoided. The study population included 7219 patients with moderate-severe TBI in the Traumatic Brain Injury Model Systems (TBIMS) National Database enrolled from 2002–2012 who had not been institutionalized prior to injury. Based on institutionalization predictors in other populations, we hypothesized that among people who had lived at a private residence prior to injury, greater dependence in locomotion, bed-chair-wheelchair transfers, bladder and bowel continence, feeding, and comprehension at admission to inpatient rehabilitation programs would predict institutionalization at discharge. Logistic regression was used, with adjustment for demographic factors, proxy measures for TBI severity, and acute-care length-of-stay. C-statistic and predictiveness curves validated a five-variable model. Higher levels of independence in bladder management (adjusted odds ratio [OR], 0.88; 95% CI 0.83, 0.93), bed-chair-wheelchair transfers (OR, 0.81 [95% CI, 0.83–0.93]), and comprehension (OR, 0.78 [95% CI, 0.68, 0.89]) at admission were associated with lower risks of institutionalization on discharge. For every 10-year increment in age was associated with a 1.38 times higher risk for institutionalization (95% CI, 1.29, 1.48) and living alone was associated with a 2.34 times higher risk (95% CI, 1.86, 2.94). The c-statistic was 0.780. We conclude that this simple model can predict risk of institutionalization after inpatient rehabilitation for patients with TBI.

Background and Purpose— The Carotid Revascularization Endarterectomy Versus Stenting Trial was completed with a low stroke and death rate. A lead-in series of patients receiving carotid artery stenting was used to select the physician-operators for the study, where performance was evaluated by complication rates and by peer review of cases. Herein, we assess the potential contribution of statistical evaluation of complication rates. Methods— The ability to discriminate between stent operators who can successfully meet the published guideline of <3% combined rate of stroke and death is calculated under the binomial distribution, based on a small consecutive case series (n=24 patients). Results— A criterion of ≤2 stroke or death events among the 24 patients (<8% event rate) was required of operators. Setting such a high criterion, however, ensures an inability to exclude operators who cannot meet the criteria. In fact, if a good operator is defined as having a 2% event rate and a poor operator as a 6% event rate, even a series of 240 patients would (on average) still exclude 5.4% of the good operators and include 4.6% of the poor operators. Conclusions— The low periprocedural event rates in the trial suggest success in separating skillful operators from less skillful. However, it seems unlikely that statistical assessment of event rates in the lead-in contributed to successful selection, but rather successful selection was more likely because of peer review of subjective and other factors including patient volume and technical approaches. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT00004732.

Heart failure with preserved ejection fraction (HFpEF) is a major cause of morbidity and mortality. Exercise training is an established adjuvant therapy in heart failure; however, the effects of high-intensity interval training (HIIT) in HFpEF are unknown. We compared the effects of HIIT vs. moderate-intensity aerobic continuous training (MI-ACT) on peak oxygen uptake (V̇o2peak), left ventricular diastolic dysfunction, and endothelial function in patients with HFpEF. Nineteen patients with HFpEF (age 70 ± 8.3 yr) were randomized to either HIIT (4 × 4 min at 85-90% peak heart rate, with 3 min active recovery) or MI-ACT (30 min at 70% peak heart rate). Fifteen patients completed exercise training (HIIT: n = 9; MI-ACT: n = 6). Patients trained 3 days/wk for 4 wk. Before and after training patients underwent a treadmill test for V̇o2peak determination, 2D-echocardiography for assessment of left ventricular diastolic dysfunction, and brachial artery flow-mediated dilation (FMD) for assessment of endothelial function. HIIT improved V̇o2peak (pre = 19.2 ± 5.2 ml·kg−1·min−1; post = 21.0 ± 5.2 ml·kg−1·min−1; P = 0.04) and left ventricular diastolic dysfunction grade (pre = 2.1 ± 0.3; post = 1.3 ± 0.7; P = 0.02), but FMD was unchanged (pre = 6.9 ± 3.7%; post = 7.0 ± 4.2%). No changes were observed following MI-ACT. A trend for reduced left atrial volume index was observed following HIIT compared with MI-ACT (−3.3 ± 6.6 vs. +5.8 ± 10.7 ml/m2; P = 0.06). In HFpEF patients 4 wk of HIIT significantly improved V̇o2peak and left ventricular diastolic dysfunction. HIIT may provide a more robust stimulus than MI-ACT for early exercise training adaptations in HFpEF.

Carotid intima-medial thickness (CIMT) allows for early detection of carotid atherosclerotic vascular disease. Using fuzzy logic techniques, we propose a model for calculating the risk for predicting CIMT using expert opinion and various factors associated with CIMT in recently menopausal women. Study participants were enrolled in the Kronos Early Estrogen Prevention Study (KEEPS), a four year study where participants were assigned to either oral or transdermal hormone therapy or to the placebo group. The fuzzy mathematical model uses five fuzzy logic methods to calculate this risk factor for CIMT, including the analytic hierarchy process (AHP) method, Guiasu method, Yen method, Dempster–Shafer (DS) method, and the set valued statistical method (SVSM). The four methods, AHP, Guiasu, Yen, DS, and SVSM, were correlated to each other according to the Pearson ranking method. In addition, results showed that the estrogen treatment groups showed a statically significant decrease in calculated CIMT risk compared to placebo when all the methods were combined together (p = 0.0017). Our fuzzy mathematical model provides the first fuzzy mathematical model to predict the risk of CIMT in recently menopausal women and menopausal hormone therapy may be beneficial in reducing this risk.