39 research outputs found

    Evaluating the Economic Impact of Palliative and End-of-Life Care Interventions on Intensive Care Unit Utilization and Costs from the Hospital and Healthcare System Perspective.

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    Purpose of report: Understanding the impact of palliative care interventions on intensive care unit (ICU) costs and utilization is critical for demonstrating the value of palliative care. Performing these economic assessments, however, can be challenging. The purpose of this special report is to highlight and discuss important considerations when assessing ICU utilization and costs from the hospital perspective, with the goal of providing recommendations on methods to consider for future analyses. FINDINGS: ICU length of stay (LOS) and associated costs of care are common and important outcome measures, but must be analyzed properly to yield valid conclusions. There is significant variation in costs by day of stay in the ICU with only modest differences between an ICU day at the end of a stay and the first day on the acute care floor; this variation must be appropriately accounted for analytically. Furthermore, reporting direct variable costs, in addition to total ICU costs, is needed to understand short-term and long-term impact of a reduction in LOS. Importantly, incentives for the hospital to realize savings vary depending on reimbursement policies. SUMMARY: ICU utilization and costs are common outcomes in studies evaluating palliative care interventions. Accurate estimation and interpretation are key to understanding the economic implications of palliative care interventions

    Late systolic central hypertension as a predictor of incident heart failure : the Multi-Ethnic Study of Atherosclerosis

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    Background: Experimental studies demonstrate that high aortic pressure in late systole relative to early systole causes greater myocardial remodeling and dysfunction, for any given absolute peak systolic pressure. Methods and Results: We tested the hypothesis that late systolic hypertension, defined as the ratio of late (last one third of systole) to early (first two thirds of systole) pressure-time integrals (PTI) of the aortic pressure waveform, independently predicts incident heart failure (HF) in the general population. Aortic pressure waveforms were derived from a generalized transfer function applied to the radial pressure waveform recorded noninvasively from 6124 adults. The late/early systolic PTI ratio (L/ESPTI) was assessed as a predictor of incident HF during median 8.5 years of follow-up. The L/ESPTI was predictive of incident HF (hazard ratio per 1% increase= 1.22; 95% CI= 1.15 to 1.29; P58.38%) was more predictive of HF than the presence of hypertension. After adjustment for each other and various predictors of HF, the HR associated with hypertension was 1.39 (95% CI= 0.86 to 2.23; P=0.18), whereas the HR associated with a high L/E was 2.31 (95% CI=1.52 to 3.49; P<0.0001). Conclusions: Independently of the absolute level of peak pressure, late systolic hypertension is strongly associated with incident HF in the general population

    Infant lung function tests as endpoints in the ISIS multicenter clinical trial in cystic fibrosis

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    BACKGROUND: The Infant Study of Inhaled Saline (ISIS) in CF was the first multicenter clinical trial to utilize infant pulmonary function tests (iPFTs) as an endpoint. METHODS: Secondary analysis of ISIS data was conducted in order to assess feasibility of iPFT measures and their associations with respiratory symptoms. Standard deviations were calculated to aid in power calculations for future clinical trials. RESULTS: Seventy-three participants enrolled, 70 returned for the final visit; 62 (89%) and 45 (64%) had acceptable paired functional residual capacity (FRC) and raised volume measurements, respectively. Mean baseline FEV0.5, FEF75 and FRC z-scores were 0.3 (SD: 1.2), -0.2 (SD: 2.0), and 1.8 (SD: 2.0). CONCLUSIONS: iPFTs are not appropriate primary endpoints for multicenter clinical trials due to challenges of obtaining acceptable data and near-normal average raised volume measurements. Raised volume measures have potential to serve as secondary endpoints in future clinical CF trials

    Inhaled hypertonic saline in infants and toddlers with cystic fibrosis: short-term tolerability, adherence, and safety

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    Inhaled hypertonic saline (HS) is an attractive agent for chronic maintenance therapy in infants and toddlers with cystic fibrosis (CF) because it improves defective mucociliary clearance. Prior to undertaking a clinical trial of HS efficacy in young children with CF, tolerability, adherence and safety must be established

    INHALED HYPERTONIC SALINE IN INFANTS AND CHILDREN LESS THAN SIX YEARS OF AGE WITH CYSTIC FIBROSIS: THE ISIS RANDOMIZED TRIAL

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    Inhaled hypertonic saline is recommended as therapy for cystic fibrosis (CF) patients 6 years of age and older, but its efficacy has never been evaluated in CF patients <6 years of age

    Lack of Fit in Self Modeling Regression: Application to Pulse Waveforms

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    Self modeling regression (SEMOR) is an approach for modeling sets of observed curves that have a common shape (or sequence of features) but have variability in the amplitude (y-axis) and/or timing (x-axis) of the features across curves. SEMOR assumes the x and y axes for each observed curve can be separately transformed in a parametric manner so that the features across curves are aligned with the common shape, usually represented by non-parametric function. We show that when the common shape is modeled with a regression spline and the transformational parameters are modeled as random with the traditional distribution (normal with mean zero), the SEMOR model may surprisingly suffer from lack of fit and the variance components may be over-estimated. A random effects distribution that restricts the predicted random transformational parameters to have mean zero or the inclusion of a fixed transformational parameter improves estimation. Our work is motivated by arterial pulse pressure waveform data where one of the variance components is a novel measure of short-term variability in blood pressure.

    Lack of Fit in Self Modeling Regression: Application to Pulse Waveforms*

    No full text
    Self modeling regression (SEMOR) is an approach for modeling sets of observed curves that have a common shape (or sequence of features) but have variability in the amplitude (y-axis) and/or timing (x-axis) of the features across curves. SEMOR assumes the x and y axes for each observed curve can be separately transformed in a parametric manner so that the features across curves are aligned with the common shape, usually represented by non-parametric function. We show that when the common shape is modeled with a regression spline and the transformational parameters are modeled as random with the traditional distribution (normal with mean zero), the SEMOR model may surprisingly suffer from lack of fit and the variance components may be over-estimated. A random effects distribution that restricts the predicted random transformational parameters to have mean zero or the inclusion of a fixed transformational parameter improves estimation. Our work is motivated by arterial pulse pressure waveform data where one of the variance components is a novel measure of short-term variability in blood pressure
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