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Browsing by Subject "Outcome Assessment (Health Care)"
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Item Differences in health care use and outcomes by the timing of in-hospital worsening heart failure(Elsevier, 2015-12) Cooper, Lauren B.; Hammill, Bradley G.; Sharma, Puza P.; DeVore, Adam D.; Mentz, Robert J.; Fonarow, Gregg C.; Pang, Peter S.; Curtis, Lesley H.; Hernandez, Adrian F.; Department of Emergency Medicine, IU School of MedicineBACKGROUND: Patients hospitalized with acute heart failure may experience worsening symptoms requiring escalation of therapy. In-hospital worsening heart failure is associated with worse in-hospital and postdischarge outcomes, but associations between the timing of worsening heart failure and outcomes are unknown. METHODS: Using data from a large clinical registry linked to Medicare claims, we examined characteristics, outcomes, and costs of patients hospitalized for acute heart failure. We defined in-hospital worsening heart failure by the use of inotropes or intravenous vasodilators or initiation of mechanical circulatory support, hemodialysis, or ventilation. The study groups were early worsening heart failure (n = 1,990), late worsening heart failure (n = 4,223), complicated presentation (n = 15,361), and uncomplicated hospital course (n = 41,334). RESULTS: Among 62,908 patients, those with late in-hospital worsening heart failure had higher in-hospital and postdischarge mortality than patients with early worsening heart failure or complicated presentation. Those with early or late worsening heart failure had more frequent all-cause and heart failure readmissions at 30 days and 1 year, with resultant higher costs, compared with patients with an uncomplicated hospital course. CONCLUSION: Although late worsening heart failure was associated with the highest mortality, both early and late worsening heart failures were associated with more frequent readmissions and higher health care costs compared to uncomplicated hospital course. Prevention of worsening heart failure may be an important focus in the care of hospitalized patients with acute heart failure.Item Group variable selection via convex log-exp-sum penalty with application to a breast cancer survivor study(Wiley Blackwell (Blackwell Publishing), 2015-03) Geng, Zhigeng; Wang, Sijian; Yu, Menggang; Monahan, Patrick O.; Champion, Victoria; Wahba, Grace; Biostatistics, School of Public HealthIn many scientific and engineering applications, covariates are naturally grouped. When the group structures are available among covariates, people are usually interested in identifying both important groups and important variables within the selected groups. Among existing successful group variable selection methods, some methods fail to conduct the within group selection. Some methods are able to conduct both group and within group selection, but the corresponding objective functions are non-convex. Such a non-convexity may require extra numerical effort. In this article, we propose a novel Log-Exp-Sum(LES) penalty for group variable selection. The LES penalty is strictly convex. It can identify important groups as well as select important variables within the group. We develop an efficient group-level coordinate descent algorithm to fit the model. We also derive non-asymptotic error bounds and asymptotic group selection consistency for our method in the high-dimensional setting where the number of covariates can be much larger than the sample size. Numerical results demonstrate the good performance of our method in both variable selection and prediction. We applied the proposed method to an American Cancer Society breast cancer survivor dataset. The findings are clinically meaningful and may help design intervention programs to improve the qualify of life for breast cancer survivors.Item Impact of and Correction for Outcome Misclassification in Cumulative Incidence Estimation(Public Library of Science, 2015) Bakoyannis, Giorgos; Yiannoutsos, Constantin T.; Department of Biostatistics, School of Public HealthCohort studies and clinical trials may involve multiple events. When occurrence of one of these events prevents the observance of another, the situation is called "competing risks". A useful measure in such studies is the cumulative incidence of an event, which is useful in evaluating interventions or assessing disease prognosis. When outcomes in such studies are subject to misclassification, the resulting cumulative incidence estimates may be biased. In this work, we study the mechanism of bias in cumulative incidence estimation due to outcome misclassification. We show that even moderate levels of misclassification can lead to seriously biased estimates in a frequently unpredictable manner. We propose an easy to use estimator for correcting this bias that is uniformly consistent. Extensive simulations suggest that this method leads to unbiased estimates in practical settings. The proposed method is useful, both in settings where misclassification probabilities are known by historical data or can be estimated by other means, and for performing sensitivity analyses when the misclassification probabilities are not precisely known.Item Impact of Donor Pre-Procurement Cardiac Arrest (PPCA) on Clinical Outcomes in Liver Transplantation(Springer Verlag, 2018-11-20) Mangus, Richard S.; Schroering, Joel R.; Fridell, Jonathan A.; Kubal, Chandrashekhar A.; Surgery, School of MedicineBACKGROUND Transplantation of liver grafts from deceased donors who experienced cardiac arrest prior to liver procurement is now common. This single-center study analyzed the impact of pre-donation arrest time on clinical outcomes in liver transplantation. MATERIAL AND METHODS Records of all orthotopic liver transplants performed at a single center over a 15-year period were reviewed. Donor records were reviewed and total arrest time was calculated as cumulative minutes. Post-transplant liver graft function was assessed using laboratory values. Graft survival was assessed with Cox regression analysis. RESULTS Records for 1830 deceased donor transplants were reviewed, and 521 donors experienced pre-procurement cardiac arrest (28%). Median arrest time was 21 min (mean 25 min, range 1-120 min). After transplant, the peak alanine aminotransferase and bilirubin levels for liver grafts from donors with arrest were lower compared to those for donors without arrest (p<0.001). Early allograft dysfunction occurred in 25% (arrest) and 28% (no arrest) of patients (p=0.22). There were no differences in risk of early graft loss (3% vs. 3%, p=0.84), length of hospital stay (10 vs. 10 days, p=0.76), and 1-year graft survival (89% vs. 89%, p=0.94). Cox regression analysis comparing 4 groups (no arrest, <20 min, 20-40 min, and >40 min arrest) demonstrated no statistically significant difference in survival at 10 years. Subgroup analysis of 93 donation after cardiac death grafts showed no significant difference for these same outcomes. CONCLUSIONS These results support the use of select deceased liver donors who experience pre-donation cardiac arrest. Pre-donation arrest may be associated with less early allograft dysfunction, but had no impact on long-term clinical outcomes. The results for donation after cardiac death donors were similar.Item The POLST program: a retrospective review of the demographics of use and outcomes in one community where advance directives are prevalent(2012-01) Hammes, Bernard J.; Rooney, Brenda L.; Gundrum, Jacob D.; Hickman, Susan E.; Hager, NickijoOBJECTIVES: Determine the use and utility of the Physician Orders for Life-Sustaining Treatment (POLST) program in a community where powers of attorney for health care (POAHCs) are prevalent. METHODS: A retrospective review of medical record and death certificate data of 400 adults who died between September 1, 2007, and March 31, 2008, in the La Crosse County, Wisconsin community. Demographic and cause-of-death data were collected from death certificates. Information about POAHC, POLST forms, and medical treatments provided in the last 30 days of life were abstracted from decedents' medical records. RESULTS: Sixty-seven percent of decedents had a POLST form, whereas 22% had POAHC alone. In comparison with decedents with POAHC alone, decedents with a POLST form were significantly older (83 versus 77 years, p<0.001), more likely to die in a nursing home than in a hospital (p<0.001), and more likely to die from a terminal or chronic illnesses (97%). Decedents with POLST orders for higher levels of medical treatment received more treatment, and in only two cases was there evidence that treatment was discrepant with POLST orders. In 31% of all POLST forms, the person appointed in the POAHC consented to the POLST orders. CONCLUSIONS: POLST can be a highly effective program to ensure that patient preferences are known and honored in all settings. POAHCs are valuable because they identify appropriate surrogates when patients are incapacitated.Item Simultaneous variable selection for joint models of longitudinal and survival outcomes(Wiley Blackwell (Blackwell Publishing), 2015-03) He, Zangdong; Tu, Wanzhu; Wang, Sijian; Fu, Haoda; Yu, Zhangsheng; Department of Biostatistics, Richard M. Fairbanks School of Public HealthJoint models of longitudinal and survival outcomes have been used with increasing frequency in clinical investigations. Correct specification of fixed and random effects is essential for practical data analysis. Simultaneous selection of variables in both longitudinal and survival components functions as a necessary safeguard against model misspecification. However, variable selection in such models has not been studied. No existing computational tools, to the best of our knowledge, have been made available to practitioners. In this article, we describe a penalized likelihood method with adaptive least absolute shrinkage and selection operator (ALASSO) penalty functions for simultaneous selection of fixed and random effects in joint models. To perform selection in variance components of random effects, we reparameterize the variance components using a Cholesky decomposition; in doing so, a penalty function of group shrinkage is introduced. To reduce the estimation bias resulted from penalization, we propose a two-stage selection procedure in which the magnitude of the bias is ameliorated in the second stage. The penalized likelihood is approximated by Gaussian quadrature and optimized by an EM algorithm. Simulation study showed excellent selection results in the first stage and small estimation biases in the second stage. To illustrate, we analyzed a longitudinally observed clinical marker and patient survival in a cohort of patients with heart failure.