Browsing by Subject "Logistic Models"
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Item Depression, inflammation, and memory loss among Mexican Americans: analysis of the HABLE cohort(Cambridge University Press, 2017-06-20) Johnson, Leigh A.; Edwards, Melissa; Gamboa, Adriana; Hall, James R.; Robinson, Michelle; O'Bryant, Sid E.Background: This study explored the combined impact of depression and inflammation on memory functioning among Mexican-American adults and elders. Methods: Data were analyzed from 381 participants of the Health and Aging Brain study among Latino Elders (HABLE). Fasting serum samples were collected and assayed in duplicate using electrochemiluminesce on the SECTOR Imager 2400A from Meso Scale Discovery. Positive DepE (depression endophenotype) was codified as any score >1 on a five-point scale based on the GDS-30. Inflammation was determined by TNFɑ levels and categorized by tertiles (1st, 2nd, 3rd). WMS-III LMI and LMII as well as CERAD were utilized as measures of memory. ANOVAs examined group differences between positive DepE and inflammation tertiles with neuropsychological scale scores as outcome variables. Logistic regressions were used to examine level of inflammation and DepE positive status on the risk for MCI. Results: Positive DepE as well as higher inflammation were both independently found to be associated with lower memory scores. Among DepE positive, those who were high in inflammation (3rd tertile) were found to perform significantly worse on WMS-III LM I (F = 4.75, p = 0.003), WMS-III LM II (F = 8.18, p < 0.001), and CERAD List Learning (F = 17.37, p < 0.001) when compared to those low on inflammation (1st tertile). The combination of DepE positive and highest tertile of inflammation was associated with increased risk for MCI diagnosis (OR = 6.06; 95% CI = 3.9-11.2, p < 0.001). Conclusion: Presence of elevated inflammation and positive DepE scores increased risk for worse memory among Mexican-American older adults. Additionally, the combination of DepE and high inflammation was associated with increased risk for MCI diagnosis. This work suggests that depression and inflammation are independently associated with worse memory among Mexican-American adults and elders; however, the combination of both increases risk for poorer memory beyond either alone.Item Improving the Efficiency of A and D Optimal Designs for Dose Response Models(2021-08) Jasti, Srichand; Nandy, Rajesh R.; Aryal, Subhash; Thombs, Dennis; Barnett, Tracey; Haque, UbydulFor A-optimality, by virtue of Cramér–Rao bound, the trace of the inverse of Information matrix for the parameters serves as a lower bound for the sum of variances of the estimators and the bound is attained asymptotically. Hence, asymptotically, A-optimality is achieved by minimizing the trace of the inverse of the Information matrix. For non-linear models, Cramér–Rao bound is crude for finite samples and hence the asymptotic solution can be very different from the design that minimizes the sum of variances. We explore the validity of the asymptotic solution by directly minimizing the sum of variances using numerical methods in a restricted search space. We demonstrate that even in a very restrictive search space of point symmetric designs, the theoretical solution is half as efficient for a sample size of 100. Further improvement can be achieved by relaxing the restriction of the solution being point symmetric. The solution to A and D optimal designs for the logistic model depend on the unknown parameters of the model. Therefore, to obtain an optimal design the experimenter must inform the design based on some prior knowledge, or a guess, of the unknown parameters. This is a severe limitation on the ability to identify an optimal design especially when there is little prior information to inform the guess. Here we explore the use of a two-stage A-optimal design for finite samples and three-stage D-optimal design for large samples to mitigate the loss in efficiency which may arise due to poor guess values. We demonstrate that while two-stage finite sample model results in gain in efficiency with small sample sizes at 70% allocation to the first stage. The three-stage D optimal design is shown to be almost always better than the single stage and the corresponding two-stage design.Item Roles of disease severity and post-discharge outpatient visits as predictors of hospital readmissions(BioMed Central Ltd., 2016-10-10) Wang, Hao; Johnson, Carol; Robinson, Richard D.; Nejtek, Vicki A.; Schrader, Chet D.; Leuck, JoAnna; Umejiego, Johnbosco; Trop, Allison; Delaney, Kathleen A.; Zenarosa, Nestor R.BACKGROUND: Risks prediction models of 30-day all-cause hospital readmissions are multi-factorial. Severity of illness (SOI) and risk of mortality (ROM) categorized by All Patient Refined Diagnosis Related Groups (APR-DRG) seem to predict hospital readmission but lack large sample validation. Effects of risk reduction interventions including providing post-discharge outpatient visits remain uncertain. We aim to determine the accuracy of using SOI and ROM to predict readmission and further investigate the role of outpatient visits in association with hospital readmission. METHODS: Hospital readmission data were reviewed retrospectively from September 2012 through June 2015. Patient demographics and clinical variables including insurance type, homeless status, substance abuse, psychiatric problems, length of stay, SOI, ROM, ICD-10 diagnoses and medications prescribed at discharge, and prescription ratio at discharge (number of medications prescribed divided by number of ICD-10 diagnoses) were analyzed using logistic regression. Relationships among SOI, type of hospital visits, time between hospital visits, and readmissions were also investigated. RESULTS: A total of 6011 readmissions occurred from 55,532 index admissions. The adjusted odds ratios of SOI and ROM predicting readmissions were 1.31 (SOI: 95 % CI 1.25-1.38) and 1.09 (ROM: 95 % CI 1.05-1.14) separately. Ninety percent (5381/6011) of patients were readmitted from the Emergency Department (ED) or Urgent Care Center (UCC). Average time interval from index discharge date to ED/UCC visit was 9 days in both the no readmission and readmission groups (p > 0.05). Similar hospital readmission rates were noted during the first 10 days from index discharge regardless of whether post-index discharge patient clinic visits occurred when time-to-event analysis was performed. CONCLUSIONS: SOI and ROM significantly predict hospital readmission risk in general. Most readmissions occurred among patients presenting for ED/UCC visits after index discharge. Simply providing early post-discharge follow-up clinic visits does not seem to prevent hospital readmissions.Item Uptake of cancer screenings among a multiethnic refugee population in North Texas, 2014-2018(PLOS, 2020-03-30) Raines-Milenkov, Amy; Felini, Martha; Baker, Eva; Acharya, Rushil; Longanga Diese, Elvis; Onsa, Sara; Fernando, Shane I.; Chor, HolyBACKGROUND: Refugees are less likely than US born populations to receive cancer screenings. Building Bridges is a community health worker prevention program designed to increase refugee's cancer screening uptake. The purpose of this cross sectional analysis was to assess differences in uptake of cervical, breast, liver, and colorectal screens across six cultural groups. METHODS: Data was abstracted in 2018 for this analysis. Participants were categorized into six cultural groups (Myanmar, Central Africa, Bhutan, Somalia, Arabic Speaking Countries, and Other) to assess differences in sociodemographic measures and screening uptake. Uptake proportions were calculated for each cancer type (cervical, breast, liver, and colon) among eligible participants, by gender and cultural group. Differences in uptake across groups were assessed using stratified analysis and logistic regression. Prevalence odds ratios (POR) and 95% confidence intervals (CIs) were calculated for each group to assess the association between screening completion and cultural group. FINDINGS: 874 refugees were asked about cancer screening history. The majority of participants were either 'never had been screened' or 'not up-to-date' for every cancer screening. Among age eligible, 82% had no prior pap exam within the past 3 years, 81% had no prior mammogram within the past year, 69% didn't know their Hepatitis B status and 87% never had a colon cancer screening. Overall, higher uptake of all types of cancer screenings was observed in Myanmar and Bhutanese groups, except colon cancer screening which was higher among Central African Region and Arabic Speaking participants. CONCLUSION: Screening uptake varied by ethnic group and screening type. The program reached an under and never screened population, however, the proportion of refugees who received a cancer screening remained low compared to the US population. Diversity within refugee communities requires adaptation to specific cultural and linguistic needs to include new Americans in cancer elimination efforts.Item Water T2 as an early, global and practical biomarker for metabolic syndrome: an observational cross-sectional study(BioMed Central Ltd., 2017-12-19) Robinson, Michelle D.; Mishra, Ina; Deodhar, Sneha; Patel, Vipulkumar; Gordon, Katrina V.; Vintimilla, Raul; Brown, Kim; Johnson, Leigh A.; O'Bryant, Sid E.; Cistola, David P.BACKGROUND: Metabolic syndrome (MetS) is a highly prevalent condition that identifies individuals at risk for type 2 diabetes mellitus and atherosclerotic cardiovascular disease. Prevention of these diseases relies on early detection and intervention in order to preserve pancreatic beta-cells and arterial wall integrity. Yet, the clinical criteria for MetS are insensitive to the early-stage insulin resistance, inflammation, cholesterol and clotting factor abnormalities that characterize the progression toward type 2 diabetes and atherosclerosis. Here we report the discovery and initial characterization of an atypical new biomarker that detects these early conditions with just one measurement. METHODS: Water T2, measured in a few minutes using benchtop nuclear magnetic resonance relaxometry, is exquisitely sensitive to metabolic shifts in the blood proteome. In an observational cross-sectional study of 72 non-diabetic human subjects, the association of plasma and serum water T2 values with over 130 blood biomarkers was analyzed using bivariate, multivariate and logistic regression. RESULTS: Plasma and serum water T2 exhibited strong bivariate correlations with markers of insulin, lipids, inflammation, coagulation and electrolyte balance. After correcting for confounders, low water T2 values were independently and additively associated with fasting hyperinsulinemia, dyslipidemia and subclinical inflammation. Plasma water T2 exhibited 100% sensitivity and 87% specificity for detecting early insulin resistance in normoglycemic subjects, as defined by the McAuley Index. Sixteen normoglycemic subjects with early metabolic abnormalities (22% of the study population) were identified by low water T2 values. Thirteen of the 16 did not meet the harmonized clinical criteria for metabolic syndrome and would have been missed by conventional screening for diabetes risk. Low water T2 values were associated with increases in the mean concentrations of 6 of the 16 most abundant acute phase proteins and lipoproteins in plasma. CONCLUSIONS: Water T2 detects a constellation of early abnormalities associated with metabolic syndrome, providing a global view of an individual's metabolic health. It circumvents the pitfalls associated with fasting glucose and hemoglobin A1c and the limitations of the current clinical criteria for metabolic syndrome. Water T2 shows promise as an early, global and practical screening tool for the identification of individuals at risk for diabetes and atherosclerosis.