Differences In Predictor Variables Research Articles

Identifying factors that affect mountain lake sensitivity to atmospheric nitrogen deposition across multiple scales

Increased nitrogen (N) deposition rates over the past century have affected both North American and European mountain lake ecosystems. Ecological sensitivity of mountain lakes to N deposition varies, however, because chemical and biological responses are modulated by local watershed and lake properties. We evaluated predictors of mountain lake sensitivity to atmospheric N deposition across North American and European mountain ranges and included as response variables dissolved inorganic N (DIN = NNH4+ + NNO3–) concentrations and phytoplankton biomass. Predictors of these responses were evaluated at three different spatial scales (hemispheric, regional, subregional) using regression tree, random forest, and generalized additive model (GAM) analysis. Analyses agreed that Northern Hemisphere mountain lake DIN was related to N deposition rates and smaller scale spatial variability (e.g., regional variability between North American and European lakes, and subregional variability between mountain ranges). Analyses suggested that DIN, N deposition, and subregional variability were important for Northern Hemisphere mountain lake phytoplankton biomass. Together, these findings highlight the need for finer-scale, subregional analyses (by mountain range) of lake sensitivity to N deposition. Subregional analyses revealed differences in predictor variables of lake sensitivity. In addition to N deposition rates, lake and watershed features such as land cover, bedrock geology, maximum lake depth (Zmax), and elevation were common modulators of lake DIN. Subregional phytoplankton biomass was consistently positively related with total phosphorus (TP) in Europe, while North American locations showed variable relationships with N or P. This study reveals scale-dependent watershed and lake characteristics modulate mountain lake ecological responses to atmospheric N deposition and provides important context to inform empirically based management strategies.

Depressive symptoms, childhood maltreatment, and allostatic load: The importance of sex differences

ObjectiveRoughly half the individuals who experience childhood maltreatment also experience depressive symptoms in adulthood; however, many current treatments are ineffective. Allostatic load (AL) offers a method of exploring this relationship through the lens of biometric dysregulation that may explain these increased odds for depressive symptoms in adulthood. We attempted to expand the limited research base on AL, depressive symptoms, and childhood maltreatment by examining how these variables are associated in a U.S. community sample. MethodData were acquired through secondary analysis of the Midlife in the United States Refresher biomarker survey (n = 691). Depression severity, measured by the Center for Epidemiologic Studies Depression Scale, served as the dependent variable, while summed scores for the Childhood Trauma Questionnaire, and a 16 measure AL index served as independent variables. All analyses were stratified by sex (n male = 347, n female = 344). The Perceived Stress Scale was included to control for recent stress. An OLS regression was used to understand the relationship between depression and predictor variables before then being tested for the possible mediating role of AL. ResultsComparison of OLS models yielded notable differences in predicting depressive symptoms between males and females, namely that while maltreatment was significant for both groups, AL was only significant for females. Mediation by allostatic load was not significant for males or females. ConclusionWe explored the possible mediation of childhood maltreatment and adulthood depressive symptoms by AL. While our study did not confirm mediation, this was the first known study to explore these relationships in a U.S., community sample. Sex stratification reveals a clear need for accounting for sex differences in predictor variables for future studies.

Predictors of Internet Use Among Older Adults With Diabetes in South Korea: Survey Study.

BackgroundInternet access in Korea has grown dramatically over the past two decades. However, disparities in internet use, referred to as the second level of the digital divide, persist.ObjectiveThis study aims to examine opportunity, motivation, and health variables that indicate internet use among older adults with diabetes.MethodsData were sourced from a nationally representative sample of people 65 years and older with diabetes (N=1919). Logistic regression was used to explore potential differences in predictor variables between internet users and nonusers.ResultsOnly 306 of the 1919 (15.95%) participants in the sample used the internet. They were more likely to be younger (odds ratio [OR] 0.89, 95% CI 0.87-0.92), well-educated (OR 1.20, 95% CI 1.16-1.26), and able to afford leisure expenditures (OR 1.02, 95% CI 1.01-1.04). Additionally, they had more information and communications technology (ICT) training experience, were motivated to learn, volunteered, and reported good physical and cognitive function. Participation in ICT education and better health more positively correlated with a higher rate of internet use than did years of education or economic standing in older adults with diabetes.ConclusionsTo support older adults with diabetes in the internet age, policies and health care providers should focus on digital competency training as well as physical and cognitive function.

2161-PUB: Determinants of Digital Divide among Older Adults with Diabetes Mellitus

Background: Access to the internet has grown dramatically over the past two decades. However disparities in internet use, the second level of the digital divide, persist. Objective: This study examined the opportunity-, motivation-, and health-related factors to determine variables that might predict the digital divide among older adults with DM. Methods: Data for this study came from a nationally representative sample of people aged 65 years or older (N=1919). The dependent variable, digital divide, is designated by use or nonuse of internet or mobile searching for information. Dependent variables are opportunity (demographic and socioeconomic), motivation (participation in *ICT skill education, voluntary work, and intention of education) and health related factors (self-rated health, physical and cognitive functions). Logistic regression was used to explore potential differences in predictor variables between users and nonuser groups. Results: Only 16.0% of older adults with DM currently used the internet for information searching and they are more likely to be younger, have a higher level of education, and more leisure activity expenditure. Most of all, they were more likely to have had experience of ICT skill, and more motivated to education than nonuser. They also were more likely to do volunteer work, be healthier in in terms of physical and cognitive functions, and perceived better health status. Conclusions: Our results suggest the experience of ICT skill education and better physical and cognitive functions are more predictive of internet use than education or economic level in older adults with DM. Lest the frailest and vulnerable older adults, such as DM sufferers, be left behind with the move towards online and digital first health care, health care providers should offer them digital health interventions including digital competency training programs.*Information and communication technology. Disclosure S. Park: None.

Surgeon Performance Predicts Early Continence After Robot-Assisted Radical Prostatectomy.

There is limited, yet compelling evidence supporting the role of surgeon technical performance in influencing patient outcomes. To date, this concept has been underexplored in endourologic procedures. We hypothesized that a surgeon's technical performance plays a role in predicting an early return to continence after robot-assisted radical prostatectomy (RARP). We conducted a retrospective, matched case-control analysis of prospectively collected unedited RARP endoscopic videos performed by a single surgeon. A blinded observer with expertise in intraoperative video analysis evaluated clinically relevant steps of RARP using the global evaluative assessment of robotic skill (GEARS) and the generic error rating tool (GERT). The primary outcome was continence status at 3 months postoperatively, defined as patient use of less than or equal to a single precautionary pad. Mann-Whitney U tests examined differences in predictor variables between cases and controls, and multivariate analysis was conducted using binary logistic regression models. Twenty-four incontinent patients were matched for age, body mass index, preoperative International Prostate Symptoms Score, use of posterior/anterior hitch, prostate weight, and learning curve position. No statistically significant difference in errors between groups was observed using the GERT. On multivariate analysis, overall case GEARS score was independently predictive of 3-month continence status (odds ratios [OR] = 0.55, 95% confidence interval [CI] 0.33-0.91), as were urethrovesical anastomosis (OR = 0.70, 95% CI 0.50-0.97) and bladder neck GEARS scores (OR = 0.69, 95% CI 0.51-0.94). Our study generates the hypothesis that there may be a link between surgeon technical performance and functional outcomes in RARP. This relationship may have implications for the accreditation and training of future urologists and warrants further investigation.

MP51-15 SURGICAL TECHNICAL PERFORMANCE IMPACTS PATIENT OUTCOMES IN ROBOTIC-ASSISTED RADICAL PROSTATECTOMY

You have accessJournal of UrologySurgical Technology & Simulation: Training & Skills Assessment I1 Apr 2017MP51-15 SURGICAL TECHNICAL PERFORMANCE IMPACTS PATIENT OUTCOMES IN ROBOTIC-ASSISTED RADICAL PROSTATECTOMY Mitchell G. Goldenberg, S. Larry Goldenberg, and Teodor P. Grantcharov Mitchell G. GoldenbergMitchell G. Goldenberg More articles by this author , S. Larry GoldenbergS. Larry Goldenberg More articles by this author , and Teodor P. GrantcharovTeodor P. Grantcharov More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.1624AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The few studies that question the role of individual surgeon′s technical skill in influencing patient outcomes and safety have produced compelling results. To date, this linkage has not been published in urology. We designed a study to understand how surgeon skill and error rating contribute to functional outcomes in robotic-assisted radical prostatectomy (RARP). METHODS We conducted a case-matched analysis of 28 prospectively collected RARP endoscopic videos performed by a single surgeon, between 2008 and 2015. Research Ethics Board approval was granted. Patient information was retrieved from an institutionally maintained database. The primary outcome parameter was continence status at 3 months post-operatively, defined as patient use of more than a single precautionary pad. A blinded observer with expertise in intraoperative video analysis evaluated clinically relevant steps of RARP using the Global Evaluative Assessment of Robotic Skill (GEARS), Robotic Anastomosis Competency Evaluation (RACE) and the Generic Error Rating Tool (GERT). Mann Whitney U tests explored differences in predictor variables between cases and controls (two-tailed, p≤0.05). RESULTS 14 patients deemed to be incontinent at 3 months were matched for age, pre-operative International Prostate Symptoms Score (IPSS), use of posterior/anterior hitch, and prostate weight. Matching also accounted for position of the case on the surgeon′s learning curve. Statistically significant differences were detected on nonparametric testing in RACE (p=0.03) score and GEARS urethrovesical anastomosis score (p=0.02) between case and control groups. There were a greater number of errors committed during bladder neck dissection in the incontinent patient cohort (p=0.01). CONCLUSIONS Our study is the first that suggests a link between surgeon technical performance and continence outcomes in RARP. While this single surgeon, patient-matched case-control design limits confounding, multi-institutional prospective studies studying multiple surgeons of different abilities forms the basis of future research in this area. The implication of our findings are potentially far reaching, and moving forward, stakeholders in education and accreditation of RARP should incorporate both surgeon technical skill and error rating into judgments of surgical quality. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e699 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Mitchell G. Goldenberg More articles by this author S. Larry Goldenberg More articles by this author Teodor P. Grantcharov More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Incremental Utility of Iodine-123 Meta-Iodobenzylguanidine Imaging Beyond Established Heart Failure Risk Models

BackgroundNuclear myocardial imaging with iodine-123 meta-iodobenzylguanidine (123I-mIBG) is approved for risk stratification of patients with systolic heart failure (HF). Whether 123I-mIBG imaging provides incremental prognostic utility beyond established risk models remains unclear. Methods and ResultsIn a multicenter study, 961 patients with moderate systolic HF underwent 123I-mIBG imaging and were followed for cardiac death, progressive HF, or life-threatening arrhythmias over 2 years. We constructed 4 multivariable models, using variables from each of 4 published HF risk models, and patient-level scores were calculated both before and after adding the heart-to-mediastinum ratio (H/M) from 123I-mIBG imaging. Incremental utility was evaluated by calculating integrated discrimination improvement (IDI), which quantifies the increase in probability of experiencing the primary end point after adding H/M to each model. The composite end point occurred in 25% of patients. After adding H/M, absolute IDI ranged from 2.1% to 3.0%, representing 33%–59% relative improvements in risk stratification. Of note, hazard ratios for H/M were remarkably similar between risk models (0.40–0.44 for predicting the composite end point, 0.10–0.18 for mortality; all P < .001). ConclusionsDespite notable differences in predictor variables, patient populations, and analytic techniques from which each model was initially derived, adding 123I-mIBG data to HF risk models consistently identified patients at lower risk of experiencing adverse events.

Explaining Racial/Ethnic Differences in Adolescent Substance Abuse Treatment Completion in the United States: A Decomposition Analysis

To identify contributors to racial/ethnic differences in completion of alcohol and marijuana treatment among adolescents at publicly funded providers. The 2007 Treatment Episode Data Set provided substance use history, treatment setting, and treatment outcomes for youth aged 12-17 years from five racial/ethnic groups (N = 67,060). Individual-level records were linked to variables measuring the social context and service system characteristics of the metropolitan area. We implemented nonlinear regression decomposition to identify variables that explained minority-white differences. Black and Hispanic youth were significantly less likely than whites to complete treatment for both alcohol and marijuana. Completion rates were similar for whites, Native Americans, and Asian-Americans, however. Differences in predictor variables explained 12.7% of the black-white alcohol treatment gap and 7.6% of the marijuana treatment gap. In contrast, predictors explained 57.4% of the Hispanic-white alcohol treatment gap and 19.8% of the marijuana treatment gap. While differences in the distribution of individual-level variables explained little of the completion gaps, metropolitan-level variables substantially contributed to Hispanic-white gaps. For example, racial/ethnic composition of the metropolitan area explained 41.0% of the Hispanic-white alcohol completion gap and 23.2% of the marijuana completion gap. Regional differences in addiction treatment financing (particularly use of Medicaid funding) explained 13.7% of the Hispanic-white alcohol completion gap and 9.8% of the Hispanic-white marijuana treatment completion gap. Factors related to social context are likely to be important contributors to white-minority differences in addiction treatment completion, particularly for Hispanic youth. Increased Medicaid funding, coupled with culturally tailored services, could be particularly beneficial.

The Digital Divide and Urban Older Adults

Computers and the Internet offer older adults opportunities and resources for independent living. However, many urban older adults do not use computers. This study examined the demographic, health, and social activities of urban older adults to determine variables that might predict the use and nonuse of computers in this population. A secondary data analysis was performed using the 2001 Detroit City-Wide Needs Assessment of Older Adults (n = 1410) data set. Logistic regression was used to explore potential differences in predictor variables between computer users and nonusers. Overall, computer users were younger (27%), had a higher level of education, were more likely to be employed, had an annual income greater than $20,000, and were healthier and more active than nonusers. They also were more likely to have memberships in community organizations and do volunteer work. Preferred computer activities included conducting Internet searches, playing games, writing, and communicating with family members and friends. The results suggest significant differences in demographic and health-related characteristics between computer users and nonusers among urban older adults. Although about a quarter of participants in this study used computers, the Digital Divide continues to exist in urban settings for scores of others.

Effects of sample survey design on the accuracy of classification tree models in species distribution models

We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by resubstitution rates were similar for each lichen species irrespective of the underlying sample survey form. Cross-validation estimates of prediction accuracies were lower than resubstitution accuracies for all species and both design types, and in all cases were closer to the true prediction accuracies based on the EVALUATION data set. We argue that greater emphasis should be placed on calculating and reporting cross-validation accuracy rates rather than simple resubstitution accuracy rates. Evaluation of the DESIGN and PURPOSIVE tree models on the EVALUATION data set shows significantly lower prediction accuracy for the PURPOSIVE tree models relative to the DESIGN models, indicating that non-probabilistic sample surveys may generate models with limited predictive capability. These differences were consistent across all four lichen species, with 11 of the 12 possible species and sample survey type comparisons having significantly lower accuracy rates. Some differences in accuracy were as large as 50%. The classification tree structures also differed considerably both among and within the modelled species, depending on the sample survey form. Overlap in the predictor variables selected by the DESIGN and PURPOSIVE tree models ranged from only 20% to 38%, indicating the classification trees fit the two evaluated survey forms on different sets of predictor variables. The magnitude of these differences in predictor variables throws doubt on ecological interpretation derived from prediction models based on non-probabilistic sample surveys.

Length of Stay, Discharge Disposition, and Hospital Charge Predictors

THIS STUDY EXPLORED the effect of patient, clinical, and treatment factors on length of stay (LOS), discharge disposition, and total acute care hospital charges for older adults undergoing elective total hip arthroplasty or total knee arthroplasty. A CAUSATIVE RETROSPECTIVE DESIGN was used, and data analysis included descriptive statistics, multiple regression, and logistic regression. SIGNIFICANT DIFFERENCES in predictor variables (ie, age, gender, living arrangement, comorbidities, postoperative complications) were found between patients who were discharged to home and those who were discharged to another facility. Only postoperative complications contributed significantly to LOS. Total surgical time and postoperative complications contributed significantly to hospital charges.

The effects of health and treatment perceptions on the use of prescribed medication and home remedies among African American and white American hypertensives

This study examines the relationships between health beliefs and the use of both prescribed medication and home remedies among a group of African American and White American hypertensives. Data were collected via telephone interviews with 300 individuals who had been medically diagnosed as having hypertension and had been prescribed at least one antihypertensive medication. Using the health belief model (HBM) as the theoretical framework, 4 primary hypotheses involving the perceptions of severity, susceptibility, benefits and costs of each treatment and compliance with prescribed mediation (Rx) and use of home remedies (HR) were tested. Multivariate logistic regression analyses indicated that age, costs of Rx and benefits of HR predicted compliance with Rx. The primary predictors of use of HR were ethnicity, poverty status, education, severity, benefits and costs of HR. The differences in predictor variables for each treatment behavior are discussed and speculations about the nature and importance of these differences are offered. Study findings support the suggestion that patient beliefs about their disease and their evaluations of treatment options should be considered when developing therapeutic plans and when monitoring patient outcomes.