Regenstrief Institute

About: Regenstrief Institute is a nonprofit organization based out in Indianapolis, Indiana, United States. It is known for research contribution in the topics: Health care & Population. The organization has 742 authors who have published 2042 publications receiving 96966 citations.

SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer

Abstract: Improved cancer prognosis is a central goal for precision health medicine. Though many models can predict differential survival from data, there is a strong need for sophisticated algorithms that can aggregate and filter relevant predictors from increasingly complex data inputs. In turn, these models should provide deeper insight into which types of data are most relevant to improve prognosis. Deep Learning-based neural networks offer a potential solution for both problems because they are highly flexible and account for data complexity in a non-linear fashion. In this study, we implement Deep Learning-based networks to determine how gene expression data predicts Cox regression survival in breast cancer. We accomplish this through an algorithm called SALMON (Survival Analysis Learning with Multi-Omics Neural Networks), which aggregates and simplifies gene expression data and cancer biomarkers to enable prognosis prediction. The results revealed improved performance when more omics data were used in model construction. Rather than use raw gene expression values as model inputs, we innovatively use eigengene modules from the result of gene co-expression network analysis. The corresponding high impact co-expression modules and other omics data are identified by feature selection technique, then examined by conducting enrichment analysis and exploiting biological functions, escalated the interpretation of input feature from gene level to co-expression modules level. Our study shows the feasibility of discovering breast cancer related co-expression modules, sketch a blueprint of future endeavors on Deep Learning-based survival analysis. SALMON source code is available at https://github.com/huangzhii/SALMON/.

Health-related quality of life in patients with coronary artery disease treated for angina: validity and reliability of German translations of two specific questionnaires.

Abstract: The German versions of two patient-perceived heart disease specific health-related quality of life (HRQL) questionnaires, the Seattle Angina Questionnaire (SAQ) and the MacNew Heart Disease questionnaire, were examined for their psychometric properties in patients with angiographically documented coronary artery disease and angina who were treated either medically or invasively and followed up for 1 year. Both HRQL questionnaires and the modified Canadian Cardiovascular Society (CCS) angina-associated disability scale were completed by 158 patients at baseline and 12 months later when they also completed a generic health status questionnaire, the SF-36. Both specific HRQL questionnaires were acceptable to patients. Three of the four MacNew scales, but none of the SAQ scales, discriminated between patients by baseline CCS disability levels I and IV. Internal consistency ranged from 0.75 to 0.94 for the SAQ and from 0.86 to 0.97 for the MacNew scales. Test-retest reliability over a 4-week period of time ranged from 0.45 to 0.81 for the SAQ scales and 0.61 to 0.68 for the MacNew scales. Over 12 months, HRQL improved (p < 0.001) on three of the five SAQ and on all four of the MacNew scales with the responsiveness statistic ranging from 0.59 to 1.55 for the SAQ and 0.86 to 1.12 for the MacNew. The 12 month scores on all SAQ and MacNew scales were significantly higher in patients who improved than those who deteriorated on the SF-36 reported health transition question. We conclude that the SAQ and the MacNew are both valid, reliable, and responsive in German, that the MacNew discriminates better between angina grades at baseline, that HRQL improves over 12 months with both measures, that the SAQ angina frequency and disease perception scales have the largest effect sizes, and that the 12-month change in HRQL with both instruments was associated with change in SF-36 reported health transition status.

Incident and long-term opioid therapy among patients with psychiatric conditions and medications: a national study of commercial health care claims.

Abstract: There is growing evidence that opioid prescribing in the United States follows a pattern in which patients who are at the highest risk of adverse outcomes from opioids are more likely to receive long-term opioid therapy. These patients include, in particular, those with substance use disorders (SUDs) and other psychiatric conditions. This study examined health insurance claims among 10,311,961 patients who filled prescriptions for opioids. Specifically, we evaluated how opioid receipt differed among patients with and without a wide range of preexisting psychiatric and behavioral conditions (ie, opioid and nonopioid SUDs, suicide attempts or other self-injury, motor vehicle crashes, and depressive, anxiety, and sleep disorders) and psychoactive medications (ie, antidepressants, benzodiazepines, hypnotics, mood stabilizers, antipsychotics, and medications used for SUD, tobacco cessation, and attention-deficit/hyperactivity disorder). Relative to those without, patients with all assessed psychiatric conditions and medications had modestly greater odds of subsequently filling prescriptions for opioids and, in particular, substantially greater risk of long-term opioid receipt. Increases in risk for long-term opioid receipt in adjusted Cox regressions ranged from approximately 1.5-fold for prior attention-deficit/hyperactivity disorder medication prescriptions (hazard ratio [HR] = 1.53; 95% confidence interval [CI], 1.48-1.58) to approximately 3-fold for prior nonopioid SUD diagnoses (HR = 3.15; 95% CI, 3.06-3.24) and nearly 9-fold for prior opioid use disorder diagnoses (HR = 8.70; 95% CI, 8.20-9.24). In sum, we found evidence of greater opioid receipt among commercially insured patients with a breadth of psychiatric conditions. Future studies assessing behavioral outcomes associated with opioid prescribing should consider preexisting psychiatric conditions.

Biomarkers for Delirium—A Review

Abstract: To improve delirium recognition and care, numerous serum biomarkers have been investigated as potential tools for risk stratification, diagnosis, monitoring, and prognostication of delirium. The literature was reviewed, and no evidence was found to support the clinical use of any delirium biomarker, although certain biomarkers such as S-100 beta and insulin-like growth factor-1 and inflammatory markers have shown some promising results that need to be evaluated in future studies with appropriate sample size, prospective designs, and in a more-generalizable population.