Effects of VA Facility Dog on Hospitalized Veterans Seen by a Palliative Care Psychologist: An Innovative Approach to Impacting Stress Indicators.

The United States is home to 23 million veterans. In many instances, veterans with serious illness who seek healthcare at the VA receive care from a palliative care service. Animal-assisted intervention (AAI) is gaining attention as a therapeutic stress reducing modality; however, its effects have not been well studied in veterans receiving palliative care in an acute care setting. A crossover repeated-measures study was conducted to examine the effects of an animal-assisted intervention (AAI) in the form of a therapy dog on stress indicators in 25 veterans on the palliative care service at the VA Eastern Colorado Healthcare System in Denver, CO. Veterans had a visit from a therapy dog and the dog's handler, a clinical psychologist (experimental condition) and an unstructured visit with the clinical psychologist alone (control condition). Blood pressure, heart rate, and the salivary biomarkers cortisol, alpha-amylase, and immunoglobulin A were collected before, after, and 30-minutes after both the experimental and control conditions. Significant decreases in cortisol were found when the before time period was compared to the 30-minutes after time period for both the experimental ( p = 0.007) and control condition ( p = 0.036). A significant decrease in HR was also found when the before time period was compared to the 30-minutes after time period for both the experimental ( p = 0.0046) and control ( p = 0.0119) condition. Results of this study supported that a VA facility dog paired with a palliative care psychologist had a measurable impact on salivary cortisol levels and HR in veterans.

Nonparametric multivariate inference on shift parameters.

RATIONALE AND OBJECTIVES: Consider a study evaluating the prognostic value of prostate-specific antigen (PSA), in the presence of Gleason score, in differentiating between early and advanced prostate cancer. This data set features subjects divided into two groups (early versus advanced cancer), with one manifest variable (PSA), one covariate (Gleason score), and one stratification variable (hospital, taking three values). We present a nonparametric method for estimating a shift in median PSA score between the two groups, after adjusting for differences in Gleason score and stratifying on hospital. This method can also be extended to cases involving multivariate manifest variable. MATERIALS AND METHODS: Our method uses estimating equations derived from an existing rank-based estimator of the area under the receiver operating characteristic curve (AUC). This existing AUC estimator is adjusted for stratification and for covariates. We use the adjusted AUC estimator to construct a family of tests by shifting manifest variables in one of the treatment groups by an arbitrary constant. The null hypothesis for these tests is that the AUC is half. We report the set of shift values for which the null hypothesis is not rejected as the resulting confidence region. RESULTS: Simulated data show performance consistent with the distributional approximations used by the proposed methodology. This methodology is applied to two examples. In the first example, the mean difference in PSA levels between advanced and nonadvanced prostate cancer patients is estimated, controlling for Gleason score. In the second example, to assess the degree to which age and baseline tumor size are prognostic factors for breast cancer recurrence, differences in age and tumor size between subjects with recurrent and nonrecurrent breast cancer, stratified on Tamoxifen treatment and adjusting for tumor grade, are estimated. CONCLUSIONS: The proposed methodology provides a nonparametric method for a statistic measuring adjusted AUC to be used to estimate shift between two manifest variables.

Evaluation of injury databases as a preliminary step to developing a triage decision rule.

PURPOSE: To evaluate accessibility and appropriateness of the Crash Outcomes Data Evaluation Systems (CODES) databases for prehospital trauma triage decision-rule development for people age 65 years and older. DESIGN AND METHODS: This informatics feasibility study included five steps for evaluating the accessibility of CODES databases. Eight criteria were used to evaluate the appropriateness of these databases for older person prehospital trauma triage decision-rule development. FINDINGS: Only 4 of the 33 states funded for CODES database development released their data to the study team during the 13-month data-acquisition period. Potential predictor variables (of life-threatening injury) and outcome variables (need for trauma center care) were identified for each database. Several databases had large amounts of missing data. Codebooks were available but descriptions of data validation procedures were unavailable. CONCLUSIONS: At this time, limited access to and development of CODES databases and missing data preclude the usefulness of these databases for older person triage decision rule development. Although adequate funding must be appropriated for continued CODES development, and commitment from individual states is essential, these databases offer great promise as a mechanism for decision-rule development to guide triage decision-making. Investigators should systematically evaluate large databases before using them in secondary analyses for clinical decision rule development. CLINICAL RELEVANCE: Nurses participate in the planning, development, and implementation of health information systems in various settings. They also assume important roles in prehospital care as direct care providers, EMS administrators, participants of local and state EMS councils where emergency care problems are discussed and policies are formulated, and through use at state and federal levels.

Using crash scene variables to predict the need for trauma center care in older persons.

Current trauma triage protocols lack sensitivity to occult injuries in older persons, resulting in unacceptable undertriage rates. We identified crash scene information that could be used by emergency personnel to identify the need for trauma center care in older persons injured in motor vehicle crashes. Crash records of 7,883 persons 65 years and older were explored using classification and regression trees (CART) analysis. CART analysis of 26 crash scene variables resulted in two classification trees from which triage decision rules were stated for persons with severe and moderate injuries. Sensitivity and specificity of the rules were 95.15% and 76.47% for severe injury and 83.1% and 81.5% for moderate injury.