Feasibility of High-Frequency Monitoring of the Home Environment and Health in Older Adults: Proof of Concept.

Technology provides new opportunities to understand and optimize the relationship between the home indoor environmental quality and health outcomes in older adults. We aimed to establish proof-of-concept and feasibility of remote, real-time, high-frequency, and simultaneous monitoring of select environmental variables and outcomes related to health and wellbeing in older adults. Thirty-four participants (27 were female) with an average age (SD) of 81 years (±7.1) were recruited from community and supportive housing environments. Environmental sensors were installed in each home and participants were asked to use a wearable device on their finger and answer smartphone-based questionnaires on a daily basis. Further, a subgroup of participants were asked to complete tablet-based cognitive tests on a daily basis. Average compliance with the wearable (time worn properly / total time with device) was 81%. Participants responded to 69% of daily smartphone surveys and completed 80% of the prescribed cognitive tests. These results suggest that it is feasible to study the impact of the home thermal environment and air quality on biological rhythms, cognition, and other outcomes in older adults. However, the success of non-passive data collection elements may be contingent upon baseline cognition.

Hospital resource intensity and cirrhosis mortality in United States.

AIM: To determine whether hospital characteristics predict cirrhosis mortality and how much variation in mortality is attributable to hospital differences. METHODS: We used data from the 2005-2011 Nationwide Inpatient Sample and the American Hospital Association Annual survey to identify hospitalizations for decompensated cirrhosis and corresponding facility characteristics. We created hospital-specific risk and reliability-adjusted odds ratios for cirrhosis mortality, and evaluated patient and facility differences based on hospital performance quintiles. We used hierarchical regression models to determine the effect of these factors on mortality. RESULTS: Seventy-two thousand seven hundred and thirty-three cirrhosis admissions were evaluated in 805 hospitals. Hospital mean cirrhosis annual case volume was 90.4 (range 25-828). Overall hospital cirrhosis mortality rate was 8.00%. Hospital-adjusted odds ratios (aOR) for mortality ranged from 0.48 to 1.89. Patient characteristics varied significantly by hospital aOR for mortality. Length of stay averaged 6.0 ± 1.6 days, and varied significantly by hospital performance (P < 0.001). Facility level predictors of risk-adjusted mortality were higher Medicaid case-mix (OR = 1.00, P = 0.029) and LPN staffing (OR = 1.02, P = 0.015). Higher cirrhosis volume (OR = 0.99, P = 0.025) and liver transplant program status (OR = 0.83, P = 0.026) were significantly associated with survival. After adjusting for patient differences, era, and clustering effects, 15.3% of variation between hospitals was attributable to differences in facility characteristics. CONCLUSION: Hospital characteristics account for a significant proportion of variation in cirrhosis mortality. These findings have several implications for patients, providers, and health care delivery in liver disease care and inpatient health care design.

Rapid assessment of technical competency: the 8-min suture test.

BACKGROUND: Although simulation training and evaluation have become increasingly popular for teaching minimally invasive surgery, tools to measure open surgical skills remain underdeveloped. As there is increasing demand for objective measures of technical competency at the completion of surgical training (postgraduate year [PGY]-6 and -7), this project was designed to assess the feasibility, reliability, and validity of a novel open surgical skills evaluation tool, the 8-min suture test (8MST). METHODS: During an annual surgical skills laboratory session, fellows and residents were asked to complete a simulated end-to-end vascular anastomosis. They were limited to 8 min to perform the anastomosis between two 12-mm Dacron grafts mounted on a customized platform. Their real-time and video-recorded performance was scored by two blinded evaluators and compared with their faculty-rated technical performance on clinical rotations completed around the time of 8MST administration. RESULTS: PGY-6 and PGY-7 trainees were compared across several domains including 8MST total score (4.6 versus 5.5, P = 0.030), 8MST setup score (2.3 versus 2.4, P = 0.797), 8MST technical score (2.3 versus 3.1, P = 0.026), and clinical performance score (3.1 versus 3.6, P = 0.006). Comparison of 8MST total score to the clinical performance score identified a strong relationship with a Pearson r = 0.55 (P < 0.001) and r(2) = 0.30. Additionally, 8MST displayed high inter-rater reliability and test-retest reliability. CONCLUSIONS: The 8MST is a rapid, feasible, inexpensive, reliable, and valid test for assessment of surgical trainee technical abilities.

Near-native protein loop sampling using nonparametric density estimation accommodating sparcity.

Unlike the core structural elements of a protein like regular secondary structure, template based modeling (TBM) has difficulty with loop regions due to their variability in sequence and structure as well as the sparse sampling from a limited number of homologous templates. We present a novel, knowledge-based method for loop sampling that leverages homologous torsion angle information to estimate a continuous joint backbone dihedral angle density at each loop position. The φ,ψ distributions are estimated via a Dirichlet process mixture of hidden Markov models (DPM-HMM). Models are quickly generated based on samples from these distributions and were enriched using an end-to-end distance filter. The performance of the DPM-HMM method was evaluated against a diverse test set in a leave-one-out approach. Candidates as low as 0.45 Å RMSD and with a worst case of 3.66 Å were produced. For the canonical loops like the immunoglobulin complementarity-determining regions (mean RMSD <2.0 Å), the DPM-HMM method performs as well or better than the best templates, demonstrating that our automated method recaptures these canonical loops without inclusion of any IgG specific terms or manual intervention. In cases with poor or few good templates (mean RMSD >7.0 Å), this sampling method produces a population of loop structures to around 3.66 Å for loops up to 17 residues. In a direct test of sampling to the Loopy algorithm, our method demonstrates the ability to sample nearer native structures for both the canonical CDRH1 and non-canonical CDRH3 loops. Lastly, in the realistic test conditions of the CASP9 experiment, successful application of DPM-HMM for 90 loops from 45 TBM targets shows the general applicability of our sampling method in loop modeling problem. These results demonstrate that our DPM-HMM produces an advantage by consistently sampling near native loop structure. The software used in this analysis is available for download at http://www.stat.tamu.edu/~dahl/software/cortorgles/.

A DIRICHLET PROCESS MIXTURE OF HIDDEN MARKOV MODELS FOR PROTEIN STRUCTURE PREDICTION.

By providing new insights into the distribution of a protein's torsion angles, recent statistical models for this data have pointed the way to more efficient methods for protein structure prediction. Most current approaches have concentrated on bivariate models at a single sequence position. There is, however, considerable value in simultaneously modeling angle pairs at multiple sequence positions in a protein. One area of application for such models is in structure prediction for the highly variable loop and turn regions. Such modeling is difficult due to the fact that the number of known protein structures available to estimate these torsion angle distributions is typically small. Furthermore, the data is "sparse" in that not all proteins have angle pairs at each sequence position. We propose a new semiparametric model for the joint distributions of angle pairs at multiple sequence positions. Our model accommodates sparse data by leveraging known information about the behavior of protein secondary structure. We demonstrate our technique by predicting the torsion angles in a loop from the globin fold family. Our results show that a template-based approach can now be successfully extended to modeling the notoriously difficult loop and turn regions.