Effect of a pharmacist-led multicomponent intervention focussing on the medication monitoring phase to prevent potential adverse drug events in nursing homes

OBJECTIVES: To determine the extent to which the use of a clinical informatics tool that implements prospective monitoring plans reduces the incidence of potential delirium, falls, hospitalizations potentially due to adverse drug events, and mortality.

DESIGN: Randomized cluster trial.

SETTING: Twenty-five nursing homes serviced by two long-term care pharmacies.

PARTICIPANTS: Residents living in nursing homes during 2003 (1,711 in 12 intervention; 1,491 in 13 usual care) and 2004 (1,769 in 12 intervention; 1,552 in 13 usual care).

INTERVENTION: The pharmacy automatically generated Geriatric Risk Assessment MedGuide (GRAM) reports and automated monitoring plans for falls and delirium within 24 hours of admission or as part of the normal time frame of federally mandated drug regimen review.

MEASUREMENTS: Incidence of potential delirium, falls, hospitalizations potentially due to adverse drug events, and mortality.

RESULTS: GRAM triggered monitoring plans for 491 residents. Newly admitted residents in the intervention homes experienced a lower rate of potential delirium onset than those in usual care homes (adjusted hazard ratio (HR)=0.42, 95% confidence interval (CI)=0.35–0.52), overall hospitalization (adjusted HR=0.89, 95% CI=0.72–1.09), and mortality (adjusted HR=0.88, 95% CI=0.66–1.16). In longer stay residents, the effects of the intervention were attenuated, and all estimates included unity.

CONCLUSION: Using health information technology in long-term care pharmacies to identify residents who might benefit from the implementation of prospective medication monitoring care plans when complex medication regimens carry potential risks for falls and delirium may reduce adverse effects associated with appropriate medication use.

Do general practitioners change how they use the computer during consultations with a significant psychological component?

objectives: To describe the patterns of computer use during patient visits to family doctors and to determine whether doctors alter their pattern of computer use in consultations which have significant psychological content.

Relative metabolomic flux: Predicting changes in the environmental metabolome from the metagenome

Background: The world's oceans are home to a diverse array of microbial life whose metabolic activity helps to drive the earth's biogeochemical cycles. Metagenomic analysis has revolutionized our access to these communities, providing a system-scale perspective of microbial community interactions. However, while metagenome sequencing can provide useful estimates of the relative change in abundance of specific genes and taxa between environments or over time, this does not investigate the relative changes in the production or consumption of different metabolites.
Results: We propose a methodology, Predicted Relative Metabolic Turnover (PRMT) that defines and enables exploration of metabolite-space inferred from the metagenome. Our analysis of metagenomic data from a time-series study in the Western English Channel demonstrated considerable correlations between predicted relative metabolic turnover and seasonal changes in abundance of measured environmental parameters as well as with observed seasonal changes in bacterial population structure.
Conclusions: The PRMT method was successfully applied to metagenomic data to explore the Western English Channel microbial metabalome to generate specific, biologically testable hypotheses. Generated hypotheses linked organic phosphate utilization to Gammaproteobactaria, Plantcomycetes, and Betaproteobacteria, chitin degradation to Actinomycetes, and potential small molecule biosynthesis pathways for Lentisphaerae, Chlamydiae, and Crenarchaeota. The PRMT method can be applied as a general tool for the analysis of additional metagenomic or transcriptomic datasets.

Diabetes-related adduct formation and retinopathy

The pathogenesis of diabetic retinopathy is complex, reflecting the array of systemic and tissue-specific metabolic abnormalities. A range of pathogenic pathways are directly linked to hyperglycaemia and dyslipidaemia, and the retina appears to be exquisitely sensitive to damage. Establishing the biochemical and molecular basis for this pathology remains an important research focus. This review concentrates on the formation of a range of protein adducts that form after exposure to modifying intermediates known to be elevated during diabetes. These so-called advanced glycation end products (AGEs) and advanced lipoxidation end products (ALEs) are thought to play an important role in the initiation and progression of diabetic retinopathy, and mechanisms leading to dysfunction and death of various retinal cells are becoming understood. Perspective is provided on AGE/ALE formation in the retina and the impact that such adducts have on retinal cell function. There will be emphasis placed on the role of the receptor for AGEs and how this may modulate retinal pathology, especially in relation to oxidative stress and inflammation. The review will conclude by discussion of strategies to inhibit AGE/ALE formation or harmful receptor interactions in order to prevent disease progression from the point of diabetes diagnosis to sight-threatening proliferative diabetic retinopathy and diabetic macular oedema.

Accelerating Multiple Sequence Alignment with the Cell BE Processor

The Cell Broadband Engine (BE) Architecture is a new heterogeneous multi-core architecture targeted at compute-intensive workloads. The architecture of the Cell BE has several features that are unique in high-performance general-purpose processors, most notably the extensive support for vectorization, scratch pad memories and explicit programming of direct memory accesses (DMAs) and mailbox communication. While these features strongly increase programming complexity, it is generally claimed that significant speedups can be obtained by using Cell BE processors. This paper presents our experiences with using the Cell BE architecture to accelerate Clustal W, a bio-informatics program for multiple sequence alignment. We report on how we apply the unique features of the Cell BE to Clustal W and how important each is in obtaining high performance. By making extensive use of vectorization and by parallelizing the application across all cores, we demonstrate a speedup of 24.4 times when using 16 synergistic processor units on a QS21 Cell Blade compared to single-thread execution on the power processing unit. As the Cell BE exploits a large number of slim cores, our highly optimized implementation is just 3.8 times faster than a 3-thread version running on an Intel Core2 Duo, as the latter processor exploits a small number of fat cores.

Web Data Extraction from Query Result Pages Based on Visual and Content Features

A rapidly increasing number of Web databases are now become accessible via
their HTML form-based query interfaces. Query result pages are dynamically generated
in response to user queries, which encode structured data and are displayed for human
use. Query result pages usually contain other types of information in addition to query
results, e.g., advertisements, navigation bar etc. The problem of extracting structured data
from query result pages is critical for web data integration applications, such as comparison
shopping, meta-search engines etc, and has been intensively studied. A number of approaches
have been proposed. As the structures of Web pages become more and more complex, the
existing approaches start to fail, and most of them do not remove irrelevant contents which
may a®ect the accuracy of data record extraction. We propose an automated approach for
Web data extraction. First, it makes use of visual features and query terms to identify data
sections and extracts data records in these sections. We also represent several content and
visual features of visual blocks in a data section, and use them to ¯lter out noisy blocks.
Second, it measures similarity between data items in di®erent data records based on their
visual and content features, and aligns them into di®erent groups so that the data in the
same group have the same semantics. The results of our experiments with a large set of
Web query result pages in di®erent domains show that our proposed approaches are highly
e®ective.

Diagnostic accuracy and clinical management by realtime teledermatology. Results from the Northern Ireland arms of the UK Multicentre Teledermatology Trial

Diagnostic accuracy and management recommendations of realtime teledermatology consultations using low-cost telemedicine equipment were evaluated. Patients were seen by a dermatologist over a video-link and a diagnosis and treatment plan were recorded. This was followed by a face-to-face consultation on the same day to confirm the earlier diagnosis and management plan. A total of 351 patients with 427 diagnoses participated. Sixty-seven per cent of the diagnoses made over the video-link agreed with the face-to-face diagnosis. Clinical management plans were recorded for 214 patients with 252 diagnoses. For this cohort, 44% of the patients were seen by the same dermatologist at both consultations, while 56% were seen by a different dermatologist. In 64% of cases the same management plan was recommended at both consultations; a sub-optimum treatment plan was recommended in 8% of cases; and in 9% of cases the video-link management plans were judged to be inappropriate. In 20% of cases the dermatologist was unable to recommend a suitable management plan by video-link. There were significant differences in the ability to recommend an optimum management plan by video-link when a different dermatologist made the reference management plan. The results indicate that a high proportion of dermatological conditions can be successfully managed by realtime teledermatology.