Patterns of primary care and mortality among patients with schizophrenia or diabetes: a cluster analysis approach to the retrospective study of healthcare utilization

Abstract Background Patients with schizophrenia have difficulty managing their medical healthcare needs, possibly resulting in delayed treatment and poor outcomes. We analyzed whether patients reduced primary care use over time, differentially by diagnosis with schizophrenia, diabetes, or both schizophrenia and diabetes. We also assessed whether such patterns of primary care use were a significant predictor of mortality over a 4-year period. Methods The Veterans Healthcare Administration (VA) is the largest integrated healthcare system in the United States. Administrative extracts of the VA's all-electronic medical records were studied. Patients over age 50 and diagnosed with schizophrenia in 2002 were age-matched 1:4 to diabetes patients. All patients were followed through 2005. Cluster analysis explored trajectories of primary care use. Proportional hazards regression modelled the impact of these primary care utilization trajectories on survival, controlling for demographic and clinical covariates. Results Patients comprised three diagnostic groups: diabetes only (n = 188,332), schizophrenia only (n = 40,109), and schizophrenia with diabetes (Scz-DM, n = 13,025). Cluster analysis revealed four distinct trajectories of primary care use: consistent over time, increasing over time, high and decreasing, low and decreasing. Patients with schizophrenia only were likely to have low-decreasing use (73% schizophrenia-only vs 54% Scz-DM vs 52% diabetes). Increasing use was least common among schizophrenia patients (4% vs 8% Scz-DM vs 7% diabetes) and was associated with improved survival. Low-decreasing primary care, compared to consistent use, was associated with shorter survival controlling for demographics and case-mix. The observational study was limited by reliance on administrative data. Conclusion Regular primary care and high levels of primary care were associated with better survival for patients with chronic illness, whether psychiatric or medical. For schizophrenia patients, with or without comorbid diabetes, primary care offers a survival benefit, suggesting that innovations in treatment retention targeting at-risk groups can offer significant promise of improving outcomes.http://deepblue.lib.umich.edu/bitstream/2027.42/78274/1/1472-6963-9-127.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78274/2/1472-6963-9-127.pdfPeer Reviewe

An effective non-parametric method for globally clustering genes from expression profiles

Clustering is widely used in bioinformatics to find gene correlation patterns. Although many algorithms have been proposed, these are usually confronted with difficulties in meeting the requirements of both automation and high quality. In this paper, we propose a novel algorithm for clustering genes from their expression profiles. The unique features of the proposed algorithm are twofold: it takes into consideration global, rather than local, gene correlation information in clustering processes; and it incorporates clustering quality measurement into the clustering processes to implement non-parametric, automatic and global optimal gene clustering. The evaluation on simulated and real gene data sets demonstrates the effectiveness of the algorithm. <br /

Bacterial and Archaea Community Present in the Pine Barrens Forest of Long Island, NY: Unusually High Percentage of Ammonia Oxidizing Bacteria

Of the few preserved areas in the northeast of United States, the soil in the Pine Barrens Forests presents a harsh environment for the microorganisms to grow and survive. In the current study we report the use of clustering methods to scientifically select the sampling locations that would represent the entire forest and also report the microbial diversity present in various horizons of the soil. Sixty six sampling locations were selected across the forest and soils were collected from three horizons (sampling depths). The three horizons were 0–10 cm (Horizon O); 11–25 cm (Horizon A) and 26–40 cm (Horizon B). Based on the total microbial substrate utilization pattern and K-means clustering analysis, the soil in the Pine Barrens Forest can be classified into four distinct clusters at each of the three horizons. One soil sample from each of the four clusters were selected and archaeal and bacterial populations within the soil studied using pyrosequencing method. The results show the microbial communities present in each of these clusters are different. Within the microbial communities present, microorganisms involved in nitrogen cycle occupy a major fraction of microbial community in the soil. High level of diversity was observed for nitrogen fixing bacteria. In contrast, Nitrosovibrio and Nitrosocaldus spp are the single bacterial and archaeal population respectively carrying out ammonia oxidation in the soil

HIV Services Utilization in Los Angeles County, California

Recipients of HIV/AIDS prevention services in Los Angeles County California were surveyed in 2004 by 220 HIV prevention service provider staff from 51 agencies funded by the Office of AIDS Programs and Policy. This resulted in 2,102 usable surveys for cluster analysis purposes. This Countywide Risk Assessment Survey assessed demographics, sexual history, substance use, perceptions regarding HIV/AIDS, and use of 18 different services at both the agency administering the survey and at other agencies. The 36 types of service use data were subjected to a cluster analysis that found five clusters. These service pattern clusters differed from each other on proportion HIV positive, HIV testing history, history of abuse, education, type of residence, type of funding, intervention type, and ethnicity. The analysis also suggests that domestic violence services availability and utilization should be examined more thoroughly in the future for HIV infected/affected populations

Identification of symptom and functional domains that fibromyalgia patients would like to see improved: a cluster analysis

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to determine whether some of the clinical features of fibromyalgia (FM) that patients would like to see improved aggregate into definable clusters.</p> <p>Methods</p> <p>Seven hundred and eighty-eight patients with clinically confirmed FM and baseline pain ≥40 mm on a 100 mm visual analogue scale ranked 5 FM clinical features that the subjects would most like to see improved after treatment (one for each priority quintile) from a list of 20 developed during focus groups. For each subject, clinical features were transformed into vectors with rankings assigned values 1-5 (lowest to highest ranking). Logistic analysis was used to create a distance matrix and hierarchical cluster analysis was applied to identify cluster structure. The frequency of cluster selection was determined, and cluster importance was ranked using cluster scores derived from rankings of the clinical features. Multidimensional scaling was used to visualize and conceptualize cluster relationships.</p> <p>Results</p> <p>Six clinical features clusters were identified and named based on their key characteristics. In order of selection frequency, the clusters were Pain (90%; 4 clinical features), Fatigue (89%; 4 clinical features), Domestic (42%; 4 clinical features), Impairment (29%; 3 functions), Affective (21%; 3 clinical features), and Social (9%; 2 functional). The "Pain Cluster" was ranked of greatest importance by 54% of subjects, followed by Fatigue, which was given the highest ranking by 28% of subjects. Multidimensional scaling mapped these clusters to two dimensions: Status (bounded by Physical and Emotional domains), and Setting (bounded by Individual and Group interactions).</p> <p>Conclusion</p> <p>Common clinical features of FM could be grouped into 6 clusters (Pain, Fatigue, Domestic, Impairment, Affective, and Social) based on patient perception of relevance to treatment. Furthermore, these 6 clusters could be charted in the 2 dimensions of Status and Setting, thus providing a unique perspective for interpretation of FM symptomatology.</p

A simple and rapid method for assessing similarities among directly observable behavioral effects of drugs: PCP-like effects of 2-amino-5-phosphonovalerate in rats

Directly observable behavioral effects of the N-methyl- D -aspartate (NMDA) receptor antagonist 2-amino-5-phosphonovalerate (AP5) (10–1,000 mg/kg IP, 0.18–5.6 μmol/rat ICV) and of phencyclidine (PCP) (3.2–56 mg/kg IP, 0.032–3.2 mg/rat ICV), ketamine (10–100 mg/kg), amphetamine (1–18 mg/kg), apomorphine (0.1–5.6 mg/kg), chlordiazepoxide (1–100 mg/kg), and pentobarbital (3.2–56 mg/kg) were studied in rats. Pharmacologically specific results were obtained rapidly and reliably, using a cumulative dosing procedure. Cluster analysis grouped the drug treatments, on the basis of their similarities in producing different behavioral activities, into three main clusters; characteristically, stimulant drugs (amphetamine, apomorphine) produced sniffing and gnawing; PCP-like drugs (PCP, ketamine) produced locomotion, sniffing, swaying and falling; sedative drugs (pentobarbital, chlordiazepoxide) produced loss of righting. The behavioral effects of ICV administration of AP5 were more similar to the effects of PCP-like drugs than to the effects of either stimulant or sedative drugs, thus supporting the hypothesis that the behavioral effects of PCP-like drugs may result from reduced neurotransmission at excitatory synapses utilizing NMDA preferring receptors. The present procedure is simple, rapid and may provide a useful approach in the classification of behaviorally active drugs.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46445/1/213_2004_Article_BF00518181.pd

Knowledge translation research in population health: establishing a collaborative research agenda

<p>Abstract</p> <p>Background</p> <p>Despite the increasing mobilization of researchers and funding organizations around knowledge translation (KT) in Canada and elsewhere, many questions have been only partially answered, particularly in the field of population health. This article presents the results of a systematic process to draw out possible avenues of collaboration for researchers, practitioners and decision-makers who work in the area of KT. The main objective was to establish a research agenda on knowledge translation in population health.</p> <p>Methods</p> <p>Using the Concept Mapping approach, the research team wanted to identify priority themes for the development of research on KT in population health. Mapping is based on multivariate statistical analyses (multidimensional scaling and hierarchical cluster analysis) in which statements produced during a brainstorming session are grouped in weighted clusters. The final maps are a visual representation of the priority themes of research on KT. Especially designed for facilitating consensus in the understanding and organization of various concepts, the Concept Mapping method proved suitable for achieving this objective.</p> <p>Results</p> <p>The maps were produced by 19 participants from university settings, and from institutions within the health and social services network. Three main perspectives emerge from this operation: (1) The evaluation of the effectiveness of KT efforts is one of the main research priorities; (2) The importance of taking into consideration user contexts in any KT effort; (3) The challenges related to sharing power for decision-making and action-taking among various stakeholder groups. These perspectives open up avenues of collaboration for stakeholders who are involved in research on KT. Besides these three main perspectives, the concept maps reveal three other trends which should be emphasized.</p> <p>Conclusion</p> <p>The Concept Mapping process reported in this article aimed to provoke collective reflection on the research questions that should be studied, in order to foster coherence in research activities in the field of population health. Based on this, it is appropriate to continue to support the development of research projects in KT and the formation of research teams in this field. Research on KT must lead to concrete outcomes within communities that are interested in the question.</p