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1.
BMC Nephrol ; 19(1): 13, 2018 01 15.
Artigo em Inglês | MEDLINE | ID: mdl-29334900

RESUMO

BACKGROUND: The Reducing Disparities in Access to kidNey Transplantation Community Study (RaDIANT) was an End-Stage Renal Disease (ESRD) Network 6-developed, dialysis facility-level randomized trial testing the effectiveness of a 1-year multicomponent education and quality improvement intervention in increasing referral for kidney transplant evaluation among selected Georgia dialysis facilities. METHODS: To assess implementation of the RaDIANT intervention, we conducted a process evaluation at the conclusion of the intervention period (January-December 2014). We administered a 20-item survey to the staff involved with transplant education in 67 dialysis facilities randomized to participate in intervention activities. Survey items assessed facility participation in the intervention (fidelity and reach), helpfulness and willingness to continue intervention activities (sustainability), suggestions for improving intervention components (sustainability), and factors that may have influenced participation and study outcomes (context). We defined high fidelity to the intervention as completing 11 or more activities, and high participation in an activity as having at least 75% participation across intervention facilities. RESULTS: Staff from 65 of the 67 dialysis facilities completed the questionnaire, and more than half (50.8%) reported high adherence (fidelity) to RaDIANT intervention requirements. Nearly two-thirds (63.1%) of facilities reported that RaDIANT intervention activities were helpful or very helpful, with 90.8% of facilities willing to continue at least one intervention component beyond the study period. Intervention components with high participation emphasized staff and patient-level education, including in-service staff orientations, patient and family education programs, and patient educational materials. Suggested improvements for intervention activities emphasized addressing financial barriers to transplantation, with financial education materials perceived as most helpful among RaDIANT educational materials. Variation in facility-level fidelity of the RADIANT intervention did not significantly influence the mean difference in proportion of patients referred pre- (2013) and post-intervention (2014). CONCLUSIONS: We found high fidelity to the RaDIANT multicomponent intervention at the majority of intervention facilities, with sustainability of select intervention components at intervention facilities and feasibility for dissemination across ESRD Networks. Future modification of the intervention should emphasize financial education regarding kidney transplantation and amend intervention components that facilities perceive as time-intensive or non-sustainable. TRIAL REGISTRATION: Clinicaltrials.gov number NCT02092727 . Registered 13 Mar 2014 (retrospectively registered).


Assuntos
Instituições de Assistência Ambulatorial/normas , Disparidades em Assistência à Saúde/normas , Falência Renal Crônica/terapia , Transplante de Rim/normas , Encaminhamento e Consulta/normas , Diálise Renal/normas , Idoso , Instituições de Assistência Ambulatorial/tendências , Serviços de Saúde Comunitária/normas , Serviços de Saúde Comunitária/tendências , Feminino , Pessoal de Saúde/normas , Pessoal de Saúde/tendências , Disparidades em Assistência à Saúde/tendências , Humanos , Falência Renal Crônica/diagnóstico , Falência Renal Crônica/epidemiologia , Transplante de Rim/tendências , Masculino , Pessoa de Meia-Idade , Encaminhamento e Consulta/tendências , Diálise Renal/tendências
2.
Appl Math (Prague) ; 56(6): 533-541, 2011 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-24843228

RESUMO

Convergence of the ensemble Kalman filter in the limit for large ensembles to the Kalman filter is proved. In each step of the filter, convergence of the ensemble sample covariance follows from a weak law of large numbers for exchangeable random variables, the continuous mapping theorem gives convergence in probability of the ensemble members, and Lp bounds on the ensemble then give Lp convergence.

3.
Ann Biomed Eng ; 42(4): 833-42, 2014 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-24370942

RESUMO

In vivo measurement of lumbar spine configuration is useful for constructing quantitative biomechanical models. Positional magnetic resonance imaging (MRI) accommodates a larger range of movement in most joints than conventional MRI and does not require a supine position. However, this is achieved at the expense of image resolution and contrast. As a result, quantitative research using positional MRI has required long reconstruction times and is sensitive to incorrectly identifying the vertebral boundary due to low contrast between bone and surrounding tissue in the images. We present a semi-automated method used to obtain digitized reconstructions of lumbar vertebrae in any posture of interest. This method combines a high-resolution reference scan with a low-resolution postural scan to provide a detailed and accurate representation of the vertebrae in the posture of interest. Compared to a criterion standard, translational reconstruction error ranged from 0.7 to 1.6 mm and rotational reconstruction error ranged from 0.3 to 2.6°. Intraclass correlation coefficients indicated high interrater reliability for measurements within the imaging plane (ICC 0.97-0.99). Computational efficiency indicates that this method may be used to compile data sets large enough to account for population variance, and potentially expand the use of positional MRI as a quantitative biomechanics research tool.


Assuntos
Vértebras Lombares/anatomia & histologia , Imageamento por Ressonância Magnética/métodos , Postura , Adulto , Animais , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Vértebras Lombares/fisiologia , Masculino , Ovinos , Adulto Jovem
4.
Spat Spatiotemporal Epidemiol ; 10: 39-48, 2014 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-25113590

RESUMO

We present a preliminary test of the Ensemble Optimal Statistical Interpolation (EnOSI) method for the statistical tracking of an emerging epidemic, with a comparison to its popular relative for Bayesian data assimilation, the Ensemble Kalman Filter (EnKF). The spatial data for this test was generated by a spatial susceptible-infectious-removed (S-I-R) epidemic model of an airborne infectious disease. Both tracking methods in this test employed Poisson rather than Gaussian noise, so as to handle epidemic data more accurately. The EnOSI and EnKF tracking methods worked well on the main body of the simulated spatial epidemic, but the EnOSI was able to detect and track a distant secondary focus of infection that the EnKF missed entirely.


Assuntos
Doenças Transmissíveis Emergentes/epidemiologia , Monitoramento Ambiental/estatística & dados numéricos , Epidemias , Análise Espacial , Teorema de Bayes , Doenças Transmissíveis Emergentes/prevenção & controle , Saúde Global , Humanos
5.
Procedia Comput Sci ; 1(1): 1221-1229, 2010 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-21031155

RESUMO

The FFT EnKF data assimilation method is proposed and applied to a stochastic cell simulation of an epidemic, based on the S-I-R spread model. The FFT EnKF combines spatial statistics and ensemble filtering methodologies into a localized and computationally inexpensive version of EnKF with a very small ensemble, and it is further combined with the morphing EnKF to assimilate changes in the position of the epidemic.

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