RESUMEN
As population health has become a focus of health care payers and providers, interest has grown in mail, phone, and other forms of outreach for improving population rates of cancer screening. Translational research is needed to compare the effectiveness and cost of low- and high-intensity behavioral outreach interventions for promoting cancer screening. The purpose of the article is to compare the effectiveness in promoting biannual mammograms of three interventions delivered over 4 years to a primary care population with a high baseline mammography adherence of 83.3%. We randomized women aged 40-84 to reminder letter only (LO arm), letter + reminder call (RC arm), and two letters + counseling call (CC arm) involving tailored education and motivational interviewing. Mammography adherence (≥1 mammogram in the previous 24 months) at four time points was determined from insurance claims records. Over 4 years, 30,162 women were randomized. At the end of 4 years, adherence was highest in the RC arm (83.0%) compared with CC (80.8%) and LO (80.8%) arms (p = .03). Only 23.5% of women in the CC arm were reached and accepted full counseling. The incremental cost per additional mammogram for RC arm women was $30.45 over the LO arm cost. A simple reminder call can increase screening mammogram adherence even when baseline adherence is high. Some more complex behavioral interventions delivered by mail and phone as in this study may be less effective, due to limited participation of patients, a focus on ambivalence, lack of follow-up, and other factors.
Asunto(s)
Consejo , Detección Precoz del Cáncer , Mamografía , Sistemas Recordatorios , Adulto , Anciano , Anciano de 80 o más Años , Neoplasias de la Mama/diagnóstico , Neoplasias de la Mama/economía , Análisis Costo-Beneficio , Consejo/economía , Detección Precoz del Cáncer/economía , Detección Precoz del Cáncer/métodos , Femenino , Costos de la Atención en Salud , Humanos , Mamografía/economía , Mamografía/métodos , Persona de Mediana Edad , Cooperación del Paciente , Sistemas Recordatorios/economía , Telemedicina/economía , Telemedicina/métodos , Teléfono , Terapia Asistida por Computador/economía , Terapia Asistida por Computador/métodos , Resultado del TratamientoRESUMEN
Blood pH is an important indicator of anaerobic metabolism in exercising muscle. This paper demonstrates multivariate calibration techniques that can be used to produce a general pH model that can be applied to spectra from any new subject without significant prediction error. Tissue spectra (725 approximately 880 nm) were acquired through the skin overlying the flexor digitorum profundus muscle on the forearms of eight healthy subjects during repetitive hand-grip exercise and referenced to the pH of venous blood drawn from a catheter placed in a vein close to the muscle. Calibration models were developed using multi-subject partial least squares (PLS) and validated using subject-out cross-validation after the subject-to-subject spectral variations were corrected by mathematical preprocessing methods. A combination of standard normal variate (SNV) scaling and principal component analysis loading correction (PCALC) successfully removed most of the subject-to-subject variations and provided the most accurate prediction results.
Asunto(s)
Análisis Químico de la Sangre/métodos , Ejercicio Físico/fisiología , Adulto , Calibración , Interpretación Estadística de Datos , Femenino , Fuerza de la Mano/fisiología , Humanos , Concentración de Iones de Hidrógeno , Análisis de los Mínimos Cuadrados , Masculino , Análisis de Componente Principal , Espectroscopía Infrarroja CortaRESUMEN
A method to non-invasively and quantitatively measure muscle oxygen saturation (SmO(2)) using broadband continuous-wave diffuse reflectance near infrared (NIR) spectroscopy is presented. The method obtained SmO(2) by first correcting NIR spectra for absorption and scattering of skin pigment and fat, then fitting to a Taylor expansion attenuation model. A non-linear least squares optimization algorithm with set boundary constraints on the fitting parameters was used to fit the model to the acquired spectra. A data preprocessing/optimization scheme for accurately determining the initial values needed for the optimization was also employed. The method was evaluated on simulated muscle spectra with 4 different scattering properties, as well as on in vivo forearm spectra from 5 healthy volunteer subjects during arterial occlusion. Measurement repeatability was assessed on 24 healthy volunteers with 5 repeated measurements, each separated by at least 48 hours.
RESUMEN
This paper describes mathematical techniques to correct for analyte-irrelevant optical variability in tissue spectra by combining multiple preprocessing techniques to address variability in spectral properties of tissue overlying and within the muscle. A mathematical preprocessing method called principal component analysis (PCA) loading correction is discussed for removal of inter-subject, analyte-irrelevant variations in muscle scattering from continuous-wave diffuse reflectance near-infrared (NIR) spectra. The correction is completed by orthogonalizing spectra to a set of loading vectors of the principal components obtained from principal component analysis of spectra with the same analyte value, across different subjects in the calibration set. Once the loading vectors are obtained, no knowledge of analyte values is required for future spectral correction. The method was tested on tissue-like, three-layer phantoms using partial least squares (PLS) regression to predict the absorber concentration in the phantom muscle layer from the NIR spectra. Two other mathematical methods, short-distance correction to remove spectral interference from skin and fat layers and standard normal variate scaling, were also applied and/or combined with the proposed method prior to the PLS analysis. Each of the preprocessing methods improved model prediction and/or reduced model complexity. The combination of the three preprocessing methods provided the most accurate prediction results. We also performed a preliminary validation on in vivo human tissue spectra.
Asunto(s)
Grasas/química , Músculos/química , Piel/química , Espectroscopía Infrarroja Corta/métodos , Humanos , Concentración de Iones de Hidrógeno , Análisis de los Mínimos Cuadrados , Reconocimiento de Normas Patrones Automatizadas , Fantasmas de Imagen , Análisis de Componente PrincipalRESUMEN
We have demonstrated simultaneous correction for the optical interference of skin and fat in tissue spectra by using a two-distance fiber-optic probe. We obtained the correction by orthogonalizing the spectra collected at a long source-detector distance (SD) to the spectra collected at a short SD and mapped to the long SD space. The method was validated in tissuelike three-layer phantoms as well as preliminarily in human tissue. After the correction, a partial-least-squares model of the phantoms showed enhanced prediction performance.
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Tejido Adiposo/química , Algoritmos , Tecnología de Fibra Óptica/instrumentación , Músculo Esquelético/química , Pigmentación de la Piel/fisiología , Espectroscopía Infrarroja por Transformada de Fourier/instrumentación , Espectroscopía Infrarroja por Transformada de Fourier/métodos , Tejido Adiposo/fisiología , Artefactos , Diseño de Equipo , Análisis de Falla de Equipo , Tecnología de Fibra Óptica/métodos , Humanos , Músculo Esquelético/fisiología , Fibras Ópticas , Fantasmas de Imagen , Proyectos Piloto , TransductoresRESUMEN
The influence of fat thickness on the diffuse reflectance spectra of muscle in the near infrared (NIR) region is studied by Monte Carlo simulations of a two-layer structure and with phantom experiments. A polynomial relationship was established between the fat thickness and the detected diffuse reflectance. The influence of a range of optical coefficients (absorption and reduced scattering) for fat and muscle over the known range of human physiological values was also investigated. Subject-to-subject variation in the fat optical coefficients and thickness can be ignored if the fat thickness is less than 5 mm. A method was proposed to correct the fat thickness influence.
Asunto(s)
Tejido Adiposo/diagnóstico por imagen , Algoritmos , Rayos Infrarrojos , Método de Montecarlo , Músculos/diagnóstico por imagen , Simulación por Computador , Humanos , Modelos Biológicos , Fantasmas de Imagen , Radiografía , Espectrofotometría Infrarroja , Tomografía Óptica/métodosRESUMEN
The application of partial least squares (PLS) regression to visible-near-infrared (VIS-NIR) spectroscopy for modeling important blood and tissue parameters is generally complicated by the variation in skin pigmentation (melanin) across the human population. An orthogonal correction method for removing the influence of skin pigmentation has been demonstrated in diffuse reflectance spectra from two-layer tissue-mimicking phantoms. The absorption properties of the phantoms were defined by lyophilized human hemoglobin (bottom layer) and synthetic melanin (top layer). Tissue-like scattering was simulated in both layers with intralipid. The approach uses principal components analysis (PCA) loading vectors from a separate set of phantom spectra that encode the unwanted melanin variation to remove the effect of melanin from the test phantoms. The preprocessing of phantom spectra using this orthogonal correction method resulted in PLS models with reduced complexity and enhanced prediction performance. Preliminary results from a separate study that evaluates the feasibility of defining skin color variation in an experiment with a single human subject are also presented.