Quantitative antibiogram as a typing method for the prospective epidemiological surveillance and control of MRSA: comparison with molecular typing.

OBJECTIVE: Evaluation of the quantitative antibiogram as an epidemiological tool for the prospective typing of methicillin-resistant Staphylococcus aureus (MRSA), and comparison with ribotyping. METHODS: The method is based on the multivariate analysis of inhibition zone diameters of antibiotics in disk diffusion tests. Five antibiotics were used (erythromycin, clindamycin, cotrimoxazole, gentamicin, and ciprofloxacin). Ribotyping was performed using seven restriction enzymes (EcoRV, HindIII, KpnI, PstI, EcoRI, SfuI, and BamHI). SETTING: 1,000-bed tertiary university medical center. RESULTS: During a 1-year period, 31 patients were found to be infected or colonized with MRSA. Cluster analysis of antibiogram data showed nine distinct antibiotypes. Four antibiotypes were isolated from multiple patients (2, 4, 7, and 13, respectively). Five additional antibiotypes were isolated from the remaining five patients. When analyzed with respect to the epidemiological data, the method was found to be equivalent to ribotyping. Among 206 staff members who were screened, six were carriers of MRSA. Both typing methods identified concordant of MRSA types in staff members and in the patients under their care. CONCLUSIONS: The quantitative antibiogram was found to be equivalent to ribotyping as an epidemiological tool for typing of MRSA in our setting. Thus, this simple, rapid, and readily available method appears to be suitable for the prospective surveillance and control of MRSA for hospitals that do not have molecular typing facilities and in which MRSA isolates are not uniformly resistant or susceptible to the antibiotics tested.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

PET-measured responses of MBF to cold pressor testing correlate with indices of coronary vasomotion on quantitative coronary angiography.

The aims of this study were to determine whether responses in myocardial blood flow (MBF) to the cold pressor testing (CPT) method noninvasively with PET correlate with an established and validated index of flow-dependent coronary vasomotion on quantitative angiography. METHODS: Fifty-six patients (57 +/- 6 y; 16 with hypertension, 10 with hypercholesterolemia, 8 smokers, and 22 without coronary risk factors) with normal coronary angiograms were studied. Biplanar end-diastolic images of a selected proximal segment of the left anterior descending artery (LAD) (n = 27) or left circumflex artery (LCx) (n = 29) were evaluated with quantitative coronary angiography in order to determine the CPT-induced changes of epicardial luminal area (LA, mm(2)). Within 20 d of coronary angiography, MBF in the LAD, LCx, and right coronary artery territory was measured with (13)N-ammonia and PET at baseline and during CPT. RESULTS: CPT induced on both study days comparable percent changes in the rate x pressure product (%DeltaRPP, 37% +/- 13% and 40% +/- 17%; P = not significant [NS]). For the entire study group, the epicardial LA decreased from 5.07 +/- 1.02 to 4.88 +/- 1.04 mm(2) (DeltaLA, -0.20 +/- 0.89 mm(2)) or by -2.19% +/- 17%, while MBF in the corresponding epicardial vessel segment increased from 0.76 +/- 0.16 to 1.03 +/- 0.33 mL x min(-1) x g(-1) (DeltaMBF, 0.27 +/- 0.25 mL x min(-1) x g(-1)) or 36% +/- 31% (P <or= 0.0001). However, in normal controls without coronary risk factors (n = 22), the epicardial LA increased from 5.01 +/- 1.07 to 5.88 +/- 0.89 mm(2) (19.06% +/- 8.9%) and MBF increased from 0.77 +/- 0.16 to 1.34 +/- 0.34 mL x min(-1) x g(-1) (74.08% +/- 23.5%) during CPT, whereas patients with coronary risk factors (n = 34) revealed a decrease of epicardial LA from 5.13 +/- 1.48 to 4.24 +/- 1.12 mm(2) (-15.94% +/- 12.2%) and a diminished MBF increase (from 0.76 +/- 0.20 to 0.83 +/- 0.25 mL x min(-1) x g(-1) or 10.91% +/- 19.8%) as compared with controls (P < 0.0001, respectively), despite comparable changes in the RPP (P = NS). In addition, there was a significant correlation (r = 0.87; P <or= 0.0001) between CPT-related percent changes in LA on quantitative angiography and in MBF as measured with PET. CONCLUSION: The observed close correlation between an angiographically established parameter of flow-dependent and, most likely, endothelium-mediated coronary vasomotion and PET-measured MBF further supports the validity and value of MBF responses to CPT as a noninvasively available index of coronary circulatory function.

High-throughput SELEX SAGE method for quantitative modeling of transcription-factor binding sites.

The ability to determine the location and relative strength of all transcription-factor binding sites in a genome is important both for a comprehensive understanding of gene regulation and for effective promoter engineering in biotechnological applications. Here we present a bioinformatically driven experimental method to accurately define the DNA-binding sequence specificity of transcription factors. A generalized profile was used as a predictive quantitative model for binding sites, and its parameters were estimated from in vitro-selected ligands using standard hidden Markov model training algorithms. Computer simulations showed that several thousand low- to medium-affinity sequences are required to generate a profile of desired accuracy. To produce data on this scale, we applied high-throughput genomics methods to the biochemical problem addressed here. A method combining systematic evolution of ligands by exponential enrichment (SELEX) and serial analysis of gene expression (SAGE) protocols was coupled to an automated quality-controlled sequence extraction procedure based on Phred quality scores. This allowed the sequencing of a database of more than 10,000 potential DNA ligands for the CTF/NFI transcription factor. The resulting binding-site model defines the sequence specificity of this protein with a high degree of accuracy not achieved earlier and thereby makes it possible to identify previously unknown regulatory sequences in genomic DNA. A covariance analysis of the selected sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism.

Osteoporotic fracture risk in elderly women: estimation with quantitative heel US and clinical risk factors

PURPOSE: To derive a prediction rule by using prospectively obtained clinical and bone ultrasonographic (US) data to identify elderly women at risk for osteoporotic fractures. MATERIALS AND METHODS: The study was approved by the Swiss Ethics Committee. A prediction rule was computed by using data from a 3-year prospective multicenter study to assess the predictive value of heel-bone quantitative US in 6174 Swiss women aged 70-85 years. A quantitative US device to calculate the stiffness index at the heel was used. Baseline characteristics, known risk factors for osteoporosis and fall, and the quantitative US stiffness index were used to elaborate a predictive rule for osteoporotic fracture. Predictive values were determined by using a univariate Cox model and were adjusted with multivariate analysis. RESULTS: There were five risk factors for the incidence of osteoporotic fracture: older age (>75 years) (P < .001), low heel quantitative US stiffness index (<78%) (P < .001), history of fracture (P = .001), recent fall (P = .001), and a failed chair test (P = .029). The score points assigned to these risk factors were as follows: age, 2 (3 if age > 80 years); low quantitative US stiffness index, 5 (7.5 if stiffness index < 60%); history of fracture, 1; recent fall, 1.5; and failed chair test, 1. The cutoff value to obtain a high sensitivity (90%) was 4.5. With this cutoff, 1464 women were at lower risk (score, <4.5) and 4710 were at higher risk (score, >or=4.5) for fracture. Among the higher-risk women, 6.1% had an osteoporotic fracture, versus 1.8% of women at lower risk. Among the women who had a hip fracture, 90% were in the higher-risk group. CONCLUSION: A prediction rule obtained by using quantitative US stiffness index and four clinical risk factors helped discriminate, with high sensitivity, women at higher versus those at lower risk for osteoporotic fracture.

Bilateral Sequential NAION: A Comparison of Visual Outcomes in Fellow Eyes Using Quantitative Analysis of Goldmann Visual Fields

Purpose: Previous studies of the visual outcome in bilateral non-arteritic anterior ischemic optic neuropathy (NAION) have yielded conflicting results, specifically regarding congruity between fellow eyes. Prior studies have used measures of acuity and computerized perimetry but none has compared Goldmann visual field outcomes between fellow eyes. In order to better define the concordance of visual loss in this condition, we reviewed our cases of bilateral sequential NAION, including measures of visual acuity, pupillary function and both pattern and severity of visual field loss.Methods: We performed a retrospective chart review of 102 patients with a diagnosis of bilateral sequential NAION. Of the 102 patients, 86 were included in the study for analysis of final visual outcome between the affected eyes. Visual function was assessed using visual acuity, Goldmann visual fields, color vision and RAPD. A quantitative total visual field score and score per quadrant was analyzed for each eye using the numerical Goldmann visual field scoring method previously described by Esterman and colleagues. Based upon these scores, we calculated the total deviation and pattern deviation between fellow eyes and between eyes of different patients. Statistical significance was determined using nonparametric tests.Results: A statistically significant correlation was found between fellow eyes for multiple parameters, including logMAR visual acuity (P = 0.0101), global visual field (P = 0.0001), superior visual field (P = 0.0001), and inferior visual field (P = 0.0001). In addition, the mean deviation of both total (P = 0.0000000007) and pattern (P = 0.000000004) deviation analyses was significantly less between fellow eyes ("intra"-eyes) than between eyes of different patients ("inter"-eyes).Conclusions: Visual function between fellow eyes showed a fair to moderate correlation that was statistically significant. The pattern of vision loss was also more similar in fellow eyes than between eyes of different patients. These results may help allow better prediction of visual outcome for the second eye in patients with NAION. These findings may also be useful for evaluating efficacy of therapeutic interventions.

Viscoelasticity in Achilles Tendonopathy: Quantitative Assessment by Using Real-time Shear-Wave Elastography.

Purpose To investigate the differences in viscoelastic properties between normal and pathologic Achilles tendons ( AT Achilles tendon s) by using real-time shear-wave elastography ( SWE shear-wave elastography ). Materials and Methods The institutional review board approved this study, and written informed consent was obtained from 25 symptomatic patients and 80 volunteers. One hundred eighty ultrasonographic (US) and SWE shear-wave elastography studies of AT Achilles tendon s without tendonopathy and 30 studies of the middle portion of the AT Achilles tendon in patients with tendonopathy were assessed prospectively. Each study included data sets acquired at B-mode US (tendon morphology and cross-sectional area) and SWE shear-wave elastography (axial and sagittal mean velocity and relative anisotropic coefficient) for two passively mobilized ankle positions. The presence of AT Achilles tendon tears at B-mode US and signal-void areas at SWE shear-wave elastography were noted. Results Significantly lower mean velocity was shown in tendons with tendonopathy than in normal tendons in the relaxed position at axial SWE shear-wave elastography (P < .001) and in the stretched position at sagittal (P < .001) and axial (P = .0026) SWE shear-wave elastography . Tendon softening was a sign of tendonopathy in relaxed AT Achilles tendon s when the mean velocity was less than or equal to 4.06 m · sec(-1) at axial SWE shear-wave elastography (sensitivity, 54.2%; 95% confidence interval [ CI confidence interval ]: 32.8, 74.4; specificity, 91.5%; 95% CI confidence interval : 86.3, 95.1) and less than or equal to 5.70 m · sec(-1) at sagittal SWE shear-wave elastography (sensitivity, 41.7%; 95% CI confidence interval : 22.1, 63.3; specificity, 81.8%; 95% CI confidence interval : 75.3, 87.2) and in stretched AT Achilles tendon s, when the mean velocity was less than or equal to 4.86 m · sec(-1) at axial SWE shear-wave elastography (sensitivity, 66.7%; 95% CI confidence interval : 44.7, 84.3; specificity, 75.6%; 95% CI confidence interval : 68.5, 81.7) and less than or equal to 14.58 m · sec(-1) at sagittal SWE shear-wave elastography (sensitivity, 58.3%; 95% CI confidence interval : 36.7, 77.9; specificity, 83.5%; 95% CI confidence interval : 77.2, 88.7). Anisotropic results were not significantly different between normal and pathologic AT Achilles tendon s. Six of six (100%) partial-thickness tears appeared as signal-void areas at SWE shear-wave elastography . Conclusion Whether the AT Achilles tendon was relaxed or stretched, SWE shear-wave elastography helped to confirm and quantify pathologic tendon softening in patients with tendonopathy in the midportion of the AT Achilles tendon and did not reveal modifications of viscoelastic anisotropy in the tendon. Tendon softening assessed by using SWE shear-wave elastography appeared to be highly specific, but sensitivity was relatively low. © RSNA, 2014.

Counterfactuals and causal inference: Methods and principles for social research

"Most quantitative empirical analyses are motivated by the desire to estimate the causal effect of an independent variable on a dependent variable. Although the randomized experiment is the most powerful design for this task, in most social science research done outside of psychology, experimental designs are infeasible. (Winship & Morgan, 1999, p. 659)." This quote from earlier work by Winship and Morgan, which was instrumental in setting the groundwork for their book, captures the essence of our review of Morgan and Winship's book: It is about causality in nonexperimental settings.

Direct in vitro comparison of six three-dimensional positive contrast methods for susceptibility marker imaging.

PURPOSE: To compare different techniques for positive contrast imaging of susceptibility markers with MRI for three-dimensional visualization. As several different techniques have been reported, the choice of the suitable method depends on its properties with regard to the amount of positive contrast and the desired background suppression, as well as other imaging constraints needed for a specific application. MATERIALS AND METHODS: Six different positive contrast techniques are investigated for their ability to image at 3 Tesla a single susceptibility marker in vitro. The white marker method (WM), susceptibility gradient mapping (SGM), inversion recovery with on-resonant water suppression (IRON), frequency selective excitation (FSX), fast low flip-angle positive contrast SSFP (FLAPS), and iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) were implemented and investigated. RESULTS: The different methods were compared with respect to the volume of positive contrast, the product of volume and signal intensity, imaging time, and the level of background suppression. Quantitative results are provided, and strengths and weaknesses of the different approaches are discussed. CONCLUSION: The appropriate choice of positive contrast imaging technique depends on the desired level of background suppression, acquisition speed, and robustness against artifacts, for which in vitro comparative data are now available.

A benchmark test for a quantitative assessment of simple neuron models

Several methods and algorithms have recently been proposed that allow for the systematic evaluation of simple neuron models from intracellular or extracellular recordings. Models built in this way generate good quantitative predictions of the future activity of neurons under temporally structured current injection. It is, however, difficult to compare the advantages of various models and algorithms since each model is designed for a different set of data. Here, we report about one of the first attempts to establish a benchmark test that permits a systematic comparison of methods and performances in predicting the activity of rat cortical pyramidal neurons. We present early submissions to the benchmark test and discuss implications for the design of future tests and simple neurons models

Combining bone resorption markers and heel quantitative ultrasound to discriminate between fracture cases and controls.

This nested case-control analysis of a Swiss ambulatory cohort of elderly women assessed the discriminatory power of urinary markers of bone resorption and heel quantitative ultrasound for non-vertebral fractures. The tests all discriminated between cases and controls, but combining the two strategies yielded no additional relevant information. INTRODUCTION: Data are limited regarding the combination of bone resorption markers and heel quantitative bone ultrasound (QUS) in the detection of women at risk for fracture. METHODS: In a nested case-control analysis, we studied 368 women (mean age 76.2 +/- 3.2 years), 195 with low-trauma non-vertebral fractures and 173 without, matched for age, BMI, medical center, and follow-up duration, from a prospective study designed to predict fractures. Urinary total pyridinolines (PYD) and deoxypyridinolines (DPD) were measured by high performance liquid chromatography. All women underwent bone evaluations using Achilles+ and Sahara heel QUS. RESULTS: Areas under the receiver operating-characteristic curve (AUC) for discriminative models of the fracture group, with 95% confidence intervals, were 0.62 (0.56-0.68) and 0.59 (0.53-0.65) for PYD and DPD, and 0.64 (0.58-0.69) and 0.65 (0.59-0.71) for Achilles+ and Sahara QUS, respectively. The combination of resorption markers and QUS added no significant discriminatory information to either measurement alone with an AUC of 0.66 (0.60-0.71) for Achilles+ with PYD and 0.68 (0.62-0.73) for Sahara with PYD. CONCLUSIONS: Urinary bone resorption markers and QUS are equally discriminatory between non-vertebral fracture patients and controls. However, the combination of bone resorption markers and QUS is not better than either test used alone.

High-resolution three-dimensional aortic magnetic resonance angiography and quantitative vessel wall characterization of different atherosclerotic stages in a rabbit model

PURPOSE: Atherosclerosis results in a considerable medical and socioeconomic impact on society. We sought to evaluate novel magnetic resonance imaging (MRI) angiography and vessel wall sequences to visualize and quantify different morphologic stages of atherosclerosis in a Watanabe hereditary hyperlipidemic (WHHL) rabbit model. MATERIAL AND METHODS: Aortic 3D steady-state free precession angiography and subrenal aortic 3D black-blood fast spin-echo vessel wall imaging pre- and post-Gadolinium (Gd) was performed in 14 WHHL rabbits (3 normal, 6 high-cholesterol diet, and 5 high-cholesterol diet plus endothelial denudation) on a commercial 1.5 T MR system. Angiographic lumen diameter, vessel wall thickness, signal-/contrast-to-noise analysis, total vessel area, lumen area, and vessel wall area were analyzed semiautomatically. RESULTS: Pre-Gd, both lumen and wall dimensions (total vessel area, lumen area, vessel wall area) of group 2 + 3 were significantly increased when compared with those of group 1 (all P < 0.01). Group 3 animals had significantly thicker vessel walls than groups 1 and 2 (P < 0.01), whereas angiographic lumen diameter was comparable among all groups. Post-Gd, only diseased animals of groups 2 + 3 showed a significant (>100%) signal-to-noise ratio and contrast-to-noise increase. CONCLUSIONS: A combination of novel 3D magnetic resonance angiography and high-resolution 3D vessel wall MRI enabled quantitative characterization of various atherosclerotic stages including positive arterial remodeling and Gd uptake in a WHHL rabbit model using a commercially available 1.5 T MRI system.

FastEpistasis: a high performance computing solution for quantitative trait epistasis.

Motivation: Genome-wide association studies have become widely used tools to study effects of genetic variants on complex diseases. While it is of great interest to extend existing analysis methods by considering interaction effects between pairs of loci, the large number of possible tests presents a significant computational challenge. The number of computations is further multiplied in the study of gene expression quantitative trait mapping, in which tests are performed for thousands of gene phenotypes simultaneously. Results: We present FastEpistasis, an efficient parallel solution extending the PLINK epistasis module, designed to test for epistasis effects when analyzing continuous phenotypes. Our results show that the algorithm scales with the number of processors and offers a reduction in computation time when several phenotypes are analyzed simultaneously. FastEpistasis is capable of testing the association of a continuous trait with all single nucleotide polymorphism ( SNP) pairs from 500 000 SNPs, totaling 125 billion tests, in a population of 5000 individuals in 29, 4 or 0.5 days using 8, 64 or 512 processors.

Ensemble methods for environmental data modelling with support vector regression

This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

Combining clinical factors and quantitative ultrasound improves the detection of women both at low and high risk for hip fracture.

We hypothesized that combining clinical risk factors (CRF) with the heel stiffness index (SI) measured via quantitative ultrasound (QUS) would improve the detection of women both at low and high risk for hip fracture. Categorizing women by risk score improved the specificity of detection to 42.4%, versus 33.8% using CRF alone and 38.4% using the SI alone. This combined CRF-SI score could be used wherever and whenever DXA is not readily accessible. INTRODUCTION AND HYPOTHESIS: Several strategies have been proposed to identify women at high risk for osteoporosis-related fractures; we wanted to investigate whether combining clinical risk factors (CRF) and heel QUS parameters could provide a more accurate tool to identify women at both low and high risk for hip fracture than either CRF or QUS alone. METHODS: We pooled two Caucasian cohorts, EPIDOS and SEMOF, into a large database named "EPISEM", in which 12,064 women, 70 to 100 years old, were analyzed. Amongst all the CRF available in EPISEM, we used only the ones which were statistically significant in a Cox multivariate model. Then, we constructed a risk score, by combining the QUS-derived heel stiffness index (SI) and the following seven CRF: patient age, body mass index (BMI), fracture history, fall history, diabetes history, chair-test results, and past estrogen treatment. RESULTS: Using the composite SI-CRF score, 42% of the women who did not report a hip fracture were found to be at low risk at baseline, and 57% of those who subsequently sustained a fracture were at high risk. Using the SI alone, corresponding percentages were 38% and 52%; using CRF alone, 34% and 53%. The number of subjects in the intermediate group was reduced from 5,400 (including 112 hip fractures) and 5,032 (including 111 hip fractures) to 4,549 (including 100 including fractures) for the CRF and QUS alone versus the combination score. CONCLUSIONS: Combining clinical risk factors to heel bone ultrasound appears to correctly identify more women at low risk for hip fracture than either the stiffness index or the CRF alone; it improves the detection of women both at low and high risk.