ライフサイエンスコーパス: DXA

1 DXA BMD measurements were significantly associated (P <

2 DXA data were available for 129, 121 and 107 patients at

3 DXA has not been fully validated for use in South Asians

4 DXA may estimate a higher prevalence of peripheral lipoa

5 DXA measures did not correlate significantly with biliar

6 DXA measures of abdominal fat are suitable for use in In

7 DXA measures of change in lean mass were modestly associ

8 DXA modeling showed no significant differences in predic

9 DXA should be performed in men aged >/=50 years, postmen

10 DXA thigh lean mass was compared to MRI mid-thigh MV, an

11 DXA thus provides an important opportunity for quantifyi

12 DXA was performed on participants aged >5 years (with na

13 DXA was used to determine BMD of the radius, lumbar spin

14 DXA-volume and ADP-volume measures were highly correlate

15 ear interval, was 7.5%; no screening, 11.1%; DXA screening, 9%; for wrist fractures, 14%, 17.8%, and

16 I z score (0.12 higher; 95% CI: 0.01, 0.23), DXA lean mass index (1.34% higher; 95% CI: -0.07%, 2.78%

17 Thus the enhanced extraction of 3-DXA under MAE was due to their structural stability, alo

18 ve stability and extractability of sorghum 3-DXA vs anthocyanins from maize and cowpea under microwav

19 MAE increased sorghum 3-DXA yield 100% versus control (3100 vs 1520 mg/g).

20 The 3-DXA remained structurally stable to MAE conditions up to

21 In models that contained all 4 DXA measures, the OR (95% confidence interval [CI]) for

22 n their remaining life (no screening, 18.7%; DXA screening, 15.8%).

23 error of overweight or obesity (defined as a DXA-measured body fat percentage at the 85(th) percentil

24 hod to measure total body protein by using a DXA system and BIA unit was developed and compared with

25 included Dual-emission X-ray absorbtiometry (DXA)-measured percent changes in spine and hip BMD at we

26 with FM by dual-energy X-ray absorptiometry (DXA) 2 wk postpartum.

27 Dual-energy X-ray absorptiometry (DXA) analysis was performed in children with intrahepati

28 d by using dual-energy X-ray absorptiometry (DXA) and anthropometric measures.

29 n by using dual-energy X-ray absorptiometry (DXA) and bioimpedance analysis (BIA).

30 easured by dual-energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI), but no such s

31 lopment of dual-energy x-ray absorptiometry (DXA) and quantitative computed tomography (QCT), which a

32 density (BMD) by Dual X-Ray Absorptiometry (DXA) and repeated after 12 weeks of regulated physical t

33 erence and Dual-energy X-ray absorptiometry (DXA) assessed fat mass), and logistic regression was use

34 se of only dual-energy X-ray absorptiometry (DXA) attenuation values for use in Lohman's 4C body comp

35 age 15 yr dual-energy x-ray absorptiometry (DXA) bone outcomes (whole body, lumbar spine, and hip),

36 nderwent a dual-energy X-ray absorptiometry (DXA) bone scan.

37 Dual energy X-ray absorptiometry (DXA) can be used to determine abdominal fat depots, bein

38 Dual-energy x-ray absorptiometry (DXA) can provide accurate measurements of body compositi

39 ation with dual-energy X-ray absorptiometry (DXA) derived body-fat distribution traits.

40 Dual-energy X-ray absorptiometry (DXA) derived measures of lean mass demonstrate strong as

41 undergone dual-energy x-ray absorptiometry (DXA) during the previous 12 months.

42 maging and dual-energy X-ray absorptiometry (DXA) estimates of evaluated components in adults (total

43 icknesses, dual-energy X-ray absorptiometry (DXA) fat mass, DXA lean mass, height z score, and IGF-I

44 tential of dual-energy X-ray absorptiometry (DXA) for measuring total-body SM in pediatric subjects.

45 Dual-energy x-ray absorptiometry (DXA) for visceral adipose tissue (VAT) assessment is use

46 rs apart) and hip dual x-ray absorptiometry (DXA) had been performed (2 years after baseline) were in

47 alysis and dual-energy x-ray absorptiometry (DXA) in 136 women (age range, 43-92 years), each of whom

48 ds such as dual-energy X-ray absorptiometry (DXA) in children.

49 (aBMD) by dual-energy X-ray absorptiometry (DXA) in midchildhood.

50 cal use of dual-energy X-ray absorptiometry (DXA) in the diagnosis and treatment of osteoporosis and,

51 urement by dual-energy x-ray absorptiometry (DXA) is an internationally accepted standard-of-care scr

52 Although dual-energy X-ray absorptiometry (DXA) is considered the most accurate measure of adiposit

53 ation with dual-energy x-ray absorptiometry (DXA) is cost-effective as a screening tool for osteoporo

54 ssessed by dual-energy x-ray absorptiometry (DXA) is the clinical standard for determining fracture r

55 y (BMD) by dual-energy x-ray absorptiometry (DXA) is the primary way to identify asymptomatic men who

56 Dual-energy X-ray absorptiometry (DXA) is widely used to assess body composition in resear

57 nthropometric and dual X-ray absorptiometry (DXA) measurements.

58 Recently, dual-energy X-ray absorptiometry (DXA) modeling of organ-tissue mass combined with specifi

59 asures and dual-energy X-ray absorptiometry (DXA) scan for body composition will be completed.

60 ged with a dual-energy x-ray absorptiometry (DXA) scanner, a clinical energy-integrating detector CT

61 e was analyzed by dual x-ray absorptiometry (DXA) scanning, and the trabecular and cortical bone volu

62 undergone dual-energy x-ray absorptiometry (DXA) scans for bone mass density assessment.

63 h multiple dual-energy X-ray absorptiometry (DXA) scans to measure changes in body energy stores.

64 Dual-energy x-ray absorptiometry (DXA) scans were performed before starting ADT and subseq

65 ssessed by dual energy x-ray absorptiometry (DXA) scans.

66 rived from dual-energy X-ray absorptiometry (DXA) scans.

67 Dual x-ray absorptiometry (DXA) was performed before treatment, and Z scores for th

68 Dual-energy x-ray absorptiometry (DXA) was used as the reference standard.

69 Dual-energy X-ray absorptiometry (DXA) was used for an assessment of bone mineral density

70 st composition by dual X-ray absorptiometry (DXA) were measured in daughters at Tanner B4.

71 easured by dual-energy X-ray absorptiometry (DXA) which were combined with energy intake measurements

72 tor CT and dual-energy x-ray absorptiometry (DXA) within 6 months of each other between 2000 and 2007

73 easured by dual-energy X-ray absorptiometry (DXA), abdominal computed tomography, and standard anthro

74 f birth by dual-energy x-ray absorptiometry (DXA), analysed in all randomly assigned neonates who had

75 y (BMD) by dual-energy x-ray absorptiometry (DXA), and BMD by quantitative computed tomography (QCT)

76 as measured using dual x-ray absorptiometry (DXA), and to assess their relationship to disease-relate

77 years with dual-energy x-ray absorptiometry (DXA), anthropometric, demographic, and prescription medi

78 ipants had dual-energy x-ray absorptiometry (DXA), entered a clinical BMD registry, and were followed

79 eling with dual energy x-ray absorptiometry (DXA), high-resolution peripheral quantitative computed t

80 We used dual-energy x-ray absorptiometry (DXA), high-resolution peripheral quantitative computed t

81 ), without dual-energy X-ray absorptiometry (DXA), in all HIV-infected men aged 40-49 years and HIV-i

82 lity using dual-energy X-ray absorptiometry (DXA), micro-computed tomography, Raman spectroscopy, and

83 easured by dual-energy x-ray absorptiometry (DXA), to increased serum alanine aminotransferase (ALT)

84 depots on dual-energy X-ray absorptiometry (DXA), whole-body MRI, and cardiac MRI.

85 f obesity, dual-energy X-ray absorptiometry (DXA)-derived visceral-fat-volume measurements, in a subs

86 as measured using dual x-ray absorptiometry (DXA).

87 easured by dual-energy X-ray absorptiometry (DXA).

88 mined with dual-energy x-ray absorptiometry (DXA).

89 d by using dual-energy X-ray absorptiometry (DXA).

90 sured with dual-energy x-ray absorptiometry (DXA).

91 measurement, and dual x-ray absorptiometry (DXA).

92 easured by dual-energy X-ray absorptiometry (DXA).

93 the use of dual-energy X-ray absorptiometry (DXA).

94 ody fat by dual energy x-ray absorptiometry (DXA); (4) liver and muscle insulin sensitivity (insulin

95 sured with dual-energy X-ray absorptiometry (DXA)] and energy expenditure [measured with doubly label

96 s (BMI and dual-energy X-ray absorptiometry [DXA] determined fat mass index [FMI]) in a MR approach.

97 Bone densities (dual x-ray absorptiometry [DXA]) were normal, low, or osteoporotic in 24%, 55%, and

98 diography, dual-energy x-ray absorptiometry [DXA], and quantitative computed tomography [CT]) and tha

99 s (central dual-energy x-ray absorptiometry [DXA], calcaneal quantitative ultrasonography [QUS], and

100 easured by dual energy X-ray absorptiometry, DXA) among girls (percentage of estimates that were <20%

101 mass (via dual-energy X-ray absorptiometry; DXA) and strength were determined.

102 ydroxy-9,11-dioxolane eicosatetraenoic acid (DXA(3)).

103 Anthropometrically adjusted DXA measures in ALGS correlate with markers of cholestas

104 A previously published adult DXA SM prediction formula was evaluated in children and

105 A previously reported adult DXA SM prediction model is applicable in children and ad

106 The adult DXA SM prediction model was valid in subjects at Tanner

107 Although DXA- and MRI-measured adipose tissue depots correlate st

108 In probabilistic sensitivity analysis, DXA and quantitative CT at age 55 years with quantitativ

109 Healthy adults underwent whole-body 3DO and DXA scans, blood tests, and strength assessments in the

110 ement between body fat estimation by ADP and DXA did not vary with race or sex.

111 ted for correlations with anthropometric and DXA measurements with Spearman rho and Pearson correlati

112 correlation between dual-energy CT-based and DXA-based BMD values, with a mean difference of 0.7441 a

113 tissue strongly correlate with clinical and DXA fat measurements.

114 , each of whom underwent CT colonography and DXA within a 6-month period (between January 2008 and Ap

115 from clinically indicated dual-energy CT and DXA examinations within 2 months, comprising the lumbar

116 Multidetector CT and DXA scans were acquired in 178 proximal femur specimens

117 load; however, combining quantitative CT and DXA yielded a performance as good as that attained with

118 iography and DXA and (b) quantitative CT and DXA, correlations with mechanical failure load increased

119 001) , respectively, for quantitative CT and DXA.

120 n BMD values derived from dual-energy CT and DXA.

121 Body mass index and DXA-derived body fat percentage were divided into quinti

122 les) who had >/=3 serum 25(OH)D measures and DXA data.

123 with ADP-volume percentage fat measures and DXA software-reported percentage fat measures (R(2) = 0.

124 change in size was compared between MRI and DXA.

125 By combining (a) radiography and DXA and (b) quantitative CT and DXA, correlations with m

126 P < .001), respectively, for radiography and DXA and to 0.80 (P < .001) and 0.86 (P < .001) , respect

127 orrelation was observed between uRBP/uCr and DXA T scores (lumbar [P = .03], femoral neck [P < .001],

128 se (%CV = 7.4 for males, 6.8 for females) as DXA (%CV = 6.8 for males, 7.4 for females).

129 At DXA, 39 (48%) of 81 patients with unreported vertebral b

130 fat distribution, such as total fat mass at DXA, visceral and subcutaneous adipose tissue, and liver

131 hile hip BMD did not change significantly at DXA.

132 approach correlates well with the available DXA measurements and has the potential for screening pat

133 gths, angles, and cortical thicknesses), (b) DXA (reference standard) to determine areal bone mineral

134 to determine the level of agreement between DXA and CT when assessing VAT area and volume among canc

135 proportional bias in the association between DXA and MRI (correlation between difference and mean -0.

136 Intra-class correlation coefficients between DXA and MRI measures of abdominal fat were high (0.98 fo

137 d from 0.73 to 0.82 for correlations between DXA BMC and FL (P < .001).

138 d from 0.77 to 0.80 for correlations between DXA BMD and FL and from 0.73 to 0.82 for correlations be

139 level of the individual, differences between DXA and MRI could be large (95% of DXA measures were bet

140 associated with greater differences between DXA and MRI measurements.

141 ody composition was assessed by a whole-body DXA scan.

142 ng body-composition software from whole-body DXA scans.

143 rwent abdominal and pelvis CT and whole-body DXA within 48 hours.

144 We measured areal BMD (aBMD) by DXA, and distal radius and tibia bone microstructure usi

145 veloped, several parameters were analyzed by DXA scanning and micro-CT.

146 during which changes in body composition (by DXA) and appetite (by visual analog scale appetite perce

147 able to identify osteoporosis (as defined by DXA), with 100% sensitivity in eight of eight patients (

148 line, 12-month areal bone mineral density by DXA did not change significantly at the spine and hip, b

149 vel-dependent MRI; fat mass was estimated by DXA; GFR and RPF were estimated by iohexol and p-aminohi

150 dicular lean soft tissue (ALST) estimates by DXA as the main predictor variable (eg, model 1, ALST al

151 Percentage fat by DXA volume was highly correlated with ADP-volume percent

152 ) of the lumbar spine and proximal femur (by DXA), liver function, and bone markers were measured at

153 and BC [fat mass (FM) and lean mass (LM) by DXA] were measured (n = 118).

154 erence was observed in trunk fat measured by DXA and MRI, but the difference was still statistically

155 Body composition was measured by DXA and REE was assessed by indirect calorimetry in 201

156 free mass (FFM), and weight were measured by DXA and the 4C model.

157 ody mass but decreased the % fat measured by DXA in the Control group.

158 cts, greater amounts of fat were measured by DXA than by MRI when control subjects were compared with

159 Bone mineral content measured by DXA, total body water by deuterium dilution, and total b

160 t, total fat, and lean mass were measured by DXA.

161 mbar spine, and femoral neck measurements by DXA.

162 fferences in organ-tissue mass as modeled by DXA.

163 classifications for clinical osteoporosis by DXA (T score </=-2.5 at the hip or spine), with 82.8% se

164 rence and mean -0.3), with overestimation by DXA greater in individuals with less abdominal fat (mean

165 the bottom decile of the control subjects by DXA than by MRI (P < 0.0001).

166 he effect of several genes common to central DXA-derived BMD and heel ultrasound/DXA measures and poi

167 Correlation was made with central DXA T scores.

168 to calculate TBV with the use of a clinical DXA system was developed, compared against ADP as proof

169 he most cost-effective strategy was combined DXA and quantitative CT screening starting at age 55 wit

170 We compared DXA- with MRI-measured trunk, leg, arm, and total fat in

171 er operating characteristic curves comparing DXA-scan prediction based on a 10% subset of the cohort

172 s from lowest to highest were 4-compartment, DXA, TBW(VRJ), 3-compartment, Db(VRJ), BIA, air displace

173 holds do not definitively exclude or confirm DXA-determined osteoporosis.

174 At least two consecutive DXA scans were required for this analysis.

175 ticipant and compared them with conventional DXA measures.

176 ic syndrome in comparison with corresponding DXA measurements.

177 The quantitative CT DXA combination may be easier to use in fracture predict

178 Sorghum derived 3-deoxyanthocyanin (DXA) pigments are stable relative to their anthocyanin a

179 n square deviation between the model and DLW/DXA method was 215 kcal/d, and most of the model-calcula

180 es of DeltaEI that are comparable to the DLW/DXA method can be obtained by using a mathematical model

181 y the model were within 40 kcal/d of the DLW/DXA method throughout the 2-y study.

182 aEI values were within 132 kcal/d of the DLW/DXA method.

183 d the DeltaEI values calculated by using DLW/DXA with those obtained by using a mathematical model of

184 TBV measures with the use of only DXA (DXA-volume) and ADP-volume measures were compared for ea

185 ury risk factors in separate models for each DXA measure.

186 Eight DXA area loci associate with osteoarthritis, including r

187 are highly correlated with CT VAT estimates, DXA estimates show substantial bias which indicates the

188 gh-spatial-resolution BMD data from existing DXA datasets without the limitations imposed by region o

189 Finally, DXA and regression modeling of REE suggests that increas

190 For DXA, the strongest correlation with mechanical failure l

191 n the animal phantom was 4.6 cGy . cm(2) for DXA, 3.5-11.5 cGy . cm(2) for energy-integrating detecto

192 DeltaBMD ranged from -5% to -1.8% for DXA, from -2.3% to -1.7% for energy-integrating detector

193 sought to reverse reimbursement declines for DXA services, whereas updated guidelines have attempted

194 ype of hospital regarding Hologic device for DXA scans, previous aromatase inhibitor use, and baselin

195 nding percentages of vertebral fractures for DXA and quantitative CT with a 5-year interval, was 7.5%

196 mated limb fat was substantially greater for DXA than for MRI for HIV+ and control men and women (all

197 bone mineral density can be substituted for DXA.

198 re used to develop a region of interest-free DXA analysis method with increased spatial resolution fo

199 commended which populations may benefit from DXA screening and the use of the fracture risk assessmen

200 (R(2) = 0.84) with DXA, did not differ from DXA (P = .15, paired t test), and was able to identify o

201 Percentage fat estimated from DXA showed the highest correlation with leptin (R(2) = 0

202 nd 0.17 kg/m(2) (95% CI: -0.02, 0.36) higher DXA total fat mass index in mid-childhood.

203 Hip DXA scans were assessed using the Hip Structural Analysi

204 hip, and hip geometry was extracted from hip DXA scans using the hip structural analysis method.

205 Hip morphology was quantified using hip DXA scans from the Avon Longitudinal Study of Parents an

206 ty of 81% and specificity of 68% to identify DXA-determined osteoporosis.

207 f 75% and specificity of 66% for identifying DXA-determined osteoporosis (DXA T-score, -2.5).

208 Oral bisphosphonate therapy was started if DXA hip T scores were less than or equal to -2.5, 10-yea

209 Decreases in DXA BMD were observed when aromatization was suppressed

210 regression model for predicting FL included DXA BMD and regional quantitative CT BMD measurements.

211 Instead, DXA and regression modeling of REE suggests that skeleta

212 tal n=411; organs=76) and the other a larger DXA database (n=1346) that included related estimates of

213 .4 times MRI measures), at the sample level, DXA only slightly overestimated MRI measures of abdomina

214 dolescents reporting stimulant use had lower DXA measurements of the lumbar spine and femur compared

215 -energy X-ray absorptiometry (DXA) fat mass, DXA lean mass, height z score, and IGF-I concentration.

216 man analysis revealed that in women and men, DXA VAT-area estimates were larger and smaller, respecti

217 DiEpHEDE, substituted for the previous name DXA(3) We found that in platelets, the lipid likely form

218 hort, and then additionally for femoral neck DXA aBMD or FRAX.

219 A new DXA SM prediction model was developed for prepubertal an

220 Non-DXA tests either are too insensitive or have insufficien

221 missions of updated guidelines for obtaining DXA testing may serve again to restrict initial access,

222 s between DXA and MRI could be large (95% of DXA measures were between 0.8 and 1.4 times MRI measures

223 this study was to determine the accuracy of DXA at detecting changes in lean mass, using MRI-derived

224 Here, we determined the accuracy of DXA for measurement of abdominal fat in an Indian popula

225 The accuracy of DXA-measured body-composition outcomes differed signific

226 Univariate associations of DXA with MRI were strongest for total and trunk fat (r >

227 The bias of DXA varies according to the sex, size, fatness, and dise

228 rescreening intervals, and a combination of DXA and quantitative CT with different intervals (3, 5,

229 The authors compared correlations of DXA measurements of total fat mass and fat mass percent

230 average risk), the post-test probability of DXA-determined osteoporosis was 34% (CI, 26% to 41%) aft

231 In a GWA study of DXA bone area of the hip and lumbar spine (N >= 28,954),

232 such as BMI and WC is comparable to that of DXA measurements of fat mass and fat mass percent, as ev

233 Serum specimens obtained at the time of DXA were analyzed for concentrations of RANKL and OPG, u

234 for race, body mass index (BMI), and type of DXA (Hologic/Lunar).

235 sidual mass) were calculated with the use of DXA modeling and body weight.

236 udies have compared the relative validity of DXA measures with anthropometric measures such as body m

237 mpared changes in weight and regional fat on DXA from baseline to week 48 between CYP2B6 metabolizer

238 TBV measures with the use of only DXA (DXA-volume) and ADP-volume measures were compared f

239 t and muscle) composition analysis by MRI or DXA.

240 for identifying DXA-determined osteoporosis (DXA T-score, -2.5).

241 antitative CT pixel distribution parameters, DXA BMD, and FL were correlated at multiple regression a

242 but it markedly overestimated levels of PBF(DXA) in children with large skinfold thicknesses.

243 >/= 50 mm, PBF(Slaughter) overestimated PBF(DXA) by 12 percentage points.

244 r) was highly correlated (r = 0.90) with PBF(DXA), but it markedly overestimated levels of PBF(DXA) i

245 Compared with postpartum DXA values, Deming regressions revealed no substantial d

246 The objectives were to predict DXA total and regional body composition, serum lipid and

247 to compare the accuracy of the Lunar Prodigy DXA for body-composition analysis with that of the refer

248 one mineral density (BMD) assessed by X-ray (DXA), may be convenient alternatives for evaluating oste

249 access, and the recent controversy of repeat DXA testing may make monitoring results of therapy more

250 e reflects the ongoing controversy of repeat DXA testing.

251 n of the method was examined by using repeat DXA acquisitions in 29 patients, and its ability to allo

252 re, 62 (52.1%) had nonosteoporotic T-scores (DXA false-negative results), and most (97%) had L1 or me

253 hree strategies were compared: no screening, DXA with T score-dependent rescreening intervals, and a

254 rly to track expected gains in BMD by serial DXA scans.

255 quisition of 4C body composition to a single DXA scan and TBW measure.

256 The strongest DXA area association is with rs11614913[T] in the microR

257 Unlike previous studies, DXA showed no post-transplant bone loss in either group;

258 ts were recruited to have 4C measures taken: DXA, air-displacement plethysmography (ADP), and total b

259 ith an emphasis on L1 measures (study test); DXA BMD measures (reference standard).

260 state of the subjects, which indicates that DXA is unreliable for patient case-control studies and f

261 The DXA-volume approach eliminates many of the inherent inac

262 CT systems were compared with those from the DXA scanner (the reference standard).

263 We also show that the DXA area measure contributes to the risk of hip fracture

264 Blinded to the DXA data, biomechanical CT analysis was retrospectively

265 aller with both CT systems compared with the DXA scanner (both P < .05).

266 Patient access to DXA scans has been threatened by declining reimbursement

267 3DO body composition accuracy to DXA was: fat mass R2 = 0.88 male, 0.93 female; visceral

268 central DXA-derived BMD and heel ultrasound/DXA measures and points to a new genetic locus with pote

269 revious fracture, and 47% had ever undergone DXA.

270 All subjects underwent DXA of spine, hip, and whole body to determine BMD and b

271 male subjects (29.2 +/- 9.5 years) underwent DXA and MRI scans before and after a 10-week resistance

272 es in the cholecalciferol group had a usable DXA scan and were analysed for the primary endpoint.

273 randomly assigned neonates who had a usable DXA scan.

274 one mineral density (BMD) was assessed using DXA.

275 iation of screening at age 55 years by using DXA -2.5 with rescreening every 5 years.

276 iation of screening at age 55 years by using DXA with a T-score threshold of -2.0 or less for treatme

277 ercentage of body fat were measured by using DXA, and waist circumference (WC) and BMI were assessed.

278 measured in 313 children at age 5 y by using DXA.

279 6/17 y, we determined body composition using DXA and quantified metabolic parameters in a blood sampl

280 Body composition was determined using DXA, and a BMI z-score was calculated.

281 one mineral density (BMD) was measured using DXA.

282 While there are several advantages to using DXA for the measurement of lean mass, the inability to a

283 Body composition was assessed via DXA.

284 metry, serum zinc, and body composition (via DXA).

285 tio (ICER) of less than $50,000 per QALY was DXA screening with a T-score threshold of -2.5 or less f

286 It is unknown whether DXA is comparable to CT among cancer survivors, especial

287 set of rash or weakness to the time at which DXA was performed.

288 Overall, while DXA VAT estimates are highly correlated with CT VAT esti

289 sis was highly correlated (R(2) = 0.84) with DXA, did not differ from DXA (P = .15, paired t test), a

290 found for ADP (Siri equation) compared with DXA for all subjects examined together, and agreement be

291 Compared with DXA, there appears to be no noninvasive and simple metho

292 etric models and precision was compared with DXA.

293 All methods were highly correlated with DXA (P < 0.001).

294 3%; 95% CI: 17%, 29%) highly correlated with DXA abdominal fat measurements (mean, 26%; 95% CI: 21%,

295 S results showed a moderate correlation with DXA outputs.

296 Mean BMD of L1-L4 determined with DXA was 0.995 g/cm(2), and 18 patients (45%) showed an o

297 44% to 70%) for identifying individuals with DXA T-scores of -2.5 or less at the hip or spine.

298 Compared with EI measured with DXA and DLW, the model errors were -71 +/- 272 kcal/d an

299 er at all vertebral levels for patients with DXA-defined osteoporosis (P < 0.001).

300 ne with all women with a baseline and 3 year DXA assessment) was the effect of risedronate versus pla