ライフサイエンスコーパス: negative predictive value

1 specificity, positive predictive value, and negative predictive value.

2 city, 94% positive predictive value, and 94% negative predictive value.

3 tive in over 90% of cases and carries a high negative predictive value.

4 a 93% positive predictive value, and an 88% negative predictive value.

5 city, 17% positive predictive value, and 95% negative predictive value.

6 city, 66% positive predictive value, and 91% negative predictive value.

7 did not significantly affect sensitivity or negative predictive values.

8 effective and cost-saving method, with high negative predictive values.

9 nt recipients with greater than 95% positive/negative predictive values.

10 quadrant demonstrated the best positive and negative predictive values.

11 d a model score threshold demonstrating high negative predictive value (0.95) for death.

12 er sensitivity (100% versus 70%, P<0.05) and negative predictive value (100% versus 89%, P<0.05) than

13 ), specificity (91%), and positive (93%) and negative predictive value (100%) for ISH positivity.

14 k stigmata, had a higher sensitivity (100%), negative predictive value (100%), and accuracy (66%) for

15 = 97.4%, positive predictive value = 93.3%, negative predictive value = 100%).

16 RMCCs were sensitive (100%; negative predictive value, 100%) for VT recurrence but t

17 ity=100%, positive predictive value=93%, and negative predictive value=100%).

18 ositive predictive value (83-86%) but a poor negative predictive value (50-55%) to detect the presenc

19 specificity was 76.3%, and the positive and negative predictive values 62.2% and 95.7%, respectively

20 7.5 min: sensitivity, 73%; specificity, 67%; negative predictive value, 67%; positive predictive valu

21 of diagnostic sensitivity, specificity, and negative predictive values (70% to 100%) but low positiv

22 7% and 77.5%, respectively) and positive and negative predictive values (74.7% and 78.5%, respectivel

23 > 2.46: sensitivity, 82%; specificity, 89%; negative predictive value, 80%; positive predictive valu

24 90.5%, positive predictive value 99.1%, and negative predictive value 86.4%.

25 to achieve an objective response by RECIST (negative predictive value, 91% [95% CI, 74% to 100%] for

26 1.23, 1.22, and 1.05, respectively; P<0.05; negative predictive value 92%).

27 ision ruling out sc-TCMR (specificity = 70%, negative predictive value = 92.5%), but could not predic

28 64 [95% CI, 0.61-0.67], respectively; 1-year negative predictive values, 92% [95% CI, 91%-93%] and 91

29 plasma CXCL8 in healthy individuals found a negative predictive value 93.5%, given the population pr

30 e <37 mL/m(2) and strain >23.4% yielded high negative predictive value (93% and 98%, respectively) fo

31 ty, 95.5%; positive predictive value, 66.7%; negative predictive value, 94.1%).

32 d 100% sensitivity (95% CI, 94-100) and 100% negative predictive value (95% CI, 79-100); regional cer

33 5), 72% specificity (95% CI, 65-79), and 98% negative predictive value (95% CI, 93-100) for cerebral

34 e value (76.7% and 69.2%, respectively), and negative predictive value (95.0% and 99.6%, respectively

35 elihood ratio, positive predictive value and negative predictive values (95% confidence interval): ur

36 differences in sensitivity (83% vs. 70%) or negative predictive values (96% vs. 92%).

37 urve of 0.91 (95% CI: 0.86, 0.96) and a high negative predictive value (97%; 95% CI: 93%, 99%).

38 ictive value, 61% and 88%, respectively; and negative predictive value, 97% and 97%, respectively.

39 ely, missing 18 index and two 30-day events (negative predictive value, 97.9%; 95% confidence interva

40 airment as low risk for the primary outcome (negative predictive value, 98.4%; 95% confidence interva

41 cificity 93%; positive predictive value 90%; negative predictive value 99%) and lasted 1 single cycle

42 e value (40%) but high specificity (94%) and negative predictive value (99%) for ISH positivity.

43 igh sensitivity (97%), specificity (79%) and negative predictive value (99%) to render it useful for

44 tive predictive value (85.8-91.3), and 99.9% negative predictive value (99.9-100.0) in the validation

45 ours, missing 2 index and two 30-day events (negative predictive value, 99.5%; 95% confidence interva

46 pairment (P<0.001) with similar performance (negative predictive value, 99.7%; 95% CI, 99.4%-99.9%; s

47 edictive value) and sNGAL (>/=179 ng/mL; 93% negative predictive value and 20% positive predictive va

48 hours for both urine NGAL (>/=20 ng/mL; 97% negative predictive value and 27% positive predictive va

49 The negative predictive value and accuracy were 59% and 68.8

50 The negative predictive value and sensitivity of troponin co

51 prior expertise in NBI were able to meet the negative predictive value and surveillance interval thre

52 The positive and negative predictive values and the accuracy of visual an

53 vs. 57%positive predictive value, 95% vs. 94%negative predictive value, and 0.87 vs. 0.82 area under

54 city, a 97% positive predictive value, a 42% negative predictive value, and 72% accuracy.

55 Positive predictive value, negative predictive value, and accuracy of fully automat

56 ity, specificity, positive predictive value, negative predictive value, and accuracy of the Hopkins s

57 ity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of 71

58 cificity, 44% positive predictive value, 80% negative predictive value, and likelihood ratio 1.54 to

59 ity, specificity, positive predictive value, negative predictive value, and likelihood ratio of every

60 Sensitivity, specificity, positive and negative predictive value, and positive and negative lik

61 l TM) had a better sensitivity, specificity, negative predictive value, and positive predictive value

62 Sensitivity, specificity, negative predictive value, and positive predictive value

63 old value was used to determine positive and negative predictive values, and a full logistic regressi

64 ss upgrade and downgrade rates, positive and negative predictive values, and positive and negative li

65 We analyze their development, positive- and negative-predictive values, and ability to predict respo

66 exercise E/e' data improves sensitivity and negative predictive value but compromises specificity, s

67 o>14) improved sensitivity (to 90%) and thus negative predictive value, but decreased specificity (71

68 specificity, positive predictive value, and negative predictive value for (18)F-FDG PET/CT were 82%,

69 characterized with high confidence, a >/=90% negative predictive value for adenomas in the rectosigmo

70 n had 100% positive predictive value and 87% negative predictive value for airway mucosal CCL26-high

71 Specificity and negative predictive value for AL with PCT less than 2.7

72 PCT and CRP demonstrated to have a good negative predictive value for AL, both in 3rd and in 5th

73 factor was of moderate sensitivity, but high negative predictive value for all ages.

74 specificity, positive predictive value, and negative predictive value for an FFR of </=0.8 were 91.4

75 runs yielded a success rate of 92%, and the negative predictive value for both the influenza A and B

76 , 82.4% positive predictive value, and 83.3% negative predictive value for cellulitis diagnosis.

77 gative likelihood ratio and the positive and negative predictive value for detection of prostate canc

78 The overall negative predictive value for high-confidence characteri

79 ctive value for K103N (100%) and the highest negative predictive value for M184V (97.5%).

80 specificity, positive predictive value, and negative predictive value for NLP algorithm in predictin

81 sensitivity, positive predictive value, and negative predictive value for OC/FTC detection within 1

82 specificity, positive predictive value, and negative predictive value for PLC injuries were 55% (11

83 tivity to first-line platinum therapy (94.3% negative predictive value for progression < 6 months).

84 specificity, positive predictive value, and negative predictive value for separating MPNSTs from BNF

85 hen both parameters exceeded thresholds, the negative predictive value for survival above 1 y was 79%

86 specificity, positive predictive value, and negative predictive value for the first step were estima

87 have 95% positive predictive value (PPV) or negative predictive value for the persistence or resolut

88 specificity, positive predictive value, and negative predictive value for the Qiagen artus C. diffic

89 Positive and negative predictive values for ABMR at a cutoff of 1.0%

90 Positive and negative predictive values for active rejection at a cut

91 All PFPs exhibited high specificity and negative predictive values for identifying frailty syndr

92 Sensitivity, specificity, and positive and negative predictive values for malignant tumors of the c

93 e sensitivity, specificity, and positive and negative predictive values for the index TKA and revisio

94 TB groups was reflected in poor positive and negative predictive values for treatment failure.

95 The positive and negative predictive values for unauthorised leave were 5

96 e sensitivity, specificity, and positive and negative predictive values for WGS in predicting AMR wer

97 The 3 types of specimens had similar negative predictive value >99% and sensitivity >83%.

98 n, an sFlt-1:PlGF ratio of 38 or lower had a negative predictive value (i.e., no preeclampsia in the

99 The saEPI was associated with a high negative predictive value in both groups.

100 an adjunct to US to improve sensitivity and negative predictive value in breast cancer diagnosis.

101 dictive value in phase 1 (64.0%) and highest negative predictive value in phase 2 (90.2%).

102 Negative predictive values in both analyses were higher

103 C statistics and negative predictive values indicate that the CHA2DS2-VAS

104 0.98, positive predictive value (PPV) 0.87, negative predictive value (NPV) 0.90, and accuracy (Acc)

105 pecificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy

106 The positive predictive value (PPV) and negative predictive value (NPV) for each code of interes

107 nt (ED) have been shown to have an excellent negative predictive value (NPV) for the identification o

108 87%-95%, sensitivity of 32%-55% and 50%-67%, negative predictive value (NPV) of 88%-91% and 86%-89%,

109 ive value (PPV) of 93.3% (86.8 to 97.3), and negative predictive value (NPV) of 97.2% (96.0 to 98.2).

110 itive predictive value (PPV) of 74.0%, and a negative predictive value (NPV) of 97.5%.

111 tive [AFB(-)] sputum), specificity of 99.2%, negative predictive value (NPV) of 97.6%, and positive p

112 ificity of 20.8% (95% CI 19.2%-22.4%), and a negative predictive value (NPV) of 99.8% (95% CI 98.9%-1

113 The primary outcome measure was the negative predictive value (NPV) of FDG-PET/CT scans and

114 ficity, positive predictive value (PPV), and negative predictive value (NPV) of MALDI-TOF MS alone an

115 ficity, positive predictive value (PPV), and negative predictive value (NPV) of MRI-based T-staging w

116 ficity, positive predictive value (PPV), and negative predictive value (NPV) of RDTs were 51.7%, 94.1

117 ated the positive predictive value (PPV) and negative predictive value (NPV) of ST for anaphylaxis re

118 ecificity was 0.94 (95% CI: 0.77, 0.99), the negative predictive value (NPV) was 0.92 (95% CI: 0.75,

119 No difference in negative predictive value (NPV) was found between FLT PE

120 In group 2, the sensitivity and negative predictive value (NPV) were 100 % and 100 % for

121 ficity, positive predictive value (PPV), and negative predictive value (NPV) were all 100%.

122 Sensitivity, specificity, and negative predictive value (NPV) were calculated by compa

123 pecificity, positive predictive value (PPV), negative predictive value (NPV), and Cohen's kappa coeff

124 pecificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic time.

125 pecificity, positive predictive value (PPV), negative predictive value (NPV), and positive likelihood

126 ficity, positive predictive value (PPV), and negative predictive value (NPV).

127 ficity, positive predictive value (PPV), and negative predictive value (NPV).

128 The negative predictive values (NPV) for GI and GII were 100

129 ities, positive predictive values (PPV), and negative predictive values (NPV) were 92.7%, 100%, 100%,

130 Positive (PPV) and negative predictive values (NPV) were calculated on a pe

131 ificity, positive predictive value [PPV] and negative predictive value [NPV] of both MR cisternograph

132 cificity range, 91%-99%; PPV range, 0%-3.6%; negative predictive value [NPV] range, >/=99%).

133 atients required neurosurgical intervention (negative predictive value [NPV], 100.0% [95% CI: 99.9%-1

134 predictive value [PPV], 24 [95% CI, 16-32]; negative predictive value [NPV], 92 [95% CI, 87-96]) and

135 ficity, positive predictive value [PPV], and negative predictive value [NPV]; treatment efficacy (COP

136 ulated positive predictive values (PPVs) and negative predictive values (NPVs) by comparing agreement

137 The negative predictive values (NPVs) for rayon swabs and ES

138 ty, specificity, positive predictive values, negative predictive values (NPVs), and accuracy were cal

139 with an AUC of 0.88 (95% CI 0.79-0.94) and a negative predictive value of 0.92 (95% 0.88-0.95) at the

140 a specificity of 0.83 (95% CI, 0.36-1.0), a negative predictive value of 1.0 (95% CI, 0.48-1.0), and

141 (18)F-FDG PET/CT had a negative predictive value of 100% and a positive predict

142 specificity, positive predictive value, and negative predictive value of 100%, 88%, 86%, and 100%, r

143 bviate the need for antifungal agents with a negative predictive value of 100%, whereas the presence

144 ch, with sensitivity of 100.0% and 63.6% and negative predictive value of 100.0% and 66.6%, respectiv

145 onstrated sensitivity, specificity, PPV, and negative predictive value of 47.6%, 93.9%, 55.6%, and 91

146 ficity, positive predictive value (PPV), and negative predictive value of 54.8%, 97.7%, 79.3%, and 93

147 predictive value of 98% (95% CI, 94%-100%), negative predictive value of 66% (95% CI, 56%-75%), spec

148 .0%, positive predictive value of 75.0%, and negative predictive value of 66.7%.

149 had a positive predictive value of 94% and a negative predictive value of 67%.

150 predictive value of 74.8% (80 of 107), and a negative predictive value of 78.1% (364 of 466).

151 tive value of 91.3% (95% CI: 73.3-97.6%) and negative predictive value of 78.6% (95% CI: 64.2-88.2%).

152 ctive value of 89.6% (95% CI, 89.1-90.1) and negative predictive value of 79.7% (95% CI, 79.4-80.1).

153 tive value of 62.5% (95% CI 40.6-81.2) and a negative predictive value of 79.8% (69.6-87.8).

154 lution to ESRD before 60 years of age with a negative predictive value of 81.4%, a score >6 forecasts

155 predictive value of 95.5% (21 of 22), and a negative predictive value of 83.3% (10 of 12).

156 specificity, positive predictive value, and negative predictive value of 84.7%, 78.2%, 75%, and 87%,

157 specificity, positive predictive value, and negative predictive value of 85.3%, 93.9%, 27.4%, and 99

158 90-93), sensitivity of 75% (95% CI, 72-78), negative predictive value of 86% (95% CI, 84-88), positi

159 %, a positive predictive value of 77%, and a negative predictive value of 86%.

160 edictive value of 41% (95% CI, 35%-46%), and negative predictive value of 88% (95% CI, 80%-94%).

161 e of 91%, whereas a cutoff of 641 IU/L had a negative predictive value of 88%.

162 cificity of 100.0% (95% CI, 90.9%-100.0%), a negative predictive value of 89.1% (95% CI, 77.1%-95.5%)

163 specificity, positive predictive value, and negative predictive value of 89.5%, 100%, 100%, and 97.2

164 to a positive predictive value of 25% and a negative predictive value of 90%.

165 00%, positive predictive value of 100% and a negative predictive value of 91.67%.

166 ded Cerebral Performance Category 4-5 with a negative predictive value of 92%.

167 80 seconds had sensitivity, specificity, and negative predictive value of 92.3%, 92.4%, and 98.6%, re

168 t culture positivity at 2 months with a high negative predictive value of 93% (95% CI, 89 to 96).

169 ensitivity of 88.9% and 63.9% (P = .013) and negative predictive value of 93.1% and 80.9% (P = .045),

170 ecificity, 71.2%; sensitivity, 71.0%, with a negative predictive value of 93.1% and a positive predic

171 .9%, positive predictive value of 94.1%, and negative predictive value of 93.8%.

172 h a positive predictive value of 21.5% and a negative predictive value of 94.2%.

173 1-82) and specificity of 63% (55-71), with a negative predictive value of 95% (94-97).

174 a sensitivity of 97%, specificity of 23%, a negative predictive value of 95%, and a positive predict

175 specificity, positive predictive value, and negative predictive value of 96.0% (95% confidence inter

176 US had a negative predictive value of 96.2% and a positive predic

177 a positive predictive value of 71.62% and a negative predictive value of 96.77% in terms of pixel-by

178 ve predictive value of 84.3% (70 of 83), and negative predictive value of 96.9% (157 of 162) for the

179 sensitivity of 81%, specificity of 69%, and negative predictive value of 97% at 6 hours from sample

180 tive value of 88.2% (95% CI 63.6-98.5) and a negative predictive value of 97.8% (92.2-99.7) and ident

181 had a positive predictive value of 83% and a negative predictive value of 98% for identifying partici

182 .0%, positive predictive value of 48.9%, and negative predictive value of 98.3% for the differentiati

183 sitivity of 83.6%, specificity of 82.6%, and negative predictive value of 98.4%, which are pessimisti

184 e predictive value 10% (95% CI, 9%-12%), and negative predictive value of 99% (95% CI, 98%-100%) in t

185 o predict ICU mortality was 155 pg/mL with a negative predictive value of 99%.

186 Computed tomographic scans had an overall negative predictive value of 99.2% for patients with CSI

187 594 (56%) of 1061 patients, with an overall negative predictive value of 99.4% (98.8-99.9).

188 tients with CRC with 87.0% sensitivity and a negative predictive value of 99.4%.

189 , a positive predictive value of 5.7%, and a negative predictive value of 99.4%.

190 This resulted in a negative predictive value of 99.5% (95% CI, 99.3%-99.6%)

191 ng/L in 2311 (61%) of 3799 patients, with a negative predictive value of 99.6% (95% CI 99.3-99.8) fo

192 ve disease of 97.2% (95% CI 85.0-100), and a negative predictive value of 99.6% (97.9-100).

193 6 ng/L, the rule-out algorithm showed a high negative predictive value of 99.8% (95% CI, 98.6%-100.0%

194 value of 99.2% for patients with CSIs and a negative predictive value of 99.8% for ruling out CSIs t

195 hs at 30 days and 7 (0.1%) at 1 year, with a negative predictive value of 99.9% (95% CI, 99.7%-99.9%)

196 specificity, positive predictive value, and negative predictive value of a NRL-sIgE level >/=0.35 kU

197 ion and validation cohorts, we evaluated the negative predictive value of a range of troponin concent

198 The primary outcome was a comparison of the negative predictive value of both pathways for index typ

199 specificity, positive predictive value, and negative predictive value of cMR was 57%, 57%, 27%, and

200 The negative predictive value of CTC for adenomas >/=6 mm wa

201 The negative predictive value of having 0 points (ie, none o

202 The negative predictive value of programmatic early success

203 Given the high sensitivity and negative predictive value of results obtained, BacterioS

204 specificity, positive predictive value, and negative predictive value of SE were 51.35 %, 67.33 %, 3

205 his study was to measure the sensitivity and negative predictive value of sentinel-lymph-node mapping

206 The negative predictive value of skin prick test with peanut

207 Antischemic therapy markedly affects the negative predictive value of stress echocardiography in

208 d TTPVI) was associated with tumor size: The negative predictive value of the absence of worrisome fe

209 The negative predictive value of the combination of SPT and

210 mean sensitivity, specificity, positive and negative predictive value of the corresponding optimal c

211 Although the high negative predictive value of the Fungitell assay in both

212 The negative predictive value of the High-STEACS pathway was

213 Reactions to the graded PC, the negative predictive value of the PC for nonimmediate rea

214 The negative predictive value of the skin test protocol was

215 The negative predictive value of the staged algorithm was 99

216 ith radiographic nodules less than 3 cm, the negative predictive value of the TM panel was 71.8%, hen

217 arge meta-analyses that have highlighted the negative predictive value of this test.

218 or epileptiform discharges with positive and negative predictive values of 0.71 (95% CI 0.51, 0.87) a

219 8.8%, specificity of 40.1%, and positive and negative predictive values of 17.0% and 99.6%, respectiv

220 6.7% and 52%, respectively, and positive and negative predictive values of 31.9% and 82.2%, respectiv

221 nd a specificity of 47.1%, with positive and negative predictive values of 36.5% and 86.3%, respectiv

222 4%, a specificity of 40.1%, and positive and negative predictive values of 41.1% and 95.2%, respectiv

223 5%, a specificity of 71.4%, and positive and negative predictive values of 45.1% and 98.8%, respectiv

224 h high-risk cirrhosis generates positive and negative predictive values of 80% and 86%, respectively.

225 ence interval, 0.764-0.917) and positive and negative predictive values of 83% and 81%, respectively.

226 with sensitivity, specificity, positive, and negative predictive values of 84%, 80%, 64%, and 92%, re

227 97%, a specificity of 99%, and positive and negative predictive values of 89% and 100% for detecting

228 ost-CRT and ADC change measurements achieved negative predictive values of 96% (44 of 46) to 100% (39

229 YG Carba v2.0 displayed overall positive and negative predictive values of 99.7% (CI95: 95.4-98.9) an

230 The positive and negative predictive values of an abnormal UA finding wer

231 Because of the low prevalence, negative predictive values of CLQ cutoff values (men, 0.

232 The positive and negative predictive values of FFR for flow-limiting coro

233 e sensitivity, specificity, and positive and negative predictive values of IVCM compared with those o

234 Positive and negative predictive values of low and elevated risk were

235 e sensitivity, specificity, and positive and negative predictive values of methacholine challenges at

236 Sensitivity, specificity, and positive and negative predictive values of the Amsler grid scotoma ar

237 Sensitivity, specificity, and positive and negative predictive values of the Amsler grid test were

238 Positive and negative predictive values of the ESwab were 86% (95% CI

239 pecificities and calculated the positive and negative predictive values of the Lipsker and of the Str

240 e sensitivity, specificity, and positive and negative predictive values of the methacholine challenge

241 e sensitivity, specificity, and positive and negative predictive values of the Xpert Carba-R assay co

242 te cutoff (ie, one with high sensitivity and negative predictive value) of the MPD diameter on CT or

243 ity, specificity, positive predictive value, negative predictive value, or overall accuracy were foun

244 city, 85% positive predictive value, and 89% negative predictive value (p < 0.001).

245 % reduction, but more specific with a higher negative predictive value (P < 0.001).

246 ning visual score, sensitivity, specificity, negative predictive value, positive predictive value, an

247 lues, sensitivity, specificity, positive and negative predictive values, positive and negative likeli

248 ng sensitivity, specificity and positive and negative predictive value (PPV and NPV) for the two Arab

249 We aimed to validate the positive and negative predictive values (PPV and NPV) of these diagno

250 , with a 80.8% (21 of 26) and 90% (18 of 20) negative predictive value, respectively.

251 The high negative predictive value suggests that a negative stain

252 hese data, we conclude that UA has excellent negative predictive value that is not enhanced by urine

253 as assessed by positive predictive value and negative predictive value, that is, the probability of a

254 With its excellent negative predictive value, the use of this biomarker in

255 atients who have low heart rates with a high negative predictive value to rule out coronary artery di

256 specificity, positive predictive value, and negative predictive value using the histopathological di

257 of immunochemotherapy, iPET has a very good negative predictive value, utilizing both visual (qualit

258 lue of confocal microscopy was 87.5% and the negative predictive value was 58.5%.

259 e positive predictive value was 54%, and the negative predictive value was 67%.

260 lue was 78.6% (95% CI, 60.5%-89.8%), and the negative predictive value was 75.0% (95% CI, 55.1%-88.0%

261 85%, positive predictive value was 81%, and negative predictive value was 79%.

262 om the 92 segmental pairs, were 82% and 72%, negative predictive value was 81%, and overall positive

263 redictive value was 95% (21 of 22 patients), negative predictive value was 90% (nine of 10 patients),

264 alue was 70% (95% CI 60.5-73.5), whereas the negative predictive value was 91.3% (90.0-92.5).

265 dictive value was 72% (95% CI, 61%-90%), and negative predictive value was 96.4% (95% CI, 90%-98.7%).

266 value was 10.8% (95% CI, 9.6%-11.9%) and the negative predictive value was 97.8% (95% CI, 96.8%-98.6%

267 The negative predictive value was 97.9% in the prospective v

268 lue was 33.3% (95% CI, 25.6%-45.5%), and the negative predictive value was 98.1% (95% CI, 96.9%-100%)

269 CI, 86.7-94.5) and for adenomas >/=10 mm the negative predictive value was 98.6% (95% CI, 97.0-100).

270 the positive predictive value was 16.4 % and negative predictive value was 99.4 %.

271 The negative predictive value was 99.5% and the likelihood r

272 The negative predictive value was consistent across groups s

273 The negative predictive value was estimated to range from 99

274 he positive predictive value was 11% and the negative predictive value was more than 99%.

275 The positive predictive value and the negative predictive value were 91% (95% CI, 59-99) and 6

276 specificity, positive predictive value, and negative predictive value were 96.6%-100%, 77.3%-83.3%,

277 ty, accuracy, positive predictive value, and negative predictive value were 97%, 95.1%, 96.6%, 98.5%,

278 The readers' positive predictive value and negative predictive value were broadly consistent with e

279 ficity, positive predictive value (PPV), and negative predictive value were calculated for both imagi

280 sitive predictive value, and 80% (96 of 120) negative predictive value were obtained.

281 , 76 to 85, and >85 years, respectively; the negative predictive values were >98% across all age grou

282 Positive and negative predictive values were 1.9% (95% confidence int

283 Positive and negative predictive values were 21% (95% CI 19-22) and 9

284 Positive and negative predictive values were 21.3% and 95.6%, respect

285 Positive and negative predictive values were 37% (95% CI 35-39) and 8

286 The positive and negative predictive values were 41.5% and 99.4%, respect

287 3.7% (95% CI, 83.4%-84.0%), and positive and negative predictive values were 72.7% (95% CI, 72.2%-73.

288 test sensitivity, specificity, positive and negative predictive values were 79.2%, 38.5%, 27.6%, and

289 81% and 79%, respectively, and positive and negative predictive values were 81% and 79%, respectivel

290 The decision tree's positive and negative predictive values were 90.8% and 91.9%, respect

291 Using a score threshold of </=46.15, negative predictive values were 92% in the derivation an

292 9.03% and 99.23%, respectively; positive and negative predictive values were 92.01% and 99.91%, respe

293 y was 96%, specificity was 82%, positive and negative predictive values were 93% and 90%, and the are

294 e sensitivity, specificity, and positive and negative predictive values were 98.1%, 39.1%, and 44.0%

295 The negative predictive values were all higher than 0.99.

296 while sensitivity, specificity, positive and negative predictive values were calculated as 98.1, 94.4

297 ive fractions were 22% and 2%, respectively; negative predictive values were especially low for 10- t

298 Negative predictive values were high for both groups, bu

299 GM negative predictive values were high, ranging from 85% t

300 Positive and negative predictive values were, respectively, 50% and 1