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 ld to 1.0 resulted in a high specificity and negative predictive value.

3 monary embolism, although YEARS has a better negative predictive value.

4 ty, 75% positive predictive value, and 91.9% negative predictive value.

5 icity, 89%-positive predictive value and 76%-negative predictive value.

6 sumed to exclude malignancy with a very high negative predictive value.

7 RE biomarkers with both high sensitivity and negative predictive value.

8 (T) ) can predict toxin positivity with high negative predictive value.

9 hypertension 100% of the time and had a 100% negative predictive value.

10 ffects of disease prevalence on positive and negative predictive values.

11 antibody-mediated acute rejection, with high negative predictive values.

12 monstrates persistently high sensitivity and negative predictive values.

13 ificity 0.6, positive predictive value 0.81, negative predictive value 0.69).

14 positive predictive value (0.74, 0.75), and negative predictive value (0.76, 0.82).

15 = 0.80, positive predictive value = 0.73 and negative predictive value = 0.74, and disease activity b

16 sk of metastasis with sensitivity = 0.94 and negative predictive value = 0.89.

17 = 0.032; positive predictive value = 0.257, negative predictive value = 0.929].

18 obial detection bioassay lacked a sufficient negative predictive value (10%; 95% confidence interval,

19 ictive value (positive predictive value 85%, negative predictive value 100%, sensitivity 100%) than s

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

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

22 sitive predictive value (one of 11), and 97% negative predictive value (132 of 136) for TOC.

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

24 6.7%; positive predictive value - 85.7%; and negative predictive value - 72.4%.

25 7% and 77.5%, respectively) and positive and negative predictive values (74.7% and 78.5%, respectivel

26 test correlating with the absence of subAR (negative predictive value: 78%-88%), while a positive te

27 l, 8.0-34.4; positive predictive value, 66%; negative predictive value, 80%).

28 40% was more prevalent (86% v 46%; P < .001; negative predictive value, 88%; positive predictive valu

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

30 The negative predictive value 94.5%, and the accuracy was 71

31 t sensitivity (91.1%, 95%CI: 88.8, 93.4) and negative predictive value (94.5%, 95%CI: 93.1, 96.1) com

32 ive value, 97% [95% CI: 90%, 99%], 68 of 70; negative predictive value, 94% [95% CI: 79%, 98%], 30 of

33 ess than or equal to 3 (93% v 38%; P < .001; negative predictive value, 94%; positive predictive valu

34 t for symptomatic probands (sensitivity 92%; negative predictive value 95%) with limited specificity

35 I: 10%-47%) and a SALT score of <5 had a 95% negative predictive value (95% CI: 89%-98%) for sustaine

36 .0%), positive predictive value (98.6%), and negative predictive value (95.6%) as compared with >=20

37 demonstrated the high sensitivity (94%) and negative predictive value (97%) of GIP measurements in r

38 ms, and far-field EGM QRSd <120 ms) had high negative predictive value (97%, 95%, and 92%).

39 ctive value (PPV), 89% (95% CI, 86% to 91%); negative predictive value, 97% (95% CI, 96% to 98%); and

40 YEARS provides better negative predictive value (98% vs 92.4%), and both score

41 and/or "acute on chronic" renal dysfunction (negative predictive value, 98.0%; sensitivity, 92.9%; sp

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

43 pplied in patients with acute kidney injury (negative predictive value, 98.8%; sensitivity, 95.8%; sp

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

45 confidence interval [CI]: 81.5%, 93.6%) and negative predictive value (99.1% [1528 of 1542]; 95% CI:

46 to 0.9%; p = 0.429), resulting in a similar negative predictive value (99.4%; 95% CI: 98.9% to 99.6%

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

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

49 d for sensitivity, specificity, positive and negative predictive values, according to results of gene

50 ity, sensitivity, positive predictive value, negative predictive value and accuracy were determined f

51 The negative predictive value and positive predictive value

52 The negative predictive value and sensitivity of troponin co

53 e electrode aggregometry showed an excellent negative predictive value and sensitivity, at 98% and 92

54 Sensitivity, specificity, positive and negative predictive values and accuracy and discriminant

55 included positivity as well as positive and negative predictive values and likelihood ratios.

56 tions of lower fibrosis prevalence increased negative predictive values and reduced positive predicti

57 tus, with 70% positive predictive value, 60% negative predictive value, and 66% accuracy.

58 city, 45.5% positive predictive value, 92.0% negative predictive value, and 70.2% diagnostic accuracy

59 city, 96.7% positive predictive value, 64.7% negative predictive value, and 85.11% diagnostic accurac

60 onresponse in patients with a sensitivity, a negative predictive value, and a specificity of 71.4%, 8

61 ity, specificity, positive predictive value, negative predictive value, and accuracy and to evaluate

62 ity, specificity, positive predictive value, negative predictive value, and accuracy for diagnosis of

63 Sensitivity, specificity, positive and negative predictive value, and accuracy for LNM detectio

64 pecificity, positive predictive value (PPV), negative predictive value, and accuracy for pelvic lymph

65 ity, specificity, positive predictive value, negative predictive value, and accuracy were calculated

66 ity, sensitivity, positive predictive value, negative predictive value, and accuracy were determined

67 ity, specificity, positive predictive value, negative predictive value, and accuracy) were calculated

68 s of sensitivity, positive predictive value, negative predictive value, and accuracy, were higher in

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

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

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

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

73 ary endpoints were sensitivity, specificity, negative predictive value, and positive predictive value

74 lated sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy were

75 lated sensitivity, specificity, positive and negative predictive values, and the area under the recei

76 h platform showed 98.91% positive and 96.95% negative predictive values, and there was no significant

77 specificity, positive predictive value, and negative predictive value based on infants testing posit

78 nd 100%, respectively, with the positive and negative predictive values being 100% and 98.6%, respect

79 y group, we found comparable sensitivity and negative predictive value, but greater specificity and p

80 The negative predictive value curves were also superimposabl

81 ic curve, sensitivity, specificity, PPV, and negative predictive value for a CR were 0.80 to 0.84, 72

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

83 absence of alveolar neutrophilia has a high negative predictive value for bacterial pneumonia in cri

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

85 sterone-renin ratio had poor sensitivity and negative predictive value for detecting biochemically ov

86 lmonary congestion detected by LUS implied a negative predictive value for in-hospital mortality of 9

87 nary congestion on LUS provided an excellent negative predictive value for in-hospital mortality.

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

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

90 Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infe

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

92 ve value but low to moderate sensitivity and negative predictive value for the detection of PTLD in a

93 The negative predictive value for the primary outcome was 99

94 specificity, positive predictive value, and negative predictive value for the proposed optimal cutof

95 High sensitivity and negative predictive value for the RAPID Index was associ

96 whereas the extended algorithm had a higher negative predictive value for the rule-out.

97 Sensitivity, specificity, and positive and negative predictive values for individual suspicious ult

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

99 The negative predictive values for monocyte distribution wid

100 d sensitivity, specificity, and positive and negative predictive values for PET/MRI were 55%, 100%, 1

101 Positive predictive and negative predictive values for SS-OCT were 75% (95% CI 5

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

103 tive predictive value from 0.70 to 0.93, and negative predictive value from 0.94 to 0.96.

104 plied, test characteristics remained stable: negative predictive value (> 99%), sensitivity (91.2% vs

105 higher positive predictive value, comparable negative predictive value, higher yield, and greater ove

106 g sensitivity, specificity, and positive and negative predictive value in comparison with CECT findin

107 specificity, positive predictive value, and negative predictive value in identifying PLWDH.

108 , specificity, positive predictive value and negative predictive value in identifying PLWDH.

109 e likelihood ratio, and correspondingly high negative predictive value in low-incidence settings to f

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

111 had a 100% positive predictive value and 81% negative predictive value in predicting ajmaline test re

112 Negative predictive values in both analyses were higher

113 specificity, positive predictive values, and negative predictive values in the main analysis.

114 Interpretation of sensitivity and negative predictive value is limited by modest follow-up

115 stimating sensitivity, specificity, positive/negative predictive values, likelihood ratios, and accur

116 (95% CI: 92.2% to 97.9%), respectively, with negative predictive value (NPV) (100%), positive predict

117 arget performance criteria were at least 90% negative predictive value (NPV) and at least 90% sensiti

118 Visually, the best negative predictive value (NPV) and positive predictive

119 The primary endpoint was to estimate the negative predictive value (NPV) and positive predictive

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

121 (AUROC), specificity at 90% sensitivity, and negative predictive value (NPV) for each gene signature

122 ount <5 x 109/L at presentation, which had a negative predictive value (NPV) for likely bacterial pne

123 The negative predictive value (NPV) for malignancy of the be

124 ficity, positive predictive value (PPV), and negative predictive value (NPV) for the rectal swabs, wi

125 ficity, positive predictive value (PPV), and negative predictive value (NPV) from 2 separate gradings

126 dentified 45% of patients at low risk with a negative predictive value (NPV) of 100% (95% CI: 99.4% t

127 o sign has shown a sensitivity of 100% and a negative predictive value (NPV) of 100% in our study.

128 ficity, positive predictive value (PPV), and negative predictive value (NPV) of 216Dx versus UA were

129 , positive predictive value (PPV) of 57% and negative predictive value (NPV) of 86%.

130 , positive predictive value (PPV) of 86% and negative predictive value (NPV) of 99% was achieved for

131 ture samples after 12 hours incubation has a negative predictive value (NPV) of 99.5%.

132 ficity, positive predictive value (PPV), and negative predictive value (NPV) of CryptoPS were assesse

133 etection of cirrhosis greater than 90% and a negative predictive value (NPV) of greater than 95% in t

134 The objective was to determine the negative predictive value (NPV) of MRSA screening in the

135 objective of this study was to determine the negative predictive value (NPV) of MRSA screening in the

136 objective of this study was to determine the negative predictive value (NPV) of positron emission tom

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

138 ficity, positive predictive value (PPV), and negative predictive value (NPV) of STs for metronidazole

139 ficity, positive predictive value (PPV), and negative predictive value (NPV) of the serum BDG at diff

140 ificity, positive predictive value (PPV) and negative predictive value (NPV) of Xpert MTB/RIF assay f

141 ficity, positive predictive value (PPV), and negative predictive value (NPV) were also determined.

142 ficity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each

143 ficity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for MRI

144 ved 94% positive predictive value (PPV), 53% negative predictive value (NPV), 75% sensitivity, 86% sp

145 predictive value (PPV), 29.3% (25.6%-33.3%); negative predictive value (NPV), 90.2% (82.8%-94.7%); se

146 pecificity, positive predictive value (PPV), negative predictive value (NPV), accuracy) were compared

147 pecificity, positive predictive value (PPV), negative predictive value (NPV), and positive and negati

148 overall accuracy, sensitivity, specificity, negative predictive value (NPV), and positive predictive

149 Sensitivity, specificity, negative predictive value (NPV), and positive predictive

150 r sensitivity and specificity, unconditional negative predictive value (NPV), positive likelihood rat

151 Positive predictive value (PPV), negative predictive value (NPV), sensitivity, specificit

152 al infarction and estimates the sensitivity, negative predictive value (NPV), specificity and positiv

153 ) in the entire population, expressed as the negative predictive value (NPV), using ICA as the refere

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

155 n rate (IFR), false-negative rate (FNR), and negative predictive value (NPV).

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

157 substantially, with a minimal effect on the negative predictive value (NPV).

158 72.4%; Positive predictive value (PPV): 50%; Negative predictive value (NPV): 95.5%).

159 sitive predictive value (PPV) with estimated negative predictive values (NPV) of 81%-99%.

160 90% positive predictive values (PPV) and 74% negative predictive values (NPV); the Nugent scores had

161 was 94.9% (95% CI 93.6-96.0%) for grader 1 (negative predictive value [NPV] 99%) and 96.4% (95% CI 9

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

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

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

165 dentify low-risk patients, sensitivities and negative predictive values (NPVs) for acute MI and MI or

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

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

168 erived as a threshold for positivity, with a negative predictive value of >97% for CMV events.

169 specificity, positive predictive value, and negative predictive value of (18)F-FDG PET/CT for the de

170 ensitivity of 0.91, a specificity of 0.79, a negative predictive value of 0.91, and a positive predic

171 A threshold of 8,500 pg/mL gives Ang-2 a negative predictive value of 100% and positive predictiv

172 sensitivity, positive predictive value, and negative predictive value of 100%, 96%, 100%, and 98%, r

173 sensitivity of 100% (95% CI 72%-100%) and a negative predictive value of 100%, as compared to a sens

174 31%, positive predictive value of 87.5%, and negative predictive value of 100%.

175 eas day 5 score of <=2 had a sensitivity and negative predictive value of 100%.

176 ve value of 5.9% (95% CI, 2.6%-12.2%), and a negative predictive value of 100.0% (95% CI, 100.0%-100.

177 o a sensitivity of 24% (95% CI 8%-50%) and a negative predictive value of 19% (95% CI 5%-46%) for the

178 ease were 96.1 and 26.2% with a positive and negative predictive value of 24.3 and 96.1%, consistent

179 dictive value of 96% (95% CI: 93%, 98%), and negative predictive value of 67% (95% CI: 53%, 78%) in t

180 The model provides a specificity of 78% and negative predictive value of 73%.

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

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

183 tion were 99.0 and 23.2% with a positive and negative predictive value of 8.0 and 99.7%.

184 f 93%, positive predictive value of 86%, and negative predictive value of 83%.

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

186 0/176), with a positive predictive value and negative predictive value of 83.8% (31/37) and 50.1% (17

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

188 specificity, positive predictive value, and negative predictive value of 86% (119 of 139), 96% (55 o

189 sensitivity of 79% (95% CI, 0.72-0.85) and a negative predictive value of 87% (95% CI, 0.83-0.91).

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

191 f 0.74, positive predictive value of 70% and negative predictive value of 88.3% against the manual gr

192 ptical density thresholds, a specificity and negative predictive value of 89% and 95% were achieved,

193 28), specificity of 44.2% (53 of 120), and a negative predictive value of 90% (53 of 59).

194 ificity of 55% for severe impairment, with a negative predictive value of 91%.

195 a positive predictive value of 77.8%, and a negative predictive value of 92.9%.

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

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

198 1-82) and specificity of 63% (55-71), with a negative predictive value of 95% (94-97).

199 .0%, positive predictive value of 86.5%, and negative predictive value of 95.8% for identifying a tri

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

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

202 .4%, positive predictive value of 88.9%, and negative predictive value of 97.6%.

203 a positive predictive value of 88.0%, and a negative predictive value of 97.6%.

204 a positive predictive value of 88.0%, and a negative predictive value of 97.6%.

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

206 %, a positive predictive value of 32%, and a negative predictive value of 98%.

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

208 ing positive predictive value of 0.84% and a negative predictive value of 99.2%.

209 95% confidence interval [CI], 15.7-84.3) and negative predictive value of 99.3% (95% CI, 97.5-99.9).

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

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

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

213 inutes (early serial sampling) resulted in a negative predictive value of 99.5% for myocardial infarc

214 charged from ED, the 0/1-hour protocol had a negative predictive value of 99.6% (95% CI, 99.0-99.9%)

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

216 atients with a high pretest probability, the negative predictive value of a D-dimer less than 500 ng/

217 (72.2%) than TST (54.2%) and TSPOT (51.9%); negative predictive value of all tests was high (TST 97.

218 an showing complete PVD was 53%, whereas the negative predictive value of an OCT scan showing attache

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

220 In the same cohort, sensitivity and negative predictive value of depth of invasion, currentl

221 , specificity, positive predictive value and negative predictive value of each symptom-predictor, WHO

222 ar neutrophil percentage less than 50% had a negative predictive value of greater than 90% for bacter

223 A high negative predictive value of greater than 90% in both co

224 ll nodules were benign, confirming the known negative predictive value of HTNs with regard to maligna

225 included the ME panel test utilization rate, negative predictive value of nonpleocytic CSF samples, t

226 g culture-based testing as the standard, the negative predictive value of PCR was found to be 100%, w

227 strating limitations ABVD therapy and of the negative predictive value of PET2.

228 The negative predictive value of programmatic early success

229 The negative predictive value of REFtb for tuberculosis infe

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

231 ng was applied to assess the sensitivity and negative predictive value of screening with various simu

232 The negative predictive value of the first-day result among

233 The negative predictive value of the negligible risk categor

234 The negative predictive value of the staged algorithm was 99

235 of 1, specificity of 0.57, and positive and negative predictive values of 0.42 and 1, respectively.

236 values of -1.455 (NFS) and 1.3 (FIB-4) have negative predictive values of 0.80 and 0.82, respectivel

237 e sensitivity, specificity, and positive and negative predictive values of 18F-FDG-PET/CT focal uptak

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

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

240 d ischemia as 2.6 and 1.5, with positive and negative predictive values of 91% and 86%, respectively.

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

242 The negative predictive values of a normal CSF white blood c

243 Sensitivity, specificity, and positive and negative predictive values of FIT for ACN were 0.90, 0.8

244 e sensitivity, specificity, and positive and negative predictive values of International Classificati

245 e sensitivity, specificity, and positive and negative predictive values of saliva real-time PCR were

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

247 e sensitivity, specificity, and positive and negative predictive values of the panel compared to myco

248 The reproducibility and positive and negative predictive values of three consecutive NAC-S pe

249 ve value of 41.6% (95% CI, 32.9-50.8), and a negative-predictive value of 98.1% (95% CI, 97.5-98.7).

250 gle 10-second ECG yielded a sensitivity (and negative predictive value) of 1.5% (66%) for AF detectio

251 While maintaining higher negative predictive value, our final fusion model achiev

252 % reduction, but more specific with a higher negative predictive value (P < 0.001).

253 ity, specificity, positive predictive value, negative predictive value, positive and negative likelih

254 Negative predictive value, positive predictive value of

255 -DOTATATE included sensitivity, specificity, negative predictive value, positive predictive value, an

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

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

258 80.0% and 87.5%, respectively, positive and negative predictive values (PPV, NPV) of 93.8% and 65.1%

259 itivity (Se), specificity (Sp), positive and negative predictive values (PPV, NPV), according to resu

260 uld predict LR histopathologic features) and negative predictive values (probability that absence of

261 ectively, and positive predictive values and negative predictive values ranged between 0.59 and 0.92

262 r than or equal to 0.33 (P = .01), while the negative predictive value remained unchanged (83% [25 of

263 olds are 2.6 and 1.5, with high-positive and negative predictive values, respectively.

264 ith penicillin skin testing, which carries a negative predictive value that exceeds 95% and approache

265 s improved sensitivity, but has insufficient negative predictive value to exclude TBM.

266 Its value is largely related to its negative predictive value to rule out CD in patients who

267 negative likelihood ratios, and positive and negative predictive values to determine the diagnostic p

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

269 ve predictive value for SIRE was 25% and the negative predictive value was 100%.

270 1%, positive predictive value was 21.8%, and negative predictive value was 100%.

271 e predictive value of this model was 83% and negative predictive value was 40%.

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

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

274 R-TR Nonviable category was 67%-71%, and the negative predictive value was 81%-87%.

275 was 84%, positive predictive value was 77%, negative predictive value was 89%, and accuracy was 84%

276 Overall negative predictive value was 91%.

277 staging was 98.5% (95% CI: 92-100%), and the negative predictive value was 96.4% (86.2-99.9%).

278 positive predictive value was 97.1%, and the negative predictive value was 97.6%.

279 Negative predictive value was 98%.

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

281 alue was 94.0% (95% CI, 89.3% to 96.7%), and negative predictive value was 99.1% (95% CI, 97.7% to 99

282 tive value was 86.3% (95% CI, 80.4 to 90.6), negative predictive value was 99.3% (95% CI, 98.0 to 99.

283 and 90% (CI, 88% to 91%), respectively; the negative predictive value was 99.7% (1242 of 1246).

284 20.9% (14 of 67; 95% CI: 11.9%, 32.6%), and negative predictive value was 99.7% (789 of 791; 95% CI:

285 At both thresholds, the negative predictive value was consistent in men and wome

286 The negative predictive value was determined in all patients

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

288 tive value of biopsy performed (PPV(3)), and negative predictive value were determined.ResultsIn the

289 specificity, positive predictive value, and negative predictive value were reported for each radiotr

290 specificity, positive predictive value, and negative predictive value were respectively 80%, 91%, 80

291 The positive and negative predictive values were 40.7% and 98.5%, respect

292 specificity, positive predictive value, and negative predictive values were 73.9%, 78.4%, 68.0%, and

293 ivity, specificity, positive predictive, and negative predictive values were 76.5%, 77.3%, 72.2%, and

294 sion were 14.8% and 26.2%, respectively, and negative predictive values were 91.6% and 86.4%, respect

295 9.03% and 99.23%, respectively; positive and negative predictive values were 92.01% and 99.91%, respe

296 compared to HC2 was 91.5% for CIN3+, and the negative predictive values were 99.8% (95% CI, 99.5 to 9

297 Positive and negative predictive values were calculated for progressi

298 itivity (SN), specificity (SP), positive and negative predictive values were performed for all questi

299 specificity, positive predictive values, and negative predictive values were recalculated.

300 e sensitivity, specificity, and positive and negative predictive values, were calculated for each def