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

1 cytometry, after consolidation therapy (100% positive predictive value).

2 ng/mL; 93% negative predictive value and 20% positive predictive value).

3 y), without any false-positive results (100% positive predictive value).

4 iously undiagnosed cases of AERD with a high positive predictive value.

5 o 99.5% in specificity, and 41.3 to 84.3% in positive predictive value.

6 bined is limited by low sensitivity and poor positive predictive value.

7 nce standard for calculating sensitivity and positive predictive value.

8 migatus sensitization with good negative and positive predictive values.

9 nce of this algorithm with high negative and positive predictive values.

10 ensitivity was 100% and specificity was 98% (positive predictive value 0.92).

11 80%-92%), specificity 88% (95% CI, 87%-89%), positive predictive value 10% (95% CI, 9%-12%), and nega

12 (with ventricular fusion; specificity 100%; positive predictive value 100%).

13 for VT recurrence but the specificity (43%; positive predictive value, 35.7%) may be limited by blin

14 ified variant in HLA-DQB1 (OR=15.6, P=0.015, positive predictive value=35.1%).

15 HNSCCs, p16 had lower sensitivity (83%) and positive predictive value (40%) but high specificity (94

16 d for 63 patients who lived at least a year (positive predictive value, 45.2%).

17 ve results and 15960 false-positive results (positive predictive value, 50%).

18 ]; specificity, 99.9% [95% CI, 99.9%-99.9%]; positive predictive value, 59.0% [95% CI, 52.3%-65.5%])

19 ely; specificity, 93% and 98%, respectively; positive predictive value, 61% and 88%, respectively; an

20 nd for 5 patients who lived at least a year (positive predictive value, 61.5%).

21 (</=3 mm; n = 95), specificity(82% vs. 62%), positive predictive value(66% vs. 50%) and area under cu

22 ohort (sensitivity, 60%; specificity, 95.5%; positive predictive value, 66.7%; negative predictive va

23 ficity, 67%; negative predictive value, 67%; positive predictive value, 73%; and accuracy, 70%), shor

24 specificity (93.0% and 99.0%, respectively), positive predictive value (76.7% and 69.2%, respectively

25 CT had 75% sensitivity, 51% specificity, 44% positive predictive value, 80% negative predictive value

26 in sensitivity (92.9% vs. 92.9%, P = 1.00), positive predictive value (81.3% vs. 86.7%, P = 0.68), o

27 -2, and p-ERK expression showed an increased positive predictive value (81.8% vs 75.9%) and an increa

28 ge children, lung clearance index has a good positive predictive value (83-86%) but a poor negative p

29 -99.7), 97.7% sensitivity (96.1-99.2), 88.6% positive predictive value (85.8-91.3), and 99.9% negativ

30 specificity, negative predictive value, and positive predictive value (88.5, 82, 83.7, and 87.3%, re

31 /- 0.09; sensitivity, 79%; specificity, 71%; positive predictive value, 88%; P = 0.02).

32 (P<0.001; sensitivity 98%; specificity 93%; positive predictive value 90%; negative predictive value

33 ficity, 89%; negative predictive value, 80%; positive predictive value, 90%; and accuracy, 85%).

34 accuracy predicting sc-AR (specificity, 98%; positive predictive value 93%) (all sc-ABMR and 58% sc-T

35 ponse with high specificity (92%) and strong positive predictive value (93%).

36 ce (sensitivity = 100%, specificity = 97.4%, positive predictive value = 93.3%, negative predictive v

37 ppa=0.89, sensitivity=86%, specificity=100%, positive predictive value=93%, and negative predictive v

38 ing (indicative estimates of sensitivity and positive predictive value 94% and 84%, respectively).

39 ssed early treatment success both had a high positive predictive value (94.3%-100.0%) for late clinic

40 ded 99% specificity (95% CI, 95-100) and 93% positive predictive value (95% CI, 66-100) for return of

41 sitivity, 89% vs. 78%specificity, 73% vs. 57%positive predictive value, 95% vs. 94%negative predictiv

42 with higher levels of specificity (95%) and positive predictive values (96%) than wireless pH monito

43 .4%]; specificity, 100% [95% CI, 100%-100%]; positive predictive value, 96.5% [95% CI, 92.5%-98.7%];

44 s, sensitivity was 98.6%, specificity 90.5%, positive predictive value 99.1%, and negative predictive

45 gave 67% sensitivity, 92% specificity, a 97% positive predictive value, a 42% negative predictive val

46 The FIT positivity rate (5.0%) and positive predictive values (adenoma, 51.5%; CRC, 3.4%) w

47 The positive predictive values after biopsy (PPV3) for BI-RA

48 formance, with specificity, sensitivity, and positive predictive value all >99%, whereas other linkag

49 nd serum CCL17 and CCL26 expression had 100% positive predictive value and 87% negative predictive va

50 The readers' positive predictive value and negative predictive value

51 Clinical utility was assessed by positive predictive value and negative predictive value,

52 likelihood ratio, negative likelihood ratio, positive predictive value and negative predictive values

53 Positive predictive value and NPV ranged from 17% to 45%

54 Moreover, the positive predictive value and positive-likelihood ratio

55 ty and proportion with AMI ruled out and the positive predictive value and proportion ruled-in.

56 The positive predictive value and specificity at the 99th ce

57 The positive predictive value and specificity at the 99th ce

58 The positive predictive value and the negative predictive va

59 Positive predictive values and referral criteria that mi

60 ng/mL; 97% negative predictive value and 27% positive predictive value) and sNGAL (>/=179 ng/mL; 93%

61 96.6% sensitivity, 45.5% specificity, 82.4% positive predictive value, and 83.3% negative predictive

62 T with 76% sensitivity, 93% specificity, 85% positive predictive value, and 89% negative predictive v

63 , with 92% sensitivity, 95% specificity, 94% positive predictive value, and 94% negative predictive v

64 stress syndrome cases), 31% specificity, 17% positive predictive value, and 95% negative predictive v

65 ity, specificity, negative predictive value, positive predictive value, and accuracy were 95.2%, 75%,

66 ited 66% sensitivity, 98% specificity, a 93% positive predictive value, and an 88% negative predictiv

67 reening population by analyzing recall rate, positive predictive value, and cancer detection rate.

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

69 racteristic curve, sensitivity, specificity, positive predictive value, and negative predictive value

70 arge diagnoses had sensitivity, specificity, positive predictive value, and negative predictive value

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

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

73 The sensitivity, specificity, positive predictive value, and negative predictive value

74 The sensitivity, specificity, positive predictive value, and negative predictive value

75 T data resulted in sensitivity, specificity, positive predictive value, and negative predictive value

76 ion demonstrated a sensitivity, specificity, positive predictive value, and negative predictive value

77 omes and Measures: Sensitivity, specificity, positive predictive value, and negative predictive value

78 The sensitivity, specificity, positive predictive value, and negative predictive value

79 The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value

80 mal, demonstrating sensitivity, specificity, positive predictive value, and negative predictive value

81 used together, the sensitivity, specificity, positive predictive value, and negative predictive value

82 agnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value

83 ive samples with a sensitivity, specificity, positive predictive value, and negative predictive value

84 Modeled sensitivity, positive predictive value, and negative predictive value

85 ighly variable sensitivity, specificity, and positive predictive values, and these were generally poo

86 , sensitivity, specificity, and negative and positive predictive values at three cutoffs: 0.3, 1.0, a

87 tive predictive values (70% to 100%) but low positive predictive values (below 50%).

88 fferences in image contrast, sensitivity, or positive predictive values between the 2 (68)Ga-OPS202 p

89 ms-based methods of defining events had high positive predictive values but low sensitivities.

90 ediction approach had a significantly higher positive predictive value compared to minimum inhibitory

91 d significant improvement in specificity and positive predictive value compared with CTA alone for pr

92 value for cardiac ATTR amyloidosis of 100% (positive predictive value confidence interval, 98.0-100)

93 Positive predictive values decreased with decreasing ren

94 The primary outcome, positive predictive value for a physician-confirmed diag

95 The positive predictive value for all suspicious lesions was

96 The positive predictive value for an application-reported ho

97 tein in serum or urine had a specificity and positive predictive value for cardiac ATTR amyloidosis o

98 ve values were high for both groups, but the positive predictive value for cirrhosis was >66% in the

99 IgE to Can f 1 showed a higher positive predictive value for dog allergy than dog extra

100 tom scores at baseline provided the greatest positive predictive value for first-onset depressive dis

101 r better motor reaction had greater than 70% positive predictive value for good outcome; reactivity (

102 LR-5 criteria also improved specificity and positive predictive value for HCC (R1, two fewer false-p

103 f the LR-5V pathway improved specificity and positive predictive value for HCC to 83.3% and 92.9%, re

104 h a single agent had 98% specificity and 89% positive predictive value for identifying regimens achie

105 An optical biopsy has excellent positive predictive value for intraoperative diagnosis o

106 The results indicated the highest positive predictive value for K103N (100%) and the highe

107 Positive predictive value for MR imaging recalls was 9.3

108 New R ratio Hy's law had a higher positive predictive value for overall fatality (14% vers

109 of CNS disease had 88% specificity and a 92% positive predictive value for predicting the presence of

110 hold, the combined diaschisis measures had a positive predictive value for survival below 1 y of 100%

111 Positive predictive values for (68)Ga-OPS202 PET/CT and

112 T positivity (>/=20 microg of hemoglobin/g), positive predictive values for adenoma and CRC, and FIT

113 of the algorithm yielded an average of 95.8% positive predictive values for both cases and control su

114 , IgE to Fel d 1 and cat extract had similar positive predictive values for cat allergy.

115 Positive predictive values for identifying true NF and d

116 orebrain and hindbrain had high negative and positive predictive values for survival for less than a

117 was calculated as initial screening yield x positive predictive value from a study with confirmatory

118 5 plus 6.01/6.02 >/= 1.46 kUA /l provided a positive predictive value >95% with a higher sensitivity

119 T/CT did not improve the specificity and the positive predictive value in our series.

120 erroni adjusted alpha = .0125), with highest positive predictive value in phase 1 (64.0%) and highest

121 The positive predictive value increased above 95% when incre

122 Considering its positive predictive value, it might allow to make a cons

123 olid-organ transplantation patients, the low positive predictive value limits its utility as a screen

124 ; women, 0.97 [745 of 766]) were higher than positive predictive values (men, 0.01 [88 of 582]; women

125 The sensitivity, specificity, positive predictive value, negative predictive value, an

126 active CHB with a sensitivity, specificity, positive predictive value, negative predictive value, an

127 Positive predictive value, negative predictive value, an

128 The sensitivity, specificity, positive predictive value, negative predictive value, an

129 cant difference in sensitivity, specificity, positive predictive value, negative predictive value, or

130 Sensitivity, specificity, positive predictive values, negative predictive values (

131 specificity, negative predictive value, and positive predictive value of (124)I PET/CT were 44% (con

132 In contrast, the positive predictive value of (18)F-FLT iPET remains too

133 ctive value of 1.0 (95% CI, 0.48-1.0), and a positive predictive value of 0.86 (95% CI, 0.42-1.0) for

134 positive predictive value, with the highest positive predictive value of 0.86 seen in the PFP charac

135 f all three worrisome features returned to a positive predictive value of 0.95 for observer 1 and 0.9

136 Plasma ddPCR exhibited a positive predictive value of 100% (95% CI, 91%-100%) for

137 specificity of 100% (CI, 97% to 100%) and a positive predictive value of 100% (CI, 99% to 100%).

138 h sensitivity of 96.4%, specificity of 100%, positive predictive value of 100% and a negative predict

139 value of 89.1% (95% CI, 77.1%-95.5%), and a positive predictive value of 100.0% (95% CI, 86.3%-100.0

140 44.7% sensitivity, 94.0% specificity, and a positive predictive value of 2.6%.

141 a period in which a relapse occurred, with a positive predictive value of 21.5% and a negative predic

142 5 nonprogressive lesions, corresponding to a positive predictive value of 25% and a negative predicti

143 h a negative predictive value of 93.1% and a positive predictive value of 31.0%).

144 %, a negative predictive value of 95%, and a positive predictive value of 38%.

145 0%, specificity of 82.6%, accuracy of 84.0%, positive predictive value of 48.9%, and negative predict

146 with 87.0% sensitivity, 60.8% specificity, a positive predictive value of 5.7%, and a negative predic

147 detectable by pooled HIV RNA testing, with a positive predictive value of 59%.

148 ectable interim circulating tumour DNA had a positive predictive value of 62.5% (95% CI 40.6-81.2) an

149 94.0%-98.8%) and ruled-in 292 (13.1%) with a positive predictive value of 63.4% (95% CI, 57.5%-68.9%)

150 6.4%-99.7%)) and ruled-in 310 (14.0%) with a positive predictive value of 68.1% (95% CI, 62.6%-73.2%)

151 oach yielded a Dice coefficient of 75.86%, a positive predictive value of 71.62% and a negative predi

152 were detected at a sensitivity of 85% and a positive predictive value of 74%.

153 182), a specificity of 93.1% (364 of 391), a positive predictive value of 74.8% (80 of 107), and a ne

154 ad a negative predictive value of 100% and a positive predictive value of 75% for pancreatic cysts.

155 parameter was below the threshold, it had a positive predictive value of 75%, and when both paramete

156 false alarm rate of only 0.31 per day and a positive predictive value of 75%.

157 sensitivity of 60.0%, specificity of 80.0%, positive predictive value of 75.0%, and negative predict

158 ensitivity of 42.5%, a specificity of 97%, a positive predictive value of 77%, and a negative predict

159 NEDA at 2 years had a positive predictive value of 78.3% for no progression (E

160 s A (n = 511) and B (n = 127) demonstrated a positive predictive value of 78.4% for "clinical AERD,"

161 dual high-risk children at 24 months (with a positive predictive value of 81% and a sensitivity of 88

162 n indeterminate Quantiferon-CMV result had a positive predictive value of 83% and a negative predicti

163 ive predictive value of 86% (95% CI, 84-88), positive predictive value of 84% (95% CI, 81-87), and a

164 157 of 170), accuracy of 92.7% (227 of 245), positive predictive value of 84.3% (70 of 83), and negat

165 hly suggestive of an active infection with a positive predictive value of 88%.

166 Surveillance circulating tumour DNA had a positive predictive value of 88.2% (95% CI 63.6-98.5) an

167 nsitivity (58.4%; 95% CI, 57.7-59.1), with a positive predictive value of 89.6% (95% CI, 89.1-90.1) a

168 had 77% sensitivity, 84% specificity, and a positive predictive value of 90% for >/=70% stenosis.

169 sts ESRD onset before 60 years of age with a positive predictive value of 90.9%.

170 For M65, a cutoff of 2000 IU/L had a positive predictive value of 91%, whereas a cutoff of 64

171 sing 51 independent clinical samples, with a positive predictive value of 91.3% (95% CI: 73.3-97.6%)

172 g 272 who were successfully extubated, for a positive predictive value of 92%.

173 st and 736 were successfully extubated for a positive predictive value of 93%.

174 d a negative predictive value of 96.2% and a positive predictive value of 93.3% for depicting appendi

175 The classifier had a positive predictive value of 94% and a negative predicti

176 0%, specificity of 99.3%, accuracy of 93.9%, positive predictive value of 94.1%, and negative predict

177 egative predictive value (NPV) of 97.6%, and positive predictive value of 94.9%.

178 9% (10 of 11), accuracy of 91.2% (31 of 34), positive predictive value of 95.5% (21 of 22), and a neg

179 onal perimetry results in 147 eyes yielded a positive predictive value of 98% (95% CI, 94%-100%), neg

180 ted Cerebral Performance Category 4-5 with a positive predictive value of 99%, false positive rate of

181 Specificity and positive predictive value of an HCC imaging diagnosis (L

182 The positive predictive value of an sFlt-1:PlGF ratio above

183 ong them, 27 awoke from coma, resulting in a positive predictive value of awakening of 82% (95% confi

184 on and included cancer detection rate (CDR), positive predictive value of biopsy recommendation (PPV2

185 Positive predictive value of recall and positive predictive value of biopsy were lowest in women

186 y rate, positive predictive value of recall, positive predictive value of biopsy, cancer detection ra

187 nt to use, the sensitivity, specificity, and positive predictive value of Campylobacter stool antigen

188 Positive predictive value of CMV PCR in saliva was 59%;

189 e images (at least 1 of the 3 features), the positive predictive value of confocal microscopy was 87.

190 The positive predictive value of DSE was calculated for each

191 Positive predictive value of DSE was similar for patient

192 Sensitivity, specificity, and positive predictive value of hepatic USG for detecting a

193 The sensitivity, specificity, and positive predictive value of hepatic USG for findings th

194 For instance, the positive predictive value of International Classificatio

195 ponents can masquerade as TCFA and cause low positive predictive value of IVOCT for TCFA detection (4

196 ion PFP achieved a sensitivity of 0.82 but a positive predictive value of only 0.53.

197 Positive predictive value of recall and positive predict

198 Recall rate, biopsy rate, positive predictive value of recall, positive predictive

199 The positive predictive value of tissue transglutaminase typ

200 The sensitivity, specificity, and positive predictive value of ultrasound in diagnosing de

201 The sensitivity and positive predictive value of Xpert MTB/RIF in culture-ne

202 We found positive predictive values of 1.0 (95% confidence interv

203 c >0.80) for prediction of preeclampsia, and positive predictive values of 4% in the largest, most ap

204 However, the very good negative and good positive predictive values of iPET support its use in da

205 However, the low positive predictive values of symptoms elicited in prima

206 Despite the increased risk, the positive predictive values of this symptom cluster were

207 ults represent a 169-fold improvement in the positive predictive value over previous attempts.

208 FLT PET/CT had a significantly higher positive predictive value (PPV) (91%) in predicting resi

209 te per 1000 screens, 0.8 (95% CI: 0.7, 0.8); positive predictive value (PPV) 1, 4.4% (95% CI: 4.3%, 4

210 entifies children with celiac disease with a positive predictive value (PPV) above 99% in clinical pr

211 s >/= 0.80 for sensitivity, specificity, and positive predictive value (PPV) among females, 6 and 10

212 The sensitivity, specificity, positive predictive value (PPV) and diagnostic OR of alg

213 the equation had a sensitivity, specificity, positive predictive value (PPV) and negative (N) PV of 7

214 The positive predictive value (PPV) and negative predictive

215 We calculated the positive predictive value (PPV) and negative predictive

216 ons from RNA-Seq data, including the highest Positive Predictive Value (PPV) compared to the current

217 We assessed sensitivity, specificity, and positive predictive value (PPV) for current medication u

218 The positive predictive value (PPV) for rayon swabs was 78.7

219 The positive predictive value (PPV) for recall was almost do

220 icrocalcifications, MR imaging increased the positive predictive value (PPV) from 17.5% (21 of 120 ca

221 the positive likelihood ratio is 9.9 and the positive predictive value (PPV) is 7.0%.

222 algorithm 1) had a sensitivity of 0.40 and a positive predictive value (PPV) of 0.96 for heart failur

223 sitivity of 85.86%, specificity of 100%, and positive predictive value (PPV) of 100% for detecting ca

224 atients had confirmed AH, corresponding to a positive predictive value (PPV) of 54% (95% CI 47-60%).

225 edictive value (NPV) of 88%-91% and 86%-89%, positive predictive value (PPV) of 60%-70% and 62%-75%,

226 ates of minor response of 70% and 75%, and a positive predictive value (PPV) of 71% [95% confidence i

227 sitivity of 91.9%, a specificity of 90.7%, a positive predictive value (PPV) of 74.0%, and a negative

228 84.7), specificity of 99.3% (98.6 to 99.7), positive predictive value (PPV) of 93.3% (86.8 to 97.3),

229 ).MRI showed a high sensitivity of 93.7% and positive predictive value (PPV) of 96.7% when correlated

230 retation rate, 12.6% (95% CI: 12.5%, 12.7%); positive predictive value (PPV) of a biopsy recommendati

231 The main outcome was the positive predictive value (PPV) of ICD-9 codes for ident

232 ditional cancers, as well as specificity and positive predictive value (PPV) of MR imaging screening.

233 specificity, area under the curve (AUC), and positive predictive value (PPV) of the revised ASRS.

234 The positive predictive value (PPV) of the Xpert Norovirus a

235 y either clinical history of reactivity, 95% positive predictive value (PPV) or challenge, corrected

236 measured at age 1 and 4 years that have 95% positive predictive value (PPV) or negative predictive v

237 uished from APS with 94% specificity and 96% positive predictive value (PPV) using the original 2-lev

238 (NPV) was 0.92 (95% CI: 0.75, 0.99), and the positive predictive value (PPV) was 0.93 (95% CI: 0.75,

239 Incidence of IMLN and positive predictive value (PPV) were calculated on a per

240 Sensitivity and positive predictive value (PPV) were determined for the

241 ne sequencing, the sensitivity, specificity, positive predictive value (PPV), and negative predictive

242 th nested PCR, the sensitivity, specificity, positive predictive value (PPV), and negative predictive

243 antibody detection sensitivity, specificity, positive predictive value (PPV), and negative predictive

244 come measures were sensitivity, specificity, positive predictive value (PPV), and negative predictive

245 was used to derive sensitivity, specificity, positive predictive value (PPV), and negative predictive

246 overall accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive

247 Sensitivity, specificity, positive predictive value (PPV), and negative predictive

248 ation demonstrated sensitivity, specificity, positive predictive value (PPV), and negative predictive

249 0% to 83%; specificity, from 86% to 94%; and positive predictive value (PPV), from 3% to 8%.

250 rmance in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive val

251 agnostic accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive val

252 Concordance rates, sensitivity, specificity, positive predictive value (PPV), negative predictive val

253 agnostic accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive val

254 ith 81% sensitivity, 87% specificity and 93% positive predictive value (PPV).

255 at the gene signature predicts RIF with 100% positive predictive value (PPV).

256 nd 1000 Genomes (1KG; 84.1%) and the highest positive predictive value (PPV; 96.1%) for a random samp

257 tion year, we investigated the incidence and positive predictive values (PPV) of C4d-CD68 and pAMR gr

258 The sensitivity and positive predictive values (PPV) of the AAML0531 AE repo

259 Sensitivity, specificity, and positive predictive values (PPV) of the codes were calcu

260 copies/ml, the sensitivities, specificities, positive predictive values (PPV), and negative predictiv

261 high risk (score >/=6, 4.8% of total cohort, positive predictive value [PPV] 11.7%), those at low ris

262 The sensitivity, specificity, positive predictive value [PPV] and negative predictive

263 I), 53-83]; specificity, 62 [95% CI, 62-68]; positive predictive value [PPV], 24 [95% CI, 16-32]; neg

264 9-containing, carbapenem-resistant isolates (positive predictive value [PPV], 78%).

265 agnostic accuracy (sensitivity, specificity, positive predictive value [PPV], and negative predictive

266 ovarian cancer consistently resulted in low positive predictive values (PPVs) and false-positive rat

267 We calculated positive predictive values (PPVs) and negative predictiv

268 on, the number of positive test results, and positive predictive values (PPVs) for advanced neoplasia

269 ecall rate, cancer detection rate (CDR), and positive predictive values (PPVs) for digital mammograph

270 Positive predictive values (PPVs) of these determinants

271 r operating characteristic curves [AUCs] and positive predictive values [PPVs].

272 The low positive predictive value suggests that further clinical

273 ortantly, the presence of cfDNA had a higher positive predictive value than that of currently used pr

274 Moreover, the presence of ctDNA had a higher positive predictive value than that of six tumor biomark

275 ntitative PLR < 13% had 100% specificity and positive predictive value to predict poor recovery (0% f

276 ing diabetic eye disease, the IRIS algorithm positive predictive value was 10.8% (95% CI, 9.6%-11.9%)

277 The positive predictive value was 11% and the negative predi

278 .9% in the prospective validation, while the positive predictive value was 11.1%.

279 s 55.6 % and 96.2 %, respectively, while the positive predictive value was 16.4 % and negative predic

280 The positive predictive value was 33.3% (95% CI, 25.6%-45.5%

281 tivity was 50%, the specificity was 71%, the positive predictive value was 54%, and the negative pred

282 The positive predictive value was 70% (95% CI 60.5-73.5), wh

283 Lesion-level overall positive predictive value was 70.5%.

284 97%), specificity was 85% (95% CI, 75%-92%), positive predictive value was 72% (95% CI, 61%-90%), and

285 gative predictive value was 81%, and overall positive predictive value was 74%.

286 The positive predictive value was 78.6% (95% CI, 60.5%-89.8%

287 specificity for endoscopy were 74% and 85%, positive predictive value was 81%, and negative predicti

288 ty for ASD was 21%, specificity was 98%, and positive predictive value was 86%.

289 , specificity was 90% (nine of 10 patients), positive predictive value was 95% (21 of 22 patients), n

290 However, the positive predictive value was modest for both algorithms

291 41.6%, respectively, while the negative and positive predictive values were 86.1% and 65.6%, respect

292 By applying a cutoff >/=69.72, positive predictive values were 92% and 89% in the deriv

293 .6% and 73.5% (P = 0.001), respectively; and positive predictive values were 94.2% and 89.3%, respect

294 tection rates, sensitivity, specificity, and positive predictive values were calculated for both mamm

295 es overlapped between cases and controls and positive predictive values were poor (<3%).

296 m based on troponin I levels provided a high positive predictive value with 82.8% (95% CI, 73.2%-90.0

297 Only minor improvement was found in the positive predictive values with additional follow-up of

298 5%) than with DBT-FFDM (61.3%, P = .01), and positive predictive values with DBT-s2D mammography (40.

299 insensitive but were the best performers for positive predictive value, with the highest positive pre

300 nity-based practice improved recall rate and positive predictive values without loss of cancer detect