ライフサイエンスコーパス: poor outcome

1 type of ALL in adults and is associated with poor outcome.

2 st frequent type of ovarian cancer and has a poor outcome.

3 , p38, STAT1, and STAT5 were associated with poor outcome.

4 drug resistance frequently occurs leading to poor outcome.

5 th decreased necrosis and apoptosis preceded poor outcome.

6 (total PSOM score <1) and 39/78 (50%) had a poor outcome.

7 y be encountered, which is associated with a poor outcome.

8 g identified subgroups of patients with very poor outcome.

9 tion (EMT), and PDX1 loss is associated with poor outcome.

10 0 years, nearly 30% of patients experience a poor outcome.

11 A. fumigatus DNAemia was associated with poor outcome.

12 years or > 10 years was not associated with poor outcome.

13 ncreased frequency of distant metastases and poor outcome.

14 tal cancer (mCRC) and may be associated with poor outcome.

15 ary aspergillosis (IPA) is associated with a poor outcome.

16 indicators of resistance to chemotherapy and poor outcome.

17 cerbate brain inflammation and contribute to poor outcome.

18 olid tumors is a hallmark of progression and poor outcome.

19 ver transaminase levels at baseline indicate poor outcome.

20 l axes that are proportionate to the risk of poor outcome.

21 its association with aggressive disease and poor outcome.

22 valve replacement and was associated with a poor outcome.

23 thought to contribute to disease relapse and poor outcome.

24 ociated with high-risk genetic subgroups and poor outcome.

25 nly interval increase in PHE correlated with poor outcome.

26 nosis of post-anoxic coma are informative of poor outcome.

27 sion models adjusted for known predictors of poor outcome.

28 loid leukemia (AML) and is associated with a poor outcome.

29 rearrangement sites, older diagnosis age and poor outcome.

30 NUP214 chimeric gene, and has a particularly poor outcome.

31 n 1 (MRP-1) in Ewing's sarcoma (ES) predicts poor outcome.

32 d glucose with delayed cerebral ischemia and poor outcome.

33 4 patients (29%), and 106 patients (39%) had poor outcome.

34 ociated with malignant tumor progression and poor outcome.

35 ctive infection contributed to high cost and poor outcome.

36 children and adults, and is associated with poor outcome.

37 esources despite a predicted and often known poor outcome.

38 TEN correlates with increased PTK6 PY342 and poor outcome.

39 g breast cancer, and usually correlates with poor outcome.

40 uld be associated with cancer recurrence and poor outcome.

41 heterozygosity at HLA-I was associated with poor outcome.

42 ic phase of dependence, which contributes to poor outcome.

43 e associated with disease aggressiveness and poor outcome.

44 egarding factor V values are predictive of a poor outcome.

45 outcome while retaining high sensitivity for poor outcome.

46 d elevated levels of HP1gamma in PCa predict poor outcome.

47 egative and cognitive symptoms contribute to poor outcome.

48 ficantly associated with advanced stages and poor outcome.

49 ts with cirrhosis, and is a warning sign for poor outcome.

50 s with infection who are at elevated risk of poor outcomes.

51 advanced donor age is considered a risk for poor outcomes.

52 ophil migration, potentially contributing to poor outcomes.

53 ion of patients with newly diagnosed MM with poor outcomes.

54 lung, heart, and sleep functions to improve poor outcomes.

55 o be the best discriminator between good and poor outcomes.

56 are consequence of breast RT associated with poor outcomes.

57 mong hemodialysis (HD) patients is linked to poor outcomes.

58 ademic year is assumed to be associated with poor outcomes.

59 bjects have more rapid cognitive decline and poor outcomes.

60 for invasive candidiasis (IC) contributes to poor outcomes.

61 LC2A5 or increased fructose utilization have poor outcomes.

62 -DLBCL subtype and is highly correlated with poor outcomes.

63 a serious breathing disorder associated with poor outcomes.

64 calcitrant to treatment, and associated with poor outcomes.

65 abolism but largely lack treatments and have poor outcomes.

66 Posttransplant smoking is associated with poor outcomes.

67 tatic group 3 patients do not uniformly have poor outcomes.

68 e in the number of patients with good versus poor outcomes.

69 4; P = .003) as independent risk factors for poor outcomes.

70 rred rarely, it was strongly associated with poor outcomes.

71 s who receive conventional chemotherapy have poor outcomes.

72 aracteristics that result in higher risks of poor outcomes.

73 loid leukemia (AML) and a FLT3 mutation have poor outcomes.

74 bial resistance may result in bacteremia and poor outcomes.

75 stenosis is linked to renal dysfunction and poor outcomes.

76 tivated B-cell DLBCL (ABC-DLBCL) and predict poor outcomes.

77 combinations have been able to improve these poor outcomes.

78 tion pneumonia is also associated with these poor outcomes.

79 acute kidney injury (AKI) is associated with poor outcomes.

80 ecifically, AKI) is a strong risk factor for poor outcomes.

81 ndependent contribution of each condition to poor outcomes.

82 ts and better understanding why elderly have poor outcomes.

83 iomarker in PAH with the capacity to predict poor outcomes.

84 dren with moderate to severe latent RHD have poor outcomes.

85 depressant medication is common and leads to poor outcomes.

86 rved for those with severe presentations and poor outcomes.

87 ium keratitis is common and often results in poor outcomes.

88 Patient characteristics did not predict poor outcomes.

89 as been associated with an increased risk of poor outcomes.

90 o identify MALT lymphoma patients at risk of poor outcomes.

91 y to or relapse after ibrutinib therapy have poor outcomes.

92 te IPF exacerbations and are associated with poor outcomes.

93 = 0.007) was found to significantly predict poor outcomes.

94 ve historically been turned down for fear of poor outcomes.

95 markers could improve risk stratification of poor outcomes.

96 ults, due to lack of experience and previous poor outcomes.

97 indicating that low ScvO2 is associated with poor outcomes.

98 s shutdown is common postinjury and predicts poor outcomes.

99 ssociated with reduced exercise capacity and poor outcomes.

100 t patients, approximately 1 in 3 still had a poor outcome 1 year after TAVR.

101 L had high specificity and sensitivity for a poor outcome (100% and 83%;P= .015).

102 ding: (1) screening for patients at risk for poor outcomes, (2) integrating patient- and family-repor

103 groups with relatively low predicted risk of poor outcome (25%-50% risk): Case Fatality Rate of 21% i

104 w patients with concurrent DEL and DHL had a poor outcome (4-year PFS, 0%).

105 timal were over 2-fold more likely to report poor outcomes; 52% and 26% more likely to report that th

106 of miR-124-3p were higher in patients with a poor outcome (8408 [12 465] copies/microL) compared with

107 yed cerebral ischemia-related infarction and poor outcome (a modified Rankin Scale score of 4, 5, or

108 ma was associated with DNA demethylation and poor outcome; a group of IDH-wild-type diffuse glioma sh

109 In addition, its mRNA expression predicted poor outcome across breast cancer subtypes.

110 ents with chronic lymphocytic leukaemia with poor outcome after first-line chemoimmunotherapy.

111 , serial NSE values are strong predictors of poor outcome after OHCA.

112 Poor outcome after TAVR was defined as death, poor quali

113 Dialysis dependence has been associated with poor outcomes after CEA in small studies, but, to our kn

114 gery in the last weeks of life, high risk of poor outcomes after emergency operations in these patien

115 ational Prognostic Index [m7-FLIPI]) and for poor outcomes after frontline therapy (National LymphoCa

116 Bleeding is associated with poor outcomes after percutaneous coronary intervention (

117 arge B-cell lymphoma (DLBCL) associated with poor outcomes after standard chemoimmunotherapy.

118 eloped to identify patients at high risk for poor outcomes after transcatheter aortic valve replaceme

119 Here we determine if patients with poor outcomes after trauma have dysregulated lipid media

120 geted temperature management toward good and poor outcomes, along with other recognized predictors.

121 OR 2.63, CI 1.10 to 6.25), while the odds of poor outcome also increased with greater PHE growth (OR

122 ycosis (IWM) is associated with an extremely poor outcome among critically ill burn patients.

123 ored and unmonitored patients (odds ratio of poor outcome among those who underwent ICP monitoring, 1

124 The mechanisms linking inequality to poor outcomes among individuals are poorly understood.

125 kidney injury biomarkers are associated with poor outcomes among KTRs.

126 Among ischemic stroke, elevated odds of poor outcomes among transferred patients remained after

127 t specific risks factors are predictive of a poor outcome and are important to identify.

128 n of ARF in the nucleolus is associated with poor outcome and attenuated response to chemotherapy.

129 ombocytopenia is independently predictive of poor outcome and describe the incidence and time course

130 sustained immune dysfunction responsible for poor outcome and nosocomial infections.

131 GFAP concentrations also strongly predicted poor outcome and performed better than S100B and MBP.

132 ignature correlated with known predictors of poor outcome and retained independent prognostic capacit

133 Currently, GBM has an extremely poor outcome and there is no effective treatment.

134 the clinical data linking hyperkalemia with poor outcomes and discusses how the efficacy of certain

135 s of endometrial cancer, is characterized by poor outcomes and mutations in the tumour suppressor p53

136 SCCs), a finding that unveils new markers of poor outcomes and potential targets for therapeutic inte

137 LE: Fibrosis after lung injury is related to poor outcome, and idiopathic pulmonary fibrosis (IPF) ca

138 Esophageal adenocarcinoma (EAC) has a poor outcome, and targeted therapy trials have thus far

139 sk of developing a psychiatric disorder, but poor outcomes are not inevitable.

140 history who go on to have recurrences and a poor outcome as they mature.

141 week 1 of S100B and NSE were associated with poor outcome, as were highest concentration overall and

142 Whether poor outcome associated with cannabis use is mediated th

143 erability and may underlie the wide range of poor outcomes associated with early adversity.

144 to adequate prenatal care may contribute to poor outcomes associated with preeclampsia in African Am

145 The poors outcomes associated with pancreatic cancer clearly

146 ; QOL decline, 2.0%) and 50.8% experienced a poor outcome at 1 year (death, 30.2%; poor QOL, 19.6%; Q

147 tom severity at 1 year as risk factors for a poor outcome at 5 years, with an area under the curve of

148 Increased tau was associated with poor outcome at 6 months after cardiac arrest (median =

149 inued access registries, 31.2% experienced a poor outcome at 6 months following TAVR (death, 17.6%; v

150 Cumulative incidence of poor outcome at 6, 12, and 18 months was 13.9%, 18.4%, a

151 lase serum concentrations reliably predicted poor outcome at ICU discharge.

152 Poor outcomes at hospitals are frequent and associated w

153 malignant astrocytoma and is associated with poor outcomes because of heterogeneous tumour cell popul

154 The relative risk of these poor outcomes below these peak concentration thresholds

155 ed Rankin Scale outcome and none worsened to poor outcome between postarrest months 1 and 6 (p = 0.06

156 Delirium in the ICU is associated with poor outcomes but is under-detected.

157 lood lactate at admission is associated with poor outcome, but after aneurysmal subarachnoid hemorrha

158 thout associated shutdown was not related to poor outcome, but extreme HF (LY30 >30%, n = 3) was leth

159 of intracerebral haemorrhage (ICH) predicts poor outcome, but the significance of delayed intraventr

160 of intracerebral haemorrhage (ICH) predicts poor outcome, but the significance of delayed intraventr

161 circulatory death (DCD) livers is limited by poor outcomes, but its application may be expanded by ex

162 r first-episode psychosis is associated with poor outcomes, but the causal nature of this association

163 of associations between the mPICH score and poor outcome cohorts were assessed (C statistics, Hosmer

164 negative fluid balances are associated with poor outcome compared to patients with even fluid balanc

165 Tau improved prediction of poor outcome compared to using clinical information (p <

166 monosomy 7 (NCK-7) independently predicted a poor outcome, compared with RBM15/MKL1-rearranged patien

167 Poor outcome could be predicted at a threshold of 0.34 w

168 riables tested were strongly associated with poor outcome (CSF culture positivity, CSF white blood ce

169 against genotoxic chemotherapy (del17p) and poor outcome (del11q and del17p).

170 identify patients with a high probability of poor outcome, despite aggressive treatment.

171 mmunosuppression is the major determinant of poor outcomes during ART, baseline inflammation is an ad

172 youngest and oldest age groups had similarly poor outcomes even when a targetable genotype was presen

173 go transplant survive, but adults have quite poor outcomes even with aggressive management.

174 ion is a potentially modifiable predictor of poor outcome following an acute intracerebral hemorrhage

175 adequate cardiac output is associated with a poor outcome following cardiac surgery and is generally

176 between reduced brain tissue oxygenation and poor outcome following severe traumatic brain injury has

177 nth retention rates seldom exceeding 50% and poor outcomes following dropout, we must explore innovat

178 lue of 7 different frailty scales to predict poor outcomes following TAVR or SAVR.

179 egative hepatitis is a clinical indicator of poor outcome for chronic hepatitis B viral (HBV) infecti

180 of cavin-1 represents the major mechanism of poor outcome for PDAC patients with the CA19-9 signature

181 In this issue of Blood, Martin et al report poor outcomes for ibrutinib-refractory patients with man

182 tunities for further reducing the persisting poor outcomes for infected critically ill patients.

183 ired genotype correlates with metastasis and poor outcomes for patients, and is associated with intra

184 Two predictors of poor outcomes for STEC-infected children were identified

185 n are known to be common and associated with poor outcomes for women and their children.

186 ibility to bacterial infections and predicts poor outcome from sepsis.

187 rculating tumor cells (CTCs) correlated with poor outcomes from the use of abiraterone and enzalutami

188 658, respectively) and identified those with poor outcomes (GOS-E, </=4 vs >4) (AUC = 0.771 and 0.777

189 From the results, in AIS, patients with a poor outcome had lower levels of triiodothyronine (T3) a

190 the time delay most strongly associated with poor outcomes has not been defined.

191 ccurred in 1.9% (1.7-2.1), with an immediate poor outcome in 5.4% (3.7-7.5) of these cases.

192 en associated with loss of consciousness and poor outcome in a range of acute neurologic disorders.

193 plification is significantly associated with poor outcome in activated B-cell-like and BCL2 transloca

194 ntrol, dIVH is independently associated with poor outcome in acute small to moderate-size ICH.

195 lin A (IgA) autoantibodies are predictors of poor outcome in AHA.

196 tion (yellow fever, malaria, influenza), but poor outcome in autoimmune and inflammatory disease (typ

197 IKZF1 (encoding IKAROS) are associated with poor outcome in B lineage acute lymphoblastic leukemia (

198 actor, whose over-expression is a marker for poor outcome in cancers.

199 a spliceosome component, are associated with poor outcome in chronic lymphocytic leukemia (CLL), but

200 As myocardial dysfunction contributes to poor outcome in critically ill patients, we wanted to as

201 mmunohistochemistry (IHC) is associated with poor outcome in diffuse large B-cell lymphoma (DLBCL).

202 ocytopenia is an independent risk factor for poor outcome in extracorporeal membrane oxygenation pati

203 ated B-cell-like and BCL2 translocation with poor outcome in germinal center B-cell subtypes, respect

204 The poor outcome in high risk NB is largely attributed to th

205 g Gstp1 and Gstz1, which are associated with poor outcome in human neuroblastoma.

206 D1-regulated gene expression module predicts poor outcome in human prostate cancer.

207 on of GPC5 was significantly associated with poor outcome in lung adenocarcinoma.

208 ZNF322A was an independent risk factor for a poor outcome in lung cancer, corroborating the Kaplan-Me

209 ssociated with delayed cerebral ischemia and poor outcome in multivariable analyses with either lacta

210 asome subunit suppression is associated with poor outcome in myeloma patients, where proteasome inhib

211 ALK is now known to be a marker of poor outcome in neuroblastoma, and therefore, urgent dev

212 o inversely correlated prognostic factors of poor outcome in neuroblastoma.

213 pneumonia is thought to be associated with a poor outcome in patients with community acquired pneumon

214 l growth factor C (VEGFC) is associated with poor outcome in primary CRC.

215 and antibiotic resistance as associated with poor outcome in S. epidermidis ODRI.

216 l protein whose expression is prognostic for poor outcome in several cancers.

217 tion (a clinically-established biomarker for poor outcome in TBI) and decrease in OCR.

218 athoadrenal activation, endotheliopathy, and poor outcome in trauma has only been demonstrated in sma

219 pathoadrenal activation, endotheliopathy and poor outcome in trauma patients.

220 , nuclear YAP expression was associated with poor outcome in UCC patients who received perioperative

221 sation registry to identify risk factors for poor outcomes in adult patients with community-acquired

222 Poor outcomes in ARN were common in this cohort.

223 hod to risk-stratify severity of disease and poor outcomes in both children and adults, respectively,

224 NA in clinical specimens was a biomarker for poor outcomes in chemotherapy-treated RMS patients.

225 Metabolic acidosis is associated with poor outcomes in CKD.

226 and glycemic variability are associated with poor outcomes in critically ill patients.

227 pertension (PH) contributes significantly to poor outcomes in diverse pediatric diseases, approaches

228 High expression of CCAR2 correlates with poor outcomes in many human tumor types such as squamous

229 eptor tyrosine kinase Axl is associated with poor outcomes in pancreatic cancer (PDAC), where it coor

230 1-C-induced gene expression patterns predict poor outcomes in patients.

231 g transcriptomic profile predictive of these poor outcomes in SCD.

232 ted an association between nonwhite race and poor outcomes in small subsets of cardiac surgery patien

233 lmonary hypertension (PH) is associated with poor outcomes in the dialysis and general populations, b

234 Results suggest that inequality may promote poor outcomes, in part, by increasing risky behavior.

235 with LMNA cardiomyopathy is associated with poor outcomes including high rate of arrhythmia recurren

236 These changes are associated with poor outcomes including low birthweight delivery and mat

237 r adjusting for established risk factors for poor outcome, including poor admission clinical grade (a

238 Continued cannabis use predicted poor outcome, including risk of relapse, number of relap

239 CLL cells harboring features associated with poor outcomes, including 17p deletion and unmutated IGHV

240 dney injury is common and is associated with poor outcomes, including increased mortality, among crit

241 This "genomic storm" can lead to poor outcomes, including Multiple Organ Dysfunction Synd

242 howed that the signature was associated with poor outcome independently of well-defined prognostic fa

243 talizations for recurrent congestion portend poor outcomes independently of age and renal function.

244 ey features of systemic inflammation and its poor outcome is closely associated with exacerbated syst

245 keratitis who are at risk of experiencing a poor outcome may be useful to allocate resources toward

246 concern of excessive hematologic toxicity or poor outcomes may not be justified with appropriate dosi

247 r progressive disease prior to surgery had a poor outcome (median OS, 5.7 [95% CI, 2.6-10.8] and 3.9

248 All 11 patients older than 75 years had poor outcomes (mRS score >3) at 90 days.

249 ables have very low false positive rates for poor outcome, multimodal assessment provides resassuranc

250 zures at onset of AIS were associated with a poor outcome (Odds Ratio 3.5 95% CI 1.16-10.6).

251 ctate showed an independent association with poor outcome (odds ratio, 1.42; 95% CI, 1.11-1.81).

252 ognized that major roles of platelets in the poor outcome of cancer patients occurs during hematogeno

253 ion correlates with clinical progression and poor outcome of cancer patients.

254 and STAT4 overexpression was associated with poor outcome of ovarian cancer patients, which promoted

255 ys in pancreatic tumor cells may improve the poor outcome of pancreatic ductal adenocarcinoma (PDA).

256 and MondoA coregulated genes correlates with poor outcome of patients with diverse cancers.

257 evels in NSCLC patients, and correlates with poor outcome of patients with lung adenocarcinoma.

258 ociated with a more aggressive phenotype and poor outcome of patients, although more specific signatu

259 ors to target CSC plasticity and improve the poor outcome of PDAC patients.

260 dherence to medication is a salient cause of poor outcomes of health care and a primary driver of gro

261 oup of aggressive non-Hodgkin lymphomas with poor outcomes on current therapy.

262 Odds ratio (OR) for predicting poor outcome or standardized mean difference (SMD) of th

263 urate identification of patients at risk for poor outcomes or drug-related adverse effects, will ulti

264 significantly associated with infarct size, poor outcome, or death.

265 a subset of patients negative for T790M with poor outcomes (ORR, 25%; PFS, 2.8 months).

266 between the observed and predicted risks of poor outcome (P = .46).

267 n-specific enolase greater than 90 mug/L and poor outcome patients with neuron-specific enolase less

268 Mutations predict a poor outcome, probably as a result of impaired mitochond

269 ification, and independently associated with poor outcomes, providing a rationale for chromosomal los

270 emerged as the most strongly associated with poor outcome, regardless of ER status.

271 performance of the previously developed TAVR Poor Outcome risk models in an external dataset and expl

272 Although discrimination of the TAVR Poor Outcome risk models was generally moderate, calibra

273 We tested 4 TAVR Poor Outcome risk models: 6-month and 1-year full and cl

274 nxiety was not significantly associated with poor outcomes, screening for posttransplant anxiety shou

275 a and insulin resistance are associated with poor outcomes, studies should focus on how long these pr

276 rcinoma (HCC) is an independent predictor of poor outcomes subsequent to surgical resection or liver

277 ould benefit from tailored services to avoid poor outcomes such as death and loss to follow-up.

278 nts with well-characterised risk factors for poor outcomes such as high disease activity, presence of

279 ssociated with delayed cerebral ischemia and poor outcome, suggesting that they may be considered in

280 ical risk factors and are more predictive of poor outcomes than the rate of development of hyponatrem

281 otherapy is an early event associated with a poor outcome that may deserve intensive salvage with aut

282 oxia metagene signature is associated with a poor outcome to endocrine treatment in ERalpha(+) breast

283 es have identified patients at high risk for poor outcomes to first-line therapy (m7-Follicular Lymph

284 idly identified as being more likely to have poor outcomes typical of sepsis if they have at least 2

285 We sought to evaluate the frequency of poor outcomes using a novel composite measure that integ

286 sted Circulatory Support) national registry, poor outcome was defined as death or an average Kansas C

287 The accuracy of the score for prediction of poor outcome was evaluated (sensitivity, specificity).

288 Poor outcome was predicted by a loss of effective contra

289 The most predictive factor of poor outcome was the degree of bile duct loss on liver b

290 as developed after variables associated with poor outcome were identified at multivariate analysis (K

291 pecificity and sensitivity for prediction of poor outcome were independent of age, sex, and initial r

292 Patients who had a poor outcome were more likely to have higher body mass i

293 vival and HER2-enriched breast tumors have a poor outcome when Akt is upregulated.

294 th triple-negative breast cancer (TNBC) have poor outcome when pathologic complete response (pCR) is

295 ldren with MLL-rearranged BCP-ALL who have a poor outcome when treated with chemotherapy only.

296 identified several factors associated with a poor outcome, which may inform discussions before LVAD i

297 Among 1638 patients with LVAD, 29.7% had a poor outcome, with death in 22.4% and persistently poor

298 on of older trauma patients at high risk for poor outcomes, with the potential for targeted intervent

299 atin-spliceosome and TP53-aneuploidy AML had poor outcomes, with the various class-defining mutations

300 Neural invasion is associated with poor outcome, yet its mechanism remains unclear.