ライフサイエンスコーパス: patient characteristics

1 e intervals of ERG expression in relation to patient characteristics.

2 calculator to report outcomes by region and patient characteristics.

3 stic regression models adjusted for selected patient characteristics.

4 s using a model based on routinely available patient characteristics.

5 igated their relation to stroke severity and patient characteristics.

6 on of mechanical ventilation using ICU day 1 patient characteristics.

7 ) while accounting for baseline preoperative patient characteristics.

8 mber of postbaseline assessments and several patient characteristics.

9 eting behavior-change interventions based on patient characteristics.

10 teristics such as follow-up style superseded patient characteristics.

11 etermine how these phenotypes are related to patient characteristics.

12 previous studies was hampered by dissimilar patient characteristics.

13 ssociations between observation and selected patient characteristics.

14 between placebo-response rates and study and patient characteristics.

15 ost periods, while adjusting for confounding patient characteristics.

16 ublic holidays after adjustment for standard patient characteristics.

17 ed with provider practice patterns than with patient characteristics.

18 st levels, respectively, after adjusting for patient characteristics.

19 after APCD purchase, adjusting for baseline patient characteristics.

20 he amount of fibrosis was unrelated to CV or patient characteristics.

21 s may be optimized by considering individual patient characteristics.

22 t the HbA1C distribution based on individual patient characteristics.

23 ction by race/ethnicity, adjusting for other patient characteristics.

24 administration, the underlying disease, and patient characteristics.

25 detection of histologic HSIL, regardless of patient characteristics.

26 ovarian cancer and to evaluate the impact of patient characteristics.

27 apted to each individual, including relevant patient characteristics.

28 justed for 8 physician characteristics and 4 patient characteristics.

29 ter, physician random effects, and admission patient characteristics.

30 complications, adjusting for other important patient characteristics.

31 sk-standardized to account for variations in patient characteristics.

32 extent to which treatment was determined by patient characteristics.

33 ain and anxiety, but not illness severity or patient characteristics.

34 ts performed medical record review to obtain patient characteristics.

35 and propensity score methods to control for patient characteristics.

36 soriasis treatment responses are affected by patient characteristics.

37 actice type and service characteristics, and patient characteristics.

38 yses explored effect variations by trial and patient characteristics.

39 n by practice were calculated, adjusting for patient characteristics.

40 g dabigatran dose after considering selected patient characteristics.

41 e and after adjusting for other hospital and patient characteristics.

42 but this was attenuated after adjustment for patient characteristics.

43 n only partly be explained by differences in patient characteristics.

44 eatitis was not associated with any baseline patient characteristics.

45 e used depending on physician preference and patient characteristics.

46 using a risk calculator based on nodule and patient characteristics.

47 haracteristics, ex vivo characteristics, and patient characteristics.

48 w-intensity prescribers, with adjustment for patient characteristics.

49 val exists and is associated with individual patient characteristics.

50 e in mortality and readmission rates, beyond patient characteristics.

51 Descriptive statistics examined patient characteristics.

52 provider practice even after adjustment for patient characteristics.

53 bility were high, with no differences due to patients' characteristics.

54 ity to capture what providers do rather than patients' characteristics.

55 s based on symptom profiles which related to patients' characteristics.

56 change over time, adjusted for hospital and patient characteristics, 0.90; 95% confidence interval [

57 ration of therapy was determined by baseline patient characteristics: 4 or 6 weeks for treatment-naiv

58 After adjusting for patient characteristics, 57 hospitals (26%) were identif

59 When taken together, hospital and patient characteristics accounted for 12% (lower extremi

60 Though previous work has examined how patient characteristics affect sleep medication prescrip

61 ce overall survival; however, differences in patient characteristics affected the treatment received.

62 ble logistic regression, with adjustment for patient characteristics (age, measured body mass index,

63 by Cox proportional hazards regression with patient characteristics (age, sex, and Mini-Mental State

64 , we examined the impact of sociodemographic patient characteristics (age, sex, education, income, an

65 In vivo and ex vivo features, as well as patient characteristics (age, weight, height, body mass

66 sease stage (including myometrial invasion), patients' characteristics (age and comorbidities), and n

67 no differences between groups with regard to patient characteristics: age (P = 0.78), underlying dise

68 not improve risk adjustment models based on patient characteristics alone.

69 he DonateLife Audit on the basis of baseline patient characteristics alone.

70 ficant differences were found in hospital or patient characteristics among high, intermediate, or low

71 liomas and compared acquired alterations and patient characteristics among the five primary molecular

72 or treatment-by-subgroup interactions for 16 patient characteristics and 6 care-delivery characterist

73 Patient characteristics and adverse events were studied

74 After adjusting for patient characteristics and center volume, HBHs still ha

75 between severity and sensitization patterns, patient characteristics and clinical history, and to dev

76 Baseline patient characteristics and clinical outcomes were colle

77 Patient characteristics and clinical presentations were

78 sion analysis to assess associations between patient characteristics and clinical worsening.

79 ysis showed no correlation between high-risk patient characteristics and composite complication rate.

80 e hypothesized that daily activity varies by patient characteristics and correlates with established

81 ith regimen and dose variations according to patient characteristics and country.

82 lear whether NMR status is consistent across patient characteristics and current treatment choice.

83 ized incidence of endocarditis and trends in patient characteristics and disease etiology.

84 able from 1998 through 2013, with changes in patient characteristics and etiology over this time.

85 ALY, with ICER of $413579 per QALY for trial patient characteristics and event rate of 4.2 per 100 pa

86 Patient characteristics and findings at colonoscopic sur

87 it could also clarify relationships between patient characteristics and health care provider outcome

88 based on a relatively simple combination of patient characteristics and hemodynamics.

89 Adjusting for patient characteristics and illness severity, patients i

90 Patient characteristics and in-hospital mortality were c

91 in 2005-2010, accounting for differences in patient characteristics and influenza virulence.

92 Patient characteristics and intensity of care were extra

93 ine any significant difference in mortality, patient characteristics and mortality data from the Nati

94 We assessed temporal trends in patient characteristics and outcomes among older patient

95 litative analyses were performed to identify patient characteristics and outcomes associated with pot

96 The patient characteristics and outcomes were recorded.

97 c and culture order combinations in terms of patient characteristics and outcomes.

98 iographic laboratory investigators masked to patient characteristics and outcomes.

99 tient Register to retrieve information about patient characteristics and outcomes.

100 ivariable models adjusted for differences in patient characteristics and PCI volume.

101 Patient characteristics and procedural data and complica

102 The patient characteristics and procedures performed were si

103 rmed a discrete event simulation to forecast patient characteristics and rate of waitlist dropout.

104 Baseline patient characteristics and reaction results were analyz

105 Patient characteristics and recurrence-free survival rat

106 cation may enhance tailoring of treatment to patient characteristics and response.

107 The relationships between various patient characteristics and the appropriateness ratings

108 evaluated the distribution and frequency of patient characteristics and the need for invasive therap

109 mited by an absence of a measure of frailty, patient characteristics and treatment intensity suggest

110 Baseline patient characteristics and treatment outcomes were reco

111 n was used to assess the association between patient characteristics and utilization.

112 Patient characteristics and vital signs prior to cardiac

113 We describe the baseline patient characteristics and well-defined outcomes for ma

114 medical offices with diverse geographic and patient characteristics and whether long-term BP control

115 After controlling for patient characteristics and workload we found that highe

116 The study analyzed patients' characteristics and 30-day outcomes by LOS (sh

117 We identified seven independent preoperative patients' characteristics and comorbidities in our adult

118 Understanding if links exist between patients' characteristics and GERD symptoms, and classif

119 Patients' characteristics and hematologic tests data at

120 Patients' characteristics and outcomes after extracorpor

121 Tumor genotype, patient characteristics, and clinical outcomes were coll

122 nal outcome depends on calcification extent, patient characteristics, and immediate results of PMC.

123 Tailor treatment to tumor biology and patient characteristics, and offer active surveillance t

124 Demographics, patient characteristics, and operative factors were simi

125 e overall trends in CRT device implantation, patient characteristics, and outcomes were examined in d

126 cted on vital signs at admission to the ICU, patient characteristics, and outcomes.

127 quality and extracted data on study design, patient characteristics, and outcomes.

128 e the incidence rate of massive transfusion, patient characteristics, and the mortality of massively

129 ssociations between gene mutations, clinical patient characteristics, and therapeutic outcomes in thi

130 vestigators abstracted data on study design, patient characteristics, and virologic and safety outcom

131 ble logistic regression was used to identify patient characteristics as potential barriers to receivi

132 gistic regression model was used to identify patient characteristics associated with meeting the tria

133 Patient characteristics associated with receiving an ICD

134 act logistic regression revealed no specific patient characteristics associated with relapse.

135 We identified selected hospital and patient characteristics associated with short-term adver

136 rral, percentage of completed referrals, and patient characteristics associated with varying levels o

137 was no significant difference in observable patient characteristics at the 37 hospitals meeting the

138 Patient characteristics at the time of presentation in t

139 Patients' characteristics at baseline were similar betwe

140 es for study characteristics, interventions, patients' characteristics at baseline, and outcomes for

141 Patients' characteristics at ICU admission and their out

142 5, which were compared in terms of study and patient characteristics, baseline risk, outcome definiti

143 s accommodated a propensity score to balance patient characteristics between the groups.

144 Differences in patient characteristics between the lowest and highest q

145 Differences in patient characteristics between the MSSP and control gro

146 ned the distribution of demographic data and patient characteristics between those receiving ranibizu

147 hma patient cohorts, identified a variety of patient characteristics, but they also consistently iden

148 Here we describe hemodialysis prevalence and patient characteristics by sex, compare the adult male-t

149 We adjusted for patients' characteristics by fitting a multivariable gen

150 rolled the participants, and incentives) and patient characteristics (cancer type, patient or parent

151 Baseline patient characteristics, clinical care, and volumes of i

152 To describe patient characteristics, clinical manifestations, diseas

153 However, after adjusting for patient characteristics, comorbidities, and operation ty

154 Secondary outcomes included patient characteristics, complications, treatments, and

155 Differences in patient characteristics, demographics, comorbidities, an

156 Patient characteristics derived from review of the elect

157 tients with full data collection, we studied patient characteristics (descriptively) and mortality (v

158 After adjusting for patient characteristics, diabetes was associated with hi

159 We summarized patient characteristics, diagnoses, and costs from SEER-

160 Patient characteristics did not predict poor outcomes.

161 treatment, we aimed to assess any effect of patient characteristics, disease characteristics, or tre

162 the prevalence of common drug allergies and patient characteristics documented in EHRs of a large he

163 1998 to 2011 and retrieved data on tumor and patient characteristics, drug use, and primary treatment

164 terrelated and also associated with baseline patient characteristics (eg, age>/=75 years, hypertensio

165 e more accurately than did simple antecedent patient characteristics (eg, age, sex, or chronic health

166 DATA EXTRACTION: Baseline patient characteristics, enrollment time, methodology of

167 There were no differences in patient characteristics except for a higher proportion o

168 compare resistance patterns, serotypes, and patient characteristics for Salmonella isolated from blo

169 ICU and hospital characteristics outweighed patient characteristics for stress ulcer prophylaxis (om

170 e as a function of the injected hormones and patient characteristics has been developed and validated

171 critical event in tumor development, yet few patient characteristics have been identified that can be

172 linical trials, therapies guided by specific patient characteristics have had better outcomes than pr

173 o 50.9%]), with multivariable adjustment for patient characteristics having little effect (interquart

174 Patient characteristics (high age and risk score) and ho

175 Patient characteristics, hospital course, and complicati

176 Main Outcomes and Measures: Patient characteristics, hospital course, and complicati

177 Independent variables were patient characteristics, hospital type, unit type, nurse

178 Logistic regression, controlling for patient characteristics, identified full adoption of ele

179 Confounders included (i) patients' characteristics; (ii) associated surgical proc

180 ore the possible effects of trial design and patient characteristics in accounting for the contrastin

181 compare the incidence of specific high-risk patient characteristics in each group.

182 A EXTRACTION: Two authors abstracted data on patient characteristics in exposed and control groups; u

183 After accounting for patient characteristics in propensity-adjusted analyses,

184 Patient characteristics in the 2 cohorts were similar.

185 Patient characteristics in the NIS OCEAN were evaluated

186 stic regressions were carried out to compare patient characteristics, incident AVF frequencies, and c

187 Patient characteristics included age, sex, comorbidity s

188 losses in the subregions differ by tumor and patient characteristics including race/ethnicity.

189 Descriptive statistics were used to define patient characteristics, including age, prostate-specifi

190 s, we collected information on caregiver and patient characteristics, including caregiver depressive

191 distribution regression models adjusted for patient characteristics, including chronic conditions an

192 Patient characteristics, including diagnoses in the emer

193 This paper describes patient characteristics, including Ebola viral load, ass

194 intake is easily estimated through access to patient characteristics, independent of world regions, a

195 Patient characteristics influenced the clinical decision

196 Sensitivity analyses explored the effects of patient characteristics, institutional/surgeon volumes,

197 For the primary analysis, patient characteristics, interventions, and outcomes wer

198 tly, and criteria do not specify how to take patient characteristics into account.

199 Study design, quality, patient characteristics, length of follow-up, and outcom

200 Patients' characteristics, long-term surveillance and fo

201 Patients were categorized by patient characteristics (marital status, educational lev

202 measured differences in clinic structure and patient characteristics may have partially contributed t

203 ferent clinical settings with exploration of patient characteristics, measurement techniques, and out

204 f PHS on outcomes is independent of baseline patient characteristics, medical comorbidities, quality

205 Patient characteristics modifying the associations and p

206 Treatment was modestly related to patient characteristics (Nagelkerke R range, 0.12-0.52)

207 onably complete data for a limited number of patient characteristics, namely age, sex, and ethnicity;

208 Compared to the patient characteristics of published RCTs (trials select

209 hic and clinical characteristics of enrolled patients, characteristics of participating centers, and

210 The effects of patient characteristics on adenosine dose required to pr

211 tered outcomes, and the influence of various patient characteristics on antipsychotic effectiveness.

212 The effects of many clinical and patient characteristics on neurocognitive functioning ha

213 luence of the study year and other trial and patient characteristics on the response rates through me

214 Data were collected on patient characteristics, operative, and postoperative fa

215 oximal anterior circulation, irrespective of patient characteristics or geographical location.

216 ose was to evaluate the associations between patient characteristics or surgical site classifications

217 These effects were independent of dose, patient characteristics, or aetiology of TIA or stroke.

218 howed no clear effects of technical factors, patient characteristics, or comparator interventions on

219 Patient characteristics, outcome measures, treatment reg

220 izations in the United States and to compare patient characteristics, outcomes, and comorbid diagnose

221 ds, which account for potentially unmeasured patient characteristics, patients undergoing laparoscopi

222 Baseline patient characteristics, performance measures, and in-ho

223 tracted data included study characteristics, patient characteristics, plug type, insertion technique,

224 Specific patient characteristics predicted prescription of aspiri

225 Patient characteristics, preoperative baseline data, dur

226 Patient characteristics, prescription-related clinical f

227 After adjusting for relevant patient characteristics, presence of clinical pharmacist

228 In this study, we describe key patient characteristics present within 4 hours of emerge

229 Recovery trajectories differed by patient characteristics, providing valuable information

230 DAPT duration was on the basis of patient characteristics, rather than stent characteristi

231 To account for differences in patients' characteristics recorded daily before study en

232 After adjusting for patient characteristics, relative to low-volume hospital

233 disparities are attributed to both tumor and patient characteristics, requiring an individualized app

234 d more frequent testing after adjustment for patient characteristics, risk factors, and provider char

235 veral risk factors are predictive, including patient characteristics, sedative exposure, additional s

236 ife vignette with five experimentally varied patient characteristics: setting, alimentation, pain, co

237 Patient characteristics significantly influence the phys

238 een race and mortality rates, accounting for patient characteristics, socioeconomic status, and hospi

239 We abstracted data on patient characteristics, stroke, mortality, and adverse

240 his is not fully explained by differences in patient characteristics such as age, sex, or comorbiditi

241 At other times patient characteristics such as health literacy supersed

242 the evaluation of calf DVT may be limited by patient characteristics such as obesity, edema, and tend

243 Furthermore, patient characteristics, such as age and renal function,

244 ic characteristics in combination with other patient characteristics, such as early onset, cuticular

245 d across practices, even after adjusting for patient characteristics, suggesting that quality improve

246 main covariate after adjusting for baseline patient characteristics, surgery type, and admission hem

247 This study sought to identify patient characteristics, surgical interventions, institu

248 Patient characteristics, surgical technique, intraoperat

249 atures are more consistent with contemporary patient characteristics than in previous prostate cancer

250 Little is known about the patient characteristics that affect physician-assessed q

251 trument controls for unobserved and observed patient characteristics that affect the outcome.

252 Purpose To explore provider and patient characteristics that influence how primary care

253 Moreover, patient characteristics that influence responsiveness to

254 ed patients represent a complex admixture of patient characteristics that result in higher risks of p

255 Two RCTs found no patient characteristics that were associated with outcom

256 The aim of this study was to identify patients' characteristics that may predict failure and r

257 In 3-level models adjusted for patient characteristics, the percentage of patients who

258 In analyses accounting for patient characteristics, the risk ratio for achieving su

259 We studied caregiver and patient characteristics to determine which characteristi

260 By providing a mechanistic framework to link patient characteristics to the risk of resistance, these

261 emotherapy-related hospitalization-including patient characteristics, treatment characteristics, and

262 lity of MRD surrogacy for PFS across diverse patient characteristics, treatment regimens, and differe

263 Data were collected on patient characteristics, treatment, and 6-month Glasgow

264 Information on patient characteristics, treatment, MRD assessment, and

265 This annual report focuses on patient characteristics, trends, and outcomes of transca

266 AFP level was evaluated against patient characteristics, tumour characteristics and surv

267 es: Information extracted included study and patients characteristics, type of intervention and data

268 t hoc analysis, between-study differences in patient characteristics, use of various d-dimer assays,

269 Adding patient characteristics was of limited additional predic

270 ble logistic regression models to adjust for patient characteristics, we examined the relationship be

271 redict outcome better than do simple pre-ICU patient characteristics, we measured the timing of this

272 After adjusting for patient characteristics, we used hierarchical logistic r

273 Patient characteristics were balanced between arms, in w

274 both the N3I1 and the N1I3 arm, and baseline patient characteristics were balanced between arms.

275 Baseline patient characteristics were compared by indication with

276 ontributions of resuscitation parameters and patient characteristics were evaluated.

277 Associations between symptoms and baseline patient characteristics were examined with chi(2) and Fi

278 ared, and multivariable models adjusting for patient characteristics were fit.

279 Differences in patient characteristics were found between the biologics

280 of trials was limited, and study designs and patient characteristics were heterogeneous.

281 Mortality rates adjusted for patient characteristics were higher for all minority gro

282 Baseline patient characteristics were investigated to determine d

283 Patient characteristics were matched.

284 Most patient characteristics were not associated with treatme

285 etween 2006 and 2010, only modest changes in patient characteristics were noted.

286 Patient characteristics were obtained from electronic me

287 Codes pertaining to PCP and patient characteristics were organized into an explanato

288 Patient characteristics were similar although more patie

289 Patient characteristics were similar between groups, exc

290 Results Baseline patient characteristics were similar in both arms.

291 Patient characteristics were similar in both arms.

292 Baseline patient characteristics were similar in those given acet

293 Patients' characteristics were highly biased concerning

294 ear regression models, adjusted for baseline patient characteristics, were used to analyze the effect

295 sk-standardization methodology to adjust for patient characteristics when comparing major adverse out

296 l multivariable analysis with adjustment for patient characteristics where volume was assessed as a c

297 between increased artifact prevalence and 10 patient characteristics, which included age, sex, race,

298 cation rates were risk-adjusted according to patient characteristics with multiple logistic regressio

299 ear model to test the association of various patient characteristics with QoL in rural patients with

300 When adjusted for differences in patient characteristics, young and middle-aged adults ha