ライフサイエンスコーパス: demographics

1 with postmortem tau pathology adjusting for demographics.

2 , sexual behaviours, treatment scale-up, and demographics.

3 health, economics, conflict, migration, and demographics.

4 y, vaccine coverage, treatment dynamics, and demographics.

5 include shifts in body sizes and population demographics.

6 The 2 groups showed similar patient demographics.

7 erized each Tweet relative to estimated user demographics.

8 formed CD4 cell count, drug use, and patient demographics.

9 we estimated indications for PrEP for MSM by demographics.

10 fferences persisted after adjusting clinical demographics.

11 sensitivity to high temperatures and future demographics.

12 aire on general and dental health, diet, and demographics.

13 n-diagnosed thyroid disease), behaviors, and demographics.

14 , use of cleaning chemicals, and participant demographics.

15 Baseline demographics, AAL history, age-adjusted Charlson comorbi

16 m birth between 2008 and 2012, adjusting for demographics, access to care, and general health service

17 , 1.18-3.30; p < 0.009]) after adjusting for demographics, Acute Physiology and Chronic Health Evalua

18 We also examined demographics-adjusted difference in differences in APC b

19 ted with relatively high CD8 counts included demographics (age </= 40 years, adjusted P = 0.010) and

20 etained in multivariable models adjusted for demographics (age, sex, race/ethnicity, and income level

21 ; and (3) untreated depression adjusting for demographics, AMI severity, and clinical factors.

22 agnosed dry eye disease (DED) and associated demographics among US adults aged >/=18 years.

23 comorbidities, laboratory test results, and demographics, among others.

24 and around the globe as a result of shifting demographics and aging populations.

25 bases that contain patient data from diverse demographics and ancestries.

26 istically significant differences in patient demographics and baseline characteristics among the 4 tr

27 Patient demographics and baseline QOL scores were comparable bet

28 (ORs) and 95% CIs were adjusted for patient demographics and baseline risk factors.

29 The relationship of demographics and cardiovascular risk factors to LA size

30 ased nutrient levels resulting from changing demographics and climatic impacts on hydrology that driv

31 Results Pre-TIPS demographics and clinical characteristics of the two gro

32 utine diagnostic turbidimetry and related to demographics and clinical course during a follow-up of 6

33 Patient demographics and clinical examination findings were coll

34 Demographics and clinical factors were modeled in a deri

35 After adjustment for demographics and clinical factors, including incident he

36 After adjustment for demographics and clinical factors, women had a persisten

37 Demographics and clinical findings were analyzed at base

38 Beyond the effects of cortisol, demographics and clinical symptoms, NR3C1 variation pred

39 PDR prevalence was calculated by demographics and codon, stratifying by prior ARV experie

40 Changes in population demographics and comorbid illness prevalence, improvemen

41 They were individually matched by demographics and comorbidities to a Medicare enrollee wi

42 tal mortality and length of stay adjusted by demographics and comorbidities.

43 d descriptive statistics were calculated for demographics and costs.

44 In models adjusting for individual-level demographics and county-level socioeconomic characterist

45 The associations of demographics and CRP with vitamin D were determined, fol

46 We obtained baseline demographics and data for alcohol consumption (units per

47 and corresponding uncertainty on population demographics and dietary habits from National Health and

48 cognition and assess whether the effects of demographics and each neuropathologic index on cognition

49 Baseline demographics and imaging of patients with suspected coro

50 Patient factors (demographics and indications for tracheal intubation), p

51 trauma patients selected by matching patient demographics and injury characteristics.

52 tructed to incrementally account for patient demographics and injury mechanism, followed by injury se

53 unt trauma patients may present with similar demographics and injury severity yet differ with regard

54 Diabetes article, we emphasize that changing demographics and lifestyles over the past few decades ha

55 with hypertrophic cardiomyopathy matched for demographics and maximum wall thickness (60.1+/-14.8 yea

56 ive memory impairment in models adjusted for demographics and medical comorbidities (29% versus 24%;

57 Patient demographics and medical history including current medic

58 required to establish the role of all tests, demographics and phenotypes in diagnosis.

59 e was no difference between groups regarding demographics and predisposing factors for PSH.

60 Staff demographics and previous exposure to dementia training

61 These include current workforce demographics and projections, evolving health care and p

62 We evaluated demographics and risk factors for ZIKV infection among o

63 HIV-1-infected individuals sharing a similar demographics and route of infection, compared the differ

64 lation of each weekly observation to compare demographics and seasonality of nonallergic conjunctivit

65 t, fat mass, and fatfree mass in addition to demographics and smoking partially attenuated associatio

66 Demographics and socioeconomic status should not be nece

67 orted the P-indexes of participants based on demographics and states like Missouri and Massachusetts

68 assessed data integrity for common baseline demographics and study endpoints, including hospital mor

69 Apart from demographics and the APOE genotype, only midlife dyslipi

70 itical care medicine physician assistants on demographics and the full 22-question Maslach Burnout In

71 bled a cross-sectional analysis of physician demographics and training and practice characteristics a

72 The patient demographics and treatment received were comparable.

73 Changes in demographics and treatments may affect the prevalence an

74 Patients with liver LELC display distinctive demographics and tumor characteristics.

75 In multivariable modeling, including patient demographics and type of injury, helicopter transport pr

76 trol continuum, with respect to investigator demographics and use of theory, technology, policy, and

77 In multivariate models adjusted for demographics and vascular risk factors, higher levels of

78 controlling for surgeon, department, patient demographics, and clinical indicators in a mixed-effects

79 me, with subgroup analyses by surgical risk, demographics, and comorbidities.

80 To determine the national estimates, demographics, and costs of inpatient eye care in the Uni

81 l function (visual acuity and visual field), demographics, and disease characteristics was assessed u

82 dermoscopically) SK-like melanomas, patient demographics, and interobserver agreement of criteria we

83 t to characterize its prevalence, associated demographics, and motivations.

84 Using household locations, demographics, and prevalence data from a survey of four

85 ves provided information on insecticide use, demographics, and reproductive history at enrollment in

86 ics of both cohorts are presented, including demographics, and structural and functional retinal metr

87 Clinical predictors included demographics, anthropometrics, cardiac and blood measure

88 Demographics, anticoagulation practices, severity of ill

89 Data including demographics, antimicrobial and immunosuppression regime

90 We collected data for baseline demographics, antithrombotic therapy, and clinical outco

91 We evaluated predictors including demographics, APOE, intellectual enrichment, midlife ris

92 tes of population dynamics, but age-specific demographics are generally lacking for many long-lived i

93 e reaching childbearing age and the changing demographics associated with advancing maternal age.

94 Intern data including demographics, attendance at US or Canadian medical schoo

95 We adjusted models for demographics, baseline eGFR, urine albumin-to-creatinine

96 We obtained questionnaire data on demographics, behaviour, and residential malaria risk fa

97 ubject variability might be easy to measure (demographics, behavioural scores, or experimental factor

98 Data collected included patient demographics, best-corrected visual acuity, and OCT feat

99 There was no difference in baseline demographics between recipients with and without RHF.

100 d LTL using linear regression, adjusting for demographics, blood cell count and distribution, and ano

101 Patient demographics, brain biopsy technique, histopathology and

102 Demographics, burn size, concomitant injuries, and morta

103 change after patient groups were matched for demographics, but decreased to 4.9% (47% relative decrea

104 We exemplify an application of stock demographics by characterizing the composition and servi

105 ) using a Cox model, adjusting for age, sex, demographics, cardiovascular risk factors, and apolipopr

106 tivariable regression analyses adjusting for demographics, cardiovascular risk factors, and left vent

107 We adjusted for demographics, cardiovascular risk factors, eGFR, and uri

108 We corrected for demographics, cell composition, and multiple testing (Be

109 otective effect remained after adjusting for demographics, clinic type, abnormal baseline cervical cy

110 Patient demographics, clinical Alvarado scoring, CT images, and

111 After obtaining patient informed consent, demographics, clinical and health-related quality of lif

112 Demographics, clinical characteristics, and imaging base

113 Data on demographics, clinical characteristics, and outcomes wer

114 Demographics, clinical characteristics, and sputum cytol

115 x models adjusted for potential confounders (demographics, clinical characteristics, comorbidities, a

116 nst all-cause mortality after accounting for demographics, clinical characteristics, human immunodefi

117 SSIs and those without SSIs were similar in demographics, clinical characteristics, length of hospit

118 Demographics, clinical data, and health literacy were co

119 We extracted demographics, clinical data, invasive hemodynamics, echo

120 llected by chart review and included patient demographics, clinical examination findings, and history

121 For this cohort we described demographics, clinical features, and pathogenic variants

122 Demographics, clinical history, presentation, and in-hos

123 A chart review yielded demographics, clinical information, and 5 categories of

124 clinical spectrum of the disorder, including demographics, clinical manifestations, imaging features,

125 Baseline demographics, clinical status, and hospital course were

126 Patient demographics, clinical variables, and outcome data were

127 Adjusting for demographics, cohort, hypertension, diabetes, hyperlipid

128 Baseline demographics, comorbid conditions, clinical risk scores,

129 ivariable Cox regression models adjusted for demographics, comorbid conditions, lifestyle and disabil

130 ty (25% versus 6%), but after accounting for demographics, comorbidities accounted for more variation

131 adjusted for multiple confounders including demographics, comorbidities, and admission characteristi

132 The 2 groups had similar demographics, comorbidities, and clinical signs.

133 n is influenced by CLI presentation, patient demographics, comorbidities, and in-hospital complicatio

134 Other variables of interest included demographics, comorbidities, and other risk factors for

135 After adjustment for demographics, comorbidities, and procedural characterist

136 Differences in patient characteristics, demographics, comorbidities, and reason for admission be

137 sess trends in outcomes after adjustment for demographics, comorbidities, and symptomatic status.

138 s were comparable to the PiB- individuals on demographics, comorbidities, cognition, hippocampal volu

139 All other variables (ie, demographics, comorbidities, medications, tear film fact

140 Baseline differences in demographics, comorbidities, objective disease measures,

141 There were no differences between cohorts in demographics, comorbidities, pathology, pancreatic duct

142 and the hospital, and adjusting for patient demographics, comorbidities, presence of cirrhosis, and

143 Patient demographics, comorbidities, presenting symptoms and vis

144 We examined changes in patient demographics, comorbidities, procedure use, and risk-adj

145 All models were adjusted for patient demographics, comorbidities, severity of illness, clinic

146 idney transplantation, controlling for year, demographics, comorbidities, socioeconomic factors, and

147 Demographics, comorbidities, surgical procedures, and ho

148 re-adjusted analysis, which included patient demographics, comorbidity status, and clinical T stage,

149 estimate the contribution of differences in demographics, comorbidity, insurance, tumor characterist

150 y hormone receptor status for each variable (demographics, comorbidity, insurance, tumor characterist

151 inuation, and hospitalization controlled for demographics, comorbidity, modality, and residence.

152 Rapidly changing population demographics complicate this relationship, however.

153 care, were examined separately in regard to demographics, complications of hemophilia and its treatm

154 usted for potentially confounding variables (demographics, current socioeconomic status, body mass in

155 acid diethylamide (LSD) and magic mushrooms; demographics, current well-being and past-year problemat

156 derly individuals, with information on socio-demographics, daily habits, and medical characteristics.

157 Demographics, death-to-preservation time, ECD, lens stat

158 In analysis adjusted for demographics, diabetes, and hypertension, having zero or

159 We sought to describe the changing demographics, diagnoses, and outcomes of patients admitt

160 Data extracted included patient demographics, diagnoses, length of stay, circumstances,

161 nicity and hospital mortality, adjusting for demographics, diagnosis, pre-extracorporeal life support

162 Demographics, disease characteristics, and healthcare re

163 thout necrosectomy) and 22 factors regarding demographics, disease severity (eg, Acute Physiology And

164 and prey with respect to temporal abundance, demographics, distribution, and diet.

165 Thus, assuming that demographics do not change incidence, the calculated tot

166 Participant demographics, drug use, and risk behaviours were assesse

167 Demographics, duration of symptoms and proton pump inhib

168 on model of CVD and country-specific data on demographics, epidemiology, SSB consumption, and short-t

169 ltivariable analysis included adjustment for demographics, ethnicity, cardiovascular risk factors, se

170 Patient demographics, etiology of ALF, and laboratory values wer

171 Data were collected regarding demographics, etiology of cataract, method of undercorre

172 Demographics explained more variation in readmissions th

173 ize material stocks, defined herein as stock demographics, exploring the insights that this approach

174 All groups were similar for baseline demographics, extent of resection, presence of residual

175 nary clinical evaluation, including clinical demographics, genetic testing, symptom evaluation, neuro

176 Population demographics, geography, and hospital and physician pres

177 Population demographics, geography, and hospital and physician pres

178 my, there were no differences in the patient demographics, geography, or disease types treated with a

179 my, there were no differences in the patient demographics, geography, or disease types treated with a

180 By use of regression analyses adjusted for demographics, gross and microscopic infarcts, and Alzhei

181 Medical records were reviewed for demographics, Hanifin & Rajka (H&R) and United Kingdom W

182 ciated with incident AMI after adjusting for demographics (hazard ratio [HR], 1.31; 95% CI, 1.05-1.62

183 ed the association of QOL with self-reported demographics, health behaviors, physical impairments, su

184 sity and sleep duration (covariates included demographics, health behaviours, and health problems) in

185 ional hazards regression models adjusted for demographics, health factors that differed between group

186 Demographics, health history, and HbA1c levels were retr

187 Covariates included demographics, history of cataract surgery, refractive er

188 Covariates included demographics, hospital course (e.g., lowest hematocrit,

189 s were interviewed to collect information on demographics, household characteristics, and healthcare

190 There were similar intergroup demographics; however, significantly more bleeders had a

191 Baseline demographics (ie, aspirin use, smoking, body mass index,

192 ents that permit the representation of plant demographics in ESMs, and identify issues raised by thes

193 Patient demographics, in-hospital, and 30-day outcomes data were

194 nt (following antibiotic treatment); patient demographics including 8- and 70-day mortality were coll

195 ted in cancer survivors after accounting for demographics (including age), myocardial fibrosis risk f

196 ing generalized linear models, adjusting for demographics, individual and area-level measures of soci

197 Data collected included demographics, infections, transfusions, and outcomes.

198 Demographics, injury-related scores, prehospital, and re

199 ty and patient-specific risk factors such as demographics, insurance, smoking, comorbidities, and con

200 ability to adjust for comorbid conditions or demographics known to impact fibrosis progression in NAF

201 Demographics, laboratory values, and medical history at

202 variables were curated centrally, including demographics, laboratory values, medical history, lesion

203 ittle information exists regarding survival, demographics, late outcomes, and comorbidities in this e

204 information about spill-related activities, demographics, lifestyle, and health.

205 ltivariable linear regression, adjusting for demographics, lifestyle, and metabolic factors including

206 nfected participants-and after adjusting for demographics, lifestyle, and metabolic factors-HIV monoi

207 uninfected adults, even after adjusting for demographics, lifestyle, metabolic factors, and hepatic

208 We control for physician demographics (like age, gender, and religiosity), patien

209 ransplantation recurrence were compared with demographics, liver function, basic immune markers, trea

210 PAI suitability maps were based on wild bird demographics, LPAI surveillance, and poultry density in

211 y aims was to characterise variations in the demographics, management, and outcome of patients with A

212 This review describes the demographics, management, and outcomes of a large cohort

213 ailable about the geo-economic variations in demographics, management, and outcomes of patients with

214 for death in black versus white women in the demographics-matched model was 2.05 (95% CI, 1.94 to 2.1

215 uggest that automated systems for monitoring demographics may effectively complement labor-intensive

216 art transplantation (HT) donor and recipient demographics may influence the incidence of primary graf

217 In Cox regression models (adjusted for demographics, measured GFR, proteinuria, body mass index

218 vel logistic regression model, adjusting for demographics, mechanism, vital signs, and injury severit

219 Eighty patients were enrolled with similar demographics: median age 67 years, 41% high-risk Rai dis

220 Patient demographics, medical and medication history, and clinic

221 Measurements included self-reported demographics, medical and smoking history, and lung canc

222 those without TBI even after adjustment for demographics, medical comorbidities, and active depressi

223 groups using regression models adjusting for demographics, medical comorbidities, and depression.

224 s are asked to complete questionnaires about demographics, medical history, health habits, and QOL.

225 bles analyzed included aggregate beneficiary demographics, Medicare payments to ophthalmologists, oph

226 n pooled multivariate analyses adjusting for demographics, metabolic risk factors, lifestyle, diet, a

227 duals in California, according to individual demographics, neighborhood socioeconomic environment, an

228 multinomial transition models adjusting for demographics, nonrenal organ failure, sepsis, prior ment

229 he nest distribution patterns and population demographics of a native ant species, Formica obscuripes

230 ifetime prevalence, patterns, and associated demographics of heroin use and use disorder from 2001-20

231 nd produce rapid unanticipated shifts in the demographics of pest complexes.

232 ited States reported on the racial or ethnic demographics of study participants.

233 Demographics of subjects such as age and sex; descriptio

234 f suspected SCFE, especially considering the demographics of the affected population.

235 The demographics of the emerging critical care physician wor

236 The demographics of the HIV epidemic in the USA have shifted

237 esholds varied predictably with the spectral demographics of the surrounding cones.

238 Amid the changing demographics of the US population and the rising rates o

239 ving an oncology workforce that reflects the demographics of the US population it serves.

240 The 1054 patients reflected the demographics of those treated in this timeframe (75% mal

241 Results: The 1054 patients reflected the demographics of those treated in this timeframe (75% mal

242 underreporting, undertreating, or differing demographics of those with eye disease.

243 tecture of the air network, historical ties, demographics of travellers, and malaria endemicity contr

244 imaging, and the potential effect of reader demographics on agreement with a preselected nonconsecut

245 were no significant differences in baseline demographics or transplant data among the 4 neutralizing

246 The changing donor demographics, organ utilization, and outcomes associated

247 ception month, humidity, site, sex, maternal demographics, parity, insurance, prepregnancy body mass

248 Patient demographics, patient disease, and the ability to access

249 ary diagnosis of cellulitis as a function of demographics, payer, location, patient severity, admissi

250 mpleted a self-administered survey assessing demographics, perceived severity of glaucoma, prior know

251 Main outcome measures included demographics, perioperative details, wound complications

252 class model was constructed on the basis of demographics, phenotypes and test results from patients

253 Data included demographics, preinjury health, injury characteristics,

254 Data collected included patient demographics, preoperative and postoperative best-correc

255 ociation of postoperative CDI with patients' demographics, preoperative comorbidities, operative char

256 n BIA-ALCL, such as pathophysiology, patient demographics, presentation, diagnosis, treatment, and ou

257 nce interval 1.13, 1.48) after adjusting for demographics, prevalent cardiovascular disease, cardiova

258 We examined trends in demographics, primary diagnosis, and outcomes among pati

259 Data collected included patient demographics, primary lesion characteristics, operative

260 ustering method were associated with subject demographics, questionnaire results, medication history,

261 the second year and was not associated with demographics, recent malaria, health facility testing ch

262 Factors of interest were demographics, recommended interval length, comorbidities

263 oncentration >1 g/L) and covariates, such as demographics, reported illness, and anthropometric statu

264 of women enrolled in a cohort study compares demographics, risk behaviour, and sexually transmitted i

265 noted significant geographical variations in demographics, risk factors for ARDS, and comorbid diseas

266 Against the backdrop of shifting demographics, risk factors for brain injury in the CHD p

267 (1990-1992) through 2013 with adjustment for demographics, risk factors, a latent variable for glycem

268 After adjusting for demographics, risk factors, and the latent variable for

269 After adjusting for demographics, risk factors, and treatments, those with a

270 was used, integrating US population-specific demographics, risk factors, background therapy, and even

271 a multivariable analysis including baseline demographics, risk factors, coronary anatomy, and left v

272 Patient demographics (sex, age, race/ethnicity, and insurance ty

273 Information abstracted included demographics, signs and symptoms, laboratory results, an

274 Baseline data included demographics, smoking history, and computed tomography e

275 contact with STEC-contaminated environments, demographics, socioeconomic status, and immunity.

276 mild, HEV can be severe or fatal in certain demographics, such as expectant mothers.

277 Methods Data from demographics, survival, diagnoses codes, procedure codes

278 remission over and above the contribution of demographics, symptom severity, ELS, and amygdala reacti

279 characteristics that were examined included demographics, systemic comorbidities, and ocular comorbi

280 es during the 3-year period, including donor demographics, time from death to refrigeration and prese

281 Patient demographics, time to organism identification, time to e

282 Patient demographics, transfer status, type of repair, and intra

283 Risk factors assessed included baseline demographics, treatment, and ocular characteristics on i

284 Mortality rates were examined by patient demographics, tumor characteristics, and hospital proced

285 Groups were similar in demographics, tumor characteristics, and treatment detai

286 formation regarding the influence of patient demographics, tumor characteristics, and treatment type

287 Data were collected on patient demographics, tumor features, and specific diagnoses to

288 ups of ATRTs, associated with differences in demographics, tumor location, and type of SMARCB1 altera

289 abstracted and categorized study population demographics, type of intervention, and primary and seco

290 e Community (EPIC) study, adjusting for age, demographics, underlying conditions, and smoking status

291 Patient demographics, US and MR imaging findings, and clinical a

292 Information on demographics was obtained by a questionnaire.

293 s Survey scores and health care professional demographics were collected as independent data.

294 Demographics were comparable: median age, 67 years; 77%

295 h care insurance, income quartile, and other demographics were described.

296 Baseline demographics were similar but significant differences we

297 The subject demographics were well balanced across groups; 99% of th

298 Baseline demographics were well balanced among the cohorts.

299 ved volasertib and 55 received chemotherapy; demographics were well balanced.

300 ve approaches, with the potential to measure demographics with fine spatial resolution, in close to r