ライフサイエンスコーパス: demographic

1 ncreased over time, associated with an aging demographic.

2 ed survey responses on health, behaviour and demographics.

3 ences for individual survival and population demographics.

4 associations with immune parameters and key demographics.

5 le whole-brain RSFC patterns, behaviors, and demographics.

6 2]; P=0.01) in a model adjusted for baseline demographics.

7 rol (p = 0.005), after controlling for socio-demographics.

8 line survey that assessed the following: (1) demographics; (2) social network; (3) perceived stress;

9 and Fisher's exact tests to compare baseline demographics across groups.

10 sson analysis demonstrated secular trends in demographics, admissions, operations, and outcomes in de

11 sed the effect of tumour subtype and patient demographics (age and sex) on prevalence and mortality f

12 usion of bilateral eyes, sample size issues, demographics (age, gender, and ethnicity), and whether s

13 ng tuberculosis by time-period of follow-up, demographics (age, region), and clinical attributes (HIV

14 lowly or fail to persist (termed group-level demographic Allee effects).

15 Data were collected on patient demographics, anatomic characteristics of the RRD, surgi

16 ultiple logistic regression was performed on demographic and anatomic factors.

17 ardiovascular mortality after adjustment for demographic and cardiovascular risk factors, overall and

18 Demographic and clinic characteristics of the participan

19 se in Clinical Care (EMBARC) study completed demographic and clinical assessments, and pretreatment f

20 Demographic and clinical characteristics and outcomes da

21 Demographic and clinical characteristics and self-report

22 Demographic and clinical characteristics and self-report

23 multivariable adjustment for a wide range of demographic and clinical characteristics including comor

24 We compared demographic and clinical characteristics of IC and non-I

25 The demographic and clinical characteristics of this patient

26 ith non-traumatic AKI-RRT cases with similar demographic and clinical characteristics.

27 line concentrations of both lipoproteins and demographic and clinical characteristics.

28 correlations between antibody responses and demographic and clinical characteristics.

29 agnosed with HCC were recruited and provided demographic and clinical data and blood specimens.

30 blood culture capability and matched patient demographic and clinical data from January 2008 through

31 Demographic and clinical data were collected, including

32 Demographic and clinical data were collected.

33 Data included baseline demographic and clinical features, surgical details, and

34 s association and determine the influence of demographic and clinical parameters on both conditions.

35 ented in our cohort and, when accounting for demographic and clinical profile of admission, black pat

36 was consistent across infection subtypes and demographic and clinical subgroups, and remained signifi

37 A combination of demographic and clinical variables is strongly associate

38 ion models to assess the association between demographic and clinical variables, including time to AR

39 ina during the period 2015-2024, using local demographic and consumption data.

40 spanned most of central Europe and exhibits demographic and cultural associations to the Yamnaya cul

41 riodontal procedures, prescribing rationale, demographic and dental practice information, and accepta

42 model incorporated nationally representative demographic and dietary data from National Health and Nu

43 s, Costs, and Trends), incorporated national demographic and dietary data from the National Health an

44 reductive treatment followed immediately by demographic and ecological perturbations, similar to the

45 Our study thus identifies major demographic and functional determinants of species' nich

46 Demographic and genetic consequences are unknown.

47 imited evidence on their relationship across demographic and geographic groups.

48 rhood factors using datasets from successive demographic and health survey conducted between 2010 and

49 ies in sub-Saharan Africa where at least one Demographic and Health Survey was done before and after

50 iptive analyses of cross-sectional data from demographic and health surveys and multiple indicator cl

51 trospective quantitative data analysis using Demographic and Health Surveys from 2000-2016, qualitati

52 ied 716 478 births from 338 223 women in 123 Demographic and Health Surveys from 58 LMICs, of which 9

53 We investigated the completeness of demographic and hospital data, as well as those values r

54 on recent weight and height as well as other demographic and lifestyle data were obtained by standard

55 QR of protein intake was not associated with demographic and lifestyle factors including sex, race, i

56 kers, genome-wide SNP data, and 27 clinical, demographic and lifestyle variables.

57 Demographic and MT characteristics were assessed and com

58 imates of genome-wide genetic variation with demographic and niche modeling to investigate the histor

59 Demographic and ocular variables related to greater PD l

60 We analyzed state identification card demographic and organ donor registration data from 5 sta

61 Demographic and perioperative data were reviewed, and th

62 ong North American psychiatrists, determined demographic and practice characteristics that increase t

63 .5) and in adjusted analyses controlling for demographic and transplant-related covariates and use of

64 Demographic and vascular risk factors and levels of outd

65 ed data about disease severity and household demographics and assets.

66 gnificant after multivariable adjustment for demographics and cardiovascular disease risk factors.

67 Demographics and clinical information were recorded from

68 Multivariate Cox regression adjusting for demographics and clinical measures of vision (low-lumina

69 Patient demographics and disease characteristics of the Asian su

70 ts who developed hepatitis and examined both demographics and inflammatory laboratory values to ascer

71 After adjustment for demographics and lifestyle behaviors, severe obstructive

72 atients and all household contacts to obtain demographics and medical histories.

73 Patient demographics and PP data were collected.

74 All analyses were adjusted for demographics and standard COPD risk factors (primary and

75 All associations were independent of socio-demographics and vascular risk factors (body mass index,

76 R K. pneumoniae from 2011-2018 and collected demographic, antimicrobial exposure, and infection data.

77 iptions, medical history, incarceration, and demographics as strong predictors.

78 ze factors; child's fragility factors; socio-demographic background; obstetric history; obstetric con

79 ges, consisting of 103 subjects with diverse demographic backgrounds.

80 They completed a survey on demographics, barriers to glaucoma medication adherence,

81 There were no differences in demographics, baseline VA, or IOD between groups (P >= .

82 At screening, demographic/behavioral/psychosocial questionnaires were

83 ciated with hospitalization rates, including demographics, blood pressure, estimated glomerular filtr

84 Groups were compared by demographics, body mass index, ophthalmic examination, t

85 le accounting for the complex survey design, demographics, body mass, and time between sleep and echo

86 The most striking finding is that age demographics break the expected self-similarity underlyi

87 We analyzed demographics, cerebrovascular risk factors, clinical fin

88 not sufficiently effective to counter global demographic changes.

89 Demographic characteristics and clinical parameters were

90 for specific regions with varying population demographic characteristics and different levels of adhe

91 This study describes demographic characteristics and hospital bed capacities

92 re attributed to regional SARS-CoV-2 burden, demographic characteristics and obesity with a minor con

93 fy patterns of 30-day readmission by patient demographic characteristics and time after hospitalizati

94 e estimated the association between baseline demographic characteristics and time to ART initiation u

95 performed to assess the association between demographic characteristics of participants with practic

96 oint) and rate-(i.e., temporal change) based demographic characteristics of species representing lowe

97 ater life varies significantly by individual demographic characteristics such as age, sex, and race/e

98 Basic socio-demographic characteristics were collected and participa

99 r family history, ethnic background or other demographic characteristics(2).

100 CV (RNA+) and time to MI while adjusting for demographic characteristics, cardiovascular risk factors

101 Associations between demographic characteristics, diagnosed comorbid conditio

102 hese hospitalizations were examined, as were demographic characteristics, discharge disposition, paye

103 Demographic characteristics, histopathologic features, t

104 and to test any potential associations with demographic characteristics, past diagnoses, and drug pr

105 Data were collected on demographic characteristics, preoperative and postoperat

106 ediction beyond that offered by clinical and demographic characteristics.

107 tal health outcomes were examined, including demographics, characteristics of the cancer-affected chi

108 ive city size distributions from fundamental demographic choices while also explaining consistent var

109 We examined the effect of demographic, clinical, and behavioral factors and the de

110 HIV surveillance data were used to assess demographic, clinical, and behavioral factors for PWID w

111 uartile, adjusted for geographic clustering, demographic, clinical, and hospital characteristics.

112 The aim of the present study is to evaluate demographic, clinical, laboratory, and prognostic charac

113 Demographic, clinical, laboratory, and radiographic data

114 Demographic, clinical, management data (including compli

115 Baseline differences in demographic, clinical, socioeconomic, and hospital-relat

116 Demographic, clinical, treatment, and outcome data were

117 Patient demographics, clinical characteristics, and outcomes wer

118 in the upper airway is influenced by patient demographics, clinical characteristics, comorbidities, o

119 We collected data on demographics, clinical features, and indocyanine green a

120 AD were matched with those receiving IABP on demographics, clinical history, presentation, infarct lo

121 ctober 2015 and March 2020 were reviewed for demographics, clinical presentation, comorbidities, and

122 Materials and Methods The demographics, clinical presentation, injuries, and radio

123 While the impact of demographic-, clinical- and hospital-level factors on ou

124 Sex differences in demographics, clinicopathologic characteristics, and pos

125 ed, laboratory test results, blood pressure, demographic, cognitive, motor, olfactory and affective i

126 This study assessed the demographics, comorbidities, and health care use of adul

127 gy and Cox regression analysis adjusting for demographics, comorbidities, and operative approach.

128 After adjustments for demographics, comorbidities, dialysis vintage, and kidne

129 Relevant data, including demographics, comorbidities, extracorporeal membrane oxy

130 Patient demographics, comorbidities, preoperative laboratory res

131 Demographic compensation arises when vital rates change

132 We discovered demographic compensation in the form of negative correla

133 Even if their contribution to demographic compensation was small, this highlights a pr

134 Hosts with high demographic competence are more likely to act as keyston

135 between pathogen life history traits and the demographic competence of faster-living hosts also has i

136 We introduce the concept of demographic competence to describe the ability of host p

137 ach household head was interviewed to record demographic components of the household, including compo

138 enotype could have negative evolutionary and demographic consequences, potentially reducing adaptabil

139 by evaluating the social, psychological, and demographic correlates of blatant disregard for immigran

140 ework facilitates to quantify the effects of demographic covariates and social mobility on doubling r

141 regression models to adjust for clinical and demographic covariates.

142 population models that account for seasonal demographic covariation using a latent variable.

143 ure, particularly in the Pyrenees, where the demographic crisis was less severe.

144 lly significant difference regarding initial demographic criteria between both groups.

145 Given the difficulties in obtaining demographic data across a species' range, this assumptio

146 ts at 36 +/- 1 weeks' PMA were compared with demographic data and clinical ROP examination performed

147 Model inputs came from demographic data and the literature; 95% uncertainty int

148 In the U.S., demographic data are only available aggregated at county

149 We calibrated the model to country-level demographic data for 1960-2015 (including population gro

150 We used 41 y of demographic data for more than 2,500 brown bears-one of

151 n the TCGA cohort, we evaluated clinical and demographic data from 152 (46%) patients with advanced (

152 We abstracted demographic data from the electronic health record (EHR)

153 on grid cells with geographic, economic, and demographic data from ~65,000 U.S. census tracts.

154 e-specific mortality patterns in tandem with demographic data to map projections of the cumulative ca

155 Demographic data were collected using a questionnaire.

156 Self-reported genetic and demographic data were collected.

157 Case-level clinical and demographic data were integrated with isolate characteri

158 Clinical and socio-demographic data will also be collected.

159 More broadly, the underlying incidence and demographic data, accompanying this paper, will also pro

160 e performed to study the association between demographic data, clinical features, markers of inflamma

161 r clinical variables included diagnostic and demographic data, median values of respiratory variables

162 Demographic data, postoperative outcomes and complicatio

163 Demographic data, presenting complaints and duration, tr

164 Demographic data, TBM severity grade, HIV co-infection s

165 ndent population models built from long-term demographic data, theoretical models, and methods that l

166 on the basis of their baseline clinical and demographic data.

167 -time from observed time-series of infected (demographic) data is an important problem in population

168 We addressed this question using a demographic dataset of female Asian elephants from timbe

169 We use a multigenerational demographic dataset of semi-captive Asian elephants to i

170 story, while demonstrating the importance of demographic-dependent selection in shaping functional ph

171 The aggregate demographic details for study participants were a mean a

172 standing of secular trends of EGS, including demographics, diagnoses, operations, and outcomes.

173 ed global burden of COVID-19, as a result of demographic differences across settings.

174 Despite the demographic differences between the surveillance populat

175 Despite randomization, demographic differences were apparent between the 2 grou

176 66 participants from 1339 households, with a demographic distribution similar to that of the canton o

177 man capital, recent work has argued that the demographic dividend is related to education and has sug

178 Patient demographics, donor cornea source, indications for graft

179 registered before 2018), including baseline demographics, donor, biochemical and clinical data at LT

180 differences in habitat use might have strong demographic effects because mesopredators need to simult

181 we therefore call for increased attention to demographic effects such as aging on plant reproductive

182 routes and barriers that reflect historical demographic events.

183 Identify key demographic factors and modes of follow-up in surgical s

184 Mother and sibling demographic factors associated with increased risk of ad

185 ological age, lifestyle, health-related, and demographic factors in post-menopausal, but not pre-meno

186 racterise the effects of malaria disease and demographic factors on the QT interval in order to impro

187 Information about vision, clinical and socio-demographic factors were extracted from medical records

188 performed Cox regression models adjusted for demographic factors, baseline HIV RNA/CD4 cell counts, A

189 te modeling to explore relationships between demographic factors, HIV disease characteristics, and AR

190 After adjustment for demographic factors, pre-stroke risk factors, and stroke

191 tions were applied to examine the impacts of demographic factors.

192 ychological outcomes with clinical and socio-demographic factors.

193 on, highlighting the fact that both of these demographic features should be considered in interpretin

194 een the geometric measurements and patients' demographic features.

195 Using a demographic forest model, we show that the basal area an

196 randomized into groups matched for baseline demographics, glaucoma status, and baseline IOP.

197 , and patterns of local transmission between demographic groups of resistant and susceptible strains

198 rollment is associated with VS across states/demographic groups.

199 orted falls even after controlling for socio-demographic, health and life-style differences.

200 This case series characterizes the demographics, health services use, and vital status and

201 shape and may, alone or in combination with demographic, histologic, genomic, or proteomic data, be

202 Collected data included demographics, histopathologic details, survival, and rec

203 3) This demographic history allowed for cases of positive natura

204 rosatellite markers to investigate both past demographic history and contemporaneous genetic structur

205 erent environmental conditions and differ in demographic history and genetic composition, characteris

206 of applications from disease association to demographic history estimation.

207 impact of past climate-warming events on the demographic history of an Arctic specialist, we examined

208 e a reliable genetic marker for studying the demographic history of sheep (Ovis aries).

209 ling of weakly deleterious mutations and the demographic history of the outgroup species and ancestra

210 peration, genetic drift (as modulated by the demographic history of the population) and purifying sel

211 we simulated GWAS under realistic models of demographic history.

212 dministered glaucoma patient survey assessed demographics, history of glaucoma, knowledge and rate of

213 d our model using publicly available data on demographics; HIV prevalence by 5-year age bins, sex, an

214 ed cases likely reflects in part the younger demographic; however, Candida endocarditis seen among ap

215 There were no differences in patient demographics, IDH/MGMT mutation status, or treatment.

216 lated by age, sex and according to the Socio-Demographic Index (SDI).

217 Here we analyse demographic information combined with routinely collecte

218 Demographic information was collected using a questionna

219 Demographic information, laboratory data, medical comorb

220 The data provide socio-demographic information, level of concerns about the flu

221 Demographic, laboratory and molecular characteristics we

222 History of knee pain, and socio-demographic, laboratory, and clinical data were recorded

223 Patient demographics, laboratory values, and outcomes were compa

224 ity with risk of incident CKD, adjusting for demographics, lifestyle behaviors, and cardiometabolic c

225 Covariates grouped in terms of demographics, lifestyle factors and co-morbidities and c

226 ed with higher CAD risk after adjustment for demographics, lifestyle factors, and other CAD risk fact

227 REBOA details, demographics, mechanism of injury, complications, and ou

228 carnivores-to understand the behavioral and demographic mechanisms promoting carnivore coexistence i

229 We collected demographics, medical history, and development of new-on

230 Patient demographics, medical history, procedural details, and c

231 Using demographic microsimulation-based estimates of kinship n

232 gration of genome-wide data with spatial and demographic modeling can reveal the timing and spatial e

233 It automates the task of describing complex demographic models (e.g. with divergence times, effectiv

234 aucoma, including factors related to patient demographics, ocular history, and comorbidity.

235 Patient demographics, ocular history, type of drops used, durati

236 e surgery (ACS) with a survey to examine the demographics of ACS surgeons, the exclusionary or biased

237 ve in most locations, although shifts in the demographics of reported cases were still indicative of

238 Comparison of baseline demographics of the unmatched cohort revealed that patie

239 Patient demographics, OFMD imaging, courses, and outcomes were a

240 Data on demographics, oncological history and comorbidities, COV

241 Demographics, operative data, perioperative pain medicat

242 Review of patient demographics, ophthalmologic examination results, and re

243 lly significant increases in KS rates in any demographic or geographic group, nondecreasing/stagnant

244 oups did not differ with respect to baseline demographic or ocular characteristics.

245 Standard methods for estimating demographic parameters from noninvasive genetic samples

246 methods to reliably and efficiently estimate demographic parameters such as population density and tr

247 e contribution of the relevant selective and demographic parameters.

248 ated immunological changes with clinical and demographic parameters.

249 ntal lineages and genomic data both revealed demographic patterns in France for the Neolithic and Bro

250 al records were reviewed to obtain patients' demographics, physical signs, comorbidities, laboratory

251 Patient demographics, procedure details, and clinical outcomes d

252 ironmental drivers and disturbances with the demographic processes of recruitment, growth, and mortal

253 mitigating threats requires knowledge of how demographic processes operate throughout the annual cycl

254 This study sought to evaluate the demographic profile, clinical features, topographic feat

255 Main outcome measurements were demographic profile, clinical features, visual acuity, c

256 arkedly different from APSGN in terms of its demographic profile, temporal association with active in

257 Detailed demographic profiles, systemic symptoms, comorbidities,

258 We used a demographic projection model beginning with the country

259 Among this cohort, we abstracted clinical demographic, radiographical, procedural, cytopathologica

260 ottom-up and density-dependent regulation of demographic rates in an imperilled mesopredator, the che

261 p and density-dependent factors may regulate demographic rates of cheetahs and other mesopredators.

262 out the integrated effects of drivers on all demographic rates provides no justification for ignoring

263 change influences fitness-related traits and demographic rates, which in herbivores are often linked

264 We used long-term demographic records and extensive databases of functiona

265 ve population resilience through genetic and demographic rescue.

266 We introduce a framework of demographic resilience that draws on existing concepts f

267 e survival analysis, controlling for patient demographics, risk factors, and year of admission (odds

268 d to ICU than can be explained solely by the demographic shift.

269 economic and geopolitical effects of future demographic shifts.

270 elucidate the complex relationships between demographics, social and spatial structure, abiotic and

271 "Did you notice any bleeding in your gums?" Demographic, socioeconomic, and psychosocial variables w

272 Covariates included demographic, socioeconomic, lifestyle, chronic disease,

273 a different district, questions about socio-demographic status were delivered for heads of household

274 and low levels of an identified driver from demographic studies of terrestrial plants.

275 ng encounter, participants were surveyed for demographics, substance use, risk behavior (previous 3 m

276 Patient demographics, surgical data, and complications were coll

277 The survey included questions about demographics, symptoms of burnout, the frequency of misi

278 Data were collected on baseline demographics, systemic and ocular comorbidities, ocular

279 al Center for Health Statistics, we employed demographic techniques to pursue three aims: first, we c

280 including model structure, scope and scale, demographics, time horizons, counterfactuals, health res

281 Patient demographics, tissue characteristics, intraoperative par

282 rm our understanding of differences in a key demographic trait.

283 Demographics, treatment, microbiologic results, and outc

284 We included patient demographics, tumor characteristics, treatment, and soci

285 Patient demographics, tumor clinical size, AJCC stage, COMS size

286 ected data on predictors including admission demographics, underlying medical conditions, outpatient

287 djusted for potential confounders, including demographics, urban/rural residence, systemic health (Ch

288 Patient demographics, use of PPIs, duration of use and dose were

289 ObservationProcedure: Patient demographics, VA, IOD, and stereopsis were compared betw

290 Both LF and NF groups had similar demographics, valve areas and indices.

291 The cohorts were compared to assess demographic variables and clinical presentations.

292 wever, the MRI-derived atrophy component and demographic variables were excluded from the optimal pre

293 djusted for percentage total weight loss and demographic variables, insulin cessation following surge

294 Demographics, visual outcomes, OCT, and treatment data w

295 Demographics were assessed categorically, and response d

296 Demographics were compared, and univariate and risk-adju

297 Bivariate analyses of participant demographics were conducted with 8 types of perceived ha

298 Patient demographics were recorded using a questionnaire.

299 Demographic, work-related information, lifestyle questio

300 After adjusting for patient demographics, year of consultation, comorbidities, smoki