ライフサイエンスコーパス: smoking status

1 t. George's Respiratory Questionnaire score, smoking status).

2 microm (P = .01; adjusted for age, sex, and smoking status).

3 P1) expression in WAT, which correlates with smoking status.

4 ng factors such as age, anthropometrics, and smoking status.

5 loci, 8 showed significant interaction with smoking status.

6 risk factor such as body mass index, age, or smoking status.

7 sex, employment grade, body mass index, and smoking status.

8 : 0.63, 0.91; P-trend < 0.01), regardless of smoking status.

9 by PD-L1 expression, choice of platinum, and smoking status.

10 dependent of demographic characteristics and smoking status.

11 y control subjects matched for age, sex, and smoking status.

12 (10,856 CD cases and 8879 UC cases) of known smoking status.

13 city, body mass index, diabetes, parity, and smoking status.

14 processed red meat while taking into account smoking status.

15 expectancy of HIV-infected persons, based on smoking status.

16 mRNA expression and protein expression with smoking status.

17 cal model that included tumor size, age, and smoking status.

18 gular exercise, cardiovascular activity, and smoking status.

19 fferences in survival based on trial arm and smoking status.

20 ex-specific data on mortality, stratified by smoking status.

21 tment-seeking volunteers based on reflux and smoking status.

22 ted with AAA, regardless of study design and smoking status.

23 ignificant clustering based on pregnancy and smoking status.

24 dure, performance status score, and lifetime smoking status.

25 from TCGA cohort matched for tumour size and smoking status.

26 reported risk of type 2 diabetes by baseline smoking status.

27 ciated with KS, after adjustment for age and smoking status.

28 education, race, estimated intelligence, and smoking status.

29 ided a CO measurement or self-reported their smoking status.

30 to 2005) with known human papillomavirus and smoking status.

31 tively, p < 0.001) were independent of prior smoking status.

32 (PR/RP+saline; n = 26) therapies by sex and smoking status.

33 ne in survivors, smoking history, or current smoking status.

34 rs, suggesting the result was independent of smoking status.

35 ere also associated with body mass index and smoking status.

36 s and 95% confidence intervals, adjusted for smoking status.

37 , obesity, cardiovascular disease, COPD, and smoking status.

38 of pocket depth, gingival bleeding, ACH, and smoking status.

39 l features were measured and correlated with smoking status.

40 y control subjects matched for age, sex, and smoking status.

41 etected only because association differed by smoking status.

42 ing for age, gender, level of education, and smoking status.

43 ood method adjusting for age, sex, race, and smoking-status.

44 ter adjusting for race, body mass index, and smoking status (1.38 years, p = 0.02).

45 " or "periodically" ask patients about their smoking status, 251 (86%) "seldom" or "never" ask patien

46 Of these, tobacco habit (smoking status 35% and number of cigarettes/day 32%) acc

47 owing data were recorded: 1) age; 2) sex; 3) smoking status; 4) number of missing teeth; and 5) numbe

48 ive (multivariate GEE adjusted for age, sex, smoking status, ACPA, and year of recruitment to NOAR: b

49 e populations, combined with a meta-GWAS for smoking status, adds new insights into the genetic vulne

50 ge, demographics, underlying conditions, and smoking status (adults only).

51 To assess how tobacco smoking status affects baseline dopamine D2/D3 (D2R) rec

52 ucation, calcium/vitamin D, body mass index, smoking (status, age at start, duration, and pack-years)

53 Demographic data, smoking status, age at diagnosis, disease duration, loca

54 tic regression and was further stratified by smoking status, alcohol consumption, and body mass index

55 conomic status, social and leisure activity, smoking status, alcohol consumption, and physical activi

56 y, study center, body mass index, education, smoking status, alcohol consumption, physical activity,

57 pitalizations differed according to baseline smoking status, alcohol intake, BMI, and diabetes status

58 rticipants' ethnicity, sex, body mass index, smoking status, alcohol intake, or diabetes status.

59 cluding age, center, year of screening exam, smoking status, alcohol intake, physical activity, educa

60 x, ethnicity, height, body mass index (BMI), smoking status, alcohol intake, Townsend deprivation ind

61 tics, and angiotensin receptor antagonists), smoking status, alcohol intake, years of education, temp

62 nalyst, image quality, study site, age, sex, smoking status, alcohol use, daily blocks walked, diuret

63 n analyses adjusted for age, sex, ethnicity, smoking status, alcohol, and high-sensitivity C-reactive

64 Cox regression model, adjusted for age; sex; smoking status; alcohol intake; SBP; DBP; cholesterol:hi

65 Patients and Methods We analyzed survival by smoking status among 1,037 patients from two large US pr

66 characterize trends by sociodemographic and smoking status among young adults (18-24 years).

67 reduced TL when we used prospective data on smoking statuses among men and women, but the associatio

68 ese findings were consistent irrespective of smoking status and across study centers.

69 shed computational model captured effects of smoking status and administration of nicotine and vareni

70 Associations of microRNA expression with smoking status and associations of smoking-related micro

71 nant predictors for uncontrolled asthma were smoking status and asthma symptom scores and an addition

72 search, we examined the associations between smoking status and colorectal cancer subtypes defined by

73 rent error-prone method of self-reporting of smoking status and could be expanded to assess the effec

74 rolling for age, sex, race, body mass index, smoking status and depression severity.

75 Most eye care providers assess patients' smoking status and educate patients regarding ocular ris

76 ates (US) with regard to assessing patients' smoking status and exposure, educating patients regardin

77 ogistic regression was conducted to evaluate smoking status and hypertension differences between case

78 After adjustment for sex, age, height, smoking status and intensity, pack-years, asthma, and FE

79 itions, including positive correlations with smoking status and moderate levels of physical activity,

80 ence intervals (CIs), adjusting for smoking (smoking status and pack-years), sex, and lifetime days o

81 d to study the association of mortality with smoking status and pack-years.

82 Smoking status and periodontal examination data from NHA

83 CAL) for six sites/tooth were ascertained by smoking status and plotted using contour maps to identif

84 Smoking status and preoperative exhaled carbon monoxide

85 Main effects of smoking status and PTSD symptom severity on pain-related

86 Further analyses tested interactions between smoking status and PTSD symptom severity on pain-related

87 A linear mixed model controlling for smoking status and sex identified significantly higher [

88 lts were stratified by histological subtype, smoking status and sex.

89 Proportions of nurses' smoking status and smoking cessation practices were pool

90 ization meta-analyses of the associations of smoking status and smoking heaviness with systolic and d

91 r, there was evidence of interaction between smoking status and the effect of HPR.

92 rvals (CIs) of preterm birth associated with smoking status and the number of cigarettes consumed, ad

93 Our study examined the association between smoking status and time to first bowel resection in pati

94 ver, whether cTnI levels differ according to smoking status and whether smoking modifies the prognost

95 ssure, waist circumference, body mass index, smoking status, and alcohol consumption over a 17-year p

96 ed for educational level, physical activity, smoking status, and alcohol consumption.

97 sting for age, sex, body mass index, current smoking status, and antidepressant use.

98 ody weight, body mass index (BMI), diabetes, smoking status, and aspirin use.

99 disease when controlling for age, sex, race, smoking status, and autoimmune disease.

100 for age, race, WIHS site, education, income, smoking status, and baseline ART regimen.

101 for age, race, WIHS site, education, income, smoking status, and baseline ART regimen.

102 uL, adjusting for age, sex, body-mass index, smoking status, and Charlson comorbidity index.

103 ization, adjusting for demographics, current smoking status, and cumulative pack-years.

104 case-control study, adjusting for ethnicity, smoking status, and dental characteristics.

105 HRs were adjusted for age, smoking status, and education level, and number of colon

106 014, adjusted for age, race/Hispanic origin, smoking status, and education, showed significant increa

107 ile correcting for age, sex, BMI, education, smoking status, and estimated socioeconomic status (ZIP

108 ariable, while adjusting for age, sex, race, smoking status, and history of autoimmune disease.

109 , allergic rhinitis, chronic rhinosinusitis, smoking status, and history of NSAID-induced hypersensit

110 egression models adjusted for age, sex, BMI, smoking status, and hypertension.

111 , cholesterol levels, use of blood thinners, smoking status, and lens status also were evaluated.

112 mellitus, cardiovascular and kidney disease, smoking status, and lifetime socioeconomic position.

113 Hcy concentrations, irrespective of lipid or smoking status, and lowered systolic blood pressure in b

114 group), stratified by bevacizumab treatment, smoking status, and M-substage using a dynamic-balancing

115 ent for diet quality, body mass index (BMI), smoking status, and medication use, specifically, the re

116 or subgroup interaction by stimulation type, smoking status, and number of levels fused was not signi

117 n analyses, partially adjusted for age, sex, smoking status, and obesity.

118 for sex, age, history of cancer, ethnicity, smoking status, and oral contraceptive use.

119 with lower FMD, adjusting for age, BMI, sex, smoking status, and other CVD risk factors.

120 adjusted for COPD status, age, sex, current smoking status, and pack-years of cigarette smoking.

121 s (total energy intake, alcohol consumption, smoking status, and physical activity).

122 of bleeding on probing and/or suppuration), smoking status, and potential risk variables were analyz

123 1090 controls (1:2) by age, sex, ethnicity, smoking status, and presence of cardiovascular disease.

124 ustment for age, sex, race, body mass index, smoking status, and previous myocardial infarction, a sh

125 rcinoma (based on age, sex, body mass index, smoking status, and prior esophageal conditions) with an

126 or untreated), body mass index, cholesterol, smoking status, and QRS duration.

127 ssociated with increased age, comorbidities, smoking status, and recent chemotherapy.

128 ting for age, body mass index, race, current smoking status, and recent hormonal contraceptive use, w

129 model, adjusted for age, height, sex, race, smoking status, and scanner make.

130 ffect on SSI, adjusting for body mass index, smoking status, and sex.

131 th adjustment for age, sex, body mass index, smoking status, and the first 5 principal components der

132 ting for age, estimates of cell proportions, smoking status, and the first three principal components

133 ons with tumor types and subtypes, patients' smoking status, and the response to immunotherapy.

134 lf-report alone; 2) age, sex, education, and smoking status; and 3) a combination of the above.

135 and 17, respectively, for current and former smoking status; and 77 for cigarette pack-years.

136 Biobank (stage 1) matched for age, sex, and smoking status; and a follow-up of associated genetic va

137 Efficiency and Duration scale (SATED): <8); smoking status; and, alcohol intake (high-risk drinker b

138 stolic and diastolic blood pressure, current smoking status, antihypertensive medication use, diabete

139 cteristics such as lower body mass index and smoking status as well as increased intakes of fruit, ve

140 Factors, including age, gender, smoking status, aspirin use, and history of diabetes, hy

141 47%]), 299 (80%) and 278 (74%) self-reported smoking status at 12 and 24 weeks, respectively.

142 xhaled CO measurement or self-reported their smoking status at 12 months were included in the primary

143 Our primary outcome was smoking status at 12 months, verified by carbon monoxide

144 ; p=0.65) or in pooled analyses adjusted for smoking status at each study visit (difference of -5.2 m

145 dy-II Nutrition Cohort participants reported smoking status at enrollment in 1992 to 1993 and approxi

146 sed at birth, family income at 23 years, and smoking status at the age of 23 and 30 years.

147 or different drinking patterns, obesity, and smoking status at the individual level.

148 Potential risk determinants (smoking status, baseline histology, cancer history, and

149 We evaluated the association between smoking status before and after breast cancer diagnosis

150 c blood pressure, hypertension, diabetes and smoking status, blood glucose and inflammatory markers,

151 ted for age, sex, race/ethnicity, education, smoking status, body mass index, and baseline glucose le

152 after adjustment for history of statin use, smoking status, body mass index, and history of cardiova

153 t as an independent variable identified age, smoking status, body mass index, haemoglobin, serum uric

154 r age; sex; race/ethnicity; education; diet; smoking status; body mass index; self-reported health; m

155 8 variables and treatment interactions with smoking status (c = 0.67).

156 study we demonstrate for the first time that smoking status can be predicted using blood biochemistry

157 adjusted for demographics, anthropometrics, smoking status, cardiac risk factors, and LV parameters,

158 s with no teeth removed, all combinations of smoking status categories and tooth loss had a higher li

159 sex, primary tumour type, age at diagnosis, smoking status, chemotherapy drug class, and duration of

160 haemoglobin (HbA1c), body mass index (BMI), smoking status, comorbidities, consultations, medication

161 Blood eosinophil counts and smoking status could be important modifiers of treatment

162 household wealth quintile, body-mass index, smoking status, country, and region.

163 ificantly associated (P=6.1 x 10(-134)) with smoking status (current versus never).

164 n = 12) reporting on the association between smoking status (current, former, and never) and surgery

165 y mass index at diabetes mellitus diagnosis, smoking status, diabetes mellitus duration, nut consumpt

166 n models fitted the association of age, sex, smoking status, diabetes mellitus, educational level, al

167 er we controlled for age, educational level, smoking status, diabetes status, and presence of human i

168 cluded baseline covariates: race, education, smoking status, diabetes, and cardiovascular disease.

169 ing 4 risk factors: systolic blood pressure, smoking status, diabetes, and total cholesterol.

170 , adjusting for age, sex, education, income, smoking status, diabetes, body mass index, and calcium l

171 evious myocardial infarction, heart failure, smoking status, diabetes, heart rate, and ST-segment dep

172 ncontrolled CRS, whereas allergy, asthma and smoking status did not alter the percentage of patients

173 e ventral striatum may also be influenced by smoking status, drug metabolites, and treatment status i

174 th parents in the Original cohort with known smoking status during the offspring's childhood.

175 n of eye care providers who assess patients' smoking status, educate patients regarding ocular risks

176 were adjusted for age, sex, body mass index, smoking status, education, energy intake, examination ye

177 age, body mass index, race, supplement use, smoking status, educational level, income, and aspirin u

178 tes diagnosis, systolic blood pressure, BMI, smoking status, estimated glomerular filtration rate, LD

179 pulation counts from the 2010 US census, and smoking status estimates from the Behavioral Risk Factor

180 s) with 95% CIs were calculated according to smoking status for death as a result of breast cancer; c

181 % CI 1.53-2.21), male sex (1.63, 1.07-2.48), smoking status (former smoker vs never smoked: 1.60, 1.0

182 R] = 0.6, P < 0.05), adjusting for age, sex, smoking status, FPL, education level, and dental visit.

183 Models were adjusted for age, income, smoking status, frequency of dental visits, waist circum

184 health outcomes were found between different smoking status groups, suggesting that smoking/vaping pr

185 hat assessment of blood eosinophil count and smoking status has the potential to optimise ICS use in

186 for baseline Gender-Age-Physiology stage and smoking status (hazard ratio per 10% visual GGR increase

187 After adjustment for age, gender, smoking status, HCV, HBV co-infection, group of exposure

188 After adjustment for age, gender, smoking status, hepatitis C and hepatitis B virus coinfe

189 of systolic blood pressure, body mass index, smoking status, high-density lipoprotein and total chole

190 Trends in systolic blood pressure, smoking status, high-density lipoprotein cholesterol, an

191 After adjusting for sex, age, current smoking status, history of hypercholesterolemia, history

192 for interaction were performed for age, sex, smoking status, household income, obesity status, and as

193 amily history of disease and lifestyle (e.g. smoking status); however, in recent years, there has bee

194 variable logistic regression, with sex, age, smoking status, hypertension, and chronic obstructive pu

195 etter-seeing eye, educational level, income, smoking status, hypertension, diabetes, cardiovascular d

196 ical cataract, after adjusting for age, sex, smoking status, hypertension, diabetes, education, and m

197 education, prepregnancy obesity, atopy, and smoking status identified two sensitive windows (7-19 an

198 it and the cessation aids used, and reported smoking status in 2016-2017 (outcome assessment; self-re

199 important sex differences in obesity risk by smoking status in adolescents, with those who may be mos

200 stantially complement NCC as an indicator of smoking status in periodontal research.

201 erformed European-ancestry meta-analyses for smoking status in the MVP and GWAS & Sequencing Consorti

202 This score reliably predicted smoking status in the training set (n = 1,057; accuracy

203 nvasive coronary strategy, and current or ex-smoking status increased (all P < .001).

204 evere periodontitis with AHI score, age, and smoking status indicated a significant association with

205 y age, sex, previous exacerbation frequency, smoking status, inhaled corticosteroid use at baseline,

206 A significant treatment-by-smoking status interaction was observed on the mean chan

207 nd ISOS-RPE was additionally associated with smoking status, IOPcc and corneal hysteresis.

208 nicity, season of delivery, parity, maternal smoking status, maternal educational level, pregnancy co

209 Age, prior provoked VTE, and smoking status may be important predictors of occult can

210 CP forms, concomitant with determination of smoking status, may allow the dental health professional

211 We also adjusted the model to account for smoking status, menopausal hormone therapy status, body-

212 Findings did not vary by body mass index, smoking status, menopausal status, or time between urine

213 Smoking status modified the relationship between observe

214 nicity, mother's educational level, mother's smoking status, mother's age at parturition, birth order

215 ired in healthy controls matched for sex and smoking status (n = 20).

216 (0, 1 to 5, 6 to 31, or all) and cigarettes smoking status (never, former, or current) with COPD aft

217 Neural effects of smoking status, nicotine, and varenicline were tested fo

218 t the treatment effects may be influenced by smoking status (nonsmokers OR, 0.65; 95% CI, 0.26-1.22 v

219 ation level and atherosclerosis extent were: smoking status, number of cigarettes/day, and dietary pa

220 risk differences were adjusted for sex, age, smoking status, obesity, socioeconomic status, and time

221 zophrenia or nonaffective psychosis from the smoking status of 1,413,849 women and 233,879 men from,

222 The smoking status of nurses appears to have a negative impa

223 AIM: To establish whether the smoking status of nurses is associated with their profes

224 To establish whether the smoking status of nurses is associated with their profes

225 ) were not significantly associated with the smoking status of the nurse.

226 ng an odds ratio (adjusted for age, sex, and smoking status) of 5.9.

227 We also examined the impact of smoking status on AGER (encodes RAGE) and TLR4 bronchial

228 There was a significant effect of smoking status on baseline striatal D2R availability; wi

229 The effect of smoking status on methylphenidate-induced DA release ten

230 Subgroup analyses by chronic morbidity or smoking status or by excluding women with early death di

231 and whether this association was modified by smoking status or inhaled corticosteroid (ICS) use.

232 compared to controls, independent of active smoking status or poor oral hygiene.

233 move during the study or when stratified by smoking status or population density.

234 (OR, 0.98), attained age (OR, 0.97), current smoking status (OR, 1.48), and cranial irradiation (OR,

235 820299, LIPA rs1412444, alcohol consumption, smoking status, or physical activity on MetS and its ind

236 other race (P = .002), diabetes (P = .001), smoking status (P < .001), and larger breast volume (P <

237 , Black (P < .001) or other race (P = .002), smoking status (P < .001), larger breast volume (P = .00

238 teraction between ozone exposure and current smoking status (P = 0.007).

239 cranial volume, p=0.024 for putamen volume), smoking status (p=0.024), and educational attainment (p=

240 ce/ethnicity, education, birth year, cohort, smoking status, pack-years of smoking, renal function, h

241 t, principal components of genetic ancestry, smoking status, pack-years, CT model, milliamperes, and

242 urements were investigated, including active smoking status, pack-years, years as a smoker, packs smo

243 atus, employment status, level of education, smoking status, personality trait of optimism and eviden

244 Covariates included age, education, smoking status, plaque level, and initial level of the a

245 nt effect modifiers and confounders, such as smoking status, postmenopausal hormone use, and ethnicit

246 Associations of AMD incidence with age, sex, smoking status, presence of the complement factor H (CFH

247 , family history of gastrointestinal cancer, smoking status, previous negatives and whether a GP had

248 Subgroup analyses by smoking status, previous thiopurines, previous inflixima

249 unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of al

250 b = 0.05, S.E. = 0.006, p < 2 x 10(-16)) and smoking status PRS (b = 0.05, S.E. = 0.005, p < 2 x 10(-

251 nd high ABL groups versus low, regardless of smoking status (q <0.1%).

252 und several that were highly associated with smoking status, race, and other covariates.

253 h radiomic and clinical features (gender and smoking status) reached a diagnostic accuracy of 88.1% i

254 aphics, year of consultation, comorbidities, smoking status, recent hospitalizations, recent accident

255 n using saliva DNA, with concurrent and past smoking status reported biennially for up to 16 years be

256 haracterized by differences in asthma onset, smoking status, residential locations, percentage of blo

257 ge, sex, race/ethnicity, height, weight, and smoking status.ResultsAmong 70 participants (29 particip

258 n analyses between PTSD symptom severity and smoking status revealed that smoking attenuated the impa

259 M-ISOS was additionally associated with age, smoking status, SBP and refractive error; and ISOS-RPE w

260 ression models after adjusting for age, sex, smoking status, serum lipid levels, systemic and dietary

261 adjusting for potential confounders such as smoking status, sex, age, education level, and dental vi

262 ight was maintained across strata defined by smoking status, sex, and age, but the excess was greates

263 Projected survival was based on smoking status, sex, and initial age.

264 s, having sleep apnea, sex, body mass index, smoking status, Short Form-12 Physical Health Composite

265 age and various aspects of smoking exposure (smoking status, smoking duration, cigarettes per day, pa

266 logistic regression modeling (adjusting for smoking status, sociodemographic, and dental characteris

267 sical activity, body mass index, heart rate, smoking status, systolic blood pressure, fasting glucose

268 dy mass index (BMI), alcohol consumption and smoking status that reach the significance threshold aft

269 ary), arch location (anterior or posterior), smoking status, titanium reinforcement in the membrane,

270 C-reactive protein, HbA1c, height, obesity, smoking status, triglycerides, type 2 diabetes, waist-hi

271 bA1c, longevity, obesity, self-rated health, smoking status, triglycerides, type 2 diabetes, waist-hi

272 mained after adjusting for age, sex, height, smoking status, use of airway medication, blood eosinoph

273 ustment for age, sex, social deprivation and smoking status using logistic regression.

274 adjusted for age, gender, disease duration, smoking status, vitamin D levels, body mass index and tr

275 Smoking status was also strongly associated with MRS (be

276 We found that current smoking status was associated with the DNA methylation l

277 Smoking status was biochemically verified (exhaled air C

278 Smoking status was confirmed via salivary cotinine.

279 Smoking status was defined as ex-smoker, current smoker,

280 Smoking status was dichotomized as current smoking versu

281 eta-analyses suggested that nurses' personal smoking status was not associated significantly with nur

282 Smoking status was not significantly correlated with ICA

283 Active smoking status was reported at baseline and updated on a

284 Smoking status was significantly associated with periodo

285 The association of airflow obstruction with smoking status was stronger in women (odds ratio for ex-

286 Smoking status was unavailable.

287 Smoking status was validated by cotinine assay.

288 teristics, best-corrected visual acuity, and smoking status were also assessed.

289 Age and smoking status were associated with HPV detection.

290 ammatory disease, laterality of uveitis, and smoking status were not associated with differential inc

291 rs, fibrosis within the surrounding lung and smoking status were the best discriminators for an EGFR

292 nalysis (evaluating the influence of current smoking status) were 2452 SSI cases matched to 4467 cont

293 Self-reported smoking status, which may be unreliable, was confirmed b

294 th, family history, alcohol consumption, and smoking status, which suggests that most risk factor ass

295 014) interactions of 40 BMI-related SNPs and smoking status with percent of the CDC/NCHS 2000 median

296 Time-updated self-reported smoking status, years since quitting, and cumulative pac

297 Participants reported their smoking status (yes or no) and daily number of cigarette

298 or clinical management groups, stratified by smoking status (yes or no), weight (<70 kg or >/=70 kg),

299 sed by gestation (<16 weeks vs >/=16 weeks), smoking status (yes vs no), and preferred language of da

300 x, body mass index, race, surgical approach, smoking status, Zubrod and American Society of Anesthesi