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31941por Lee, Frank, Jain, Jennifer Payaal, Duthely, Lunthita M, Ikeda, Janet, Santos, Glenn-Milo“…Multivariable models controlled for age, race, health insurance, and relationship status. …”
Publicado 2023
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31942“…There were significant differences (p<.05) by all criteria of MetS in waist circumference (WC), GAR, DVAI, and PMI, but no differences by any criteria of MetS in the distribution of age, sex, race/ethnicity, or BMI Z-scores. In all regression models, higher both DVAI and PMI were significant predictors for MetS. …”
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31943por Srinath, Reshmi, Pedersen, Sue, Neff, Lisa, Cao, Dachuang, Kao, Christi Y, Stefanski, Adam, Ahmad, Nadia, Eun Lee, Clare Jung“…Baseline factors not associated with higher odds of achieving BW reduction ≥20% were age, race, BW, years of education, fasting insulin, and systolic blood pressure. …”
Publicado 2023
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31944“…We collected demographics like age, sex and race. Other variables like admitting and discharging team, length of hospital stay, readmission and mortality rate, referral to specialty (Endocrinology/Rheumatology) on discharge, specialty follow up after discharge, treatment initiation after discharge, preadmission and postadmission DXA scan and polypharmacy (five or more daily prescription medication) were collected. …”
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31945por Kim, Catherine, Schreiner, Pamela, Siscovick, David, Wang, Ange, Wellons, Melissa, Ebong, Imo, Vu, Thanh-Huyen, Appiah, Duke, Catov, Janet, Schisterman, Enrique, Yin, Zhe, Lewis, Cora E“…In polychotomous logistic regression models adjusting for age, race, and center, women with self-reported PCOS had greater odds of having obesity (OR 1.83, 95% CI 1.22, 2.75) and diabetes (OR 2.37, 95% CI 1.05, 5.33) compared to women without PCOS. …”
Publicado 2023
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31946por Becetti, Imen, Lauze, Meghan, Lee, Hang, Bredella, Miriam, Misra, Madhusmita, Singhal, Vibha“…Results: SG and NS groups were similar for age, sex and race. SG had higher median body mass index (BMI) vs. …”
Publicado 2023
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31947por Saini, Jasmine, Nathani, Rohit, Zhang, Catherine, Suresh, Malavika, Thangamuthu, Karthik, Singh, Sumitabh, Fell, Vanessa, Atkinson, Elizabeth J, Achenbach, Sara, Stricker, Nikki H, Bancos, Irina“…Fully corrected T-scores for age, sex, education, and race were compared using a paired t-test before and after adrenalectomy. …”
Publicado 2023
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31948“…But because of globalization; people from all races are seen in every part of the world. It will be beneficial to screen patients for IAS which can decrease cost of work up and treatment, when considering imaging modalities which were included as the part of the work up. …”
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31949por Iovoli, Austin J., Turecki, Lauren, Qiu, Michelle L., Khan, Michael, Smith, Kelsey, Yu, Han, Ma, Sung Jun, Farrugia, Mark K., Singh, Anurag K.“…RESULTS: Among 576 eligible patients, the median age was 62.5 (IQR, 56.3-69.1) years, and 451 patients (78.3%) were men. In terms of race and ethnicity, 6 patients (1.0%) were American Indian or Alaska Native; 2 (0.3%), Asian; 31 (5.4%), Black; 8 (1.4%), Hispanic or Latino; 509 (88.4%), White; and 28 (4.9%), unknown. …”
Publicado 2023
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31950por Giovanelli, Alison, Sanchez Karver, Tahilin, Roundfield, Katrina D, Woodruff, Sean, Wierzba, Catherine, Wolny, J, Kaufman, Michelle R“…Teenagers endorsing symptoms of depression or anxiety (n=14) were paired with a mentor (n=10) based on preferred characteristics such as gender, race or ethnicity, and lesbian, gay, bisexual, transgender, queer (LGBTQ) status. …”
Publicado 2023
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31951por Hoffman, Valerie, Flom, Megan, Mariano, Timothy Y, Chiauzzi, Emil, Williams, Andre, Kirvin-Quamme, Andrew, Pajarito, Sarah, Durden, Emily, Perski, Olga“…Significant differences across clusters were found by age, gender identity, race and ethnicity, sexual orientation, education, and insurance coverage. …”
Publicado 2023
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31952The Role of Telehealth in Promoting Equitable Abortion Access in the United States: Spatial Analysis“…OBJECTIVE: We sought to examine the amount of travel that patients averted by using telehealth for abortion care, and the role of telehealth in mitigating inequities in abortion access by race or ethnicity, age, pregnancy duration, socioeconomic status, rural residence, and distance to a facility. …”
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31953por Marks, Asher, Garbatini, Amanda, Hieftje, Kimberly, Puthenpura, Vidya, Weser, Veronica, Fernandes, Claudia-Santi F“…Furthermore, 5 (31%) participants identified as Hispanic, 1 (6%) identified as non-Hispanic Asian, 3 (19%) identified as non-Hispanic Black, 6 (38%) identified as non-Hispanic White, and 1 (6%) identified as other race or ethnicity. Hematologic malignancies or bone marrow failure was the most common diagnosis (8/16, 50%). …”
Publicado 2023
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31954por Andronescu, Liana, Richard, Stephanie A, Hone, Emily, Scher, Ann, Lindholm, David, Mende, Katrin, Ganesan, Anuradha, Huprikar, Nikhil, Lalani, Tahaniyat, Smith, Alfred, Mody, Rupal, Jones, Milissa U, Colombo, Rhonda, Ewers, Evan, Berjohn, Catherine, Maldonado, Carlos, Edwards, Margaret Sanchez, Rozman, Julia, Rusiecki, Jennifer, Byrne, Celia, Simons, Mark P, Tribble, David R, Tribble, David R, Burgess, Timothy, Rubin, Leah H, Severson, Joan, O’Connell, Robert, Pollett, Simon, Agan, Brian“…Logistic regression models adjusted for sex, race/ethnicity, age, and education showed no difference in impairment in any of the BRACE tests comparing those with and without a history of SARS-CoV-2 infection (Figure 1). …”
Publicado 2023
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31955por Cantos, Valeria D, Neradilek, Moni, Gillespie, Kevin, Huang, Yunda, deCamp, Allan C, Karuna, Shelly T, Edupuganti, Srilatha, del Rio, Carlos, Veloso, Valdilea, Cohen, Myron S, Donnell, Deborah J, Corey, Lawrence, Roxby, Alison C, Kelley, Colleen F“…Participants from Switzerland [0.5 (0.3-1.0)] and Peru [0.08 (0.06-0.1)] had lower likelihood of PrEP initiation compared to the US, while participants from Brazil had higher likelihood [2.6 (2.0-3.3)]. Age, race, gender, and sexual orientation were not associated with PrEP initiation. …”
Publicado 2023
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31956por Yuengling, Katharine, Surie, Diya, DeCuir, Jennifer, Zhu, Yuwei, Gaglani, Manjusha, Ginde, Adit A, Gibbs, Kevin, Prekker, Matthew, Mohamed, Amira, Johnson, Nicholas, Peltan, Ithan, Bender, William, Mallow, Christopher, Kwon, Jennie H, Lauring, Adam S, Columbus, Cristie, Vaughn, Ivana, Safdar, Basmah, Chappell, James, Baughman, Adrienne, Swan, Sydney A, Johnson, Cassandra, McMorrow, Meredith L, Self, Wesley, Martin, Emily T“…COVID-19 and RSV vs. influenza using multivariable logistic regression models adjusted for age, sex, race and ethnicity, number of chronic medical condition categories, admission date, and geographic region. …”
Publicado 2023
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31957por Collins, Lauren F, Ofotokun, Igho, Greene, Quincy, Palella, Frank J, Naggie, Susanna, Topper, Elizabeth F, Anastos, Kathryn, French, Audrey L, Kassaye, Seble, Taylor, Tonya, Fischl, Margaret A, Adimora, Adaora A, Kempf, Mirjam-Colette, Tien, Phyllis C, Sheth, Anandi N, Mehta, Cyra Christina“…In covariate-adjusted models (race, BMI, cigarette, alcohol or crack use, menopausal status, socioeconomic status), NACM burden was associated with QoLI (p< 0.0001) but age and HIV did not modify this effect (age*HIV*NACM burden, p=0.83). …”
Publicado 2023
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31958por Zambrano, Laura D, Newhams, Margaret M, Wu, Michael J, Simeone, Regina, Orzel, Amber, Halasa, Natasha B, Fleming-Dutra, Katherine E, Campbell, Angela P, Randolph, Adrienne G“…Adjusted models included ≥1 underlying medical condition (yes/no), age in years, census region, biweekly date of hospital admission, and social vulnerability index (SVI) score. Sex and race/ethnicity were tested as confounders in the full model but were dropped for absence of evidence of confounding. …”
Publicado 2023
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31959por Du, Wen, Chen, Zijin, Fang, Zhengyin, Li, Junru, Weng, Qinjie, Zheng, Qimin, Xie, Lin, Yu, Hanlan, Gu, Xiangchen, Shi, Hao, Wang, Zhaohui, Ren, Hong, Wang, Weiming, Ouyang, Yan, Xie, Jingyuan“…Based on multivariate Cox regression analysis, GCS + CTX treatment was found to be independently associated with a decrease in risk for the composite endpoint after adjusted by the International Risk Prediction Score with race (hazard ratio = 0.17, 95% confidence interval 0.04–0.83, P = .03). …”
Publicado 2023
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31960por Reddy, Chethan, Venishetty, Nikit, Jones, Hunter, Mounasamy, Varatharaj, Sambandam, Senthil“…Risk factors that were found to be associated with a higher incidence of PPD are gender (female), race (Caucasian), and age (young patients). Analysis revealed the history of tobacco-related disorder, obesity, morbid obesity, liver cirrhosis, and Parkinson’s disease increased the odds of developing PPD following RSA. …”
Publicado 2023
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