Evaluation of routinely collected records for dementia outcomes in UK: a prospective cohort study by Kay-Tee Khaw, Carol Brayne, Robert Luben, Shabina Hayat, Nicholas Wareham

“…We present potential selection biases that might occur depending on whether cause of death, or primary and secondary care data sources are used. …”
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Application of Perclose ProGlide closure device in transbrachial endovascular intervention by Peng Zhao, Yao Yao, Quan Yang, Ning Wang, Liang Wang, Qianquan Ma, Wenchao Zhang

“…Two patients in the manual compression group reported long-term numbness around the puncture site, while no similar neurological dysfunction was observed in the ProGlide group (P = 0.243). Although selection bias was present in this retrospective study, the Perclose ProGlide system presents a beneficial closure method for patients undergoing transbrachial access.…”
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Risk of bias and confounding of observational studies of Zika virus infection: A scoping review of research protocols. by Ludovic Reveiz, Michelle M Haby, Ruth Martínez-Vega, Carlos E Pinzón-Flores, Vanessa Elias, Emma Smith, Mariona Pinart, Nathalie Broutet, Francisco Becerra-Posada, Sylvain Aldighieri, Maria D Van Kerkhove

“…Potential confounders need to be measured where known and controlled for in the analysis. Selection bias due to non-random selection is a significant issue, particularly in the case-control design, and losses to follow-up is equally important for the cohort design.…”
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Ensemble Deep Learning Object Detection Fusion for Cell Tracking, Mitosis, and Lineage by Imad Eddine Toubal, Noor Al-Shakarji, D. D. W. Cornelison, Kannappan Palaniappan

“…However, manual tracking is labor-intensive, tedious, and prone to selection bias and errors. Building upon our previous work, we propose a new deep learning-based method, EDNet, for cell detection, tracking, and motility analysis that is more robust to shape across different cell lines, and models cell lineage and proliferation. …”
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Effects of Breast-Conserving Surgery Combined with Sentinel Lymph Node Biopsy on Breast Cosmetic Appearance and Systemic Stress of Patients with Breast Cancer by Jing Ji, Junfeng Shi, Xia Da, Guozhu Wang, Jin Xu

“…Propensity score matching was performed to minimize selection bias based on baseline characteristics, resulting in two matched groups of 55 patients each. …”
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Diabetes Increases Risk of Cardiovascular Events in Patients Receiving Permanent Pacemaker: A Propensity Score-Matched Cohort Study by Huang-Chung Chen, Wen-Hao Liu, Chien-Hao Tseng, Yung-Lung Chen, Wei-Chieh Lee, Yen-Nan Fang, Shaur-Zheng Chong, Mien-Cheng Chen

“…Propensity score matching (PSM) was applied to reduce selection bias between the study groups. Result. During a mean follow-up period of 7.8±4.8 years, 264 patients had a cardiovascular event. …”
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Comparison of clinician- and patient-reported outcome measures in 95 abdominoplasty cases using BODY-Q and MCCRO-Q by Samuel Thomas Kitching, Claudia Rocco, Rachel Harwood, Gary Ross

“…None of the tested factors significantly affected how the patients scored these outcomes.We demonstrated that clinicians underestimate the improvement in outcomes described by the patients and they need to be aware of their selection bias when consulting with patients preoperatively, as patients reported improvement regardless of the pre-operative or post-operative variable tested.…”
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Toward Intelligent Financial Advisors for Identifying Potential Clients: A Multitask Perspective by Qixiang Shao, Runlong Yu, Hongke Zhao, Chunli Liu, Mengyi Zhang, Hongmei Song, Qi Liu

“…However, two critical problems encountered in real practice make this prediction task challenging, i.e., sample selection bias and data sparsity. In this study, we formalize a potential conversion relationship, i.e., user → activated user → client and decompose this relationship into three related tasks. …”
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EU-TIRADS-Based Omission of Fine-Needle Aspiration and Cytology from Thyroid Nodules Overlooks a Substantial Number of Follicular Thyroid Cancers by Tamas Solymosi, Laszlo Hegedüs, Miklos Bodor, Endre V. Nagy

“…This study design is unique in avoiding the common selection bias when TIRADS’ sensitivity is tested in a cohort selected for FNA and surgery based on the same US characteristics on which TIRADS is based. …”
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Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic Review by Mariana Herrera, Cristian Vera, Yoav Keynan, Zulma Vanessa Rueda

“…We found high heterogeneity between studies including failure to account for the time/illness of the individuals studied; varied samples and protocols; different clinical classification of TB; different laboratory methods for IP detection, which in turn leads to variable units of measurement and assay sensitivities; and selection bias regarding TST and booster effect. None of the studies adjusted the analysis for the effect of ethnicity. …”
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Real-World Assessment of Weight Change in African American Females and Hispanics with HIV-1 After Initiating Integrase Strand-Transfer Inhibitors or Protease Inhibitors by Yen-Wen Chen, David Anderson, Christopher D. Pericone, Prina Donga

“…Inverse probability of treatment weighting was used to reduce selection bias and improve cohort comparability. Multivariable models were used to compare absolute weight/body mass index (BMI) changes and proportion of patients with weight/BMI increases from pre- to post-index (last measure between the 4th and 12th months post-index). …”
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Structures and strategies for retaining an international pediatric cohort from birth: Lessons from The Environmental Determinants of Diabetes in the Young (TEDDY) study by Patricia Gesualdo, Jessica Melin, Rachel Karban, Claire Crouch, Michael Killian, Diane Hopkins, Annika Adamsson, Joanna Stock, Suzanne Bennett Johnson, Judith Baxter

“…Background: Retention of study participants in observational studies is essential to maintaining the representativeness of the population, minimizing selection bias, and assuring sufficient statistical power. …”
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Association between herpes simplex virus infection and Alzheimer’s disease biomarkers: analysis within the MAPT trial by Morgane Linard, Isabelle Garrigue, Bruno Vellas, Nicola Coley, Henrik Zetterberg, Kaj Blennow, Nicholas James Ashton, Pierre Payoux, Anne-Sophie Salabert, Jean-François Dartigues, Joachim Mazere, Sandrine Andrieu, Catherine Helmer

“…The trend toward lower cortical amyloid load in HSV-1-infected participants was unexpected given the pre-existing literature and may be explained either by a modified immune response in HSV-1 infected subjects which could favour the clearance of amyloid deposits or by a selection bias.…”
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Patient and Hospital Characteristics Associated with Admission Among Patients With Minor Isolated Extremity Firearm Injuries: A Propensity-Matched Analysis by Arielle C. Thomas, MD, MPH, MS, Regina Royan, MD, MPH, Avery B. Nathens, MD, PhD, Brendan T. Campbell, MD, MPH, Susheel Reddy, MPH, Sarabeth Spitzer, MD, Doulia Hamad, MD, Angie Jang, BA, Anne M. Stey, MD, MSc

“…Admitted patients were propensity score matched to nonadmitted patients on age, extremity Abbreviated Injury Score, and Elixhauser Comorbidity Index with exact matching within hospital to adjust for selection bias. A general estimating equation logistic regression estimated the association between insurance and odds of admission in the matched cohort while controlling for sex, race, injury intent, injury type, hospital profit type, and trauma center designation with observations clustered by propensity score-matched pairs within hospital. …”
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Effectiveness of chain of survival for out-of-hospital-cardiac-arrest (OHCA) in resource limited countries: A systematic review by Mirza Noor Ali Baig, Zafar Fatmi, Nadeem Ullah Khan, Uzma Rahim Khan, Ahmed Raheem, Junaid Abdul Razzak

“…Risk of bias was moderate to high due to selection bias, inadequate confounding control, and inconsistent reporting. …”
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Metagenomics: a new frontier for routine pathology testing of gastrointestinal pathogens by Nicola Z. Angel, Mitchell J. Sullivan, Areej Alsheikh-Hussain, Liang Fang, Samantha MacDonald, Alena Pribyl, Blake Wills, Gene W. Tyson, Philip Hugenholtz, Donovan H. Parks, Paul Griffin, David L. A. Wood

“…Metagenomic next-generation sequencing (mNGS) allows the identification of all pathogens in a sample in a single test, without a reliance on culture or introduction of target selection bias. This study aims to determine the ability to routinely apply mNGS testing, in comparison to traditional culture or polymerase chain reaction (PCR) based tests, for the identification of causal pathogens for gastrointestinal infections. …”
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The superiority of veno-arterial over veno-venous extracorporeal membrane oxygenation for operative support of lung transplantation by Sen Lu, Pin Wang, Xiao-qin Zhang, Gang Feng, Hong-li He, Yue Chen, Xiao-bo Huang, Chun Pan, Jing-chao Luo

“…To address potential selection bias, we employed entropy weighted inverse probability of treatment weighting (IPTW-EW). …”
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Estimates of disclosure and victimization rates for fishery observers in the maritime workplace by Lacey Jeroue, Lacey Jeroue, Craig Faunce, Andy Kingham, Jaclyn Smith

“…Victimization rates computed from raw survey summary statistics suffer from self-selection bias while rates derived solely from submission of official statements suffer from bias in underreporting. …”
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Machine learning prediction models for mortality risk in sepsis-associated acute kidney injury: evaluating early versus late CRRT initiation by Chuanren Zhuang, Ruomeng Hu, Ke Li, Zhengshuang Liu, Songjie Bai, Sheng Zhang, Xuehuan Wen

“…Propensity score matching was performed to address potential selection bias. Subgroup analyses stratified patients by disease severity using SOFA scores (low ≤10, medium 11–15, high >15) and creatinine levels (low ≤3 mg/dL, medium 3–5 mg/dL, high >5 mg/dL). …”
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Comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with T1c, node-negative, triple-negative breast cancer: A population-based analysis by Yi-Zi Zheng, Jia-Qi Ying, Ting-Ting Wu, Yong-Hui Su, Ou-Chen Wang

“…To balance baseline characteristics and mitigate selection bias, propensity score matching (PSM) was used to create the NAT and AT cohorts. …”
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