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Mendelian randomization (MR), which utilizes genetic variants as instrumental variables (IVs), has gained popularity as a method for causal inference between phenotypes using genetic data. While efforts have been made to relax IV assumptions and develop new methods for causal inference in the presence of invalid IVs due to confounding, the reliability of MR methods in real-world applications remains uncertain. Instead of using simulated datasets, we conducted a benchmark study evaluating 16 two-sample summary-level MR methods using real-world genetic datasets to provide guidelines for the best practices. Our study focused on the following crucial aspects: type I error control in the presence of various confounding scenarios (e.g., population stratification, pleiotropy, and family-level confounders like assortative mating), the accuracy of causal effect estimates, replicability, and power. By comprehensively evaluating the performance of compared methods over one thousand exposure-outcome trait pairs, our study not only provides valuable insights into the performance and limitations of the compared methods but also offers practical guidance for researchers to choose appropriate MR methods for causal inference.

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Background: Observational studies of SARS-CoV-2 vaccine effectiveness are prone to confounding, which can be illustrated using negative control methods. Methods: Nationwide population-based cohort study including two cohorts of Danish residents 60-90 years of age matched 1:1 on age and sex: A vaccinated and a non-vaccinated cohort, including 61052 SARS-CoV-2 vaccinated individuals between 1 March and 1 July 2021 and 61052 individuals not vaccinated preceding 1 July 2021. From these two cohorts, we constructed negative control cohorts of individuals diagnosed with SARS-CoV-2 infection or acute myocardial infarction, stroke, cancer, low energy fracture, or head-trauma. Outcomes were SARS-CoV-2 infection, negative control outcomes (eg, mammography, prostate biopsy, operation for cataract, malignant melanoma, examination of eye and ear), and death. We used Cox regression to calculate adjusted incidence and mortality rate ratios (aIRR and aMRR). Results: Risks of SARS-CoV2 infection and all negative control outcomes were elevated in the vaccinated population, ranging from an aIRR of 1.15 (95% CI: 1.09-1.21) for eye examinations to 3.05 (95% CI: 2.24-4.14) for malignant melanoma. Conversely, the risk of death in the SARS-CoV-2 infected cohort and in all negative control cohorts was lower in vaccinated individuals, ranging from an aMRR of 0.23 (95% CI: 0.19-0.26) after SARS-CoV-2 infection to 0.50 (95% CI: 0.37-0.67) after stroke. Conclusion: Our findings indicate that observational studies of SARS-CoV-2 vaccine effectiveness may be subject to substantial confounding. Therefore, randomized trials are essential to establish vaccine efficacy after the emergence of new SARS-CoV-2 variants and the rollout of multiple booster vaccines.

Why was this study done: : After the emergence of new SARS-CoV-2 variants and the rollout of multiple booster SARS-CoV-2 vaccines, the impact of vaccination on risk of SARS-CoV-2 infection and death after the infection has mainly been explored in observational studies. We used negative control methods to investigate whether confounding affects the results of observational SARS-CoV-2 vaccine effectiveness studies. Findings: : We used Danish registry data obtained during the SARS-CoV-2 vaccine roll-out to conduct a nationwide, matched population-based cohort study of Danish residents 60­90 years in which we compared vaccinated individuals with non-vaccinated individuals. Compared with unvaccinated individuals, vaccinated individuals had increased risks of SARS-CoV2 infection but also had increased risks of all negative control outcomes (mammography, prostate biopsy, operation for cataract, malignant melanoma, examination of eye and ear). The risk of death after SARS-CoV2 infection was lower in the vaccinated cohort, as was the risk of death after acute myocardial infarction, stroke, cancer, low energy fracture, and head-trauma. Meaning: : The negative control methods indicate that observational studies of SARS-CoV-2 vaccine effectiveness may be prone to substantial confounding which may impact the observed associations. This bias may both lead to underestimation of vaccine effectiveness (increased risk of SARS-CoV2 infection among vaccinated individuals) and overestimation of the vaccine effectiveness (decreased risk of death after of SARS-CoV2 infection among vaccinated individuals). Our results highlight the need for randomized vaccine efficacy studies after the emergence of new SARS-CoV-2 variants and the rollout of multiple booster vaccines.

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Discrete myoelectric control-based gesture recognition has recently gained interest as a possible input modality for many emerging ubiquitous computing applications. Unlike the continuous control commonly employed in powered prostheses, discrete systems seek to recognize the dynamic sequences associated with gestures to generate event-based inputs. More akin to those used in general-purpose human-computer interaction, these could include, for example, a flick of the wrist to dismiss a phone call or a double tap of the index finger and thumb to silence an alarm. Moelectric control systems have been shown to achieve near-perfect classification accuracy, but in highly constrained offline settings. Real-world, online systems are subject to 'confounding factors' (i.e. factors that hinder the real-world robustness of myoelectric control that are not accounted for during typical offline analyses), which inevitably degrade system performance, limiting their practical use. Although these factors have been widely studied in continuous prosthesis control, there has been little exploration of their impacts on discrete myoelectric control systems for emerging applications and use cases. Correspondingly, this work examines, for the first time, three confounding factors and their effect on the robustness of discrete myoelectric control: (1)limb position variability, (2)cross-day use, and a newly identified confound faced by discrete systems (3)gesture elicitation speed. Results from four different discrete myoelectric control architectures: (1) Majority Vote LDA, (2) Dynamic Time Warping, (3) an LSTM network trained with Cross Entropy, and (4) an LSTM network trained with Contrastive Learning, show that classification accuracy is significantly degraded (p<0.05) as a result of each of these confounds. This work establishes that confounding factors are a critical barrier that must be addressed to enable the real-world adoption of discrete myoelectric control for robust and reliable gesture recognition.

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OBJECTIVES: To evaluate some confounding factors that influence the concentrations of S100 calcium binding protein B (S100B), glial fibrillary acidic protein (GFAP), and ubiquitin carboxyl-terminal hydrolase L-1 (UCH-L1) in older individuals. Indeed, recent guidelines have proposed the combined use of S100B and the "GFAP-UCH-L1" mTBI test to rule out mild traumatic brain injuries (mTBI). As older adults are the most at risk of mTBI, it is particularly important to understand the confounding factors of those mTBI rule-out biomarkers in aging population. METHODS: The protein S100B and the "GFAP and UCH-L1" mTBI test were measured using Liaison XL (Diasorin) and Alinity I (Abbott), respectively, in 330 and 341 individuals with non-suspected mTBI from the SarcoPhAge cohort. RESULTS: S100B, GFAP and UCH-L1 were all significantly correlated with renal function whereas alcohol consumption, Geriatric Depression Score (GDS), smoking habits and anticoagulant intake were not associated with any of these three biomarkers. Body mass index (BMI) and age were associated with GFAP and UCH-L1 expression while sex and mini-mental state examination (MMSE) were only associated with GFAP. According to the manufacturer's cut-offs for mTBI rule-out, only 5.5 % of participants were positive for S100B whereas 66.9 % were positive for the "GFAP-UCH-L1" mTBI test. All positive "GFAP-UCH-L1" mTBI tests were GFAP+/UCH-L1-. Among individuals with cystatin C>1.55 mg/L, 25 % were positive for S100B while 90 % were positive for the mTBI test. CONCLUSIONS: Our data show that confounding factors have different impacts on the positivity rate of the "GFAP-UCH-L1" mTBI test compared to S100B.

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As novel substances, short time windows, and limits of detection increasingly challenge direct methods of doping detection in sports, indirect tools inevitably take a greater role in the fight against it. One such tool is the athlete biological passport (ABP) - a longitudinal profiling of the measured haematological and biochemical biomarkers, combined with calculated scores, against the background of epidemiological data crucial for doping detection. In both of its modules, haematological and steroidal, ABP parameters are analysed with the Bayesian adaptive model, which individualises reference and cut-off values to improve its sensitivity. It takes into account the confounding factors with proven and potential influence on the biomarkers, such as race and altitude exposure. The ABP has already changed the fight against doping, but its importance will further grow with the new modules (e.g., endocrinological), parameters (e.g., plasma volume-independent parameters), and complementing indirect methods (e.g., transcriptomic).

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BACKGROUND: The Glasgow coma score (GCS) is a clinical tool used to measure level of consciousness in traumatic brain injury and other settings. Despite its widespread use, there are many inaccuracies in its reporting. One source of inaccuracy is confounding factors which affect consciousness as well as each sub-score of the GCS. The purpose of this article was to create a comprehensive list of confounding factors in order to improve the accuracy of the GCS and ultimately improve decision-making. METHODS: An English language literature search was conducted discussing GCS and multiple other keywords. Ultimately, 64 out of 3972 articles were included for further analysis. RESULTS: A multitude of confounding factors were identified which may affect consciousness or GCS sub-scores including the eye exam, motor exam and the verbal response. CONCLUSIONS: An up-to-date comprehensive list of confounding factors has been created that may be used to aide in GCS recording in hopes of improving its accuracy and utility.

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We conducted an ambispective cohort study to assess the association between symptomatic radioulnar impingement syndrome (SRUIS) and distal radioulnar joint (DRUJ) salvage surgery to examine the influence of confounders on the final effect. The outcome variable was the incidence of SRUIS and the exposure variable was the surgical procedure. Seventy-two patients with median age of 48 years (IQR 25-78) were examined using bivariate and logistic regression multivariate analyses, and confounders were analysed in 15 multivariate models. Overall, SRUIS occurred in 21 patients (29%). Bivariate analysis showed a significant association between SRUIS and type of surgical procedure, observed in 71% after Sauvé-Kapandji, 50% after Bowers and 15% after Darrach procedure. When adjusted for age, aetiology and previous surgery, the significant association disappeared. Confounding is an important factor when accounting for SRUIS after DRUJ salvage surgery. The risk of SRUIS did not depend on the procedure, but rather on patient's age, aetiology and previous surgery.Level of evidence: II.

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OBJECTIVE: To establish the scanning protocol for 2-dimensional shear wave elastography (SWE) on normal entheses by investigating the possible confounding factors that may increase the variability of measured elasticity. MATERIAL AND METHODS: 30 normal quadriceps entheses were scanned using SWE to compare the stiffness and coefficient variation by changing the ultrasonic coupling gel thickness, knee position, region of interest size, and scanning plane. RESULTS: No significant difference in median shear wave velocity (SWV) was observed in different coupling gel thicknesses. The median SWV was higher in the knee flexion position than in the extended position (p < 0.001). Increased knee flexion led to stiffer quadriceps enthesis and higher SWV (ρ = 0.8, p < 0.001). The median SWV was higher when the diameter region of interest was 4.0 mm than 2.0 mm (p = 0.001). The median SWV was higher in the transverse plane than in the longitudinal plane (p < 0.001). Strong correlation was found between SWV and the degree of the shear wave to muscle fiber direction (ρ = 0.8, p < 0.001). The coefficient variation was lower in a gel thickness of 2.5 cm, with an extended knee, a region of interest of 2.0 mm, and a longitudinal plane (p > 0.05). For interobserver reliability for the proposed protocol, the intraclass correlation coefficients was 0.763. CONCLUSION: In this study, we determined supine position with the knee extended; using 2.0 mm diameter region of interest and image acquisition at the longitudinal plane with thicker layer coupling gel seems most appropriate to reliably image healthy quadriceps entheses with SWE.

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The paper by Forde et al, newly published in this journal, sheds light on how sugar-sweetened beverages (SSBs) companies may react to the introduction of a SSB tax. This commentary goes over the paper's main findings and drafts implications for research on the impacts of SSB taxes. First and foremost, future research needs to assess the actual impacts of SSB taxes on companies' actions, especially reformulation. Second, cross-country research, comparing large companies with similar beverage portfolios, could bring insights about the impacts of external factors, including different SSB taxes, on companies' decisions. Third, SSB companies' actions are potential confounders in empirical studies looking into the impacts of SSB taxes on prices, demand, or other outcomes. Researchers need to be aware of and discuss such aspects thoroughly in their studies, as the implications for the interpretation of results are evident.

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In addition to pollution, organisms are exposed to natural variations of the biotic and abiotic factors of their environment. A battery of sub-cellular biomarkers has been measured seasonally in several populations of both Dreissena polymorpha and Dreissena rostriformis bugensis. To observe and understand the variability associated with biomarker responses, water physicochemistry, sediment contamination, and internal concentrations of contaminants in soft tissues were also considered. Results evidenced seasonal, inter-specific, and inter-populational variability of the measured responses, highlighting the needs (1) to acquire long-term data on the studied populations and (2) to incorporate environmental parameters and contamination in the interpretation of biological responses. From a biomonitoring perspective, significant relationships were identified between biomarkers, internal concentrations of contaminants in soft tissues, and sediment contamination in D. r. bugensis and, to a lesser extent, in D. polymorpha. The detailed interpretation of each biomarker of the battery measured is complex, but a global analysis of all biomarkers at once allows to obtain this signature of the contamination of the studied sites.

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INTRODUCTION: Various studies have identified TB-induced metabolome variations. However, in most of these studies, a large degree of variation exists between individual patients. OBJECTIVES: To identify differential metabolites for TB, independent of patients' sex or HIV status. METHODS: Untargeted GCxGC/TOF-MS analyses were applied to the sputum of 31 TB + and 197 TB- individuals. Univariate statistics were used to identify metabolites which are significantly different between TB + and TB- individuals (a) irrespective of HIV status, and (b) with a HIV + status. Comparisons a and b were repeated for (i) all participants, (ii) males only and (iii) females only. RESULTS: Twenty-one compounds were significantly different between the TB + and TB- individuals within the female subgroup (11% lipids; 10% carbohydrates; 1% amino acids, 5% other and 73% unannotated), and 6 within the male subgroup (20% lipids; 40% carbohydrates; 6% amino acids, 7% other and 27% unannotated). For the HIV + patients (TB + vs. TB-), a total of 125 compounds were significant within the female subgroup (16% lipids; 8% carbohydrates; 12% amino acids, 6% organic acids, 8% other and 50% unannotated), and 44 within the male subgroup (17% lipids; 2% carbohydrates; 14% amino acids related, 8% organic acids, 9% other and 50% unannotated). Only one annotated compound, 1-oleoyl lysophosphaditic acid, was consistently identified as a differential metabolite for TB, irrespective of sex or HIV status. The potential clinical application of this compound should be evaluated further. CONCLUSIONS: Our findings highlight the importance of considering confounders in metabolomics studies in order to identify unambiguous disease biomarkers.

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INTRODUCTION: Amyloid-ß (Aß) and tau can be quantified in blood. However, biological factors can influence the levels of brain-derived proteins in the blood. The blood-brain barrier (BBB) regulates protein transport between cerebrospinal fluid (CSF) and blood. BBB altered permeability might affect the relationship between brain and blood biomarkers. METHODS: We assessed 224 participants in research (TRIAD, n = 96) and clinical (BIODEGMAR, n = 128) cohorts with plasma and CSF/positron emission tomography Aß, p-tau, and albumin measures. RESULTS: Plasma Aß42/40 better identified CSF Aß42/40 and Aß-PET positivity in individuals with high BBB permeability. An interaction between plasma Aß42/40 and BBB permeability on CSF Aß42/40 was observed. Voxel-wise models estimated that the association of positron emission tomography (PET), with plasma Aß was most affected by BBB permeability in AD-related brain regions. BBB permeability did not significantly impact the relationship between brain and plasma p-tau levels. DISCUSSION: These findings suggest that BBB integrity may influence the performance of plasma Aß, but not p-tau, biomarkers in research and clinical settings. HIGHLIGHTS: BBB permeability affects the association between brain and plasma Aß levels. BBB integrity does not affect the association between brain and plasma p-tau levels. Plasma Aß was most affected by BBB permeability in AD-related brain regions. BBB permeability increases with age but not according to cognitive status.

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OBJECTIVES: Confounding factors, including sex, age, and renal dysfunction, affect high-sensitivity cardiac troponin T (hs-cTnT) concentrations and the acute myocardial infarction (AMI) diagnosis. This study assessed the effects of these confounders through logistic regression models and evaluated the diagnostic performance of an optimized, integrated prediction model. METHODS: This retrospective study included a primary derivation cohort of 18,022 emergency department (ED) patients at a US medical center and a validation cohort of 890 ED patients at a Canadian medical center. Hs-cTnT was measured with 0/3 h sampling. The primary outcome was index AMI diagnosis. Logistic regression models were optimized to predict AMI using delta hs-cTnT and its confounders as covariates. The diagnostic performance of model cutoffs was compared to that of the hs-cTnT delta thresholds. Serial logistic regressions were carried out to evaluate the relationship between covariates. RESULTS: The area under the curve of the best-fitted model was 0.95. The model achieved a 90.0% diagnostic accuracy in the validation cohort. The optimal model cutoff yielded comparable performance (90.5% accuracy) to the optimal sex-specific delta thresholds (90.3% accuracy), with 95.8% agreement between the two diagnostic methods. Serial logistic regressions revealed that delta hs-cTnT played a more predominant role in AMI prediction than its confounders, among which sex is more predictive of AMI (total effect coefficient 1.04) than age (total effect coefficient 0.05) and eGFR (total effect coefficient -0.008). CONCLUSIONS: The integrated prediction model incorporating confounding factors does not outperform hs-cTnT delta thresholds. Sex-specific hs-cTnT delta thresholds remain to provide the highest diagnostic accuracy.

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Resting-state functional connectivity (RSFC) has been widely adopted for individualized trait prediction. However, multiple confounding factors may impact the predicted brain-behavior relationships. In this study, we investigated the impact of 4 confounding factors including time series length, functional connectivity (FC) type, brain parcellation choice, and variance of the predicted target. The data from Human Connectome Project including 1,206 healthy subjects were employed, with 3 cognitive traits including fluid intelligence, working memory, and picture vocabulary ability as the prediction targets. We compared the prediction performance under different settings of these 4 factors using partial least square regression. Results demonstrated appropriate time series length (300 time points) and brain parcellation (independent component analysis, ICA100/200) can achieve better prediction performance without too much time consumption. FC calculated by Pearson, Spearman, and Partial correlation achieves higher accuracy and lower time cost than mutual information and coherence. Cognitive traits with larger variance among subjects can be better predicted due to the well elaboration of individual variability. In addition, the beneficial effects of increasing scan duration to prediction partially arise from the improved test-retest reliability of RSFC. Taken together, the study highlights the importance of determining these factors in RSFC-based prediction, which can facilitate standardization of RSFC-based prediction pipelines going forward.

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La identificación de relaciones causales es uno de los problemas fundamentales de la investigación científica en medicina y es necesaria para poder ejercerla en forma efectiva. Sin embargo, desde el punto de vista práctico es difícil establecer la existencia de relaciones causales en estudios de carácter observacional, en gran parte por la presencia de factores de confusión. El análisis a través de variables instrumentales es una de las estrategias que permite controlar el efecto confundidor y documentar la presencia de relaciones causa-efecto en estas situaciones. En este artículo, el autor resume los principales supuestos del análisis a través de variables instrumentales, haciendo foco en la aleatorización mendeliana. (AU)

The identification of causal relationships is one of the fundamental challenges in scientific research in medicine and is necessary for its effective practice. However, from a practical standpoint, establishing the existence of causal relationships in observational studies is difficult, largely due to the presence of confounding factors. Analysis through instrumental variables is one of the strategies that allows to control the confounding effect and documenting the presence of cause-and-effect relationships in these situations. In this article, the author summarizes the main assumptions of analysis through instrumental variables, with a focus on Mendelian randomization. (AU)

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