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Готові списки джерел за темами / Confounding Factor

Добірка наукової літератури з теми "Confounding Factor"

Автор: Grafiati

Опубліковано: 7 липня 2024

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Статті в журналах з теми "Confounding Factor":

1

Pantoja Zarza, Lucía, Carolina Díez Morrondo, and José Antonio Manjón Haces. "Arthritis and Onychophagia: A Confounding Factor." Reumatología Clínica (English Edition) 10, no. 4 (July 2014): 260–61. http://dx.doi.org/10.1016/j.reumae.2013.12.004.

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2

Gençağa, Deniz. "Confounding Factor Analysis for Vocal Fold Oscillations." Entropy 25, no. 12 (November 23, 2023): 1577. http://dx.doi.org/10.3390/e25121577.

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This paper provides a methodology to better understand the relationships between different aspects of vocal fold motion, which are used as features in machine learning-based approaches for detecting respiratory infections from voice recordings. The relationships are derived through a joint multivariate analysis of the vocal fold oscillations of speakers. Specifically, the multivariate setting explores the displacements and velocities of the left and right vocal folds derived from recordings of five extended vowel sounds for each speaker (/aa/, /iy/, /ey/, /uw/, and /ow/). In this multivariate setting, the differences between the bivariate and conditional interactions are analyzed by information-theoretic quantities based on transfer entropy. Incorporation of the conditional quantities reveals information regarding the confounding factors that can influence the statistical interactions among other pairs of variables. This is demonstrated on a vector autoregressive process where the analytical derivations can be carried out. As a proof of concept, the methodology is applied on a clinically curated dataset of COVID-19. The findings suggest that the interaction between the vocal fold oscillations can change according to individuals and presence of any respiratory infection, such as COVID-19. The results are important in the sense that the proposed approach can be utilized to determine the selection of appropriate features as a supplementary or early detection tool in voice-based diagnostics in future studies.

3

Md Muslim, Mohd Zakwan, Tuan Salwani Tuan Ismail, Siti Nadirah Ab Rahim, and Rahidatul Fairuz Ibrahim. "Challenges Confounding Biochemical Diagnosis of Acromegaly." Asian Journal of Medicine and Biomedicine 8, no. 1 (February 28, 2024): 50–57. http://dx.doi.org/10.37231/ajmb.2024.8.1.716.

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Abstract: Acromegaly is a disorder caused by growth hormone (GH) hypersecretion resulting in excessive release of insulin like growth factor-1 (IGF-1). Both GH and IGF-1 measurements are crucial in its accurate diagnosis and in differentiating it from pseudoacromegaly. Early diagnosis is frequently restricted by its subtle, unnoticeable pathological changes; hence, clinical presentation is often late. Therefore, biochemical diagnosis is critical. However, the straightforward interpretation of these markers are hindered by factors that contribute to GH – IGF-1 discordance observed both in static and in dynamic function tests. These factors include both markers biological variation and their analytical assay limitations, which lead to false positive and negative results. This review is describing the pitfalls and challenges confounding the biochemical diagnosis of acromegaly. Despite these interpretive challenges, we strongly believe that interpretation of these results could be facilitated by effective clinician-laboratory professional communications which is the highlight of this review. Keywords: Acromegaly, growth hormone (GH), insulin like growth factor-1 (IGF-1), IGF-binding proteins (IGFBP)

4

Beder, Jay H. "The problem of confounding in two-factor experiments." Communications in Statistics - Theory and Methods 18, no. 2 (January 1989): 591–612. http://dx.doi.org/10.1080/03610928908829921.

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5

Beder, Jay H. "The problem of confounding in two-factor experiments." Communications in Statistics - Theory and Methods 18, no. 6 (January 1989): 2165–88. http://dx.doi.org/10.1080/03610928908830029.

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6

Sneddon, Lynne U. "Pain in Laboratory Animals: A Possible Confounding Factor?" Alternatives to Laboratory Animals 45, no. 3 (July 2017): 161–64. http://dx.doi.org/10.1177/026119291704500309.

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7

Randhawa, Puneet Kaur, Anjana Bali, Jasleen Kaur Virdi, and Amteshwar Singh Jaggi. "Conditioning-induced cardioprotection: Aging as a confounding factor." Korean Journal of Physiology & Pharmacology 22, no. 5 (2018): 467. http://dx.doi.org/10.4196/kjpp.2018.22.5.467.

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8

Laszlo, John. "Is Sjogren's syndrome a confounding factor in COVID-19?" Journal of Oral Medicine and Oral Surgery 27, no. 2 (2021): 26. http://dx.doi.org/10.1051/mbcb/2021003.

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9

Kallmes, D. F. "Point: CFD—Computational Fluid Dynamics or Confounding Factor Dissemination." American Journal of Neuroradiology 33, no. 3 (January 19, 2012): 395–96. http://dx.doi.org/10.3174/ajnr.a2993.

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10

Jardri, Renaud, Michel Maron, Pierre Delion, and Pierre Thomas. "Pain as a confounding factor in postnatal depression screening." Journal of Psychosomatic Obstetrics & Gynecology 31, no. 4 (October 12, 2010): 252–55. http://dx.doi.org/10.3109/0167482x.2010.521271.

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Дисертації з теми "Confounding Factor":

1

Tarassova, Olga. "Effects of physical and cognitive exercise on levels of peripheral BDNF in elderly : with cardiorespiratory fitness as a potential confounding factor." Thesis, Gymnastik- och idrottshögskolan, GIH, Institutionen för idrotts- och hälsovetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:gih:diva-5850.

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2

Zayat, Ahmed Salem. "Confounding factors in musculoskeletal ultrasound." Thesis, University of Leeds, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.574628.

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Musculoskeletal ultrasound (US) is an imaging modality with the potential to revolutionise the way we practise rheumatology. Ultrasound has been shown to be more sensitive and valid when compared to conventional imaging methods and clinical examination in the assessment of inflammatory arthropathies (lA). However, major limitations to its widespread use have been its perceived poor reliability and unknown diagnostic discriminative ability. Image acquisition is a key point for improving reliability. A systematic literature review was performed and a survey of experts was obtained in order to understand the important confounding factors in image acquisition. The effect of two of these factors on synovitis detection was then examined. Non-steroidal anti-inflammatory drugs (NSAIDs) usage was found to significantly mask both grey scale (GS) and power Doppler (PD) signal and resultedinlower assessment of disease activity. Change in the joint position during scanning was found to significantly alter US findings in patients with lA. Scanning the hands in a flat position and the knees in a 30° position provided the highest GS and PD scores suggesting that they may be the optimal scanning positions. The ability of US to discriminate rheumatoid arthritis (RA) from other diseases by detecting bone erosions was explored by examining the specificity of US detected bone erosion. The overall presence of US detected erosions was not a specific fmding for RA. However, erosions in certain anatomical sites were specific for RA. In conclusion, this thesis has demonstrated that certain factors. including concurrent NSAID intake and joint position can affect US image acquisition. Ultrasound does / IV have the ability to discriminate RA from other diseases by specifically detecting bone erosions in target joints. Standardisation of the US confounding factors and better understanding of the specificity of common US findings may enhance the role of US in the assessment of IA.

3

Redman, Mary W. "Estimating causal effects with observational data : the intensity-score approach to adjusting for confounding /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/9596.

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4

Taylor, Jean. "Birth weight and acute childhood leukemia : a meta-analysis of observational studies /." Download the dissertation in PDF, 2005. http://www.lrc.usuhs.mil/dissertations/pdf/Taylor2005.pdf.

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5

Bernhardt, Alexandra A. "Saliva cortisol profiles in field research internal structure, confounding factors, quantification, and stability." [S.l. : s.n.], 2007. http://nbn-resolving.de/urn:nbn:de:bsz:180-madoc-13928.

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6

Zielke, Hanno [Verfasser]. "Time-related alterations and other confounding factors in direct sediment contact tests / Hanno Zielke." Aachen : Hochschulbibliothek der Rheinisch-Westfälischen Technischen Hochschule Aachen, 2011. http://d-nb.info/1014298180/34.

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7

Ylöstalo, P. (Pekka). "Dental health, lifestyle and cardiovascular risk factors—a study among a cohort of young adult population in northern Finland." Doctoral thesis, University of Oulu, 2008. http://urn.fi/urn:isbn:9789514287213.

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Abstract To date, most epidemiological studies have shown a weak or moderate association between dental diseases such as periodontal infections, dental caries and tooth loss, and atherosclerotic vascular diseases. However, the nature of this association is not known; it may be due to the biological effect of oral infections on initiation or progress of atherosclerosis or it may be non-causal due to determinants in common, either biological or behavioural. Methodological shortcomings, inconsistent results and a lack of definite proof from intervention studies have led to the conclusion that causality between dental diseases and atherosclerotic vascular diseases has not been established. The aim of this study was to produce evidence on the nature of the association between dental diseases and atherosclerotic vascular diseases. The study uses data from the 1966 Birth Cohort of Northern Finland (N = 11,637). The data were collected in 1997–1998, when the cohort members had reached 31 years of age. The respondents were asked through a postal questionnaire about their oral health. In addition, respondents were asked about their general health and oral and general health habits. The response rate was 75.3%. Those who lived in Northern Finland or the capital city region were invited to clinical health examination (N = 8,463). Altogether 5,696 subjects supplied the data, representing 67.3% of those who were invited to the clinical examination. While the study showed an association of self-reported gingivitis, dental caries and tooth loss with the prevalent angina pectoris, it also showed that these self-reported dental diseases were not important determinants for elevated C-reactive protein levels. This suggests that the associations that were found between dental conditions and prevalent angina pectoris are mainly caused by factors other than biological mechanisms related to infection or inflammation. The lack of a biological explanation related to infections or inflammatory processes suggests that other biological mechanisms or biases, including confounding, should be considered as an alternative explanation. However, it must be noted that the possibility that oral infections also contribute to the development of atherosclerosis should not be rejected either.

8

Tarafder, Mushfiqur R. "Effect of measurement error in the estimation of prevalence of infection and epidemiological associations for helminths." Oklahoma City : [s.n.], 2009.

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9

Pressat-Laffouilhère, Thibaut. "Modèle ontologique formel, un appui à la sélection des variables pour la construction des modèles multivariés." Electronic Thesis or Diss., Normandie, 2023. http://www.theses.fr/2023NORMR104.

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Répondre à une question de recherche causale dans un contexte d’étude observationnelle nécessite desélectionner des variables de confusion. Leur intégration dans un modèle multivarié en tant que co-variablespermet de diminuer le biais dans l’estimation de l'effet causal de l'exposition sur le critère de jugement. Leuridentification est réalisée grâce à des diagrammes causaux (DCs) ou des graphes orientés acycliques. Cesreprésentations, composées de noeuds et d'arcs orientés, permettent d’éviter la sélection de variables quiaugmenteraient le biais, comme les variables de médiation et de collision. Les méthodes existantes deconstruction de DCs manquent cependant de systématisme et leur représentation de formalisme, d’expressivité etde complétude. Afin de proposer un cadre de construction formel et complet capable de représenter toutes lesinformations nécessaires à la sélection des variables sur un DC enrichi, d’analyser ce DC et surtout d’expliquerles résultats de cette analyse, nous avons proposé d'utiliser un modèle ontologique enrichi de règles d'inférences.Un modèle ontologique permet notamment de représenter les connaissances sous la forme de graphe expressif etformel composé de classes et de relations similaires aux noeuds et arcs des DCs. Nous avons développél’ontologie OntoBioStat (OBS) à partir d’une liste de questions de compétence liée à la sélection des variables etde l'analyse de la littérature scientifique relative aux DCs et aux ontologies. Le cadre de construction d’OBS estplus riche que celui d’un DC, intégrant des éléments implicites tels que les causes nécessaires, contextuels d’uneétude, sur l’incertitude de la connaissance et sur la qualité du jeu de données correspondant. Afin d’évaluerl’apport d’OBS, nous l’avons utilisée pour représenter les variables d’une étude observationnelle publiée etavons confronté ses conclusions à celle d’un DC. OBS a permis d'identifier de nouvelles variables de confusiongrâce au cadre de construction différent des DCs et aux axiomes et règles d'inférence. OBS a également étéutilisée pour représenter une étude rétrospective en cours d’analyse : le modèle a permis d’expliquer dans unpremier temps les corrélations statistiques retrouvées entre les variables de l’étude puis de mettre en évidence lespotentielles variables de confusion et leurs éventuels substituts ("proxys"). Les informations sur la qualité desdonnées et l’incertitude des relations causales ont quant à elles facilité la proposition des analyses de sensibilité,augmentant la robustesse de la conclusion de l’étude. Enfin, les inférences ont été expliquées grâce aux capacitésde raisonnement offertes par le formalisme de représentation d'OBS. À terme OBS sera intégrée dans des outilsd’analyse statistique afin de bénéficier des bibliothèques existantes pour la sélection des variables et de permettreson utilisation par les épidémiologistes et les biostatisticiens
Responding to a causal research question in the context of observational studies requires the selection ofconfounding variables. Integrating them into a multivariate model as co-variables helps reduce bias in estimatingthe true causal effect of exposure on the outcome. Identification is achieved through causal diagrams (CDs) ordirected acyclic graphs (DAGs). These representations, composed of nodes and directed arcs, prevent theselection of variables that would introduce bias, such as mediating and colliding variables. However, existingmethods for constructing CDs lack systematic approaches and exhibit limitations in terms of formalism,expressiveness, and completeness. To offer a formal and comprehensive framework capable of representing allnecessary information for variable selection on an enriched CD, analyzing this CD, and, most importantly,explaining the analysis results, we propose utilizing an ontological model enriched with inference rules. Anontological model allows for representing knowledge in the form of an expressive and formal graph consisting ofclasses and relations similar to the nodes and arcs of Cds. We developed the OntoBioStat (OBS) ontology basedon a list of competency questions about variable selection and an analysis of scientific literature on CDs andontologies. The construction framework of OBS is richer than that of a CD, incorporating implicit elements likenecessary causes, study context, uncertainty in knowledge, and data quality. To evaluate the contribution of OBS,we used it to represent variables from a published observational study and compared its conclusions with thoseof a CD. OBS identified new confounding variables due to its different construction framework and the axiomsand inference rules. OBS was also used to represent an ongoing retrospective study analysis. The modelexplained statistical correlations found between study variables and highlighted potential confounding variablesand their possible substitutes (proxies). Information on data quality and causal relation uncertainty facilitatedproposing sensitivity analyses, enhancing the study's conclusion robustness. Finally, inferences were explainedthrough the reasoning capabilities provided by OBS's formal representation. Ultimately, OBS will be integratedinto statistical analysis tools to leverage existing libraries for variable selection, making it accessible toepidemiologists and biostatisticians

10

Eklundh, Thomas. "Lumbar puncture in psychiatric research : on the impact of confounding factors on monoamine compounds in cerebrospinal fluid /." Stockholm, 2000. http://diss.kib.ki.se/2000/91-628-4490-3/.

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Книги з теми "Confounding Factor":

1

Kleespies, Phillip M. Medical Illness, Suicide, and Assisted Death. Edited by Phillip M. Kleespies. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199352722.013.28.

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Because of their focus on psychopathology, mental health clinicians may overlook the potential significance of medical illness as a risk factor for suicide. In this chapter, the author presents evidence that physical illness, particularly certain physical illnesses, can be independent risk factors for suicide. In a number of these illnesses, depression is clearly a confounding risk factor, while in others the illness itself or its consequent functional impairments may lead to increased risk. When an individual has multiple physical illnesses, as often happens with the elderly, the cumulative burden can become overwhelming and heighten the risk of suicide. When physical illness becomes terminal, the competent patient has the right to refuse life-sustaining treatment. Whether that individual can receive assistance in dying has been more controversial. The chapter concludes with a presentation of data from a state where assisted suicide, also known as assisted death, has been legalized.

2

Jardine, Alan G., and Rajan K. Patel. Lipid disorders of patients with chronic kidney disease. Edited by David J. Goldsmith. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199592548.003.0102.

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The risk of developing cardiovascular (CV) disease is increased in patients with chronic kidney disease (CKD) and although dyslipidaemia is a major contributory factor to the development of premature CV disease, the relationship is complex. Changes in lipid fractions are related to glomerular filtration rate and the presence and severity of proteinuria, diabetes, and other confounding factors. The spectrum of CV disease changes from lipid-dependent, atheromatous coronary disease in early CKD to lipid-independent, non-coronary disease, manifesting as heart failure, and sudden cardiac death in advanced and end-stage renal disease. Statin-based lipid-lowering therapy is proven to reduce coronary events across the spectrum of CKD. The relative reduction in overall CV events, however, diminishes as CKD progresses and the proportion of lipid-dependent coronary events declines. There is nevertheless a strong argument for the use of statin-based therapy across the spectrum of CKD. The argument is particularly strong for those patients with progressive renal disease who will eventually require transplantation, in whom preventive therapy should start as early as possible. The SHARP study established the benefits and endorses the use of lipid-lowering therapy in CKD 3-4 but uncertainty about the value of initiation of statin therapy in CKD 5 remains. There is, however, no rationale for stopping agents started earlier in the course of the illness for compelling indications, particularly in those who will ultimately be transplanted. The place of high-density lipoprotein-cholesterol raising and triglyceride lowering therapy needs to be assessed in trials. Modifying dyslipidaemia in CKD has demonstrated that lipid-dependent atheromatous cardiovascular disease is only one component of the burden of CV disease in CKD patients, that this is proportionately less in advanced CKD, and that modification of lipid profiles is only one part of CV risk management.

3

Smith, George Davey. The biopsychosocial approach. Oxford University Press, 2015. http://dx.doi.org/10.1093/med:psych/9780198530343.003.0005.

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This chapter provides a critique of whether the biopsychosocial model is useful in understanding aetiological factors in chronic diseases. It illustrates the arguments by referring to studies on peptic ulcer and ischaemic heart diseases, and shows that bias and confounding can generate spurious findings and associations, especially in observational studies.

4

Scott, David L. Outcomes. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199642489.003.0029.

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Outcomes evaluate the impact of disease. In rheumatology they span measures of disease activity, end-organ damage, and quality of life. Some outcomes are categorical, such as the presence or absence of remission. Other outcomes involve extended numeric scales such as joint counts, radiographic scores, and quality of life measures. Outcomes can be measured in the short term—weeks and months—or over years and decades. Short-term outcomes, though readily related to treatment, may have less relevance for patients. Clinical trials focus on short-term outcomes whereas observational studies explore longer-term outcomes. The matrix of rheumatic disease outcomes is exemplified by rheumatoid arthritis. Its outcomes span disease activity assessments like joint counts, damage assessed by erosive scores, quality of life evaluated by disease-specific measures like the Health Assessment Questionnaire (HAQ) or generic measures like the Short Form 36 (SF-36), overall assessments like remission, and end result such as joint replacement or death. Outcome measures are used to capture the impact of treating rheumatic diseases, and are influenced by both disease severity and the effectiveness of treatment. However, they are also influenced by a range of confounding factors. Demographic factors like age, gender, and ethnicity can all have crucial impacts. Deprivation is important, as poverty invariably worsens outcomes. Finally, comorbidities affect outcomes and patients with multiple comorbid conditions usually have worse quality of life with poorer outcomes for all diseases. These multiple confounding factors mean comparing outcomes across units without adjustment will invariably show major differences.

5

Scott, David L. Outcomes. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199642489.003.0029_update_001.

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Outcomes evaluate the impact of disease. In rheumatology they span measures of disease activity, end-organ damage, and quality of life. Some outcomes are categorical, such as the presence or absence of remission. Other outcomes involve extended numeric scales such as joint counts, radiographic scores, and quality of life measures. Outcomes can be measured in the short term—weeks and months—or over years and decades. Short-term outcomes, though readily related to treatment, may have less relevance for patients. Clinical trials focus on short-term outcomes whereas observational studies explore longer-term outcomes. The matrix of rheumatic disease outcomes is exemplified by rheumatoid arthritis. Its outcomes span disease activity assessments like joint counts, damage assessed by erosive scores, quality of life evaluated by disease-specific measures like the Health Assessment Questionnaire (HAQ) or generic measures like the Short Form 36 (SF-36), overall assessments like remission, and end result such as joint replacement or death. Outcome measures are used to capture the impact of treating rheumatic diseases, and are influenced by both disease severity and the effectiveness of treatment. However, they are also influenced by a range of confounding factors. Demographic factors like age, gender, and ethnicity can all have crucial impacts. Deprivation is important, as poverty invariably worsens outcomes. Finally, comorbidities affect outcomes and patients with multiple comorbid conditions usually have worse quality of life with poorer outcomes for all diseases. These multiple confounding factors mean comparing outcomes across units without adjustment will invariably show major differences.

6

McLean, Anthony S., and Stephen J. Huang. Cardiac injury biomarkers in the critically ill. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0301.

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To be clinically relevant, a good cardiac biomarker should have four main characteristics. It should be organ-, disease- and stage-specific to be useful in diagnosis. Its release should be timely and its half-life should be long enough to make measurement possible and meaningful. Its serum or blood concentration should be proportional to disease severity; hence, can be used as a monitoring tool. Finally, their concentrations have implications on long-term outcomes. To date, only a handful of cardiac biomarkers have clinical relevance in the intensive care setting—cardiac troponins (as a marker of cardiac injury) and B-type natriuretic peptide (as a marker of cardiac stress) being probably the most useful. However, cautious interpretations of these biomarkers are needed in intensive care patients as several confounding factors can affect their concentrations.

7

Weiss, Helen. Design issues in global mental health trials in low-resource settings. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199680467.003.0004.

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In this chapter we outline the key principles in design and analysis of trials for mental health. The chapter focuses on randomized controlled trials as these are the gold-standard trial design, which minimizes confounding due to other factors and enables us to draw conclusions about the effectiveness of the intervention. Other key principles of trial design discussed in the chapter include methods to develop a clearly stated, testable research hypothesis, definition of well-defined outcomes, appropriate choice of the control condition, masking of providers and participants where possible, realistic sample size estimates, and appropriate data monitoring and statistical analysis plans. The chapter also outlines alternatives to the parallel arm superiority trial design, such as equivalence and non-inferiority trials, cross-over, stepped wedge, fixed adaptive, and patient preference trial designs.

8

Glover, Vivette. Maternal Stress During Pregnancy and Infant and Child Outcome. Edited by Amy Wenzel. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199778072.013.006.

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Many independent prospective studies show maternal stress, anxiety, or depression during pregnancy poses an increased risk for her child to have a wide range of adverse outcomes including emotional problems, ADHD or conduct disorder, or impaired cognitive development. Several studies have shown that these adverse outcomes are independent of possible confounding factors, such as postpartum anxiety and depression. Most children are not affected, and those who are can be affected in different ways, probably due to different genetic vulnerabilities and the quality of postpartum care. An evolutionary explanation for the observed changes is proposed. Underlying mechanisms are just starting to be understood: altered function of the placenta, allowing more of the stress hormone cortisol to pass through to the fetus, may well be important, as may epigenetic changes. The implications are that improved emotional care of pregnant women should improve outcomes for their children to a clinically significant degree.

9

Cleary, Paul, Sam Ghebrehewet, and David Baxter. Essential statistics and epidemiology. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198745471.003.0022.

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This chapter provides a grounding in basic statistics, descriptive epidemiology, analytical epidemiology, and hypothesis testing appropriate for health protection practitioners. The analysis of categorical data using frequency distributions, and charts, and the interpretation of epidemic curves is described. The description of quantitative data including central tendency, standard deviation, and interquartile range is concisely explained. The role of geographical information systems and different disease map types is used to demonstrate how disease clusters may be detected. Determining possible association between specific risk factors and outcome is described in the section on analytical epidemiology, using the risk ratio and the odds ratio. The use of these in different study/investigation types is explained. The importance of confounding, matching, and standardization in study design is described. The final part of the chapter covers hypothesis testing to distinguish between real differences and chance variation, and the use of confidence intervals.

10

Knezevic, Nebojsa Nick, Benjamin Cantu, Ivana Knezevic, and Kenneth D. Candido. Chronic Back Pain in the Elderly: Spinal Stenosis. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190271787.003.0022.

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Chronic low back pain (CLBP) is a common reason for physician office visits among the elderly. Predictive factors for CLBP are female sex, social isolation, hypertension, and joint pain. In the elderly, CLBP may be related to degenerative spinal stenosis with disk degeneration and overall spondylosis. A detailed medical history and a targeted, comprehensive physical examination are the initial approaches to rule out underlying disease that requires urgent attention. Clinical and evidence-based approaches to management suggest avoiding early MRI or CT, as imaging in elderly patients has proven both impractical and uneconomical. Instead, good clinical judgment should be used for making diagnoses. Consensus on the best initial approaches for managing CLBP has not yet been achieved, and conservative therapy is suggested, varying from use of pharmacologic agents, physical therapy, electrical stimulation, and physical manipulations to epidural injections. Surgical alternatives are avoided due to confounding and multiple comorbidities in older patients.

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Частини книг з теми "Confounding Factor":

1

Marcus, Pamela M. "Observational Research Designs." In Assessment of Cancer Screening, 79–100. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94577-0_7.

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AbstractObservational studies do not dictate the cancer screening regimens that their study subjects utilize. Instead, these studies collect data on individuals’ cancer screening practices, cancer outcomes, and other factors if needed. Because no regimens are dictated, an observational study can capture information about and evaluate a variety of cancer screening practices, including use of different tests or cancer screening regimens. Observational studies can be retrospective or prospective in nature, with the distinction dependent on how and when individuals are chosen for study inclusion. Observational studies provide weaker evidence than experimental studies because observational studies are subject to confounding. Confounding occurs when a third factor is associated with both the cancer screening practice and cause-specific mortality, meaning that the third factor is not equally present among groups of individuals with different cancer screening practices and is not equally present among groups of individuals with different cancer outcomes.

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Vincze, I., G. Elek, and G. Nádor. "Is Iodide a Confounding or Effect Modifying Factor of Liver Cirrhosis?" In Environmental Health for All, 77–84. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4740-8_7.

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3

Marcus, Pamela M. "Experimental Research Designs." In Assessment of Cancer Screening, 67–78. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94577-0_6.

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AbstractRandomized controlled trials (RCTs) are experimental in nature because the intervention is assigned at random rather than chosen by the study participant or study researcher. Most RCTs comprise two groups, referred to as trial arms. The intervention arm receives the cancer screening regimen that is under intervention, while the control arm receives no intervention or the current standard of care. The control arm is treated as the counterfactual experience of the intervention arm, which is the hypothetical experience that the intervention arm would have had if the intervention had not been administered. It is the counterfactual principle that allows the outcome to be fully and solely attributable to the intervention, as randomization greatly minimizes the possibility of confounding. In the context of cancer screening, confounding occurs when a third factor is related to both screening activity and cause-specific mortality. Individual-level, cluster-level, and pragmatic RCTs are discussed in detail. Examples of each are provided.

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Maizels, Neil. "The destructive confounding of intra-uterine and post-uterine feeding as a factor against emotional growth." In The Life-Death Instinct, 24–36. London: Routledge, 2023. http://dx.doi.org/10.4324/9781003364788-3.

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5

Navarro Yáñez, Clemente J., Manuel Fernández-García, and Alicia Domínguez-González. "The Impact of the URBAN Initiative: On Residential Mobility and ‘Contextual Exposure’ to EU-Integrated Urban Development Strategies." In EU Integrated Urban Initiatives, 131–46. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-20885-0_8.

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AbstractPrevious evaluations of integrated area-based initiatives have shown moderate effects on residents’ living conditions and, therefore, neighbourhood socioeconomic composition. This chapter sustains this could be explained by residential mobility in targeted neighbourhoods: according to the ‘neighbourhood revitalisation’ frame of policy analysed, impacts should be more evident among ‘stayers’ residents who have been exposed to the project implementation. This idea is studied by performing two analyses: all residents and only ‘stayers’ residents. Both apply a repeated measurement with control groups design to analyse the change in unemployment rates, educational attainment, and socioeconomic status in experimental and control neighbourhoods. The analysis controlling by contextual exposure, including only stayers residents, shows a better impact than the analysis including all residents. Therefore, in addition to contrafactual selection according to programme eligibility criteria, impact studies should consider residential mobility as a confounding factor regarding the impact of area-based policy actions on targeted territories providing policy evidence for the debate between urban revitalisation and state-led gentrification theses on area-based initiatives.

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Pérez-García, Osvaldo Andrés. "Confounding Factors in Keystroke Dynamics." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 192–99. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25751-8_24.

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Kleinbaum, David G., Kevin M. Sullivan, and Nancy D. Barker. "Confounding Involving Several Risk Factors." In ActivEpi Companion Textbook, 311–29. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5428-1_11.

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Steele, Rachael. "Confounding Factors and Decision Enhancers." In Exploring the Criminal Decision Process, 153–92. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-46231-3_11.

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Zazueta, Aaron E., and Jeneen R. Garcia. "Multiple actors and confounding factors." In Evaluating Environment in International Development, 93–110. 2nd ed. 2. | Milton Park, Abingdon, Oxon; New York, NY: Routledge, 2021.: Routledge, 2021. http://dx.doi.org/10.4324/9781003094821-8.

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Bullinaria, John A. "Connectionist Dissociations, Confounding Factors and Modularity." In Connectionist Models in Cognitive Neuroscience, 52–63. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0813-9_5.

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Тези доповідей конференцій з теми "Confounding Factor":

1

Lu, Rui. "Controlling for Latent Confounding by Confirmatory Factor Analysis." In 2019 AERA Annual Meeting. Washington DC: AERA, 2019. http://dx.doi.org/10.3102/1442244.

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Keskin, Y. "ENVIRONMENTAL VIEWS AND BEHAVIORS OF MUNICIPALITY EMPLOYEES AND CONFOUNDING FACTOR." In SGEM2011 11th International Multidisciplinary Scientific GeoConference and EXPO. Stef92 Technology, 2011. http://dx.doi.org/10.5593/sgem2011/s20.124.

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Baselli, Giuseppe, Federico Aletti, and Manuela Ferrario. "Respiration in cardiovascular regulation models: Signal or confounding factor? A review." In 2014 8th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO). IEEE, 2014. http://dx.doi.org/10.1109/esgco.2014.6847606.

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4

Mahmoud, A., A. Gomaa, E. Eisa, M. S. Ismail, F. Ismail, M. Hassan, and I. Ismail-Sayed. "COPD: A Confounding Factor for Dyspnea on Exertion in Atrial Myxoma." In American Thoracic Society 2023 International Conference, May 19-24, 2023 - Washington, DC. American Thoracic Society, 2023. http://dx.doi.org/10.1164/ajrccm-conference.2023.207.1_meetingabstracts.a4165.

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Zayed, Nourhan, Brad Goodyear, and Michael Smith. "Is undiagnosed synaesthesia a confounding factor in the interpretation of MRI images?" In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2008. http://dx.doi.org/10.1109/iembs.2008.4650527.

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Levy, Roy. "Precluding Interpretational Confounding in Factor Analysis via Measurement and Uncertainty Preserving Parametric Modeling." In 2023 AERA Annual Meeting. Washington DC: AERA, 2023. http://dx.doi.org/10.3102/2011895.

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Wang, Haohan, Xiang Liu, Yunpeng Xiao, Ming Xu, and Eric P. Xing. "Multiplex confounding factor correction for genomic association mapping with squared sparse linear mixed model." In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2017. http://dx.doi.org/10.1109/bibm.2017.8217649.

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Frey, Daniel D., and Rajesh Jugulum. "How One-Factor-at-a-Time Experimentation Can Lead to Greater Improvements Than Orthogonal Arrays." In ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/detc2003/dtm-48646.

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This paper attempts to explain the empirically demonstrated phenomena that, under some conditions, one-at-a-time experiments outperform orthogonal arrays (on average) in parameter design of engineering systems. Five case studies are presented, each based on data from previously published full factorial experiments on actual engineering systems. Computer simulations of adaptive one-at-a-time plans and orthogonal arrays were carried out with varying degrees of pseudo-random error added to the data. The average outcomes are plotted for both approaches to optimization. For each of the five case studies, the main effects and interactions of the experimental factors are presented and analyzed to explain the observed simulation results. It is shown that, for some types of engineering systems, “one-at-a-time” designs consistently exploit interactions despite the fact that these designs lack the resolution to estimate interactions. It is also confirmed that orthogonal arrays are adversely affected by confounding of main effects and interactions.

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Uttley, J., S. Fotios, C. J. Robbins, and C. Moscoso. "THE EFFECT OF CHANGES IN LIGHT LEVEL ON THE NUMBERS OF CYCLISTS." In CIE 2021 Conference. International Commission on Illumination, CIE, 2021. http://dx.doi.org/10.25039/x48.2021.po63.

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Cycling has a range of benefits and should be encouraged, but darkness may put people off from cycling due to reductions in visibility, road safety and personal security. We summarise analyses of observational data to confirm the negative impact darkness has on cycling rates. Using a Case / Control method that accounts for confounding factors such as time of day and seasonal variations in weather, we demonstrate a consistent effect of darkness across different locations and countries. The size of this effect varies though, suggesting certain unknown factors may be important in mediating the impact of darkness on cycling rates. One factor that is known to mediate the effect is road lighting. We show that increased illuminance can offset the reductions in cyclists caused by darkness and also that there may be an optimal illuminance after which no further benefits may be achieved.

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Bittner, Alvah. "Criterion Referenced Factor Analysis (CRFA): Method and Illustration." In 33rd Annual International Occupational Ergonomics and Safety Conference. International Society for Occupational Ergonomics and Safety, 2021. http://dx.doi.org/10.47461/isoes.2021_041.

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CRFA is a valid method for evaluating relationships between criteria and “factors'' initially identified from both the predictor and the criterion variables. Among others, it may be applied to classical problems involving: 1) Changes in complex task ability requirements as a function of practice, 2) Impacts of environmental stressors on personality or performance factors overtime, or 3) Residential Lifestyle Factor Impacts on Energy-Use (as herein). CRFA differs from traditional battery developments in its: (a) Initial inclusion of both criterion and predictor variables for factor identifications, but (b) Exclusion of criterion in the ultimate calculation of factor-scores. This avoids the vexing confounding of criterion variance in factor score estimates, and ultimately provides for unconfounded analyses of criterion and factor relationships. A “Big-Data'' illustration of CRFA is presented that highlights the stability of model results for independent samples across years. The primary model of interest built upon a USA-representative survey (N = 2,165) sample of 17 variables adapted from RECS-2005 (USEIA, 2019). These included16 lifestyle-related and an annual energy use criterion (i.e., LNKWH, Ln-transformed annual KiloWatt Hours). Unweighted least squares (ULS) factor analysis revealed a 5- Lifestyle factor solution that accounted for 45.5% of the total variation in the 17-variable set and 45.3% of the 16 less LNKWH. “Lifestyle” factor predictions – subsequently derived by CRFA less LNKWH– are found to be remarkably stable when compared to a similar sample taken 4-years earlier (RECS-2001). Specifically, (1) the proportions of LNKWH variance explained with lifestyle factor scores alone are nearly identical across the 4-year gap (2005 R2 = 0.42- and 2001 R2 = 0.38; ps <10-10), (2) these increased after external additions of household characteristics (R2 = 0.55 both fore- and back-casting; ps <10-15), and model B-weights were near identical. CRFA is strongly recommended for valid evaluations of relationships between criteria and predictor-based factor-scores, where factor characterizations are initially derived from both predictor and criterion variables.

Звіти організацій з теми "Confounding Factor":

1

John, Oliver, and Manuela Ott. SNSF Datastory - Gender monitoring (part 3): The impact of confounding factors. Swiss National Science Foundation, April 2022. http://dx.doi.org/10.46446/datastory.gender-monitoring-confounders.

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Differences in success rates between women and men in SNSF funding can be explained by a variety of different direct and indirect influences. This data story summarizes the SNSF's gender monitoring that looks at potential confounding variables using the example of project funding.

2

Esbach, Michael, and Brian Weeks. Valuing Ecosystem Services: A Qualitative Analysis of Drinking Water in the Solomon Islands. American Museum of Natural History, 2010. http://dx.doi.org/10.5531/cbc.ncep.0014.

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This case study introduces the concept of ecosystem valuation through a hypothetical drinking water scenario in the Solomon Islands. Solomon Islanders, along with all humans, benefit from the resources and processes supplied by natural ecosystems that are increasingly threatened due to human demands. On top of this, ecosystem services are undervalued in a market-based system. This case study gives readers a real-world perspective of the applicability, opportunities, and confounding factors that exist when valuing ecosystem services.

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Buvinic, Mayra. Cost of Adolescent Childbearing: A Review of Evidence from Chile, Barbados, Guatemala and Mexico. Inter-American Development Bank, July 1998. http://dx.doi.org/10.18235/0008884.

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Does early childbearing restrict women's social and economic opportunities? These questions are explored by examining the effects, first on marital status and family formation, and second on women's employment options, earnings and poverty condition. The four studies presented here (from Chile, Barbados, Guatemala and Mexico) include controls for background variables and the timing of the consequences of observations. The review describes gross differences that emerged in the studies and explores how much the observed differences were due to background factors associated with adolescent childbearing, including poverty, which is a potentially large confounding variable in developing economies. The presence of sizable poverty and the nature of women's economic participation provide the common ground to assess consequences of adolescent childbearing in countries that otherwise iffer considerable in the cultural circumstances surrounding family formation and childbearing.

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Walthert, Lorenz, Douglas R. Cobos, and Patrick Schleppi. Technical report. Equations for improving the accuracy of Decagon MPS-2 matric potential readings in dry soils. Swiss Federal Institute for Forest, Snow and Landscape Research, WSL, November 2023. http://dx.doi.org/10.55419/wsl:33724.

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Soil matric potential quantifies water availability in soils. Low soil matric potentials are difficult to measure with most in situ techniques. This is also the case for the widely-used dielectric MPS-2 sensor. This probe determines matric potential indirectly from the measured water content in its porous sensor ceramics using dielectric permittivity as a proxy for water content. The accuracy of MPS-2 readings was analyzed in desiccation experiments using 13 soils with different texture and organic carbon content and a WP4C dewpoint potentiometer as reference instrument. Further, it was explored whether observed inaccuracies relate to sensor calibration, confounding dielectric effects, or the water release characteristics of the sensor ceramics. Above -1000 kPa, the MPS-2 readings were accurate in all tested soils with a mean deviation of 3% to the reference values. Below -1000 kPa, MPS-2 readings were increasingly higher than the reference in all tested soils, but the deviation from the reference depended on soil type. Poor factory calibration of the sensors, soil texture dependent differences of water flow at the soil-ceramic interface, and dielectric effects are supposed to be the main reasons for the low and soil-type-specific MPS-2 sensor accuracy in dry soils. Nevertheless, the high consistency of the MPS-2 readings allowed us to derive soil-type-specific equations to improve the accuracy of measurements to values as low as -4000 kPa. We recommend applying the equations to any MPS-2 readings below ~ -1000 kPa to obtain more reliable data and thus an improved insight into the role of soil water in ecosystems.

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Balza, Lenin, Nicolás Gómez Parra, Jorge Cuartas, and Tomás Serebrisky. Infrastructure Services and Early Childhood Development in Latin America and the Caribbean: Water, Sanitation, and Garbage Collection. Inter-American Development Bank, June 2024. http://dx.doi.org/10.18235/0012998.

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Access to essential infrastructure services such as water, sanitation, and garbage collection can considerably affect children's environment and may play a significant role in shaping early childhood developmental and health outcomes. Using data from the Multiple Indicator Cluster Surveys (MICS) and the Demographic and Health Surveys (DHS) for 18 countries in Latin America and the Caribbean (LAC), we show a significant positive association between access to water and sanitation and early childhood development, as well as reduced instances of stunting. In addition, we identify a negative association between access to improved garbage collection services and the rates of stunting and underweight among children under five. Our findings are robust after using alternative measures for access and controlling for individual, maternal, and household factors, alongside considerations of household wealth and caregiver's stimulation activities. Similarly, the economic relevance of the relationship is highlighted by the substantial gap relative to the size of the vulnerable groups, persisting even after adjusting for confounding variables. Our results also suggest that households may be able to lessen the potential impact of pollutants through mitigation measures such as treating water to make it safe for consumption, using handwashing cleansers, and storing household trash in lidded containers. The current findings underscore the importance of investing in basic infrastructure services as a critical component of comprehensive strategies to enhance early childhood development and health in low- and middle-income countries. We emphasize the importance of considering the quality and type of infrastructure services alongside their availability. Future research should incorporate more complete and detailed data to improve understanding of the causal relationship between water, sanitation, and garbage collection and early childhood development, as well as the mechanisms underlying the observed associations.

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Investigation of the Relative Performance of Vaned and Vaneless Mixed Flow Turbines for Medium and Heavy-Duty Diesel Engine Applications with Pulse Exhaust Systems. SAE International, April 2021. http://dx.doi.org/10.4271/2021-01-0644.

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This paper details results of a numerical and experimental investigation into the relative performance of vaned and vaneless mixed flow turbines for application to medium and heavy-duty diesel engines utilizing pulse exhaust systems. Previous investigations into the impact of nozzle vanes on turbine performance considered only open turbine housings, whereas a majority of medium and heavy-duty diesel engine applications are six-cylinder engines using pulse exhaust systems with divided turbines. The two turbine stages for this investigation were carefully designed to meet the constraints of engines with pulse exhaust systems and to control confounding factors that would undermine the vaned vs vaneless performance comparison. Detailed CFD analysis and turbine dynamometer test results confirm a significant efficiency advantage for the vaned turbine stage under both full and partial admission conditions.