A Simple Method to Remove Timing Bias From the Kidney Disease: Improving Global Outcomes Definition and Classification of Acute Kidney Injury.
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ABSTRACT:
SUBMITTER: Buchkremer F
PROVIDER: S-EPMC8207322 | biostudies-literature | 2021 Jun
REPOSITORIES: biostudies-literature
Publications
A Simple Method to Remove Timing Bias From the Kidney Disease: Improving Global Outcomes Definition and Classification of Acute Kidney Injury.
Buchkremer Florian F Segerer Stephan S
Kidney international reports 20210411 6
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Project description:ObjectivesThe definition of acute renal failure has been recently reviewed, and the term acute kidney injury (AKI) was proposed to cover the entire spectrum of the syndrome, ranging from small changes in renal function markers to dialysis needs. This study was aimed to evaluate the incidence, morbidity and mortality associated with AKI (based on KDIGO criteria) in patients after cardiac surgery (coronary artery bypass grafting or cardiac valve surgery) and to determine the value of this feature as a predictor of hospital mortality (30 days).MethodsFrom January 2003 to June 2013, a total of 2,804 patients underwent cardiac surgery in our service. Cox proportional hazard models were used to determine the association between the development of AKI and 30-day mortality.ResultsA total of 1,175 (42%) patients met the diagnostic criteria for AKI based on KDIGO classification during the first 7 postoperative days: 978 (35%) patients met the diagnostic criteria for stage 1 while 100 (4%) patients met the diagnostic criteria for stage 2 and 97 (3%) patients met the diagnostic criteria for stage 3. A total of 63 (2%) patients required dialysis treatment. Overall, the 30-day mortality was 7.1% (2.2%) for patients without AKI and 8.2%, 31% and 55% for patients with AKI at stages 1, 2 and 3, respectively. The KDIGO stage 3 patients who did not require dialysis had a mortality rate of 41%, while the mortality of dialysis patients was 62%. The adjusted Cox regression analysis revealed that AKI based on KDIGO criteria (stages 1-3) was an independent predictor of 30-day mortality (P<0.001 for all. Hazard ratio = 3.35, 11.94 and 24.85).ConclusionIn the population evaluated in the present study, even slight changes in the renal function based on KDIGO criteria were considered as independent predictors of 30-day mortality after cardiac surgery.
| S-EPMC4020924 | biostudies-literature
Project description:A simple method of sequence comparison, based on a correlation analysis of oligonucleotide frequency distributions, is here shown to be a reliable test of overall sequence similarity. The method does not involve sequence alignment procedures and permits the rapid screening of large amounts of sequence data. It identifies those sequences which deserve more careful analysis of sequence similarity at the level of resolution of the single nucleotide. It uses observed quantities only and does not involve the adoption of any theoretical model.
| S-EPMC310336 | biostudies-other
Project description:Activation of seven-transmembrane (7TM) receptors by agonists does not always lead to uniform activation of all signaling pathways mediated by a given receptor. Relative to other ligands, many agonists are "biased" toward producing subsets of receptor behaviors. A hallmark of such "functional selectivity" is cell type dependence; this poses a particular problem for the profiling of agonists in whole cell test systems removed from the therapeutic one(s). Such response-specific cell-based variability makes it difficult to guide medicinal chemistry efforts aimed at identifying and optimizing therapeutically meaningful agonist bias. For this reason, we present a scale, based on the Black and Leff operational model, that contains the key elements required to describe 7TM agonism, namely, affinity (K(A) (-1)) for the receptor and efficacy (τ) in activating a particular signaling pathway. Utilizing a "transduction coefficient" term, log(τ/K(A)), this scale can statistically evaluate selective agonist effects in a manner that can theoretically inform structure-activity studies and/or drug candidate selection matrices. The bias of four chemokines for CCR5-mediated inositol phosphate production versus internalization is quantified to illustrate the practical application of this method. The independence of this method with respect to receptor density and the calculation of statistical estimates of confidence of differences are specifically discussed.
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Project description:BackgroundCase-crossover studies have been widely used in various fields including pharmacoepidemiology. Vines and Farrington indicated in 2001 that when within-subject exposure dependency exists, conditional logistic regression can be biased. However, this bias has not been well studied.MethodsWe have extended findings by Vines and Farrington to develop a weighting method for the case-crossover study which removes bias from within-subject exposure dependency. Our method calculates the exposure probability at the case period in the case-crossover study which is used to weight the likelihood formulae presented by Greenland in 1999. We simulated data for the population with a disease where most patients receive a cyclic treatment pattern with within-subject exposure dependency but no time trends while some patients stop and start treatment. Finally, the method was applied to real-world data from Japan to study the association between celecoxib and peripheral edema and to study the association between selective serotonin reuptake inhibitor (SSRI) and hip fracture in Australia.ResultsWhen the simulated rate ratio of the outcome was 4.0 in a case-crossover study with no time-varying confounder, the proposed weighting method and the Mantel-Haenszel odds ratio reproduced the true rate ratio. When a time-varying confounder existed, the Mantel-Haenszel method was biased but the weighting method was not. When more than one control period was used, standard conditional logistic regression was biased either with or without time-varying confounding and the bias increased (up to 8.7) when the study period was extended. In real-world analysis with a binary exposure variable in Japan and Australia, the point estimate of the odds ratio (around 2.5 for the association between celecoxib and peripheral edema and around 1.6 between SSRI and hip fracture) by our weighting method was equal to the Mantel-Haenszel odds ratio and stable compared with standard conditional logistic regression.ConclusionCase-crossover studies may be biased from within-subject exposure dependency, even without exposure time trends. This bias can be identified by comparing the odds ratio by the Mantel-Haenszel method and that by standard conditional logistic regression. We recommend using our proposed method which removes bias from within-subject exposure dependency and can account for time-varying confounders.
| S-EPMC8520620 | biostudies-literature
Project description:Symmetry is a fundamental biological concept in all living organisms. It is related to a variety of physical and social traits ranging from genetic background integrity and developmental stability to the perception of physical appearance. Within this context, the study of human facial asymmetry carries a unique significance. Here, we validated an efficient method to assess 3D facial surface symmetry by best-fit approximating the original surface to its mirrored one. Following this step, the midsagittal plane of the face was automatically defined at the midpoints of the contralateral corresponding vertices of the superimposed models and colour coded distance maps were constructed. The method was tested by two operators using facial models of different surface size. The results show that the midsagittal plane definition was highly reproducible (maximum error < 0.1 mm or°) and remained robust for different extents of the facial surface model. The symmetry assessments were valid (differences between corresponding bilateral measurement areas < 0.1 mm), highly reproducible (error < 0.01 mm), and were modified by the extent of the initial surface model. The present landmark-free, automated method to assess facial asymmetry and define the midsagittal plane of the face is accurate, objective, easily applicable, comprehensible and cost effective.
| S-EPMC10681257 | biostudies-literature
Project description:PurposeDespite extensive knowledge gained over the last 3 decades regarding limbal stem cell deficiency (LSCD), the disease is not clearly defined, and there is lack of agreement on the diagnostic criteria, staging, and classification system among treating physicians and research scientists working on this field. There is therefore an unmet need to obtain global consensus on the definition, classification, diagnosis, and staging of LSCD.MethodsA Limbal Stem Cell Working Group was first established by The Cornea Society in 2012. The Working Group was divided into subcommittees. Four face-to-face meetings, frequent email discussions, and teleconferences were conducted since then to obtain agreement on a strategic plan and methodology from all participants after a comprehensive literature search, and final agreement was reached on the definition, classification, diagnosis, and staging of LSCD. A writing group was formed to draft the current manuscript, which has been extensively revised to reflect the consensus of the Working Group.ResultsA consensus was reached on the definition, classification, diagnosis, and staging of LSCD. The clinical presentation and diagnostic criteria of LSCD were clarified, and a staging system of LSCD based on clinical presentation was established.ConclusionsThis global consensus provides a comprehensive framework for the definition, classification, diagnosis, and staging of LSCD. The newly established criteria will aid in the correct diagnosis and formulation of an appropriate treatment for different stages of LSCD, which will facilitate a better understanding of the condition and help with clinical management, research, and clinical trials in this area.
| S-EPMC6363877 | biostudies-literature
Project description:The recent sequencing of a large number of Xenopus tropicalis expressed sequences has allowed development of a high-throughput approach to study Xenopus global RNA gene expression. We examined the global gene expression similarities and differences between the historically significant Xenopus laevis model system and the increasingly used X.tropicalis model system and assessed whether an X.tropicalis microarray platform can be used for X.laevis. These closely related species were also used to investigate a more general question: is there an association between mRNA sequence divergence and differences in gene expression levels? We carried out a comprehensive comparison of global gene expression profiles using microarrays of different tissues and developmental stages of X.laevis and X.tropicalis. We (i) show that the X.tropicalis probes provide an efficacious microarray platform for X.laevis, (ii) describe methods to compare interspecies mRNA profiles that correct differences in hybridization efficiency and (iii) show independently of hybridization bias that as mRNA sequence divergence increases between X.laevis and X.tropicalis differences in mRNA expression levels also increase.
| S-EPMC1325202 | biostudies-literature
Project description:BackgroundIn spite of the recognized diagnostic potential of biomarkers, the quest for squelching noise and wringing in information from a given set of biomarkers continues. Here, we suggest a statistical algorithm that--assuming each molecular biomarker to be a diagnostic test--enriches the diagnostic performance of an optimized set of independent biomarkers employing established statistical techniques. We validated the proposed algorithm using several simulation datasets in addition to four publicly available real datasets that compared i) subjects having cancer with those without; ii) subjects with two different cancers; iii) subjects with two different types of one cancer; and iv) subjects with same cancer resulting in differential time to metastasis.ResultsOur algorithm comprises of three steps: estimating the area under the receiver operating characteristic curve for each biomarker, identifying a subset of biomarkers using linear regression and combining the chosen biomarkers using linear discriminant function analysis. Combining these established statistical methods that are available in most statistical packages, we observed that the diagnostic accuracy of our approach was 100%, 99.94%, 96.67% and 93.92% for the real datasets used in the study. These estimates were comparable to or better than the ones previously reported using alternative methods. In a synthetic dataset, we also observed that all the biomarkers chosen by our algorithm were indeed truly differentially expressed.ConclusionThe proposed algorithm can be used for accurate diagnosis in the setting of dichotomous classification of disease states.
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Project description:Breast cancer becomes the second major cause of death among women cancer patients worldwide. Based on research conducted in 2019, there are approximately 250,000 women across the United States diagnosed with invasive breast cancer each year. The prevention of breast cancer remains a challenge in the current world as the growth of breast cancer cells is a multistep process that involves multiple cell types. Early diagnosis and detection of breast cancer are among the greatest approaches to preventing cancer from spreading and increasing the survival rate. For more accurate and fast detection of breast cancer disease, automatic diagnostic methods are applied to conduct the breast cancer diagnosis. This paper proposed the fuzzy-ID3 (FID3) algorithm, a fuzzy decision tree as the classification method in breast cancer detection. This study aims to resolve the limitation of an existing method, ID3 algorithm that unable to classify the continuous-valued data and increase the classification accuracy of the decision tree. FID3 algorithm combined the fuzzy system and decision tree techniques with ID3 algorithm as the decision tree learning. FUZZYDBD method, an automatic fuzzy database definition method, would be used to design the fuzzy database for fuzzification of data in the FID3 algorithm. It was used to generate a predefined fuzzy database before the generation of the fuzzy rule base. The fuzzified dataset was applied in FID3 algorithm, which is the fuzzy version of the ID3 algorithm. The inference system of FID3 algorithm is simple with direct extraction of rules from generated tree to determine the classes for the new input instances. This study also analysed the results using three breast cancer datasets: WBCD (Original), WDBC (Diagnostic) and Coimbra. Furthermore, the comparison of FID3 algorithm with the existing methods is conducted to verify the proposed method's capability and performance. This study identified that the combination of FID3 algorithm with FUZZYDBD method is reliable, robust and managed to perform well in breast cancer classification.
| S-EPMC8114800 | biostudies-literature
Project description:Coeliac disease is an intolerance triggered by the ingestion of wheat gluten proteins. It is of increasing concern to consumers and health professionals as its incidence appears to be increasing. The amino acid sequences in gluten proteins that are responsible for triggering responses in sensitive individuals have been identified showing that they vary in distribution among and between different groups of gluten proteins. Conventional breeding may therefore be used to select for gluten protein fractions with lower contents of coeliac epitopes. Molecular breeding approaches can also be used to specifically down-regulate coeliac-toxic proteins or mutate coeliac epitopes within individual proteins. A combination of these approaches may therefore be used to develop a "coeliac-safe" wheat. However, this remains a formidable challenge due to the complex multigenic control of gluten protein composition. Furthermore, any modified wheats must retain acceptable properties for making bread and other processed foods. Not surprisingly, such coeliac-safe wheats have not yet been developed despite over a decade of research.
| S-EPMC4767027 | biostudies-literature