The single individual in medicine: how to escape from the probability theory trap

Doctors and their patients are always concerned with the likely outcome of an existing disease and the risk of future diseases, but there are many problems in interpreting for the individual data derived from populations. Yet recent developments in mathematics and science should allow us to do much better

Medical concepts related to individual risk are better explained with "plausibility" rather than "probability"

BACKGROUND: The concept of risk has pervaded medical literature in the last decades and has become a familiar topic, and the concept of probability, linked to binary logic approach, is commonly applied in epidemiology and clinical medicine. The application of probability theory to groups of individuals is quite straightforward but can pose communication challenges at individual level. Few articles by the way have tried to focus the concept of "risk" at the individual subject level rather than at population level. DISCUSSION: The author has reviewed the conceptual framework which has led to the use of probability theory in the medical field in a time when the principal causes of death were represented by acute disease often of infective origin. In the present scenario, in which chronic degenerative disease dominate and there are smooth transitions between health and disease the use of fuzzy logic rather than binary logic would be more appropriate. The use of fuzzy logic in which more than two possible truth-value assignments are allowed overcomes the trap of probability theory when dealing with uncertain outcomes, thereby making the meaning of a certain prognostic statement easier to understand by the patient. SUMMARY: At individual subject level the recourse to the term plausibility, related to fuzzy logic, would help the physician to communicate to the patient more efficiently in comparison with the term probability, related to binary logic. This would represent an evident advantage for the transfer of medical evidences to individual subjects

How artificial intelligence tools can be used to assess individual patient risk in cardiovascular disease: problems with the current methods

BACKGROUND: In recent years a number of algorithms for cardiovascular risk assessment has been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years DISCUSSION: The author has identified three major pitfalls of these algorithms, linked to the limitation of the classical statistical approach in dealing with this kind of non linear and complex information. The pitfalls are the inability to capture the disease complexity, the inability to capture process dynamics, and the wide confidence interval of individual risk assessment. Artificial Intelligence tools can provide potential advantage in trying to overcome these limitations. The theoretical background and some application examples related to artificial neural networks and fuzzy logic have been reviewed and discussed. SUMMARY: The use of predictive algorithms to assess individual absolute risk of cardiovascular future events is currently hampered by methodological and mathematical flaws. The use of newer approaches, such as fuzzy logic and artificial neural networks, linked to artificial intelligence, seems to better address both the challenge of increasing complexity resulting from a correlation between predisposing factors, data on the occurrence of cardiovascular events, and the prediction of future events on an individual level

Optical Coherence Tomography in the UK Biobank Study - Rapid Automated Analysis of Retinal Thickness for Large Population-Based Studies

PURPOSE: To describe an approach to the use of optical coherence tomography (OCT) imaging in large, population-based studies, including methods for OCT image acquisition, storage, and the remote, rapid, automated analysis of retinal thickness. METHODS: In UK Biobank, OCT images were acquired between 2009 and 2010 using a commercially available “spectral domain” OCT device (3D OCT-1000, Topcon). Images were obtained using a raster scan protocol, 6 mm x 6 mm in area, and consisting of 128 B-scans. OCT image sets were stored on UK Biobank servers in a central repository, adjacent to high performance computers. Rapid, automated analysis of retinal thickness was performed using custom image segmentation software developed by the Topcon Advanced Biomedical Imaging Laboratory (TABIL). This software employs dual-scale gradient information to allow for automated segmentation of nine intraretinal boundaries in a rapid fashion. RESULTS: 67,321 participants (134,642 eyes) in UK Biobank underwent OCT imaging of both eyes as part of the ocular module. 134,611 images were successfully processed with 31 images failing segmentation analysis due to corrupted OCT files or withdrawal of subject consent for UKBB study participation. Average time taken to call up an image from the database and complete segmentation analysis was approximately 120 seconds per data set per login, and analysis of the entire dataset was completed in approximately 28 days. CONCLUSIONS: We report an approach to the rapid, automated measurement of retinal thickness from nearly 140,000 OCT image sets from the UK Biobank. In the near future, these measurements will be publically available for utilization by researchers around the world, and thus for correlation with the wealth of other data collected in UK Biobank. The automated analysis approaches we describe may be of utility for future large population-based epidemiological studies, clinical trials, and screening programs that employ OCT imaging

Associations with Retinal Pigment Epithelium Thickness Measures in a Large Cohort: Results from the UK Biobank

PURPOSE: To describe associations of ocular and systemic factors with retinal pigment epithelium (RPE)-Bruch's membrane (BM) complex thickness as measured by spectral-domain (SD) optical coherence tomography (OCT). DESIGN: Multisite community-based study. This research has been conducted using the UK Biobank Resource. PARTICIPANTS: Sixty-seven thousand three hundred eighteen people 40 to 69 years old received questionnaires, physical examination, and eye examination, including macular SD OCT. Systematic selection process identified 34 652 eyes with high-quality SD OCT images from normal individuals for analysis. METHODS: We included people with no self-reported ocular disease, diabetes, or neurologic disorders; visual acuity of ≥20/25; refraction between -6 diopters (D) to 6 D, and IOP of 6 to 21 mmHg. Only high-quality, well-centered SD OCT images with central, stable fixation were included. Descriptive statistics, t tests, and regression analyses were performed. Multivariate regression modeling was used to adjust for covariates and to identify relationships between RPE-BM thickness and ocular and systemic features. MAIN OUTCOME MEASURES: Retinal pigment epithelium-BM thickness, as measured by SD OCT segmentation using Topcon Advanced Boundary Segmentation at 9 Early Treatment of Diabetic Retinopathy Study subfields. RESULTS: Mean RPE-BM thickness was 26.3 μm (standard deviation, 4.8 μm) at central subfield. Multivariate regression with age stratification showed that RPE thinning became apparent after age 45. Among those aged ≤45, RPE-BM was significantly thicker among those of black or mixed/other race (+3.61 and +1.77 μm vs. white, respectively; P 45, RPE-BM was significantly thinner with older age (-0.10 μm/year; P < 0.001), Asian ethnicity (-0.45 μm vs. white; P = 0.02), taller height (-0.02 μm/cm; P < 0.001), higher IOP (-0.03 μm/mmHg; P < 0.001), and regular smoking (-0.27 μm vs. nonsmokers; P = 0.02). In contrast, RPE-BM was significantly thicker among black or mixed/other race (+3.29 μm and +0.81 μm vs. white, respectively; P < 0.001) and higher hyperopia (+0.28 μm/D; P < 0.001). There was no significant association with sex or Chinese ethnicity. CONCLUSIONS: We describe novel findings of RPE-BM thickness in normal individuals, a structure that varies with age, ethnicity, refraction, IOP, and smoking. The significant association with IOP is especially interesting and may have relevance for the etiology of glaucoma, while the association between age and smoking may have relevance for the etiology of age-related macular degeneration

Cervical spine signs and symptoms: perpetuating rather than predisposing factors for temporomandibular disorders in women

AIM: The purpose of this study was to assess in a sample of female community cases the relationship between the increase of percentage of cervical signs and symptoms and the severity of temporomandibular disorders (TMD) and vice-versa. MATERIAL AND METHODS: One hundred women (aged 18-26 years) clinically diagnosed with TMD signs and symptoms and cervical spine disorders were randomly selected from a sample of college students. RESULTS: 43% of the volunteers demonstrated the same severity for TMD and cervical spine disorders (CSD). The increase in TMD signs and symptoms was accompanied by increase in CSD severity, except for pain during palpation of posterior temporal muscle, more frequently observed in the severe CSD group. However, increase in pain during cervical extension, sounds during cervical lateral flexion, and tenderness to palpation of upper fibers of trapezius and suboccipital muscles were observed in association with the progression of TMD severity. CONCLUSION: The increase in cervical symptomatology seems to accompany TMD severity; nonetheless, the inverse was not verified. Such results suggest that cervical spine signs and symptoms could be better recognized as perpetuating rather than predisposing factors for TMD

Isolation and functional characterization of a cotton ubiquitination-related promoter and 5'UTR that drives high levels of expression in root and flower tissues

<p>Abstract</p> <p>Background</p> <p>Cotton (<it>Gossypium </it>spp.) is an important crop worldwide that provides raw material to 40% of the textile fiber industry. Important traits have been studied aiming the development of genetically modified crops including resistance to insect and diseases, and tolerance to drought, cold and herbicide. Therefore, the characterization of promoters and regulatory regions is also important to achieve high gene expression and/or a specific expression pattern. Commonly, genes involved in ubiquitination pathways are highly and differentially expressed. In this study, we analyzed the expression of a cotton ubiquitin-conjugating enzyme (E2) family member with no previous characterization.</p> <p>Results</p> <p>Nucleotide analysis revealed high identity with cotton <it>E2 </it>homologues. Multiple alignment showed a premature stop codon, which prevents the encoding of the conserved cysteine residue at the <it>E2 </it>active site, and an intron that is spliced in <it>E2 </it>homologues, but not in <it>GhGDRP85</it>. The <it>GhGDRP85 </it>gene is highly expressed in different organs of cotton plants, and has high transcript levels in roots. Its promoter (uceApro2) and the 5'UTR compose a regulatory region named uceA1.7, and were isolated from cotton and studied in <it>Arabidopsis thaliana</it>. uceA1.7 shows strong expression levels, equaling or surpassing the expression levels of CaMV35S. The uceA1.7 regulatory sequence drives GUS expression 7-fold higher in flowers, 2-fold in roots and at similar levels in leaves and stems. GUS expression levels are decreased 7- to 15-fold when its 5'UTR is absent in uceApro2.</p> <p>Conclusions</p> <p>uceA1.7 is a strong constitutive regulatory sequence composed of a promoter (uceApro2) and its 5'UTR that will be useful in genetic transformation of dicots, having high potential to drive high levels of transgene expression in crops, particularly for traits desirable in flower and root tissues.</p