Interrater reliability of diagnostic methods in traditional Indian ayurvedic medicine.
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ABSTRACT:
SUBMITTER: Kurande V
PROVIDER: S-EPMC3803118 | biostudies-literature | 2013
REPOSITORIES: biostudies-literature
Publications
Interrater reliability of diagnostic methods in traditional Indian ayurvedic medicine.
Kurande Vrinda V Bilgrau Anders Ellern AE Waagepetersen Rasmus R Toft Egon E Prasad Ramjee R
Evidence-based complementary and alternative medicine : eCAM 20130926
This study assesses the interrater reliability of Ayurvedic pulse (nadi), tongue (jivha), and body constitution (prakriti) assessments. Fifteen registered Ayurvedic doctors with 3-15 years of experience independently examined twenty healthy subjects. Subjects completed self-assessment questionnaires and software analyses for prakriti assessment. Weighted kappa statistics for all 105 pairs of doctors were computed for the pulse, tongue, and prakriti data sets. According to the Landis-Koch scale, ...[more]
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Project description:BackgroundInterrater reliability, aka intercoder reliability, is defined as true agreement between raters, aka coders, without chance agreement. It is used across many disciplines including medical and health research to measure the quality of ratings, coding, diagnoses, or other observations and judgements. While numerous indices of interrater reliability are available, experts disagree on which ones are legitimate or more appropriate. Almost all agree that percent agreement (ao), the oldest and the simplest index, is also the most flawed because it fails to estimate and remove chance agreement, which is produced by raters' random rating. The experts, however, disagree on which chance estimators are legitimate or better. The experts also disagree on which of the three factors, rating category, distribution skew, or task difficulty, an index should rely on to estimate chance agreement, or which factors the known indices in fact rely on. The most popular chance-adjusted indices, according to a functionalist view of mathematical statistics, assume that all raters conduct intentional and maximum random rating while typical raters conduct involuntary and reluctant random rating. The mismatches between the assumed and the actual rater behaviors cause the indices to rely on mistaken factors to estimate chance agreement, leading to the numerous paradoxes, abnormalities, and other misbehaviors of the indices identified by prior studies.MethodsWe conducted a 4 × 8 × 3 between-subject controlled experiment with 4 subjects per cell. Each subject was a rating session with 100 pairs of rating by two raters, totaling 384 rating sessions as the experimental subjects. The experiment tested seven best-known indices of interrater reliability against the observed reliabilities and chance agreements. Impacts of the three factors, i.e., rating category, distribution skew, and task difficulty, on the indices were tested.ResultsThe most criticized index, percent agreement (ao), showed as the most accurate predictor of reliability, reporting directional r2 = .84. It was also the third best approximator, overestimating observed reliability by 13 percentage points on average. The three most acclaimed and most popular indices, Scott's π, Cohen's κ and Krippendorff's α, underperformed all other indices, reporting directional r2 = .312 and underestimated reliability by 31.4 ~ 31.8 points. The newest index, Gwet's AC1, emerged as the second-best predictor and the most accurate approximator. Bennett et al's S ranked behind AC1, and Perreault and Leigh's Ir ranked the fourth both for prediction and approximation. The reliance on category and skew and failure to rely on difficulty explain why the six chance-adjusted indices often underperformed ao, which they were created to outperform. The evidence corroborated the notion that the chance-adjusted indices assume intentional and maximum random rating while the raters instead exhibited involuntary and reluctant random rating.ConclusionThe authors call for more empirical studies and especially more controlled experiments to falsify or qualify this study. If the main findings are replicated and the underlying theories supported, new thinking and new indices may be needed. Index designers may need to refrain from assuming intentional and maximum random rating, and instead assume involuntary and reluctant random rating. Accordingly, the new indices may need to rely on task difficulty, rather than distribution skew or rating category, to estimate chance agreement.
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Project description:Traditional Triphala (three fruits), consisting of Phyllanthus emblica, Terminalia chebula, and Terminalia bellirica, presents a broad range of biological activities. However, its ability to inhibit dengue virus (DENV) infection has not been reported yet. Herein, the authors investigated the efficiency of three different Triphala formulations and its individual extract constituents to inhibit DENV infection. Treatment with T. bellirica extract or Triphala formulated with a high ratio of T. bellirica extract showed remarkable efficiency in significantly lowering DENV infection in Vero cells. Their effects were further studied in Huh7 cells, to address its potential ability in human cells. Treatment with 100 μg/mL of T. bellirica extract or Triphala resulted in an approximate 3000-fold or 1000-fold lowering of virus production, respectively. Furthermore, the treatment diminished IL-6 and CXCL-10 expressions, which are the hallmark of the cytokine storm phenomenon in DENV infection. The HPLC profiling demonstrated gallic acid as a major compound, the treatment by which showed its ability to effectively inhibit DENV infection after virus entry. Molecular docking demonstrated that gallic acid was able to interact with DENV NS5 protein, which could be one of Triphala's antiviral mechanism. This study offers Triphala formulation and its ingredient, T. bellirica extract, as a natural based pharmaceutical to be used in DENV infection treatment.
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Project description:traditional chinese medicine Targeted loci
| PRJNA796441 | ENA
Project description:Background: Ayurveda is a traditional Indian system of medicine. The customized Ayurvedic approach consists of a combination of several diagnostic procedures and subsequent individualized therapeutic interventions. Evaluation of inter-rater reliability (IRR) of Ayurvedic diagnoses has rarely been performed. The aim of this study was to evaluate IRR of Ayurvedic diagnosis for patients with knee osteoarthritis. Methods: A diagnostic reliability study of 30 patients and 4 Ayurvedic experts was nested in a randomized controlled trial. Patients were diagnosed in a sequential order by all experts utilizing a semistructured patient history form. A nominal group technique as consensus procedure was performed to reach agreement on the items to be diagnosed. An IRR analysis using Fleiss' and Cohen's kappa statistics was performed to determine a chance-corrected measure of agreement among raters. Results: One hundred and twenty different ratings and 30 consensus ratings were performed and analyzed. While high percentages of agreement for main diagnostic entities and the final Ayurveda diagnosis (95% consensus agreement on main diagnosis) could be observed, this was not reflected in the corresponding kappa values, which largely yielded fair-to-poor inter-rater agreement kappas for central diagnostic aspects such as prakriti and agni (κ values between 0 and 0.4). Notably, agreement on disease-related entities was better than that on constitutional entities. Conclusions: This is the first diagnostic study embedded in a clinical trial on patients with knee osteoarthritis utilizing a multimodality whole systems approach. Results showed a contrast between the high agreement of the consented final diagnosis and disagreement on certain diagnostic details. Future diagnostic studies should have larger sample sizes and a methodology more tailored to the specificities of traditional whole systems of medicine. Equal emphasis will need to be placed on all core diagnostic components of Ayurveda, both constitutional and disease specific, using detailed structured history taking forms.
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Project description:ObjectivesThe aim of this study was to evaluate the reliability between observers with regard to pulse signs that are observed by Traditional Korean Medicine (TKM) clinicians.MethodsA total 658 patients with stroke who were admitted into Oriental medical university hospitals from February 2010 through December 2010 were included in this study. Each patient was seen independently by 2 experts from the same department for an examination of the pulse signs. Interobserver reliability was measured using three methods: simple percentage agreement, the ? value, and the AC(1) statistic.ResultsThe ? value indicated that the interobserver reliability in evaluating the pulse signs of the subjects ranged from poor to moderate, whereas the AC(1) analysis revealed that agreement between the 2 experts was generally high (with the exception of slippery pulse). The ? value indicated that the interobserver reliability for assessing subjects who garnered the same opinion between the raters was generally moderate to good (with the exceptions of rough pulse and sunken pulse) and that the AC(1) measure of agreement between the 2 experts was generally high.ConclusionsPulse diagnosis is regarded as one of the most important procedures in TKM, despite the aforementioned limitations. This study reveals that the interobserver reliability in making a pulse diagnosis in stroke patients is not particularly high when objectively quantified. Additional research is needed to help reduce this lack of reliability for various portions of the pulse diagnosis.
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Project description:BackgroundWith the development of technology and the renewal of traditional Chinese medicine (TCM) diagnostic equipment, artificial intelligence (AI) has been widely applied in TCM. Numerous articles employing this technology have been published. This study aimed to outline the knowledge and themes trends of the four TCM diagnostic methods to help researchers quickly master the hotspots and trends in this field. Four TCM diagnostic methods is a TCM diagnostic method through inspection, listening, smelling, inquiring and palpation, the purpose of which is to collect the patient's medical history, symptoms and signs. Then, it provides an analytical basis for later disease diagnosis and treatment plans.MethodsPublications related to AI-based research on the four TCM diagnostic methods were selected from the Web of Science Core Collection, without any restriction on the year of publication. VOSviewer and Citespace were primarily used to create graphical bibliometric maps in this field.ResultsChina was the most productive country in this field, and Evidence-Based Complementary and Alternative Medicine published the largest number of related papers, and the Shanghai University of Traditional Chinese Medicine is the dominant research organization. The Chengdu University of Traditional Chinese Medicine had the highest average number of citations. Jinhong Guo was the most influential author and Artificial Intelligence in Medicine was the most authoritative journal. Six clusters separated by keywords association showed the range of AI-based research on the four TCM diagnostic methods. The hotspots of AI-based research on the four TCM diagnostic methods included the classification and diagnosis of tongue images in patients with diabetes and machine learning for TCM symptom differentiation.ConclusionsThis study demonstrated that AI-based research on the four TCM diagnostic methods is currently in the initial stage of rapid development and has bright prospects. Cross-country and regional cooperation should be strengthened in the future. It is foreseeable that more related research outputs will rely on the interdisciplinarity of TCM and the development of neural networks models.
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Project description:BackgroundIndian medicinal plants used in the Ayurvedic traditional system to treat diabetes are a valuable source of novel anti-diabetic agents. Pancreatic ?-amylase inhibitors offer an effective strategy to lower the levels of post-prandial hyperglycemia via control of starch breakdown. In this study, seventeen Indian medicinal plants with known hypoglycemic properties were subjected to sequential solvent extraction and tested for ?-amylase inhibition, in order to assess and evaluate their inhibitory potential on PPA (porcine pancreatic ?-amylase). Preliminary phytochemical analysis of the lead extracts was performed in order to determine the probable constituents.MethodsAnalysis of the 126 extracts, obtained from 17 plants (Aloe vera (L.) Burm.f., Adansonia digitata L., Allium sativum L., Casia fistula L., Catharanthus roseus (L.) G. Don., Cinnamomum verum Persl., Coccinia grandis (L.) Voigt., Linum usitatisumum L., Mangifera indica L., Morus alba L., Nerium oleander L., Ocimum tenuiflorum L., Piper nigrum L., Terminalia chebula Retz., Tinospora cordifolia (Willd.) Miers., Trigonella foenum-graceum L., Zingiber officinale Rosc.) for PPA inhibition was initially performed qualitatively by starch-iodine colour assay. The lead extracts were further quantified with respect to PPA inhibition using the chromogenic DNSA (3, 5-dinitrosalicylic acid) method. Phytochemical constituents of the extracts exhibiting? 50% inhibition were analysed qualitatively as well as by GC-MS (Gas chromatography-Mass spectrometry).ResultsOf the 126 extracts obtained from 17 plants, 17 extracts exhibited PPA inhibitory potential to varying degrees (10%-60.5%) while 4 extracts showed low inhibition (< 10%). However, strong porcine pancreatic amylase inhibitory activity (> 50%) was obtained with 3 isopropanol extracts. All these 3 extracts exhibited concentration dependent inhibition with IC50 values, viz., seeds of Linum usitatisumum (540 ?gml-1), leaves of Morus alba (1440 ?gml-1) and Ocimum tenuiflorum (8.9 ?gml-1). Acarbose as the standard inhibitor exhibited an IC50 (half maximal inhibitory concentration)value of 10.2 ?gml-1. Phytochemical analysis revealed the presence of alkaloids, tannins, cardiac glycosides, flavonoids, saponins and steroids with the major phytoconstituents being identified by GC-MS.ConclusionsThis study endorses the use of these plants for further studies to determine their potential for type 2 diabetes management. Results suggests that extracts of Linum usitatisumum, Morus alba and Ocimum tenuiflorum act effectively as PPA inhibitors leading to a reduction in starch hydrolysis and hence eventually to lowered glucose levels.
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Project description:IntroductionClinical clerkships that rely on community preceptors as faculty and assessors are challenged by the variability in their assessments of student performance. This workshop was designed to improve the interrater reliability of preceptors' assessment of student performance.MethodsThis workshop uses a series of videos showing standardized student interactions with standardized patients and a preceptor. The videos feature a borderline satisfactory student-patient encounter and a superior student encounter. For each case, there is a video of the student providing an oral presentation of the encounter to a preceptor. The concept of a plus/delta card is also presented. Participants are asked to note positive elements of the interactions and elements needing improvement on the plus/delta card while watching the videos. Next, participants share their assessment of the students with the group using an audience response system. Group discussion allows for consensus and leads to decreased variation in preceptor assessments of each student's performance. This workshop has been delivered to preceptors in our institution as a 1-hour workshop. Additionally, a version has been presented twice at national medical teaching conferences as a faculty development workshop, instructing faculty how to facilitate the workshop.ResultsParticipant evaluations from the workshop show an increase in preceptors' awareness of specific student behaviors to observe as well as increased confidence with assessing more consistently across various student performances.DiscussionUsing videos with standardized patients, students, and preceptors demonstrating various qualities of performance is effective in improving precision in preceptors' assessment of students in clinical settings.
| S-EPMC6338197 | biostudies-literature