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Inter-examiner reliability of the interpretation of paraspinal thermographic pattern analysis.

ABSTRACT: A few spinal manipulation techniques use paraspinal surface thermography as an examination tool that informs clinical-decision making; however, inter-examiner reliability of this interpretation has not been reported. The purpose of this study was to report inter-examiner reliability for classifying cervical paraspinal thermographic findings.Seventeen doctors of chiropractic self-reporting a minimum of 2 years of experience using thermography classified thermographic scans into categories (full pattern, partial +, partial, partial -, and adaptation). Kappa statistics (k) were calculated to determine inter-examiner reliability.Overall inter-examiner reliability was fair (k=0.43). There was good agreement for identifying full pattern (k=0.73) and fair agreement for adaptation (k=0.55). Poor agreement was noted in partial categories (k=0.05-0.22).Inter-examiner reliability demonstrated fair to good agreement for identifying comparable (full pattern) and disparate (adaptation) thermographic findings; agreement was poor for those with moderate similarity (partial). Further research is needed to determine whether thermographic findings should be used in clinical decision-making for spinal manipulation.

SUBMITTER: Mansholt BA

PROVIDER: S-EPMC4486995 | biostudies-other | 2015 Jun

REPOSITORIES: biostudies-other

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Inter-examiner reliability of the interpretation of paraspinal thermographic pattern analysis.

Mansholt Barbara A BA Vining Robert D RD Long Cynthia R CR Goertz Christine M CM

The Journal of the Canadian Chiropractic Association 20150601 2

<h4>Introduction</h4>A few spinal manipulation techniques use paraspinal surface thermography as an examination tool that informs clinical-decision making; however, inter-examiner reliability of this interpretation has not been reported. The purpose of this study was to report inter-examiner reliability for classifying cervical paraspinal thermographic findings.<h4>Methods</h4>Seventeen doctors of chiropractic self-reporting a minimum of 2 years of experience using thermography classified thermo ...[more]

PMID: 26136608

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Project description:BackgroundThe reported level of lumbar paraspinal intramuscular fat (IMF) in people with low back pain (LBP) varies considerably across studies using conventional T1- and T2-weighted magnetic resonance imaging (MRI) sequences. This may be due to the different thresholding models employed to quantify IMF. In this study we investigated the accuracy and reliability of established (two-component) and novel (three-component) thresholding models to measure lumbar paraspinal IMF from T2-weighted MRI.MethodsIn this cross-sectional study, we included MRI scans from 30 people with LBP (50% female; mean (SD) age: 46.3 (15.0) years). Gaussian mixture modelling (GMM) and K-means clustering were used to quantify IMF bilaterally from the lumbar multifidus, erector spinae, and psoas major using two and three-component thresholding approaches (GMM2C; K-means2C; GMM3C; and K-means3C). Dixon fat-water MRI was used as the reference for IMF. Accuracy was measured using Bland-Altman analyses, and reliability was measured using ICC3,1. The mean absolute error between thresholding models was compared using repeated-measures ANOVA and post-hoc paired sample t-tests (α = 0.05).ResultsWe found poor reliability for K-means2C (ICC3,1 ≤ 0.38), moderate to good reliability for K-means3C (ICC3,1 ≥ 0.68), moderate reliability for GMM2C (ICC3,1 ≥ 0.63) and good reliability for GMM3C (ICC3,1 ≥ 0.77). The GMM (p < .001) and three-component models (p < .001) had smaller mean absolute errors than K-means and two-component models, respectively. None of the investigated models adequately quantified IMF for psoas major (ICC3,1 ≤ 0.01).ConclusionsThe performance of automated thresholding models is strongly dependent on the choice of algorithms, number of components, and muscle assessed. Compared to Dixon MRI, the GMM performed better than K-means and three-component performed better than two-component models for quantifying lumbar multifidus and erector spinae IMF. None of the investigated models accurately quantified IMF for psoas major. Future research is needed to investigate the performance of thresholding models in a more heterogeneous clinical dataset and across different sites and vendors.

Project description:BackgroundGenotype-phenotype correlation measures the correlation between the presence of a physical trait with a group of similar mutations but is dependent on reliable phenotyping. It can provide information on disease pathogenesis, future disease progression, severity or activity. Such indicators would be valuable in hidradenitis suppurativa (HS).ObjectivesTo assess inter-rater reliability (IRR) of HS clinical phenotypes and perform exploratory genotype-phenotype correlation in cases of HS with identified sequence variants.MethodsLinkage disequilibrium between variants was assessed. Genotype-phenotype correlations were explored using Spearman correlation coefficients. IRR was calculated using Cohen's κ. Correlation between phenotype classifications was assessed using the χ2 statistic.ResultsForty-three sequence variants with clinical information were identified. Clinical phenotypes were classified as LC2 (n = 29; 67%), scarring folliculitis (n = 18; 42%), atypical (n = 38; 88%) and nodular (n = 26; 60%). LC1 phenotype was associated with regular (χ2 = 41·289, P < 0·001) and typical (χ2 = 29·013, P < 0·001) phenotypes. Cohen's κ was highest for van der Zee and Jemec (0·815), followed by Martorell-Calatayud et al. (0·813), Naasan and Affleck (0·774) and Canoui-Poitrine et al. (0·435) classifications. High linkage disequilibrium was seen between variants of Han Chinese pedigrees. No significant genotype-phenotype correlations were identified.ConclusionsThese findings may be influenced by selection, publication bias and the assumption that HS is a monogenic disorder. The poor IRR of existing phenotype measures suggests limited utility of existing measures. Further investigations into the correlation of clinical phenotypes with inflammatory biomarkers may aid in prognostic efforts for this disease. What's already known about this topic? Genotype-phenotype correlation can provide information regarding disease pathogenesis and predictions for future disease progression, severity or activity. The identification of such indicators in hidradenitis suppurativa (HS) would be valuable for patients and clinicians alike, given the lack of biomarkers or clinical predictors of disease. What does this study add? Sixty-five sequence variants across 20 separate genes were identified. There was no significant correlation between phenotype classification in four separate classification schema and gene, mutation type or impact on Notch signalling. Utility of current phenotype measurements are limited. The lack of genotype-phenotype correlation in HS is suggestive that the underlying assumption of inherited HS as a monogenic disorder may need revision.

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Inter-examiner reliability of the interpretation of paraspinal thermographic pattern analysis.

Publications

Inter-examiner reliability of the interpretation of paraspinal thermographic pattern analysis.

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