Measure Of Concordance Research Articles

Concordance of grip strength measurement between a digital handheld dynamometer and a Hydraulic dynamometer.

Assessment of muscle strength is of great interest for the study of age-associated pathologies, including frailty and sarcopenia. However, the cost of some of the equipment necessary for its evaluation could be prohibitive for its generalized use in some settings. The purpose of the present study was to compare two handheld dynamometers to evaluate the measure of concordance between the measurements. Material and methods The study was conducted in the outpatient Geriatrics clinics where 120 community-dwelling participants aged 60 years and more were evaluated using two devices: the JAMAR® Hydraulic Hand Dynamometer and the digital hand dynamometer CAMRY® EH101. We observed a positive correlation between the two devices for dominant hand (DH) Pearson r 0.974 (p < 0.001) and a Spearman ρ 0.973 (p < 0.001) for non-dominant hand (NDH) Lin's coefficient for the DH was 0.98 (p < 0.001) and for the NDH 0.97 (p < 0.001). The intraclass correlation coefficient was 0.971 (95% CI, 0.95-0.97; p < 0.001) for DH and 0.975 (95% CI, 0.96-0.98; p < 0.001) for NDH. In this study, the Camry dynamometer was observed to be reliable for measuring hand grip strength in community-dwelling people 60 years or older.

Concordance of Traumatic Brain Injury Symptoms, Evaluation, and Diagnosis Between Teens and Parents: Data From the National Health Interview Survey-Teen

PurposeTo investigate differences in teen-reported and parent-reported lifetime prevalence estimates of traumatic brain injury (TBI) symptoms, TBI evaluation, and TBI diagnosis among a nationally representative sample of teenagers aged 12–17 years old and their parents. MethodsParent-reported data from the 2021 to 2022 National Health Interview Survey linked with teen-reported data from the National Health Interview Survey-Teen July 2021-December 2022 (n = 1,153) were analyzed. Lifetime prevalence estimates for TBI symptoms (e.g., selected symptoms as a result of a blow or jolt to the head), history of evaluation by health professional for TBI (i.e., TBI evaluation), and TBI diagnosis stratified by sociodemographic characteristics and reporter type were produced, and z-tests were conducted to test for differences. Concordance measures were calculated to assess agreement between teen and parent survey responses to TBI measures. ResultsLifetime prevalence of TBI symptoms varied by reporter type across all sociodemographic characteristics with teen-report consistently producing higher estimates. Estimates of TBI evaluation varied by reporter type only among older teens, non-Hispanic teens, and teens who participated in sports; there was no difference for TBI diagnosis. Percent agreement between the 2 reporters ranged from 73% to 95%, prevalence-adjusted bias-adjusted kappa ranged from 0.45 to 0.90, and Cohen's kappa ranged from 0.22 to 0.63. DiscussionThere was general agreement for observable outcomes TBI evaluation and TBI diagnosis, but discordance existed in reports of TBI symptoms. These findings suggest that youth self-report of TBI symptoms may enhance surveillance efforts.

Observational Causality Testing

ABSTRACTIn prior work, we have introduced an asymptotic threshold of sufficient randomness for causal inference from observational data. In this paper, we extend that prior work in three main ways. First, we show how to empirically estimate a lower bound for the randomness from measures of concordance transported from studies of monozygotic twins. Second, we generalize our methodology for application on a finite population, and we introduce methods to implement finite population corrections. Third, we generalize our methodology in another direction by incorporating measured covariate data into the analysis. The first extension represents a proof of concept that observational causality testing is possible. The second and third extensions help to make observational causality testing more practical. As a theoretical and indirect consequence of the third extension, we formulate and introduce a novel criterion for covariate selection. We demonstrate our proposed methodology for observational causality testing with numerous example applications.

Early experience with targeted and combination biopsies in prostate cancer work-up in Denmark from 2012 to 2016

PurposeTo investigate the early implementation of combined systematic and targeted (cBx) primary biopsy in prostate cancer diagnosis and define the concordance in Gleason grading (GG) of different biopsy techniques with radical prostatectomy (RP) pathology.MethodsThis population-based analysis includes data on all men in Denmark who underwent primary cBx or standalone systematic (sBx) prostate biopsy between 2012 and 2016. Biopsy results were compared to RP pathology if performed within a year. Concordance measurement was estimated using Cohen’s Kappa, and the cumulative incidence of cancer-specific death was estimated at 6 years with the Aalen-Johansen estimator.ResultsConcordance between biopsy and RP pathology was 0.53 (95CI: 0.43–0.63), 0.38 (95CI: 0.29–0.48), and 0.16 (95CI: 0.11–0.21) for cBx, targeted biopsy (tBx), and sBx, respectively. For standalone sBx and RP, concordance was 0.29 (95CI: 0.27–0.32). Interrelated GG concordance between tBx and sBx was 0.67 (95CI: 0.62–0.71) in cBx. The proportion of correctly assessed GG based on RP pathology was 54% in both cBx and standalone sBx. Incidence of prostate cancer-specific death was 0% regardless of biopsy technique in GG 1, and 22% (95CI: 11–32), 30% (95CI: 15–44), and 19% (95CI: 7.0–30) in GG 5 for cBx, tBx, or sBx, respectively.ConclusionOverall, the cBx strategy demonstrates higher concordance to RP pathology than the standalone sBx. However, cBx exhibits more overgrading of the GG of RP pathology compared to sBx. Ultimately, the classic grading system does not take change in the diagnostic pathway into account, and grading should be altered accordingly to ensure appropriate treatment.

A few generalizations of Kendall’s tau. Part I: Construction

Complimenting our earlier work on generalizations of popular concordance measures in the sense of Scarsini for a pair of continuous random variables (X, Y) (such measures can be understood as functions of the bivariate copula C associated with (X, Y)), we focus on generalizations of Kendall’s τ. In Part I, we give two forms of such measures and also provide general bounds for their values, which are sharp in certain cases and depend on the values of Spearman’s ρ and the original Kendall’s τ. Part II is devoted to the intrinsic meaning of presented Kendall’s τ generalizations, their degree as polynomial-type concordance measures, and computational aspects.

Quantitative read-across structure-activity relationship (q-RASAR): A novel approach to estimate the subchronic oral safety (NOAEL) of diverse organic chemicals in rats

We have developed a quantitative safety prediction model for subchronic repeated doses of diverse organic chemicals on rats using the novel quantitative read-across structure-activity relationship (q-RASAR) approach, which uses similarity-based descriptors for predictive model generation. The experimental -Log (NOAEL) values have been used here as a potential indicator of oral subchronic safety on rats as it determines the maximum dose level for which no observed adverse effects of chemicals are found. A total of 186 data points of diverse organic chemicals have been used for the model generation using structural and physicochemical (0D–2D) descriptors. The read-across-derived similarity, error, and concordance measures (RASAR descriptors) have been extracted from the preliminary 0D–2D descriptors. Then, the combined pool of RASAR and the identified 0D–2D descriptors of the training set were employed to develop the final models by using the partial least squares (PLS) algorithm. The developed PLS model was rigorously validated by various internal and external validation metrics as suggested by the Organization for Economic Co-operation and Development (OECD). The final q-RASAR model is proven to be statistically sound, robust and externally predictive (R2 = 0.85, Q2LOO = 0.82 and Q2F1 = 0.94), superseding the internal as well as external predictivity of the corresponding quantitative structure-activity relationship (QSAR) model as well as previously reported subchronic repeated dose toxicity model found in the literature. In a nutshell, the q-RASAR is an effective approach that has the potential to be used as a good alternative way to improve external predictivity, interpretability, and transferability for subchronic oral safety prediction as well as ecotoxicity risk identification.

Evaluating a Novel AI Tool for Automated Measurement of the Aortic Root and Valve in Cardiac Magnetic Resonance Imaging.

Objective Evaluating an artificial intelligence (AI) tool (AIATELLA, version 1.0; AIATELLA Oy, Helsinki, Finland) in interpreting cardiac magnetic resonance (CMR) imaging to produce measurements of the aortic root and valveby comparison ofaccuracy and efficiencywith that of three National Health Service (NHS) cardiologists. Methods AI-derived aortic root and valve measurements were recorded alongside manual measurements from three experienced NHS consultant cardiologists (CCs) over three separate sites in the northeast part of the United Kingdom. The study utilised a comprehensive dataset of CMR images, with the intraclass correlation coefficient (ICC) being the primary measure of concordance between the AI and the cardiologist assessments. Patient imaging was anonymised and blinded at the point of transfer to a secure data server. Results The study demonstrates a high level of concordance between AI assessment of the aortic root and valve with NHS cardiologists (ICC of 0.98). Notably, the AI delivered results in 2.6 seconds (+/- 0.532) compared to a mean of 334.5 seconds (+/- 61.9) by the cardiologists, a statistically significant improvement in efficiency without compromising accuracy. Conclusion AI's accuracy and speed of analysis suggest that it could be a valuable tool in cardiac diagnostics, addressing the challenges of time-consuming and variable clinician-based assessments. This research reinforces AI's role in optimising the patient journey and improving the efficiency of the diagnostic pathway.

On approximating dependence function and its derivatives

Bivariate extreme value distributions can be used to model dependence of observations from random variables in extreme levels. There is no finite dimensional parametric family for these distributions, but they can be characterized by a certain one-dimensional function which is known as Pickands dependence function. In many applications the general approach is to estimate the dependence function with a non-parametric method and then conduct further analysis based on the estimate. Although this approach is flexible in the sense that it does not impose any special structure on the dependence function, its main drawback is that the estimate is not available in a closed form. This paper provides some theoretical results which can be used to find a closed form approximation for an exact or an estimate of a twice differentiable dependence function and its derivatives. We demonstrate the methodology by calculating approximations for symmetric and asymmetric logistic dependence functions and their second derivatives. We show that the theory can be even applied to approximating a non-parametric estimate of dependence function using a convex optimization algorithm. Other discussed applications include a procedure for testing whether an estimate of dependence function can be assumed to be symmetric and estimation of the concordance measures of a bivariate extreme value distribution. Finally, an Australian annual maximum temperature dataset is used to illustrate how the theory can be used to build semi-infinite and compact predictions regions.

Evidence-based Medication knowledge Brokers in Residential Aged CarE (EMBRACE): protocol for a helix-counterbalanced randomised controlled trial

IntroductionClinical practice guidelines recommend against the routine use of psychotropic medications in residential aged care facilities (RACFs). Knowledge brokers are individuals or groups who facilitate the transfer of knowledge into practice. The objective of this trial is to evaluate the effectiveness and cost-effectiveness of using knowledge brokers to translate Australia’s new Clinical Practice Guidelines for the Appropriate Use of Psychotropic Medications in People Living with Dementia and in Residential Aged Care.Methods and analysisThe Evidence-based Medication knowledge Brokers in Residential Aged CarE (EMBRACE) trial is a helix-counterbalanced randomised controlled trial. The 12-month trial will be conducted in up to 19 RACFs operated by four Australian aged care provider organisations in Victoria, New South Wales, Western Australia and Queensland. RACFs will be randomised to receive three levels of implementation strategies (knowledge broker service, pharmacist-led quality use of medications education activities and distribution of the Guidelines and supporting materials) across three medication contexts (antipsychotics, benzodiazepines and antidepressants). Implementation strategies will be delivered by an embedded on-site aged care pharmacist working at a system level across each participating RACF. All RACFs will receive all implementation strategies simultaneously but for different medication contexts. The primary outcome will be a composite dichotomous measure of 6-month RACF-level concordance with Guideline recommendations and good practice statements among people using antipsychotics, benzodiazepines and antidepressants for changed behaviours. Secondary outcomes will include proportion of residents with Guideline concordant use of antipsychotics, benzodiazepines and antidepressants measured at the RACF-level and proportion of residents with psychotropic medication use, hospitalisation, falls, falls with injury, polypharmacy, quality of life, activities of daily living, medication incidents and behavioural incidents measured at the RACF-level.DiscussionThe EMBRACE trial investigates a novel guideline implementation strategy to improve the safe and effective use of psychotropic medications in RACFs. We anticipate that the findings will provide new information on the potential role of knowledge brokers for successful and cost-effective guideline implementation.Trial registrationAustralian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12623001141639. Registered 6 November 2023 — retrospectively registered, https://www.anzctr.org.au/TrialSearch.aspx.

Protocol to measure validity and reliability of colorectal, breast, cervical and lung cancer screening questions from the 2021 National Health Interview Survey: Methodology and design.

Previous studies demonstrate that self-reports of mammography screening for breast cancer and colonoscopy screening for colorectal cancer demonstrate concordance, based on adherence to screening guidelines, with electronic medical records (EMRs) in over 90% of those interviewed, as well as high sensitivity and specificity, and can be used for monitoring our Healthy People goals. However, for screening tests for cervical and lung cancers, and for various sub-populations, concordance between self-report and EMRs has been noticeably lower with poor sensitivity or specificity. This study aims to test the validity and reliability of lung, colorectal, cervical, and breast cancer screening questions from the 2021 and 2022 National Health Interview Survey (NHIS). We present the protocol for a study designed to measure the validity and reliability of the NHIS cancer screening questions compared to EMRs from four US-based healthcare systems. We planned a randomized trial of a phone- vs web-based survey with NHIS questions that were previously revised based on extensive cognitive interviewing. Our planned sample size will be 1576 validity interviews, and 1260 interviews randomly assigned at 1 or 3 months after the initial interview. We are enrolling people eligible for cancer screening based on age, sex, and smoking history per US Preventive Services Task Force recommendations. We will evaluate question validity using concordance, sensitivity, specificity, positive predictive value, negative predictive value, and report-to-records ratio. We further are randomizing participants to complete a second survey 1 vs 3 months later to assess question reliability. We suggest that typical measures of concordance may need to be reconsidered in evaluating cancer screening questions.

Multicellular network-informed survival model for identification of drug targets of gliomas.

Increasing evidence suggests that communication between tumor cells (TCs) and tumor-associated macrophages (TAMs) plays a substantial role in promoting progression of low-grade gliomas (LGG). Hence, it is becoming critical to model TAM-TC interplay and interrogate how the crosstalk affects prognosis of LGG patients. This paper proposed a translational research pipeline to construct the multicellular interaction gene network (MIGN) for identification of druggable targets to develop novel therapeutic strategies. Firstly, we selected immunotherapy-related feature genes (IFGs) for TAMs and TCs using RNA-seq data of glioma mice from preclinical trials. After translating the IFGs to human genome, we constructed TAM- and TC- associated networks separately, using a training set of 524 human LGGs. Subsequently, clustering analysis was performed within each network, and the concordance measure K-index was adopted to correlate gene clusters with patient survival. The MIGN was built by combining the clusters highly associated with survival in TAM- and TC-associated networks. We then developed a MIGN-based survival model to identify prognostic signatures comprised of ligands, receptors and hub genes. An independent cohort of 172 human LGG samples was leveraged to validate predictive accuracy of the signature. The areas under time-dependent ROC curves were 0.881, 0.867, and 0.839 with respect to 1-year, 3-year, and 5-year survival rates respectively in the validation set. Furthermore, literature survey was conducted on the signature genes, and potential clinical responses to targeted drugs were evaluated for LGG patients, further highlighting potential utilities of the MIGN signature to develop novel immunotherapies to extend survival of LGG patients.

Convex weak concordance measures and their constructions

Considering the framework of weak concordance measures introduced by Liebscher in 2014, we propose and study convex weak concordance measures. This class of dependence measures contains as a proper subclass the class of all convex concordance measures, introduced and studied by Mesiar et al. in 2022, and thus it also covers the well-known concordance measures as Spearman's ρ, Gini's γ and Blomqvist's β. The class of all convex weak concordance measures also contains, for example, Spearman's footrule ϕ, which is not a concordance measure. In this paper, we first introduce basic convex weak concordance measures built in general by means of a single point (u,v)∈▽={(u,v)∈]0,1[2|u≥v} and its transpose (v,u) only. Then, based on basic convex weak concordance measures and probability measures on the Borel subsets of ▽, two rather general constructions of convex weak concordance measures are proposed, discussed and exemplified. Inspired by Edwards et al., probability measures-based constructions are generalized to Borel measures on B(]0,1[2)-based constructions also allowing some infinite measures to be considered. Finally, it is shown that the presented constructions also cover the mentioned standard (convex weak) concordance measures ρ, γ, β, ϕ and provide alternative formulas for them.

Comparison of correlation-based measures of concordance in terms of asymptotic variance

We compare measures of concordance that arise as Pearson’s linear correlation coefficient between two random variables transformed so that they follow the so-called concordance-inducing distributions. The class of such transformed rank correlations includes Spearman’s rho, Blomqvist’s beta and van der Waerden’s coefficient. When only the standard axioms of measures of concordance are required, it is not always clear which transformed rank correlation is most suitable to use. To address this question, we compare measures of concordance in terms of their best and worst asymptotic variances of some canonical estimators over a certain set of dependence structures. A simple criterion derived from this approach is that concordance-inducing distributions with smaller fourth moment are more preferable. In particular, we show that Blomqvist’s beta is the optimal transformed rank correlation in this sense, and Spearman’s rho outperforms van der Waerden’s coefficient. Moreover, we find that Kendall’s tau, although it is not a transformed rank correlation of that nature, shares a certain optimal structure with Blomqvist’s beta.

A novel positive dependence property and its impact on a popular class of concordance measures

A novel positive dependence property is introduced, called positive measure inducing (PMI for short), being fulfilled by numerous copula classes, including Gaussian, Student t, Fréchet, Farlie–Gumbel–Morgenstern and Frank copulas; it is conjectured that even all positive quadrant dependent Archimedean copulas meet this property. From a geometric viewpoint, a PMI copula concentrates more mass near the main diagonal than in the opposite diagonal. A striking feature of PMI copulas is that they impose an ordering on a certain class of copula-induced measures of concordance, the latter originating in Edwards et al. (2004) and including Spearman’s rho ρ and Gini’s gamma γ, leading to numerous new inequalities such as 3γ≥2ρ. The measures of concordance within this class are estimated using (classical) empirical copulas and the intrinsic construction via empirical checkerboard copulas, and the estimators’ asymptotic behavior is determined. Building upon the presented inequalities, asymptotic tests are constructed having the potential of being used for detecting whether the underlying dependence structure of a given sample is PMI, which in turn can be used for excluding certain copula families from model building. The excellent performance of the tests is demonstrated in a simulation study and by means of a real-data example.

Quantitative Read-across structure-activity relationship (q-RASAR): A new approach methodology to model aquatic toxicity of organic pesticides against different fish species

We have developed quantitative toxicity prediction models for organic pesticides of agricultural importance considering different fish species using a novel quantitative Read-across structure-activity relationship (q-RASAR) approach. The current study uses experimental (Log 1/LC50) data of organic pesticides to various fish species, including Rainbow trout (RT: Oncorhynchus mykiss: 715 data points), Lepomis (LP: Lepomis macrochirus: 136 data points), and Miscellaneous (Pimephales promelas, Brachydanio rerio: 226 data points). This study has also discussed the validation of the developed models and the analysis of structural features that are important for aquatic toxicity towards fishes. The read-across-derived similarity, error, and concordance measures (RASAR descriptors) have been extracted from the preliminary 0D-2D descriptors; the combined pool of RASAR and selected 0D-2D descriptors have been used to develop the final models by employing partial least squares algorithm. All the q-RASAR models are acceptable in terms of goodness of fit, robustness, and external predictivity, superseding the quality of the respective QSAR models, as seen from the computed validation metrics. The q-RASAR is an effective approach that has the potential to be used as a good alternative way to enhance external predictivity, interpretability, and transferability for aquatic toxicity prediction as well as ecotoxicity potential identification.

Interlaboratory comparison of Pseudomonas aeruginosa phage susceptibility testing.

Standardized approaches to phage susceptibility testing (PST) are essential to inform selection of phages for study in patients with bacterial infections. There is no reference standard for assessing bacterial susceptibility to phage. We compared agreement between PST performed at three centers: two centers using a liquid assay standardized between the sites with the third, a plaque assay. Four Pseudomonas aeruginosa phages: PaWRA01ø11 (EPa11), PaWRA01ø39 (EPa39), PaWRA02ø83 (EPa83), PaWRA02ø87 (EPa87), and a cocktail of all four phages were tested against 145 P. aeruginosa isolates. Comparisons were made within measurements at the two sites performing the liquid assay and between these two sites. Agreement was assessed based on coverage probability (CP8), total deviation index, concordance correlation coefficient (CCC), measurement accuracy, and precision. For the liquid assay, there was satisfactory agreement among triplicate measurements made on different days at site 1, and high agreement based on accuracy and precision between duplicate measurements made on the same run at site 2. There was fair accuracy between measurements of the two sites performing the liquid assay, with CCCs below 0.6 for all phages tested. When compared to the plaque assay (performed once at site 3), there was less agreement between results of the liquid and plaque assays than between the two sites performing the liquid assay. Similar findings to the larger group were noted in the subset of 46 P. aeruginosa isolates from cystic fibrosis. Results of this study suggest that reproducibility of PST methods needs further development.

Agreement between self-reports and statutory health insurance claims data on healthcare utilization in patients with mental disorders

BackgroundData on resource use are frequently required for healthcare assessments. Studies on healthcare utilization (HCU) in individuals with mental disorders have analyzed both self-reports and administrative data. Source of data may affect the quality of analysis and compromise the accuracy of results. We sought to ascertain the degree of agreement between self-reports and statutory health insurance (SHI) fund claims data from patients with mental disorders.MethodsClaims data from six German SHI and self-reports were obtained along with a cost-effectiveness analysis performed as a part of a controlled prospective multicenter cohort study conducted in 18 psychiatric hospitals in Germany (PsychCare), including patients with pre-defined psychiatric disorders. Self-reports were collected using the German adaption of the Client Sociodemographic and Service Receipt Inventory (CSSRI) questionnaire with a 6-month recall period. Data linkage was performed using a unique pseudonymized identifier. Missing responses were coded as non-use for all analyses. HCU was calculated for inpatient and outpatient care, day-care services, home treatment, and pharmaceuticals. Concordance was measured using Cohen’s Kappa (κ) and intraclass correlation coefficient (ICC). Regression approaches were used to investigate the effect of independent variables on the agreements.ResultsIn total 274 participants (mean age 47.8 [SD = 14.2] years; 47.08% women) were included in the analysis. No significant differences were observed between the linked and unlinked patients in terms of baseline characteristics. Total agreements values were 63.9% (κ = 0.03; PABAK = 0.28) for outpatient contacts, 69.3% (κ = 0.25; PABAK = 0.39) for medication use, 81.0% (κ = 0.56; PABAK = 0.62) for inpatient days and 86.1% (κ = 0.67; PABAK = 0.72) for day-care services. There was varied quantitative agreement between data sources, with the poorest agreement for outpatient care (ICC [95% CI] = 0.22 [0.10–0.33]) and the best for psychiatric day-care services (ICC [95% CI] = 0.72 [0.66–0.78]). Marital status and time since first treatment positively affected the chance of agreement on utilization of outpatient services.ConclusionsAlthough there were high levels of absolute agreement, the measures of concordance between administrative records and self-reports were generally minimal to moderate. Healthcare investigations should consider using linked or at least different data sources to estimate HCU for specific utilization areas, where unbiased information can be expected.Trial registrationThis study was part of the multi-center controlled PsychCare trial (German Clinical Trials Register No. DRKS00022535; Date of registration: 2020–10-02).

A link between Kendall’s τ, the length measure and the surface of bivariate copulas, and a consequence to copulas with self-similar support

Abstract Working with shuffles, we establish a close link between Kendall’s τ \tau , the so-called length measure, and the surface area of bivariate copulas and derive some consequences. While it is well known that Spearman’s ρ \rho of a bivariate copula A A is a rescaled version of the volume of the area under the graph of A A , in this contribution we show that the other famous concordance measure, Kendall’s τ \tau , allows for a simple geometric interpretation as well – it is inextricably linked to the surface area of A A .

The impact of record source on multimorbidity measurement and mortality associations: A comparison study

ObjectivesMeasurement of multimorbidity is important; the impact of choice of record source on multimorbidity measurement is uncertain. We compared estimated prevalence of multimorbidity and associations with mortality using different record sources.&#x0D; MethodCross-sectional study of SAIL Databank data including 2,340,027 individuals of all ages living in Wales on 01 January 2019. Comparison of multimorbidity and LTC prevalence using diagnosis codes from primary care (PC), hospital inpatient (HI), and linked PC-HI records, and associations with 12-month mortality were calculated.&#x0D; ResultsMultimorbidity was more prevalent (32.2% versus 16.4%), included a younger population (62.5 years versus 66.8 years) with more women (54.2% versus 52.6%), and was more strongly associated with mortality (adjusted odds ratio 7.93 [95%CI 7.62-8.25] versus 4.70 [95%CI 4.55-4.85] in people with ≥ 4 LTCs) using linked PC-HI than HI records. Prevalence of LTCs using PC versus HI records was significantly higher in 37/47 and significantly lower in 10/47. Averaging all LTCs, the ratio of PC/linked PC-HI records was higher than HI/linked PC-HI records (84.7% [interquartile range, IQR 76.7 to 90.4] versus 49.0 [IQR 31.9 to 83.6]). Measures of concordance between PC and HI records varied widely across LTCs and the Kappa statistic, a comparison of percentage agreement and chance alone, was slight in five, fair in 13, moderate in 17, and substantial in 12 LTCs, and lowest in mental and behavioural disorders.&#x0D; ConclusionUsing linked PC-HI records provides higher estimated prevalence of multimorbidity with higher proportions of certain populations and higher association with mortality. Use of single record sources will underestimate the prevalence of many important conditions, especially mental and behavioural disorders.

Helping providers address psychological aspects of obesity in routine care: Development of the obesity adjustment dialogue tool (OADT)

BackgroundThis study developed and validated a dialogue tool (Obesity Adjustment Dialogue Tool) to efficiently assess QoL and drive to eat for use in routine clinical care. MethodsA 13-question interview was created, assessing the impact of living with obesity on quality of life and drive to eat. In a counter-balanced order, PwO were interviewed and completed the Obesity Adjustment Survey (OAS), the Impact of Obesity on Quality of Life-Lite scale (IWQoL), the Three Factor Eating Questionnaire (TREQ), and the Control of Eating Questionnaire (COEQ). Questionnaire results were used to validate the interview using correlational and concordance measures. Results101 PwO consented and 98 completed all measures (mean BMI = 37.8; 30.7% Class III obesity). Correlations between the QoL dialogue tool and validated instruments (OAS, IWQOL) were moderate to high. Correlations between cravings questions and validated measures (TFEQ, COEQ) were high except for attempts to control eating. Correspondence based on categorizing both the dialogue tool and scales into high/low impact was high except for attempts to control eating (which was dropped from the final tool). ConclusionThe Obesity Adjustment Dialogue Tool is a brief clinician-led structured interview which closely matches information derived from validated scales. This tool offers an efficient approach to incorporating QoL factors into obesity management.