Effect of problem-based learning on severity classification agreement by triage nurses

Background Differences in the classification results among triage nurses in the emergency room can be improved by training or applying an algorithm. This study aimed to confirm whether the agreement among triage nurses could be improved through learner-led problem-based learning. Methods This study had a single-group time series design to investigate the effect of problem-based learning led by triage nurses on the agreement of Korean Triage and Acuity Scale classification results for patients who visited the emergency department. We extracted 300 patients each in May and August 2018 before learning began and 300 patients each in May and August 2019 after learning. Results After problem-based learning was applied, the self-efficacy of triage nurses for emergency patient classification increased statistically significantly compared to before learning (7.88 ± 0.96, p < .001), and the weighted kappa coefficient was also found to be almost perfectly agreement (0.835, p < .001). Conclusions In this study, problem-based learning improved the inter-rater agreement of Korean Triage and Acuity Scale classification results and self-efficacy of triage nurses. Therefore, problem-based learning can contribute to patient safety in the emergency department by enhancing the expertise of triage nurses and increasing the accuracy of triage classification.

Comparison of Different Approaches to Operationalize Fried’s Phenotypic Frailty in the NuAge Cohort

Many operationalization approaches were proposed to identify frailty in older adults. The common use of Fried’s original criteria or other cut-offs based on cohort distribution may not apply in every cohort leading to potential bias in the identification of frail individuals. We thus aimed to apply different Fried’s phenotypic frailty operationalization approaches in the Quebec NuAge cohort of generally healthy community-dwelling older adults (n=1,753; aged 67-84 years), and longitudinally compare prevalence, incidence and predictive strength on outcomes, such as functional autonomy, falls, hospitalization and mortality. Significant variability in prevalence, classification agreement and predictive strengths were observed between approaches, notably using different types of distribution cut-offs, variables, or ways to handle missing data. This strategy helped us to prioritize a specific Fried’s phenotypic frailty operationalization in NuAge, which could then be used in secondary research projects aiming to study determinants of Fried’s phenotypic frailty and its role in health outcomes.

Evaluating Classification Consistency of Oral Lesion Images for Use in an Image Classification Teaching Tool

A web-based image classification tool (DiLearn) was developed to facilitate active learning in the oral health profession. Students engage with oral lesion images using swipe gestures to classify each image into pre-determined categories (e.g., left for refer and right for no intervention). To assemble the training modules and to provide feedback to students, DiLearn requires each oral lesion image to be classified, with various features displayed in the image. The collection of accurate meta-information is a crucial step for enabling the self-directed active learning approach taken in DiLearn. The purpose of this study is to evaluate the classification consistency of features in oral lesion images by experts and students for use in the learning tool. Twenty oral lesion images from DiLearn’s image bank were classified by three oral lesion experts and two senior dental hygiene students using the same rubric containing eight features. Classification agreement among and between raters were evaluated using Fleiss’ and Cohen’s Kappa. Classification agreement among the three experts ranged from identical (Fleiss’ Kappa = 1) for “clinical action”, to slight agreement for “border regularity” (Fleiss’ Kappa = 0.136), with the majority of categories having fair to moderate agreement (Fleiss’ Kappa = 0.332–0.545). Inclusion of the two student raters with the experts yielded fair to moderate overall classification agreement (Fleiss’ Kappa = 0.224–0.554), with the exception of “morphology”. The feature of clinical action could be accurately classified, while other anatomical features indirectly related to diagnosis had a lower classification consistency. The findings suggest that one oral lesion expert or two student raters can provide fairly consistent meta-information for selected categories of features implicated in the creation of image classification tasks in DiLearn.

The gender system of Durop

This paper presents an analysis of grammatical gender and agreement in Durop, a language of the Upper Cross subgroup of Cross River. The data used are drawn from Kastelein (Kastelein, Bianca. 1994. A phonological and grammatical sketch of DuRop. Leiden: University of Leiden Scriptie), whose analysis treats gender as the singular – plural pairings of nouns different from the present approach. Kastelein identifies eight concord classes (agreement classes); these form the basis of gender in Durop in the present analysis; as many as 24 agreement classes are identified here. The various systems comprising nominal classification, agreement and gender in Durop are compared and discussed. The agreement system comprises three subsystems of differing numbers of agreement classes.

Assessment of a Rapid Semi-Quantitative Immunochromatographic Test for the Evaluation of Transfer of Passive Immunity in Calves

Calves are born agammaglobulinemic and they rely on transfer of passive immunity (TPI) through ingestion of colostrum from the dam. Ensuring the effectiveness of TPI through blood serum immunoglobulins (IgG) quantification is of critical importance for the prevention of calf diseases. The main objective of this study was to assess the performance of a novel on-farm immunochromatographic quick assay (SmartStripsTM, Bio-X Diagnostics, Rochefort, Belgium) compared to the ELISA reference method to directly measure serum IgG concentration and assess TPI status in beef and dairy calves. Additional comparison was made with the commonly used Brix refractometer. Jugular blood samples were collected from beef (n = 71) and dairy (n = 26) calves in Belgium within 7 days post-birth. Quantitative (Pearson correlation coefficients, Bland-Altman plots) and qualitative (diagnostic test characteristics, weighted kappa for classification into 4 categories of TPI) analyses were performed to evaluate the performances of the quick test and the refractometer compared to ELISA. The quick test showed a correlation of 0.83 and a classification agreement (weighted kappa) of 0.79 with the reference method (average values for two types of blood anticoagulants). Performances were better for low IgG concentrations and the assessment of poor TPI status and they outperformed those of the Brix refractometer. Results suggested that the immunochromatographic quick test can be considered as a suitable on-farm method for direct serum IgG measurement and the assessment of TPI status in calves, contributing to timely interventions in the management of calves with inadequate TPI.

Development and Validation of Food Frequency Questionnaire for Food and Nutrient Intake of Adults in Butajira, Southern Ethiopia.

Background: To date, there is no culture-specific and validated Food Frequency Questionnaire (FFQ) available in Ethiopia. We developed a FFQ and evaluated its validity as compared to estimates of a food group and nutrient intakes derived from two 24-Hour Dietary Recalls (24-HRs).Method: A total of 105 adults, of which 43 (41%) were men and 62 (59%) women aged 20-65 years participated in this study. To evaluate the validity of FFQ against two 24-HRs, we used a paired t-test and Wilcoxon- signed rank test to compare mean and median daily nutrient and food intakes obtained from the averages of the two 24-HRs and the FFQ, correlation coefficients to measure the strength and direction of the correlation, Cross-classification and kappa to assess classification agreement and Bland-Altman analysis for assessing limits of agreement between the two methods.Results: Mean energy and macronutrient intakes obtained from the FFQ were significantly higher than those obtained from the mean of two 24-HRs. For energy and macronutrients, the crude correlation between two instruments ranged from 0.05 (total fat) to 0.32 (carbohydrate). Whereas, for micronutrients, it ranged from 0.1 (calcium) to 0.49 (vitamin B1). The de-attenuated correlation ranged from to 0.10 (total fat) to 0.80 (vitamin A) Visual inspection of the Bland-Altman plots for both energy and macronutrients shows no consistent trend across the intake values. For the majority of the food groups, no significant difference was observed in median intake of foods and nutrients between 24-HRs and FFQ. Crude correlation for food groups ranged from 0.12 (egg) to 0.78 (legumes). The de-attenuated correlation ranged from 0.24 (egg) to 0.10 (Meat/Poultry/Fish). The FFQ showed a fair classification agreement with the 24-HRs for cereals, legumes, and roots and tubers intakes. A systematic trend of overestimation for roots and tubers and under estimation of beverage intakes at higher values was observed when we used FFQ.Conclusion: The FFQ is valid to assess and rank individuals in terms of intakes of most food groups according to high and low intake categories. Individual level validity was acceptable for energy and most nutrients as indicated by de-attenuated correlation coefficients and Bland-Altman plots. However, group level validity was poor for most nutrients.

PEDICLE MORPHOLOGY IN SCOLIOSIS: CLASSIFICATION AGREEMENT FOR PRE-OPERATIVE EVALUATION

ABSTRACT Objectives Although Watanabe morphological classification is well known, there is no consensus of its use among spine surgeons. We propose an analysis of the Watanabe classification by three observers, one senior and two recently graduated orthopedic spine surgeons, and its applicability in pre-operative evaluation. Methods An intraobserver and interobserver analysis of the classifications of 937 thoracic pedicles among 55 scoliosis patients treated surgically in two institutions. The average age at time of surgery was 16.3 years (10- 50 years). The etiologies of the scoliosis were: idiopathic (n= 47), congenital (n=4), syndromic (n= 3) and neuromuscular (n=1). The mean Cobb angle was 67 degrees (41- 120º). The evaluation of the thoracic pedicle was performed using pre-operative CT images. Results A total of 937 pedicles were classified by three observers with percentages of 47.5% type A, 28.6% type B, 17.1% type C and 6.9% type D for the total pedicles, convex and concave. Intraobserver agreement was fair to almost perfect (kappa 0.34 to 0.92) and interobserver agreement was fair to moderate (kappa 0.33 to 0.59) with statistical significance of p<0.001. Conclusion Watanabe classification remains a good method for predicting intraoperative difficulties, and has better agreement as the surgeon becomes more experienced. Level of evidence II; Prognostic Studies.

Medical Mobile App Classification Using the National Institute for Health and Care Excellence Evidence Standards Framework for Digital Health Technologies: Interrater Reliability Study

Background Clinical governance of medical mobile apps is challenging, and there is currently no standard method for assessing the quality of such apps. In 2018, the National Institute for Health and Care Excellence (NICE) developed a framework for assessing the required level of evidence for digital health technologies (DHTs), as determined by their clinical function. The framework can potentially be used to assess mobile apps, which are a subset of DHTs. To be used reliably in this context, the framework must allow unambiguous classification of an app’s clinical function. Objective The objective of this study was to determine whether mobile health apps could be reliably classified using the NICE evidence standards framework for DHTs. Methods We manually extracted app titles, screenshots, and content descriptions for all apps listed on the National Health Service (NHS) Apps Library website on July 12, 2019; none of the apps were downloaded. Using this information, 2 mobile health (mHealth) researchers independently classified each app to one of the 4 functional tiers (ie, 1, 2, 3a, and 3b) described in the NICE digital technologies evaluation framework. Coders also answered contextual questions from the framework to identify whether apps were deemed to be higher risk. Agreement between coders was assessed using Cohen κ statistic. Results In total, we assessed 76 apps from the NHS Apps Library. There was classification agreement for 42 apps. Of these, 0 apps were unanimously classified into Tier 1; 24, into Tier 2; 15, into Tier 3a; and 3, into Tier 3b. There was disagreement between coders in 34/76 cases (45%); interrater agreement was poor (Cohen κ=0.32, 95% CI 0.16-0.47). Further investigation of disagreements highlighted 5 main explanatory themes: apps that did not correspond to any tier, apps that corresponded to multiple tiers, ambiguous tier descriptions, ambiguous app descriptions, and coder error. Conclusions The current iteration of the NICE evidence standards framework for DHTs did not allow mHealth researchers to consistently and unambiguously classify digital health mobile apps listed on the NHS app library according to their functional tier.