Estimating the minimally important difference (MID) of the Diabetes Health Profile-18 (DHP-18) for Type 1 and Type 2 Diabetes Mellitus

Aims: The DHP-18 is a widely used measure of health related quality of life in diabetes mellitus but it is unclear what constitutes a meaningful change in score on each domain. The aim of this study was to establish estimates for the minimally important difference (MID) for each of the domains. Methods: The MID for each domain was estimated using both anchor and distribution based approaches which were applied to data from both the United Kingdom and France. A range of anchors were tested. Results: A global health change anchor was found to be more acceptable for Type 1 diabetes than for Type 2. MID estimates varied by domain, by estimation approach used, and by diabetes type. For Type 1 diabetes the Psychological Distress domain estimates ranged from 2.86 to 11.05, Barriers to Activity domain from 2.87 to 11.32 and Disinhibited Eating domain from 1.03 to 11.53. For Type 2 diabetes the Psychological Distress estimates ranged from 0.94 to 9.71; Barriers to Activity from 1.66 to 9.88 and Disinhibited Eating from 0.90 to 11.64. Conclusions: This is the first attempt to derive estimates for the MID of an English language measure of health related quality of life in diabetes. For Type 1 diabetes we recommend using the mean MID value using both approaches. For Type 2 we recommend applying more weight to the distribution based estimations. The MID values identified in this study will help clinicians and researchers using the DHP-18 to identify clinically meaningful change in patient reported outcomes

The psychometric performance of generic preference-based measures for patients with pressure ulcers

© 2015 Palfreyman and Mulhern. Background: Pressure ulcers are wounds that result from reduced mobility, and can have a significant impact on morbidity, mortality and quality of life. As pressure ulcers are a consequence of a wide range of conditions and interventions, it is unclear whether the best means of capturing the quality of life impacts is via generic or condition specific Patient Reported Outcome Measures (PROMs). The aim of this study was to investigate the psychometric performance of the generic EQ-5D and SF-6D amongst patients identified as having or being at risk of developing pressure ulceration. Methods: A survey of patients who were using pressure relieving mattresses and other equipment was undertaken within inpatient and community settings using a handheld tablet and postal survey. Data on EQ-5D-3L, SF-12 (used to calculate SF-6D), an EQ-5D dignity bolt-on question, demographic and wound specific questions were collected. Convergent validity was assessed using Spearman's correlations, and agreement using Bland-Altman plots. Known group validity was assessed by examining whether the instruments discriminated between different pressure ulcer severity groups. Multivariate linear regression was used to examine the impact of a range of pressure ulcer related variables. Results: The total number of participants was 307, including 273 from the acute setting (52% response rate) and 41 from the community (32%). SF-6D and EQ-5D were moderately correlated (0.61), suggesting that both instruments were capturing similar quality of life impacts. Both measures were able to significantly discriminate between groups based on the ulcer grade. Presence of a pressure ulcer and number of comorbidities were significant explanatory variables of EQ-5D and SF-6D score. Conclusions: The results suggest that generic PROMs can effectively capture the impact of pressure ulcers on quality of life, although there are significant challenges in collecting data from this group of patients related to poor clinical condition and mental capacity. The most effective method for obtaining survey data was through the hand held devices and interviewers

The EQ-5D-5L value set for England : response to the “Quality Assurance”

Objectives To respond to the ‘quality assurance’ of the EQ-5D-5L value set for England study. Methods We provide a point-by-point response to the issues raised by the authors of the quality assurance paper, drawing on theoretical arguments, empirical analyses and practical considerations. Results We provide evidence to show that many of the points made by the authors of the quality assurance are misleading, suggest misunderstandings, or are irrelevant. Conclusions The modelling approaches which were used appropriately address the characteristics of the data and provide a reasonable representation of the average stated preferences of general public in England. We provide reflections on the conduct of stated preference studies, and suggestions for the way forward

Avian Cholera in a Bald Eagle from Ohio

Author Institution: Patuxent Wildlife Research Center, Laurel, Maryland 20810, and Department of Veterinary Science (J. A. N.), University of Maryland, College Park, Maryland 20742Avian cholera (Pasteurella multocida) infection was diagnosed in an adult male bald eagle (Haliaeetus leucocephalus) collected in Ohio. Brain levels of organochlorine pesticides were found to be well below the reported lethal levels; the brain contained 10.7 ppm p,p'-DDE, 0.4 ppm p,p'-DDD, 1.2 ppm dieldrin, 1.1 ppm heptachlor epoxide, and 40.0 ppm polychlorinated biphenyls (PCB)

Spirometry parameters used to define small airways obstruction in population-based studies: Systematic review

Background The assessment of small airways obstruction (SAO) using spirometry is practiced in population-based studies. However, it is not clear what are the most used parameters and cut-offs to define abnormal results. Methods We searched three databases (Medline, Web of Science, Google Scholar) for population-based studies, published by 1 May 2021, that used spirometry parameters to identify SAO and/or provided criteria for defining SAO. We systematically reviewed these studies and summarised evidence to determine the most widely used spirometry parameter and criteria for defining SAO. In addition, we extracted prevalence estimates and identified associated risk factors. To estimate a pooled prevalence of SAO, we conducted a meta-analysis and explored heterogeneity across studies using meta regression. Results Twenty-five studies used spirometry to identify SAO. The most widely utilised parameter (15 studies) was FEF25–75, either alone or in combination with other measurements. Ten studies provided criteria for the definition of SAO, of which percent predicted cut-offs were the most common (5 studies). However, there was no agreement on which cut-off value to use. Prevalence of SAO ranged from 7.5% to 45.9%. As a result of high heterogeneity across studies (I2 = 99.3%), explained by choice of spirometry parameter and WHO region, we do not present a pooled prevalence estimate. Conclusion There is a lack of consensus regarding the best spirometry parameter or defining criteria for identification of SAO. The value of continuing to measure SAO using spirometry is unclear without further research using large longitudinal data. PROSPERO registration number CRD4202125020

A Review of Scanning Tunneling Microscope and Atomic Force Microscope Imaging of Large Biological Structures: Problems and Prospects

The application of the scanning tunneling microscope (STM) and the atomic force microscope (AFM) to the study of small biological molecules, such as DNA and smaller molecules, has received considerable attention in the literature. This paper reviews STM and AFM studies of larger biological structures such as bacterial membranes, bacteriophages, viruses, antibodies, etc. The problems encountered in these applications are emphasized, with particular reference to the unknown conduction mechanism, tip-sample interaction forces, and tip-sample convolution artifacts in the images. The latter problem is illustrated by new results from IgG antibody complexes attached to a bacterial sheath layer. A new conduction mechanism involving a graphite film overlayer is suggested. The future prospects are discussed, with emphasis on the unique capabilities of these microscopes compared to conventional electron microscopes

Developing a health state classification system from NEWQOL for epilepsy using classical psychometric techniques and Rasch analysis: a technical report

Aims: Resource allocation amongst competing health care interventions is informed by evidence of both clinical- and cost-effectiveness. Cost-utility analysis is increasingly used to assess cost effectiveness through the use of Quality Adjusted Life Years (QALYs). This requires health state values. Generic measures of health related quality of life (HRQL) are usually used to produce these values, but there are concerns about their relevance and sensitivity in epilepsy. This study develops a health state classification system for epilepsy from the NEWQOL battery, a validated questionnaire measuring QoL in epilepsy. The classification system will be amenable to valuation for calculating QALYs. Methods: Factor and other psychometric analyses were undertaken to investigate the factor structure of the battery, and assess the validity and responsiveness of the items. These analyses were used alongside Rasch analysis to select the dimensions included in the classification system, and the items used to represent each domain. Analysis was carried out on a trial dataset of patients with epilepsy (n=1611). Rasch and factor analysis were performed on one half of the sample and validated on the remaining half. Dimensions and items were selected that performed well across all analyses. Results: The battery was found to demonstrate reliability and validity but responsiveness across time periods for many of the items was low. A six dimension classification system was developed: worry about seizures, depression, memory, cognition, stigmatism and control, each with four response levels. Conclusions: It is feasible to develop a health state classification system from a battery of instruments using a combination of classical psychometric, factor and Rasch analysis. This is the first condition-specific health state classification developed for epilepsy and the next stage will produce preference weights to enable the measure to be used in cost-utility analysis.quality adjusted life years; health related quality of life; Rasch analysis; preference-based measures of health; health states; epilepsy

Developing a health state classification system from NEWQOL for epilepsy using classical psychometric techniques and Rasch analysis: A technical report

Aims: Resource allocation amongst competing health care interventions is informed by evidence of both clinical- and cost-effectiveness. Cost-utility analysis is increasingly used to assess cost effectiveness through the use of Quality Adjusted Life Years (QALYs). This requires health state values. Generic measures of health related quality of life (HRQL) are usually used to produce these values, but there are concerns about their relevance and sensitivity in epilepsy. This study develops a health state classification system for epilepsy from the NEWQOL battery, a validated questionnaire measuring QoL in epilepsy. The classification system will be amenable to valuation for calculating QALYs. Methods: Factor and other psychometric analyses were undertaken to investigate the factor structure of the battery, and assess the validity and responsiveness of the items. These analyses were used alongside Rasch analysis to select the dimensions included in the classification system, and the items used to represent each domain. Analysis was carried out on a trial dataset of patients with epilepsy (n=1611). Rasch and factor analysis were performed on one half of the sample and validated on the remaining half. Dimensions and items were selected that performed well across all analyses. Results: The battery was found to demonstrate reliability and validity but responsiveness across time periods for many of the items was low. A six dimension classification system was developed: worry about seizures, depression, memory, cognition, stigmatism and control, each with four response levels. Conclusions: It is feasible to develop a health state classification system from a battery of instruments using a combination of classical psychometric, factor and Rasch analysis. This is the first condition-specific health state classification developed for epilepsy and the next stage will produce preference weights to enable the measure to be used in cost-utility analysis