Comparison of the PROMIS Preference Score (PROPr) and EQ-5D-5L Index Value in General Population Samples in the United Kingdom,France, and Germany

ObjectivesThe Patient-Reported Outcome Measurement Information System (PROMIS) Preference score (PROPr) can be used to assess health state utility (HSU) and estimate quality-adjusted life-years in cost-effectiveness analyses. It is based on item response theory and promises to overcome limitations of existing HSU scores such as ceiling effects. The PROPr contains 7 PROMIS domains: cognitive abilities, depression, fatigue, pain, physical function, sleep disturbance, and ability to participate in social roles and activities. We aimed to compare the PROPr with the 5-level EQ-5D (EQ-5D-5L) in terms of psychometric properties using data from 3 countries.MethodsWe collected PROMIS-29 profile and EQ-5D-5L data from 3 general population samples (United Kingdom = 1509, France = 1501, Germany = 1502). Given that cognition is not assessed by the PROMIS-29, it was predicted by the recommended linear regression model. We compared the convergent validity, known-groups construct validity, and ceiling and floor effects of the PROPr and EQ-5D-5L.ResultsThe mean PROPr (0.48, 0.53, 0.48; P<.01) and EQ-5D-5L scores (0.82, 0.85, 0.83; P<.01) showed significant differences of similar magnitudes (d = 0.34; d = 0.32; d = 0.35; P<.01) across all samples. The differences were invariant to sex, income, occupation, education, and most conditions but not for age. The Pearson correlation coefficients between both scores were r = 0.74, r = 0.69, and r = 0.72. PROPr’s ceiling and floor effects both were minor to moderate. The EQ-5D-5L’s ceiling (floor) effects were major (negligible).ConclusionsBoth the EQ-5D-5L and the PROPr assessed by the PROMIS-29 show high validity. The PROPr yields considerably lower HSU values than the EQ-5D-5L. Consequences for quality-adjusted life-year measurements should be investigated in future research.     

中医药随机对照试验中采用真实世界数据作为对照组的研究设计及挑战

在设计随机对照试验（RCT）时,如果对照组存在患者招募和入组困难的情况,就会影响试验整体实施。近年来,真实世界数据（RWD）作为除RCT之外的数据来源,在医疗领域中发挥着越来越重要的作用。中医药RCT中可以尝试采用将RWD作为对照组的研究设计,不仅可以有效解决中医药RCT西医对照组患者入组困难的问题,同时能提供有力证据来评价中医药的疗效。倾向评分法目前已广泛应用于真实世界研究中混杂因素的处理,该文对RCT采用RWD作为对照组的这类设计中,基于倾向评分法常见的4种研究设计形式以实例分别进行了介绍,包括不对称随机分配、基于倾向评分分层法的两阶段设计、倾向评分联合复合似然法及倾向评分多种方法的联合。同时,这种设计类型也存在着方法学的挑战,包括RWD数据源必须是高质量且关键信息需要规范收集、RCT和RWD患者基线特征应该具有可比性、协变量选择时需要把所有已知与干预措施和结局相关的协变量都纳入进行分析等。在中医药领域采用这种设计时,还存在着有些RWD中医证型信息缺失、中医结局指标缺失等问题,在使用RWD时,需要根据数据实际情况决定如何分析。该文对以RWD作为RCT对照组的设计类型及面临的方法学挑战进行了介绍,期望能为研究者今后使用这类设计提供方法学借鉴。     

Associations of Dietary Patterns with Incident Depression: The Maastricht Study

Our aim was to assess the association between a priori defined dietary patterns and incident depressive symptoms. We used data from The Maastricht Study, a population-based cohort study (n = 2646, mean (SD) age 59.9 (8.0) years, 49.5% women; 15,188 person-years of follow-up). Level of adherence to the Dutch Healthy Diet (DHD), Mediterranean Diet, and Dietary Approaches To Stop Hypertension (DASH) were derived from a validated Food Frequency Questionnaire. Depressive symptoms were assessed at baseline and annually over seven-year-follow-up (using the 9-item Patient Health Questionnaire). We used Cox proportional hazards regression analyses to assess the association between dietary patterns and depressive symptoms. One standard deviation (SD) higher adherence in the DHD and DASH was associated with a lower hazard ratio (HR) of depressive symptoms with HRs (95%CI) of 0.78 (0.69–0.89) and 0.87 (0.77–0.98), respectively, after adjustment for sociodemographic and cardiovascular risk factors. After further adjustment for lifestyle factors, the HR per one SD higher DHD was 0.83 (0.73–0.96), whereas adherence to Mediterranean and DASH diets was not associated with incident depressive symptoms. Higher adherence to the DHD lowered risk of incident depressive symptoms. Adherence to healthy diet could be an effective non-pharmacological preventive measure to reduce the incidence of depression.     

Dietary Habit Is Associated with Depression and Intelligence: An Observational and Genome-Wide Environmental Interaction Analysis in the UK Biobank Cohort

Dietary habits have considerable impact on brain development and mental health. Despite long-standing interest in the association of dietary habits with mental health, few population-based studies of dietary habits have assessed depression and fluid intelligence. Our aim is to investigate the association of dietary habits with depression and fluid intelligence. In total, 814 independent loci were utilized to calculate the individual polygenic risk score (PRS) for 143 dietary habit-related traits. The individual genotype data were obtained from the UK Biobank cohort. Regression analyses were then conducted to evaluate the association of dietary habits with depression and fluid intelligence, respectively. PLINK 2.0 was utilized to detect the single nucleotide polymorphism (SNP) × dietary habit interaction effect on the risks of depression and fluid intelligence. We detected 22 common dietary habit-related traits shared by depression and fluid intelligence, such as red wine glasses per month, and overall alcohol intake. For interaction analysis, we detected that OLFM1 interacted with champagne/white wine in depression, while SYNPO2 interacted with coffee type in fluid intelligence. Our study results provide novel useful information for understanding how eating habits affect the fluid intelligence and depression.     

Internet Access and Nutritional Intake: Evidence from Rural China

Over the past 4 decades, China has experienced a nutritional transition and has developed the largest population of internet users. In this study, we evaluated the impacts of internet access on the nutritional intake in Chinese rural residents. An IV-Probit-based propensity score matching method was used to determine the impact of internet access on nutritional intake. The data were collected from 10,042 rural households in six Chinese provinces. The results reveal that rural residents with internet access have significantly higher energy, protein, and fat intake than those without. Chinese rural residents with internet access consumed 1.35% (28.62 kcal), 5.02% (2.61 g), and 4.33% (3.30 g) more energy, protein, and fat, respectively. There was heterogeneity in regard to the intake of energy, protein, and fat among those in different income groups. Moreover, non-staple food consumption is the main channel through which internet access affects nutritional intake. The results demonstrate that the local population uses the internet to improve their nutritional status. Further studies are required to investigate the impact of internet use on food consumed away from home and micronutrient intake.     

层次分析法在确定医疗设备维护优先级中的应用研究

目的:运用层次分析法(AHP)确定医疗设备维护中的优先级,增加医疗设备的可用性并降低维护成本。方法:采用AHP对医疗设备标准、子标准和等级进行评定获取其关键评分,基于多标准决策方法确定医疗设备维护的优先级,对选定设备进行评估,以准分子激光器和视力计为例,根据其标准权重、子标准权重和强度计算其总评分,确定维护优先级。结果:医疗设备维护的优先顺序由医疗设备评分的评估结果决定,医疗设备风险是医学技术人员在确定医疗设备维护优先级时的最重要标准。准分子激光器和视力计的关键评分权重分别为0.877和0.373,准分子激光器相比视力计在设备维护方面具有更高的优先级。结论:医疗设备维护优先级评估模型能确定医疗设备维护优先级,根据优先级规模规划医疗设备维护方案,以使资源更多地集中于具有高和中关键度的医疗设备。     

The effect of cardiovascular morbidity on clinical response provided by tadalafil in patients with erectile dysfunction

We aimed to investigate the association between erectile dysfunction and severity of cardiovascular morbidity and to assess clinical responses to tadalafil of patients in different cardiovascular risk groups. Between November 2019 and August 2020, a total of 258 male patients aged 45–70 years with ED were included. They were divided into three groups according to the Framingham risk score: low-risk (n: 86, 33.3%), intermediate-risk (n: 103, 39.9%) and high-risk (n: 69, 26.8%). At admission, all domains of the International Index of Erectile Function score were worse in high-risk group compared to other risk groups (p < .001). After a 12-week follow-up, a more significant improvement was observed in all domains of erectile function in all risk groups, but high-risk group had lower sexual scores (p < .001). The lowest rate for complete responsiveness to tadalafil was observed in the high-risk group (37.7%). The rate of failure in complete responsiveness was found to be 4.127 times greater with higher Framingham score and 3.102 times greater with higher erectile dysfunction severity at admission. Our preliminary findings show that more severe sexual disorders are observed in high-risk patients with cardiovascular morbidity. Individualised treatment may be important in high-risk group since they may benefit less from tadalafil, and failure in complete responsiveness can be more common in this group.     

Hospital Frailty Risk Score Outperforms Current Risk Stratification Models in Primary Total Hip and Knee Arthroplasty

BackgroundModels for risk stratification and prediction of outcome, such as the Charlson Comorbidity Index (CCI), the Elixhauser Comorbidity Method (ECM), the 5-factor modified Frailty Index (mFI-5), and the Hospital Frailty Risk Score (HFRS) have been validated in orthopedic surgery. The aim of this study is to compare the predictive power of these models in total hip and knee replacement.MethodsIn a retrospective analysis of 8250 patients who had undergone total joint replacement between 2011 and 2019, CCI, ECM, mFI-5, and HFRS were calculated for each patient. Receiver operating characteristic curve plots were generated and the area under the curve (AUC) was compared between each score with regard to adverse events such as transfusion, surgical, medical, and other complications. Multivariate logistic regression models were used to assess the relationship among risk stratification models, demographic factors, and postoperative adverse events.ResultsIn prediction of surgical complications, HFRS performed best (AUC: 0.719, P < .001), followed by ECM (AUC: 0.578, P < .001), mFI-5 (AUC: 0.564, P = .003), and CCI (AUC: 0.555, P = .012). With regard to medical complications, other complications, and transfusion, HFRS also was superior to ECM, mFI-5, and CCI. Multivariate logistic regression analyses revealed HFRS as an independent risk stratification model associated with all captured adverse events (P ≤ .001).ConclusionThe HFRS is superior to current risk stratification models in the context of total joint replacement. As the HRFS derives from routinely collected administrative data, healthcare providers can identify at-risk patients without additional effort or expense.