Search

The optimal cut-off value of the optical density index of the galactomannan antigen assays (GM) for diagnosing invasive pulmonary aspergillosis in hematological patients is a disputed topic. This article conducts a systematic review with a meta-analysis to establish which optical density index (ODI) cut-off value should be implemented into clinical practice. Pubmed, Embase and Cochrane databases were searched (N = 27). The pooled data, using a generalized linear mixed model with binomial distribution, resulted in an overall serum sensitivity of 0.76 and a specificity of 0.92. For serum ODI 0.5 there was a pooled sensitivity of 0.92 and a specificity of 0.84. The pooled data of all broncho-alveolar lavage (BAL) studies resulted in an overall sensitivity of 0.80 and a specificity of 0.95. For BAL ODI 0.5, there was a pooled sensitivity of 0.75 and a specificity of 0.88. For the BAL ODI 1.0 pooling, the studies resulted in a sensitivity of 0.75 and a specificity of 0.96. Serum ODI of 0.5 and BAL ODI of 1.0 are the most suitable cut-offs for clinical practice. However, our study affirms that the evidence for the use of GM in clinical practice for the hematological malignancy patient is currently insufficient and more research is needed to determine the diagnostic value of GM. [ABSTRACT FROM AUTHOR]

The robustness of the t linear mixed model (tLMM) has been proved and exploited in many applications. Various publications emerged with the aim of proving superiority with respect to traditional linear mixed models, extending to more general settings and proposing more efficient estimation methods. However, little attention has been paid to the mathematical properties of the model itself and to the evaluation of the proposed estimation methods. In this paper we perform an in-depth analysis of the tLMM, evaluating a direct maximum likelihood estimation method via an intensive simulation study and investigating some identifiability properties. The theoretical findings are illustrated through an application to a dataset collected from a sleep trial. [ABSTRACT FROM AUTHOR]

Purpose: Cardiorespiratory fitness (CRF) plays an essential role in health outcomes and quality of life. However, it is often not assessed nor estimated. Objective CRF assessment is costly, labour intensive and not widely available. Patient-reported outcome measures estimate CRF more cost-efficiently, but current questionnaires lack accuracy. The aim of this study is to develop a new self-reported questionnaire to estimate CRF. Materials and Methods: The FitMáx©-questionnaire, consisting of only three questions assessing walking, stair climbing, and cycling capacity, was compared with the commonly used Duke Activity Status Index (DASI) and Veterans Specific Activity Questionnaire (VSAQ). These questionnaires were compared to peak oxygen uptake (VO2peak) as measured with cardiopulmonary exercise testing. This study included 759 cardiac, pulmonary and oncologic patients and healthy persons aged 18‒90. Results: FitMáx© strongly correlated (r = 0.94 (0.92‒0.95) SEE = 4.14 mL∙kg− 1∙min− 1) with measured VO2peak. Bias between predicted and measured VO2peak was − 0.24 (− 9.23‒8.75; 95% limits of agreement) mL·kg− 1·min− 1. The FitMáx© scored superiorly on correlation and SEE compared with the DASI and VSAQ, r = 0.75 (0.68‒0.80) SEE = 4.62 mL∙kg− 1∙min− 1 and r = 0.87 (0.83‒0.90) SEE = 6.75 mL∙kg− 1∙min− 1, respectively. Conclusion: FitMáx© is a valid and accessible questionnaire to estimate CRF expressed as VO2peak in clinical practice and shows substantial improvement compared to currently used questionnaires. [ABSTRACT FROM AUTHOR]

Models characterized by autoregressive structure and random coefficients are powerful tools for the analysis of high-frequency, high-dimensional and volatile time series. The available literature on such models is broad, but also sector-specific, overlapping, and confusing. Most models focus on one property of the data, while much can be gained by combining the strength of various models and their sources of heterogeneity. We present a structured overview of the literature on autoregressive models with random coefficients. We describe hierarchy and analogies among models, and for each we systematically list properties, estimation methods, tests, software packages and typical applications. [ABSTRACT FROM AUTHOR]

Purpose: Cardiorespiratory fitness (CRF) plays an essential role in health outcomes and quality of life. However, it is often not assessed nor estimated. Objective CRF assessment is costly, labour intensive and not widely available. Patient-reported outcome measures estimate CRF more cost-efficiently, but current questionnaires lack accuracy. The aim of this study is to develop a new self-reported questionnaire to estimate CRF., Materials and Methods: The FitMáx©-questionnaire, consisting of only three questions assessing walking, stair climbing, and cycling capacity, was compared with the commonly used Duke Activity Status Index (DASI) and Veterans Specific Activity Questionnaire (VSAQ). These questionnaires were compared to peak oxygen uptake (VO 2peak ) as measured with cardiopulmonary exercise testing. This study included 759 cardiac, pulmonary and oncologic patients and healthy persons aged 18‒90., Results: FitMáx© strongly correlated (r = 0.94 (0.92‒0.95) SEE = 4.14 mL∙kg -1 ∙min -1 ) with measured VO 2peak . Bias between predicted and measured VO 2peak was -0.24 (-9.23‒8.75; 95% limits of agreement) mL·kg -1 ·min -1 . The FitMáx© scored superiorly on correlation and SEE compared with the DASI and VSAQ, r = 0.75 (0.68‒0.80) SEE = 4.62 mL∙kg -1 ∙min -1 and r = 0.87 (0.83‒0.90) SEE = 6.75 mL∙kg -1 ∙min -1 , respectively., Conclusion: FitMáx© is a valid and accessible questionnaire to estimate CRF expressed as VO 2peak in clinical practice and shows substantial improvement compared to currently used questionnaires., Competing Interests: Miss Renske Meijer reports grants from Stichting SOS, grants from National Foundation Against Cancer (NFtK), during the conduct of the study. The authors report no other conflicts of interest in this work., (© 2022 Meijer et al.)