Predictive Value of the PaO2/FIO2 Ratio for Mortality in Patients with Acute Respiratory Distress Syndrome: A Systematic Review and Meta-Analysis

Background PaO2 /FIO2 (P/F) ratio has been used to define the severity of acute respiratory distress syndrome (ARDS) despite the controversy of its clinical utility. This systematic review and meta-analysis (SRMA) aimed to obtain summary estimates of predictive performance of the P/F ratio for predicting mortality in ARDS patients. Methods We included a study wherein the study population comprised ARDS patients in any clinical setting. Medline and Cochrane Central Registry of Controlled Trials were searched for all English language articles. We performed a SRMA on the accuracy of diagnostic prognostic tests using QUADAS-2 tool to evaluate the risk of bias. To pool the results, we applied the bivariate model and obtained summary point estimates of sensitivity and specificity with 95% CIs. Results Twenty-eight trials and 38270 patients were included in the meta-analysis. Most of the study settings were in the intensive care units. The overall risk of bias was high. The pooled sensitivity of the P/F ratio in all included studies for a P/F ratio of 100 was 43.6% (95% CI, 36.9-50.5%) and the specificity was 71.1% (95% CI, 66.7-75.1%) and those for a P/F ratio of 200 were 83.2% (95% CI, 78.2-87.2%) and 26.2% (95% CI, 21.2-31.9%). Interpretation The P/F ratio had high sensitivity and moderate specificity at a P/F ratio of 200 and 100 respectively, which supports the use of the P/F ratio for screening ARDS patients who are at risk of deterioration.Trial registration: The study was registered in UMIN with registration number 64 000041058.

On the least squares estimator asymptotic normality of the multivariate symmetric textured surface parameters

A multivariate trigonometric regression model is considered. Various discrete modifications of the similar bivariate model received serious attention in the literature on signal and image processing due to multiple applications in the analysis of symmetric textured surfaces. In the paper asymptotic normality of the least squares estimator for amplitudes and angular frequencies is obtained in multivariate trigonometric model assuming that the random noise is a homogeneous or homogeneous and isotropic Gaussian, in particular, strongly dependent random field on R M , M > 2. \mathbb {R}^M,\,\, M>2.

Anti-Xa Activity of Enoxaparin for Prevention of Venous Thromboembolism in Severe Nephrotic Syndrome—A Single Center Prospective Study

Severe nephrotic syndrome (NS) is associated with high risk of venous thromboembolic events (VTE), as well as presumably altered heparin pharmacokinetics and pharmacodynamics. Although prophylactic anticoagulation is recommended, the optimal dose is not established. The aim of the study was to test two co-primary hypotheses: of reduced enoxaparin effectiveness and of the need for dose-adjustment in NS. Forty two nephrotic patients with serum albumin ≤2.5 g/dL were alternately assigned to a standard fixed-dose of enoxaparin (NS-FD: 40 mg/day) or ideal body weight (IBW)-based adjusted-dose (NS-AD: 1 mg/kg/day). Twenty one matched non-proteinuric individuals (C-FD) also received fixed-dose. Co-primary outcomes were: the achievement of low- and high-VTE risk threshold of antifactor-Xa activity (anti-FXa) defined as 0.2 IU/mL and 0.3 IU/mL, respectively. Low-VTE-risk threshold was achieved less often in NS-FD than C-FD group (91 vs. 62%, p = 0.024), while the high-VTE-risk threshold more often in NS-AD than in NS-FD group (90 vs. 38%, p < 0.001). Two VTE were observed in NS during 12 months of follow-up (incidence: 5.88%/year). In both cases anti-FXa were 0.3 IU/mL implying the use of anti-FXa >0.3 IU/mL as a target for dose-adjustment logistic regression models. We determined the optimal dose/IBW cut-off value at 0.8 mg/kg and further developed bivariate model (termed the DoAT model) including dose/IBW and antithrombin activity that improved the diagnostic accuracy (AUC 0.85 ± 0.06 vs. AUC 0.75 ± 0.08). Enoxaparin efficacy is reduced in severe NS and the dose should be adjusted to ideal body weight to achieve target anti-FXa activity.

Coupling Effects of Depression and Functional Disability: Using Bivariate Latent Change Score Model

The purpose of the study was to examine the coupling effect of depression and functional disability over four time points using the data from the Health and Retirement Study (HRS). The sample included participants who survived to 98 years or older (N = 458). Four alternative latent change score models were computed to examine the univariate and bivariate effects among depressive symptoms (CES-D) and functional disabilities (ADL): No-coupling, univariate model of ADL to change in CES-D, univariate model of CES-D to change in ADL, and bivariate model. As hypothesized, the no-coupling model did not fit the data well, χ2 (26) = 164.86, CFI = 0.85, RMSEA = 0.11. Model 2, ADL predicting change in CES-D, did not fit the data well, χ2 (25) = 164.18, CFI = 0.85, RMSEA = 0.11. Model 3, CES-D predicting change in ADL, also did not fit the data, χ2 (25) = 148.06, CFI = 0.87, RMSEA = 0.10. The bivariate model fit the data well, χ2 (21) = 66.94, CFI = 0.95, RMSEA = 0.07, and was the best fitting model. All level to change effects were significant in model 4. One’s CES-D at prior waves was positively associated with change in ADL at subsequent waves, and ADL at prior waves was positively associated with change in CES-D at subsequent waves. In conclusion, there is a significant coupling effect between depressive symptoms and ADL over time. Future health policies should monitor older adults’ mental and functional health simultaneously for their possible spillover effects.

Predictive Value of the PaO2/FIO2 Ratio for Mortality in Patients with Acute Respiratory Distress Syndrome: A Systematic Review and Meta-Analysis

BackgroundPaO2/FIO2 (P/F) ratio has been used to define the severity of acute respiratory distress syndrome (ARDS) despite the controversy of its clinical utility. This systematic review and meta-analysis (SRMA) aimed to obtain summary estimates of predictive performance of the P/F ratio for predicting mortality in ARDS patients.MethodsWe included a study wherein the study population comprised ARDS patients in anyclinical setting. Medline and Cochrane Central Registry of Controlled Trials were searched for all English language articles. We performed a SRMA on the accuracy of diagnostic prognostic tests using QUADAS-2 tool to evaluate the risk of bias. To pool the results, we applied the bivariate model and obtained summary point estimates of sensitivity and specificity with 95% CIs.ResultsTwenty-eight trials and 38270 patients were included in the meta-analysis. Most of the study settings were in the intensive care units. The overall risk of bias was high. The pooled sensitivity of the P/F ratio in all included studies for a P/F ratio of 100 was 43.6% (95% CI, 36.9-50.5%) and the specificity was 71.1% (95% CI, 66.7-75.1%) and those for a P/F ratio of 200 were 83.2% (95% CI, 78.2-87.2%) and 26.2% (95% CI, 21.2-31.9%). ConclusionThe P/F ratio had high sensitivity and moderate specificity at a P/F ratio of 200 and 100 respectively., which supports the use of the P/F ratio for screening ARDS patients who are at risk of deterioration.Trial registration: The study was registered in UMIN with registration number 000041058.

Classical and Bayesian Inference of a Mixture of Bivariate Exponentiated Exponential Model

Exponentiated exponential (EE) model has been used effectively in reliability, engineering, biomedical, social sciences, and other applications. In this study, we introduce a new bivariate mixture EE model with two parameters assuming two cases, independent and dependent random variables. We develop a bivariate mixture starting from two EE models assuming two cases, two independent and two dependent EE models. We study some useful statistical properties of this distribution, such as marginals and conditional distributions and product moments and conditional moments. In addition, we study a dependent case, a new mixture of the bivariate model based on EE distribution marginal with two parameters and with a bivariate Gaussian copula. Different methods of estimation for the model parameters are used both under the classical and under the Bayesian paradigm. Some simulation studies are presented to verify the performance of the estimation methods of the proposed model. To illustrate the flexibility of the proposed model, a real dataset is reanalyzed.

Single-step genomic evaluation with metafounders for feed conversion ratio and average daily gain in Danish Landrace and Yorkshire pigs

Background The single-step genomic best linear unbiased prediction (SSGBLUP) method is a popular approach for genetic evaluation with high-density genotype data. To solve the problem that pedigree and genomic relationship matrices refer to different base populations, a single-step genomic method with metafounders (MF-SSGBLUP) was put forward. The aim of this study was to compare the predictive ability and bias of genomic evaluations obtained with MF-SSGBLUP and standard SSGBLUP. We examined feed conversion ratio (FCR) and average daily gain (ADG) in DanBred Landrace (LL) and Yorkshire (YY) pigs using both univariate and bivariate models, as well as the optimal weighting factors (ω), which represent the proportions of the genetic variance not captured by markers, for ADG and FCR in SSGBLUP and MF-SSGBLUP. Results In general, SSGBLUP and MF-SSGBLUP showed similar predictive abilities and bias of genomic estimated breeding values (GEBV). In the LL population, the predictive ability for ADG reached 0.36 using uni- or bi-variate SSGBLUP or MF-SSGBLUP, while the predictive ability for FCR was highest (0.20) for the bivariate model using MF-SSGBLUP, but differences between analyses were very small. In the YY population, predictive ability for ADG was similar for the four analyses (up to 0.35), while the predictive ability for FCR was highest (0.36) for the uni- and bi-variate MF-SSGBLUP analyses. SSGBLUP and MF-SSGBLUP exhibited nearly the same bias. In general, the bivariate models had lower bias than the univariate models. In the LL population, the optimal ω for ADG was ~ 0.2 in the univariate or bivariate models using SSGBLUP or MF-SSGBLUP, and the optimal ω for FCR was 0.70 and 0.55 for SSGBLUP and MF-SSGBLUP, respectively. In the YY population, the optimal ω ranged from 0.25 to 0. 35 for ADG across the four analyses and from 0.10 to 0.30 for FCR. Conclusions Our results indicate that MF-SSGBLUP performed slightly better than SSGBLUP for genomic evaluation. There was little difference in the optimal weighting factors (ω) between SSGBLUP and MF-SSGBLUP. Overall, the bivariate model using MF-SSGBLUP is recommended for single-step genomic evaluation of ADG and FCR in DanBred Landrace and Yorkshire pigs.

The use of cone-beam computed tomography (CBCT) in radiocarpal fractures: a diagnostic test accuracy meta-analysis

Objective Occult radiocarpal fractures often present a diagnostic challenge to the emergency department. Accurate diagnosis of these injuries is crucial as a missed fracture can lead to significant morbidity. Cone-beam CT (CBCT) scan is a novel imaging modality, with minimal radiation exposure and comparatively fast acquisition time. Our aim was to evaluate its use in the diagnosis of cortical fractures in the upper limb extremity. Materials and methods We conducted a systematic review of literature and included all studies that evaluated the use of CBCT in the diagnosis of radiocarpal fractures. We used a mixed-effects logistic regression bivariate model to estimate the summary sensitivity and specificity and constructed hierarchical summary receiver operative characteristic curves (HSROC). Results We identified 5 studies, with 439 patients, and observed CBCT to be 87.7% (95% CI 77.6–93.6) sensitive and 99.2% (95% CI 92.6–99.9) specific for scaphoid fractures. For carpal fractures, CBCT was observed to have a pooled sensitivity and specificity of 90.6% (95% CI 72.7–97.2) and 100% (95% CI 99–100) respectively. For distal radius fractures, CBCT sensitivity was 90% (95% CI 67–98) and specificity was 100% (95% CI 10–100). The overall inter-rater agreement effect was shown to be 0.89 (95% CI 0.82–0.96), which is deemed to be almost perfect. Conclusion CBCT is an accurate diagnostic tool for occult radiocarpal cortical fractures, which could replace or supplement radiographs. We believe CBCT has a promising role in the acute radiocarpal fracture diagnostic algorithm in both emergency and trauma departments.

Anti-DFS70 Antibodies for Differentiating Systemic Autoimmune Rheumatic Disease in Patients with Positive ANA Tests: A Systematic Review and Meta-Analysis

Anti-DFS70 antibodies have been proposed as a marker to exclude systemic autoimmune rheumatic disease (SARD). We conducted this systematic diagnostic test accuracy review and meta-analysis to determine the performance of anti-DFS70 antibodies in patients with a positive anti-nuclear antibody (ANA) test result to exclude SARD. We searched PubMed, Embase, Web of Science, Scopus and the Cochrane Library up to 22 February 2021, and included studies examining the diagnostic accuracy of anti-DFS70 antibodies in patients with a positive ANA test result. The results were pooled using a hierarchical bivariate model and plotted in summary receiver operating characteristic curves. R software and Stata Statistical Software were used for the statistical analysis. Eight studies with 4168 patients were included. The summary sensitivity was 0.19 (95% confidence interval: 0.12–0.28) and the specificity was 0.93 (95% confidence interval: 0.88–0.96). The area under the curve was 0.69 (95% confidence interval: 0.64–0.72). The meta-regression analysis showed that targeting only ANA-associated rheumatic disease was associated with higher specificity. In addition, the studies with a non-SARD prevalence of <80% and using a chemiluminescence assay were associated with higher specificity. Anti-DFS70 antibodies have high specificity for the exclusion of SARD among patients presenting with a positive ANA test, but the sensitivity is low.

Why do Spanish households separate their e-waste for proper disposal? An econometric analysis

Improving e-waste separate collection rates is of the utmost importance to achieve the environmental targets set in the Sustainable Development Goals. Therefore, this paper aims to identify the factors influencing the intentions of Spanish households to separate their e-waste for proper disposal. To this end, we carry out an econometric analysis revealing that the preoccupation with environmental issues is an endogenous regressor, so a bivariate model is required to avoid inconsistent results. The analysis shows that environmental concern and the origin of the individuals are relevant factors that influence the e-waste separation decision. Additionally, we observe an interaction between age and city size, so the effect of one of these factors on the probability of separating e-waste depends on the other factor. Another important result is that several socio-economic variables and knowledge of environmental issues only indirectly affect attitudes, by way of environmental concern. In summary, this study offers a useful methodology to policymakers who have to deal with e-waste management, allowing them to identify the priority groups on which should be focused, as well as to design specific measures tailored to their characteristics.