Systematic Review and Meta-Analysis on the Value of Chest CT in the Diagnosis of Coronavirus Disease (COVID-19):Sol Scientiae, Illustra Nos

OBJECTIVE. The purpose of this article is to systematically review and meta-analyze the diagnostic accuracy of chest CT in detecting coronavirus disease (COVID-19). MATERIALS AND METHODS. MEDLINE was systematically searched for publications on the diagnostic performance of chest CT in detecting COVID-19. Methodologic quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Meta-analysis was performed using a bivariate random-effects model. RESULTS. Six studies were included, comprising 1431 patients. All six studies included patients at high risk of COVID-19, and five studies explicitly reported that they included only symptomatic patients. Mean prevalence of COVID-19 was 47.9% (range, 27.6–85.4%). High or potential risk of bias was present throughout all QUADAS-2 domains in all six studies. Sensitivity ranged from 92.9% to 97.0%, and specificity ranged from 25.0% to 71.9%, with pooled estimates of 94.6% (95% CI, 91.9–96.4%) and 46.0% (95% CI, 31.9–60.7%), respectively. The included studies were statistically homogeneous in their estimates of sensitivity (p = 0.578) and statistically heterogeneous in their estimates of specificity (p < 0.001). CONCLUSION. Diagnostic accuracy studies on chest CT in COVID-19 suffer from methodologic quality issues. Chest CT appears to have a relatively high sensitivity in symptomatic patients at high risk of COVID-19, but it cannot exclude COVID-19. Specificity is poor. These data, along with other local factors such as COVID-19 prevalence, available real-time reverse transcriptase–polymerase chain reaction tests, staff, hospital, and CT scanning capacity, can be useful to healthcare professionals and policy makers to decide on the utility of chest CT for COVID-19 detection in the hospital setting

Chest CT Imaging Signature of Coronavirus Disease 2019 Infection In Pursuit of the Scientific Evidence:in pursuit of the scientific evidence

BACKGROUND: Chest CT may be used for the diagnosis of coronavirus disease 2019 (COVID-19), but clear scientific evidence is lacking. Therefore, we systematically reviewed and meta-analyzed the chest CT imaging signature of COVID-19.RESEARCH QUESTION: What is the chest CT imaging signature of COVID-19 infection?STUDY DESIGN AND METHODS: A systematic literature search was performed for original studies on chest CT imaging findings in patients with COVID-19. Methodologic quality of studies was evaluated. Pooled prevalence of chest CT imaging findings were calculated with the use of a random effects model in case of between-study heterogeneity (predefined as I-2 =50); otherwise, a fixed effects model was used.RESULTS: Twenty-eight studies were included. The median number of patients with COVID-19 per study was 124 (range, 50-476), comprising a total of 3,466 patients. Median prevalence of symptomatic patients was 99% (range, &gt;76.3%-100%). Twenty-seven of the studies (96%) had a retrospective design. Methodologic quality concerns were present with either risk of or actual referral bias (13 studies), patient spectrum bias (eight studies), disease progression bias (26 studies), observer variability bias (27 studies), and test review bias (14 studies). Pooled prevalence was 10.6% for normal chest CT imaging findings. Pooled prevalences were 90.0% for posterior predilection, 81.0% for ground-glass opacity, 75.8% for bilateral abnormalities, 73.1% for left lower lobe involvement, 72.9% for vascular thickening, and 72.2% for right lower lobe involvement. Pooled prevalences were 5.2% for pleural effusion, 5.1% for lymphadenopathy, 4.1% for airway secretions/tree-in-bud sign, 3.6% for central lesion distribution, 2.7% for pericardial effusion, and 0.7% for cavitation/cystic changes. Pooled prevalences of other CT imaging findings ranged between 10.5% and 63.2%.INTERPRETATION: Studies on chest CT imaging findings in COVID-19 suffer from methodologic quality concerns. More high-quality research is necessary to establish diagnostic CT criteria for COVID-19. Based on the available evidence that requires cautious interpretation, several chest CT imaging findings appear to be suggestive of COVID-19, but normal chest CT imaging findings do not exclude COVID-19, not even in symptomatic patients.</p

Recommendations in Second Opinion Reports of Neurologic Head and Neck Imaging:Frequency, Referring Clinicians? Compliance, and Diagnostic Yield

BACKGROUND AND PURPOSE: Second opinion reports of neurologic head and neck imaging are requested with increased regularity, and they may contain a recommendation to the clinician. Our aim was to investigate the frequency and determinants of the presence of a recommendation and the adherence by the referring physician to the recommendation in a second opinion neurology head and neck imaging report and the diagnostic yield of these recommendations. MATERIALS AND METHODS: This retrospective study included 994 consecutive second opinion reports of neurology head and neck imaging examinations performed at a tertiary care center. RESULTS: Of the 994 second opinion reports, 12.2% (121/994) contained a recommendation. An oncologic imaging indication was significantly (P = .030) associated with a lower chance of a recommendation in the second opinion report (OR = .67; 95% CI, 0.46?0.96). Clinicians followed 65.7% (88/134) of the recommendations. None of the investigated variables (patient age, sex, hospitalization status, indication for the second opinion report, experience of the radiologist who signed the second opinion report, strength of the recommendation, and whether the recommendation was made due to apparent quality issues of the original examination) were significantly associated with the compliance of the referring physician to this recommendation. The 134 individual recommendations eventually led to the establishment of 52 (38.2%) benign diagnoses and 28 (20.6%) malignant diagnoses, while no definitive diagnosis could be established in 56 (41.2%) cases. CONCLUSIONS: Recommendations are relatively common in second opinion reports of neurology head and neck imaging examinations, though less for oncologic indications. They are mostly followed by requesting physicians, thus affecting patient management. In most cases, they also lead to the establishment of a diagnosis, hence adding value to patient care

Classical generalized constant coupling model for geometrically frustrated antiferromagnets

A generalized constant coupling approximation for classical geometrically frustrated antiferromagnets is presented. Starting from a frustrated unit we introduce the interactions with the surrounding units in terms of an internal effective field which is fixed by a self consistency condition. Results for the magnetic susceptibility and specific heat are compared with Monte Carlo data for the classical Heisenberg model for the pyrochlore and kagome lattices. The predictions for the susceptibility are found to be essentially exact, and the corresponding predictions for the specific heat are found to be in very good agreement with the Monte Carlo results.Comment: 4 pages, 3 figures, 2 columns. Discussion about the zero T value of the pyrochlore specific heat correcte

Design and Characterization of a Hypervelocity Expansion Tube Facility

We report on the design and characterization of a 152 mm diameter expansion tube capable of accessing a range of high enthalpy test conditions with Mach numbers up to 7.1 for aerodynamic studies. Expansion tubes have the potential to offer a wide range of test flow conditions as gas acceleration is achieved through interaction with an unsteady expansion wave rather than expansion through a fixed area ratio nozzle. However, the range of test flow conditions is in practice limited by a number of considerations such as short test time and large amplitude flow disturbances. We present a generalized design strategy for small-scale expansion tubes. As a starting point, ideal gas dynamic calculations for optimal facility design to maximize test time at a given Mach number test condition are presented, together with a correction for the expansion head reflection through a non-simple region. A compilation of practical limitations that have been identified for expansion tube facilities such as diaphragm rupture and flow disturbance minimization is then used to map out a functional design parameter space. Experimentally, a range of test conditions have been verified through pitot pressure measurements and analysis of schlieren images of flow over simple geometries. To date there has been good agreement between theoretical and experimental results

Serum IGF-1 is insufficient to restore skeletal size in the total absence of the growth hormone receptor

States of growth hormone (GH) resistance, such those observed in Laron dwarf patients, are characterized by mutations in the GH receptor (GHR), decreased serum and tissue IGF-1 levels, impaired glucose tolerance, and impaired skeletal acquisition. IGF-1 replacement therapy in such patients increases growth velocity but does not normalize growth. Herein we combined the GH-resistant (GHR knockout [GHRKO]) mouse model with mice expressing the hepatic Igf-1 transgene (HIT) to generate the GHRKO-HIT mouse model. In GHRKO-HIT mice, serum IGF-1 levels were restored via transgenic expression of Igf-1, allowing us to study how endocrine IGF-1 affects growth, metabolic homeostasis, and skeletal integrity. We show that in a GH-resistant state, normalization of serum IGF-1 improved body adiposity and restored glucose tolerance but was insufficient to support normal skeletal growth, resulting in an osteopenic skeletal phenotype. The inability of serum IGF-1 to restore skeletal integrity in the total absence of GHR likely resulted from reduced skeletal Igf-1 gene expression, blunted GH-mediated effects on the skeleton that are independent of serum or tissue IGF-1, and poor delivery of IGF-1 to the tissues. These findings are consistent with clinical data showing that IGF-I replacement therapy in patients with Laron syndrome does not achieve full skeletal growth.Fil: Wu, Yingjie. University Of New York; Estados UnidosFil: Sun, Hui. University Of New York; Estados UnidosFil: Basta Pljakic, Jelena. City College of New York; Estados UnidosFil: Cardoso, Luis. City College of New York; Estados UnidosFil: Kennedy, Oran D.. City College of New York; Estados UnidosFil: Jasper, Hector Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas; ArgentinaFil: Domene, Horacio Mario. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas; ArgentinaFil: Karabatas, Liliana Margarita. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas; ArgentinaFil: Guida, María Clara. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas; ArgentinaFil: Schaffler, Mitchell B.. City College of New York; Estados UnidosFil: Rosen, Clifford J.. Maine Medical Center Research Institute; Estados UnidosFil: Yakar, Shoshana. University Of New York; Estados Unido

Machine learning in the differentiation of follicular lymphoma from diffuse large B-cell lymphoma with radiomic [F-18]FDG PET/CT features

Background One of the challenges in the management of patients with follicular lymphoma (FL) is the identification of individuals with histological transformation, most commonly into diffuse large B-cell lymphoma (DLBCL). [F-18]FDG-PET/CT is used for staging of patients with lymphoma, but visual interpretation cannot reliably discern FL from DLBCL. This study evaluated whether radiomic features extracted from clinical baseline [F-18]FDG PET/CT and analyzed by machine learning algorithms may help discriminate FL from DLBCL. Materials and methods Patients were selected based on confirmed histopathological diagnosis of primary FL (n=44) or DLBCL (n=76) and available [F-18]FDG PET/CT with EARL reconstruction parameters within 6 months of diagnosis. Radiomic features were extracted from the volume of interest on co-registered [F-18]FDG PET and CT images. Analysis of selected radiomic features was performed with machine learning classifiers based on logistic regression and tree-based ensemble classifiers (AdaBoosting, Gradient Boosting, and XG Boosting). The performance of radiomic features was compared with a SUVmax-based logistic regression model. Results From the segmented lesions, 121 FL and 227 DLBCL lesions were included for radiomic feature extraction. In total, 79 radiomic features were extracted from the SUVmap, 51 from CT, and 6 shape features. Machine learning classifier Gradient Boosting achieved the best discrimination performance using 136 radiomic features (AUC of 0.86 and accuracy of 80%). SUVmax-based logistic regression model achieved an AUC of 0.79 and an accuracy of 70%. Gradient Boosting classifier had a significantly greater AUC and accuracy compared to the SUVmax-based logistic regression (p Conclusion Machine learning analysis of radiomic features may be of diagnostic value for discriminating FL from DLBCL tumor lesions, beyond that of the SUVmax alone

Liver-Derived IGF-I Regulates Mean Life Span in Mice

Background: Transgenic mice with low levels of global insulin-like growth factor-I (IGF-I) throughout their life span, including pre- and postnatal development, have increased longevity. This study investigated whether specific deficiency of liver-derived, endocrine IGF-I is of importance for life span. Methods and Findings: Serum IGF-I was reduced by approximately 80 % in mice with adult, liver-specific IGF-I inactivation (LI-IGF-I-/- mice), and body weight decreased due to reduced body fat. The mean life span of LI-IGF-I-/- mice (n = 84) increased 10 % vs. control mice (n = 137) (Cox’s test, p,0.01), mainly due to increased life span (16%) of female mice [LI-IGF-I-/- mice (n = 31): 26.761.1 vs. control (n = 67): 23.060.7 months, p,0.001]. Male LI-IGF-I-/- mice showed only a tendency for increased longevity (p = 0.10). Energy expenditure, measured as oxygen consumption during and after submaximal exercise, was increased in the LI-IGF-I-/- mice. Moreover, microarray and RT-PCR analyses showed consistent regulation of three genes (heat shock protein 1A and 1B and connective tissue growth factor) in several body organs in the LI-IGF-I-/- mice. Conclusions: Adult inactivation of liver-derived, endocrine IGF-I resulted in moderately increased mean life span. Body weight and body fat decreased in LI-IGF-I-/- mice, possibly due to increased energy expenditure during exercise. Genes earlier reported to modulate stress response and collagen aging showed consistent regulation, providing mechanisms tha

Lyapunov functions and strict stability of Caputo fractional differential equations

One of the main properties studied in the qualitative theory of differential equations is the stability of solutions. The stability of fractional order systems is quite recent. There are several approaches in the literature to study stability, one of which is the Lyapunov approach. However, the Lyapunov approach to fractional differential equations causes many difficulties. In this paper a new definition (based on the Caputo fractional Dini derivative) for the derivative of Lyapunov functions to study a nonlinear Caputo fractional differential equation is introduced. Comparison results using this definition and scalar fractional differential equations are presented, and sufficient conditions for strict stability and uniform strict stability are given. Examples are presented to illustrate the theory

Postoperative Ultrasound in Kidney Transplant Recipients: Association Between Intrarenal Resistance Index and Cardiovascular Events

Background. Doppler ultrasound, including intrarenal resistance index (RI) measurement, is a widely used modality to assess kidney transplantation (KTx) vascularization. The aim of this study is to gain insight in the associations between early postoperative RI measurements and cardiovascular events (CVEs), all-cause mortality, and death-censored graft survival. Methods. From 2015 to 2017, a prospective cohort study was