Diagnostic errors in paediatric cardiac intensive care

AbstractIntroductionDiagnostic errors cause significant patient harm and increase costs. Data characterising such errors in the paediatric cardiac intensive care population are limited. We sought to understand the perceived frequency and types of diagnostic errors in the paediatric cardiac ICU.MethodsPaediatric cardiac ICU practitioners including attending and trainee physicians, nurse practitioners, physician assistants, and registered nurses at three North American tertiary cardiac centres were surveyed between October 2014 and January 2015.ResultsThe response rate was 46% (N=200). Most respondents (81%) perceived that diagnostic errors harm patients more than five times per year. More than half (65%) reported that errors permanently harm patients, and up to 18% perceived that diagnostic errors contributed to death or severe permanent harm more than five times per year. Medication side effects and psychiatric conditions were thought to be most commonly misdiagnosed. Physician groups also ranked pulmonary overcirculation and viral illness to be commonly misdiagnosed as bacterial illness. Inadequate care coordination, data assessment, and high clinician workload were cited as contributory factors. Delayed diagnostic studies and interventions related to the severity of the patient’s condition were thought to be the most commonly reported process breakdowns. All surveyed groups ranked improving teamwork and feedback pathways as strategies to explore for preventing future diagnostic errors.ConclusionsPaediatric cardiac intensive care practitioners perceive that diagnostic errors causing permanent harm are common and associated more with systematic and process breakdowns than with cognitive limitations.</jats:sec

Increased Matrix Metalloproteinase (MMPs) Levels Do Not Predict Disease Severity or Progression in Emphysema

Rationale: Though matrix metalloproteinases (MMPs) are critical in the pathogenesis of COPD, their utility as a disease biomarker remains uncertain. This study aimed to determine whether bronchoalveolar lavage (BALF) or plasma MMP measurements correlated with disease severity or functional decline in emphysema. Methods: Enzyme-linked immunosorbent assay and luminex assays measured MMP-1, -9, -12 and tissue inhibitor of matrix metalloproteinase-1 in the BALF and plasma of non-smokers, smokers with normal lung function and moderate-to-severe emphysema subjects. In the cohort of 101 emphysema subjects correlative analyses were done to determine if MMP or TIMP-1 levels were associated with key disease parameters or change in lung function over an 18-month time period. Main Results: Compared to non-smoking controls, MMP and TIMP-1 BALF levels were significantly elevated in the emphysema cohort. Though MMP-1 was elevated in both the normal smoker and emphysema groups, collagenase activity was only increased in the emphysema subjects. In contrast to BALF, plasma MMP-9 and TIMP-1 levels were actually decreased in the emphysema cohort compared to the control groups. Both in the BALF and plasma, MMP and TIMP-1 measurements in the emphysema subjects did not correlate with important disease parameters and were not predictive of subsequent functional decline. Conclusions: MMPs are altered in the BALF and plasma of emphysema; however, the changes in MMPs correlate poorly with parameters of disease intensity or progression. Though MMPs are pivotal in the pathogenesis of COPD, these findings suggest that measuring MMPs will have limited utility as a prognostic marker in this disease. © 2013 D'Armiento et al

Marine Algal Toxin Azaspiracid Is an Open-State Blocker of hERG Potassium Channels

Azaspiracids (AZA) are polyether marine dinoflagellate toxins that accumulate in shellfish and represent an emerging human health risk. Although human exposure is primarily manifested by severe and protracted diarrhea, this toxin class has been shown to be highly cytotoxic, a teratogen to developing fish, and a possible carcinogen in mice. Until now, AZA's molecular target(s) has not yet been determined. Using three independent methods (voltage clamp, channel binding assay, and thallium flux assay), we have for the first time demonstrated that AZA1, AZA2, and AZA3 each bind to and block the hERG (human ether-à-go-go related gene) potassium channel heterologously expressed in HEK-293 mammalian cells. Inhibition of K+ current for each AZA analogue was concentration-dependent (IC50 value range: 0.64 - 0.84 μM). The mechanism of hERG channel inhibition by AZA1 was investigated further in Xenopus oocytes where it was shown to be an open state-dependent blocker and, using mutant channels, to interact with F656 but not with Y652 within the S6 transmembrane domain that forms the channel's central pore. AZA1, AZA2, and AZA3 were each shown to inhibit [3H]dofetilide binding to the hERG channel and thallium ion flux through the channel (IC50 value range: 2.1 – 6.6 μM). AZA1 did not block K+ current of the closely related EAG1 channel. Collectively, these data suggest that the AZAs physically block the K+ conductance pathway of hERG1 channels by occluding the cytoplasmic mouth of the open pore. Although the concentrations necessary to block hERG channels are relatively high, AZA-induced blockage may prove to contribute to the toxicological properties of the AZAs

High-Performance Acousto-Ultrasonic Scan System Being Developed

Acousto-ultrasonic (AU) interrogation is a single-sided nondestructive evaluation (NDE) technique employing separated sending and receiving transducers. It is used for assessing the microstructural condition and distributed damage state of the material between the transducers. AU is complementary to more traditional NDE methods, such as ultrasonic cscan, x-ray radiography, and thermographic inspection, which tend to be used primarily for discrete flaw detection. Throughout its history, AU has been used to inspect polymer matrix composites, metal matrix composites, ceramic matrix composites, and even monolithic metallic materials. The development of a high-performance automated AU scan system for characterizing within-sample microstructural and property homogeneity is currently in a prototype stage at NASA. This year, essential AU technology was reviewed. In addition, the basic hardware and software configuration for the scanner was developed, and preliminary results with the system were described. Mechanical and environmental loads applied to composite materials can cause distributed damage (as well as discrete defects) that plays a significant role in the degradation of physical properties. Such damage includes fiber/matrix debonding (interface failure), matrix microcracking, and fiber fracture and buckling. Investigations at the NASA Glenn Research Center have shown that traditional NDE scan inspection methods such as ultrasonic c-scan, x-ray imaging, and thermographic imaging tend to be more suited to discrete defect detection rather than the characterization of accumulated distributed micro-damage in composites. Since AU is focused on assessing the distributed micro-damage state of the material in between the sending and receiving transducers, it has proven to be quite suitable for assessing the relative composite material state. One major success story at Glenn with AU measurements has been the correlation between the ultrasonic decay rate obtained during AU inspection and the mechanical modulus (stiffness) seen during fatigue experiments with silicon carbide/silicon carbide (SiC/SiC) ceramic matrix composite samples. As shown in the figure, ultrasonic decay increased as the modulus decreased for the ceramic matrix composite tensile fatigue samples. The likely microstructural reason for the decrease in modulus (and increase in ultrasonic decay) is the matrix microcracking that commonly occurs during fatigue testing of these materials. Ultrasonic decay has shown the capability to track the pattern of transverse cracking and fiber breakage in these composites

Targeted genetic testing for familial hypercholesterolaemia using next generation sequencing:a population-based study

Background&lt;p&gt;&lt;/p&gt; Familial hypercholesterolaemia (FH) is a common Mendelian condition which, untreated, results in premature coronary heart disease. An estimated 88% of FH cases are undiagnosed in the UK. We previously validated a method for FH mutation detection in a lipid clinic population using next generation sequencing (NGS), but this did not address the challenge of identifying index cases in primary care where most undiagnosed patients receive healthcare. Here, we evaluate the targeted use of NGS as a potential route to diagnosis of FH in a primary care population subset selected for hypercholesterolaemia.&lt;p&gt;&lt;/p&gt; Methods&lt;p&gt;&lt;/p&gt; We used microfluidics-based PCR amplification coupled with NGS and multiplex ligation-dependent probe amplification (MLPA) to detect mutations in LDLR, APOB and PCSK9 in three phenotypic groups within the Generation Scotland: Scottish Family Health Study including 193 individuals with high total cholesterol, 232 with moderately high total cholesterol despite cholesterol-lowering therapy, and 192 normocholesterolaemic controls.&lt;p&gt;&lt;/p&gt; Results&lt;p&gt;&lt;/p&gt; Pathogenic mutations were found in 2.1% of hypercholesterolaemic individuals, in 2.2% of subjects on cholesterol-lowering therapy and in 42% of their available first-degree relatives. In addition, variants of uncertain clinical significance (VUCS) were detected in 1.4% of the hypercholesterolaemic and cholesterol-lowering therapy groups. No pathogenic variants or VUCS were detected in controls.&lt;p&gt;&lt;/p&gt; Conclusions&lt;p&gt;&lt;/p&gt; We demonstrated that population-based genetic testing using these protocols is able to deliver definitive molecular diagnoses of FH in individuals with high cholesterol or on cholesterol-lowering therapy. The lower cost and labour associated with NGS-based testing may increase the attractiveness of a population-based approach to FH detection compared to genetic testing with conventional sequencing. This could provide one route to increasing the present low percentage of FH cases with a genetic diagnosis

The Peculiar SN 2005hk: Do Some Type Ia Supernovae Explode as Deflagrations?

We present extensive u'g'r'i'BVRIYJHKs photometry and optical spectroscopy of SN 2005hk. These data reveal that SN 2005hk was nearly identical in its observed properties to SN 2002cx, which has been called ``the most peculiar known type Ia supernova.'' Both supernovae exhibited high ionization SN 1991T-like pre-maximum spectra, yet low peak luminosities like SN 1991bg. The spectra reveal that SN 2005hk, like SN 2002cx, exhibited expansion velocities that were roughly half those of typical type Ia supernovae. The R and I light curves of both supernovae were also peculiar in not displaying the secondary maximum observed for normal type Ia supernovae. Our YJH photometry of SN 2005hk reveals the same peculiarity in the near-infrared. By combining our optical and near-infrared photometry of SN 2005hk with published ultraviolet light curves obtained with the Swift satellite, we are able to construct a bolometric light curve from ~10 days before to ~60 days after B maximum. The shape and unusually low peak luminosity of this light curve, plus the low expansion velocities and absence of a secondary maximum at red and near-infrared wavelengths, are all in reasonable agreement with model calculations of a 3D deflagration which produces ~0.25 M_sun of 56Ni.Comment: Accepted by PASP, to appear in April 2007 issue, 63 pages, 16 figures, 11 table

An urban ecohydrological model to quantify the effect of vegetation on urban climate and hydrology (UT&C v1.0)

Increasing urbanization is likely to intensify the urban heat island effect, decrease outdoor thermal comfort and enhance runoff generation in cities. Urban green spaces are often proposed as a mitigation strategy to counteract these adverse effects and many recent developments of urban climate models focus on the inclusion of green and blue infrastructure to inform urban planning. However, many models still lack the ability to account for different plant types and oversimplify the interactions between the built environment, vegetation, and hydrology. In this study, we present an urban ecohydrological model, Urban Tethys-Chloris (UT&C), that combines principles of ecosystem modelling with an urban canopy scheme accounting for the biophysical and ecophysiological characteristics of roof vegetation, ground vegetation and urban trees. UT&C is a fully coupled energy and water balance model that calculates 2 m air temperature, 2 m humidity, and surface temperatures based on the infinite urban canyon approach. It further calculates all urban hydrological fluxes, including transpiration as a function of plant photosynthesis. Hence, UT&C accounts for the effects of different plant types on the urban climate and hydrology, as well as the effects of the urban environment on plant well-being and performance. UT&C performs well when compared against energy flux measurements of eddy covariance towers located in three cities in different climates (Singapore, Melbourne, Phoenix). A sensitivity analysis, performed as a proof of concept for the city of Singapore, shows a mean decrease in 2 m air temperature of 1.1 °C for fully grass covered ground, 0.2 °C for high values of leaf area index (LAI), and 0.3 °C for high values of Vc,max (an expression of photosynthetic activity). These reductions in temperature were combined with a simultaneous increase in relative humidity by 6.5 %, 2.1 %, and 1.6 %, for fully grass covered ground, high values of LAI, and high values of Vc,max, respectively. Furthermore, the increase of pervious vegetated ground is able to significantly reduce surface runoff. These results show that urban greening can lead to a decrease in urban air temperature and surface runoff, but this effect is limited in cities characterized by a hot, humid climate.ISSN:1991-962XISSN:1991-961

Hydrostatic pressure does not cause detectable changes to survival of human retinal ganglion

Purpose: Elevated intraocular pressure (IOP) is a major risk factor for glaucoma. One consequence of raised IOP is that ocular tissues are subjected to increased hydrostatic pressure (HP). The effect of raised HP on stress pathway signaling and retinal ganglion cell (RGC) survival in the human retina was investigated. Methods: A chamber was designed to expose cells to increased HP (constant and fluctuating). Accurate pressure control (10-100mmHg) was achieved using mass flow controllers. Human organotypic retinal cultures (HORCs) from donor eyes (<24h post mortem) were cultured in serum-free DMEM/HamF12. Increased HP was compared to simulated ischemia (oxygen glucose deprivation, OGD). Cell death and apoptosis were measured by LDH and TUNEL assays, RGC marker expression by qRT-PCR (THY-1) and RGC number by immunohistochemistry (NeuN). Activated p38 and JNK were detected by Western blot. Results: Exposure of HORCs to constant (60mmHg) or fluctuating (10-100mmHg; 1 cycle/min) pressure for 24 or 48h caused no loss of structural integrity, LDH release, decrease in RGC marker expression (THY-1) or loss of RGCs compared with controls. In addition, there was no increase in TUNEL-positive NeuN-labelled cells at either time-point indicating no increase in apoptosis of RGCs. OGD increased apoptosis, reduced RGC marker expression and RGC number and caused elevated LDH release at 24h. p38 and JNK phosphorylation remained unchanged in HORCs exposed to fluctuating pressure (10-100mmHg; 1 cycle/min) for 15, 30, 60 and 90min durations, whereas OGD (3h) increased activation of p38 and JNK, remaining elevated for 90min post-OGD. Conclusions: Directly applied HP had no detectable impact on RGC survival and stress-signalling in HORCs. Simulated ischemia, however, activated stress pathways and caused RGC death. These results show that direct HP does not cause degeneration of RGCs in the ex vivo human retina

Machine-learning to Stratify Diabetic Patients Using Novel Cardiac Biomarkers and Integrative Genomics

Background: Diabetes mellitus is a chronic disease that impacts an increasing percentage of people each year. Among its comorbidities, diabetics are two to four times more likely to develop cardiovascular diseases. While HbA1c remains the primary diagnostic for diabetics, its ability to predict long-term, health outcomes across diverse demographics, ethnic groups, and at a personalized level are limited. The purpose of this study was to provide a model for precision medicine through the implementation of machine-learning algorithms using multiple cardiac biomarkers as a means for predicting diabetes mellitus development. Methods: Right atrial appendages from 50 patients, 30 non-diabetic and 20 type 2 diabetic, were procured from the WVU Ruby Memorial Hospital. Machine-learning was applied to physiological, biochemical, and sequencing data for each patient. Supervised learning implementing SHapley Additive exPlanations (SHAP) allowed binary (no diabetes or type 2 diabetes) and multiple classifcation (no diabetes, prediabetes, and type 2 diabetes) of the patient cohort with and without the inclusion of HbA1c levels. Findings were validated through Logistic Regression (LR), Linear Discriminant Analysis (LDA), Gaussian Naïve Bayes (NB), Support Vector Machine (SVM), and Classifcation and Regression Tree (CART) models with tenfold cross validation. Results: Total nuclear methylation and hydroxymethylation were highly correlated to diabetic status, with nuclear methylation and mitochondrial electron transport chain (ETC) activities achieving superior testing accuracies in the predictive model (~84% testing, binary). Mitochondrial DNA SNPs found in the D-Loop region (SNP-73G, -16126C, and -16362C) were highly associated with diabetes mellitus. The CpG island of transcription factor A, mitochondrial (TFAM) revealed CpG24 (chr10:58385262, P=0.003) and CpG29 (chr10:58385324, P=0.001) as markers correlating with diabetic progression. When combining the most predictive factors from each set, total nuclear methylation and CpG24 methylation were the best diagnostic measures in both binary and multiple classifcation sets. Conclusions: Using machine-learning, we were able to identify novel as well as the most relevant biomarkers associated with type 2 diabetes mellitus by integrating physiological, biochemical, and sequencing datasets. Ultimately, this approach may be used as a guideline for future investigations into disease pathogenesis and novel biomarker discover

DREADD agonist 21 is an effective agonist for muscarinic-based DREADDs in vitro and in vivo

Chemogenetic tools such as designer receptors exclusively activated by designer drugs (DREADDs) are routinely used to modulate neuronal and non-neuronal signaling and activity in a relatively noninvasive manner. The first generation of DREADDs were templated from the human muscarinic acetylcholine receptor family and are relatively insensitive to the endogenous agonist acetylcholine but instead are activated by clozapine-N-oxide (CNO). Despite the undisputed success of CNO as an activator of muscarinic DREADDs, it has been known for some time that CNO is subject to a low rate of metabolic conversion to clozapine, raising the need for alternative chemical actuators of muscarinic-based DREADDs. Here we show that DREADD agonist 21 (C21) (11-(1-piperazinyl)-5H-dibenzo[b,e][1,4]diazepine) is a potent and selective agonist at both excitatory (hM3Dq) and inhibitory (hM4Di) DREADDs and has excellent bioavailability, pharmacokinetic properties, and brain penetrability. We also show that C21-induced activation of hM3Dq and hM4Di in vivo can modulate bidirectional feeding in defined circuits in mice. These results indicate that C21 represents an alternative to CNO for in vivo studies where metabolic conversion of CNO to clozapine is a concern