EDTA chelation therapy for cardiovascular disease: a systematic review

BACKGROUND: Numerous practitioners of both conventional and complementary and alternative medicine throughout North America and Europe claim that chelation therapy with EDTA is an effective means to both control and treat cardiovascular disease. These claims are controversial, and several randomized controlled trials have been completed dealing with this topic. To address this issue we conducted a systematic review to evaluate the best available evidence for the use of EDTA chelation therapy in the treatment of cardiovascular disease. METHODS: We conducted a systematic review of 7 databases from inception to May 2005. Hand searches were conducted in review articles and in any of the trials found. Experts in the field were contacted and registries of clinical trials were searched for unpublished data. To be included in the final systematic review, the studies had to be randomized controlled clinical trials. RESULTS: A total of seven articles were found assessing EDTA chelation for the treatment of cardiovascular disease. Two of these articles were subgroup analyses of one RCT that looked at different clinical outcomes. Of the remaining five studies, two smaller studies found a beneficial effect whereas the other three exhibited no benefit for cardiovascular disease from the use of EDTA chelation therapy. Adverse effects were rare but those of note included a few cases of hypocalcemia and a single case of increased creatinine in a patient on the EDTA intervention. CONCLUSION: The best available evidence does not support the therapeutic use of EDTA chelation therapy in the treatment of cardiovascular disease. Although not considered to be a highly invasive or harmful therapy, it is possible that the use of EDTA chelation therapy in lieu of proven therapy may result in causing indirect harm to the patient

High Connectivity in the Deepwater Snapper Pristipomoides filamentosus (Lutjanidae) across the Indo-Pacific with Isolation of the Hawaiian Archipelago

In the tropical Indo-Pacific, most phylogeographic studies have focused on the shallow-water taxa that inhabit reefs to approximately 30 m depth. Little is known about the large predatory fishes, primarily snappers (subfamily Etelinae) and groupers (subfamily Epinephelinae) that occur at 100–400 m. These long-lived, slow-growing species support fisheries across the Indo-Pacific, yet no comprehensive genetic surveys within this group have been conducted. Here we contribute the first range-wide survey of a deepwater Indo-Pacific snapper, Pristipomoides filamentosus, with special focus on Hawai'i. We applied mtDNA cytochrome b and 11 microsatellite loci to 26 samples (N = 1,222) collected across 17,000 km from Hawai'i to the western Indian Ocean. Results indicate that P. filamentosus is a highly dispersive species with low but significant population structure (mtDNA ΦST = 0.029, microsatellite FST = 0.029) due entirely to the isolation of Hawai'i. No population structure was detected across 14,000 km of the Indo-Pacific from Tonga in the Central Pacific to the Seychelles in the western Indian Ocean, a pattern rarely observed in reef species. Despite a long pelagic phase (60–180 days), interisland dispersal as adults, and extensive gene flow across the Indo-Pacific, P. filamentosus is unable to maintain population connectivity with Hawai'i. Coalescent analyses indicate that P. filamentosus may have colonized Hawai'i 26 K–52 K y ago against prevailing currents, with dispersal away from Hawai'i dominating migration estimates. P. filamentosus harbors low genetic diversity in Hawai'i, a common pattern in marine fishes, and our data indicate a single archipelago-wide stock. However, like the Hawaiian Grouper, Hyporthodus quernus, this snapper had several significant pairwise comparisons (FST) clustered around the middle of the archipelago (St. Rogatien, Brooks Banks, Gardner) indicating that this region may be isolated or (more likely) receives input from Johnston Atoll to the south

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

Key questions for modelling COVID-19 exit strategies

This is the final version. Available on open access from the Royal Society via the DOI in this recordCombinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.Alan Turing InstituteEPSR

Key questions for modelling COVID-19 exit strategies

This is the final version. Available on open access from the Royal Society via the DOI in this recordCombinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.Alan Turing InstituteEPSR

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

Development and validation of prediction models for fetal growth restriction and birthweight: an individual participant data meta-analysis.

BACKGROUND: Fetal growth restriction is associated with perinatal morbidity and mortality. Early identification of women having at-risk fetuses can reduce perinatal adverse outcomes. OBJECTIVES: To assess the predictive performance of existing models predicting fetal growth restriction and birthweight, and if needed, to develop and validate new multivariable models using individual participant data. DESIGN: Individual participant data meta-analyses of cohorts in International Prediction of Pregnancy Complications network, decision curve analysis and health economics analysis. PARTICIPANTS: Pregnant women at booking. External validation of existing models (9 cohorts, 441,415 pregnancies); International Prediction of Pregnancy Complications model development and validation (4 cohorts, 237,228 pregnancies). PREDICTORS: Maternal clinical characteristics, biochemical and ultrasound markers. PRIMARY OUTCOMES: fetal growth restriction defined as birthweight <10th centile adjusted for gestational age and with stillbirth, neonatal death or delivery before 32 weeks' gestation birthweight. ANALYSIS: First, we externally validated existing models using individual participant data meta-analysis. If needed, we developed and validated new International Prediction of Pregnancy Complications models using random-intercept regression models with backward elimination for variable selection and undertook internal-external cross-validation. We estimated the study-specific performance (c-statistic, calibration slope, calibration-in-the-large) for each model and pooled using random-effects meta-analysis. Heterogeneity was quantified using τ2 and 95% prediction intervals. We assessed the clinical utility of the fetal growth restriction model using decision curve analysis, and health economics analysis based on National Institute for Health and Care Excellence 2008 model. RESULTS: Of the 119 published models, one birthweight model (Poon) could be validated. None reported fetal growth restriction using our definition. Across all cohorts, the Poon model had good summary calibration slope of 0.93 (95% confidence interval 0.90 to 0.96) with slight overfitting, and underpredicted birthweight by 90.4 g on average (95% confidence interval 37.9 g to 142.9 g). The newly developed International Prediction of Pregnancy Complications-fetal growth restriction model included maternal age, height, parity, smoking status, ethnicity, and any history of hypertension, pre-eclampsia, previous stillbirth or small for gestational age baby and gestational age at delivery. This allowed predictions conditional on a range of assumed gestational ages at delivery. The pooled apparent c-statistic and calibration were 0.96 (95% confidence interval 0.51 to 1.0), and 0.95 (95% confidence interval 0.67 to 1.23), respectively. The model showed positive net benefit for predicted probability thresholds between 1% and 90%. In addition to the predictors in the International Prediction of Pregnancy Complications-fetal growth restriction model, the International Prediction of Pregnancy Complications-birthweight model included maternal weight, history of diabetes and mode of conception. Average calibration slope across cohorts in the internal-external cross-validation was 1.00 (95% confidence interval 0.78 to 1.23) with no evidence of overfitting. Birthweight was underestimated by 9.7 g on average (95% confidence interval -154.3 g to 173.8 g). LIMITATIONS: We could not externally validate most of the published models due to variations in the definitions of outcomes. Internal-external cross-validation of our International Prediction of Pregnancy Complications-fetal growth restriction model was limited by the paucity of events in the included cohorts. The economic evaluation using the published National Institute for Health and Care Excellence 2008 model may not reflect current practice, and full economic evaluation was not possible due to paucity of data. FUTURE WORK: International Prediction of Pregnancy Complications models' performance needs to be assessed in routine practice, and their impact on decision-making and clinical outcomes needs evaluation. CONCLUSION: The International Prediction of Pregnancy Complications-fetal growth restriction and International Prediction of Pregnancy Complications-birthweight models accurately predict fetal growth restriction and birthweight for various assumed gestational ages at delivery. These can be used to stratify the risk status at booking, plan monitoring and management. STUDY REGISTRATION: This study is registered as PROSPERO CRD42019135045. FUNDING: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 17/148/07) and is published in full in Health Technology Assessment; Vol. 28, No. 14. See the NIHR Funding and Awards website for further award information

Relative contributions of crust and mantle to generation of Campanian high-K calc-alkaline I-type granitoids in a subduction setting, with special reference to the Harsit Pluton, Eastern Turkey

We present elemental and Sr-Nd-Pb isotopic data for the magmatic suite (similar to 79 Ma) of the Harsit pluton, from the Eastern Pontides (NE Turkey), with the aim of determining its magma source and geodynamic evolution. The pluton comprises granite, granodiorite, tonalite and minor diorite (SiO(2) = 59.43-76.95 wt%), with only minor gabbroic diorite mafic microgranular enclaves in composition (SiO(2) = 54.95-56.32 wt%), and exhibits low Mg# (&lt;46). All samples show a high-K calc-alkaline differentiation trend and I-type features. The chondrite-normalized REE patterns are fractionated [(La/Yb)(n) = 2.40-12.44] and display weak Eu anomalies (Eu/Eu* = 0.30-0.76). The rocks are characterized by enrichment of LILE and depletion of HFSE. The Harsit host rocks have weak concave-upward REE patterns, suggesting that amphibole and garnet played a significant role in their generation during magma segregation. The host rocks and their enclaves are isotopically indistinguishable. Sr-Nd isotopic data for all of the samples display I(Sr) = 0.70676-0.70708, epsilon(Nd)(79 Ma) = -4.4 to -3.3, with T(DM) = 1.09-1.36 Ga. The lead isotopic ratios are ((206)Pb/(204)pb) = 18.79-18.87, ((207)Pb/(204)Pb) = 15.59-15.61 and ((208)Pb/(204)Pb) = 38.71-38.83. These geochemical data rule out pure crustal-derived magma genesis in a post-collision extensional stage and suggest mixed-origin magma generation in a subduction setting. The melting that generated these high-K granitoidic rocks may have resulted from the upper Cretaceous subduction of the Izmir-Ankara-Erzincan oceanic slab beneath the Eurasian block in the region. The back-arc extensional events would have caused melting of the enriched subcontinental lithospheric mantle and formed mafic magma. The underplating of the lower crust by mafic magmas would have played a significant role in the generation of high-K magma. Thus, a thermal anomaly induced by underplated basic magma into a hot crust would have caused partial melting in the lower part of the crust. In this scenario, the lithospheric mantle-derived basaltic melt first mixed with granitic magma of crustal origin at depth. Then, the melts, which subsequently underwent a fractional crystallization and crustal assimilation processes, could ascend to shallower crustal levels to generate a variety of rock types ranging from diorite to granite. Sr-Nd isotope modeling shows that the generation of these magmas involved similar to 65-75% of the lower crustal-derived melt and similar to 25-35% of subcontinental lithospheric mantle. Further, geochemical data and the Ar-Ar plateau age on hornblende, combined with regional studies, imply that the Harsit pluton formed in a subduction setting and that the back-arc extensional period started by least similar to 79 Ma in the Eastern Pontides.Geochemistry &amp; GeophysicsMineralogySCI(E)33ARTICLE4467-48716