Severe 2010 Cold-Water Event Caused Unprecedented Mortality to Corals of the Florida Reef Tract and Reversed Previous Survivorship Patterns

Background Coral reefs are facing increasing pressure from natural and anthropogenic stressors that have already caused significant worldwide declines. In January 2010, coral reefs of Florida, United States, were impacted by an extreme cold-water anomaly that exposed corals to temperatures well below their reported thresholds (16°C), causing rapid coral mortality unprecedented in spatial extent and severity. Methodology/Principal Findings Reef surveys were conducted from Martin County to the Lower Florida Keys within weeks of the anomaly. The impacts recorded were catastrophic and exceeded those of any previous disturbances in the region. Coral mortality patterns were directly correlated to in-situ and satellite-derived cold-temperature metrics. These impacts rival, in spatial extent and intensity, the impacts of the well-publicized warm-water bleaching events around the globe. The mean percent coral mortality recorded for all species and subregions was 11.5% in the 2010 winter, compared to 0.5% recorded in the previous five summers, including years like 2005 where warm-water bleaching was prevalent. Highest mean mortality (15%–39%) was documented for inshore habitats where temperatures were \u3c11°C for prolonged periods. Increases in mortality from previous years were significant for 21 of 25 coral species, and were 1–2 orders of magnitude higher for most species. Conclusions/Significance The cold-water anomaly of January 2010 caused the worst coral mortality on record for the Florida Reef Tract, highlighting the potential catastrophic impacts that unusual but extreme climatic events can have on the persistence of coral reefs. Moreover, habitats and species most severely affected were those found in high-coral cover, inshore, shallow reef habitats previously considered the “oases” of the region, having escaped declining patterns observed for more offshore habitats. Thus, the 2010 cold-water anomaly not only caused widespread coral mortality but also reversed prior resistance and resilience patterns that will take decades to recover

Prehospital risk stratification in patients with chest pain

OBJECTIVES: The History, ECG, Age, Risk Factors and Troponin (HEART) Score is a decision support tool applied by physicians in the emergency department developed to risk stratify low-risk patients presenting with chest pain. We assessed the potential value of this tool in prehospital setting, when applied by emergency medical services (EMS), and derived and validated a tool adapted to the prehospital setting in order to determine if it could assist with decisions regarding conveyance to a hospital. METHODS: In 2017, EMS personnel prospectively determined the HEART Score, including point-of-care (POC) troponin measurements, in patients presenting with chest pain, in the north of the Netherlands. The primary endpoint was a major adverse cardiac event (MACE), consisting of acute myocardial infarction or death, within 3 days. The components of the HEART Score were evaluated for their discriminatory value, cut-offs were calibrated for the prehospital setting and sex was substituted for cardiac risk factors to develop a prehospital HEART (preHEART) Score. This score was validated in an independent prospective cohort of 435 patients in 2018. RESULTS: Among 1208 patients prospectively recruited in the first cohort, 123 patients (10.2%) developed a MACE. The HEART Score had a negative predictive value (NPV) of 98.4% (96.4-99.3), a positive predictive value (PPV) of 35.5% (31.8-39.3) and an area under the receiver operating characteristic curve (AUC) of 0.81 (0.78-0.85). The preHEART Score had an NPV of 99.3% (98.1-99.8), a PPV of 49.4% (42.0-56.9) and an AUC of 0.85 (0.82-0.88), outperforming the HEART Score or POC troponin measurements on their own. Similar results were found in a validation cohort. CONCLUSIONS: The HEART Score can be used in the prehospital setting to assist with conveyance decisions and choice of hospitals; however, the preHEART Score outperforms both the HEART Score and single POC troponin measurements when applied by EMS personnel in the prehospital setting

Effectiveness and safety of dabigatran versus acenocoumarol in 'real-world' patients with atrial fibrillation

Aims Randomized trials showed non-inferior or superior results of the non-vitamin-K-antagonist oral anticoagulants (NOACs) compared with warfarin. The aim of this study was to assess the effectiveness and safety of dabigatran (direct thrombin inhibitor) vs. acenocoumarol (vitamin K antagonist) in patients with atrial fibrillation (AF) in daily clinical practice. Methods and results In this observational study, we evaluated all consecutive patients who started anticoagulation because of AF in our outpatient clinic from 2010 to 2013. Data were collected from electronic patient charts. Primary outcomes were stroke or systemic embolism and major bleeding. Propensity score matching was applied to address the non-randomized design. In total, 920 consecutive AF patients were enrolled (442 dabigatran, 478 acenocoumarol), of which 2 x 383 were available for analysis after propensity score matching. Mean follow-up duration was 1.5 +/- 0.56 year. The mean calculated stroke risk according to the CHA(2)DS(2)-VASc score was 3.5%/year in dabigatran vs. 3.7%/year acenocoumarol-treated patients. The actual incidence rate of stroke or systemic embolism was 0.8%/year [95% confidence interval (CI): 0.2-2.1] vs. 1.0%/year (95% CI: 0.4-2.1), respectively. Multivariable analysis confirmed this lower but non-significant risk in dabigatran vs. acenocoumarol after adjustment for the CHA(2)DS(2)-VASc score [hazard ratio (HR)(dabigatran) = 0.72, 95% CI: 0.20-2.63, P = 0.61]. According to the HAS-BLED score, the mean calculated bleeding risk was 1.7%/year in both groups. Actual incidence rate of major bleeding was 2.1%/year (95% CI: 1.0-3.8) in the dabigatran vs. 4.3%/year (95% CI: 2.9-6.2) in acenocoumarol. This over 50% reduction remained significant after adjustment for the HAS-BLED score (HRdabigatran = 0.45, 95% CI: 0.22-0.93, P = 0.031). Conclusion In 'real-world' patients with AF, dabigatran appears to be as effective, but significantly safer than acenocoumarol

Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics

Funding Information: Researchers were funded by investment from the European Regional Development Fund (ERDF) and the European Social Fund (ESF) Convergence Programme for Cornwall and the Isles of Scilly [J.T.]; European Research Council (ERC) [grant: SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC to T.M.F., A.R.W.], [ERC Consolidator Grant, ERC-2014-CoG-648916 to V.W.V.J.], [P.R.N.]; University of Bergen, KG Jebsen and Helse Vest [P.R.N.]; Wellcome Trust Senior Investigator Awards [A.T.H. (WT098395), M.I.M. (WT098381)]; National Institute for Health Research (NIHR) Senior Investigator Award (NF-SI-0611–10219); Sir Henry Dale Fellowship (Wellcome Trust and Royal Society grant: WT104150) [R.M.F., R.N.B.]; 4-year studentship (Grant Code: WT083431MF) [R.C.R]; the European Research Council under the European Union’s Seventh Framework Programme (FP/2007– 2013)/ERC Grant Agreement (grant number 669545; Develop Obese) [D.A.L.]; US National Institute of Health (grant: R01 DK10324) [D.A.L, C.L.R]; Wellcome Trust GWAS grant (WT088806) [D.A.L] and NIHR Senior Investigator Award (NF-SI-0611–10196) [D.A.L]; Wellcome Trust Institutional Strategic Support Award (WT097835MF) [M.A.T.]; The Diabetes Research and Wellness Foundation Non-Clinical Fellowship [J.T.]; Australian National Health and Medical Research Council Early Career Fellowship (APP1104818) [N.M.W.]; Daniel B. Burke Endowed Chair for Diabetes Research [S.F.A.G.]; UK Medical Research Council Unit grants MC_UU_12013_5 [R.C.R, L.P, S.R, C.L.R, D.M.E., D.A.L.] and MC_UU_12013_4 [D.M.E.]; Medical Research Council (grant: MR/M005070/1) [M.N.W., S.E.J.]; Australian Research Council Future Fellowship (FT130101709) [D.M.E] and (FT110100548) [S.E.M.]; NIHR Oxford Biomedical Research Centre (BRC); Oak Foundation Fellowship and Novo Nordisk Foundation (12955) [B.F.]; FRQS research scholar and Clinical Scientist Award by the Canadian Diabetes Association and the Maud Menten Award from the Institute of Genetics– Canadian Institute of Health Research (CIHR) [MFH]; CIHR— Frederick Banting and Charles Best Canada Graduate Scholarships [C.A.]; FRQS [L.B.]; Netherlands Organization for Health Research and Development (ZonMw–VIDI 016.136.361) [V.W.V.J.]; National Institute on Aging (R01AG29451) [J.M.M.]; 2010–2011 PRIN funds of the University of Ferrara—Holder: Prof. Guido Barbujani, Supervisor: Prof. Chiara Scapoli—and in part sponsored by the European Foundation for the Study of Diabetes (EFSD) Albert Renold Travel Fellowships for Young Scientists, ‘5 per mille’ contribution assigned to the University of Ferrara, income tax return year 2009 and the ENGAGE Exchange and Mobility Program for ENGAGE training funds, ENGAGE project, grant agreement HEALTH-F4–2007-201413 [L.M.]; ESRC (RES-060–23-0011) [C.L.R.]; National Institute of Health Research ([S.D., M.I.M.], Senior Investigator Award (NF-SI-0611–10196) [D.A.L]); Australian NHMRC Fellowships Scheme (619667) [G.W.M]. For study-specific funding, please see Supplementary Material. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Funding to pay the Open Access publication charges for this article was provided by the Charity Open Access Fund (COAF). Funding Information: We are extremely grateful to the participants and families who contributed to all of the studies and the teams of investigators involved in each one. These include interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. This research has been conducted using the UK Biobank Resource (Application numbers 7036 and 12703). For additional study-specific acknowledgements, please see Supplementary Material. Conflict of Interest statement. D.A.L. has received support from Roche Diagnostics and Medtronic for biomarker research unrelated to the work presented here. Funding Researchers were funded by investment from the European Regional Development Fund (ERDF) and the European Social Fund (ESF) Convergence Programme for Cornwall and the Isles of Scilly [J.T.]; European Research Council (ERC) [grant: SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC to T.M.F., A.R.W.], [ERC Consolidator Grant, ERC-2014-CoG-648916 to V.W.V.J.], [P.R.N.]; University of Bergen, KG Jebsen and Helse Vest [P.R.N.]; Wellcome Trust Senior Investigator Awards [A.T.H. (WT098395), M.I.M. (WT098381)]; National Institute for Health Research (NIHR) Senior Investigator Award (NF-SI-0611-10219); Sir Henry Dale Fellowship (Wellcome Trust and Royal Society grant: WT104150) [R.M.F., R.N.B.]; 4-year studentship (Grant Code: WT083431MF) [R.C.R]; the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement (grant number 669545; Develop Obese) [D.A.L.]; US National Institute of Health (grant: R01 DK10324) [D.A.L, C.L.R]; Wellcome Trust GWAS grant (WT088806) [D.A.L] and NIHR Senior Investigator Award (NF-SI-0611-10196) [D.A.L]; Wellcome Trust Institutional Strategic Support Award (WT097835MF) [M.A.T.]; The Diabetes Research and Wellness Foundation Non-Clinical Fellowship [J.T.]; Australian National Health and Medical Research Council Early Career Fellowship (APP1104818) [N.M.W.]; Daniel B. Burke Endowed Chair for Diabetes Research [S.F.A.G.]; UK Medical Research Council Unit grants MC_UU_12013_5 [R.C.R, L.P, S.R, C.L.R, D.M.E., D.A.L.] and MC_UU_12013_4 [D.M.E.]; Medical Research Council (grant: MR/M005070/1) [M.N.W., S.E.J.]; Australian Research Council Future Fellowship (FT130101709) [D.M.E] and (FT110100548) [S.E.M.]; NIHR Oxford Biomedical Research Centre (BRC); Oak Foundation Fellowship and Novo Nordisk Foundation (12955) [B.F.]; FRQS research scholar and Clinical Scientist Award by the Canadian Diabetes Association and the Maud Menten Award from the Institute of Genetics-Canadian Institute of Health Research (CIHR) [MFH]; CIHR-Frederick Banting and Charles Best Canada Graduate Scholarships [C.A.]; FRQS [L.B.]; Netherlands Organization for Health Research and Development (ZonMw-VIDI 016.136.361) [V.W.V.J.]; National Institute on Aging (R01AG29451) [J.M.M.]; 2010-2011 PRIN funds of the University of Ferrara-Holder: Prof. Guido Barbujani, Supervisor: Prof. Chiara Scapoli-and in part sponsored by the European Foundation for the Study of Diabetes (EFSD) Albert Renold Travel Fellowships for Young Scientists, '5 per mille' contribution assigned to the University of Ferrara, income tax return year 2009 and the ENGAGE Exchange and Mobility Program for ENGAGE training funds, ENGAGE project, grant agreement HEALTH-F4-2007-201413 [L.M.]; ESRC (RES-060-23-0011) [C.L.R.]; National Institute of Health Research ([S.D., M.I.M.], Senior Investigator Award (NFSI-0611-10196) [D.A.L]); Australian NHMRC Fellowships Scheme (619667) [G.W.M]. For study-specific funding, please see Supplementary Material. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Funding to pay the Open Access publication charges for this article was provided by the Charity Open Access Fund (COAF). Publisher Copyright: © The Author(s) 2018.Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P<5 x 10(-8). In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.Peer reviewe

Quality indicators for patients with traumatic brain injury in European intensive care units

Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust

Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe

Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations