The incidence and characteristics of venous thromboembolisms in paediatric-onset inflammatory bowel disease; a prospective international cohort study based on the PIBD-SETQuality Safety Registry.

BACKGROUND & AIMS: Guidelines regarding thromboprophylaxis for venous thromboembolisms (VTE) in children with inflammatory bowel disease (IBD) are based on limited paediatric evidence. We aimed to prospectively assess the incidence of VTE in paediatric-onset IBD (PIBD), characterize PIBD patients with VTE, and identify potential IBD-related risk factors. METHODS: From October 2016 till September 2020, paediatric gastroenterologists prospectively replied to the international Safety Registry, monthly indicating whether they had observed a VTE case in a patient <19 years with IBD. IBD details (type, Paris classification, clinical and biochemical disease activity, treatment) and VTE details (type, location, treatment, outcome) were collected. To estimate the VTE incidence, participants annually reported the number of PIBD patients, data source and catchment area of their center. A systematic literature review and meta-analysis was performed to calculate the VTE incidence in the general paediatric population. RESULTS: Participation of 129 PIBD centers resulted in coverage of 24,802 PIBD patients. Twenty cases of VTE were identified (30% Crohn's disease). The VTE incidence was 3.72 [95%CI 2.27 - 5.74] per 10,000 person-years, 14-fold higher than in the general paediatric population (0.27 [95%CI 0.18-0.38], p<0.001). Cerebral sinus venous thrombosis was most frequently reported (50%). All but one patient had active IBD, 45% were using steroids and 45% hospitalized. No patient received thromboprophylaxis, whereas according to current PIBD guidelines, this was recommended in 4/20 patients. CONCLUSION: There is an increased risk of VTE in the PIBD population compared to the general paediatric population. Awareness of VTE occurrence and prevention should be extended to all PIBD patients with active disease, especially those hospitalized

Using illness scripts to teach clinical reasoning skills to medical students

Background and Objectives: Most medical students learn clinical reasoning skills informally during clinical rotations that have varying quality of supervision. We conducted a randomized controlled trial to determine if a workshop that uses "illness scripts" could improve students' clinical reasoning skills when making diagnoses of patients portrayed in written scenarios. Methods: In 2007-2008, 53 fourth-year medical students were randomly assigned to either a family medicine (intervention) or psychiatry (control) clerkship at The Chinese University of Hong Kong. Students in the intervention group participated in a 3-hour workshop on clinical reasoning that used illness scripts. The workshop was conducted with small-group teaching using a Web-based set of clinical reasoning problems, individualized feedback, and demonstration of tutors' reasoning aloud. The effectiveness of the intervention was assessed using the Diagnostic Thinking Inventory (DTI) and the measurement of individual students' performance in solving clinical reasoning problems (CRP). Results: The postintervention overall DTI scores between groups were similar (mean difference 0, 95% confidence interval [CI]= -7.4 to 7.4). However, the total scores on the CRP assessment were 14% (95% CI=8% to 21%) higher in the intervention group than in controls. Conclusion: A workshop on illness scripts may have some benefit for improving diagnostic performance in clinical reasoning problems.link_to_OA_fulltex

Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows.

MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a machine learning algorithm. We then provide optimized techniques to validate the identified miRNAs through over-expression/loss-of-function studies. Overall, these protocols apply to any field in biology where high-dimensional data are produced. For complete details on the use and execution of this protocol, please refer to Wong et al. (2021a)

2016 Consensus statement on prevention of atherosclerotic cardiovascular disease in the Hong Kong population

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Family conflict and lower morning cortisol in adolescents and adults: modulation of puberty

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Spatial and Temporal Variations in SO₂ and PM₂.₅ Levels Around Kīlauea Volcano, Hawai'i During 2007–2018

Among the hazards posed by volcanoes are the emissions of gases and particles that can affect air quality and damage agriculture and infrastructure. A recent intense episode of volcanic degassing associated with severe impacts on air quality accompanied the 2018 lower East Rift Zone (LERZ) eruption of Kīlauea volcano, Hawai'i. This resulted in a major increase in gas emission rates with respect to usual emission values for this volcano, along with a shift in the source of the dominant plume to a populated area on the lower flank of the volcano. This led to reduced air quality in downwind communities. We analyse open-access data from the permanent air quality monitoring networks operated by the Hawai'i Department of Health (HDOH) and National Park Service (NPS), and report on measurements of atmospheric sulfur dioxide (SO2) between 2007 and 2018 and PM2.5 (aerosol particulate matter with diameter <2.5 μm) between 2010 and 2018. Additional air quality data were collected through a community-operated network of low-cost PM2.5 sensors during the 2018 LERZ eruption. From 2007 to 2018 the two most significant escalations in Kīlauea's volcanic emissions were: the summit eruption that began in 2008 (Kīlauea emissions averaged 5–6 kt/day SO2 from 2008 until summit activity decreased in May 2018) and the LERZ eruption in 2018 when SO2 emission rates reached a monthly average of 200 kt/day during June. In this paper we focus on characterizing the airborne pollutants arising from the 2018 LERZ eruption and the spatial distribution and severity of volcanic air pollution events across the Island of Hawai'i. The LERZ eruption caused the most frequent and severe exceedances of the Environmental Protection Agency (EPA) PM2.5 air quality threshold (35 μg/m3 as a daily average) in Hawai'i in the period 2010–2018. In Kona, for example, the maximum 24-h-mean mass concentration of PM2.5 was recorded as 59 μg/m3 on the twenty-ninth of May 2018, which was one of eight recorded exceedances of the EPA air quality threshold during the 2018 LERZ eruption, where there had been no exceedances in the previous 8 years as measured by the HDOH and NPS networks. SO2 air pollution during the LERZ eruption was most severe in communities in the south and west of the island, as measured by selected HDOH and NPS stations in this study, with a maximum 24-h-mean mass concentration of 728 μg/m3 recorded in Ocean View (100 km west of the LERZ emission source) in May 2018. Data from the low-cost sensor network correlated well with data from the HDOH PM2.5 instruments, confirming that these low-cost sensors provide a robust means to augment reference-grade instrument networks

Ground-Based Measurements of the 2014–2015 Holuhraun Volcanic Cloud (Iceland)

The 2014–2015 Bárðarbunga fissure eruption at Holuhraun in central Iceland was distinguished by the high emission of gases, in total 9.6 Mt SO2, with almost no tephra. This work collates all ground-based measurements of this extraordinary eruption cloud made under particularly challenging conditions: remote location, optically dense cloud with high SO2 column amounts, low UV intensity, frequent clouds and precipitation, an extensive and hot lava field, developing ramparts, and high-latitude winter conditions. Semi-continuous measurements of SO2 flux with three scanning DOAS instruments were augmented by car traverses along the ring-road and along the lava. The ratios of other gases/SO2 were measured by OP-FTIR, MultiGAS, and filter packs. Ratios SO2/HCl = 30–110 and SO2/HF = 30–130 show a halogen-poor eruption cloud. Scientists on-site reported extremely minor tephra production during the eruption. OPC and filter packs showed low particle concentrations similar to non-eruption cloud conditions. Three weather radars detected a droplet-rich eruption cloud. Top of eruption cloud heights of 0.3–5.5 km agl were measured with ground- and aircraft-based visual observations, web camera and NicAIR II infrared images, triangulation of scanning DOAS instruments, and the location of SO2 peaks measured by DOAS traverses. Cloud height and emission rate measurements were critical for initializing gas dispersal simulations for hazard forecasting

GRADE Guidelines 30: the GRADE approach to assessing the certainty of modeled evidence—An overview in the context of health decision-making

Objectives: The objective of the study is to present the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) conceptual approach to the assessment of certainty of evidence from modeling studies (i.e., certainty associated with model outputs). / Study Design and Setting: Expert consultations and an international multidisciplinary workshop informed development of a conceptual approach to assessing the certainty of evidence from models within the context of systematic reviews, health technology assessments, and health care decisions. The discussions also clarified selected concepts and terminology used in the GRADE approach and by the modeling community. Feedback from experts in a broad range of modeling and health care disciplines addressed the content validity of the approach. / Results: Workshop participants agreed that the domains determining the certainty of evidence previously identified in the GRADE approach (risk of bias, indirectness, inconsistency, imprecision, reporting bias, magnitude of an effect, dose–response relation, and the direction of residual confounding) also apply when assessing the certainty of evidence from models. The assessment depends on the nature of model inputs and the model itself and on whether one is evaluating evidence from a single model or multiple models. We propose a framework for selecting the best available evidence from models: 1) developing de novo, a model specific to the situation of interest, 2) identifying an existing model, the outputs of which provide the highest certainty evidence for the situation of interest, either “off-the-shelf” or after adaptation, and 3) using outputs from multiple models. We also present a summary of preferred terminology to facilitate communication among modeling and health care disciplines. / Conclusion: This conceptual GRADE approach provides a framework for using evidence from models in health decision-making and the assessment of certainty of evidence from a model or models. The GRADE Working Group and the modeling community are currently developing the detailed methods and related guidance for assessing specific domains determining the certainty of evidence from models across health care–related disciplines (e.g., therapeutic decision-making, toxicology, environmental health, and health economics)

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration