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    15 research outputs found

    Determinants of China’s Energy Imports: An Empirical Analysis

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    Sustained economic growth in China has triggered a surge of energy imports, especially oil imports. This paper investigates the determinants of China’s energy import demand by using cointegraiton and VECM techniques. The findings suggest that, in the long run, growth of industrial production and expansion of transport sectors affect China’s oil imports, while domestic energy output has a substitution effect. Thus, as the Chinese economy industrializes and the automotive sector expands, China’s oil imports are likely to increase. Though China’s domestic oil production has a substitution effect on imports, its growth is limited due to scarce domestic reserve and high exploration costs. It is anticipated that China will be more dependent on overseas oil supply regardless of the world oil price.Energy consumption, energy imports, China and VECM
    Research Papers in Economics

    Characteristics of patients in the individual patient data (IPD) database.

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    Characteristics of patients in the individual patient data (IPD) database.</p
    The Francis Crick Institute

    Univariate and multivariable cox regression analyses for variables associated with death for patients with individual patient data with any neurological disease, and for those with cerebrovascular events and encephalopathy<sup>1</sup><sup>,</sup><sup>2</sup><sup>,</sup><sup>3</sup>.

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    Univariate and multivariable cox regression analyses for variables associated with death for patients with individual patient data with any neurological disease, and for those with cerebrovascular events and encephalopathy1,2,3.</p
    The Francis Crick Institute

    Univariate and multivariable analyses for variables associated with poor outcome (mRS score 3–6) at discharge for patients with individual patient data with any neurological disease, and for those with cerebrovascular events and encephalopathy<sup>1</sup><sup>,</sup><sup>2</sup><sup>,</sup><sup>3</sup>.

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    Univariate and multivariable analyses for variables associated with poor outcome (mRS score 3–6) at discharge for patients with individual patient data with any neurological disease, and for those with cerebrovascular events and encephalopathy1,2,3.</p
    The Francis Crick Institute

    Outcomes—Modified Rankin scale score at discharge, mortality, and need for intensive care—For patients with individual patient data with any neurological disease, and for those with cerebrovascular events and encephalopathy.

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    Outcomes—Modified Rankin scale score at discharge, mortality, and need for intensive care—For patients with individual patient data with any neurological disease, and for those with cerebrovascular events and encephalopathy.</p
    The Francis Crick Institute

    Frequency of neurological disease subgroups in the studies contributing IPD.

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    Frequency of neurological disease subgroups in the studies contributing IPD.</p
    The Francis Crick Institute

    Time-to-event analyses for secondary outcomes for patients with COVID-19 and neurological disease in the IPD database<sup>1</sup>.

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    1. These figures show results of analyses for the whole IPD database (i.e., patients with any neurological disease diagnosis), and other than for A, the analyses use death as a competing risk. 2. A total of 1745 patients were included in this analysis. Of the 1979, 115 had no dates; 14 patients had no hospital admission date; 9 dead patients had no date of death; 88 alive patients had no discharge date; it was unknown if 8 patients were dead or alive. For time to death, individuals that were alive at discharge or last follow-up were censored. 3. This analysis uses date of hospital admission as day 0. A total of 1428 patients were included in this analysis: 404 patients had no dates; 17 had no hospital admission date; 123 (23 dead; 100 alive) patients had neither the date of admission to critical care or the date of commencement of invasive ventilation; 7 patients only had a hospital admission date, but it was unknown if they were dead or alive. For time to critical care admission, individuals who were alive at discharge or last follow-up and had not been admitted to intensive care were censored. Individuals who died without receiving critical care or invasive ventilation were treated as competing events in a competing risks analysis. 4. This analysis uses date of critical care admission as day 0. A total of 486 patients who were admitted critical care were included in this analysis: 1482 patients had no date of admission to critical care; 5 dead patients had no death date; 5 alive patients had no hospital discharge date; there were no dates for 1 patient. 5. For discharge from critical care, individuals that were alive and not yet discharged at last follow-up were censored. Individuals that died after admission to intensive care were treated as competing events in a competing risks analysis. 10. For length of hospital stay, individuals that were alive and not yet discharged at last follow-up were censored. Individuals that died were treated as competing events in a competing risks analysis.</p
    The Francis Crick Institute

    PRISMA flow diagram.

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    IPD = individual patient data.</p
    The Francis Crick Institute

    Pooled proportions of all patients hospitalised with COVID-19 reported to have acute new-onset neurological disease.

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    Neurological disease = number of patients with neurological COVID-19 disease. All COVID-19 = number of patients with all COVID-19 disease hospitalised in the same centre over the same time period.</p
    The Francis Crick Institute

    Data extraction tool and case definitions.

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    (PDF)</p
    The Francis Crick Institute
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