54 datasets found
  1. f

    Table_1_Risk Factors for Poor Outcomes of Diabetes Patients With COVID-19: A...

    • frontiersin.figshare.com
    docx
    Updated Jun 1, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Nan Zhang; Cheng Wang; Feng Zhu; Hong Mao; Peng Bai; Lu-Lu Chen; Tianshu Zeng; Miao-Miao Peng; Kang Li Qiu; Yixuan Wang; Muqing Yu; Shuyun Xu; Jianping Zhao; Na Li; Min Zhou (2023). Table_1_Risk Factors for Poor Outcomes of Diabetes Patients With COVID-19: A Single-Center, Retrospective Study in Early Outbreak in China.DOCX [Dataset]. http://doi.org/10.3389/fendo.2020.571037.s001
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers
    Authors
    Nan Zhang; Cheng Wang; Feng Zhu; Hong Mao; Peng Bai; Lu-Lu Chen; Tianshu Zeng; Miao-Miao Peng; Kang Li Qiu; Yixuan Wang; Muqing Yu; Shuyun Xu; Jianping Zhao; Na Li; Min Zhou
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Background: Diabetes has been found to increase severity and mortality under the current pandemic of coronavirus disease of 2019 (COVID-19). Up to date, the clinical characteristics of diabetes patients with COVID-19 and the risk factors for poor clinical outcomes are not clearly understood.Methods: The study was retrospectively carried out on enrolled diabetes patients with laboratory confirmed COVID-19 infection from a designated medical center for COVID-19 from January 25th, 2020 to February 14th, 2020 in Wuhan, China. The medical record was collected and reviewed. Univariate and multivariate analyses were performed to assess the risk factors associated with the severe events which were defined as a composite endpoint of admission to intensive care unit, the use of mechanical ventilation, or death.Results: A total of 52 diabetes patients with COVID-19 were finally included in the study. 21 (40.4%) patients had developed severe events in 27.50 (IQR 12.25–35.75) days follow-up, 15 (28.8%) patients experienced life-threatening complications and 8 patients died with a recorded mortality rate of 15.4%. Only 13 patients (41.9%) were in optimal glycemic control with HbA1c value of

  2. Share of U.S. COVID-19 patients who died from Jan-May, 2020, by health...

    • statista.com
    Updated Jul 27, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2022). Share of U.S. COVID-19 patients who died from Jan-May, 2020, by health condition [Dataset]. https://www.statista.com/statistics/1127644/covid-19-mortality-by-age-and-health-condition-us/
    Explore at:
    Dataset updated
    Jul 27, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 22, 2020 - May 30, 2020
    Area covered
    United States
    Description

    It was estimated that around 20 percent of those with underlying health conditions who had COVID-19 in the United States from January 22 to May 30, 2020 died from the disease, compared to just 2 percent of COVID-patients without underlying health conditions. Underlying health conditions such as cardiovascular disease, chronic lung disease, or diabetes greatly increase the chance of death due to COVID-19. This statistic shows the percentage of people in the U.S. who had COVID-19 from January 22 to May 30, 2020 with and without underlying health conditions who died, by age.

    For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  3. f

    Table 1_A multicenter, real-world cohort study: effectiveness and safety of...

    • frontiersin.figshare.com
    xlsx
    Updated Feb 19, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yongjian Zhou; Zecheng Yang; Shixi Zhang; Donghua Zhang; Hong Luo; Di Zhu; Guangming Li; Mengzhao Yang; Xiaobo Hu; Guowu Qian; Guotao Li; Ling Wang; Silin Li; Zujiang Yu; Zhigang Ren (2025). Table 1_A multicenter, real-world cohort study: effectiveness and safety of Azvudine in hospitalized COVID-19 patients with pre-existing diabetes.xlsx [Dataset]. http://doi.org/10.3389/fendo.2025.1467303.s001
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Frontiers
    Authors
    Yongjian Zhou; Zecheng Yang; Shixi Zhang; Donghua Zhang; Hong Luo; Di Zhu; Guangming Li; Mengzhao Yang; Xiaobo Hu; Guowu Qian; Guotao Li; Ling Wang; Silin Li; Zujiang Yu; Zhigang Ren
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    IntroductionDuring the Omicron infection wave, diabetic patients are susceptible to COVID-19, which is linked to a poor prognosis. However, research on the real-world effectiveness and safety of Azvudine, a common medication for COVID-19, is insufficient in those with pre-existing diabetes.MethodsIn this retrospective study, we included 32,864 hospitalized COVID-19 patients from 9 hospitals in Henan Province. Diabetic patients were screened and divided into the Azvudine group and the control group, via 1:1 propensity score matching. The primary outcome was all-cause mortality, and the secondary outcome was composite disease progression. Laboratory abnormal results were used for safety evaluation.ResultsA total of 1,417 patients receiving Azvudine and 1,417 patients receiving standard treatment were ultimately included. Kaplan−Meier curves suggested that all-cause mortality (P = 0.0026) was significantly lower in the Azvudine group than in the control group, but composite disease progression did not significantly differ (P = 0.1). Cox regression models revealed Azvudine treatment could reduce 26% risk of all-cause mortality (95% CI: 0.583-0.942, P = 0.015) versus controls, and not reduce the risk of composite disease progression (HR: 0.91, 95% CI: 0.750-1.109, P = 0.355). The results of subgroup analysis and three sensitivity analyses were consistent with the previous findings. Safety analysis revealed that the incidence rates of most adverse events were similar between the two groups.ConclusionIn this study, Azvudine demonstrated good efficacy in COVID-19 patients with diabetes, with a lower all-cause mortality rate. Additionally, the safety was favorable. This study may provide a new strategy for the antiviral management of COVID-19 patients with diabetes.

  4. Share of U.S. COVID-19 patients who died from Jan. 22-May 30, 2020, by age

    • statista.com
    Updated Jul 27, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2022). Share of U.S. COVID-19 patients who died from Jan. 22-May 30, 2020, by age [Dataset]. https://www.statista.com/statistics/1127639/covid-19-mortality-by-age-us/
    Explore at:
    Dataset updated
    Jul 27, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 22, 2020 - May 30, 2020
    Area covered
    United States
    Description

    It was estimated that around 30 percent of those aged 80 years and older who had COVID-19 in the United States from January 22 to May 30, 2020 died from the disease. Deaths due to COVID-19 are much higher among those with underlying health conditions such as cardiovascular disease, chronic lung disease, or diabetes. This statistic shows the percentage of people in the U.S. who had COVID-19 from January 22 to May 30, 2020 who died, by age.

    For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  5. Share of U.S. COVID-19 patients who died from Jan 22-May 30, 2020, by gender...

    • statista.com
    Updated Jun 24, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2020). Share of U.S. COVID-19 patients who died from Jan 22-May 30, 2020, by gender [Dataset]. https://www.statista.com/statistics/1127634/covid-19-mortality-by-gender-us/
    Explore at:
    Dataset updated
    Jun 24, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 22, 2020 - May 30, 2020
    Area covered
    United States
    Description

    It was estimated that around 6 percent of males and 4.8 percent of females who had COVID-19 in the United States from January 22 to May 30, 2020 died from the disease. Deaths due to COVID-19 are much higher among those with underlying health conditions such as cardiovascular disease, chronic lung disease, or diabetes. This statistic shows the percentage of people in the U.S. who had COVID-19 from January 22 to May 30, 2020 who died, by gender.

    For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  6. H

    Determinants of COVID-19 Mortality in Southeast Asia Region (2020 - 2022)...

    • dataverse.harvard.edu
    Updated Jun 17, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Nlandu Roger Ngatu (2024). Determinants of COVID-19 Mortality in Southeast Asia Region (2020 - 2022) "Replication Data" [Dataset]. http://doi.org/10.7910/DVN/FIVJAY
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 17, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Nlandu Roger Ngatu
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Asia, South East Asia
    Description

    The dataset contains COVID-19 epidemiological data, including cumulative cases and deaths, number of excess deaths associated with COVID-19, log-transformed prevalence of cardiometabolic risk factors and disorders (smoking, hypertension, diabetes), calculated COVID-19 case-fatality rate, as well as country-level sociodemographics. Ten out of 11 countries of the region are included; one country was excluded due to lack of a number of sociodemographic and health statistics.

  7. f

    Supplementary_Table_2_Association between mortality and cardiovascular...

    • figshare.com
    xlsx
    Updated Jun 8, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Gerardo R. Padilla-Rivas; Juan Luis Delgado-Gallegos; Gerardo Garza-Treviño; Kame A. Galan-Huerta; Zuca G-Buentello; Jorge A. Roacho-Pérez; Michelle Giovana Santoyo-Suarez; Hector Franco-Villareal; Ahidée Leyva-Lopez; Ana E. Estrada-Rodriguez; Jorge E. Moreno-Cuevas; Javier Ramos-Jimenez; Ana M. Rivas-Estrilla; Elsa N. Garza-Treviño; Jose Francisco Islas (2023). Supplementary_Table_2_Association between mortality and cardiovascular diseases in the vulnerable Mexican population: A cross-sectional retrospective study of the COVID-19 pandemic.XLSX [Dataset]. http://doi.org/10.3389/fpubh.2022.1008565.s002
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset provided by
    Frontiers
    Authors
    Gerardo R. Padilla-Rivas; Juan Luis Delgado-Gallegos; Gerardo Garza-Treviño; Kame A. Galan-Huerta; Zuca G-Buentello; Jorge A. Roacho-Pérez; Michelle Giovana Santoyo-Suarez; Hector Franco-Villareal; Ahidée Leyva-Lopez; Ana E. Estrada-Rodriguez; Jorge E. Moreno-Cuevas; Javier Ramos-Jimenez; Ana M. Rivas-Estrilla; Elsa N. Garza-Treviño; Jose Francisco Islas
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Cardiovascular diseases (CVDs) continue to be the leading cause of death worldwide. Over the past couple of years and with the surge of the COVID-19 pandemic, mortality from CVDs has been slightly overshadowed by those due to COVID-19, although it was during the peak of the pandemic. In the present study, patients with CVDs (CVDs; n = 41,883) were analyzed to determine which comorbidities had the largest impact on overall patient mortality due to their association with both diseases (n = 3,637). Obesity, hypertension, and diabetes worsen health in patients diagnosed positive for COVID-19. Hence, they were included in the overview of all patients with CVD. Our findings showed that 1,697 deaths were attributable to diabetes (p < 0.001) and 987 deaths to obesity (p < 0.001). Lastly, 2,499 deaths were attributable to hypertension (p < 0.001). Using logistic regression modeling, we found that diabetes (OR: 1.744, p < 0.001) and hypertension (OR: 2.179, p < 0.001) significantly affected the mortality rate of patients. Hence, having a CVD diagnosis, with hypertension and/or diabetes, seems to increase the likelihood of complications, leading to death in patients diagnosed positive for COVID-19.

  8. Most common cause of death in Mexico 2023

    • statista.com
    Updated Feb 20, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Most common cause of death in Mexico 2023 [Dataset]. https://www.statista.com/statistics/960030/mexico-causes-death/
    Explore at:
    Dataset updated
    Feb 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Mexico
    Description

    Heart conditions were the most common causes of death in Mexico in 2023. During that period, more than 189,000 people died in the North American country as a result from said conditions. Diabetes mellitus ranked second, with over 110,000 deaths registered that year. Obesity in MexicoObesity and being overweight can worsen many risk factors for developing heart conditions, prediabetes, type 2 diabetes, and gestational diabetes, which in the case of a COVID-19 infection can lead to a severe course of the disease. In 2020, Mexico was reported as having one of the largest overweight and/or obese population in Latin America, with 66 percent of people in the country having a body mass index higher than 25. In 2022, obesity was announced as being one of the most common illnesses experienced in Mexico, with over 821,000 cases estimated. In a decade from now, it is predicted that about 6.6 million children in Mexico will suffer from obesity. If estimations are correct, this North American country will belong to the world’s top 10 countries with the most obese children in 2030. Physical activity in MexicoIt is not only a matter of food intake. A 2023 survey found, for instance, that only 39.8 percent of Mexican population practiced sports and physical activities in their free time, a figure that has decreased in comparison to 2013. Less than 15 percent of the physically active Mexicans practice sports for fun. However, the vast majority were motivated by health reasons.

  9. Most common comorbidities in COVID-19 deceased patients in Italy 2022

    • statista.com
    Updated Sep 1, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2023). Most common comorbidities in COVID-19 deceased patients in Italy 2022 [Dataset]. https://www.statista.com/statistics/1110949/common-comorbidities-in-covid-19-deceased-patients-in-italy/
    Explore at:
    Dataset updated
    Sep 1, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 10, 2022
    Area covered
    Italy
    Description

    An in depth study on patients admitted to hospital and later deceased with the coronavirus (COVID-19) infection revealed that the majority of cases showed one or more comorbidities. As the chart shows, hypertension was the most common pre-existing health condition, detected in 65.8 percent of patients who died after contracting the virus. Type 2-diabetes, ischemic heart disease, and atrial fibrillation were also among the most common comorbidities in COVID-19 patients who lost their lives. More statistics and facts about the virus in Italy are available here. For a global overview visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

  10. Rate of U.S. COVID-19 cases as of March 10, 2023, by state

    • statista.com
    Updated May 15, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Rate of U.S. COVID-19 cases as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1109004/coronavirus-covid19-cases-rate-us-americans-by-state/
    Explore at:
    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of March 10, 2023, the state with the highest rate of COVID-19 cases was Rhode Island followed by Alaska. Around 103.9 million cases have been reported across the United States, with the states of California, Texas, and Florida reporting the highest numbers of infections.

    From an epidemic to a pandemic The World Health Organization declared the COVID-19 outbreak as a pandemic on March 11, 2020. The term pandemic refers to multiple outbreaks of an infectious illness threatening multiple parts of the world at the same time; when the transmission is this widespread, it can no longer be traced back to the country where it originated. The number of COVID-19 cases worldwide is roughly 683 million, and it has affected almost every country in the world.

    The symptoms and those who are most at risk Most people who contract the virus will suffer only mild symptoms, such as a cough, a cold, or a high temperature. However, in more severe cases, the infection can cause breathing difficulties and even pneumonia. Those at higher risk include older persons and people with pre-existing medical conditions, including diabetes, heart disease, and lung disease. Those aged 85 years and older have accounted for around 27 percent of all COVID deaths in the United States, although this age group makes up just two percent of the total population

  11. c

    Global Specific Antiviral Drugs for COVID-19 market size is USD XX million...

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated Jan 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Cognitive Market Research (2025). Global Specific Antiviral Drugs for COVID-19 market size is USD XX million in 2024. [Dataset]. https://www.cognitivemarketresearch.com/specific-antiviral-drugs-for-covid-19-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jan 15, 2025
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    According to Cognitive Market Research, the global Specific Antiviral Drugs for COVID-19 market size is USD XX million in 2024 and will expand at a compound annual growth rate (CAGR) of 5.00% from 2024 to 2031. North America held the major market share of more than 40% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.2% from 2024 to 2031. Europe accounted for a share of over 30% of the global revenue with a market size of USD XX million. Asia Pacific held the market share of around 23% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.0% from 2024 to 2031. Latin America market share of more than 5% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.4% from 2024 to 2031. Middle East and Africa held the major market share of around 2% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.7% from 2024 to 2031. The Injection segment held the highest Specific Antiviral Drugs for COVID-19 market revenue share in 2024. Market Dynamics of Specific Antiviral Drugs for COVID-19 Market Key Drivers for Specific Antiviral Drugs for COVID-19 Market Urgent need for effective treatments to Increase the Demand Globally The emergence of the COVID-19 pandemic has underscored an urgent necessity for efficacious treatments. In the United States, mortality rates surged by 19% from 2019 to 2020 following the pandemic's onset in March 2020 — marking the most significant spike in deaths in a century. This uptick translated to a staggering 19% rise (535,191) in deaths, from 2,854,838 to 3,390,029. With the virus persisting globally, there exists a critical market demand for pharmaceutical solutions capable of directly combating the virus, mitigating symptoms, and ameliorating disease severity. Rising prevalence of chronic diseases to Propel Market Growth Individuals with underlying chronic conditions, such as diabetes, hypertension, heart disease, or respiratory disorders, face an increased risk of severe complications if they contract COVID-19. According to the CDC, 90% of the nation’s $3.8 trillion per year healthcare costs are linked to individuals with chronic diseases and mental health conditions. In 2017, the total costs of diagnosed diabetes in the United States amounted to $327 billion, including $237 billion in direct medical costs and $90 billion in lost economic productivity. Cardiovascular disease, which accounts for one in three deaths in the United States, underscores the urgent need for effective treatments, including specific antiviral drugs, to mitigate the severity of COVID-19 symptoms and enhance outcomes for this vulnerable population. Restraint Factor for the Specific Antiviral Drugs for COVID-19 Market Stringent regulatory requirements and high cost of pharmaceutical development to Limit the Sales Stringent regulatory criteria and protracted approval processes may postpone the introduction of novel antiviral medications into the market. The thorough assessment of safety and efficacy data by regulatory bodies like the FDA can prolong the time required for market entry, influencing the accessibility of specific antiviral treatments. Moreover, the elevated expenses associated with pharmaceutical development, manufacturing, and distribution may lead to costly antiviral drugs, restricting access for populations in low-income countries or regions with insufficient healthcare infrastructure. Concerns regarding affordability could trigger pricing pressures and reimbursement obstacles, impacting the adoption and profitability of these medications. Impact of Covid-19 on the Specific Antiviral Drugs for COVID-19 Market The critical necessity for efficacious treatments against COVID-19 has sparked a heightened demand for targeted antiviral medications. Given the swift global dissemination of the virus and subsequent surges in infections, there is an urgent requirement for pharmaceutical solutions capable of directly combating the virus and mitigating associated symptoms. The pandemic has catalyzed unparalleled levels of investment and cooperation in research and development endeavors focused on discovering effective antiviral treatments for COVID-19. Pharmaceutical firms, academic entities, and governments across the globe have pri...

  12. Logistic regression analysis on the relationships of comorbidities with...

    • plos.figshare.com
    xls
    Updated Jun 11, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Simona Iftimie; Ana F. López-Azcona; Immaculada Vallverdú; Salvador Hernández-Flix; Gabriel de Febrer; Sandra Parra; Anna Hernández-Aguilera; Francesc Riu; Jorge Joven; Natàlia Andreychuk; Gerard Baiges-Gaya; Frederic Ballester; Marc Benavent; José Burdeos; Alba Català; Èric Castañé; Helena Castañé; Josep Colom; Mireia Feliu; Xavier Gabaldó; Diana Garrido; Pedro Garrido; Joan Gil; Paloma Guelbenzu; Carolina Lozano; Francesc Marimon; Pedro Pardo; Isabel Pujol; Antoni Rabassa; Laia Revuelta; Marta Ríos; Neus Rius-Gordillo; Elisabet Rodríguez-Tomàs; Wojciech Rojewski; Esther Roquer-Fanlo; Noèlia Sabaté; Anna Teixidó; Carlos Vasco; Jordi Camps; Antoni Castro (2023). Logistic regression analysis on the relationships of comorbidities with deaths for patients from the second wave of COVID-19. [Dataset]. http://doi.org/10.1371/journal.pone.0248029.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 11, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Simona Iftimie; Ana F. López-Azcona; Immaculada Vallverdú; Salvador Hernández-Flix; Gabriel de Febrer; Sandra Parra; Anna Hernández-Aguilera; Francesc Riu; Jorge Joven; Natàlia Andreychuk; Gerard Baiges-Gaya; Frederic Ballester; Marc Benavent; José Burdeos; Alba Català; Èric Castañé; Helena Castañé; Josep Colom; Mireia Feliu; Xavier Gabaldó; Diana Garrido; Pedro Garrido; Joan Gil; Paloma Guelbenzu; Carolina Lozano; Francesc Marimon; Pedro Pardo; Isabel Pujol; Antoni Rabassa; Laia Revuelta; Marta Ríos; Neus Rius-Gordillo; Elisabet Rodríguez-Tomàs; Wojciech Rojewski; Esther Roquer-Fanlo; Noèlia Sabaté; Anna Teixidó; Carlos Vasco; Jordi Camps; Antoni Castro
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Logistic regression analysis on the relationships of comorbidities with deaths for patients from the second wave of COVID-19.

  13. Leading causes of death in Canada in 2023

    • statista.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista, Leading causes of death in Canada in 2023 [Dataset]. https://www.statista.com/statistics/437880/proportion-of-deaths-in-canada-by-disease/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Canada
    Description

    In 2023, the leading causes of death in Canada were malignant neoplasms (cancer) and diseases of the heart. Together, these diseases accounted for around 44 percent of all deaths in Canada that year. COVID-19 was the sixth leading cause of death in Canada in 2023 with 2.4 percent of deaths. The leading causes of death in Canada In 2023, around 84,629 people in Canada died from cancer, making it by far the leading cause of death in the country. In comparison, an estimated 57,890 people died from diseases of the heart, while 20,597 died from accidents. In 2023, the death rate for diabetes mellitus was 18.1 per 100,000 population, making it the seventh leading cause of death. Diabetes is a growing problem in Canada, with around eight percent of the population diagnosed with the disease as of 2023. What is the deadliest form of cancer in Canada? In Canada, lung and bronchus cancer account for the largest share of cancer deaths, followed by colorectal cancer. In 2023, the death rate for lung and bronchus cancer was 41.8 per 100,000 population, compared to 19.6 deaths per 100,000 population for colorectal cancer. However, although lung and bronchus cancer are the deadliest cancers for both men and women in Canada, breast cancer is the second-deadliest cancer among women, accounting for 13.4 percent of all cancer deaths. Colorectal cancer is the second most deadly cancer among men in Canada followed by prostate cancer. In 2023, colorectal cancer accounted for around 11.2 percent of all cancer deaths among men in Canada, while prostate cancer was responsible for 10.5 percent of such deaths.

  14. Leading causes of death, total population, by age group

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +2more
    Updated Feb 19, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Government of Canada, Statistics Canada (2025). Leading causes of death, total population, by age group [Dataset]. http://doi.org/10.25318/1310039401-eng
    Explore at:
    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

  15. Where should we focus on improving life expectancy?

    • coronavirus-disasterresponse.hub.arcgis.com
    • coronavirus-resources.esri.com
    • +1more
    Updated Mar 26, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Urban Observatory by Esri (2020). Where should we focus on improving life expectancy? [Dataset]. https://coronavirus-disasterresponse.hub.arcgis.com/maps/af2472aaa9e94814b06e950db53f18f3
    Explore at:
    Dataset updated
    Mar 26, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    This multi-scale map shows life expectancy - a widely-used measure of health and mortality. From the County Health Rankings page about Life Expectancy:"Life Expectancy is an AverageLife Expectancy measures the average number of years from birth a person can expect to live, according to the current mortality experience (age-specific death rates) of the population. Life Expectancy takes into account the number of deaths in a given time period and the average number of people at risk of dying during that period, allowing us to compare data across counties with different population sizes.Life Expectancy is Age-AdjustedAge is a non-modifiable risk factor, and as age increases, poor health outcomes are more likely. Life Expectancy is age-adjusted in order to fairly compare counties with differing age structures.What Deaths Count Toward Life Expectancy?Deaths are counted in the county where the individual lived. So, even if an individual dies in a car crash on the other side of the state, that death is attributed to his/her home county.Some Data are SuppressedA missing value is reported for counties with fewer than 5,000 population-years-at-risk in the time frame.Measure LimitationsLife Expectancy includes mortality of all age groups in a population instead of focusing just on premature deaths and thus can be dominated by deaths of the elderly.[1] This could draw attention to areas with higher mortality rates among the oldest segment of the population, where there may be little that can be done to change chronic health problems that have developed over many years. However, this captures the burden of chronic disease in a population better than premature death measures.[2]Furthermore, the calculation of life expectancy is complex and not easy to communicate. Methodologically, it can produce misleading results caused by hidden differences in age structure, is sensitive to infant and child mortality, and tends to be overestimated in small populations."Breakdown by race/ethnicity in pop-up: (This map has been updated with new data, so figures may vary from those in this image.)There are many factors that play into life expectancy: rates of noncommunicable diseases such as cancer, diabetes, and obesity, prevalence of tobacco use, prevalence of domestic violence, and many more.Proven strategies to improve life expectancy and health in general A database of dozens of strategies can be found at County Health Rankings' What Works for Health site, sorted by Health Behaviors, Clinical Care, Social & Economic Factors, and Physical Environment. Policies and Programs listed here have been evaluated as to their effectiveness. For example, consumer-directed health plans received an evidence rating of "mixed evidence" whereas cultural competence training for health care professionals received a rating of "scientifically supported." Data from County Health Rankings (layer referenced below), available for nation, state, and county, and available in ArcGIS Living Atlas of the World.

  16. f

    Stepwiseb'*' multiple regression for covid-19 cases and deaths.

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Claudio Violato; Emilio Mauro Violato; Efrem Mauro Violato (2023). Stepwiseb'*' multiple regression for covid-19 cases and deaths. [Dataset]. http://doi.org/10.1371/journal.pone.0258205.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Claudio Violato; Emilio Mauro Violato; Efrem Mauro Violato
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Stepwiseb'*' multiple regression for covid-19 cases and deaths.

  17. Health conditions causing the largest number of deaths in Italy 2022

    • statista.com
    Updated Feb 26, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Health conditions causing the largest number of deaths in Italy 2022 [Dataset]. https://www.statista.com/statistics/1114252/health-conditions-causing-the-largest-number-of-deaths-in-italy/
    Explore at:
    Dataset updated
    Feb 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Italy
    Description

    In Italy, approximately 722,000 deaths were registered in 2022. According to the data, ischemic heart diseases were the most common cause of death in the country, with 59,052 cases registered, closely followed by cerebrovascular diseases. COVID-19 was the third illness causing the largest number of deaths in Italy. COVID-19 death comorbidities Most patients admitted to the hospital and later deceased with the coronavirus (COVID-19) infection showed one or more comorbidities. Hypertension was the most common pre-existing health condition, detected in 65.8 percent of patients who died after contracting the virus. Type 2-diabetes, ischemic heart disease, and atrial fibrillation were also among the most common comorbidities in COVID-19 patients who lost their lives. Cancer deaths The number of people who died from a tumor in Italy decreased constantly between 2006 and 2021. Indeed, the rate of deaths due to cancer among Italians dropped from 28.7 deaths per 10,000 inhabitants in 2006 to 23.3 in 2021. The Italian region with the highest cancer mortality rate was Campania, followed by Sardinia, and Sicily.

  18. Total number of U.S. COVID-19 cases as of March 10, 2023, by state

    • statista.com
    Updated Mar 28, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2023). Total number of U.S. COVID-19 cases as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1102807/coronavirus-covid19-cases-number-us-americans-by-state/
    Explore at:
    Dataset updated
    Mar 28, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of March 10, 2023, the state with the highest number of COVID-19 cases was California. Almost 104 million cases have been reported across the United States, with the states of California, Texas, and Florida reporting the highest numbers.

    From an epidemic to a pandemic The World Health Organization declared the COVID-19 outbreak a pandemic on March 11, 2020. The term pandemic refers to multiple outbreaks of an infectious illness threatening multiple parts of the world at the same time. When the transmission is this widespread, it can no longer be traced back to the country where it originated. The number of COVID-19 cases worldwide has now reached over 669 million.

    The symptoms and those who are most at risk Most people who contract the virus will suffer only mild symptoms, such as a cough, a cold, or a high temperature. However, in more severe cases, the infection can cause breathing difficulties and even pneumonia. Those at higher risk include older persons and people with pre-existing medical conditions, including diabetes, heart disease, and lung disease. People aged 85 years and older have accounted for around 27 percent of all COVID-19 deaths in the United States, although this age group makes up just two percent of the U.S. population

  19. Share of comorbidities of hospitalized patients infected by COVID-19 in...

    • statista.com
    Updated Sep 29, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2021). Share of comorbidities of hospitalized patients infected by COVID-19 in Belgium 2020 [Dataset]. https://www.statista.com/statistics/1114522/comorbidities-of-coronavirus-hospital-patients-in-belgium/
    Explore at:
    Dataset updated
    Sep 29, 2021
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 30, 2020
    Area covered
    Belgium
    Description

    At the time of arrival in the hospital, nearly 40 percent of Belgian patients admitted due to the coronavirus had high blood pressure and one out of three had cardiovascular diseases. On the other hand, roughly 20 percent of patients infected by COVID-19 suffered from diabetes at the time of hospitalization. On April 30, 2020, over 3,000 patiens who have been tested positive to the coronavirus were hospitalized in Belgium.

  20. f

    Relevant data.

    • plos.figshare.com
    xlsx
    Updated Oct 31, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Shuhei Ideguchi; Kazuya Miyagi; Wakaki Kami; Daisuke Tasato; Futoshi Higa; Noriyuki Maeshiro; Shota Nagamine; Hideta Nakamura; Takeshi Kinjo; Masashi Nakamatsu; Shusaku Haranaga; Akihiro Tokushige; Shinichiro Ueda; Jiro Fujita; Kazuko Yamamoto (2024). Relevant data. [Dataset]. http://doi.org/10.1371/journal.pone.0309808.s002
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Oct 31, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Shuhei Ideguchi; Kazuya Miyagi; Wakaki Kami; Daisuke Tasato; Futoshi Higa; Noriyuki Maeshiro; Shota Nagamine; Hideta Nakamura; Takeshi Kinjo; Masashi Nakamatsu; Shusaku Haranaga; Akihiro Tokushige; Shinichiro Ueda; Jiro Fujita; Kazuko Yamamoto
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Background and objectiveSince 2023, COVID-19 induced by SARS-CoV-2 XBB variants have been a global epidemic. The XBB variant-induced epidemic was largest in the Okinawa Prefecture among areas in Japan, and healthcare institutions have been burdened by increased COVID-19 hospitalizations. This study aimed to evaluate the clinical features of XBB variant-induced COVID-19 and risk factors for severe COVID-19.MethodsThis retrospective study included adult patients hospitalized for COVID-19 between May and July 2023 at four tertiary medical institutions in Okinawa, Japan. Patients with bacterial infection-related complications were excluded. According to oxygen supplementation and intensive care unit admission, patients were divided into two groups, mild and severe. Patient backgrounds, symptoms, and outcomes were compared between both groups, and the risk factors for severe COVID-19 were analyzed using a multivariate logistic regression model.ResultsIn total of 367 patients included, the median age was 75 years, with 18.5% classified into the severe group. The all-cause mortality rate was 4.9%. Patients in the severe group were more older, had more underlying diseases, and had a higher mortality rate (13.2%) than those in the mild group (3.0%). Multivariate logistic regression analysis showed that diabetes mellitus was an independent risk factor for severe COVID-19 (95% confidence interval [CI], 1.002–3.772), whereas bivalent omicron booster vaccination was an independent factor for less severe COVID-19 (95% CI, 0.203–0.862).ConclusionThis study implies that assessing risk factors in older adults is particularly important in the era of omicron variants.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Nan Zhang; Cheng Wang; Feng Zhu; Hong Mao; Peng Bai; Lu-Lu Chen; Tianshu Zeng; Miao-Miao Peng; Kang Li Qiu; Yixuan Wang; Muqing Yu; Shuyun Xu; Jianping Zhao; Na Li; Min Zhou (2023). Table_1_Risk Factors for Poor Outcomes of Diabetes Patients With COVID-19: A Single-Center, Retrospective Study in Early Outbreak in China.DOCX [Dataset]. http://doi.org/10.3389/fendo.2020.571037.s001

Table_1_Risk Factors for Poor Outcomes of Diabetes Patients With COVID-19: A Single-Center, Retrospective Study in Early Outbreak in China.DOCX

Related Article
Explore at:
docxAvailable download formats
Dataset updated
Jun 1, 2023
Dataset provided by
Frontiers
Authors
Nan Zhang; Cheng Wang; Feng Zhu; Hong Mao; Peng Bai; Lu-Lu Chen; Tianshu Zeng; Miao-Miao Peng; Kang Li Qiu; Yixuan Wang; Muqing Yu; Shuyun Xu; Jianping Zhao; Na Li; Min Zhou
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Background: Diabetes has been found to increase severity and mortality under the current pandemic of coronavirus disease of 2019 (COVID-19). Up to date, the clinical characteristics of diabetes patients with COVID-19 and the risk factors for poor clinical outcomes are not clearly understood.Methods: The study was retrospectively carried out on enrolled diabetes patients with laboratory confirmed COVID-19 infection from a designated medical center for COVID-19 from January 25th, 2020 to February 14th, 2020 in Wuhan, China. The medical record was collected and reviewed. Univariate and multivariate analyses were performed to assess the risk factors associated with the severe events which were defined as a composite endpoint of admission to intensive care unit, the use of mechanical ventilation, or death.Results: A total of 52 diabetes patients with COVID-19 were finally included in the study. 21 (40.4%) patients had developed severe events in 27.50 (IQR 12.25–35.75) days follow-up, 15 (28.8%) patients experienced life-threatening complications and 8 patients died with a recorded mortality rate of 15.4%. Only 13 patients (41.9%) were in optimal glycemic control with HbA1c value of

Search
Clear search
Close search
Google apps
Main menu