The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Shilu Tong - One of the best experts on this subject based on the ideXlab platform.
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the impact of temperature on mortality in tianjin china a case Crossover Design with a distributed lag nonlinear model
Environmental Health Perspectives, 2011Co-Authors: Adrian G. Barnett, Shilu Tong, Weiwei YuAbstract:Background : Although interest in assessing the impacts of temperature on mortality has increased, few studies have used a case-Crossover Design to examine non linear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature–mortality relationship in China or on what temperature measure is the best predictor of mortality. oB jectives : Our objectives were to use a distributed lag nonlinear model (DLNM) as a part of caseCrossover Design to examine the nonlinear and distributed lag effects of temperature on mortality in Tianjin, China and to explore which temperature measure is the best predictor of mortality. Methods : We applied the DLNM to a case-Crossover Design to assess the nonlinear and delayed effects of temperatures (maximum, mean , and minimum) on deaths (nonaccidental, cardiopulmonary, cardiovascular, and respiratory). results : A U-shaped relationship was found consistently between temperature and mortality. Cold effects (i.e., significantly increased mortality associated with low temperatures) were delayed by 3 days and persisted for 10 days. Hot effects (i.e., significantly increased mortality associated with high temperatures) were acute and lasted for 3 days and were followed by mortality displacement for nonaccidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. conclusions : In Tianjin, extreme cold and hot temperatures increased the risk of mortality. The effects of cold last longer than the effects of heat. Combining the DLNM and the case-Crossover Design allows the case-Crossover Design to flexibly estimate the nonlinear and delayed effects of temperature (or air pollution) while controlling for season.
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The impact of temperature on mortality in Tianjin, China : a case-Crossover Design with a distributed lag non-linear model
2011Co-Authors: Yuming Guo, Adrian G. Barnett, Xiaochuan Pan, Shilu TongAbstract:Background There has been increasing interest in assessing the impacts of temperature on mortality. However, few studies have used a case–Crossover Design to examine non-linear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature-mortality relationship in China, or what temperature measure is the best predictor of mortality. Objectives To use a distributed lag non-linear model (DLNM) as a part of case–Crossover Design. To examine the non-linear and distributed lag effects of temperature on mortality in Tianjin, China. To explore which temperature measure is the best predictor of mortality; Methods: The DLNM was applied to a case¬−Crossover Design to assess the non-linear and delayed effects of temperatures (maximum, mean and minimum) on deaths (non-accidental, cardiopulmonary, cardiovascular and respiratory). Results A U-shaped relationship was consistently found between temperature and mortality. Cold effects (significantly increased mortality associated with low temperatures) were delayed by 3 days, and persisted for 10 days. Hot effects (significantly increased mortality associated with high temperatures) were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. Conclusions In Tianjin, extreme cold and hot temperatures increased the risk of mortality. Results suggest that the effects of cold last longer than the effects of heat. It is possible to combine the case−Crossover Design with DLNMs. This allows the case−Crossover Design to flexibly estimate the non-linear and delayed effects of temperature (or air pollution) whilst controlling for season.
Bo-youl Choi - One of the best experts on this subject based on the ideXlab platform.
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Risk Analysis of Aseptic Meningitis after Measles-Mumps-Rubella Vaccination in Korean Children by Using a Case-Crossover Design
American journal of epidemiology, 2003Co-Authors: Taesung Park, Bo-youl ChoiAbstract:Epidemiologic study of a vaccine’s adverse events is not easy; so many countries have no reliable data. Vaccines containing the Urabe or Hoshino strain have been withdrawn from use in several countries. However, the data are not strong enough to form the basis of a recommendation not to use specific strains. The authors used a case-Crossover Design to estimate the relative risk of aseptic meningitis in children after receiving the measles-mumps-rubella vaccine in Korea. Study subjects were hospitalized children aged 8–36 months who had aseptic meningitis in 1998. Cases were confirmed by hospital chart reviews using previously defined criteria. Through a telephone survey, the authors obtained vaccination date and place information from parents’ vaccination records. Study results showed that no significant risk was associated with the Jeryl Lynn or Rubini strain of the vaccine (relative risk = 0.6, 95% confidence interval (CI): 0.18, 1.97). For the Urabe or Hoshino strain, the relative risk was 5.5 (95% CI: 2.6, 11.8); the risk increased in the third week after vaccination (relative risk = 15.6, 95% CI: 5.9, 41.2) and was elevated until the sixth week. The case-Crossover Design was useful in confirming the risk of acute adverse events after receiving vaccines. child, hospitalized; epidemiologic research Design; infant; meningitis, aseptic; mumps vaccine; vaccines
Adrian G. Barnett - One of the best experts on this subject based on the ideXlab platform.
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the impact of temperature on mortality in tianjin china a case Crossover Design with a distributed lag nonlinear model
Environmental Health Perspectives, 2011Co-Authors: Adrian G. Barnett, Shilu Tong, Weiwei YuAbstract:Background : Although interest in assessing the impacts of temperature on mortality has increased, few studies have used a case-Crossover Design to examine non linear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature–mortality relationship in China or on what temperature measure is the best predictor of mortality. oB jectives : Our objectives were to use a distributed lag nonlinear model (DLNM) as a part of caseCrossover Design to examine the nonlinear and distributed lag effects of temperature on mortality in Tianjin, China and to explore which temperature measure is the best predictor of mortality. Methods : We applied the DLNM to a case-Crossover Design to assess the nonlinear and delayed effects of temperatures (maximum, mean , and minimum) on deaths (nonaccidental, cardiopulmonary, cardiovascular, and respiratory). results : A U-shaped relationship was found consistently between temperature and mortality. Cold effects (i.e., significantly increased mortality associated with low temperatures) were delayed by 3 days and persisted for 10 days. Hot effects (i.e., significantly increased mortality associated with high temperatures) were acute and lasted for 3 days and were followed by mortality displacement for nonaccidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. conclusions : In Tianjin, extreme cold and hot temperatures increased the risk of mortality. The effects of cold last longer than the effects of heat. Combining the DLNM and the case-Crossover Design allows the case-Crossover Design to flexibly estimate the nonlinear and delayed effects of temperature (or air pollution) while controlling for season.
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The impact of temperature on mortality in Tianjin, China : a case-Crossover Design with a distributed lag non-linear model
2011Co-Authors: Yuming Guo, Adrian G. Barnett, Xiaochuan Pan, Shilu TongAbstract:Background There has been increasing interest in assessing the impacts of temperature on mortality. However, few studies have used a case–Crossover Design to examine non-linear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature-mortality relationship in China, or what temperature measure is the best predictor of mortality. Objectives To use a distributed lag non-linear model (DLNM) as a part of case–Crossover Design. To examine the non-linear and distributed lag effects of temperature on mortality in Tianjin, China. To explore which temperature measure is the best predictor of mortality; Methods: The DLNM was applied to a case¬−Crossover Design to assess the non-linear and delayed effects of temperatures (maximum, mean and minimum) on deaths (non-accidental, cardiopulmonary, cardiovascular and respiratory). Results A U-shaped relationship was consistently found between temperature and mortality. Cold effects (significantly increased mortality associated with low temperatures) were delayed by 3 days, and persisted for 10 days. Hot effects (significantly increased mortality associated with high temperatures) were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. Conclusions In Tianjin, extreme cold and hot temperatures increased the risk of mortality. Results suggest that the effects of cold last longer than the effects of heat. It is possible to combine the case−Crossover Design with DLNMs. This allows the case−Crossover Design to flexibly estimate the non-linear and delayed effects of temperature (or air pollution) whilst controlling for season.
C. P. Farrington - One of the best experts on this subject based on the ideXlab platform.
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RE: “RISK ANALYSIS OF ASEPTIC MENINGITIS AFTER MEASLES-MUMPS-RUBELLA VACCINATION IN KOREAN CHILDREN BY USING A CASE-Crossover Design”
American journal of epidemiology, 2004Co-Authors: C. P. FarringtonAbstract:Ki et al. used a case-Crossover Design to evaluate the relative risk of aseptic meningitis after measles-mumps-rubella vaccination. Although their results are broadly in line with those of others on the same topic, the case-Crossover Design cannot generally be recommended for investigating associations between adverse events and childhood immunizations because it requires the probability of exposure (i.e., vaccination) to be constant over time. This requirement is certainly not met by childhood immunizations administered according to highly age-dependent schedules. Measles-mumps-rubella vaccines, for example, are typically given at 12–15 months of age.
Knut Hagen - One of the best experts on this subject based on the ideXlab platform.
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The Crossover Design for migraine preventives: an analyses of four randomized placebo-controlled trials.
The journal of headache and pain, 2019Co-Authors: Astrid Bjørke Jenssen, Lars Jacob Stovner, Erling Tronvik, Trond Sand, Grethe Helde, Gøril Bruvik Gravdahl, Knut HagenAbstract:To evaluate the Crossover Design in migraine preventive treatment trials by assessing dropout rate, and potential period and carryover effect in four placebo-controlled randomized controlled trials (RCTs). In order to increase statistical power, the study combined data from four different RCTs performed from 1998 to 2015 at St. Olavs Hospital, Norway. Among 264 randomized patients, 120 received placebo treatment before and 144 after active treatment. Only 26 (10%) dropped out during the follow-up period of 30–48 weeks, the majority (n = 19) in the first 12 weeks. No period effect was found, since the treatment sequence did not influence the responder rate after placebo treatment, being respectively for migraine 30.5% vs. 27.4% (p = 0.59) and for headache 25.0% vs. 24.8% (p = 0.97, Chi-square test) when placebo occurred early or late. Furthermore, no carryover effect was identified, since the treatment sequence did not influence the treatment effect (difference between placebo and active treatment). There was no significant difference between those who received active treatment first and those who received placebo first with respect to change in number of days per 4 week of headache (− 0.9 vs. -1.3, p = 0.46) and migraine (− 1.2 vs. -0.9, p = 0.35, Student’s t-test). Summary data from four Crossover trials evaluating preventive treatment in adult migraine showed that few dropped out after the first period. No period or carryover effect was found. RCT studies with Crossover Design can be recommended as an efficient and cost-saving way to evaluate potential new preventive medicines for migraine in adults.