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Big data analysis from Sweden confirms that resting heart rate in late adolescence is significantly associated with incident heart failure and all-cause mortality.

https://arctichealth.org/en/permalink/ahliterature292673
Source
Int J Cardiol. 2018 05 15; 259:220-221
Publication Type
Editorial
Comment
Date
05-15-2018
Author
Polychronis Dilaveris
Dimitrios Tousoulis
Author Affiliation
1st Department of Cardiology, Hippokration General Hospital, National and Kapodestrian University of Athens School of Medicine, Athens, Greece. Electronic address: hrodil1@yahoo.com.
Source
Int J Cardiol. 2018 05 15; 259:220-221
Date
05-15-2018
Language
English
Publication Type
Editorial
Comment
Keywords
Adolescent
Heart Failure
Heart rate
Humans
Proportional Hazards Models
Risk factors
Sweden
Notes
CommentOn: Int J Cardiol. 2018 May 15;259:109-115 PMID 29579585
PubMed ID
29579605 View in PubMed
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[Counting method for evaluation of possible premature death due to ambient air pollution].

https://arctichealth.org/en/permalink/ahliterature178764
Source
Med Tr Prom Ekol. 2004;(6):27-32
Publication Type
Article
Date
2004
Author
R V Arutiunian
V P Reshetin
V I Kazazian
Source
Med Tr Prom Ekol. 2004;(6):27-32
Date
2004
Language
Russian
Publication Type
Article
Keywords
Air Pollution - adverse effects
Cause of Death
Humans
Proportional Hazards Models
Russia
Abstract
The authors present evaluation of possible untimely death rate due to ambient air pollution in Russian cities. For evaluation, the authors used data of everyday monitoring of air pollution in 1993 and 1998, carried out by Russian Hydrometeorology Service. Findings are that 219,000-233,000 untimely deaths (or 15-17% of total annual death rate) in Russia could be caused by air pollution. The authors discuss possible factors influencing exactness of the presented evaluation.
PubMed ID
15318455 View in PubMed
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Accelerated failure time models with covariates subject to measurement error.

https://arctichealth.org/en/permalink/ahliterature164143
Source
Stat Med. 2007 Nov 20;26(26):4817-32
Publication Type
Article
Date
Nov-20-2007
Author
Wenqing He
Grace Y Yi
Juan Xiong
Author Affiliation
Department of Statistical and Actuarial Sciences, University of Western Ontario, 1151 Richmond Street North, London, Ont., Canada N6A 5B7. whe@stats.uwo.ca
Source
Stat Med. 2007 Nov 20;26(26):4817-32
Date
Nov-20-2007
Language
English
Publication Type
Article
Keywords
Bias (epidemiology)
Data Interpretation, Statistical
Humans
Models, Statistical
Ontario
Proportional Hazards Models
Survival Analysis
Abstract
It has been well known that ignoring measurement error may result in substantially biased estimates in many contexts including linear and nonlinear regressions. For survival data with measurement error in covariates there has been extensive discussion in the literature with the focus being on the Cox proportional hazards models. However, the impact of measurement error on accelerated failure time (AFT) models has received little attention, though AFT models are very useful in survival data analysis. In this paper, we discuss AFT models with error-prone covariates and study the bias induced by the naive approach of ignoring measurement error in covariates. To adjust for such a bias, we describe a simulation and extrapolation method. This method is appealing because it is simple to implement and it does not require modelling the true but error-prone covariate process that is often not observable. Asymptotic normality for the resulting estimators is established. Simulation studies are carried out to evaluate the performance of the proposed method as well as the impact of ignoring measurement error in covariates. The proposed method is applied to analyse a data set arising from the Busselton Health study (Australian J. Public Health 1994; 18:129-135).
PubMed ID
17436310 View in PubMed
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Modelling seasonal and weather dependency of cardiac arrests using the covariate order method.

https://arctichealth.org/en/permalink/ahliterature165910
Source
Stat Med. 2007 Jul 30;26(17):3315-29
Publication Type
Article
Date
Jul-30-2007
Author
Jan Terje Kvaløy
Eirik Skogvoll
Author Affiliation
Department of Mathematics and Natural Sciences, University of Stavanger, Stavanger, Norway. jan.t.kvaloy@uis.no
Source
Stat Med. 2007 Jul 30;26(17):3315-29
Date
Jul-30-2007
Language
English
Publication Type
Article
Keywords
Emergency Service, Hospital
Heart Arrest - epidemiology
Humans
Norway - epidemiology
Proportional Hazards Models
Seasons
Weather
Abstract
A data set concerning cardiac arrests treated by the Emergency Medical Service in Trondheim during a nine year period is analysed. The relationship between the occurrence of cardiac arrest and covariates related to weather and season is examined. The covariate order method is used in the analysis of the data. It is explained how this method can be extended to recurrent event data, and the practical usefulness and flexibility of the method is demonstrated in these analyses. In the analyses a significant relationship between outdoor air temperature, or factors closely related to outdoor air temperature, and the occurrence of cardiac arrest is found. The incidence of cardiac arrest decreases with increasing temperature. Further a significant effect of snowfall is also found, with increased intensity of cardiac arrest on days with snowfall. A more borderline significant effect of precipitation is also identified.
PubMed ID
17195279 View in PubMed
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Comparison of case-cohort estimators based on data on premature death of adult adoptees.

https://arctichealth.org/en/permalink/ahliterature182410
Source
Stat Med. 2003 Dec 30;22(24):3795-803
Publication Type
Article
Date
Dec-30-2003
Author
Liselotte Petersen
Thorkild I A Sørensen
Per Kragh Andersen
Author Affiliation
Danish Epidemiology Science Centre at the Institute of Preventive Medicine, Copenhagen University Hospital, DK-1399 Copenhagen K, Denmark. lp@ipm.hosp.dk
Source
Stat Med. 2003 Dec 30;22(24):3795-803
Date
Dec-30-2003
Language
English
Publication Type
Article
Keywords
Adoption
Adult
Cohort Studies
Denmark
Environment
Genetics
Humans
Mortality
Proportional Hazards Models
Survival Analysis
Abstract
A case-cohort sample of adoptees was collected to investigate genetic and environmental influences on premature death, which motivated us to supplement existing simulation results to explore the performance of various estimators proposed for case-cohort samples of survival data. We studied six regression coefficients estimators, which differ with regard to the weighting scheme used in a pseudo-likelihood function, and two different estimators of their variances. Compared to earlier simulation studies, we changed the following conditions: type of explanatory variable, the distribution of lifetimes, and the percentage of deaths in the full cohort. The latter condition affected the performance of the estimated variances of the regression coefficients, where we found a systematic bias of the estimator, proposed by Self and Prentice, dependent on the percentages of deaths. This dependence of percentages of death was different for different sizes of case-cohort studies. A robust variance estimator showed a better overall performance. The estimators of regression coefficients compared did not differ much, the estimators proposed by Kalbfleisch and Lawless and by Prentice performing very well. Results of the case-cohort data of adoptees were not in conflict with earlier findings of a moderate genetic influence on premature death in adulthood.
PubMed ID
14673939 View in PubMed
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Source
Euro Surveill. 2012;17(17)
Publication Type
Article
Date
2012
Author
T. Grove Krause
S. Jakobsen
M. Haarh
K. Mølbak
Author Affiliation
Department of Infectious Disease Epidemiology, Statens Serum Institut, Copenhagen, Denmark. TGV@ssi.dk
Source
Euro Surveill. 2012;17(17)
Date
2012
Language
English
Publication Type
Article
Keywords
Denmark
Humans
Immunization Programs
Information Systems
Proportional Hazards Models
Registries
Vaccination - statistics & numerical data
Abstract
Immunisation information systems (IIS) are valuable tools for monitoring vaccination coverage and for estimating vaccine effectiveness and safety. Since 2009, an advanced IIS has been developed in Denmark and will be implemented during 2012–14. This IIS is based on a database existing since 2000. The reporting of all administered vaccinations including vaccinations outside the national programme will become mandatory. Citizens will get access to data about their own vaccinations and healthcare personnel will get access to information on the vaccinations of their patients. A national concept of identification, a national solution combining a personal code and a card with codes, ensures easy and secure access to the register. From the outset, the IIS will include data on childhood vaccinations administered from 1996 and onwards. All Danish citizens have a unique identifier, a so called civil registration number, which allows the linking of information on vaccinations coming from different electronic data sources. The main challenge will be to integrate the IIS with the different electronic patient record systems currently existing at general practitioner, vaccination clinic and hospital level thereby avoiding double-entry. A need has been identified for an updated international classification of vaccine products on the market. Such a classification would also be useful for the future exchange of data on immunisations from IIS between countries.
PubMed ID
22551494 View in PubMed
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The frequency of alcohol consumption is associated with the stroke mortality.

https://arctichealth.org/en/permalink/ahliterature259934
Source
Acta Neurol Scand. 2014 Aug;130(2):118-24
Publication Type
Article
Date
Aug-2014
Author
S H Rantakömi
S. Kurl
J. Sivenius
J. Kauhanen
J A Laukkanen
Source
Acta Neurol Scand. 2014 Aug;130(2):118-24
Date
Aug-2014
Language
English
Publication Type
Article
Keywords
Alcohol drinking - epidemiology
Finland - epidemiology
Humans
Male
Middle Aged
Proportional Hazards Models
Stroke - mortality
Abstract
The purpose of this study was to examine the association between the frequency of alcohol consumption and stroke mortality among eastern Finnish men.
This study is a population-based sample of men with an average follow-up of 20.2 years. A total of 2609 men with no history of stroke at baseline participated in the study. During the follow-up, 66 deaths from stroke occurred.
After adjustment for systolic blood pressure, smoking, BMI, diabetes, and socioeconomic status, the relative risk (RR) among men who consumed alcohol 2.5 times per week after adjustment for risk factors. When the total amount of alcohol consumption (g/week) was taken into account with other covariates, RR was 0.71 (95% CI, 0.30-1.68; P = 0.437) for men with alcohol consumption 2.5 times per week compared with nondrinkers, RR was 3.03 (95% CI, 1.19-7.72; P = 0.020).
This study shows a strong association between the frequency of alcohol consumption and stroke mortality, independent of total amount of alcohol consumption. The risk of stroke death was the highest among men who consumed alcohol >2.5 times per week.
PubMed ID
24606050 View in PubMed
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Analysing and interpreting competing risk data.

https://arctichealth.org/en/permalink/ahliterature167956
Source
Stat Med. 2007 Mar 15;26(6):1360-7
Publication Type
Article
Date
Mar-15-2007
Author
Melania Pintilie
Author Affiliation
Ontario Cancer Institute, Clinical Study Coordination and Biostatistics, 610 University Ave, Fl. 15, Rm. 433, Toronto, Ont., Canada M5G 2M9. pintilie@uhnres.utoronto.ca
Source
Stat Med. 2007 Mar 15;26(6):1360-7
Date
Mar-15-2007
Language
English
Publication Type
Article
Keywords
Causality
Data Interpretation, Statistical
Humans
Ontario
Proportional Hazards Models
Risk Assessment - statistics & numerical data
Abstract
When competing risks are present, two types of analysis can be performed: modelling the cause specific hazard and modelling the hazard of the subdistribution. This paper contrasts these two methods and presents the benefits of each. The interpretation is specific to the analysis performed. When modelling the cause specific hazard, one performs the analysis under the assumption that the competing risks do not exist. This could be beneficial when, for example, the main interest is whether the treatment works in general. In modelling the hazard of the subdistribution, one incorporates the competing risks in the analysis. This analysis compares the observed incidence of the event of interest between groups. The latter analysis is specific to the structure of the observed data and it can be generalized only to another population with similar competing risks.
Notes
Comment In: Stat Med. 2007 Aug 15;26(18):3521-3; author reply 352317476646
Comment In: Stat Med. 2007 Aug 30;26(19):3676-9; author reply 3679-8017299738
PubMed ID
16900575 View in PubMed
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Maximizing the benefits of model-based period analysis of cancer patient survival.

https://arctichealth.org/en/permalink/ahliterature162024
Source
Cancer Epidemiol Biomarkers Prev. 2007 Aug;16(8):1675-81
Publication Type
Article
Date
Aug-2007
Author
Hermann Brenner
Timo Hakulinen
Author Affiliation
Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Bergheimer Strasse 20, D-69115 Heidelberg, Germany. h.brenner@dkfz-heidelberg.de
Source
Cancer Epidemiol Biomarkers Prev. 2007 Aug;16(8):1675-81
Date
Aug-2007
Language
English
Publication Type
Article
Keywords
Finland - epidemiology
Humans
Neoplasms - mortality
Probability
Prognosis
Proportional Hazards Models
Registries
Survival Analysis
Time Factors
Abstract
Period analysis has been shown to provide more up-to-date estimates of cancer survival than traditional methods of survival analysis. There is, however, a tradeoff between up-to-dateness and precision of period survival estimates: increasing up-to-dateness by restricting the analysis to a relatively short period, such as the most recent calendar year, goes along with loss of precision. Recently, a model-based approach was proposed, in which more precise period survival estimates for the most recent year can be obtained through modeling of survival trends within a recent 5-year period. We assess possibilities to extend the time window used for modeling to come up with even more precise, but equally accurate and up-to-date estimates of prognosis. Empirical evaluation using data from the Finnish Cancer Registry shows that extension of the time window to about 10 years provides, in most cases, as accurate results as using a 5-year time window (whereas further extension may lead to considerably less accurate results in some cases). Using 10-year time windows for modeling, SEs of survival estimates can be approximately halved compared with conventional period survival estimates for the most recent calendar year. Furthermore, we present a modification of the modeling approach, which allows extension to 10-year time windows to be achieved without the need to include additional cohorts of patients diagnosed longer time ago and which provides similarly accurate survival estimates at comparable levels of precision in most cases. Our analyses indicate opportunities to further maximize benefits of model-based period analysis of cancer survival.
PubMed ID
17684145 View in PubMed
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Hazard screening and proposals for prevention by occupational health service: an experiment with job load and hazard analysis at a Finnish construction company.

https://arctichealth.org/en/permalink/ahliterature227116
Source
J Soc Occup Med. 1991;41(1):17-22
Publication Type
Article
Date
1991
Author
M. Mattila
P. Kivi
Author Affiliation
Tampere University of Technology, Finland.
Source
J Soc Occup Med. 1991;41(1):17-22
Date
1991
Language
English
Publication Type
Article
Keywords
Finland
Humans
Occupational Health - statistics & numerical data
Occupational Health Services - organization & administration
Proportional Hazards Models
Abstract
In this study a systematic method for workplace investigation was developed and then tested as part of the regular occupational health care procedures in the building trade. Workplace investigation is a concept which entails the analysis of hazards inherent in the work as well as assessment of their effects on workers' well-being. The aim of this paper is to evaluate the effectiveness of the workplace investigation method. The newly developed method, called Job Load and Hazard Analysis, has the following characteristics: a job analytic approach; the application of group problem-solving; and cooperation between occupational health professionals, occupational safety personnel, and line management. The method comprises the identification of health hazards, their assessment, and conclusions and proposals as to their prevention and follow-up. The method was tested as part of one constructor's actual occupational health care programme, over a 2.5-year period. The method worked well as a central component of preventive occupational health care. It yielded concrete data that could be applied to make the occupational health care programme better suited to preventing the hazards inherent in the building trade. The contents of the occupational health care programme were clearly enhanced, the number of preventive measures increased, and the organizational climate improved; the workers praised the increased emphasis on safety. More research is needed, eg in other production settings and to determine the most effective utilization of the data gathered by the method.
PubMed ID
2011001 View in PubMed
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4271 records – page 1 of 428.