Causes of Death in People with Dementia from 2002 to 2015: A Nationwide Study

2021 ◽  
pp. 1-10
Author(s):  
Lærke Taudorf ◽  
Ane Nørgaard ◽  
Sabrina Islamoska ◽  
Thomas Munk Laursen ◽  
Gunhild Waldemar
Keyword(s):  
Cause Of Death ◽  
Elderly Population ◽  
Causes Of Death ◽  
People With Dementia ◽  
Underlying Causes ◽  
Annual Frequency ◽  
Marked Decline ◽  
Underlying Cause Of Death ◽  
General Elderly Population ◽  
Over Time

Background: Dementia is associated with increased mortality. However, it is not clear whether causes of death in people with dementia have changed over time. Objective: To investigate if causes of death changed over time in people with dementia compared to the general elderly population. Methods: We included longitudinal data from nationwide registries on all Danish residents aged≥65 years to 110 years who died between 2002 to 2015. We assessed the annual frequency of dementia-related deaths (defined as a dementia diagnosis registered as a cause of death) and of underlying causes of death in people registered with dementia compared to the general elderly population. Results: From 2002 to 2015, 621,826 people died, of whom 103,785 were diagnosed with dementia. During this period, the percentage of dementia-related deaths increased from 10.1%to 15.2%in women, and from 6.3%to 9.5%in men in the general elderly population. From 2002 to 2015, dementia became the leading, registered underlying cause of death in people with diagnosed dementia. Simultaneously, a marked decline in cardiovascular and cerebrovascular deaths was observed in people with and without dementia. Conclusion: This is the first study to investigate if the causes of death change over time in people with diagnosed dementia compared with the general elderly population. The increase in the registration of dementia as an underlying cause of death could reflect increasing awareness of dementia as a fatal condition.

scholarly journals A Deep Artificial Neural Network−Based Model for Prediction of Underlying Cause of Death From Death Certificates: Algorithm Development and Validation

10.2196/17125 ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. e17125 ◽  
Author(s):  
Louis Falissard ◽  
Claire Morgand ◽  
Sylvie Roussel ◽  
Claire Imbaud ◽  
Walid Ghosn ◽  
...  
Keyword(s):  
Neural Network ◽  
Cause Of Death ◽  
Deep Neural Network ◽  
Causes Of Death ◽  
State Of The Art ◽  
Death Certificates ◽  
Current State ◽  
Underlying Causes ◽  
Artificial Neural ◽  
Underlying Cause Of Death

Background Coding of underlying causes of death from death certificates is a process that is nowadays undertaken mostly by humans with potential assistance from expert systems, such as the Iris software. It is, consequently, an expensive process that can, in addition, suffer from geospatial discrepancies, thus severely impairing the comparability of death statistics at the international level. The recent advances in artificial intelligence, specifically the rise of deep learning methods, has enabled computers to make efficient decisions on a number of complex problems that were typically considered out of reach without human assistance; they require a considerable amount of data to learn from, which is typically their main limiting factor. However, the CépiDc (Centre d’épidémiologie sur les causes médicales de Décès) stores an exhaustive database of death certificates at the French national scale, amounting to several millions of training examples available for the machine learning practitioner. Objective This article investigates the application of deep neural network methods to coding underlying causes of death. Methods The investigated dataset was based on data contained from every French death certificate from 2000 to 2015, containing information such as the subject’s age and gender, as well as the chain of events leading to his or her death, for a total of around 8 million observations. The task of automatically coding the subject’s underlying cause of death was then formulated as a predictive modelling problem. A deep neural network−based model was then designed and fit to the dataset. Its error rate was then assessed on an exterior test dataset and compared to the current state-of-the-art (ie, the Iris software). Statistical significance of the proposed approach’s superiority was assessed via bootstrap. Results The proposed approach resulted in a test accuracy of 97.8% (95% CI 97.7-97.9), which constitutes a significant improvement over the current state-of-the-art and its accuracy of 74.5% (95% CI 74.0-75.0) assessed on the same test example. Such an improvement opens up a whole field of new applications, from nosologist-level batch-automated coding to international and temporal harmonization of cause of death statistics. A typical example of such an application is demonstrated by recoding French overdose-related deaths from 2000 to 2010. Conclusions This article shows that deep artificial neural networks are perfectly suited to the analysis of electronic health records and can learn a complex set of medical rules directly from voluminous datasets, without any explicit prior knowledge. Although not entirely free from mistakes, the derived algorithm constitutes a powerful decision-making tool that is able to handle structured medical data with an unprecedented performance. We strongly believe that the methods developed in this article are highly reusable in a variety of settings related to epidemiology, biostatistics, and the medical sciences in general.

scholarly journals An Automatic Approach Designed for Inference of the Underlying Cause-of-Death of Citizens

2021 ◽  
Vol 18 (5) ◽  
pp. 2414
Author(s):  
Hui Ge ◽  
Keyan Gao ◽  
Shaoqiong Li ◽  
Wei Wang ◽  
Qiang Chen ◽  
...  
Keyword(s):  
Health Status ◽  
Cause Of Death ◽  
Causes Of Death ◽  
Health Policies ◽  
Automatic Method ◽  
Comprehensive Understanding ◽  
Public Health Policies ◽  
Underlying Causes ◽  
Manual Methods ◽  
Underlying Cause Of Death

It is very important to have a comprehensive understanding of the health status of a country’s population, which helps to develop corresponding public health policies. Correct inference of the underlying cause-of-death for citizens is essential to achieve a comprehensive understanding of the health status of a country’s population. Traditionally, this relies mainly on manual methods based on medical staff’s experiences, which require a lot of resources and is not very efficient. In this work, we present our efforts to construct an automatic method to perform inferences of the underlying causes-of-death for citizens. A sink algorithm is introduced, which could perform automatic inference of the underlying cause-of-death for citizens. The results show that our sink algorithm could generate a reasonable output and outperforms other stat-of-the-art algorithms. We believe it would be very useful to greatly enhance the efficiency of correct inferences of the underlying causes-of-death for citizens.

scholarly journals Time series of diabetes attributable mortality from 2008 to 2017

2021 ◽  
Author(s):  
U. Fedeli ◽  
E. Schievano ◽  
S. Masotto ◽  
E. Bonora ◽  
G. Zoppini
Keyword(s):  
Cause Of Death ◽  
Causes Of Death ◽  
Death Certificate ◽  
Attributable Mortality ◽  
Joinpoint Regression ◽  
Annual Percent Change ◽  
Percent Change ◽  
Underlying Causes ◽  
Underlying Cause Of Death ◽  
Circulatory Diseases

Abstract Purpose Diabetes is a growing health problem. The aim of this study was to capture time trends in mortality associated with diabetes. Methods The mortality database of the Veneto region (Italy) includes both the underlying causes of death, and all the diseases mentioned in the death certificate. The annual percent change (APC) in age-standardized rates from 2008 to 2017 was computed by the Joinpoint Regression Program. Results Overall 453,972 deaths (56,074 with mention of diabetes) were observed among subjects aged ≥ 40 years. Mortality rates declined for diabetes as the underlying cause of death and from diabetes-related circulatory diseases. The latter declined especially in females − 4.4 (CI 95% − 5.3/− 3.4), while in males the APC was − 2.8 (CI 95% − 4.0/− 1.6). Conclusion We observed a significant reduction in mortality during the period 2008–2017 in diabetes either as underlying cause of death or when all mentions of diabetes in the death certificate were considered.

Sickle Cell Disease Mortality in California and Georgia 2004-2008

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 439-439
Author(s):  
Susan Paulukonis ◽  
Todd Griffin ◽  
Mei Zhou ◽  
James R. Eckman ◽  
Robert Hagar ◽  
...  
Keyword(s):  
African American ◽  
Cause Of Death ◽  
Sickle Cell ◽  
Causes Of Death ◽  
Mortality Rates ◽  
Population Based ◽  
Age Group ◽  
Death Certificates ◽  
Underlying Causes ◽  
Underlying Cause Of Death

Abstract On-going public health surveillance efforts in sickle cell disease (SCD) are critical for understanding the course and outcomes of this disease over time. Once nearly universally fatal by adolescence, many patients are living well into adulthood and sometimes into retirement years. Previous SCD mortality estimates have relied on data from death certificates alone or from deaths of patients receiving care in high volume hematology clinics, resulting in gaps in reporting and potentially biased conclusions. The Registry and Surveillance System for Hemoglobinopathies (RuSH) project collected and linked population-based surveillance data on SCD in California and Georgia from a variety of sources for years 2004-2008. These data sources included administrative records, newborn screening reports and health insurance claims as well as case reports of adult and pediatric patients receiving care in the following large specialty treatment centers: Georgia Comprehensive Sickle Cell Center, Georgia Regents University, Georgia Comprehensive Sickle Cell Center at Grady Health Systems and Children's Healthcare of Atlanta in Georgia, and Children's Hospital Los Angeles and UCSF Benioff Children's Hospital Oakland in California. Cases identified from these combined data sources were linked to death certificates in CA and GA for the same years. Among 12,143 identified SCD cases, 640 were linked to death certificates. Combined SCD mortality rates by age group at time of death are compared to combined mortality rates for all African Americans living in CA and GA. (Figure 1). SCD death rates among children up to age 14 and among adults 65 and older were very similar to those of the overall African American population. In contrast, death rates from young adulthood to midlife were substantially higher in the SCD population. Overall, only 55% of death certificates linked to the SCD cases had SCD listed in any of the cause of death fields. Thirty-four percent (CA) and 37% (GA) had SCD as the underlying cause of death. An additional 22% and 20% (CA and GA, respectively) had underlying causes of death that were not unexpected for SCD patients, including related infections such as septicemia, pulmonary/cardiac causes of death, renal failure and stroke. The remaining 44% (CA) and 43% (GA) had underlying causes of death that were either not related to SCD (e.g., malignancies, trauma) or too vague to be associated with SCD (e.g., generalized pulmonary or cardiac causes of death. Figure 2 shows the number of deaths by state, age group at death and whether the underlying cause of death was SCD specific, potentially related to SCD or not clearly related to SCD. While the number of deaths was too small to use for life expectancy calculations, there were more deaths over age 40 than under age 40 during this five year period. This effort represents a novel, population-based approach to examine mortality in SCD patients. These data suggest that the use of death certificates alone to identify deceased cases may not capture all-cause mortality among all SCD patients. Additional years of surveillance are needed to provide better estimates of current life expectancy and the ability to track and monitor changes in mortality over time. On-going surveillance of the SCD population is required to monitor changes in mortality and other outcomes in response to changes in treatments, standards of care and healthcare policy and inform advocacy efforts. This work was supported by the US Centers for Disease Control and Prevention and the National Heart, Lung and Blood Institute, cooperative agreement numbers U50DD000568 and U50DD001008. Figure 1: SCD-Specific & Overall African American Mortality Rates in CA and GA, 2004 – 2008. Figure 1:. SCD-Specific & Overall African American Mortality Rates in CA and GA, 2004 – 2008. Figure 2: Deaths (Count) Among Individuals with SCD in CA and GA, by Age Group and Underlying Cause of Death, 2004-2008 (N=615) Figure 2:. Deaths (Count) Among Individuals with SCD in CA and GA, by Age Group and Underlying Cause of Death, 2004-2008 (N=615) Disclosures No relevant conflicts of interest to declare.

scholarly journals Comparative evaluation of underlying causes of death processed by the Automated Classification of Medical Entities and the Underlying Cause of Death Selection Systems

1998 ◽  
Vol 32 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Augusto H. Santo ◽  
Celso E. Pinheiro ◽  
Eliana M. Rodrigues
Keyword(s):  
Cause Of Death ◽  
Comparative Evaluation ◽  
Causes Of Death ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Automated Classification ◽  
Classification Of Diseases ◽  
Underlying Causes ◽  
Underlying Cause Of Death

INTRODUCTION: The correct identification of the underlying cause of death and its precise assignment to a code from the International Classification of Diseases are important issues to achieve accurate and universally comparable mortality statistics These factors, among other ones, led to the development of computer software programs in order to automatically identify the underlying cause of death. OBJECTIVE: This work was conceived to compare the underlying causes of death processed respectively by the Automated Classification of Medical Entities (ACME) and the "Sistema de Seleção de Causa Básica de Morte" (SCB) programs. MATERIAL AND METHOD: The comparative evaluation of the underlying causes of death processed respectively by ACME and SCB systems was performed using the input data file for the ACME system that included deaths which occurred in the State of S. Paulo from June to December 1993, totalling 129,104 records of the corresponding death certificates. The differences between underlying causes selected by ACME and SCB systems verified in the month of June, when considered as SCB errors, were used to correct and improve SCB processing logic and its decision tables. RESULTS: The processing of the underlying causes of death by the ACME and SCB systems resulted in 3,278 differences, that were analysed and ascribed to lack of answer to dialogue boxes during processing, to deaths due to human immunodeficiency virus [HIV] disease for which there was no specific provision in any of the systems, to coding and/or keying errors and to actual problems. The detailed analysis of these latter disclosed that the majority of the underlying causes of death processed by the SCB system were correct and that different interpretations were given to the mortality coding rules by each system, that some particular problems could not be explained with the available documentation and that a smaller proportion of problems were identified as SCB errors. CONCLUSION: These results, disclosing a very low and insignificant number of actual problems, guarantees the use of the version of the SCB system for the Ninth Revision of the International Classification of Diseases and assures the continuity of the work which is being undertaken for the Tenth Revision version.

CAUSES OF PIGLET DEATH FROM BIRTH TO WEANING

1987 ◽  
Vol 67 (2) ◽  
pp. 543-547 ◽  
Author(s):  
G. W. DYCK ◽  
E. E. SWIERSTRA
Keyword(s):  
Body Weight ◽  
Key Words ◽  
Cause Of Death ◽  
Causes Of Death ◽  
Congenital Abnormalities ◽  
Minor Importance ◽  
Secondary Importance ◽  
Adequate Nutrition ◽  
Underlying Cause Of Death

Causes of piglet death were determined for 569 piglets that died between birth and weaning out of a total of 2388 born over the second to fourth parity in 124 Yorkshire and 109 Yorkshire × Lacombe sow litters. Eight specific causes of death were identified. Starvation, crushing by the sow and stillbirths were the three main causes. Unidentified causes and piglets euthanized largely because of sow death or injury were of secondary importance. Exposure, congenital abnormalities and disease were of minor importance. In addition, the primary underlying cause of death appears to be a lack of adequate nutrition for the piglets as only 6.3% of the piglets dying during the first 3 d had an increase in body weight and only 15.4% of the piglets dying after day 3 had body weight increases that could be considered as adequate for their age. Key words: Piglets, death, birth, lactation

Mortality Profile Related to Systemic Lupus Erythematosus: A Multiple Cause-of-death Analysis

2012 ◽  
Vol 39 (3) ◽  
pp. 496-503 ◽  
Author(s):  
DEBORAH C.C. SOUZA ◽  
AUGUSTO H. SANTO ◽  
EMILIA I. SATO
Keyword(s):  
Renal Failure ◽  
Cause Of Death ◽  
Lupus Erythematosus ◽  
Digestive System ◽  
Causes Of Death ◽  
Circulatory System ◽  
Systemic Lupus ◽  
Circulatory System Diseases ◽  
Underlying Causes ◽  
Digestive System Diseases

Objective.To analyze the mortality profile related to systemic lupus erythematosus (SLE) in the state of São Paulo, Brazil.Methods.For the 1985–2007 period, we analyzed all death certificates (n = 4815) on which SLE was listed as an underlying (n = 3133) or non-underlying (n = 1682) cause of death. We evaluated sex, age, and the causes of death, comparing the first and last 5 years of the period, as well as determining the observed/expected death ratio (O/E ratio).Results.For SLE as an underlying cause, the mean age at death was 35.77 years (SD 15.12) and the main non-underlying causes of death were renal failure, circulatory system diseases, pneumonia, and septicemia. Over the period, the proportional mention of infectious causes and circulatory system diseases increased, whereas renal diseases decreased. For SLE as a non-underlying cause of death, the most common underlying causes of death were circulatory, respiratory, genitourinary, and digestive system diseases, and certain infections. The overall death O/E ratio was > 1 for renal failure, tuberculosis, septicemia, pneumonia, and digestive system diseases, as well as for circulatory system diseases at < 50 years of age, particularly acute myocardial infarct.Conclusion.Unlike in developed countries, renal failure and infectious diseases are still the most frequent causes of death. The increase in SLE deaths associated with infection, especially pneumonia and septicemia, is worrisome. The judicious use of immunosuppressive therapy together with vigorous treatment of cardiovascular comorbidities is crucial to the successful management of SLE and to improving survival of patients with SLE.

scholarly journals 1000Quantifying multiple causes of death: A systematic review and audit of methods and practice

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Saliu Balogun ◽  
Karen Bishop ◽  
James Eynstone-Hinkins ◽  
Melonie Martin ◽  
Margarita Moreno-Betancur ◽  
...  
Keyword(s):  
Statistical Methods ◽  
Cause Of Death ◽  
Causes Of Death ◽  
Analytical Framework ◽  
Multiple Causes Of Death ◽  
Underlying Cause Of Death ◽  
N 93 ◽  
International Experts ◽  
Analytical Approaches ◽  
Multiple Causes

Abstract Background Mortality reporting and research are typically focused on a single underlying cause of death (UCoD) selected from multiple reported causes. The need to incorporate multiple causes of death (MCoD) in mortality statistics is now recognised internationally, but there is scant methodological work to guide analytical approaches. This review aims to identify and appraise current methods and practices used to analyse MCoD data. Methods The Web of Science, Medline, Pubmed and Scopus (from inception to December 2019) were queried. Studies reporting MCoD alone or in comparison with single UCoD were included. The review is supplemented by qualitative interview with international experts. Results 3491 studies were identified; 141 full texts were included in the review. The measures usually estimated when analysing MCoD can be broadly categorised into descriptive measures (n = 93 studies), measures of associations between diseases (n = 46 studies) and advanced statistical methods (n = 11 studies). Descriptive statistics commonly used include standardized ratio of multiple to underlying cause (SRMU) and mortality rates based on any mention of a disease. Approaches used to assess measures of associations between diseases include the Cause-of-Death Association Indicator (CDAI) and social network analysis. The advanced statistical methods include weighting MCoD and lethal defect-wear model of mortality. Audit results will be discussed. Conclusions This review provides a comprehensive and updated summary of methodological approaches used to analyse MCoD data. The merit of each analytical framework is discussed. Key messages More work is needed to develop methodological frameworks that could be used to support routine consideration of MCoD in practice.

Development of definitions of suicidal behaviours

2021 ◽  
pp. 87-92
Author(s):  
José M. Bertolote ◽  
Danuta Wasserman
Keyword(s):  
Cause Of Death ◽  
Causes Of Death ◽  
Suicide Mortality ◽  
Sociocultural Factors ◽  
Vital Registration ◽  
Quality Of Information ◽  
Registration System ◽  
Vital Registration System ◽  
Over Time

This chapter covers definitions of suicidal behaviours and how they vary over time, reflecting predominant philosophies and schools of thought. The limitations in the quality of information about suicide mortality, as a common feature affecting the whole vital registration system, are discussed. The smaller the coverage a country receives, the greater the probability of distortions, which adds to any previous distortions already flawing the data. It should be strongly emphasized that these shortcomings affect the system as a whole, and hence all causes of death. However, suicidologists seem to be much more punctilious about under-reporting of suicide, and the essential unreliability of this information, than experts dealing with mortality from other causes. Coordinated efforts should be made to strengthen those systems, paying attention to the specificity of sociocultural factors’ influence on defining, recording, and reporting suicide as a cause of death.

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