Demography
Miranda Thurston in Key Themes in Public Health, 2014
In high-income countries death certification (by a doctor) is a legal requirement. The certificate records cause of death as well as other socio-demographic information such as the name, sex, date of birth, places of residence and death, occupation and whether the deceased had been medically attended before death. All causes should be listed and coded. Causes are defined in the tenth (1990) version of the International Classification of Diseases and Related Health Problems (ICD-10) (WHO, 2012). The cause of death is defined as all those diseases, morbid conditions, or injuries that either resulted in or contributed to death and the circumstances of the accident or violence that produced any such injuries. The underlying cause of death is defined as ‘the disease or injury that initiated the train of events leading to death or the circumstances of the accident or violence that produced the fatal injury’ (Porta, 2008: 60). The WHO describes the ICD as the ‘global standard for mortality and morbidity statistics’ (www.int/classifications/i cd/factsheet/en/index.html). The system is used by more than 100 countries to report mortality data, used as a primary indicator of population health. In the UK, however, the system of death certification has come under recent public scrutiny and there have been enduring questions relating to the accuracy of death certification with errors being common (Tuffin et al., 2009), particularly in the elderly, where post-mortems are rare.
Decision-making and communication
Peter Hoskin, Peter Ostler in Clinical Oncology, 2020
Survival is the commonest end point for a large trial comparing two or more treatments for cancer. Whilst apparently straightforward in its definition time, cause of death may be difficult to trace, particularly in trials continuing for many years and where the condition has a long natural history for example patients in trials of prostate and breast cancer. It is important to define the cause of death. This will allow a comparison of not only overall survival but also disease-specific survival, i.e. counting only those patients dying from the disease under investigation. It is always important, however, to analyse all causes of death, since this may on occasions reveal an excess of deaths from the complications of the treatment. A typical example of this is the long-term analysis of the results of radiotherapy for breast cancer, where a reduction in breast cancer death rate is seen in patients receiving radiotherapy, but overall survival differences between those receiving radiotherapy and those who did not is less. The explanation for this apparent anomaly was explained by an excess of non-cancer deaths, predominantly cardiovascular disease in the radiotherapy group which partially negated the reduction in breast cancer deaths.
Custodial Deaths in Detention
Darrell L. Ross, Gary M. Vilke in Guidelines for Investigating Officer-Involved Shootings, Arrest-Related Deaths, and Deaths in Custody, 2018
Consistent with other death investigations, the investigator should attend the autopsy. Even though the cause of death may appear to be obvious, from natural causes, accident or by suicide, the medical examiner or pathologist performing the autopsy will make the final classification of death, and the investigator should be in attendance. In cases where the cause of death may be classified as undetermined, as a result of a negative autopsy or in cases where the cause of death is classified as a homicide, the investigator needs to be in attendance at the autopsy. During the autopsy, the investigator should take notes, take photographs of the procedure, obtain a copy of the death certificate, obtain the autopsy report, and obtain a report of all tests performed on the decedent. In deaths classified as undetermined or as a homicide, the investigator should request toxicology tests be performed, including: the urine, the blood, gastric contents, vitreous humor, bile and liver, and hair (DiMaio & DiMaio, 2006; Graham, 2014; James & Nordby, 2012; Sathyavagiswaran, Rogers, & Noguchi, 2007).
The Epidemic of Madness: Killing the Community to Save It
Published in Journal of Progressive Human Services, 2020
David Wagner
A second consideration is that since the largest number of victims of CO-19 are among the elderly and ill, particularly those who had “underlying conditions” we need to understand how the data were collected and assessed. The CDC itself (see National Center for Health Statistics “Excess Deaths Associated with COVID-19”, May 29, 2020) admits this is quite difficult because when a patient has underlying conditions, his or her death may be from a combination of things. The CDC states cause of death is “usually based on the underlying cause of death” such as respiratory diseases, circulatory diseases, malignant neoplasms, and Alzheimer’s disease and dementia. In indicating there may be “false positives” and “false negatives” (that is people may be reported as being ill with CO-19 but are not, and/or they may not be recorded as having CO-19 as a result of the other conditions). But there is no reason to assume these “false” diagnoses equal themselves out. First off, the CDC and other health establishments have been promoting the dangers of the disease so it is for them not laymen to determine this. Second, with the incredibly constant and wide advocacy of the disease’s spread, it seems likely some elderly and ill people are being misdiagnosed with it. I have been told but cannot confirm that some nurses have told in nursing homes to label deaths as CO-19. With all the attention to it, it becomes the disease du jour.
The Impact of co-morbid severe mental illness and HIV upon mental and physical health and social outcomes: a systematic review
Published in AIDS Care, 2018
Ikenna Ebuenyi, Chris Taylor, David O’Flynn, A. Matthew Prina, Ruth Passchier, Rosie Mayston
We found some evidence that SMI and HIV co-morbidity might be associated with elevated mortality. The strongest evidence came from the highest quality study included in the review: a Danish cohort using linkage of national registries of psychiatric illness and HIV (n = 2,646,154). This study compared mortality for people living with schizophrenia and schizophrenia and HIV to people without either condition. Authors identified greatly elevated mortality for both groups, which was highest for people living with SMI and HIV (MMR = 76.5, 95% CI = 44–122) (Helleberg et al., 2015). Further research in settings outside of Denmark and the USA is necessary to explore the generalisability of these findings. It will be important to examine cause of death to understand the underlying mechanisms for the mortality findings.
Inference of progressively type-II censored competing risks data from Chen distribution with an application
Published in Journal of Applied Statistics, 2020
Essam A. Ahmed, Ziyad Ali Alhussain, Mukhtar M. Salah, Hanan Haj Ahmed, M. S. Eliwa
In electrical engineering, biomedical or biomedical studies or reliability analysis, the elements or individuals often fail due to different failure causes which compete with each other in product life cycles. In literature, such situations are often model using the so-called competing risks model. In a competing risk problem, the data consist of the failure times and the values of an indicator denoting the cause of failure. The causes of failure might be thought to be independent or dependent. A variety of disciplines may encounter problems involving competing risks. These include cancer research, reliability of physical equipment, economics, social sciences, insurance assessments, and outcomes of preventive behaviors, amongst many other areas. For example, during the follow-up period for breast cancer patients, some patients may die from breast cancer or other causes. In a demographic study, the main causes of death recorded are, for example, heart disease, cancer, and so on. In the reliability experiments, several reasons can lead to the failure of mechanical devices such as corrosion, vibration, and others. For an extensive review of the analysis of various competing risk models, we refer to Nelson [37] and Crowder [16].
Related Knowledge Centers
- Accidental Death
- Death
- Homicide
- International Classification of Diseases
- Suicide
- Medical Examiner
- Death Certificate
- Autopsy
- Injury
- Manner of Death
- International Classification of Diseases