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The American College of Medical Toxicology and the National Association of Medical Examiners convened an expert panel to generate evidence-based recommendations for the practice of death investigation and autopsy, toxicological analysis, interpretation of toxicology findings, and death certification to improve the precision of death certificate data available for public health surveillance. The panel finds the following: 1. A complete autopsy is necessary for optimal interpretation of toxicology results, which must also be considered in the context of the circumstances surrounding death, medical history, and scene findings. 2. A complete scene investigation extends to reconciliation of prescription information and pill counts. 3. Blood, urine, and vitreous humor, when available, should be retained in all cases. Blood from the femoral vein is preferable to blood from other sites. 4. A toxicological panel should be comprehensive and include opioid and benzodiazepine analytes, as well as other potent depressant, stimulant, and anti-depressant medications. 5. Interpretation of postmortem opioid concentrations requires correlation with medical history, scene investigation, and autopsy findings. 6. If death is attributed to any drug or combination of drugs (whether as cause or contributing factor), the certifier should list all the responsible substances by generic name in the autopsy report and on the death certificate. 7. The best classification for manner of death in deaths due to the misuse or abuse of opioids without any apparent intent of self-harm is "accident." Reserve "undetermined" as the manner for the rare cases in which evidence exists to support more than one possible determination.

Cause specific mortality was analysed among 883 white male workers from a paper company in Berlin, New Hampshire. Subjects were assigned to different exposure groups on the basis of their having worked in the pulp mill, the paper mill, or elsewhere in the paper company. A standardised mortality ratio (SMR) analysis was used to compare death rates for each of the exposure groups with United States national rates. For all the subjects, deaths due to all causes, all malignant neoplasms, and lung cancer were close to the number expected and excesses were noted for cancers of the digestive system and leukaemia. Among pulp mill workers, the number of cancers of the digestive system was raised and the SMR for pancreatic cancer was especially high (SMR = 305, 95% CI = 98-712). Among paper mill workers, more deaths were due to leukaemia and cancers of the digestive system than expected. These results are consistent with the findings from other studies that employment in pulp and paper mills is associated with excess mortality due to digestive and lymphopoietic cancers.

Background: There are scant data on the causes of adult deaths in sub-Saharan Africa. We estimated the level and trends in adult mortality, overall and by different causes, in rural Rakai, Uganda, by age, sex, and HIV status., Objectives: To estimate and analyse adult cause-specific mortality trends in Rakai, Uganda., Methodology: Mortality information by cause, age, sex, and HIV status was recorded in the Rakai Community Cohort study using verbal autopsy interviews, HIV serosurveys, and residency data. We estimated the average number of years lived in adulthood. Using demographic decomposition methods, we estimated the contribution of each cause of death to adult mortality based on the average number of years lived in adulthood., Results: Between 1999 and 2019, 63082 adults (15-60 years) were censused, with 1670 deaths registered. Of these, 1656 (99.2%) had completed cause of death data from verbal autopsy. The crude adult death rate was 5.60 (95% confidence interval (CI): 5.33-5.87) per 1000 person-years of observation (pyo). The crude death rate decreased from 11.41 (95% CI: 10.61-12.28) to 3.27 (95% CI: 2.89-3.68) per 1000 pyo between 1999-2004 and 2015-2019. The average number of years lived in adulthood increased in people living with HIV and decreased in HIV-negative individuals between 2000 and 2019. Communicable diseases, primarily HIV and Malaria, had the biggest decreases, which improved the average number of years lived by approximately extra 12 years of life in females and 6 years in males. There were increases in deaths due to non-communicable diseases and external causes, which reduced the average number of years lived in adulthood by 2.0 years and 1.5 years in females and males, respectively., Conclusion: There has been a significant decline in overall mortality from 1999 to 2019, with the greatest decline seen in people living with HIV since the availability of antiretroviral therapy in 2004. By 2020, the predominant causes of death among females were non-communicable diseases, with external causes of death dominating in males.

Background The Medical Certificate of Stillbirth (MCS) records data about a baby's death after 24 weeks of gestation but before birth. Major errors that could alter interpretation of the MCS were widespread in two UK-based regional studies. Methods A multicentre evaluation was conducted, examining MCS issued 1 January 2018 to 31 December 2018 in 76 UK obstetric units. A systematic case-note review of stillbirths was conducted by Obstetric and Gynaecology trainees, generating individual 'ideal MCSs' and comparing these to the actual MCS issued. Anonymized central data analysis described rates and types of error, agreement and factors associated with major errors. Results There were 1120 MCSs suitable for assessment, with 126 additional submitted data sets unsuitable for accuracy analysis (total 1246 cases). Gestational age demonstrated 'substantial' agreement [K = 0.73 (95% CI 0.70–0.76)]. Primary cause of death (COD) showed 'fair' agreement [K = 0.26 (95% CI 0.24–0.29)]. Major errors [696/1120; 62.1% (95% CI 59.3–64.9%)] included certificates issued for fetal demise at <24 weeks' gestation [23/696; 3.3% (95% CI 2.2–4.9%)] or neonatal death [2/696; 0.3% (95% CI 0.1–1.1%)] or incorrect primary COD [667/696; 95.8% (95% CI 94.1–97.1%)]. Of 540/1246 [43.3% (95% CI 40.6–46.1%)] 'unexplained' stillbirths, only 119/540 [22.0% (95% CI 18.8–25.7%)] remained unexplained; the majority were redesignated as either fetal growth restriction [FGR: 195/540; 36.1% (95% CI 32.2–40.3%)] or placental insufficiency [184/540; 34.1% (95% CI 30.2–38.2)]. Overall, FGR [306/1246; 24.6% (95% CI 22.3–27.0%)] was the leading primary COD after review, yet only 53/306 [17.3% (95% CI 13.5–22.1%)] FGR cases were originally attributed correctly. Conclusion This study demonstrates widespread major errors in MCS completion across the UK. MCS should only be completed following structured case-note review, with particular attention on the fetal growth trajectory. [ABSTRACT FROM AUTHOR]

Context.—: Autopsies performed on COVID-19 patients have provided critical information about SARS-CoV-2's tropism, mechanisms of tissue injury, and spectrum of disease., Objective.—: To provide an updated database of postmortem disease in COVID-19 patients, assess relationships among clinical and pathologic variables, evaluate the accuracy of death certification, and correlate disease variables to causes of death., Design.—: The 272 postmortem examinations reported in this paper were submitted by 14 pathologists from 9 medical or forensic institutions across the United States. The study spans the eras of the 3 principal COVID-19 strains and incorporates surveyed demographic, clinical, and postmortem data from decedents infected with SARS-CoV-2, including primary and contributing causes of death. It is the largest database of its kind to date., Results.—: Demographics of the decedents reported here correspond well to national statistics. Primary causes of death as determined by autopsy and official death certificates were significantly correlated. When specifically cited disease conditions found at autopsy were correlated with COVID-19 versus non-COVID-19 deaths, only lung findings characteristic of SARS-CoV-2 infection or the absence of lung findings were significantly associated., Conclusions.—: Changes in hospitalization and disease likely stem from longer lifespans after COVID-19 diagnosis and alteration in treatment approaches. Although Omicron variants preferentially replicate in the upper airways, autopsied patients who died of COVID-19 in that time period showed the same lung damage as earlier decedents. Most importantly, findings suggest that there are still unelucidated risk factors for death from COVID-19 including possibly genetic susceptibility., Competing Interests: The authors have no relevant financial interest in the products or companies described in this article., (© 2024 College of American Pathologists.)

The Manhiça Health Research Centre (Manhiça HDSS) was established in 1996 in Manhiça, a rural district at Maputo Province in the southern part of Mozambique with approximately 49,000 inhabited households, a total population of 209.000 individuals, and an annual estimated birth cohort of about 5000 babies. Since 2016, Manhiça HDSS is implementing the Child Health and Mortality Prevention Surveillance (CHAMPS) program aiming to investigate causes of death (CoD) in stillbirths and children under the age of 5 years using an innovative post-mortem technique known as Minimally Invasive Tissue sampling (MITS), comprehensive pathogen screening using molecular methods, clinical record abstraction and verbal autopsy. Both in-hospital and community pediatric deaths are investigated using MITS. For this, community-wide socio-demographic approaches (notification of community deaths by key informants, formative research involving several segments of the community, availability of free phone lines for notification of medical emergencies and deaths, etc.) are conducted alongside to foster community awareness, involvement and adherence as well as to compute mortality estimates and collect relevant information of health and mortality determinants. The main objective of this paper is to describe the Manhiça Health and Demographic Surveillance System (HDSS) site and the CHAMPS research environment in place including the local capacities among its reference hospital, laboratories, data center and other relevant areas involved in this ambitious surveillance and research project, whose ultimate aim is to improve child survival through public health actions derived from credible estimates and understanding of the major causes of childhood mortality in Mozambique., Competing Interests: No competing interests were disclosed., (Copyright: © 2024 Sacoor C et al.)

Background: In human health, vitamins play a vital role in various metabolic and regulatory processes and in the proper functioning of cells. Currently, the effect of Vitamin E (VE) intake on multiple causes of death in Chronic obstructive pulmonary disease (COPD) patients is unclear. Therefore, this paper aims to investigate the relationship between VE and multiple causes of death in COPD patients, to guide the rationalization of dietary structure and reduce the risk of COPD death., Methods: This study screened patients with COPD aged ≥40 years from the National Health and Nutrition Examination Survey (NHANES) database 2008-2018. Weighted COX regression was used to analyze the association between VE intake and multiple causes of death in COPD. The restricted cubic spline(RCS) is drawn to show their relationship. Finally, we conducted a subgroup analysis for further verification., Results: A total of 1261 participants were included in this study. After adjustment for multiple covariates, VE intake was associated with all-cause death in COPD patients, and chronic lower respiratory disease (CLRD) deaths were linearly associated with cardiovascular disease (CVD) deaths there was no such correlation. Subgroup analyses showed no interaction between subgroups, further validating the robustness of the relationship., Conclusion: In COPD patients, VE intake was negatively associated with all-cause mortality and CLRD death. Higher VE intake reduces the risk of all-cause mortality and CLRD death in COPD patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Tian et al.)

Objective: For ICD-10 coding causes of death in France in 2018 and 2019, predictions by deep neural networks (DNNs) are employed in addition to fully automatic batch coding by a rule-based expert system and to interactive coding by the coding team focused on certificates with a special public health interest and those for which DNNs have a low confidence index., Methods: Supervised seq-to-seq DNNs are trained on previously coded data to ICD-10 code multiple causes and underlying causes of death. The DNNs are then used to target death certificates to be sent to the coding team and to predict multiple causes and underlying causes of death for part of the certificates. Hence, the coding campaign for 2018 and 2019 combines three modes of coding and a loop of interaction between the three., Findings: In this campaign, 62% of the certificates are automatically batch coded by the expert system, 3% by the coding team, and the remainder by DNNs. Compared to a traditional campaign that would have relied on automatic batch coding and manual coding, the present campaign reaches an accuracy of 93.4% for ICD-10 coding of the underlying cause (95.6% at the European shortlist level). Some limitations (risks of under- or overestimation) appear for certain ICD categories, with the advantage of being quantifiable., Conclusion: The combination of the three coding methods illustrates how artificial intelligence, automated and human codings are mutually enriching. Quantified limitations on some chapters of ICD codes encourage an increase in the volume of certificates sent for manual coding from 2021 onward., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Malaria contributes substantially to the persistent burden of child deaths in sub-Saharan Africa. Accurate and comprehensive malaria mortality data are crucial to monitor the progress in reducing malaria incidence and mortality. Verbal Autopsy (VA) ascertains the cause of death despite its limitations leading to misclassification errors. Minimally Invasive Tissue Sampling (MITS) is being conducted in some settings as an alternative to Complete Diagnostic Autopsy (CDA). The present study examines the validity of malaria-related deaths comparing VA diagnoses with those obtained through MITS and/or CDA., Methods: A comprehensive literature search for original studies in English language using Ovid MEDLINE, Ovid Embase, CINAHL via EBSCO, Scopus, The Cochrane Library via Wiley, Google Scholar and searching the MITS Surveillance Alliance papers was carried out. The reference period was January 1, 1990-March 31, 2024. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were adopted., Results: Among 71 articles identified in the databases, 21 matched the eligibility criteria. Qualitative syntheses showed that malaria Cause Specific Mortality Fractions (CSMFs) across various studies ranged from 2 to 31%. Plasmodium falciparum was mostly responsible for these deaths and the most common complications were anaemia and cerebral malaria. The sensitivity and specificity of the VA validation studies ranged from 18.4% to 33% and from 86.6% to 97%, respectively, and there was a high level of misclassification for both InSilico and Expert Algorithm VA for malaria compared to MITS. The overall concordance rates between MITS and CDA diagnoses ranged from 68 to 90%, with the highest concordance seen in deaths due to infectious diseases and malignant tumours. Clinical data increased diagnostic coincidence between MITS blind to clinical data and the gold standard CDA by 11%., Conclusions: The comprehensive review finds that MITS demonstrated better accuracy compared to VA in diagnosing malaria-attributed deaths, particularly in hospital settings. The high specificity of malaria in VA diagnosis suggests population-based estimates of the proportion of deaths due to malaria are broadly plausible., (© 2024. The Author(s).)

Background: Vitamin D insufficiency is a prevalent issue in patients suffering from CKD. The purpose of this study was to determine whether serum 25(OH)D levels are associated with all-cause and cardiovascular mortality in patients with CKD., Methods: To examine the associations between 25(OH)D levels and cardiovascular mortality, this retrospective cohort study used the National Health and Nutrition Examination Survey (NHANES) and the National Death Index (NDI) 2007‒2018 database. A total of 2,668 eligible subjects were included in this study, with follow-up conducted until December 31, 2019. The associations were assessed using Cox proportional hazards regression, restricted cubic splines, Kaplan-Meier survival curves, and competing risks survival analysis. Furthermore, subgroup and sensitivity analyses were performed., Results: During a median follow-up of 72 months in a weighted population of 11,715,452 eligible participants, there were 665 deaths from any cause, including 196 cardiovascular-related deaths. After adjusting for covariates, lower levels of 25(OH)D were significantly associated with increased risks for both all-cause mortality (HR= 0.85, 95 % CI 0.77∼0.94) and cardiovascular mortality (SHR= 0.80, 95 % CI 0.67∼0.94). Consistent results were also observed when analyzing 25(OH)D as a categorical variable (quartile). Compared to group Q1, both group Q3 (HR = 0.71, 95 % CI 0.54‒0.93) and group Q4 (HR = 0.72, 95 % CI 0.55‒0.94) exhibited a significantly reduced mortality risk. Weighted restricted cubic splines revealed an inverse J-shaped linear association between levels of 25(OH) D and all-cause mortality ((PNonliner > 0.05). Subgroup analysis and sensitivity analysis yielded similar findings., Conclusions: All-cause mortality and cardiovascular disease-related mortality were significantly increased by lower 25(OH)D levels, both as continuous and categorical variables. 25(OH)D has an inverse J-shaped linear association with all-cause and cardiovascular mortality., Competing Interests: Conflicts of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 HCFMUSP. Published by Elsevier España, S.L.U. All rights reserved.)

Background: Information on the causes of deaths from diarrhoea in children younger than 5 years is needed to design improved preventive and therapeutic approaches. We aimed to conduct a systematic analysis of studies to report estimates of the causes of deaths from diarrhoea in children younger than 5 years at global and regional levels during 2000-21., Methods: For this systematic review and Bayesian multinomial analysis, we included 12 pathogens with the highest attributable incidence in the Global Enteric Multicenter Study. We searched PubMed, Scopus, Embase, Web of Science, Global Health Index Medicus, Global Health OVID, IndMed, Health Information Platform for the Americas (PLISA), Africa-Wide Information, and Cochrane Collaboration for articles published between Jan 1, 2000, and Dec 31, 2020, using the search terms "child", "hospital", "diarrhea", "diarrhoea", "dysentery", "rotavirus", "Escherichia coli", "salmonella", "shigella", "campylobacter", "Vibrio cholerae", "cryptosporidium", "norovirus", "astrovirus", "sapovirus", and "adenovirus". To be included, studies had to have a patient population of children younger than 5 years who were hospitalised for diarrhoea (at least 90% of study participants), at least a 12-month duration, reported prevalence in diarrhoeal stools of at least two of the 12 pathogens, all patients with diarrhoea being included at the study site or a systematic sample, at least 100 patients with diarrhoea, laboratory tests done on rectal swabs or stool samples, and standard laboratory methods (ie, quantitative PCR [qPCR] or non-qPCR). Studies published in any language were included. Studies were excluded if they were limited to nosocomial, chronic, antibiotic-associated, or outbreak diarrhoea or to a specific population (eg, only children with HIV or AIDS). Each article was independently reviewed by two researchers; a third arbitrated in case of disagreement. If both reviewers identified an exclusion criterion, the study was excluded. Data sought were summary estimates. Data on causes from published studies were adjusted when necessary to account for the poor sensitivity of non-qPCR methods and for attributable fraction based on quantification of pathogens in children who are ill or non-ill. The causes of deaths from diarrhoea were modelled on the causes of hospitalisations for diarrhoea. We separately modelled studies reporting causes of diarrhoea in children who were hospitalised in low-income and middle-income countries (LMICs) and in high-income countries (HICs)., Findings: Of 74 282 papers identified in the initial database search, we included 138 studies (91 included data from LMICs and 47 included data from HICs) from 73 countries. We modelled estimates for 194 WHO member states (hereafter referred to as countries), including 42 HICs and 152 LMICs. We could attribute a cause to 1 003 448 (83·8%) of the estimated 1 197 044 global deaths from diarrhoea in children younger than 5 years in 2000 and 360 730 (81·3%) of the estimated 443 833 global deaths from diarrhoea in children younger than 5 years in 2021. The cause with the largest estimated global attribution was rotavirus; in LMICs, the proportion of deaths from diarrhoea due to rotavirus in children younger than 5 years appeared lower in 2021 (108 322 [24·4%] of 443 342, 95% uncertainty interval 21·6-29·5) than in 2000 (316 382 [26·5%] of 1 196 134, 25·7-28·5), but the 95% CIs overlapped. In 2000, the second largest estimated attribution was norovirus GII (95 817 [8·0%] of 1 196 134 in LMICs and 225 [24·7%] of 910 in HICs); in 2021, Shigella sp had the second largest estimated attribution in LMICs (36 082 [8·1%] of 443 342), but norovirus remained with the second largest estimated attribution in HICs (84 [17·1%] of 490)., Interpretation: Our results indicate progress in the reduction of deaths from diarrhoea caused by 12 pathogens in children younger than 5 years in the past two decades. There is a need to increase efforts for prevention, including with rotavirus vaccine, and treatment to eliminate further deaths., Funding: Bill & Melinda Gates Foundation via Johns Hopkins University and the University of Virginia., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: The Three Delays Framework was instrumental in the reduction of maternal mortality leading up to, and during the Millennium Development Goals. However, this paper suggests the original framework might be reconsidered, now that most mothers give birth in facilities, the quality and continuity of the clinical care is of growing importance. Methods: The paper explores the factors that contributed to maternal deaths in rural Pakistan and Mozambique, using 76 verbal autopsy narratives from the Community Level Interventions for Pre-eclampsia (CLIP) Trial. Results: Qualitative analysis of these maternal death narratives in both countries reveals an interplay of various influences, such as, underlying risks and comorbidities, temporary improvements after seeking care, gaps in quality care in emergencies, convoluted referral systems, and arrival at the final facility in critical condition. Evaluation of these narratives helps to reframe the pathways of maternal mortality beyond a single journey of care-seeking, to update the categories of seeking, reaching and receiving care. Conclusions: There is a need to supplement the pioneering "Three Delays Framework" to include focusing on continuity of care and the "Four Critical Connection Points": (1) between the stages of pregnancy, (2) between families and health care workers, (3) between health care facilities and (4) between multiple care-seeking journeys. Trial registration: NCT01911494, Date Registered 30/07/2013. [ABSTRACT FROM AUTHOR]

Background: Research over the past decade has suggested that prenatal and early postnatal nutrition influence the risk of developing chronic degenerative diseases up to 60 years later. We now present evidence that risk of death from infectious diseases in young adulthood is similarly programmed by early life events., Methods: In three rural Gambian villages, affected by a marked annual seasonality in diet and disease, we have kept detailed demographic, anthropometric and health records since 1949. Fate was known with certainty for 3,162 individuals (2,059 alive/1,103 dead, most dying in childhood). For this case-control analysis of antecedent predictors of premature mortality, all adult deaths (n = 61) were paired with two randomly selected controls matched for sex and year of birth., Results: Mean age at death was 25 (SD: 8) years. Adult death was associated with a profound bias in month of birth with 49 cases born in the nutritionally-debilitating hungry season (Jul-Dec) versus 12 in the harvest season (Jan-Jun). Relative to harvest season the hazard ratio for early death in hungry-season births rose from 3.7 (for deaths >14.5 years, P = 0.000013) to 10.3 (for deaths >25 years, P = 0.00002). Anthropometric and haematological status at 18 months of age was identical in cases and controls, indicating an earlier origin to the defect. Most deaths for which cause was known had a definite or possible infectious aetiology; none were from degenerative diseases of affluence., Conclusions: Early life exposures, correlated with season of birth, strongly influence susceptibility to fatal infections in young adulthood. The evidence suggests that nutritionally-mediated intrauterine growth retardation may permanently impair the development of immune function.

Although 25% of US men indicate that they are trying to lose weight, the association between intentional weight loss and longevity in men is unknown. The authors analyzed prospective data from 49,337 overweight (initial body mass index > or =27) white men aged 40-64 years who, in 1959-1960, answered questions on weight change direction, amount, time interval, and intent. Vital status was determined in 1972. Proportional hazards regression estimated mortality rate ratios for men who intentionally lost weight compared with men with no weight change. Analyses were stratified by health status and adjusted for age, initial body mass index, smoking status, alcohol intake, education, physical activity, health history, and physical symptoms. Among men with no reported health conditions (n = 36,280), intentional weight loss was not associated with total, cardiovascular (CVD), or cancer mortality, but diabetes-associated mortality was increased 48% (95% confidence interval (CI) -7% to +133%) among those who lost 20 pounds (9.1 kg) or more; this increase was largely related to non-CVD mortality. Among men with reported health conditions (n = 13,057), intentional weight loss had no association with total or CVD mortality, but cancer mortality increased 25% (95% confidence interval -4% to +63%) among those who lost 20 pounds or more. Diabetes-associated mortality was reduced 32% (95% confidence interval -52% to -5%) among those who lost less than 20 pounds and 36% (95% confidence interval -49% to -20%) among those who lost more than 20 pounds. These results and those from our earlier study in women (Williamson et al., Am J Epidemiol 1995;141:1128-41) suggest that intentional weight loss may reduce the risk of dying from diabetes, but not from CVD. In observational studies, however, it is difficult to separate intentional weight loss from unintentional weight loss due to undiagnosed, underlying disease. Well-designed observational studies, as well as randomized controlled trials, are needed to determine whether intentional weight loss reduces CVD mortality.

Mortality indicators and causes of death in Jordan were assessed by verbal autopsy. A random sample of 100 clusters of ca. 300 households each were monitored for one year by notification assistants selected from the study area itself. Registered deaths were reported to research assistants who visited the family to complete the verbal autopsy form, which was structured and contained about 100 questions. Causes of death were determined by two physicians according to preset algorithms. A total of 965 deaths were reported among 198,989 persons, giving a crude death rate of 5 per 1000 population per year. The three leading causes of death were diseases of the circulatory system, malignancies and accidents. In the absence of a health information system, verbal autopsy as implemented in Jordan can serve as a reliable substitute.

The coronavirus disease 2019 （COVID-19） has been a global epidemic for more than three years, causing more than 6.9 million deaths. COVID-19 has the clinical characteristics of strong infectivity and long incubation period, and can cause multi-system damage, mainly lung damage, clinical symptoms of acute respiratory distress syndrome （ARDS） and systemic multiple organ damage. The SARS-CoV-2 virus is still constantly mutating. At present, there is no global consensus on the pathological changes of COVID-19 associated deaths and even no consensus on the criteria for determining the cause of death. The investigation of the basic pathological changes and progression of the disease is helpful to guide the clinical treatment and the development of therapeutic drugs. This paper reviews the autopsy reports and related literature published worldwide from February 2020 to June 2023, with a clear number of autopsy cases and corresponding pathological changes of vital organs as the inclusion criteria. A total of 1 111 autopsy cases from 65 papers in 18 countries are included. Pathological manifestations and causes of death are classified and statistically analyzed, common pathological changes of COVID-19 are summarized, and analytical conclusions are drawn, suggesting that COVID-19 infection can cause life-threatening pathological changes in vital organs. On the basis of different health levels of infected groups, the direct cause of death is mainly severe lung damage and secondary systemic multiple organ failure.

COVID-19 outbreaks have had high mortality in low- and middle-income countries such as Ecuador. Human mobility is an important factor influencing the spread of diseases possibly leading to a high burden of disease at the country level. Drastic control measures, such as complete lockdown, are effective epidemic controls, yet in practice one hopes that a partial shutdown would suffice. It is an open problem to determine how much mobility can be allowed while controlling an outbreak. In this paper, we use statistical models to relate human mobility to the excess death in Ecuador while controlling for demographic factors. The mobility index provided by GRANDATA, based on mobile phone users, represents the change of number of out-of-home events with respect to a benchmark date (March 2nd, 2020). The study confirms the global trend that more men are dying than expected compared to women, and that people under 30 show less deaths than expected, particularly individuals younger than 20 with a death rate reduction between 22 and 27%. The weekly median mobility time series shows a sharp decrease in human mobility immediately after a national lockdown was declared on March 17, 2020 and a progressive increase towards the pre-lockdown level within two months. Relating median mobility to excess deaths shows a lag in its effect: first, a decrease in mobility in the previous two to three weeks decreases excess death and, more novel, we found an increase of mobility variability four weeks prior increases the number of excess deaths., (© 2022. The Author(s).)

The availability of models for predicting future events is essential for enhancing the efficiency of systems. This paper attempts to predict demographic variation by employing multi-layer perceptron network. Here we present the implementation of a system for predicting the number and causes of deaths, for a future 2-year period. The system was built using predictive models and data that is as accurate as possible under the current conditions of the northern Region of Iraq (the Autonomous Region of Kurdistan). Our predictive model is based on quarterly periods, with the intention of providing predictions on the number of deaths, classified by gender, cause of death, age at death, administrative district (governorate), and hospital where the death occurred. The data was collected from birth and death registry bureaus and forensic medicine departments for the years 2009–2020. The python programming language was used to test the designed multi-layer perceptron network with backpropagation training algorithm. With learning rate 0.01 and 500 epochs we were able to obtain good results, as the neural network was able to represent the string, and predict future values well, with a mean squared error of 0.43, and we found that number of deaths is quite stable, with a slight increase. [ABSTRACT FROM AUTHOR]

Background: The current burden of >5 million deaths yearly is the focus of the Sustainable Development Goal (SDG) to end preventable deaths of newborns and children under 5 years old by 2030. To accelerate progression toward this goal, data are needed that accurately quantify the leading causes of death, so that interventions can target the common causes. By adding postmortem pathology and microbiology studies to other available data, the Child Health and Mortality Prevention Surveillance (CHAMPS) network provides comprehensive evaluations of conditions leading to death, in contrast to standard methods that rely on data from medical records and verbal autopsy and report only a single underlying condition. We analyzed CHAMPS data to characterize the value of considering multiple causes of death., Methods and Findings: We examined deaths identified from December 2016 through November 2020 from 7 CHAMPS sites (in Bangladesh, Ethiopia, Kenya, Mali, Mozambique, Sierra Leone, and South Africa), including 741 neonatal, 278 infant, and 241 child <5 years deaths for which results from Determination of Cause of Death (DeCoDe) panels were complete. DeCoDe panelists included all conditions in the causal chain according to the ICD-10 guidelines and assessed if prevention or effective management of the condition would have prevented the death. We analyzed the distribution of all conditions listed as causal, including underlying, antecedent, and immediate causes of death. Among 1,232 deaths with an underlying condition determined, we found a range of 0 to 6 (mean 1.5, IQR 0 to 2) additional conditions in the causal chain leading to death. While pathology provides very helpful clues, we cannot always be certain that conditions identified led to death or occurred in an agonal stage of death. For neonates, preterm birth complications (most commonly respiratory distress syndrome) were the most common underlying condition (n = 282, 38%); among those with preterm birth complications, 256 (91%) had additional conditions in causal chains, including 184 (65%) with a different preterm birth complication, 128 (45%) with neonatal sepsis, 69 (24%) with lower respiratory infection (LRI), 60 (21%) with meningitis, and 25 (9%) with perinatal asphyxia/hypoxia. Of the 278 infant deaths, 212 (79%) had ≥1 additional cause of death (CoD) beyond the underlying cause. The 2 most common underlying conditions in infants were malnutrition and congenital birth defects; LRI and sepsis were the most common additional conditions in causal chains, each accounting for approximately half of deaths with either underlying condition. Of the 241 child deaths, 178 (75%) had ≥1 additional condition. Among 46 child deaths with malnutrition as the underlying condition, all had ≥1 other condition in the causal chain, most commonly sepsis, followed by LRI, malaria, and diarrheal disease. Including all positions in the causal chain for neonatal deaths resulted in 19-fold and 11-fold increases in attributable roles for meningitis and LRI, respectively. For infant deaths, the proportion caused by meningitis and sepsis increased by 16-fold and 11-fold, respectively; for child deaths, sepsis and LRI are increased 12-fold and 10-fold, respectively. While comprehensive CoD determinations were done for a substantial number of deaths, there is potential for bias regarding which deaths in surveillance areas underwent minimally invasive tissue sampling (MITS), potentially reducing representativeness of findings., Conclusions: Including conditions that appear anywhere in the causal chain, rather than considering underlying condition alone, markedly changed the proportion of deaths attributed to various diagnoses, especially LRI, sepsis, and meningitis. While CHAMPS methods cannot determine when 2 conditions cause death independently or may be synergistic, our findings suggest that considering the chain of events leading to death can better guide research and prevention priorities aimed at reducing child deaths., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: QB, a co-author of this paper is also a Guest Editor on this special issue on Global Child Health: From Birth to Adolescence and Beyond. QB was not directly involved in editorial decisions regarding this paper. JAGS reports current funding for other projects to his institution (London School of Hygiene & Tropical Medicine) from the UK Medical Research Council, Wellcome Trust, Gavi, Bill & Melinda Gates Foundation, and the UK National Institute for Health Research.

This paper quantifies the net impact (direct and indirect effects) of the pandemic on the United States population in 2020 using three metrics: excess deaths, life expectancy, and total years of life lost. The findings indicate there were 375,235 excess deaths, with 83% attributable to direct, and 17% attributable to indirect effects of COVID-19. The decrease in life expectancy was 1.67 years, translating to a reversion of 14 years in historical life expectancy gains. Total years of life lost in 2020 was 7,362,555 across the USA (73% directly attributable, 27% indirectly attributable to COVID-19), with considerable heterogeneity at the individual state level., Competing Interests: The authors have declared that no competing interests exist.

Abstract Background The Three Delays Framework was instrumental in the reduction of maternal mortality leading up to, and during the Millennium Development Goals. However, this paper suggests the original framework might be reconsidered, now that most mothers give birth in facilities, the quality and continuity of the clinical care is of growing importance. Methods The paper explores the factors that contributed to maternal deaths in rural Pakistan and Mozambique, using 76 verbal autopsy narratives from the Community Level Interventions for Pre-eclampsia (CLIP) Trial. Results Qualitative analysis of these maternal death narratives in both countries reveals an interplay of various influences, such as, underlying risks and comorbidities, temporary improvements after seeking care, gaps in quality care in emergencies, convoluted referral systems, and arrival at the final facility in critical condition. Evaluation of these narratives helps to reframe the pathways of maternal mortality beyond a single journey of care-seeking, to update the categories of seeking, reaching and receiving care. Conclusions There is a need to supplement the pioneering “Three Delays Framework” to include focusing on continuity of care and the “Four Critical Connection Points”: (1) between the stages of pregnancy, (2) between families and health care workers, (3) between health care facilities and (4) between multiple care-seeking journeys. Trial registration NCT01911494, Date Registered 30/07/2013.

We systematically reviewed published data on autopsies of patients who died from COVID-19 to identify pathological changes that are consistently reported in autopsies and those that were reported anecdotally, and to compare consistent findings with autopsy findings in similar diseases. The MEDLINE, Google Scholar, and Embase databases were searched for full-text articles in the English language from December 2019 to March 2021 to include publications on autopsy findings in patients whose main cause of death was COVID-19 and COVID-19-related complications. This review included 124 published papers documenting COVID-19 patient autopsies for over 1100 patients. Most frequent and consistently reported pathological findings included diffuse alveolar damage in the lungs, cardiac inflammation, and hypertrophy, vascular microthrombi, shock kidney and acute tubular necrosis, congested liver and spleen, and shock-associated changes in other organs. These findings by themselves were not unique, and were similar to other severe viral infections and septic shock. However, the frequency of diffuse alveolar damage and the extent of microvascular thrombosis were much higher among the autopsies of patients who had died from COVID-19 compared with other severe viral infections. Autopsy data confirm clinical reports of high incidences of diffuse alveolar damage and microvascular thrombosis in the most severe cases of COVID-19 that caused death. [ABSTRACT FROM AUTHOR]

Actuaries utilize demographic features such as mortality and longevity rates for pricing, valuation, and reserving life insurance and pension contracts. Capturing accurate mortality estimates requires factual mortality assumptions in mortality models. However, the dynamic and uncertain nature of mortality improvements and deteriorations necessitates better approaches in tracking mortality changes, for instance, using the causes of deaths features. This paper aims to determine temporal homogeneous clusters using unsupervised learning, a clustering approach to group causes of death based on (dis)similarity measures to set representative clusters in detection and monitoring death trends. The causes of death dataset were derived from the World Health Organization, Global Health Estimates for males and females, from 2000 to 2019, for Kenya. A hierarchical agglomerative clustering technique was implemented with modified Dynamic Time Warping distance criteria. Between 6 and 14 clusters were optimally achieved for both males and females. Using visualisations, principal clusters were detected. Over time, the causes of death trends of these clusters have demonstrated a correlated association with mortality and longevity rates, rationalizing why insurance and pension offices may include this approach as a preliminary step to undertake mortality and longevity modelling. [ABSTRACT FROM AUTHOR]

Autoimmune diseases are not always recognized as urgent health issues, despite a worldwide prevalence of 4%-5%. Most estimates come from high-income countries, as low- and middle-income countries face more issues of under-reporting. Despite this and the lack of recognition under current reporting practices, the role these diseases play in mortality must be acknowledged. In particular, considering multiple causes of death as opposed to a single cause of death results in a 1.5-4.2-fold increase in deaths classified as relating to autoimmune diseases, evidence of their share in overall mortality burden, a factor important for patient care and healthcare policy decision making. However, formulating such policies and programs for timely, appropriate diagnoses and care is stymied in low- and middle-income countries by the shortage of methodologically sound studies on mortality from systemic autoimmune diseases. This limitation exacerbates inequalities and health gaps among patients in different countries and localities. Multiple cause-of-death methodology has been validated for research on other diseases and demonstrates the mortality burden of these illnesses in countries where traditional methodological approaches, primarily based on prospective cohort studies, are not feasible. Studying mortality from systemic autoimmune diseases by analyzing multiple causes of death with data from national mortality registries is a low-cost alternative to traditional mortality analysis. The objective of this paper is to demonstrate and defend the usefulness of this approach to estimate mortality burden.

Background: The accurate attribution of death in oncologic patients is a difficult task. The patient's death is often attributed to his or her underlying cancer and therefore judged as cancer-related. We hypothesized that even though our patient's cancers were either advanced or metastatic, not all patients had died simply because of their cancer. Methods: A total of 105 patients were included in this retrospective analysis. Patient data were collected from digital and paper-based records. Cause of death was assessed from death certificate and compared to the medical autopsy reports. Discrepancies between premortem and postmortem diagnoses were classified as class I and II discrepancies. Results: Of 105 patients included, autopsy consent was obtained in 56 cases (53%). Among them, 32 of 56 were palliatively sedated, and 42/56 patients died cancer-related as confirmed by autopsy. The most common cause of death by autopsy report was multiorgan failure followed by a combination of tumor and infection, predominantly lung cancer with pneumonia. Here, 21/56 cases (37%) showed major missed diagnoses: seven cases showed class I, 10 class II, and both discrepancies. The most commonly missed diagnoses in both categories were infections, again mainly pneumonia. Conclusions: Cancer was the leading cause of death in our study population. A quarter of the patients, however, did not die due to their advanced or metastatic cancers but of potentially curable causes. We therefore conclude that it is important to consider competing causes of death when treating palliative cancer patients. In a palliative setting, the treatment of a potentially curable complication should be discussed with the patients and their families in a shared decision-making process. From our experience, many patients will decline treatment or even further diagnostics when given the option of best supportive care. [ABSTRACT FROM AUTHOR]

Purpose: The associations of high-density lipoprotein cholesterol (HDL-C) with mortality are still unclear. We explored the associations of HDL-C with all-cause and cause-specific mortality in an adult population., Methods: Deaths were classified into all-cause, cardiovascular, and cancer mortality. Survival curve, multivariate Cox regression, and subgroup analyses were conducted, and hazard ratio (HR) and 95% confidence interval (CI) were performed. We fitted Cox regression models for all-cause, cardiovascular, and cancer mortality to evaluate their associations with categories of HDL-C (≤30, 31-40, 41-50, 51-60 [reference], 61-70, >70 mg/dL)., Results: A total of 42,145 (20,415 (48.44%) males, mean age 47.12±19.40 years) subjects were enrolled. At an average follow-up of 97.52±54.03 months, all-cause, cardiovascular, and cancer mortality numbers were 5,061 (12.01), 1,081 (2.56%), and 1,061 (2.52%), respectively. When compared with the reference group (HDL-C: 51-60 mg/dL), a U-shaped association was apparent for all-cause mortality, with elevated risk in participants with the lowest (≤30 mg/dL) (HR=1.33; 95% CI=1.14- 1.56) and highest (>70 mg/dL) (HR=1.14; 95% CI=1.02-1.27) HDL-C concentration. Associations for cardiovascular and cancer mortality were non-linear. An elevated risk for cancer mortality was observed in those with the highest HDL-C concentration (HR=1.06; 95% CI-0.84-1.34) compared with the reference group, although it was not statistically significant. The effect of HDL-C on mortality was adjusted by some traditional risk factors including age, gender, race, or comorbidities., Conclusion: A U-shaped association was observed between HDL-C and all-cause mortality among an adult population., Competing Interests: The authors of this paper reported no financial conflicts of interest., (© 2020 Huang et al.)

We examined family isolation, economic hardship, and long-distance migration as potential patterns of an extreme outcome of a lonely death: bodily remains that remain unclaimed and are left to the state. This paper combines a unique dataset-Los Angeles County's records of unclaimed deaths-with the Vital Statistics' Mortality data and the Annual Social and Economic Survey (ASEC) to examine 1) whose remains are more likely to become unclaimed after death and, 2) whether population-level differences and trends in family isolation, economic hardship, and long-distance migration explain the differences in the rates of unclaimed deaths. We employ multivariate Poisson models to estimate relative rates of unclaimed deaths by social and demographic characteristics. We find that increases in never married, divorced/separated, and living without family were positively associated with rates of unclaimed deaths. Unemployment among men and poverty among women was associated with higher unclaimed deaths. Long-distance migration was not associated with more unclaimed bodies., Competing Interests: The authors have declared that no competing interests exist.

Measurement of alcohol use and associated harms at the city level is often incomplete or non-existent even though such data are often critical to informing local prevention strategies. This paper models how to generate local estimates of the morbidity, mortality, and cost of current alcohol use instead of abstaining. Administrative data sources, including medical examiner records, hospital records, and police records, among others, were used to obtain local estimates of alcohol-attributable outcomes. In 2018, we used alcohol-attributable fractions and scaled national estimates to quantify the burden of current alcohol use in Baltimore, MD, in 2013. Fifty-two percent of Baltimore adults reported past 30-day drinking. There were 276 alcohol-attributable deaths in 2013, and 106 (38.4%) of these were persons other than the drinker. In 2013, current alcohol use cost $582.3 million in Baltimore City. This burden was distributed across drinkers (40.1%), persons other than the drinker (21.3%), and the government (38.6%). It is possible to quantify this burden at the local level, and these data could be used to inform evidence-based alcohol policy strategies at the local level.

Life expectancy at a given age is a summary measure of mortality rates present in a population (estimated as the area under the survival curve), and represents the average number of years an individual at that age is expected to live if current age-specific mortality rates apply now and in the future. A complementary metric is the number of Life Years Lost, which is used to measure the reduction in life expectancy for a specific group of persons, for example those diagnosed with a specific disease or condition (e.g. smoking). However, calculation of life expectancy among those with a specific disease is not straightforward for diseases that are not present at birth, and previous studies have considered a fixed age at onset of the disease, e.g. at age 15 or 20 years. In this paper, we present the R package lillies (freely available through the Comprehensive R Archive Network; CRAN) to guide the reader on how to implement a recently-introduced method to estimate excess Life Years Lost associated with a disease or condition that overcomes these limitations. In addition, we show how to decompose the total number of Life Years Lost into specific causes of death through a competing risks model, and how to calculate confidence intervals for the estimates using non-parametric bootstrap. We provide a description on how to use the method when the researcher has access to individual-level data (e.g. electronic healthcare and mortality records) and when only aggregated-level data are available., Competing Interests: The authors have declared that no competing interests exist.

Background: Because most deaths in Africa and Asia are not well documented, estimates of mortality are often made using scanty data. The INDEPTH Network works to alleviate this problem by collating detailed individual data from defined Health and Demographic Surveillance sites. By registering all deaths over time and carrying out verbal autopsies to determine cause of death across many such sites, using standardised methods, the Network seeks to generate population-based mortality statistics that are not otherwise available. Objective: To build a large standardised mortality database from African and Asian sites, detailing the relevant methods, and use it to describe cause-specific mortality patterns. Design: Individual demographic and verbal autopsy (VA) data from 22 INDEPTH sites were collated into a standardised database. The INDEPTH 2013 population was used for standardisation. The WHO 2012 VA standard and the InterVA-4 model were used for assigning cause of death. Results: A total of 111,910 deaths occurring over 12,204,043 person-years (accumulated between 1992 and 2012) were registered across the 22 sites, and for 98,429 of these deaths (88.0%) verbal autopsies were successfully completed. There was considerable variation in all-cause mortality between sites, with most of the differences being accounted for by variations in infectious causes as a proportion of all deaths. Conclusions: This dataset documents individual deaths across Africa and Asia in a standardised way, and on an unprecedented scale. While INDEPTH sites are not constructed to constitute a representative sample, and VA may not be the ideal method of determining cause of death, nevertheless these findings represent detailed mortality patterns for parts of the world that are severely under-served in terms of measuring mortality. Further papers explore details of mortality patterns among children and specifically for NCDs, external causes, pregnancy-related mortality, malaria, and HIV/AIDS. Comparisons will also be made where possible with other findings on mortality in the same regions. Findings presented here and in accompanying papers support the need for continued work towards much wider implementation of universal civil registration of deaths by cause on a worldwide basis. [ABSTRACT FROM AUTHOR]

Objectives: This paper analyses the patterns and trends in the mortality rates of infants and children under the age of 5 in India (1992-2016) and quantifies the variation in performance between different geographical states through three rounds of nationally representative household surveys., Design: Three rounds of cross-sectional survey data., Setting: The study is conducted at the national level: India and its selected good-performing states, namely Haryana, Kerala, Maharashtra, Punjab and Tamil Nadu, and selected poor-performing states, namely Bihar, Chhattisgarh, Madhya Pradesh and Uttar Pradesh., Participants: Adopting a multistage, stratified random sampling, 601 509 households with 699 686 women aged 15-49 years in 2015-2016, 109 041 households with 124 385 women aged 15-49 years in 2005-2006, and 88 562 households with 89 777 ever married women in the age group 13-49 years in 1992-1993 were selected., Results: Through the use of maps, this paper clearly shows that the overall trend in infant and child mortality is on a decline in India. Computation of relative change shows that majority of the states have witnessed over 50% reduction in both infant and under-5 mortality rates from National Family Health Survey (NFHS)-I to NFHS-4. However, the improvements are not evenly distributed, and there is huge variation in performance between states over time. Funnel plots show that the most populous states like Uttar Pradesh Bihar and Madhya Pradesh have underperformed consistently across the survey period from 1992 to 2016. Regression analysis comparing high-performing and low-performing states revealed that female infants and women with shorter birth intervals had greater risk of infant deaths in poor-performing states., Conclusion: Attempts to reduce infant and child mortality rates in India are heading in the right direction. Even so, there is huge variation in performance between states. This paper recommends a mix of strategies that reduce child and infant mortality among the high-impact states where the biggest improvements can be expected, including the need to address neonatal mortality., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The World Health Organization recommends a minimum requirement of 0.8 g/day protein/kg ideal weight. Low protein diets are used against kidney failure progression. Efficacy and safety of these diets are uncertain. This paper reviews epidemiological studies about associations of protein intake with kidney function decline and mortality. Three studies investigated these associations; two reported data on mortality. Protein intake averaged >60 g/day and 1.2 g/day/kg ideal weight. An association of baseline protein intake with long-term kidney function decline was absent in the general population and/or persons with normal kidney function but was significantly positive in persons with below-normal kidney function. Independent of kidney function and other confounders, a J-curve relationship was found between baseline protein intake and mortality due to ≈35% mortality excess for non-cardiovascular disease in the lowest quintile of protein intake, a quintile where protein intake averaged <0.8 g/day/kg ideal weight. Altogether, epidemiological evidence suggests that, in patients with reduced kidney function, protein intakes of ≈0.8 g/d/kg ideal weight could limit kidney function decline without adding non-renal risks. Long-term lower protein intake could increase mortality. In most patients, an intake of ≈0.8 g/day/kg would represent a substantial reduction of habitual intake considering that average intake is largely higher., Competing Interests: The authors declare no conflict of interest.

Half of the world's deaths and their causes pass unrecorded by routine registration systems, particularly in low- and middle-income countries. Verbal autopsy (VA) collects information on medical signs, symptoms and circumstances from witnesses of a death that is used to assign likely medical causes. To further contextualise information on mortality, understanding underlying determinants, such as logistics, barriers to service utilisation and health systems responses, is important for health planning. Adding systematic methods for categorising circumstantial determinants of death to conventional VA tools is therefore important. In this context, the World Health Organization (WHO) leads the development of international standards for VA, and added questions on the social and health systems circumstances of death in 2012. This paper introduces a pragmatic and scalable approach for assigning relevant Circumstances Of Mortality CATegories (COMCATs) within VA tools, and examines their consistency, reproducibility and plausibility for health policy making, as well as assessing additional effort and cost to the routine VA process. This innovative COMCAT model is integrated with InterVA-5 software (which processes WHO-2016 VA data), for assigning numeric likelihoods to six circumstantial categories for each death. VA data from 4,116 deaths in the Agincourt Health and Socio-Demographic Surveillance System in South Africa from 2012 to 2016 were used to demonstrate proof of principle for COMCATs. Lack of resources to access health care, poor recognition of diseases and inadequate health systems responses ranked highest among COMCATs in the demonstration dataset. COMCATs correlated plausibly with age, sex, causes of death and local knowledge of the demonstration population. The COMCAT approach appears to be plausible, feasible and enhances the functionality of routine VA to account for critical limiting circumstances at and around the time of death. It is a promising tool for evaluating progress towards the Sustainable Development Goals and the roll-out of Universal Health Coverage.

Learning dependence relationships among variables of mixed types provides insights in a variety of scientific settings and is a well-studied problem in statistics. Existing methods, however, typically rely on copious, high quality data to accurately learn associations. In this paper, we develop a method for scientific settings where learning dependence structure is essential, but data are sparse and have a high fraction of missing values. Specifically, our work is motivated by survey-based cause of death assessments known as verbal autopsies (VAs). We propose a Bayesian approach to characterize dependence relationships using a latent Gaussian graphical model that incorporates informative priors on the marginal distributions of the variables. We demonstrate such information can improve estimation of the dependence structure, especially in settings with little training data. We show that our method can be integrated into existing probabilistic cause-of-death assignment algorithms and improves model performance while recovering dependence patterns between symptoms that can inform efficient questionnaire design in future data collection. [ABSTRACT FROM AUTHOR]

Background: Triangulating findings from MDSR with other sources can better inform maternal health programs. A national Emergency Obstetric and Newborn Care (EmONC) assessment and the Maternal Death Surveillance and Response (MDSR) system provided data to determine the coverage of MDSR implementation in health facilities, the leading causes and contributing factors to death, and the extent to which life-saving interventions were provided to deceased women.Methods: This paper is based on triangulation of findings from a descriptive analysis of secondary data extracted from the 2016 EmONC assessment and the MDSR system databases. EmONC assessment was conducted in 3804 health facilities. Data from interview of each facility leader on MDSR implementation, review of 1305 registered maternal deaths and 679 chart reviews of maternal deaths that happened form May 16, 2015 to December 15, 2016 were included from the EmONC assessment. Case summary reports of 601 reviewed maternal deaths were included from the MDSR system.Results: A maternal death review committee was established in 64% of health facilities. 5.5% of facilities had submitted at least one maternal death summary report to the national MDSR database. Postpartum hemorrhage (10-27%) and severe preeclampsia/eclampsia (10-24.1%) were the leading primary causes of maternal death. In MDSR, delay-1 factors contributed to 7-33% of maternal deaths. Delay-2, related to reaching a facility, contributed to 32% & 40% of maternal deaths in the EmONC assessment and MDSR, respectively. Similarly, delay-3 factor due to delayed transfer of mothers to appropriate level of care contributed for 29 and 22% of maternal deaths. From the EmONC data, 72% of the women who died due to severe pre-eclampsia or eclampsia were given anticonvulsants while 48% of those dying of postpartum haemorrhage received uterotonics.Conclusion: The facility level implementation coverage of MDSR was sub-optimal. Obstetric hemorrhage and severe preeclampsia or eclampsia were the leading causes of maternal death. Delayed arrival to facility (Delay 2) was the predominant contributing factor to facility-based maternal deaths. The limited EmONC provision should be the focus of quality improvement in health facilities. [ABSTRACT FROM AUTHOR]

Background: Globally, an estimated two-thirds of all deaths occur in the community, the majority of which are not attended by a physician and remain unregistered. Identifying and registering these deaths in civil registration and vital statistics (CRVS) systems, and ascertaining the cause of death, is thus a critical challenge to ensure that policy benefits from reliable evidence on mortality levels and patterns in populations. In contrast to traditional processes for registration, death notification can be faster and more efficient at informing responsible government agencies about the event and at triggering a verbal autopsy for ascertaining cause of death. Thus, innovative approaches to death notification, tailored to suit the setting, can improve the availability and quality of information on community deaths in CRVS systems.Improving the Notification Of Community Deaths: Here, we present case studies in four countries (Bangladesh, Colombia, Myanmar and Papua New Guinea) that were part of the initial phases of the Bloomberg Data for Health Initiative at the University of Melbourne, each of which faces unique challenges to community death registration. The approaches taken promote improved notification of community deaths through a combination of interventions, including integration with the health sector, using various notifying agents and methods, and the application of information and communication technologies. One key factor for success has been the smoothing of processes linking notification, registration and initiation of a verbal autopsy interview. The processes implemented champion more active notification systems in relation to the passive systems commonly in place in these countries.Conclusions: The case studies demonstrate the significant potential for improving death reporting through the implementation of notification practices tailored to a country's specific circumstances, including geography, cultural factors, structure of the existing CRVS system, and available human, information and communication technology resources. Strategic deployment of some, or all, of these innovations can result in rapid improvements to death notification systems and should be trialled in other settings. [ABSTRACT FROM AUTHOR]

Background: Despite attempts to apply standard methods proven to work in high-income nations, nearly all civil registration and vital statistics (CRVS) systems in low- and middle-income countries are failing to achieve adequate levels of registration completeness or produce the high-quality vital statistics needed to support better health outcomes and monitor progress towards the 2030 Sustainable Development Goals. This suggests that, rather than simple technical issues, these countries are facing additional or different systemic challenges, including duplication of roles and responsibilities, inefficient methods of data collection, and a reluctance to change.Applying Process Management: Process management is a valuable tool that strengthens the production of vital statistics by providing a visualisation of data flow from start to finish. It helps identify gaps and bottlenecks in the process, allowing stakeholders to work collaboratively to find solutions and target interventions. As part of the Bloomberg Philanthropies Data for Health Initiative at the University of Melbourne, 16 countries were supported in mapping the varied processes required in registering a birth or death. Comparative analysis exposed several limitations in the design of CRVS systems that hinder their performance - from 'passive' systems, to overly complex and fragmented system design, through to poor collaboration and duplication of efforts.Conclusions: The experiences from Myanmar, Papua New Guinea and Rwanda reported in this paper illustrate the benefits of process management to improve CRVS. While these three countries are at different stages of system development, each uniquely benefited. Process management is a useful tool for all CRVS systems, from the most rudimentary to the most developed. It can strengthen CRVS systems and improve the quality and completeness of vital statistics, resulting in more robust, reliable and timely vital statistics for health planning and better monitoring of the 2030 Sustainable Development Goal agenda. [ABSTRACT FROM AUTHOR]

The 2011 Tohoku earthquake and tsunami caused the loss of 20,000 lives in Japan. According to the National Police Agency (2012), 90% of deaths in the Iwate, Miyagi, and Fukushima prefectures were due to drowning. On the other hand, this report also showed that the remaining 10% died from circumstances other than drowning, as suggested by the Japanese Society of Legal Medicine (2012). A new solution is needed to propose practical measures against a tsunami. In this paper, the authors suggest the science of human survival from disaster as one of the solutions and illustrate the research design implemented to build it. Constructing the science of human survival shall be important to mitigate human damages in future tsunami disasters. [ABSTRACT FROM AUTHOR]

This data note provides details of the development of a Verbal Autopsy (VA) dataset produced with the South African Population Research Infrastructure Network (SAPRIN) drawing on datasets from health and socio-demographic surveillance sites’ (HDSS) ‘ covering a population of over 250,000 in two rural provinces in South Africa for the period 2012–2019. The purpose of the data set was to refine an analytical tool within VA, which provides unique information on care seeking and utilisation at and around the time of death complementary to that of medical cause of death. On an individual basis, the dataset includes demographic data, probable cause of death data, and data on care seeking and utilisation at or around the time of death drawn from longitudinal population cohorts. The purpose of this publication is to describe both the dataset and methods in formatting and processing the data for other researchers who may be interested in similar data. The data described in this paper are available to be requested from the respective HDSS repositories.

There is no nationwide necropsy database of animals in Japan, and most of the records are available from the postwar period. To clarify the chronological transition of animal necropsy cases in Tokyo, Japan, the records accumulated in The University of Tokyo from 1902 were investigated. Of necropsy records on paper or electronic from 1902 to 2021 kept at the Laboratory of Veterinary Pathology, The University of Tokyo, totally 3,137 cases including 572 in 1903-1914 (the Meiji-Taisho period), 1,258 in 1956-1969 (the Showa period) and 1,307 in 2006-2020 (the Heisei-Reiwa period), respectively, were examined for species, breed, age and pathological diagnosis. Dogs (44.6%) and horses (34.8%) in the Meiji-Taisho period, dogs (62.9%) and cats (17.3%) in the Showa period, and dogs (46.0%), cats (26.1%) and exotic animals (20.5%) in the Heisei-Reiwa period were the most necropsied animal species. With the passage of time, the number of animal species increased, and the breeds of dogs and cats came to be more various. The median ages of death were 2 years, 3 years and 10 years old in dogs in the Meiji-Taisho, Showa and Heisei-Reiwa periods, respectively, and 2 years and 10 years old in cats in the Showa and Heisei-Reiwa periods, respectively. Viral, bacterial and parasitic infections were decreased, and inversely tumor cases increased due to the prolonged lifespan. [ABSTRACT FROM AUTHOR]

Background Consumption of alcohol is a risk factor for non-communicable and infectious diseases, mental health problems, and can lead injuries and violence. The aim of this study was to evaluate the prevalence of alcohol-involved deaths among decedents who died of external causes and underwent autopsy in Lithuania. Methods Study includes age persons of any age (from 0 to 110 years) who died and were autopsied in Lithuania from 1 January 2017 to 31 December 2020. Data were obtained from the Lithuanian State Register of Deaths and Their Causes. Results Among external causes of death, the presence of alcohol was detected in 55.0% of cases. Male decedents had a significantly higher number of positive BAC level recorded, at 46.6%, compared with female decedents (32.1%; P  < 0.001). The highest incidence of deaths where the alcohol was detected in the deceased's blood was found when the decedent was listed as being in the victims of assault group (71.5%, 95% CI 65.4–77.2). However, the highest median BAC score was found for those in the accidents group (59.7%, 95% CI: 58.2–61.2, BAC 2.42 ‰, IQR 1.86). Conclusions The findings of this study suggest that alcohol use may be a contributing factor in a wide range of fatal incidents, including accidents, injuries, and cases of violent intent. Inequalities between males and females were identified, with a higher proportion of males with alcohol detected in blood at the time of death. [ABSTRACT FROM AUTHOR]

The gender gap in life expectancy (GGLE) varies substantially in EU 28 Member States. This paper addresses the question of whether gender inequality affects the GGLE as well as life expectancy (LE) in both genders. We conducted an ecological study and used the gender inequality index (GII) developed by the United Nations as well as the gender difference in LE in 2015. We found a correlation between GGLE and GII (r2=0.180) and between GII and LE of 0.418 (women) and 0.430 (men). Gender equality policies are still necessary and will have an effect on women's as well as men's health.

Significant increases in excess all-cause mortality, particularly in the elderly, were observed during the winter of 2014/15 in England. With influenza A(H3N2) the dominant circulating influenza A subtype, this paper determines the contribution of influenza to this excess controlling for weather. A standardised multivariable Poisson regression model was employed with weekly all-cause deaths the dependent variable for the period 2008-2015. Adjusting for extreme temperature, a total of 26 542 (95% CI 25 301-27 804) deaths in 65+ and 1942 (95% CI 1834-2052) in 15-64-year-olds were associated with influenza from week 40, 2014 to week 20, 2015. This is compatible with the circulation of influenza A(H3N2). It is the largest estimated number of influenza-related deaths in England since prior to 2008/09. The findings highlight the potential health impact of influenza and the important role of the annual influenza vaccination programme that is required to protect the population including the elderly, who are vulnerable to a severe outcome.

Background: Recently, a new algorithm for automatic computer certification of verbal autopsy data named InSilicoVA was published. The authors presented their algorithm as a statistical method and assessed its performance using a single set of model predictors and one age group., Methods: We perform a standard procedure for analyzing the predictive accuracy of verbal autopsy classification methods using the same data and the publicly available implementation of the algorithm released by the authors. We extend the original analysis to include children and neonates, instead of only adults, and test accuracy using different sets of predictors, including the set used in the original paper and a set that matches the released software., Results: The population-level performance (i.e., predictive accuracy) of the algorithm varied from 2.1 to 37.6% when trained on data preprocessed similarly as in the original study. When trained on data that matched the software default format, the performance ranged from -11.5 to 17.5%. When using the default training data provided, the performance ranged from -59.4 to -38.5%. Overall, the InSilicoVA predictive accuracy was found to be 11.6-8.2 percentage points lower than that of an alternative algorithm. Additionally, the sensitivity for InSilicoVA was consistently lower than that for an alternative diagnostic algorithm (Tariff 2.0), although the specificity was comparable., Conclusions: The default format and training data provided by the software lead to results that are at best suboptimal, with poor cause-of-death predictive performance. This method is likely to generate erroneous cause of death predictions and, even if properly configured, is not as accurate as alternative automated diagnostic methods.

Background: Digoxin is widely used in patients with atrial fibrillation (AF)., Objectives: The goal of this paper was to explore whether digoxin use was independently associated with increased mortality in patients with AF and if the association was modified by heart failure and/or serum digoxin concentration., Methods: The association between digoxin use and mortality was assessed in 17,897 patients by using a propensity score-adjusted analysis and in new digoxin users during the trial versus propensity score-matched control participants. The authors investigated the independent association between serum digoxin concentration and mortality after multivariable adjustment., Results: At baseline, 5,824 (32.5%) patients were receiving digoxin. Baseline digoxin use was not associated with an increased risk of death (adjusted hazard ratio [HR]: 1.09; 95% confidence interval [CI]: 0.96 to 1.23; p = 0.19). However, patients with a serum digoxin concentration ≥1.2 ng/ml had a 56% increased hazard of mortality (adjusted HR: 1.56; 95% CI: 1.20 to 2.04) compared with those not on digoxin. When analyzed as a continuous variable, serum digoxin concentration was associated with a 19% higher adjusted hazard of death for each 0.5-ng/ml increase (p = 0.0010); these results were similar for patients with and without heart failure. Compared with propensity score-matched control participants, the risk of death (adjusted HR: 1.78; 95% CI: 1.37 to 2.31) and sudden death (adjusted HR: 2.14; 95% CI: 1.11 to 4.12) was significantly higher in new digoxin users., Conclusions: In patients with AF taking digoxin, the risk of death was independently related to serum digoxin concentration and was highest in patients with concentrations ≥1.2 ng/ml. Initiating digoxin was independently associated with higher mortality in patients with AF, regardless of heart failure., (Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: There is increasing interest in using verbal autopsy to produce nationally representative population-level estimates of causes of death. However, the burden of processing a large quantity of surveys collected with paper and pencil has been a barrier to scaling up verbal autopsy surveillance. Direct electronic data capture has been used in other large-scale surveys and can be used in verbal autopsy as well, to reduce time and cost of going from collected data to actionable information., Methods: We collected verbal autopsy interviews using paper and pencil and using electronic tablets at two sites, and measured the cost and time required to process the surveys for analysis. From these cost and time data, we extrapolated costs associated with conducting large-scale surveillance with verbal autopsy., Results: We found that the median time between data collection and data entry for surveys collected on paper and pencil was approximately 3 months. For surveys collected on electronic tablets, this was less than 2 days. For small-scale surveys, we found that the upfront costs of purchasing electronic tablets was the primary cost and resulted in a higher total cost. For large-scale surveys, the costs associated with data entry exceeded the cost of the tablets, so electronic data capture provides both a quicker and cheaper method of data collection., Conclusions: As countries increase verbal autopsy surveillance, it is important to consider the best way to design sustainable systems for data collection. Electronic data capture has the potential to greatly reduce the time and costs associated with data collection. For long-term, large-scale surveillance required by national vital statistical systems, electronic data capture reduces costs and allows data to be available sooner.

Introduction: Verbal autopsy (VA) is a method that determines the cause of death by interviewing a relative of the deceased about the events occurring before the death, in regions where medical certification of cause of death is incomplete. This paper aims to review the ethical standards reported in peer-reviewed VA studies., Methods: A systematic review of Medline and Ovid was conducted by two independent researchers. Data were extracted and analysed for articles based on three key areas: Institutional Review Board (IRB) clearance and consenting process; data collection and management procedures, including: time between death and interview; training and education of interviewer, confidentiality of data and data security; and declarations of funding and conflict of interest., Results: The review identified 802 articles, of which 288 were included. The review found that 48% all the studies reported having IRB clearance or obtaining consent of participants. The interviewer training and education levels were reported in 62% and 21% of the articles, respectively. Confidentiality of data was reported for 14% of all studies, 18% did not report the type of respondent interviewed and 51% reported time between death and the interview for the VA. Data security was reported in 8% of all studies. Funding was declared in 63% of all studies and conflict of interest in 42%. Reporting of all these variables increased over time., Conclusions: The results of this systematic review show that although there has been an increase in ethical reporting for VA studies, there still remains a large gap in reporting., (© The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association)

One of the tasks of the forensic specialist is to attempt to determine the interval between fatal injuries and death, and to assess whether the victim could be physically active before death and, if so, to what extent. There is ongoing research aimed at the application of additional tests (histological, immunohistochemical and others) to answer these questions. Unfortunately, currently used methods have numerous limitations and require further improvements. Moreover, they are not commonly employed in medicolegal practice in Poland. The greatest difficulty in assessing the time of survival and activity occurs when the period is relatively short (seconds-minutes-hours). Therefore, in practice, injury examination is often the only tool to assess the interval between fatal injuries and death, and the possibility of physical activity during that time. The aim of the paper is review the literature on this topic with a focus on biological methods and attempt to find a correlation between the nature of injuries and survival time, and between the nature of injuries and the capability to be physically active. An analysis of available cases has shown that unfortunately, on account of numerous limitations, the approach with the exception of specific situations, allows determining at most an approximate time interval during which the victim could be alive and active.