Death Certificates Research Articles

Decedents Found in Bathtubs.

We investigated deaths in bathtubs for criteria to assist in death certification. We reviewed 252 deaths in which the person was found dead in a bathtub/shower at home. We extracted cause, manner, age, clad or unclad, water in the bathtub, water running, and face submersion. Of the 252 deaths, heart disease was the leading cause of death (129), followed by intoxication (47), trauma (22), drowning (28), and other diseases (26). The manners of death were 155 natural, 64 accident, 30 suicide, and 3 homicides. All drowning fatalities involved the decedent having their face submerged. Intoxication and natural deaths had submersion of the face in 15% and 12% of deaths, respectively. For nondrowning causes of death, the majority were without face submersion. For natural deaths, the predominant circumstance was the individual discovered unclad with water in the bathtub and the face not submerged. Conversely, for suicides, the majority were found clad without water. A comprehensive investigation incorporating a scene examination, gathering of the medical and psychosocial history, and typically an autopsy is needed to certify the cause and manner of death. Face submersion alone is not diagnostic of a drowning and must be interpreted with the medical history and autopsy findings.

The burden of all-cause mortality following influenza-associated hospitalizations, FluSurv-NET, 2010-2019.

While the estimated number of U.S. influenza-associated deaths is reported annually, detailed data on the epidemiology of influenza-associated deaths, including the burden of in-hospital versus post-hospital discharge deaths are limited. Using data from the 2010-11 through 2018-19 seasons from the Influenza Hospitalization Surveillance Network, we linked cases to death certificates to identify patients who died from any cause during their influenza hospital stay or within 30 days post discharge. We described demographic and clinical characteristics of patients who died in hospital versus post discharge and characterized locations and causes of death (COD). Among 121,390 cases hospitalized with laboratory-confirmed influenza over 9 seasons, 5.5% died; 76% of deaths were in patients ≥65 years, 71% were non-Hispanic White, and 34% had ≥4 underlying medical conditions. Among all patients with an influenza-associated hospitalization who died, 48% of deaths occurred after hospital discharge; the median days from discharge to death was 9 days (IQR 3-19 days). Post-discharge deaths more often occurred in older patients and among those with underlying medical conditions. Only 37% of patients who died had "influenza" as a COD on their death certificate. Influenza was more frequently listed as a COD among persons who died in-hospital compared with cardiovascular disease among those who died after discharge. All-cause mortality burden is substantial among patients hospitalized with influenza, with almost 50% of deaths occurring within 30 days after hospital discharge. Surveillance systems should consider capture of post-discharge outcomes to better characterize the impact of influenza on all-cause mortality.

Characteristics of Children Ages 1-17 Who Died of COVID-19 in 2020-2022 in the United States.

This study describes characteristics of children ages 1 to 17 years who died of coronavirus disease 2019 (COVID-19) in 2020 to 2022 and whose deaths were reviewed by child death review (CDR) teams across the United States. We used data in the National Fatality Review-Case Reporting System to examine children who died of COVID-19. Deaths were determined because of COVID-19 from death certificates or CDR determinations. A total of 183 children 1 to 17 years old who died of COVID-19 were reported in the National Fatality Review-Case Reporting System. One-third (33%) were 15- to 17-year-olds, and 26% were 1- to 4-year-olds. Fifty-six percent were reported as male, 54% white, 24% Black, and 18% Hispanic ethnicity. Physicians declared cause of death in at least 82% of deaths. More than two-thirds (68%) had a medical condition (excluding COVID-19) at time of death. The most common conditions were nervous system disorders (19%), congenital disorders (14%), obesity (12%), respiratory disorders (12%), and neurodevelopmental disorders (10%). Of children with an underlying condition, 35% had 3 or more conditions. Less than half (42%) had contact with a health care provider within a month of their death; and three-fourths died within 14 days of exposure. This study describes the demographics, death investigation findings, and medical conditions of children who died of COVID-19. The results highlight the short timeline between COVID-19 exposure and death. Pandemic planning that prioritizes prevention efforts and timely access to effective medical care may result in saving children's lives.

Risk of second primary cancers in nodal non-Hodgkin lymphoma patients by primary lymph node location: a retrospective cohort population-based study

Background: Non-Hodgkin lymphoma (NHL) is a diverse group of blood cancers with increasing incidence and survival rates due to advancements in treatment and early detection. However, NHL survivors are at significant risk of developing second primary cancers, which can adversely impact their long-term survival. Methods: This retrospective population-based cohort study utilized data from the Surveillance, Epidemiology, and End Results database, covering 17 geographic areas in the United States from 2000 to 2021. The authors included patients diagnosed with nodal NHL as a first primary cancer and excluded those diagnosed at autopsy or via death certificate only. Standardized Incidence Ratios, Absolute Excess Risks, and Person-Years at Risk were calculated to evaluate the risk of developing SPCs according to the primary lymph node site and stratified by latency periods following the initial NHL diagnosis. Results: The cohort included 54 012 NHL patients. The authors’ results showed that for most SPCs, the risk of development was different for different primary NHL lymph node locations. The highest risks were observed for thyroid cancer, acute myeloid leukemia, and Hodgkin lymphoma. Notably, the risk for thyroid cancer was highest in the first year post-diagnosis, while hematological malignancies such as acute myeloid leukemia and Hodgkin lymphoma showed elevated risks in the intermediate and late latency periods. Conclusion: NHL survivors are at an increased risk of developing SPCs, influenced by the primary lymph node site and latency period. These findings highlight the need for tailored surveillance strategies and preventive measures to mitigate the long-term risks of SPCs in NHL survivors. Further research is necessary to elucidate the underlying mechanisms and to develop targeted interventions for this high-risk population.

Reactive surveillance of deaths involving a fall among the elderly in France, 2015 to March 2023

Abstract In 2022, France launched an elderly anti-fall plan with a goal to reduce fatal falls by 20% within 5 years. In a reactive monitoring approach ensuring comparability over the period, our study aims to develop an algorithm to identify deaths involving a fall using free-text medical causes in death certificates. This will enable proactive surveillance and evaluate plan effectiveness upon completion. We devised an algorithm based on textual search of fall-related expressions in death certificates. Performance metrics were assessed by contrasting algorithm-identified deaths with those flagged by ICD-10 fall-related codes. We compared also temporal dynamics between the algorithms from 2015 to 2021. Analysis was performed by age group, gender and place of death. Additionally, our algorithm enabled estimation of fall-related death trends from 2015 to 2023. The free-text algorithm exhibited robust performance, with a sensitivity and PPV of 95% when compared to deaths coded with an ICD-10 fall-related underlying or associated cause. Temporal trends between both were highly correlated (correlation coefficient=0.99). Instead of the usual 10000 deaths for fall, we revealed about 13000 deaths linked to falls considering both primary and associated causes. Among these, approximately three-quarters were coded as the underlying cause of death in ICD-10 coding. Regarding trends, the results are preliminary and suggested an increase in mortality rates related to falls detected by the algorithm between 2015 and 2022. Our approach distinguishes falls from other competing causes that often relegate them to secondary status in the chain of morbid events leading to death. With free-text medical causes accessible within 3 to 4 months, monitoring deaths involving falls can be done at a detailed geographic level and in a more reactive way. Looking ahead, we must also consider incorporating the impact of epidemics and/or heat waves to accurately evaluate the effectiveness of the anti-fall plan. Key messages • Algorithm using free-text of death certificates identify deaths involving falls. • Our innovative approach isolates falls from other competing causes, elevating their significance in death processes.

Polygenic prediction of coronary artery disease among 130,000 Mexican adults

Abstract Background Coronary artery disease (CAD) is a leading cause of premature mortality globally. Polygenic risk scores (PRSs) have been reported to enhance CAD prediction in populations of European ancestry but evidence from other populations is limited. We assessed the transferability and relevance of eight different external PRSs to the odds of premature CAD in a Mexican population with high levels of relatedness and ancestry admixture. Methods 128,388 genotyped participants aged 35-74 years who were recruited between 1998 and 2004 into the Mexico City Prospective Study (MCPS) were included. We selected and recreated eight previously-reported CAD PRSs. The number of single nucleotide polymorphism variants included in the PRSs varied from 44 to 6,472,620. Premature CAD was defined as either self-reported history of heart attack or angina at recruitment or death before age 75 with CAD recorded on the death certificate. Age and sex-adjusted logistic regression was used to estimate the ability of each PRS to predict CAD, both overall and separately by age, sex and estimated proportion of Indigenous American ancestry. Analyses were repeated after further adjustment for conventional risk factors (blood pressure, adiposity, smoking, diabetes and highest education achieved). Risk discrimination was assessed using C-statistic. Results Of the 128,388 participants, 68% were women, mean (SD) age was 50.2±10.9 years and the average proportion of Indigenous American ancestry was 67%. CAD was identified for 3,871 (3.0%) participants; prior CAD was reported by 1,669 (1.3%) participants while 2,360 (1.8%) participants died before age 75 years with CAD mentioned on the death certificate. All eight PRSs were positively and approximately log-linearly associated with the odds of CAD, but the strength of association varied between the PRSs, ranging from a 7% increase per 1SD higher PRS (odds ratio [OR] 1.07, 95% CI 1.04-1.11) to a 33% increase (OR 1.33, 95% CI 1.29-1.37). Collectively, age, sex and (any) PRS resulted in a C-statistic of 0.70-0.71. C-statistics were slightly lower among those with a higher proportion of indigenous American ancestry. For four of the eight PRSs (including three of the four multi-ancestry PRSs) the increase in odds of CAD per 1SD higher PRS was significantly greater for men than women (eg, for the PRS with the strongest overall association with CAD the OR per 1SD higher PRS was 1.43 [95% CI 1.36-1.49] in men and 1.25 [1.20-1.31] in women). Further inclusion of conventional vascular risk factors reduced the strengths of associations of each PRS with CAD only slightly but increased the model C statistic to 0.74 in all cases. Conclusions In this population of admixed Mexican adults, existing PRSs predicted CAD reasonably well and independently of conventional vascular risk factors. Ancestry-specific instruments that more closely represent genetic variation in Mexico may further enhance polygenic prediction of CAD risk.Table 1.Baseline characteristicsFigure 1.Main analysis results

Left atrial function for predicting atrial fibrillation: a machine learning approach

Abstract Background Common risk scores for atrial fibrillation (AF) are based on clinical risk factors, and little is known about the contribution of left atrial (LA) function parameters to risk assessment. Purpose To determine whether a machine learning-based model that includes LA function parameters outperforms a commonly used risk scores, the CHARGE-AF, in predicting AF. Methods Participants in the Atherosclerosis Risk in Communities (ARIC) Study (a community-based cohort study in the USA) who attended visit 5 (2011-2013) and without a history of AF were included in this analysis. Incident AF was ascertained from ECG during study visits, hospitalization discharge codes, and death certificates. Random survival forest methodology was used to build a prediction model for AF; candidate variables included traditional clinical risk factors and measures of LA structure and function. Dataset was randomly split into a training (75%) and testing (25%) cohort. For each variable, importance was measured based on the reduction in Harrell’s c-statistic if the variable was randomly permuted prior to obtaining predicted values. Variables significantly associated with AF were included in the final model. Model calibration was tested using the Greenwood-Nam-D'Agostino (GND) test. Discrimination ability of our model was assessed in the testing cohort using Harrell’s c-statistic and compared with that of the CHARGE-AF model. Results 4,909 participants (59% female, 22% Black, mean age 75 years) were included. During a median follow-up of 7.0 years (1st-3rd quartile: 5.4-7.8), 650 participants developed AF. Variables significantly associated with incident AF were race, triglycerides, systolic blood pressure, coronary heart disease, age, LA maximal volume index, NT-proBNP, and LA reservoir strain (Figure 1). LA reservoir strain was the variable most strongly associated with AF. The final model showed good discrimination (c-statistic (95% CI): 0.734 (0.698-0.768)). The GND test did not detect statistically significant miscalibration (GND p=0.08). Compared with our model, CHARGE-AF had lower discrimination ability (c-statistic (95% CI): 0.635 (0.594-0.677)) and the difference was statistically significant (difference in c-statistic (95% CI): 0.099 (0.043-0.152)). Conclusion A machine learning-based model with few variables including LA function outperforms a commonly used risk model in predicting AF. Incorporation of LA functional assessment may help inform clinicians regarding individual risk of AF.

A novel electrocardiogram-based model for prediction of dementia: the Atherosclerosis Risk in Communities (ARIC) study

Abstract Background Current dementia prediction models, such as the UK Biobank Dementia Risk Score (UKBDRS, 12 variables), are limited by having variables that are difficult to obtain, subjectively measured, and self-reported. Although individual ECG parameters are linked to higher dementia risk, no study has combined multiple ECG parameters to create an ECG model for dementia prediction. Purpose Using data from the ARIC study, a prospective community-based cohort of Black and White participants in the USA that started in 1987-89, we created an ECG model (based on 7 pre-defined ECG parameters linked to dementia) and compared its model discrimination with the UKBDRS. Methods Participants without prevalent dementia from 2 baselines were included: Visit 4 (V4, 1996-98) and V5 (2011-13). Seven ECG parameters were examined: heart rate, abnormal P-wave terminal force in lead V1 (PTFV1), prolonged P wave duration, abnormal P wave axis, advanced interatrial block, left ventricular hypertrophy (LVH, Cornell voltage criteria), and corrected QT interval (QTc). Dementia cases were identified through 2019 using in-person and phone cognitive assessments, hospitalisation codes, and death certificates. Using a backward selection method (keeping variables with P<0.10 and age, since it is an important dementia risk factor), parsimonious Cox regression models were constructed for prediction of dementia over the longest available follow-up (V4: 23 years, V5: 8 years). Model discrimination of the ECG models and UKBDRS variables was evaluated by the Harrell’s C-statistic (95% CI). Results At V4, 11,520 participants (mean age, 62.8 ± 5.7 years; 56% women; 22% Black) were included; 2,427 developed dementia. At V5, 5,667 participants (mean age, 75.4 ± 5.1 years; 59% women; 22% Black) were included; 830 developed dementia. Figures 1 and 2 show the C-statistic (95%) and area under the ROC curve for the ECG model and UKBDRS variables at V4 and V5, respectively. The C-statistic (95% CI) for both ECG models were >0.70 and comparable with the corresponding UKBDRS models. Conclusion For middle-aged and older adults, a dementia prediction model comprising age and 4 ECG variables has good discrimination for dementia that is comparable with the 12-variable UKBDRS model. Since ECG variables are easily obtainable and objectively measured, these ECG models will be easier to adopt than the UKBDRS model. Further work to validate this model in an external cohort and develop a risk score will facilitate clinical translation.

Mortality related to different circulatory diseases: a multiple causes of death analysis, 2008-2022

Abstract Background Mortality from circulatory diseases significantly increased in 2020 compared to pre-pandemic years in many countries. However, data were mostly limited to the underlying cause of death and to the first phases of the pandemic. Analyses of any mention of a disease in death certificates (multiple causes of death approach, MCOD) are more robust to changes in coding rules/practices and to the role of COVID-19 as a competing cause of death. Methods Mortality records were extracted from 2008 to 2022 among residents of the Veneto Region (Northeastern Italy, 4.9 million population). Based on MCOD, age-standardized mortality rates (2013 European standard) were computed for ischemic heart diseases (IHD), cerebrovascular diseases (CVD), atrial fibrillation (AF), and hypertensive diseases (HD). The annual percent change (APC) was estimated through the pre-pandemic period (2008-2019), and change in rates during pandemic years were computed compared to 2019. Results Before the pandemic, rates were steeply declining for IHD (APC -5.1%; 95%CI -5.5, -4.6) and CVD (-4.0%; -4.4, -3.5); mortality related to HD reduced at a slower pace (-1.9%; -2.3, -1.4), whereas AF-related mortality was increasing (+1.0%; 0.1, 1.8). During the first year of the pandemic, the growth in mortality compared to 2019 was +26% for HD, +18% for AF, +13% for CVD and +12% for IHD. In 2021-2022, rates for CVD and IHD returned to pre-pandemic levels; rates for HD reduced with respect to 2020 but remained above the baseline; AF-related mortality was still increasing. Conclusions The pandemic differentially impacted mortality associated to different circulatory diseases, depending on pre-existing long-term trends (increasing for AF) and on susceptibility to severe COVID-19 disease (higher for HD). Continuous surveillance based on MCOD is warranted to properly assess changes in mortality associated to specific circulatory diseases after the end of the pandemic. Key messages • Multiple causes of death analyses are warranted to assess how the pandemic affected pre-existing long term trends in cause-specific mortality. • Mortality related to different circulatory diseases increased in 2020, but pre-pandemic trends, the extent of the increase in 2020, and further changes observed in 2021-2022 largely diverged.

Time and cause of death in patients after acute coronary syndrome

Abstract Background Acute coronary syndrome (ACS) remains a substantial mortality burden despite enormous progress achieved in treatment and prevention in recent decades, yet systematic investigation of detailed causes of death among ACS patients remains limited. Objective This study aimed to describe the association between time and cause of death in patients after ACS using data from a large, multicenter, contemporary cohort. Methods Patients’ data from the China Chest Pain Database between 2015 and 2021 were linked to the China National Death Registration System Database using unique national IDs to obtain accurate vital status. Patients with documented death records were extracted into a merged database, which encompassed all deaths that occurred in the hospital and post-discharge out-of-hospital. Patients were enrolled with a discharge diagnosis of ACS. Cardiovascular (CV) mortality was defined as a death certificate with a CV diagnosis using the ICD-10 classification listed as the primary cause of death. A trend chi-square test was performed to assess the causes of death at different times after ACS. Results Among the 126,704 eligible patients, the mean age at baseline was 74 (66, 81) years old, 39.3% were women. Of these patients, 16,546 (13.1%) died during hospitalisation, 53,980 (42.6%) within the first six months after discharge, 19,664 (15.5%) from 6 to12 months after discharge, and 36,514 (28.8%) beyond 12 months after discharge. The most common cause of CV death was ischemic heart disease (70.1%), followed by ischemic stroke (7.1%) and hemorrhagic stroke (6.8%). The main causes of non-CV death were malignant tumours (37.1%) and respiratory disease (21.5%). For death in-hospital, within the first six months, from 6 to 12 months post-discharge, and beyond 12 months, the proportion of CV causes was 86.3%, 78.3%, 70.7%, and 67.9%, respectively (P<0.001). The proportion of deaths due to haemorrhagic stroke and aortic aneurysm/dissection increased progressively with time to death increasing (P<0.001). Meanwhile, the proportion of non-CV deaths continuously increased, reaching 13.7%, 21.7%, 29.3%, and 32.1%, respectively. Conclusion Despite cardiovascular diseases being the primary cause of death in patients after ACS, the causes of death vary among patients with different times of death, highlighting the importance of categorising patients into distinct population groups according to time after ACS for targeted cause-specific preventive strategies.

Long-term exposure to PM2.5 and mortality among Japanese community-dwelling adults

Abstract Background Long-term exposure to PM2.5 (particulate matter with a diameter of 2.5 μm or smaller) is a risk factor for mortality and cardiovascular disease including stroke. However, there was limited evidence for the association between PM2.5 exposure and stroke in Asia where the major cardiovascular disease is stroke. Additionally, the causal association between PM2.5 and respiratory disease is still unresolved. The aim of this study was to investigate the association between long-term exposure to PM2.5 and all-cause, cardiovascular, and respiratory disease mortality in a Japanese community-based prospective cohort. Methods This study included 46,974 participants (19,707 men; 27,267 women) from the second cohort of the Ibaraki Prefectural Health Study. The participants were followed up from baseline survey (in 2009) to 31 December 2019. We confirmed underlying causes by death certificates. Using the PM2.5 concentrations estimated by the inverse distance weighting methods based on ambient air monitoring data, administrative area level concentrations were assigned to each participant. The hazard ratios (HRs) and 95% confidence intervals (CIs) of mortality using a Cox proportional hazard model were presented. Results We identified 2,789 all-cause deaths during the 470,178 person-years of follow-up. PM2.5 exposure had no significant association with all-cause and cause-specific mortality. The multivariable-adjusted HRs per 1 μg/m3 increase in the PM2.5 concentration were 0.94 (95% CI = 0.80-1.12) for coronary heart disease, 0.92 (95% CI = 0.81-1.04) for stroke and 1.09 (95% CI = 0.97-1.23) for non-malignant respiratory disease. Conclusions We observed little evidence of increased risk of all-cause and cause-specific mortality by long-term exposure to PM2.5 whose concentrations ranged from 8.3 to 13.1 μg/m3. A somewhat increased trend for non-malignant respiratory disease mortality may not be negligible. Key messages • We found little evidence of increased risk of all-cause and cause-specific mortality by long-term exposure to PM2.5. • Somewhat increased tendency for non-malignant respiratory disease mortality associated with PM2.5 exposure was observed.

Mortality and causes of death in Serbia: redistribution of garbage codes to ischemic heart disease

Abstract Background Cardiovascular diseases are ranked as the number one cause of death in Serbia, and one-fifth of them present ischemic heart disease (IHD). However, the physicians certifying the cause of death have either not been adequately involved in how to complete a death certificate according to the current International Statistical Classification of Diseases (ICD-10) or due to a high level of administrative tasks sometimes fail to complete the process of death certification. That is why we aimed to investigate the garbage codes (GCs) and the effects of their redistribution on underlying cause of death (CoD) estimates for IHD for 2015 and 2020. Methods Data from Belgrade mortality statistics in 2015 and 2020 were used to describe the occurrence and redistribution of garbage codes (GCs), defined as unspecified or impossible causes of death. In order to redistribute GCs we observed the underlying, antecedent, immediate causes and other conditions that contributed to deaths. Redistribution was done by consulting GBD methodology for GC proportional redistribution. The ICD-10 code range for IHD is I20-I25. Results In Belgrade, 17% (4022/23663) and 20.9% (5818/27775) of the deaths were coded with a garbage code in 2015 and 2020, respectively. In 2015, 2102 deaths (10.7% of all well-defined CoD) were attributed to IHD, while in 2020, 1806 (8,2% of all well-defined CoD) deaths were attributed to IHD. Finally, we redistributed a total of 452 deaths (GC type 1 203.9, GC type 2 122.1 and GC type 3 126.2 deaths) and 572 deaths (GC type 1 250.1, GC type 2 110.9, GC type 3 210.7 and GC type 4 22) due to IHD in 2015 and 2020, respectively. These calculations indicate a total number of 2554 and 2378 deaths due to IHD in 2015 and 2020, respectively. Conclusions A more detailed analysis of local practices, as well as continuing medical education in the field of death certification, could be a step forward in the future process of decreasing the number of GCs. Key messages • Since the huge number of deaths was added to ischemic heart disease in 2015 and 2020, it is crucial to focus on a more reliable disease surveillance system including better coding practices. • A deep understanding of the garbage codes and their redistribution could significantly shape future decisions on factors contributing to ischemic heart diseases.

Evaluating perinatal health in Europe: a comparison of routine population birth data sources

Abstract Background International comparisons provide essential benchmarks for evaluating perinatal health policies, but these rely on the availability of routine national birth data. This study aimed to describe population birth data sources in Europe by their ability to provide core perinatal health indicators. Methods The Euro-Peristat Network collected routine national data on a recommended set of core indicators from 2015 to 2021 using a federated protocol based on a common data model with 17 data items. Data providers filled in an on-line questionnaire to describe the sources used in each country. We classified countries by the number of data items they provided (all 16, 15-14, <14). Results 28 out of the 31 countries that provided data responded to the survey. Routine data sources included birth certificates (14 countries), electronic medical records (EMR) from delivery hospitalizations (14 countries), direct entry by health providers (9 countries), EMR from other care providers (6 countries) and Hospital Discharge Summaries (7 countries). Completeness of population coverage was at least 98%, with 15 countries reporting 100%. These databases most often included mothers giving birth on the national territory, regardless of nationality or place of residence (19 countries). In 20 countries, routine sources were linked, including linkage between birth and death certificates (15 countries). Countries providing all 16 items (N = 8) were more likely to use EMRs from delivery hospitalizations, 88%, compared to 50% and 13% in countries with 15-14 items (N = 13) and <14 items (N = 8). Linkage was also more common in these countries, 100%, versus 75% and 50% respectively. Other data source characteristics did not differ by the ability to provide data for the common data model. Conclusions There is high diversity in the data sources used to construct perinatal health indicators in Europe. Countries using EMR with linkage to other sources had the best data availability. Key messages • There is high diversity in the data sources used to construct perinatal health indicators in Europe. • Countries using Electronic Medical Records with linkage to other sources had the best data availability.

Circulating secretoneurin concentrations predict cardiovascular death in ambulatory patients with heart failure

Abstract Background Secretoneurin (SN) is a novel biomarker, which predicts cardiovascular (CV)-related mortality in patients with acute dyspnea and sepsis. Higher SN concentrations have also been found associated with all-cause death in outpatients with heart failure (HF), but whether SN primarily reflects cardiovascular (CV)-related mortality in HF outpatients is not known. Objectives To evaluate the relation between SN concentrations and CV- & non-CV death in ambulatory patients with HF. Methods We studied 184 consecutive patients who attended our HF clinic for routine follow up and had stored blood samples available for SN analysis. SN concentrations were measured with a CE-marked SN ELISA assay. We assessed the associations between SN concentrations and CV & non-CV death. Mortality was ascertained using medical records, autopsy reports and death certificates, and CV deaths included sudden cardiac deaths or mortality due to myocardial infarction, HF or stroke. We assessed association with CV & non-CV death by Kaplan-Meier curves and by Cox proportional hazard regression analysis. Results Median age was 76 years (range: 38-94 years) and two thirds were male. Sixty-three percent had HF with reduced ejection fraction, 22% had NYHA III/IV symptoms and median NT-proBNP was 1079 (interquartile range: 462-2347) ng/L. Median SN level was 60 (range: 21-134) pmol/L. In multivariable linear regression analysis, impaired renal function and lower body-mass index were significantly associated with increasing (log)SN concentration. During median follow up of 540 days, there were 18 CV deaths, including 15 HF deaths, and 7 non-CV deaths. A higher SN concentration was associated with higher risk of CV death, while we did not find statistically significant association between SN concentrations and non-CV deaths (Figure). Patients with SN concentration in the top tertile had 15-fold increased risk of CV death compared to patients with SN concentration in the lowest tertile. In multivariable Cox regression analysis that adjusted for age, NYHA functional class, frailty status, increasing SN concentrations were independently associated with CV death: hazard ratio per logSN (95% CI): 3.01 (1.02-8.90), p=0.04. Conclusion In ambulatory patients with HF, circulating SN concentrations were predictive of CV death. Higher SN concentrations in ambulatory HF patients seemed to be linked to impaired renal function and lower body-mass index. Figure: Kaplan Meier curves illustrating the relation between SN tertiles and (A) CV mortality (B) Non-CV mortality.

Comparing Italian hospital discharge and mortality data: implications for epidemiological research

Abstract Background In Italy, regional governments maintain data warehouses of linked administrative health data (AHD) linked to demographic information including mortality. Legal reporting pathways for death certificate detail bypass the Region, resulting in significant amounts of missing data on cause and location of death in regional AHD warehouses and limiting epidemiological research on mortality and incidence. In this study, we determine for the first time in Italy the degree of agreement between last hospital diagnosis and primary cause of death, and how that agreement changes over time. Previous studies have found agreement ranging from 40% to 60%. Methods The COV-CVD cohort is comprised of 7.3 million adults aged 30+ from the Lombardy region of northwest Italy, representing all Lombardy residents registered with the health system as of 31 December 2019. Concordance was assessed using the first three characters of the reported cause of death (ICD-10 codes) and primary diagnosis at last hospitalization (converted from ICD-9CM). Results In the COV-CVD cohort there were 401,085 deaths between 1 January 2020 and 23 June 2023. Cause and location of death is missing for 50% and 54% of these deaths, respectively. 60% of deceased individuals had a hospitalization in the year before their death. Agreement between primary diagnosis at last hospitalization and cause of death was 27% overall and 40.5% for deaths in hospital. Missing location of death was reduced from 54% to 26%. Conclusions When using AHD from Italy, primary diagnosis at last hospitalization prior to death is not an appropriate proxy for cause of death, even when the death occurred in hospital. Different coding systems (ICD-10, ICD-9CM) further complicate comparisons and definitions in observational studies. Key messages • In Italy, primary diagnosis at last hospitalization before death is not an appropriate proxy for cause of death. • Poor linkage of mortality and health data limits epidemiological research.

Increasing trends in hypertension-related mortality in European Union 27 countries from 2011 to 2019

Abstract Background Arterial Hypertension (HT) is one of the most common chronic cardiovascular disease in adults and a leading cause of disability and mortality worldwide. However, update data regarding the HT-related mortality trends in Europe are lacking. Therefore, we assess the age- and sex- specific trends in HT-related mortality in the 27 European Union Member States (EU-27) between years 2011 and 2029. Methods Data were retrieved from the free publicly available EUROSTAT death certificate database to examine age-adjusted HT-related mortality rates (AAMR) (per 100.000 people) and relative average annual percentage change (AAPC) across all European Union 27 countries (EU27) from 2011 to 2019 using the International Classification of diseases, Tenth Revision (ICD-10) codes I10-I13 and I15. To calculate annual trends in HT-related mortality, we assessed the average annual percent change (AAPC) and relative 95% confidence intervals (CIs) using Joinpoint regression analysis. Results Over the study period, 254.540 HT-related deaths (157,081 males) were listed in EU27. Age-adjusted HT-related death increased from 9.12 to 10.7 per 100,000 people [AAPC: +1.5% (95% CI: 0.8-2.0), p<0.001]. Specifically, the HT-related mortality increased in males [AAPC: +1.8 (95% CI: 0.9-2.6) while decreased in women [AAPC: -1.1 (95% CI: -2.0 to 0.2), p=0.001]. Additionally, the HT-related mortality rates increased in northern [+1.5 (95% CI: 0.7 to 2.3), p<0.001] and eastern [AAPC: +3.9 (95% CI: 2.3 to 5.4), p<0.001] EU-27 states. Conversely, the AAMR plateaued in southern [AAPC: -0.1 (95% ci: 0.6 to 0.7), p=0.96)] and western EU-27 countries [AAPC: 1.0 (95% CI: -0.1 to 2.1, p=0.07] over the same period. Conclusions In EU27, HT-related mortality increased from 2011 to 2019, especially in men. However, significant disparities in HT-related mortality rates still exist between different European regions.

Diabetes and sudden cardiac death in a nationwide, unselected population

Abstract Background and purpose Sudden cardiac death (SCD) remains a prominent cause of mortality, with individuals afflicted by diabetes mellitus (DM) bearing a heightened risk of ventricular arrhythmias and SCD. However, comprehensive investigations in a nationwide, unselected context are lacking. Therefore, this study aimed to compare the incidence rates (IR) of SCD among individuals with Type 1 Diabetes Mellitus (T1DM) and Type 2 Diabetes Mellitus (T2DM) to the general population. Methods The study included the entire Danish population (approximately 5.5 million individuals) in 2010. SCD cases were identified through the detailed Danish death certificates and discharge summaries, yielding 6851 cases of SCD. The Danish Register of Medicinal Product Statistics, containing comprehensive prescription data from Danish pharmacies, facilitated the identification of individuals with T1DM and T2DM. Loss of life years was estimated for both T1DM and T2DM patients. Results Among the identified 6851 SCD cases, 272 (4%) were diagnosed with T1DM, and 833 (12%) with T2DM. Incidence rates of SCD were consistently elevated across all age groups for individuals with diabetes, compared to the general population (Figure 1). Patients with T1DM exhibited higher incidence rates than patients with T2DM (Figure 1). Notably, individuals aged 30-40 years with DM showed the greatest differences in incidence rates of SCD compared to the general population, with incidence rate ratios of 20.0 (95% confidence interval: 11.8-80.0) and 5.6 (95% confidence interval: 2.7-14.0) for T1DM and T2DM, respectively. On average, each 30-year-old patient with either T1DM or T2DM experiences a reduction of 3.7 and 3 life-years, respectively, due to the increased risk of SCD in these groups (Figure 2). Conclusion This nationwide study examines the incidence rates of SCD among individuals with and without a history of DM across all age brackets. Notably, patients with DM display consistently elevated incidence rates across age groups, with a particularly pronounced risk observed in those with T1DM. For both T1DM and T2DM, SCD is an important contributing factor to their shorter life expectancy compared to the general population. The heightened risk among individuals with DM underscores the importance of improved risk stratification for these patients.Incidence rates of SCDStacked cumulative incidence curves

Communities That HEAL Intervention and Mortality Including Polysubstance Overdose Deaths

The HEALing Communities Study (HCS) evaluated the effectiveness of the Communities That HEAL (CTH) intervention in preventing fatal overdoses amidst the US opioid epidemic. To evaluate the impact of the CTH intervention on total drug overdose deaths and overdose deaths involving combinations of opioids with psychostimulants or benzodiazepines. This randomized clinical trial was a parallel-arm, multisite, community-randomized, open, and waitlisted controlled comparison trial of communities in 4 US states between 2020 and 2023. Eligible communities were those reporting high opioid overdose fatality rates in Kentucky, Massachusetts, New York, and Ohio. Covariate constrained randomization stratified by state allocated communities to the intervention or control group. Trial groups were balanced by urban or rural classification, 2016-2017 fatal opioid overdose rate, and community population. Data analysis was completed by December 2023. Increased overdose education and naloxone distribution, treatment with medications for opioid use disorder, safer opioid prescribing practices, and communication campaigns to mitigate stigma and drive demand for evidence-based interventions. The primary outcome was the number of drug overdose deaths among adults (aged 18 years or older), with secondary outcomes of overdose deaths involving specific opioid-involved drug combinations from death certificates. Rates of overdose deaths per 100 000 adult community residents in intervention and control communities from July 2021 to June 2022 were compared with analyses performed in 2023. In 67 participating communities (34 in the intervention group, 33 in the control group) and including 8 211 506 participants (4 251 903 female [51.8%]; 1 273 394 Black [15.5%], 603 983 Hispanic [7.4%], 5 979 602 White [72.8%], 354 527 other [4.3%]), the average rate of overdose deaths involving all substances was 57.6 per 100 000 population in the intervention group and 61.2 per 100 000 population in the control group. This was not a statistically significant difference (adjusted rate ratio [aRR], 0.92; 95% CI, 0.78-1.07; P = .26). There was a statistically significant 37% reduction (aRR, 0.63; 95% CI, 0.44-0.91; P = .02) in death rates involving an opioid and psychostimulants (other than cocaine), and nonsignificant reductions in overdose deaths for an opioid with cocaine (6%) and an opioid with benzodiazepine (1%). In this clinical trial of the CTH intervention, death rates involving an opioid and noncocaine psychostimulant were reduced; total deaths did not differ statistically. Community-focused data-driven interventions that scale up evidence-based practices with communications campaigns may effectively reduce some opioid-involved polysubstance overdose deaths. ClinicalTrials.gov Identifier: NCT04111939.

The role of prescribed controlled substance acquisition as potential triggers of opioid overdose: A case-crossover study

Background: The role of prescribed opioids and benzodiazepines as risk factors for opioid overdose are well established, however, their role as potential ‘triggers’ of opioid overdose has not been formally investigated. Objective: The objective of this study was to evaluate the temporal relationship between controlled substance acquisition and opioid overdose utilizing a case-crossover design. Methods: This study utilized Arkansas statewide data between 2014 and 2020. Prescription Drug Monitoring Program (PDMP) data were used to assess controlled substance acquisition and fatal and non-fatal opioid overdose were assessed using linked death certificate, inpatient discharge, and emergency department (ED) data. All persons residing in Arkansas who experienced an opioid overdose or had ≥ 1 Arkansas PDMP prescription fill(s) were included. Controlled substance characteristics were described in the 7 days prior to overdose and compared to the controlled substance characteristics in 11 weekly (7-day) control windows prior to overdose. Binary controlled substance variables indicating presence or absence of: any controlled substance, opioid, benzodiazepine, stimulant, sedative, carisoprodol, opioid and benzodiazepine, and opioid and benzodiazepine and carisoprodol were created. Additionally, total morphine milliequivalents were calculated for each time window. Conditional logistic regression models were estimated and adjusted odds ratios for each controlled substance characteristic after accounting for other controlled substance, and prior overdose, and clinical characteristics derived from ED and inpatient data are reported. Results: A total of 2,818,135 individuals with ≥1 Arkansas PDMP record(s) (45.10 % male; 39.94 mean age) were included, of which 28,670 (1.02 %) experienced ≥1 opioid overdose. There was a significant association between opioid overdose and the acquisition of a controlled substance (OR=1.785; p < 0.001), opioid (OR=1.992; p < 0.001), benzodiazepine (OR=1.379; p < 0.001), carisoprodol (OR=1.744; p < 0.001), opioid and benzodiazepine (OR=2.203; p < 0.001), and opioid and benzodiazepine and carisoprodol (OR=2.503; p < 0.001), in the 7 days prior to an opioid overdose event. Conclusion: Controlled substance prescription acquisition, particularly opioids in combination with carisoprodol and/or benzodiazepines, are potential triggers of opioid overdose.

Debatable issues of coding chronic forms of ischemic heart disease as the primary cause of death

Aim: to examine the opinions of healthcare professionals on using codes from the ICD-10 group chronic ischemic heart disease (CIHD) (I25.0, I25.1, I25.8, I25.9) as the primary cause of death and discuss the results in the context of comparing with regional variability of standardized mortality ratio (SMR) from different forms of CIHD.Materials and methods. A one-stage study was conducted. This article describes the results of a survey of 366 medical workers (cardiologists, internists/general practitioners/family doctors, pathologists, public health and healthcare specialists, paramedics) from 47 subjects of the Russian Federation who fill out a medical death certificate (MDS) more often than 2–3 times a month. In addition, SMR from coronary heart disease were determined based on a brief nomenclature of causes of death of Rosstat in 82 regions of the Russian Federation for 2022.Results. 80.1 % of respondents expressed the opinion that I25.0, I25.1, I25.8, I25.9 are necessary for coding causes of death, but half of those surveyed do not see any differences in them. At the same time, respondents admit the possibility of using these CIHD codes as the primary cause of death without ante-mortem and pathological verification. The relatively small coefficient of variation of SMR overall from CIHD (34.19 per 100,000 population) is associated with high values from its individual forms: the coefficient of variation of average regional SMRs ranged from 62 % for code I25.1 to 174 % for code I25.0.Conclusions. The results of this study indicate a variable attitude of specialists filling out MSD towards choosing ICD-10 codes from the CIHD group, leading to significant interregional differences in CIHD mortality rates. It is necessary to develop unified recommendations describing situations in which codes from the CIHD group can be considered the primary (main) cause of death.