THE USAGE OF MEDICAL INFORMATICS IN CRITICAL CARE MEDICINE

Introduction: The intensive care unit can be defined as a complex system that composed of clinical informations, tasks and knowledge. It is also one of the most stressful and most vital parts of healthcare centers which involve a huge amount of information and clinical data daily. These informations should be analyzed and managed in the best way as soon as possible to restore patients to normal by health professionals. Accurate and timely diagnosis, the best treatment and to avoid any possible error in this section can be equivalent to achieve the best possible result and reducing the length of hospitalization and mortality. As a result, due to the complex nature of the critical care and the mass of clinical data; using a combination of medical knowledge with the latest technologies and use of medical informatics capabilities can be the best way to reduce the workload of the sector and improve the quality of patient care. Methods: A systematic search was conducted on the PubMed/MEDLINE, web of science, BMJ, ScienceDirect, and Scopus database for finding studies that have related to critical care and usage of informatics or medical informatics. The collected data and results are summarized by researchers and the results analyzed based on similarities and differences. Results: With increased development of medical informatics and electronic systems has led to substantial progress in the field of critical care since 1980 till now around the world. Several articles, research projects has published. From 1981 to 2016 almost 600 scientific papers were found which included reports, posters and thesis written in context of critical care medical informatics. More than 65 percent of these studies is about designing CDSS in this field. Today, many of these systems are used in medical centers around the world and lead to improving the quality of patient care and reduce medical errors in intensive care units. Among these 600 papers, 230 articles related to our issue in fields of the design of electronic records, clinical information systems, decision support systems, data mining, telemedicine, smart analysis of clinical information and knowledge extraction techniques were selected as the main source of this study. Conclusion: According to results of our study, it seems that critical care is potentially a valuable resource for medical informatics researches. The applied of medical informatics in the different fields of the diagnosis, interpretation, and treatment in different countries have improved the quality of care for patients in critical care field. We can mention some common fields which used such as infection control and early detection in intensive care units, clinical information systems, and CPOE and decision support systems such as APACHE system for grading the severity of illness of patients who hospitalized and even telemedicine. Since this area of research has not been a field of interest in Iran yet, it seems that this study with the aim of review the application of medical informatics in different countries could lead to practical researches in this field

Hearing loss etiology in patients referring to Isfahan cochlear implantation center

Introduction: Hearing loss is the most common congenital disorders occurring among newborn. Identifying the factors affecting it would reduce the incidence of this disorder. Therefore, the aim of this study was to examine the etiology of congenital hearing loss in patients referring to Isfahan Cochlear implantation center. Materials and Method: This study was performed on 689 patients with cochlear implantation. Demographic data and relative frequency of different causes of congenital hearing loss (acquired and genetic) were determined and recorded. T-test, Chi-Square and Mann-Whitney tests were used to compare the variables studied. Results: Our findings showed that 50 patients (7.7%) had history of drug use, 9 (1.3%) had history of taking ototoxic drugs, 99 (14.3%) had history of kernicterus, 157 patients (22.8%) had a history of hyperbilirubinemia, 15 (2.1%) history of meningitis, 57 (8.3%) had a history of seizure, one (0.1%) had a birth weight less than 1500 grams, 4 cases (0.06%) had history of hypoxia, 18 cases (2.6%) had history of trauma, one (0.1%) had CMV history, and one (0.1%) hearing loss due to syndromicity. On the other hand, it was determined that the probable causes of hearing loss were not related to the severity of hearing loss and age of the patients (p <0.05) Conclusion: Although the prevalence of congenital hearing loss is low, it is important to identify and screen for postnatal congenital hearing loss, especially in people with risk factors known in this study, including patients with kernicterus.

Thinking outside the skin: Look at the thyroid for true diagnosis

Keratoderma is a group of disorders characterized by abnormal thickening of skin. Acquired palmar keratoderma has many underlying causes. The association of thyroid disease and palmar keratoderma rarely reported. Hypothyroidism, although very rare association, must be suspected in patients with acquired PPK, particularly when it occurs in setting of systemic symptoms or predisposing conditions.We report first case of acquired plantar keratoderma associated with undiagnosed hypothyroidism in Down syndrome

Low-level laser for treatment of tinnitus: a self-controlled clinical trial

BACKGROUND: Despite the high prevalence and morbidity, tinnitus still remains an obscure symptom. We assessed the efficacy of low-level laser for treatment of tinnitus. METHODS: It was a self controlled clinical trial study on 61 outpatients with subjective tinnitus. The patients were irradiated with a 650-nm, 5-mW soft laser for twenty days and twenty minutes per day. The sensation of tinnitus was measured on a Visual Analog Scale (VAS) before and two weeks after treatment and they were compared by means of Wilcoxon signed rank-test. RESULTS: Thirty-eight (62.3%) patients were men and twenty-three (37.7%) were women. Fourteen patients (31.8%) worked in noisy environment. The VAS mean difference before and after the treatment was statistically significant (p < 0.0001). The best treatment effect was in the youngest group and there were significant differences between this group and the middle age and older groups (p = 0.018 and 0.001, respectively). The mean VAS score reduction was not statistically significant between male and female patients (p = 0.23). Also, the treatment outcome according to the noise level in patient’s workplaces was not significantly different in women (p = 0.693), but it was significant in men (p = 0.029). CONCLUSIONS: Transmeatal low-level laser irradiation is effective for the treatment of tinnitus and some variables like age and job can affect the treatment outcom

COVID-19 Associated Mucormycosis::A Review of an Emergent Epidemic Fungal Infection in 3 Era of COVID-19 Pandemic

At a time when the COVID-19's second wave is still picking up in countries like India, a number of reports describe the potential association with a rise in the number of cases of mucormycosis, commonly known as the black fungus. This fungal infection has been around for centuries and affects those people whose immunity has been compromised due to severe health conditions. In this article, we provide a detailed overview of mucormycosis and discuss how COVID-19 could have caused a sudden spike in an otherwise rare disease in countries like India. The article discusses the various symptoms of the disease, class of people most vulnerable to this infection, preventive measures to avoid the disease, and various treatments that exist in clinical practice and research to manage the disease

GJB2 mutations causing autosomal recessive non-syndromic hearing loss (ARNSHL) in two Iranian populations: Report of two novel variants

OBJECTIVE: Hereditary hearing loss (HL) is a noticeable concern in medicine all over the world. On average, 1 in 166 babies born are diagnosed with HL in Iran, which makes it a major public health issue. Autosomal recessive non-syndromic HL (ARNSHL) is the most prevalent form of HL. Although over 60 genes have been identified for ARNSHL, GJB2 mutations are the most prevalent causes of ARNSHL in many populations. Previous studies have estimated the average frequency of GJB2 mutations to be between 16 and 18% in Iran, but would vary among different ethnic groups. In the present study, we aimed to determine the frequency and mutation profile of 70 deaf patients from two different provinces (center and west) of Iran. METHODS: We enrolled 70 Iranian deaf patients with ARNSHL from Isfahan (40 family) and Hamedan (30 family) provinces. After extraction of genomic DNA, the entire coding region of GJB2 was directly sequenced in all patients. Multiplex PCR was used for detection of del(GJB6-D13S1830) and del(GJB6-D13S1854) in the GJB6 gene. In silico analyses were also performed by available software tools. RESULTS: A total of eleven different mutations were detected, nine of which were previously reported and the other two (c.130T > G and c.178T > G) were novel. Homozygous GJB2 mutations were observed in 22.5% and 20% of all the subjects from Isfahan and Hamedan provinces, respectively. c.35delG was the most frequent mutation. One compound heterozygous genotype (c.358_360delGAG/c.35delG) was observed for c.35delG. Screening for the two GJB6 deletions did not reveal any positive sample among heterozygous or GJB2 negative samples. CONCLUSIONS: The present study suggests that mutations in the GJB2 gene specially c.35delG are important causes of ARNSHL in the center and west of Iran. Totally, 15% of the patients were heterozygous carriers. Further investigation is needed to detect the genetic cause of HL in the patients with monoallelic GJB2 mutations

Screening of 10 DFNB Loci Causing Autosomal Recessive Non-Syndromic Hearing Loss in Two Iranian Populations Negative for GJB2 Mutations.

BACKGROUND: Autosomal recessive non-syndromic hearing loss (ARNSHL), one of the global public health concerns, is marked by a high degree of genetic heterogeneity. The role of GJB2, as the most common cause of ARNSHL, is only <20% in the Iranian population. Here, we aimed to determine the relative contribution of several apparently most common loci in a cohort of ARNSHL Iranian families that were negative for the GJB2 mutations. METHODS: Totally, 80 Iranian ARNSHL families with 3 or more affected individuals from Isfahan and Hamedan provinces, Iran were enrolled in 2017. After excluding mutations in the GJB2 gene via Sanger sequencing, 60 negative samples (30 families from each province) were analyzed using homozygosity mapping for 10 ARNSHL loci. RESULTS: Fourteen families were found to be linked to five different known loci, including DFNB4 (5 families), DFNB2 (3 families), DFNB7/11 (1 family), DFNB9 (2 families) and DFNB3 (3 families). CONCLUSION: Despite the high heterogeneity of ARNSHL, the genetic causes were determined in 23.5% of the studied families using homozygosity mapping. This data gives an overview of the ARNSHL etiology in the center and west of Iran, used to establish a diagnostic gene panel including most common loci for hearing loss diagnostics. Copyright© Iranian Public Health Association & Tehran University of Medical Sciences. KEYWORDS: Autosomal recessive non-syndromic hearing loss (ARNSHL); DFNB loci; Homozygosity mapping; Ira

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. METHODS: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. FINDINGS: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. INTERPRETATION: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. FUNDING: Bill & Melinda Gates Foundation

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation