5 research outputs found

    Avaliação de dispositivos médicos nas radiografias de tórax em unidades de terapia intensiva - tempo de prestar atenção!

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    OBJECTIVE: To identify and evaluate the correct positioning of the most commonly used medical devices as visualized in thoracic radiograms of patients in the intensive care unit of our center.METHODS: A literature search was conducted for the criteria used to evaluate the correct positioning of medical devices on thoracic radiograms. All the thoracic radiograms performed in the intensive care unit of our center over an 18-month period were analyzed. All admissions in which at least one thoracic radiogram was performed in the intensive care unit and in which at least one medical device was identifiable in the thoracic radiogram were included. One radiogram per admission was selected for analysis. The radiograms were evaluated by an independent observer.RESULTS: Out of the 2,312 thoracic radiograms analyzed, 568 were included in this study. Several medical devices were identified, including monitoring leads, endotracheal and tracheostomy tubes, central venous catheters, pacemakers and prosthetic cardiac valves. Of the central venous catheters that were identified, 33.6% of the subclavian and 23.8% of the jugular were malpositioned. Of the endotracheal tubes, 19.9% were malpositioned, while all the tracheostomy tubes were correctly positioned.CONCLUSION: Malpositioning of central venous catheters and endotracheal tubes is frequently identified in radiograms of patients in an intensive care unit. This is relevant because malpositioned devices may be related to adverse events. In future studies, an association between malpositioning and adverse events should be investigated

    Avaliação de dispositivos médicos nas radiografias de tórax em unidades de terapia intensiva - tempo de prestar atenção!

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    RESUMO Objetivo: Identificar e avaliar o posicionamento correto dos dispositivos médicos mais comumente utilizados, observados nas radiografias de tórax de pacientes durante a permanência em unidade de terapia intensiva de nosso centro. Métodos: Foi realizada uma pesquisa bibliográfica quanto aos critérios utilizados para avaliar o posicionamento correto dos dispositivos médicos nas radiografias de tórax. Avaliamos todas as radiografias de tórax realizadas na unidade de terapia intensiva de nosso centro durante um período de 18 meses. Incluíram-se todas as admissões nas quais foi realizada uma radiografia do tórax na unidade de terapia intensiva, nas quais fosse identificável a presença de pelo menos um dispositivo médico. Para análise, selecionou-se uma radiografia por admissão. As radiografias foram avaliadas por um observador independente. Resultados: De um total de 2.312 radiografias analisadas, 568 foram incluídas neste estudo. Identificaram-se diversos dispositivos médicos, incluindo eletrodos de monitoramento, tubos endotraqueais, cânulas de traqueostomia, cateteres venosos centrais, marca-passos e próteses valvares cardíacas. Dentre os cateteres venosos centrais identificados, 33,6% dos subclávios e 23,8% dos jugulares estavam mal posicionados. Dentre os tubos endotraqueais, 19,9% estavam mal posicionados, enquanto todas as cânulas de traqueostomia tinham posicionamento correto. Conclusão: Frequentemente se identificam, na radiografia de tórax realizada em pacientes na unidade de terapia intensiva, cateteres venosos e tubos endotraqueais mal posicionados. Isso é importante, pois dispositivos mal posicionados podem se relacionar a eventos adversos. Estudos futuros devem investigar possíveis associações entre o mau posicionamento dos dispositivos e eventos adversos

    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

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    BackgroundRegular, 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.MethodsThe 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.FindingsThe 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.InterpretationLong-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
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