38 research outputs found
Outcomes of Patients with Thrombocytopenia Evaluated at Hematology Subspecialty Clinics
BACKGROUND: Thrombocytopenia is a frequently encountered laboratory abnormality and a common reason for hematology referrals. Workup for thrombocytopenia is not standardized and frequently does not follow an evidence-based algorithm. We conducted a systematic analysis to evaluate the laboratory testing and outcomes of patients evaluated for thrombocytopenia at hematology clinics in a tertiary referral center between 2013 and 2016.
PATIENT AND METHODS: We performed a comprehensive chart review for patients evaluated for thrombocytopenia during the study period. Patients were followed for 1 year from the initial hematology evaluation and assessed for the development of a hematologic malignancy, rheumatologic, or infectious diseases among other clinical outcomes.
RESULTS: We evaluated 472 patients with a median (range) age of 61 (17-94) years. The majority (63.8%) had mild thrombocytopenia. Within 1 year of follow-up, 14 patients (3.0%) were diagnosed with a hematologic malignancy. A higher likelihood of developing a hematologic malignancy was noted in patients with concurrent leukopenia (hazard ratio [HR] 9.97, 95% confidence interval [CI] 3.28-30.32, p \u3c .01) and increasing age (HR per 10-year deciles 1.52, 95% CI 1.03-2.25, p = .03). In patients with asymptomatic isolated mild thrombocytopenia, laboratory testing did not reveal any significant positive findings and patients did not receive any new major diagnosis during the follow-up period.
CONCLUSION: Our findings provide basis and call for development of an evidence-based algorithmic approach for evaluation of patients with thrombocytopenia, testing, and referrals. It also supports a conservative approach mainly driven by physical exam signs, symptoms, and other laboratory findings for patients with isolated mild thrombocytopenia
Outcomes of patients with thrombocytopenia evaluated at hematology subspecialty clinics
BACKGROUND: Thrombocytopenia is a frequently encountered laboratory abnormality and a common reason for hematology referrals. Workup for thrombocytopenia is not standardized and frequently does not follow an evidence-based algorithm. We conducted a systematic analysis to evaluate the laboratory testing and outcomes of patients evaluated for thrombocytopenia at hematology clinics in a tertiary referral center between 2013 and 2016.
PATIENT AND METHODS: We performed a comprehensive chart review for patients evaluated for thrombocytopenia during the study period. Patients were followed for 1 year from the initial hematology evaluation and assessed for the development of a hematologic malignancy, rheumatologic, or infectious diseases among other clinical outcomes.
RESULTS: We evaluated 472 patients with a median (range) age of 61 (17-94) years. The majority (63.8%) had mild thrombocytopenia. Within 1 year of follow-up, 14 patients (3.0%) were diagnosed with a hematologic malignancy. A higher likelihood of developing a hematologic malignancy was noted in patients with concurrent leukopenia (hazard ratio [HR] 9.97, 95% confidence interval [CI] 3.28-30.32, p \u3c .01) and increasing age (HR per 10-year deciles 1.52, 95% CI 1.03-2.25, p = .03). In patients with asymptomatic isolated mild thrombocytopenia, laboratory testing did not reveal any significant positive findings and patients did not receive any new major diagnosis during the follow-up period.
CONCLUSION: Our findings provide basis and call for development of an evidence-based algorithmic approach for evaluation of patients with thrombocytopenia, testing, and referrals. It also supports a conservative approach mainly driven by physical exam signs, symptoms, and other laboratory findings for patients with isolated mild thrombocytopenia
Case Report A Case of False-Positive Mycobacterium tuberculosis Caused by Mycobacterium celatum
Mycobacterium celatum is a nontuberculous mycobacterium shown to cause symptoms similar to pulmonary M. tuberculosis. Certain strains have been shown to cross-react with the probes used to detect M. tuberculosis, making this a diagnostic challenge. We present a 56-year-old gentleman who developed signs and symptoms of lung infection with computed tomography scan of the chest showing right lung apex cavitation. Serial sputum samples were positive for acid-fast bacilli and nucleic acid amplification testing identified M. tuberculosis ribosomal RNA, resulting in treatment initiation. Further testing with high performance liquid chromatography showed a pattern consistent with M. celatum. This case illustrates the potential for M. celatum to mimic M. tuberculosis in both its clinical history and laboratory testing due to the identical oligonucleotide sequence contained in both. An increasing number of case reports suggest that early reliable differentiation could reduce unnecessary treatment and public health intervention associated with misdiagnosed tuberculosis
Study the Behavior of Long Spiral Tube Adsorber for Oxygen Separation from Air
Single long spiral tube column (25 mm diameter, and 4 m bed length) had been constructed to study the separation of oxygen from air using commercial 13X zeolite. The effect of adsorption pressure on the system breakthrough curves was studied. Single column with initial air pressurizing simulates the work of 2- columns, 4-steps PSA process, whereas single column with initial intermediate pure oxygen pressurizing simulates the work of 2-columns, 6-steps PSA process with pressure equalization steps of the two columns. No significant effect of pressure on the product oxygen purity is noticed when pressure increased from 2 to 5 bar in both cases. For initial air pressurizing case, the average maximum effluent oxygen purity of 88% is obtained. The range of zeolite loading capacity is q=0.25-0.35 mole N2/kg zeolite, and only 40% of the range has been utilized before breakthrough time. Whereas for initial oxygen pressurizing case, the maximum oxygen purity of 95% is obtained. The range of zeolite loading capacity is q=0.39-0.87 mole N2/kg zeolite, and 95% of the range has been utilized before breakthrough time, which agree well with the equilibrium data of multicomponent Langmuir adsorption equation
SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study
Background
Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling.
Methods
The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18â49, 50â69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty.
Results
NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year.
Conclusion
As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population
Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950â2021, 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 2020â21 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 60·5â65·1] decline), and increased during the COVID-19 pandemic period (2020â21; 5·1% [0·9â9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98â5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50â6·01) in 2019. An estimated 131 million (126â137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7â17·2) 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 (20·8â24·8), from 49·0 years (46·7â51·3) to 71·7 years (70·9â72·5). Global life expectancy at birth declined by 1·6 years (1·0â2·2) 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 (7·67â8·13) 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% [28·4â52·7]) and south Asia (26·3% [9·0â44·7]). 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
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990â2021: 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 56â604 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 100â000 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 100â000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100â000 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 100â000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100â000 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
Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries
Abstract
Background
Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres.
Methods
This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and lowâmiddle-income countries.
Results
In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of âsingle-useâ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for lowâmiddle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia.
Conclusion
This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both highâ and lowâmiddleâincome countries
Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries
Background
Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres.
Methods
This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and lowâmiddle-income countries.
Results
In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of âsingle-useâ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for lowâmiddle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia.
Conclusion
This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both highâ and lowâmiddleâincome countries