Browsing by Author "Furuya-Kanamori, Luis"

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    Fatal journeys: causes of death in international travellers in South America
    (2024) Allel, Kasim; Cabada, Miguel M.; Kiani, Behzad; Martin, Beatris Mario; Tanabe, Melinda; Restrepo, Angela Cadavid; Dos Santos, Gabriela De Souza; Lloveras, Susana; Shiferaw, Wondimeneh; Sartorius, Benn; Mills, Deborah J.; Lau, Colleen L.; Furuya-Kanamori, Luis
    Background: Understanding mortality among travellers is essential for mitigating risks and enhancing travel safety. However, limited evidence exists on severe illnesses and injuries leading to death among travellers, particularly in low- and middle-income countries and remote regions. Methods: We conducted a retrospective census study using country-level observational data from death certificates of travellers of seven South American countries (Argentina, Brazil, Chile, Colombia, Ecuador, Peru and Uruguay) from 2017 to 2021. Causes of death were evaluated using ICD-10 codes, categorized into non-communicable diseases (NCDs), communicable diseases and injuries. We quantified causes of death by demographic characteristics (e.g. age, sex) and geographical variables. Chi-square tests were used to assess differences between categories. We calculated crude mortality rates and incidence rate ratios (IRRs) per country's subregions. Results: A total of 17 245 deaths were reported. NCDs (55%) were the most common cause of death, followed by communicable diseases (23.4%) and injuries (18.1%). NCD-associated deaths increased after age 55 years and were highest among >= 85 years. Communicable diseases were more common at younger age (<20 years). Injury-associated deaths were more common in men (79.9%) and 25-29-year-olds (17.1%). Most deaths (68.2%) could have been avoided by prevention or treatment. Mortality risk was higher among travellers in bordering regions between countries. In Roraima (Brazil) and Norte de Santander (Colombia), locations bordering Venezuela, the death IRR was 863 and 60, respectively. These countries' reference mortality rates in those regions were much lower. More than 80% of the deaths in these border regions of Brazil and Colombia involved Venezuelan citizens. Conclusion: The study identified risk factors and high-risk locations for deaths among travellers in seven countries of South America. Our findings underscore the need for specific health interventions tailored to traveller demographics and destination to optimize prevention of avoidable deaths in South America.
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    Impact of inappropriate empirical antibiotic therapy on in-hospital mortality: a retrospective multicentre cohort study of patients with bloodstream infections in Chile, 2018–2022
    (2024) Allel, Kasim; Peters, Anne; Furuya-Kanamori, Luis; Spencer-Sandino, Maria; Pitchforth, Emma; Yakob, Laith; Munita, José M.; Undurraga Fourcade, Eduardo Andrés
    Introduction: Empirical antibiotic therapy is essential for treating bloodstream infections (BSI), yet there is limited evidence from resource-limited settings. We quantified the association of inappropriate empirical antibiotic therapy (IEAT) with in-hospital mortality and the associated burden on BSI patients in Chile. Methods: We used a retrospective multicentre cohort study of BSI cases in three Chilean tertiary hospitals (2018–2022) to assess the impact of IEAT on 30-day and overall in-hospital mortality and quantify excess disease and economic burdens associated with IEAT. We determined the appropriateness of pathogen-antimicrobial pairings based on in vitro susceptibilities and pathogen-corresponding antibiotic treatment, allowing a 48-hour window after the initial blood culture. We addressed confounding using propensity scores and inverse probability weights (IPW). We used IPW-weighted logistic competing-risk survival models, including time-varying independent variables after blood tests as controls. Results: Among 1323 BSI episodes, 432 (33%) received IEAT, with an average time to adequate therapy of 4.6 days. Compared with adequate treatment, IEAT was associated with 30-day and overall mortality risks that were 1.31 and 1.24 times higher, respectively. These risks were further inflated between twofold and fourfold when antibiotic-resistant bacteria (ARB) was included. Competing-risk models showed associations between IEAT and IEAT-ARB combinations with in-hospital mortality. Accounting for time-varying variables yielded similar results. The economic burden of IEAT resulted in an additional cost of ~US$9900 from premature mortality and 0.46 disability-adjusted life-years per patient with BSI. Conclusión: Approximately one in three patients received IEAT, often associated with ARB. IEAT was linked to increased mortality risk and higher economic costs. Timely appropriate treatment, early pathogen detection and resistance profiling are likely to improve health and financial outcomes at the population level.
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    The impact of inpatient bloodstream infections caused by antibiotic-resistant bacteria in low- and middle-income countries: A systematic review and meta-analysis
    (2023) Allel, Kasim; Stone, Jennifer; Undurraga Fourcade, Eduardo Andrés; Day, Lucy; Moore, Catrin E.; Lin, Leesa; Furuya-Kanamori, Luis; Yakob, Laith
    Background: Bloodstream infections (BSIs) produced by antibiotic-resistant bacteria (ARB) cause a substantial disease burden worldwide. However, most estimates come from high-income settings and thus are not globally representative. This study quantifies the excess mortality, length of hospital stay (LOS), intensive care unit (ICU) admission, and economic costs associated with ARB BSIs, compared to antibiotic-sensitive bacteria (ASB), among adult inpatients in low- and middle-income countries (LMICs).Methods and findings: We conducted a systematic review by searching 4 medical databases (PubMed, SCIELO, Scopus, and WHO’s Global Index Medicus; initial search n = 13,012 from their inception to August 1, 2022). We only included quantitative studies. Our final sample consisted of n = 109 articles, excluding studies from high-income countries, without our outcomes of interest, or without a clear source of bloodstream infection. Crude mortality, ICU admission, and LOS were meta-analysed using the inverse variance heterogeneity model for the general and subgroup analyses including bacterial Gram type, family, and resistance type. For economic costs, direct medical costs per bed-day were sourced from WHO-CHOICE. Mortality costs were estimated based on productivity loss from years of potential life lost due to premature mortality. All costs were in 2020 USD. We assessed studies’ quality and risk of publication bias using the MASTER framework. Multivariable meta-regressions were employed for the mortality and ICU admission outcomes only. Most included studies showed a significant increase in crude mortality (odds ratio (OR) 1.58, 95% CI [1.35 to 1.80], p < 0.001), total LOS (standardised mean difference “SMD” 0.49, 95% CI [0.20 to 0.78], p < 0.001), and ICU admission (OR 1.96, 95% CI [1.56 to 2.47], p < 0.001) for ARB versus ASB BSIs. Studies analysing Enterobacteriaceae, Acinetobacter baumanii, and Staphylococcus aureus in upper-middle-income countries from the African and Western Pacific regions showed the highest excess mortality, LOS, and ICU admission for ARB versus ASB BSIs per patient. Multivariable meta-regressions indicated that patients with resistant Acinetobacter baumanii BSIs had higher mortality odds when comparing ARB versus ASB BSI patients (OR 1.67, 95% CI [1.18 to 2.36], p 0.004). Excess direct medical costs were estimated at $12,442 (95% CI [$6,693 to $18,191]) for ARB versus ASB BSI per patient, with an average cost of $41,103 (95% CI [$30,931 to $51,274]) due to premature mortality. Limitations included the poor quality of some of the reviewed studies regarding the high risk of selective sampling or failure to adequately account for relevant confounders.Conclusions: We provide an overview of the impact ARB BSIs in limited resource settings derived from the existing literature. Drug resistance was associated with a substantial disease and economic burden in LMICs. Although, our results show wide heterogeneity between WHO regions, income groups, and pathogen–drug combinations. Overall, there is a paucity of BSI data from LMICs, which hinders implementation of country-specific policies and tracking of health progress.