Background Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen-drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. MethodsWe estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen-drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drugresistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. FindingsOn the basis of our predictive statistical models, there were an estimated 4•95 million (3•62-6•57) deaths associated with bacterial AMR in 2019, including 1•27 million (95% UI 0•911-1•71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27•3 deaths per 100 000 (20•9-35•3), and lowest in Australasia, at 6•5 deaths (4•3-9•4) per 100 000. Lower respiratory infections accounted for more than 1•5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000-1 270 000) deaths attributable to AMR and 3•57 million (2•62-4•78) deaths associated with AMR in 2019. One pathogen-drug combination, meticillinresistant S aureus, caused more than 100 000 deaths attributa...

Background As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has remained in Latin America, Mexico has become the third country with the highest death rate worldwide. Data regarding in-hospital mortality and its risk factors, as well as the impact of hospital overcrowding in Latin America has not been thoroughly explored. Methods and findings In this prospective cohort study, we enrolled consecutive adult patients hospitalized with severe confirmed COVID-19 pneumonia at a SARS-CoV-2 referral center in Mexico City from February 26th, 2020, to June 5th, 2020. A total of 800 patients were admitted with confirmed diagnosis, mean age was 51.9 ± 13.9 years, 61% were males, 85% were either obese or overweight, 30% had hypertension and 26% type 2 diabetes. From those 800, 559 recovered (69.9%) and 241 died (30.1%). Among survivors, 101 (18%) received invasive mechanical ventilation (IMV) and 458 (82%) were managed outside the intensive care unit (ICU); mortality in the ICU was 49%. From the non-survivors, 45.6% (n = 110) did not receive full support due to lack of ICU bed availability. Within this subgroup the main cause of death was acute respiratory distress syndrome (ARDS) in 95% of the cases, whereas among the non-survivors who received full (n = 105) support the main cause of death was septic shock (45%) followed by ARDS (29%). The main risk factors associated with in-hospital death were male sex (RR 2.05, 95% CI 1.34–3.12), obesity (RR 1.62, 95% CI 1.14–2.32)—in particular morbid obesity (RR 3.38, 95%CI 1.63–7.00)—and oxygen saturation < 80% on admission (RR 4.8, 95%CI 3.26–7.31). Conclusions In this study we found similar in-hospital and ICU mortality, as well as risk factors for mortality, compared to previous reports. However, 45% of the patients who did not survive justified admission to ICU but did not receive IMV / ICU care due to the unavailability of ICU beds. Furthermore, mortality rate over time was mainly due to the availability of ICU beds, indirectly suggesting that overcrowding was one of the main factors that contributed to hospital mortality.

Background: Regional information regarding the characteristics of patients with coronavirus disease (COVID)-19 is needed for a better understanding of the pandemic. Objective: The objective of the study to describe the clinical features of COVID-19 patients diagnosed in a tertiary-care center in Mexico City and to assess differences according to the treatment setting (ambulatory vs. hospital) and to the need of intensive care (IC). Methods: We conducted a prospective cohort, including consecutive

Objective Sarcopenia has been related to negative outcomes in different clinical scenarios from critical illness to chronic conditions. The aim of this study was to verify whether there was an association between low skeletal muscle index and in-hospital mortality, intensive care unit admission, and invasive mechanical ventilation need in hospitalized patients with COVID-19. Design This was a retrospective cohort study of a referral center for COVID-19. We included all consecutive patients admitted to the hospital between February 26 and May 15, 2020, with a confirmed diagnosis of COVID-19. Skeletal muscle index was assessed from a transverse computed tomography image at the level of twelfth thoracic vertebra with National Institutes of Health ImageJ software, and statistical analysis was performed to find an association between skeletal muscle index and in-hospital mortality, need of invasive mechanical ventilation, and intensive care unit admission. Results We included 519 patients, the median age was 51 (42–61) yrs, and 115 patients (22%) had low skeletal muscle index. On multivariable analysis, skeletal muscle index was not associated with mortality, intensive care unit admission, or invasive mechanical ventilation need nor in a subanalysis of patients 65 yrs or older. Conclusions Skeletal muscle index determined by computed tomography at the level of twelfth thoracic vertebra was not associated with negative outcomes in hospitalized patients with COVID-19.