Impact of First Wave of COVID-19 Pandemic on Mortality at Emergency Department in Older Patients with COVID and Non-COVID Diagnoses.

INTRODUCTION: Mortality in emergency departments (EDs) is not well known. This study aimed to assess the impact of the first-wave pandemic on deaths accounted in the ED of older patients with COVID and non-COVID diseases. METHODS: We used data from the Emergency Department and Elderly Needs (EDEN) cohort (pre-COVID period) and from the EDEN-COVID cohort (COVID period) that included all patients ≥65 years seen in 52 Spanish EDs from April 1 to 7, 2019, and March 30 to April 5, 2020, respectively. We recorded patient characteristics and final destination at ED. We compared older patients in the pre-COVID period, with older patients with non-COVID and with COVID-19. ED-mortality (before discharge or hospitalization) is the prior outcome and is expressed as an adjusted odds ratio (aOR) with 95% interval confidence. RESULTS: We included 23,338 older patients from the pre-COVID period (aged 78.3 [8.1] years), 6,715 patients with non-COVID conditions (aged 78.9 [8.2] years) and 3,055 with COVID (aged 78.3 [8.3] years) from the COVID period. Compared to the older patients, pre-COVID period, patients with non-COVID and with COVID-19 were more often male, referred by a doctor and by ambulance, with more comorbidity and disability, dementia, nursing home, and more risk according to qSOFA, respectively (p < 0.001). Compared to the pre-COVID period, patients with non-COVID and with COVID-19 were more often to be hospitalized from ED (24.8% vs. 44.3% vs. 79.1%) and were more often to die in ED (0.6% vs. 1.2% vs. 2.2%), respectively (p < 0.001). Compared to the pre-COVID period, aOR for age, sex, comorbidity and disability, ED mortality in elderly patients cared in ED during the COVID period was 2.31 (95% confidence interval [CI]: 1.76-3.06), and 3.75 (95% CI: 2.77-5.07) for patients with COVID. By adding the variable qSOFA to the model, such OR were 1.59 (95% CI: 1.11-2.30) and 2.16 (95% CI: 1.47-3.17), respectively. CONCLUSIONS: During the early first pandemic wave of COVID-19, more complex and life-threatening older with COVID and non-COVID diseases were seen compared to the pre-COVID period. In addition, the need for hospitalization and the ED mortality doubled in non-COVID and tripled in COVID diagnosis. This increase in ED mortality is not only explained by the complexity or severity of the elderly patients but also because of the system's overload.

Application of MALDI-TOF MS to species complex differentiation and strain typing of food related fungi: Case studies with Aspergillus section Flavi species and Penicillium roqueforti isolates.

Filamentous fungi are one of the main causes of food losses worldwide and their ability to produce mycotoxins represents a hazard for human health. Their correct and rapid identification is thus crucial to manage food safety. In recent years, MALDI-TOF emerged as a rapid and reliable tool for fungi identification and was applied to typing of bacteria and yeasts, but few studies focused on filamentous fungal species complex differentiation and typing. Therefore, the aim of this study was to evaluate the use of MALDI-TOF to identify species of the Aspergillus section Flavi, and to differentiate Penicillium roqueforti isolates from three distinct genetic populations. Spectra were acquired from 23 Aspergillus species and integrated into a database for which cross-validation led to more than 99% of correctly attributed spectra. For P. roqueforti, spectra were acquired from 63 strains and a two-step calibration procedure was applied before database construction. Cross-validation and external validation respectively led to 94% and 95% of spectra attributed to the right population. Results obtained here suggested very good agreement between spectral and genetic data analysis for both Aspergillus species and P. roqueforti, demonstrating MALDI-TOF applicability as a fast and easy alternative to molecular techniques for species complex differentiation and strain typing of filamentous fungi.

Development and application of MALDI-TOF MS for identification of food spoilage fungi.

Filamentous fungi are frequently involved in food spoilage and cause important food losses and substantial economic damage. Their rapid and accurate identification is a key step to better manage food safety and quality. In recent years, MALDI-TOF MS has emerged as a powerful tool to identify microorganisms and has successfully been applied to the identification of filamentous fungi especially in the clinical context. The aim of this study was to implement a spectral database representative of food spoilage molds. To this end, after application of a standardized extraction protocol, 6477 spectra were acquired from 618 fungal strains belonging to 136 species and integrated in the VITEK MS database. The performances of this database were then evaluated by cross-validation and ∼95% of correct identification to the species level was achieved, independently of the cultivation medium and incubation time. The database was also challenged with external isolates belonging to 52 species claimed in the database and 90% were correctly identified to the species level. To our best knowledge, this is the most comprehensive database of food-relevant filamentous fungi developed to date. This study demonstrates that MALDI-TOF MS could be an alternative to conventional techniques for the rapid and reliable identification of spoilage fungi in food and industrial environments.