Factors associated with hospital admission and adverse outcome for COVID-19: Role of social factors and medical care.

BACKGROUND: Beyond sex, age, and various comorbidities, geographical origin and socioeconomic deprivation are associated with Coronavirus Disease (COVID-19) morbidity and mortality in the general population. We aimed to assess factors associated with severe forms of COVID-19 after a hospital emergency department visit, focusing on socioeconomic factors. METHODS: Patients with laboratory-confirmed COVID-19 attending the emergency department of Béclère Hospital (France) in March-April 2020 were included. Postal addresses were used to obtain two geographical deprivation indices at the neighborhood level. Factors associated with hospitalization and factors associated with adverse outcomes, i.e. mechanical ventilation or death, were studied using logistic and Cox analyses, respectively. RESULTS: Among 399 included patients, 321 were hospitalized. Neither geographical origin nor socioeconomic deprivation was associated with any of the outcomes. Being male, older, overweight or obese, diabetic, or having a neuropsychiatric disorder were independent risk factors for hospitalization. Among 296 patients hospitalized at Béclère Hospital, 91 experienced an adverse outcome. Older age, being overweight or obese, desaturation and extent of chest CT scan lesions>25% at admission (aHR: 2.2 [95% CI: 1.3-3.5]) and higher peak CRP levels and acute kidney failure (aHR: 2.0 [1.2-3.3]) during follow-up were independently associated with adverse outcomes, whereas treatment with hydrocortisone reduced the risk of mechanical ventilation or death by half (aHR: 0.5 [0.3-0.8]). CONCLUSION: No association between geographical origin or socioeconomic deprivation and the occurrence of a severe form of COVID-19 was observed in our population after arrival to the emergency department. Empirical corticosteroid use with hydrocortisone had a strong protective impact.

Why are people still dying of drug-susceptible TB in Paris in the 21st century?

BACKGROUND: Although the burden of TB is lower in France than in low-income countries, patients continue to die from TB in Paris. Our goal was to describe TB-related deaths and to identify associated risk factors.METHODS: We conducted a retrospective cohort study in two hospitals in Paris between 2013 and 2018. All patients with drug-susceptible TB were included and followed until end of treatment. The primary outcome was death. We performed univariate and multivariate analysis using Cox proportional hazard model.RESULTS: Of the 523 patients included, 362 were men (median age 37 years), of whom 24 patients died (4.5%). The final survival model concluded that age (HR 1.1 for each additional year), not living in one´s own accommodation (HR 5.9), being born in France (HR 8.0), being alcoholic (HR 4.2), having a history of cancer (HR 7.1) or meningeal or miliary TB (HR 8.2) were associated with a higher risk of death.CONCLUSION: The rate of TB-associated death is unacceptably high for a curable disease. To note, patients born in France were much more at risk of death than immigrants. We believe raising awareness among healthcare professionals is a potentially easy and efficient lever for improving care.

Predictive modelling of Escherichia coli O157:H7: inclusion of carbon dioxide as a fourth factor in a pre-existing model.

Two models for Escherichia coli O157:H7 are compared, one with growth-controlling factors pH (4.5-7.0), temperature (10-30 degrees C) and NaCl concentration (0.5-6.5% w/v) and the other with the same factors and ranges, but with the addition of carbon dioxide (CO2: 10-80% v/v). Validation of the four-factor model, to include food packed in modified atmospheres containing CO2, was not possible due to lack of published data. However, where CO2 concentration was entered as 0%, only minor differences occurred between the predictions from the two models for the same conditions of pH, NaCl and temperature; consequently reliable, safe predictions using the four-factor model, with CO2 concentration recorded as 0%, can be made for foods packed in air. At temperatures from 10 to 30 degrees C, it was found that lower (10 and 20%) concentrations of CO2 had little effect on lag times and growth rates, and higher concentrations still permitted growth of E. coli O157:H7 under a wide range of conditions of NaCl concentration, pH value and temperature, suggesting that the organism is relatively CO2-tolerant.

Predictive modelling of growth of Listeria monocytogenes. The effects on growth of NaCl, pH, storage temperature and NaNO2.

The effect of NaCl concentration (5.0 115.0 g/l). pH value (4.0-7.2), temperature (1-35 degrees C) and NaNO2 concentration (0 200 mg/l) on the growth responses of Listeria monocytogenes, in laboratory medium was investigated. The growth curves generated within this matrix of conditions were fitted using the function of Baranyi and Roberts (1994) and the growth responses modelled using a quadratic polynomial to produce response surfaces. Growth curves could then be regenerated for any set of conditions within the experimental matrix and values predicted for the growth rate, doubling time, lag time and time to 1000-fold increase. The model was validated using data from published literature and was found to give realistic predictions for doubling times in foods, including meat and meat products, milk, dairy products and vegetables. Predictions from this model (Baranyi and Roberts. 1994) compared favourably with those from the models of Buchanan and Phillips (1990), Murphy et al. (1996) and the Food MicroModel.

Preparation and validation of a growth model for Bacillus cereus: the effects of temperature, pH, sodium chloride and carbon dioxide.

The growth responses of a vegetative inoculum of Bacillus cereus as influenced by varying conditions of temperature, pH value and sodium chloride concentration (% w/v) and carbondioxide concentration (% v/v) were determined in laboratory medium. Growth curves in concentrations of NaCl in the range 0.5-10.5% (w/v), pH values in the range 4.5-7.0, CO2 concentrations in the range 10-80% (v/v) and storage temperatures from 10 degrees C to 30 degrees C were fitted using the regime of Baranyi et al. (1993). A response surface model was prepared and predictions of doubling time, growth rate, lag time and time to 1000-fold increase could be obtained for any set of conditions within the matrix studied. This model is included in Food MicroModel Version 1. Predicted doubling times from the model were compared to observed doubling times in the literature and the model was found to give realistic estimates of doubling time for a range of foods including milk, meat and poultry and carbohydrate-based products.