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2.
Infect Dis (Lond) ; 53(10): 779-788, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1240868

ABSTRACT

BACKGROUND: Reduced mortality at 28 days in patients treated with corticosteroids was demonstrated, but this result was not confirmed by certain large epidemiological studies. Our aim was to determine whether corticosteroids improve the outcomes of our patients hospitalized with COVID-19 pneumonia. METHODS: Our retrospective, single centre cohort study included consecutive patients hospitalized for moderate to severe COVID-19 pneumonia between March 15 and April 15 2020. An early short course of corticosteroids was given during the second phase of the study. The primary composite endpoint was the need for mechanical ventilation or mortality within 28 days of admission. A multivariate logistic regression model was used to estimate the propensity score, i.e. the probability of each patient receiving corticosteroid therapy based on the initial variables. RESULTS: About 120 consecutive patients were included, 39 in the "corticosteroids group", 81 in the "no corticosteroids group"; their mean ages (±SD) were 66.4 ± 14.1 and 66.1 ± 15.2 years, respectively. Mechanical ventilation-free survival at 28 days was higher in the "corticosteroids group" than in the "no corticosteroids group" (71% and 29% of cases, respectively, p < .0001). The effect of corticosteroids was confirmed with HR .28 (95%CI .10-.79), p = .02. In older and comorbid patients who were not eligible for intensive care, the effect of corticosteroid therapy was also beneficial (HR .36 (95%CI .16-.80), p = .01). CONCLUSION: A short course of corticosteroids reduced the risks of death or mechanical ventilation in patients with moderate to severe COVID-19 pneumonia in all patients and also in older and comorbid patients not eligible for intensive care.


Subject(s)
COVID-19 , Respiration, Artificial , Adrenal Cortex Hormones/therapeutic use , Aged , Aged, 80 and over , Cohort Studies , Humans , Middle Aged , Retrospective Studies , SARS-CoV-2
4.
Bull Cancer ; 107(11): 1129-1137, 2020 Nov.
Article in French | MEDLINE | ID: covidwho-848979

ABSTRACT

PURPOSE: Human, material, and financial resources being limited, the organization of the care system must allow an efficient allocation of resources. The management of cancers leads to specific and repetitive care for which the reimbursement of transport costs represents a high cost. We carried out an analysis of the additional transport costs, linked to the care of patients in Île-de-France, in a center other than the radiotherapy center closest to their home. MATERIALS AND METHODS: Using data from the Île-de-France Regional Health Agency, we have created a model evaluating the additional cost linked to transport generated by the care of a radiotherapy patient far from his home. In order to take into account the uncertainties linked to the hypotheses made in the development of the model, we carried out deterministic and probabilistic sensitivity analyzes. RESULTS: In the base case, the additional annual cost related to transport was 841,176 euros in Île-de-France. The probabilistic sensitivity analysis reports a total annual additional cost of 2,817,481 euros. CONCLUSION: Our results are similar to a report from the General Inspectorate of Social Affairs published in July 2011, which then pointed to an additional cost of between 4 and 6 million euros annually. The long-term care of cancer patients from their homes contributes to a deterioration in the quality of life linked to travel times, a delay in the care of potential treatment complications, and the spread of infectious diseases, such as COVID-19, and bacteria resistant to antibiotics.


Subject(s)
Ambulances/economics , Cancer Care Facilities/supply & distribution , Health Services Accessibility/economics , Neoplasms/radiotherapy , Transportation of Patients/economics , Ambulances/statistics & numerical data , Costs and Cost Analysis , France , Health Services Accessibility/statistics & numerical data , Humans , Models, Statistical , Neoplasms/economics , Paris , Quality of Life , Resource Allocation , Time Factors , Transportation of Patients/statistics & numerical data , Uncertainty
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