Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT04896944 |
| Other study ID # |
Centre Hospitalier Saint Denis |
| Secondary ID |
|
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
March 13, 2020 |
| Est. completion date |
April 30, 2021 |
Study information
| Verified date |
April 2021 |
| Source |
Centre Hospitalier de Saint-Denis |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Is precariousness a risk factor for COVID-19 mortality in intensive care units ?
Abstract
Background: During the SARS-CoV-2 pandemic, the first wave overwhelmed hospitals in Paris
area (Ile-de-France) with a variable impact depending on the territory. Several studies
highlighted variable ICU mortality rates during COVID-19 surges across territories (10 to
60%) with higher rates in those most affected by poverty. We assessed the impact of
precariousness, as an independent risk factor, on mortality linked to Covid-19 between ICUs
at Delafontaine hospital and Ambroise Paré hospital.
Method: Investigators carry out a retrospective observational cohort study of consecutive ICU
patients aged ≥ 18 years admitted at Delafontaine and Ambroise Paré hospitals during the
first wave of the Covid-19 outbreak in order to compare mortality rates according to
predefined risk factors (age, diabetes, arterial hypertension, BMI, active solid or
haematological cancer, IGS2, poverty rate at the threshold of 60% (%) according to the island
grouped for statistical information (IRIS)37 of the patient, invasive ventilation or not)
that include precariousness.
Results:
Conclusion:
Description:
Introduction:
During the SARS-CoV-2 pandemic, the first health crisis overwhelmed hospitals in Ile de
France with a different impact depending on the territory . According to data on deaths
registered in the civil registry published by the National Institute of Statistics and
Economic Studies (INSEE), Seine-Saint-Denis has recorded the highest excess mortality rate in
Ile-de-France, over the period from 1st March to 19th April. Seine-Saint-Denis has an excess
mortality of over 130%, compared to over 74% in Paris and over 122% in Hauts-de-Seine. By
considering the mortality rates according to the place of residence rather than the place of
death, excess mortality has reached 134% in Seine-Saint-Denis, over 114% in Hauts-de-Seine,
and over 99 % regarding Paris.
Seine-Saint-Denis is one of the French department most affected by poverty, which is a factor
of vulnerability, and constitutes a risk factor for mortality after hospitalization in the
context of traumatic, cardiovascular or cancer pathologies. In addition, precarious people
have a reduced life expectancy, but it is not a risk factor for ICU mortality when
considering severity on admission.
In Ile-de-France, the mortality rate in intensive care could significantly vary depending on
the territory (10 to 60%), reflecting thus the disparities noticed in mortality from
Covid-19. The opensafely study enumerates some of the primary mortality risk factors from
Covid-19 such as age, sex, obesity, smoking, ethnicity, diabetes, solid and hematological
cancers, kidney failure, chronic cardiorespiratory diseases but also precariousness
independently and with a dose-response effect, whereas these risk factors could result from
precariousness itself.
Knowing these risk factors for severe infection with Covid-19, investigators assume a link
between precariousness and mortality in intensive care with Covid-19 pneumonia.
To validate this hypothesis, investigators suggest to study two intensive care populations
(Ambroise Paré Boulogne Hospital in the Hauts-de-Seine and Delafontaine Hospital in
Seine-Saint-Denis) from contrasted territories regarding the socio-economic context in Ile de
France. The socio-demographic characteristics of Seine-Saint-Denis may be one of the reason
to explain this particularity. It is an area densely populated (6,802 inhabitants per km2),
just like Hauts-de-Seine (9,164 inhabitants / km2) with households often living in
over-occupied dwellings (21% against 12,8% in Hauts-de-Seine and 5% in France excluding
Mayotte). The socio-professional category of workers is more represented than in the other
departments of Ile-de-France and the population therefore does not necessarily have a job
suitable for teleworking. Hence the fact that precariousness could promote the circulation of
the virus.
Materials and method:
Definition: the definition of precariousness is complex, multifactorial and non-consensual.
Precariousness is describe as "a state of social instability characterized by the absence of
one or more securities, in particular that of employment, allowing individuals and families
to assume their professional, family and social obligations, and to enjoy their fundamental
rights ".
In order to establish a link between precariousness and mortality in intensive care from
Covid-19, investigators choose to determine the precariousness of each patient according to
the economic data of the National Institute of Statistics and Economic Studies. It would
allow to obtain a poverty rate (percentage of living below 60% of median income) according to
the place of residence of each one, which we will divide into quintiles.
Hypothesis: there is a difference in mortality between resuscitation services at Delafontaine
hospital and Ambroise Paré hospital with the underlying idea that precariousness is an
independent risk factor for mortality linked to Covid-19.
Experimental plan and objectives: investigators will carry out a retrospective observational
cohort study on analysis of the files of patients hospitalized in intensive care at
Delafontaine and Ambroise Paré hospitals, aiming to compare their mortality according to
predefined risk factors during the first wave of the epidemic at Covid-19 (admission dates
between March 13 and May 11, 2020).
Inclusion criteria: all patients hospitalized in intensive care at Delafontaine hospital (12
intensive care beds and 6 CCU beds) and Ambroise Paré hospital (12 intensive care beds and 6
CCU beds) that has developed a Covid-19 pneumonitis confirmed biologically by nasopharyngeal
PCR or on deep respiratory samples (bronchial, tracheal aspiration or bronchoalveolar lavage)
or strongly suspected with a compatible CT27 and a very evocative clinical history depending
on the practitioner in charge would be included into the study.
Exclusion criteria: all minor patients under the age of 18 and patients transferred after
less than 24 hours of care in the service would be excluded.
Study locations: this study concerns the Ambroise Paré hospital in Boulogne and the
Delafontaine hospital in Saint-Denis, whose sectors are different, specifically regarding
precariousness of their surrounding populations.
Data to be collected:
- Data studied: age, diabetes, arterial hypertension, BMI, unhealed solid or
haematological cancer, IGS2, poverty rate at the threshold of 60% (%) according to the
island grouped for statistical information (IRIS) of the patient, invasive ventilation
or not, date of start of invasive ventilation, date of end of ventilation, NIV or high
flow oxygen therapy at initial treatment, prone position, curarization, placement of
ECMO, introduction of corticosteroid therapy within 7 first days of hospitalization,
date of entry (defined as D0), date of discharge from intensive care (death or
conventional discharge), date of discharge from hospital, death and date of death if it
occurred in hospital.
- Patients transferred to another intensive care unit after the first 24 hours for
specific treatment or discharge from the service will be included and their data
recovered by the recovery of hospitalization reports
- Patients discharged from the hospital for a rehabilitation center or another long
stay are considered alive for the study and will not have follow-up after
resuscitation
- Data to compare the workload related to Covid on the two hospitals will be collected in
order to discuss the results obtained (see table below).
- Average number of Covid patients present each day in each hospital during the
period (Average patients / days)
- Number of usual conventional hospital beds (permanently open which can admit
patient urgently and / or whose length of stay is not under control)
- Number of resuscitation beds and usual CCUs
- Average number of Covid patients present each day in each intensive care unit
- Total number of patients transferred to an intensive care unit in another hospital
over the period within the first 24 hours of care by the intensive care team
Primary endpoint: mortality in intensive care at 90 days.
Secondary judgment criteria: mortality at 90 days in hospital, length of hospital stay in
intensive care unit, length of hospital stay in hospital.
Statistics:
- univariate comparison of risk factors in the 2 groups (Chi2 / Student)
- multivariate analysis on variables whose frequency varies in the 2 groups (logistic
regression test)
Discussion:
Description of observed outcome, discussed after having identified side effect resulting from
the differences between intensive care units of two hospitals, which could be a compounding
factors during patient care.
Main compounding factors would be the workload on the hospital and the specific initial
treatments in the lack of data from the literature at this stage of the pandemic.
