Ignite Creation Date:
2024-05-06 @ 4:09 PM
Last Modification Date:
2024-10-26 @ 2:05 PM
Study NCT ID:
NCT04896944
Status:
COMPLETED
Last Update Posted:
2022-05-31
First Post:
2021-05-20
Brief Title:
Is Precariousness a Risk Factor for COVID-19 Mortality in Intensive Care
Sponsor:
Centre Hospitalier de Saint-Denis
Organization:
Centre Hospitalier de Saint-Denis
Study Overview
Official Title:
Is Precariousness a Risk Factor for COVID-19 Mortality in Intensive Care
Status:
COMPLETED
Status Verified Date:
2021-04
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief 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 IRIS37 of the patient invasive ventilation or not that include precariousness
Results
Conclusion
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 IRIS37 of the patient invasive ventilation or not that include precariousness
Results
Conclusion
Detailed 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 6802 inhabitants per km2 just like Hauts-de-Seine 9164 inhabitants km2 with households often living in over-occupied dwellings 21 against 128 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
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 6802 inhabitants per km2 just like Hauts-de-Seine 9164 inhabitants km2 with households often living in over-occupied dwellings 21 against 128 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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None