Ignite Creation Date:
2025-12-24 @ 2:40 PM
Ignite Modification Date:
2025-12-24 @ 2:40 PM
Study NCT ID:
NCT04537559
Status:
UNKNOWN
Last Update Posted:
2022-03-25
First Post:
2020-08-27
Is Possible Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Impact of COVID-19 Outbreak on Non-COVID-19 Patients
Sponsor:
University Hospital, Geneva
Organization:
Study Overview
Official Title:
Impact of the COVID-19 Pandemic on the Morbidity and Mortality of Non-COVID-19 Patients Hospitalized Around the Epidemic Peak in the Geneva Area (Switzerland) (No COVID Impact)
Status:
UNKNOWN
Status Verified Date:
2022-03
Last Known Status:
ENROLLING_BY_INVITATION
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:
NoCOVImpact
Brief Summary:
The Geneva Canton organized the health crisis of the COVID-19 epidemic around the care of COVID patients at the University Hospital (HUG), by moving the care of non-COVID patients to private hospitals of the canton. The COVID epidemic appears to have been associated with a decrease in consultations and care for non-COVID patients. An excess of morbidity and mortality (non-COVID) would be possible during or after the epidemic in connection with this "under-medicalization" of non-COVID patients.
The aim of this study is to measure and analyze the impact on the morbidity and mortality of inpatients during and after the COVID-19 epidemic in the adult inpatient wards of HUG and township hospitals / clinics.
The aim of this study is to measure and analyze the impact on the morbidity and mortality of inpatients during and after the COVID-19 epidemic in the adult inpatient wards of HUG and township hospitals / clinics.
Detailed Description:
The analysis of the various results will be carried out on all HUGs and on the various hospitals / clinics in the canton.
A survival analysis for the outcome of death or rehospitalization will be performed, with a comparison according to each period.
After epidemy evolution, finally, the outcomes will be compared between periods pre-COVID (from 01 march 2019 to 28 february 2020) versus per-COVID (01 march 2020 to 28 february 2022), and versus post-COVID (01 march 2022 to 28 february 2023). And comparaison would be performed between periods during the wave (per-wave) versus periods inter-wave.
A description will be made in number (%) for numerical data and in median (IQR) for quantitative data. Univariate comparisons between the different periods will be carried out by statistical tests, parametric or not, adapted according to the data (Chi2 or Fisher's test for qualitative data, Student's test or Mann-Whitney-Wilcoxon for quantitative data). Statistical significance will be retained in the event of p \<0.05.
Multivariate analysis will be performed by logistic regression for the main outcome and by cox model for survival analysis. Different variables will be included in the models, including data on gender, age and comorbidity, as well as any variable having a difference with p \<0.2 in univariate analysis.
Secondary analyzes will be carried out by pathology (as the main diagnosis) according to the specific results defined for each situation. In retrospective analysis, these specific data will be relatively limited on the HUG area of full analysis brings together around total of 240,000 hospital stays. The main outcome data will be complete with no missing data. On the other hand, since this is retrospective data, it is possible that some important variables are missing. In this case, other patient data with missing data will not be included in the multivariate analyzes. In the event of missing data greater than 10%, a second sensitivity analysis may be performed after replacing the missing data with a multiple imputation method.
A survival analysis for the outcome of death or rehospitalization will be performed, with a comparison according to each period.
After epidemy evolution, finally, the outcomes will be compared between periods pre-COVID (from 01 march 2019 to 28 february 2020) versus per-COVID (01 march 2020 to 28 february 2022), and versus post-COVID (01 march 2022 to 28 february 2023). And comparaison would be performed between periods during the wave (per-wave) versus periods inter-wave.
A description will be made in number (%) for numerical data and in median (IQR) for quantitative data. Univariate comparisons between the different periods will be carried out by statistical tests, parametric or not, adapted according to the data (Chi2 or Fisher's test for qualitative data, Student's test or Mann-Whitney-Wilcoxon for quantitative data). Statistical significance will be retained in the event of p \<0.05.
Multivariate analysis will be performed by logistic regression for the main outcome and by cox model for survival analysis. Different variables will be included in the models, including data on gender, age and comorbidity, as well as any variable having a difference with p \<0.2 in univariate analysis.
Secondary analyzes will be carried out by pathology (as the main diagnosis) according to the specific results defined for each situation. In retrospective analysis, these specific data will be relatively limited on the HUG area of full analysis brings together around total of 240,000 hospital stays. The main outcome data will be complete with no missing data. On the other hand, since this is retrospective data, it is possible that some important variables are missing. In this case, other patient data with missing data will not be included in the multivariate analyzes. In the event of missing data greater than 10%, a second sensitivity analysis may be performed after replacing the missing data with a multiple imputation method.
Study Oversight
Has Oversight DMC:
False
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?: