Predictive Models for Intensive Care Admission and Death of COVID-19
Development and Validation of Predictive Models for Intensive Care Admission and Death of COVID-19 Patients in a Secondary Care Hospital in Belgium.
To build simple and reliable predictive scores for intensive care admissions and deaths in COVID19 patients. These scores adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guidelines.
The outcomes of the study are (i) admission in the Intensive Care Unit admission and (ii) death.
All patients admitted in the Emergency Department with a positive reverse transcription-polymerase chain reaction SARS-COV2 test were included in the study. Routine clinical and laboratory data were collected at their admission and during their stay. Chest X-Rays and CT-Scans were performed and analyzed by a senior radiologist.
Generalized Linear Models using a binomial distribution with a logit link function (R software version X) were used to develop predictive scores for (i) admission to ICU among emergency ward patients; (ii) death among ICU patients. A first panel of Number Models with the highest AIC (BIC) was preselected. Ten-fold cross-validation was then used to estimate the out-of-sample prediction error among these preselected models. The one with the smallest prediction error was in the end singled out .
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
-
-
Brabant Wallon
-
Ottignies, Brabant Wallon, Belgium, 1340
- Clinique Saint-Pierre
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- RT-PCR + SARS Cov2 pneumonia
Exclusion Criteria:
- < 18 ans -* GOLD 3 or 4 CPOD
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
covid ICU patients
|
patients were questioned about their usual medication (Sartan, angiotensin-converting enzyme inhibitors, nonsteroidal anti-inflammatory drug, immunosuppressive drugs), their health condition (diabetes, hypertension, tobacco use, mental status). The Body mass index was computed. Age, gender, caucasian/african, weight, body mass index, number of days with symptoms before hospitalization, asthenia, pyrexia, dyspnea, chest pain, digestive sign, anosmia, ageusia, confusion, Travel or contact < one month, cigarette consumption ,hypertension, diabetes, mental status, angiotensin-converting-enzyme inhibitors, Sartan, non-steroidal anti-inflammatory drugs, immunosuppressive drugs, SpO2,Thoracic Computerized Tomography : % of lung injury, Thoracic Computerized Tomography : density of lung injury, blood type, white blood cells, neutrophils, lymphocytes, blood platelets, fibrinogen, ferritin, triglycerides, LDH, troponin, CRP. The dates of admission to ICU and death were recorded |
|
covid conventionnal ward
|
patients were questioned about their usual medication (Sartan, angiotensin-converting enzyme inhibitors, nonsteroidal anti-inflammatory drug, immunosuppressive drugs), their health condition (diabetes, hypertension, tobacco use, mental status). The Body mass index was computed. Age, gender, caucasian/african, weight, body mass index, number of days with symptoms before hospitalization, asthenia, pyrexia, dyspnea, chest pain, digestive sign, anosmia, ageusia, confusion, Travel or contact < one month, cigarette consumption ,hypertension, diabetes, mental status, angiotensin-converting-enzyme inhibitors, Sartan, non-steroidal anti-inflammatory drugs, immunosuppressive drugs, SpO2,Thoracic Computerized Tomography : % of lung injury, Thoracic Computerized Tomography : density of lung injury, blood type, white blood cells, neutrophils, lymphocytes, blood platelets, fibrinogen, ferritin, triglycerides, LDH, troponin, CRP. The dates of admission to ICU and death were recorded |
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
|
admission to ICU
Time Frame: through study completion, an average of 1 year
|
through study completion, an average of 1 year
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
|
death
Time Frame: through study completion, an average of 1 year
|
through study completion, an average of 1 year
|
Collaborators and Investigators
Sponsor
Sponsor
Publications and helpful links
General Publications
- Rubin GD, Ryerson CJ, Haramati LB, Sverzellati N, Kanne JP, Raoof S, Schluger NW, Volpi A, Yim JJ, Martin IBK, Anderson DJ, Kong C, Altes T, Bush A, Desai SR, Goldin J, Goo JM, Humbert M, Inoue Y, Kauczor HU, Luo F, Mazzone PJ, Prokop M, Remy-Jardin M, Richeldi L, Schaefer-Prokop CM, Tomiyama N, Wells AU, Leung AN. The Role of Chest Imaging in Patient Management During the COVID-19 Pandemic: A Multinational Consensus Statement From the Fleischner Society. Chest. 2020 Jul;158(1):106-116. doi: 10.1016/j.chest.2020.04.003. Epub 2020 Apr 7.
- Wynants L, Van Calster B, Collins GS, Riley RD, Heinze G, Schuit E, Bonten MMJ, Dahly DL, Damen JAA, Debray TPA, de Jong VMT, De Vos M, Dhiman P, Haller MC, Harhay MO, Henckaerts L, Heus P, Kammer M, Kreuzberger N, Lohmann A, Luijken K, Ma J, Martin GP, McLernon DJ, Andaur Navarro CL, Reitsma JB, Sergeant JC, Shi C, Skoetz N, Smits LJM, Snell KIE, Sperrin M, Spijker R, Steyerberg EW, Takada T, Tzoulaki I, van Kuijk SMJ, van Bussel B, van der Horst ICC, van Royen FS, Verbakel JY, Wallisch C, Wilkinson J, Wolff R, Hooft L, Moons KGM, van Smeden M. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. BMJ. 2020 Apr 7;369:m1328. doi: 10.1136/bmj.m1328. Erratum In: BMJ. 2020 Jun 3;369:m2204.
- Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement. Ann Intern Med. 2015 Jan 6;162(1):55-63. doi: 10.7326/M14-0697. Erratum In: Ann Intern Med. 2015 Apr 21;162(8):600.
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 0410508057
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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