NCT04401228

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.

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 60 (actual)
• Sponsor: Clinique Saint Pierre Ottignies · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: —

Summary

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 .

Conditions

• COVID19
• Pneumonia, Viral
• Inflammatory Response

Interventions

Type	Name	Description
OTHER	predict admission of covid-19 patients to ICU and death with routine and quickly avalaible clinical, biological and radiological variables?	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

Timeline

• Start date: 2020-03-01
• Primary completion: 2020-05-01
• Completion: 2021-01-01
• First posted: 2020-05-26
• Last updated: 2020-05-26

Locations

1 site across 1 country: Belgium