No abstract

BackgroundSimple and reliable predictive scores for intensive care admissions and death based on clinical data are still lacking. The goal of this study is to implement such scores based on patients coming from our population catchment area and to compare them to available ones. These scores adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guidelines.MethodsMonocentric retrospective cohort study run from early March to end of May in Clinique Saint-Pierre Ottignies, a secondary care hospital located in Ottignies-Louvain-la-Neuve, Belgium. The outcomes of the study are (i) admission in the Intensive Care Unit and (ii) death. All patients admitted in the Emergency Department with a positive RT-PCR SARS-CoV-2 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. A recently published predictive score conducted on a large scale was used as a benchmark value (Liang score)1. Logistic regressions were used to develop predictive scores for (i) admission to ICU among emergency ward patients; (ii) death among ICU patients on 40 clinical variables. These models were based on medical intuition and simple model selection tools. Their predictive capabilities were then compared to Liang score. ConclusionsOur results suggest that Liang score may not provide reliable guidance for ICU admission and death. Predictive score based on a large-scale Chinese study cannot be applied in the Belgian population, suggesting a predominant role in genetic factors for SARS-CoV-2 susceptibility. In our small cohort, it appears that LDH above 579 UI/L and venous lactate above 3.02 mmol/l may be considered as good predictive biological factors for ICU admission. With regards to death risk, Neutrophil/lymphocyte ratio above 22.1, tobacco abuse status and respiratory impairment appears to be relevant predictive factors. Predictive score for admission to ICU or death based on clinical data are still needed in secondary hospital and hospitals in developing countries that do not have high-performance laboratories. Optimal allocation of resources guided by evidence-based indicators will best guide patients at time of admission and avoid futile treatments in intensive care units.