Study design and setting
This prospective observational pragmatic cohort study took place during the COVID19 epidemic between March 13 and April 13, 2020 in the two EDs of an University Hospital. Those two EDs are located in north and south of our city. The EDs treated 78,000 and 40,000 visitors in 2018, respectively. During the pandemic, these EDs were re-organized to propose specific units for suspected COVID19 patients in order to segregate COVID19 activity from standard activity. Patients suspected of COVID19 were patients with dyspnea or unexplained fever. The medical dispatch center systematically addressed suspected COVID19 patients to these dedicated units.
A CT-scan was dedicated in each ED to this activity and these units were the only centers of the area to provide COVID19 testing by Reverse Transcriptase – Polymerase Chain Reaction (RT-PCR) daily. After admission in one of these units, patients underwent a chest CT-scan if the emergency practitioner estimated that they would potentially require hospitalization. Patients were tested by COVID19 RT-PCR (nasopharyngeal swab or throat swab) if the chest CT-scan could not exclude COVID19 infection. This strategy was justified by the lack of sensitivity of RT-PCR and the poor specificity of CT-scans (12).
Source of data
Standardized observations were completed for all patients admitted between March 13 and March 31 in one of the COVID19 dedicated units during the COVID19 epidemic in the two EDs of the University Hospital of Toulouse, France. These are the data used for the development and internal validation of the model (original data). Data were collected in the same way between April 1 and April 13 for the temporal validation (secondary data).
Inclusion criteria were: patients over 15 years old, admitted in ED for respiratory symptoms (dyspnea, cough) or fever (or sensation of fever) of unknown origin and potentially requiring hospitalization. We decided that the patient was considered by the physician who performed the first clinical examination, as potentially in need of complementary tests or hospitalization, if he or she performed a chest CT-scan, because this was the care protocol implemented within the COVID19 dedicated units. We excluded patients with already confirmed COVID19 infection on admission to the emergency department, as these patients are not part of the model's target population. The inclusion and exclusion criteria were the same for original and secondary data.
Candidate predictors were demographic characteristics (age, sex, autonomy), medical history (asthma, cardio-respiratory disease, obesity, cancer, treatment), disease history (duration, symptoms), and clinical examination (signs of heart failure, pulmonary auscultation, digestive signs, etc.). These variables were collected by the physicians during the first clinical examination.
The outcome was the diagnosis of COVID19 infection. Final diagnosis of COVID19 was assessed as follows (Fig. 1): in case of negative chest CT-scan, patient was considered as COVID19 negative ; in case of positive CT-scan and positive RT-PCR, patient was considered as COVID19 positive; in case of CT-scan results “not typical” of COVID19 infection and negative RT-PCR, patient was considered as COVID19 negative; in case of a very suspect COVID19 lesion of at the CT-scan and negative RT-PCR, patient was tested for other respiratory virus and was reassessed by a second expert physician (respiratory or infectious disease specialist).
During the implementation of the study, we had assumed an average prevalence of 15% of COVID19 positivity among the eligible population over the inclusion period (first phase of the virus diffusion at the regional level), about 10 candidate-predictors and a minimum R² of 0.15. We estimated the number of events (COVID19 positive patients) required at a minimum of 83 (13), i.e. a total number of subjects required of 553 patients.
Statistical analysis: development
Analysis were performed with R release 3.6.1(14) and R studio release 1.2.5001.
We performed a complete-case analysis. No imputation was performed. One important variable (“Anosmia or ageusia”) had more than 50% of missing data because it was not collected from the beginning, so we used the class “not known” in order to keep both the variable and the patients with missing data on the model.
We compared several modeling and screening approaches by cross-validation using variables associated with outcome with a p-value < 0.20 in bivariate analysis. Logistic regression with stepwise selection have been selected as better approach, based on optimization of C-statistic. We verified stability of the selected variables (“bootStepAIC” package) and stability of the coefficient estimation by bootstrap (100 and 200 replications respectively).
Statistical analysis: internal validation
The model has been developed on the entirety of original data. Performance, calibration and discrimination parameters have also been estimated on the total base (“apparent parameters”) then corrected by optimism (“corrected parameters”). The optimism has been estimated by bootstrap (15).
We especially estimated the corrected R², the corrected intercept and slope of calibration equation and the bias-corrected Somers D with the “rms” package developed by Harrell (16). We estimated the corrected AUROC (C-statistic) with the same approach. Then, apparent and corrected-by-optimism sensitivities, specificities, accuracies, error rates and predictive values were estimated for several thresholds. As we wanted to minimize the risk of infecting non-COVID19 units, the threshold was chosen with a view of limiting the number of false negatives.
Statistical analysis: temporal validation
Based on the final model developed in the original data, we estimated AUROC (C-statistic) and sensitivities, specificities, accuracies, error rates and predictive values for several thresholds on patients of the secondary data.
In order to improve our methodology, we used the TRIPOD checklist to report our methods and results
The study protocol was approved by the Ethics Committee Ouest-6 France (Brest: 1276 HPS 3) (NCT: RC31/20/0149). Patients received information on their participation at the study. No signed consent was required.