. 2023 May 24;2023(5):CD015201. doi: 10.1002/14651858.CD015201

IMIDIATE 2020.

*Study characteristics*
Notes	English title Severity of COVID‐19 and survival in patients with rheumatic and inflammatory diseases: data from the French RMD COVID‐19 cohort of 694 patients Study setting Start of study recruitment (MM/YYYY): 02/2020 End of study recruitment (MM/YYYY): 04/2020 Study design: Prospective cohort Study centre(s): Multiple centres/clinics/areas within a country Number of centres, clinics or areas: NR Study setting: Outpatient and inpatient Number of participants recruited: 694 Sampling method: NR Participants Female participants (absolute number): 462 Age measure, value: Mean (SD), 56.1 (16.4) Inclusion criteria: Patients of all ages with confirmed iRMD (rheumatic and inflammatory diseases) and highly suspected/confirmed diagnosis of COVID‐19 Exclusion criteria: NR Smoking frequency: NR Diabetes frequency: 62 Hypertension frequency: 182 Cardiovascular disease frequency: 85 Asthma frequency: 52 Chronic obstructive pulmonary disease frequency: 28 Other pulmonary disease frequency: interstitial lung disease (26) Immunosuppression frequency: NR Chronic kidney disease frequency: 42 Cancer frequency: 33 Steroid administration frequency: 215 Supplemental oxygen administration frequency: NR Other treatments (frequency): hydroxychloroquine (40), azithromycin (26), lopinavir/ritonavir (21), darunavir/ritonavir (10), remdesivir (2), tocilizumab (3), anakinra (1), HCQ + AZI (24), HCQ + AZI + anakinra (1) Prognostic factor(s) Study’s definition for obesity: BMI > 30 The time when obesity has been measured: Before disease or right at presentation Main variable used for determination of obesity: BMI Threshold used for definition: 30 Obesity frequency (absolute number): 146 Prognostic factor(s): BMI 30‐39.9 BMI ≥ 40 Outcome(s) Severe COVID Mortality Outcome (prognostic factor) Severe COVID (BMI 30‐39.9) Follow‐up Number of patients followed completely for the outcome: 694 Number of obese patients followed completely for the outcome: 126 Number of non‐obese patients followed completely for the outcome: 459 Univariable unadjusted analysis for obesity Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 1.25 (2.25, 0.69), 0.46 Multivariable analysis for obesity Modelling method: Logistic regression The set of prognostic factors used for adjustment: Age, sex Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 1.47 (0.76, 2.82), 0.25 Outcome (prognostic factor) Severe COVID (BMI ≥ 40) Follow‐up Number of patients followed completely for the outcome: 694 Number of obese patients followed completely for the outcome: 20 Number of non‐obese patients followed completely for the outcome: 459 Univariable unadjusted analysis for obesity Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 3.43 (1.26, 9.32), 0.016 Multivariable analysis for obesity Modelling method: Logistic regression The set of prognostic factors used for adjustment: Age, sex Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 4.10 (1.28, 13.11), 0.017 Outcome (prognostic factor) Mortality (BMI 30‐39.9) Follow‐up Number of patients followed completely for the outcome: 675 Number of obese patients followed completely for the outcome: 121 Number of non‐obese patients followed completely for the outcome: 452 Univariable unadjusted analysis for obesity Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 1.56 (0.78, 2.97), 0.19 Multivariable analysis for obesity Modelling method: Logistic regression The set of prognostic factors used for adjustment: Age, sex Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 1.95 (0.88, 4.18), 0.093 Outcome (prognostic factor) Mortality (BMI ≥ 40) Follow‐up Number of patients followed completely for the outcome: 675 Number of obese patients followed completely for the outcome: 19 Number of non‐obese patients followed completely for the outcome: 452 Univariable unadjusted analysis for obesity Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 3.64 (1.07, 10.29), 0.026 Multivariable analysis for obesity Modelling method: Logistic regression The set of prognostic factors used for adjustment: Age, sex Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 3.77 (0.86, 15.09), 0.07

Item	Authors' judgement	Support for judgement
Study Participation	Yes	Appendix 3
Study Attrition Mortality	Unclear	Appendix 3
Study Attrition Severe COVID	Unclear	Appendix 3
Prognostic Factor Measurement	Yes	Appendix 3
Outcome Measurement Mortality	Yes	Appendix 3
Outcome Measurement Severe COVID	Unclear	Appendix 3
Confounding Bias Mortality	Yes	Appendix 3
Confounding Bias Severe COVID	Yes	Appendix 3
Statistical Analysis Bias	Yes	Appendix 3