Huang 2020.

Study characteristics
Notes	English title Clinical findings of patients with coronavirus disease 2019 in Jiangsu province, China: a retrospective, multicentre study Study setting Start of study recruitment (MM/YYYY): 01/2020 End of study recruitment (MM/YYYY): 02/2020 Study design: Retrospective cohort Study centre(s): Multiple centres/clinics/areas within a country Number of centres, clinics or areas: 8 Study setting: Inpatient Number of participants recruited: 202 Sampling method: NR Participants Female participants (absolute number): 86 Age measure, value: Median (IQR), 44 (33‐54) Inclusion criteria: COVID‐19 patients from 8 designated hospitals in 8 cities of Jiangsu province, China Exclusion criteria: NR Smoking frequency: 16 Diabetes frequency: 19 Hypertension frequency: 29 Cardiovascular disease frequency: 5 Asthma frequency: NR Chronic obstructive pulmonary disease frequency: NR Other pulmonary disease frequency: 7 Immunosuppression frequency: NR Chronic kidney disease frequency: NR Cancer frequency: 2 Steroid administration frequency: 64 Supplemental oxygen administration frequency: 109 Other treatments (frequency): Antiviral therapy (196), atomised inhalation of interferon α‐2b (121), lopinavir/ritonavir (180), Arbidol (59), oseltamivir (32), antibiotic therapy (149), use of gamma globulin (31) Prognostic factor(s) Study’s definition for obesity: BMI > 28 kg/m2 The time when obesity has been measured: NR Main variable used for determination of obesity: BMI Threshold used for definition: 28 Obesity frequency (absolute number): 24 Prognostic factor(s): BMI > 28 kg/m2 Outcome(s) Severe COVID‐19 Outcome (prognostic factor) Severe COVID‐19 (BMI > 28 kg/m2) Follow‐up Number of patients followed completely for the outcome: 202 Number of obese patients followed completely for the outcome: 24 Number of non‐obese patients followed completely for the outcome: 148 Univariable unadjusted analysis for obesity Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 6.9 (2.381, 19.997), < 0.001 Multivariable analysis for obesity Modelling method: Logistic regression The set of prognostic factors used for adjustment: Age, gender, BMI, hypertension, DM, smoking, WBC, neutrophils, lymphocyte, Hb, PLT, ALT, LDH, Tbil, ALB, CR, CRP, PT Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 9219 (2.731, 31.126), < 0.001
Item	Authors' judgement	Support for judgement
Study Participation	Unclear	Appendix 3
Study Attrition Severe COVID	Yes	Appendix 3
Prognostic Factor Measurement	Yes	Appendix 3
Outcome Measurement Severe COVID	No	Appendix 3
Confounding Bias Severe COVID	Yes	Appendix 3
Statistical Analysis Bias	Unclear	Appendix 3