Rechtman 2020.

Study characteristics
Notes	English title Vital signs assessed in initial clinical encounters predict COVID‐19 mortality in an NYC hospital system Study setting Start of study recruitment (MM/YYYY): NR End of study recruitment (MM/YYYY): 04/2020 Study design: Retrospective cohort Study centre(s): Multiple centres/clinics/areas within a country Number of centres, clinics or areas: 53 Study setting: Outpatient and inpatient Number of participants recruited: 8770 Sampling method: Consecutive participants Participants Female participants (absolute number): 4004 Age measure, value: Median (IQR), 60 (44‐72) Inclusion criteria: all cases of confirmed SARS‐CoV‐2 positive by real time‐polymerase chain reaction (RT‐PCR) in nasopharyngeal or oropharyngeal swabs collected in outpatient, urgent care, emergency, and inpatient facilities Exclusion criteria: Patients with oxygen saturation inferior to 40% were excluded. Smoking frequency: 1853 Diabetes frequency: 1631 Hypertension frequency: 2281 Cardiovascular disease frequency: NR Asthma frequency: 394 Chronic obstructive pulmonary disease frequency: 222 Other pulmonary disease frequency: NR Immunosuppression frequency: NR Chronic kidney disease frequency: 753 Cancer frequency: 649 Steroid administration frequency: NR Supplemental oxygen administration frequency: NR Other treatments (frequency): NR Prognostic factor(s) Study’s definition for obesity: Obesity was defined based on ICD‐10 coding E66 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): 616 Prognostic factor(s): BMI (per kg/m2 increase) Outcome(s) Mortality Outcome (prognostic factor) Mortality (BMI (per kg/m2 increase)) Follow‐up Number of patients followed completely for the outcome: 8770 Number of obese patients followed completely for the outcome: 616 Number of non‐obese patients followed completely for the outcome: 8154 Univariable unadjusted analysis for obesity Effect measure for obesity: NR Effect measure value (95% CI), P value: NR Multivariable analysis for obesity Modelling method: Logistic regression The set of prognostic factors used for adjustment: Age, BMI, sex, race (black, Hispanic, other/unknown), smoking, heart rate, temperature, respiratory rate, oxygen saturation, hypertension, chronic kidney disease, diabetes, COPD, HIV, cancer, obesity, asthma Effect measure for obesity: Odds ratio Effect measure value (95% CI), P value: 1.03 (1.02, 1.04), NR
Item	Authors' judgement	Support for judgement
Study Participation	Unclear	Appendix 3
Study Attrition Mortality	Yes	Appendix 3
Prognostic Factor Measurement	Yes	Appendix 3
Outcome Measurement Mortality	Yes	Appendix 3
Confounding Bias Mortality	Yes	Appendix 3
Statistical Analysis Bias	Yes	Appendix 3