OBJECTIVE: To describe mortality of in-hospital patients with COVID-19 and compare risk factors between survivors and non-survivors. DESIGN: Prospective cohort of adult inpatients. SETTING: Tertiary healthcare teaching hospital in Guadalajara, Mexico. PARTICIPANTS: All patients with confirmed COVID-19 hospitalised from 25 March to 7 September 2020 were included. End of study: 7 November 2020. PRIMARY OUTCOME MEASURES: Patient survival analysed by the Kaplan-Meier method and comparison of factors by the log-rank test. Mortality risk factors analysed by multivariate Cox's proportional-hazard model. RESULTS: One thousand ten patients included: 386 (38%) died, 618 (61%) alive at discharge and six (0.6%) remained hospitalised. There was predominance of men (63%) and high frequency of overweight-obesity (71%); hypertension (54%); diabetes (40%); and lung (9%), cardiovascular (8%) and kidney diseases (11%); all of them significantly more frequent in non-survivors. Overweight-obesity was not different between groups, but severity of disease (Manchester Triage System and quick Sequential Organ Failure Assessment) was significantly worse in non-survivors, who were also significantly older (65 vs 45 years, respectively) and had haematological, biochemical, coagulation and inflammatory biomarkers more altered than survivors. Mortality predictors were invasive mechanical ventilation (IMV; OR 3.31, p<0.0001), admission to intensive care unit (ICU; OR 2.18, p<0.0001), age (OR 1.02, p<0.0001), Manchester Triage System (urgent OR 1.44, p=0.02; immediate/very urgent OR 2.02, p=0.004), baseline C reactive protein (CRP; OR 1.002, p=0.009) and antecedent of kidney disease (OR 1.58, p=0.04) CONCLUSIONS: Mortality in hospitalised patients with COVID-19 in this emerging country centre seemed to be higher than in developed countries. Patients displayed a high frequency of risk factors for poor outcome, but the need for IMV, ICU admission, older age, more severe disease at admission, antecedent of kidney disease and higher CRP levels significantly predicted mortality.