Clinical and treatment factors associated with the mortality of COVID-19 patients admitted to a referral hospital in Indonesia

Abstract

Background: Indonesia had the second-highest number of COVID-19 cases and deaths in South-East Asia. We aimed to determine the factors associated with this mortality and the effect of the recommended COVID-19 treatment regimen during the first 10 months of the epidemic.

Methods: This was a retrospective cohort study using secondary data from medical records. In total, 689 adult COVID-19 inpatients hospitalized between March and December 2020 were enrolled. Clinical characteristics, laboratory parameters, and treatments were analyzed by survival outcome. Kaplan-Meier statistics were used to estimate survival.

Findings: Of the 689 patients enrolled, 103 (14.9%) died. Disease severity was highly associated with mortality (hazard ratio [HR]: 7.69, p < 0.001). Other clinical factors associated with mortality were older age and comorbidities. Based on laboratory parameters, higher procalcitonin and C-reactive protein contents and a neutrophil-to-lymphocyte ratio >3.53 were also linked to mortality. Favipiravir was associated with lower mortality, with adjusted HRs of 0.24 (0.11-0.54) and 0.40 (0.17-0.98) among the mild/moderate and severe cases, respectively. Among patients with severe disease, steroids showed some beneficial effects in the early days of hospitalization.

Interpretation: Older age and comorbidities were associated with disease severity and, consequently, higher mortality. Higher mortality after the second week of hospitalization may be related to secondary bacterial infection. Favipiravir showed significant benefit for COVID-19 survival, while steroids showed benefit only in the early days of admission among patients with severe disease.

Funding: This research did not receive a specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Keywords: Antiviral; Cohort; Comorbidity; SARS-Cov-2; Severity; Survival.

Fig. 1

Flow diagram of data and patient outcomes.

Fig. 2

a) Proportion of deaths during different periods of management. b) Proportion of mortality by age group. c) Proportion of deaths among patients with and without comorbidity.

Fig. 3

a) Disease severity as risk factor for mortality. HR = hazard ratio. b) Age as risk factor for mortality. HR = hazard ratio.

Fig. 4

Comorbidities as risk factors for mortality. Kaplan-Meier curve of mortality related to a) hypertension b) diabetes mellitus (DM), c) coronary heart disease (CHD) and d) chronic kidney disease (CKD). HR = hazard ratio.

Fig. 5

Relationship between treatment provided and patient survival. Kaplan-Meier curve shows the survival difference of the mild/moderate patients receiving a) steroid, c) favipiravir, e) remdesivir and g) antibiotics. Similar comparison shows the survival difference of the severe patients receiving b) steroid, d) favipiravir, f) remdesivir and h) antibiotics and i) ventilator. HR = hazard ratio.

Fig. 5

Relationship between treatment provided and patient survival. Kaplan-Meier curve shows the survival difference of the mild/moderate patients receiving a) steroid, c) favipiravir, e) remdesivir and g) antibiotics. Similar comparison shows the survival difference of the severe patients receiving b) steroid, d) favipiravir, f) remdesivir and h) antibiotics and i) ventilator. HR = hazard ratio.