Duration of Oxygen Requirement and Predictors in Severe COVID-19 Patients in Ethiopia: A Survival Analysis
Leulseged, T. W.; Hassen, I. S.; Edo, M. G.; Abebe, D. S.; Maru, E. H.; Zewde, W. C.; Chamesew, N. W.; Jagema, T. B.
Show abstract
BackgroundWith the rising number of new cases of COVID-19, understanding the oxygen requirement of severe patients assists in identifying at risk groups and in making an informed decision on building hospitals capacity in terms of oxygen facility arrangement. Therefore, the study aimed to estimate time to getting off supplemental oxygen therapy and identify predictors among COVID-19 patients admitted to Millennium COVID-19 Care Center in Ethiopia. MethodsA prospective observational study was conducted among 244 consecutively admitted COVID-19 patients from July to September, 2020. Kaplan Meier plots, median survival times and Log-rank test were used to describe the data and compare survival distribution between groups. Cox proportional hazard survival model was used to identify determinants of time to getting off supplemental oxygen therapy, where hazard ratio (HR), P-value and 95%CI for HR were used for testing significance and interpretation of results. ResultsMedian time to getting off supplemental oxygen therapy among the studied population was 6 days (IQR, 4.3-20.0). Factors that affect time to getting off supplemental oxygen therapy were age group (AHR=0.52,95%CI=0.32,0.84, p-value=0.008 for [≥]70 years) and shortness of breath (AHR=0.71,95%CI=0.52,0.96, p-value=0.026). ConclusionsAverage duration of supplemental oxygen therapy requirement among COVID-19 patients was 6 days and being 70 years and older and having shortness of breath were found to be associated with prolonged duration of supplemental oxygen therapy requirement. This result can be used as a guide in planning institutional resource allocation and patient management to provide a well-equipped care to prevent complications and death from the disease.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Characteristics and outcome profile of Hospitalized African COVID-19 patients: The Ethiopian Context 98%
- COVID-19 Disease Severity and Determinants among Ethiopian Patients: A study of the Millennium COVID-19 Care Center 98%
- Laboratory Biomarkers of COVID-19 Disease Severity and Outcome: Findings from a Developing Country 97%
Similar papers in this journal
- Comparison of Efficacy of Dexamethasone and Methylprednisolone in Improving the Partial Pressure of Arterial Oxygen and Fraction of Inspired Oxygen Ratio among COVID-19 Patients 98%
- Comparative study between first and second wave of COVID-19 deaths in India - a single center study 97%
- Post mortem pathological findings in COVID-19 cases: A Systematic Review 95%
Similar papers in this journal
- Cardiovascular Risk Factors and Outcomes in COVID-19: Hospital-Based Prospective Study in India 96%
- Trends and determinants of Acute Respiratory Infection symptoms among Under-five children in Cambodia: Analysis of 2000 to 2014 Cambodia Demographic and Health Surveys 95%
- Burnout and sleep problems among nurses working in a tertiary hospital in Kathmandu, Nepal 95%
Similar papers in this journal
- Determinants of Developing Symptomatic Disease in Ethiopian COVID-19 Patients 98%
- Evaluation of the disease outcome in Covid-19 infected patients by disease symptoms: a retrospective cross-sectional study in Ilam Province, Iran 98%
- Prevalence of Common Respiratory Viruses in Children: Insights from Post-Pandemic Surveillance 94%
Similar papers in this journal
- Predictors of Death in Severe COVID-19 Patients at Millennium COVID-19 Care Center in Ethiopia: A Case-Control Study 99%
- COVID-19 in Hospitalized Ethiopian Children: Characteristics and Outcome Profile 96%
- Factors influencing intention to adhere to precautionary behavior in times of COVID- 19 pandemic in Sudan: an application of the Health Belief Model 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.