PREDICTORS OF POST-COVID SYNDROME AMONG ADULT PATIENTS WITH COVID -19 INFECTION IN IBADAN, NIGERIA
Keywords:
Post COVID 19 syndromes, Clinical spectrum, Quality of life, Ibadan, NigeriaAbstract
Background: While most individuals recover from acute Coronavirus disease (COVID-19), a subset experiences persistent symptoms, referred to as post-COVID-19 Syndrome (PCS). Understanding the clinical spectrum and determinants of PCS is essential to provide evidence-based long-term care for COVID-19 survivors. This study aimed to describe the clinical spectrum and predictors of PCS among hospitalized and non-hospitalized COVID-19 patients in Ibadan, Nigeria.
Methods: A retrospective cross-sectional study involved 536 adult individuals who tested positive for SARS-CoV-2 via polymerase chain reaction (PCR) in Ibadan, Nigeria. Data, including demographics, symptoms, comorbidities, and quality of life, were collected using a semistructured questionnaire and analyzed with descriptive statistics. Pearson's Chi-square and logistic regression were used to assess associations and predictors of PCS.
Results: Among the 536 participants, 98 (18.3%) had PCS. Of these, 67 (68.4%) reported mild symptoms, while 31 (31.6%) experienced severe symptoms. Common symptoms included fatigue/malaise (36.7%), headache (19.4%), cough (17.3%), and sore throat (13.3%). Comorbidities, initial COVID-19 severity, vaccination status pre-infection, treatment location, oxygen supplementation, and ICU care were associated with PCS. Logistic regression revealed that having received a pre-COVID-19 vaccination decreased the odds of PCS by 62.4% (aOR=0.376; 95% CI [0.205, 0.692]). Individuals that experienced PCS had lower quality of life scores (Mean EQ VAS score: 85.8) compared to those without PCS (89.7), with impacts across mobility, self-care, daily activities, pain/discomfort, and anxiety/depression domains in EQ-5D analysis.
Conclusion: PCS affects a significant proportion of COVID-19 survivors in Ibadan, Nigeria. Pre-COVID-19 vaccination was associated with a reduced risk of PCS. Understanding the clinical and demographic factors predicting PCS can aid in providing long-term care and support for affected individuals.
