| Autor: |
Muslim Dhahr Musa, Abbas Dhkeel Mutar, Dheyaa Khalf Al-Omar, Amani Mahmoud Mansour Almanasra |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
National Board of Examinations Journal of Medical Sciences, Vol Volume 2, Iss 2, Pp 112-128 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2583-7524 |
| Popis: |
Background: The early prediction of the clinical course of COVID-19 helps health professionals to discriminate the severe cases that need ICU admission from those with no risk of worsening outcomes. Materials & methods: This cohort retrospective study included 389 COVID-19 patients admitted to Al-Hussein Teaching Hospital during the period from March to August 2021. Demographic characteristics, clinical symptoms, and laboratory findings upon hospital admission were analyzed by univariate analysis to determine their association with the severity of COVID-19; only those variables with (P>0.05 ) were included in the multivariable logistic regression to find the strong predictors of severity in term of Odd ratios. Results: The mean age of the 389 patients was 33.6 +- 14.8; there were 231(59.4%) severe cases (admitted to ICU), and 158(40.6%) were non-severe cases (admitted to regular wards). Univariate analysis revealed that gender (male) presence of co-morbidities and all clinical symptoms and laboratory findings were associated with severe outcomes of COVID-19. However, multivariate logistic regression revealed that dyspnea [O.R 42.58 (12.22; 148.36)] and high grad fever [O.R 29.25 (5.34; 160.24)] were very strong predictors for severity, while male gender [O.R4.26 (1.95; 9.33)] and hypertension [O.R6.83 (2.4; 19.54)] were strong predictors of the severity. On the other hand, Ferritin gave an indiscernible predictive value [O.R1.003 (1.001; 1.006)]. Conclusion: Some risk factors are very helpful for clinicians to discriminate against patients who may develop severe outcomes and need ICU admission, which might help the efficient use of health resources in sensitive times. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
