Evaluation of the Risk of Clinical Deterioration among Inpatients with COVID-19.
Víctor de Oliveira CostaEveline M NicoliniBruna Malaquias Arguelles da CostaFabrício M TeixeiraJúlia P FerreiraMarcos A MouraJorge MontessiRogério L CamposAndrea N GuaraldoPatrícia M CostaPublished in: Advances in virology (2021)
This study aims to assess the risk of severe forms of COVID-19, based on clinical, laboratory, and imaging markers in patients initially admitted to the ward. This is a retrospective observational study, with data from electronic medical records of inpatients, with laboratory confirmation of COVID-19, between March and September 2020, in a hospital from Juiz de Fora-MG, Brazil. Participants (n = 74) were separated into two groups by clinical evolution: those who remained in the ward and those who progressed to the ICU. Mann-Whitney U test was taken for continuous variables and the chi-square test or Fisher's exact test for categorical variables. Comparing the proposed groups, lower values of lymphocytes (p = <0.001) and increases in serum creatinine (p = 0.009), LDH (p = 0.057), troponin (p = 0.018), IL-6 (p = 0.053), complement C4 (p = 0.040), and CRP (p = 0.053) showed significant differences or statistical tendency for clinical deterioration. The average age of the groups was 47.9 ± 16.5 and 66.5 ± 7.3 years (p = 0.001). Hypertension (p = 0.064), heart disease (p = 0.048), and COPD (p = 0.039) were more linked to ICU admission, as well as the presence of tachypnea on admission (p = 0.051). Ground-glass involvement >25% of the lung parenchyma or pleural effusion on chest CT showed association with evolution to ICU (p = 0.027), as well as bilateral opacifications (p = 0.030) when compared to unilateral ones. Laboratory, clinical, and imaging markers may have significant relation with worse outcomes and the need for intensive treatment, being helpful as predictive factors.
Keyphrases
- coronavirus disease
- sars cov
- intensive care unit
- blood pressure
- computed tomography
- magnetic resonance imaging
- healthcare
- end stage renal disease
- chronic kidney disease
- newly diagnosed
- chronic obstructive pulmonary disease
- machine learning
- mechanical ventilation
- ejection fraction
- early onset
- type diabetes
- magnetic resonance
- metabolic syndrome
- mass spectrometry
- artificial intelligence
- prognostic factors
- insulin resistance
- deep learning
- patient reported outcomes
- pulmonary hypertension
- acute care
- pet ct
- case report