COVID-19 in Africa: Current difficulties and future challenges considering the ACCCOS study

ROX Index Variation as a Predictor of Outcomes in COVID-19 Patients

Background: During the COVID-19 pandemic, emergency departments were overcrowded with critically ill patients, and many providers were confronted with ethical dilemmas in assigning respiratory support to them due to scarce resources. Quick tools for evaluating patients upon admission were necessary, as many existing scores proved inaccurate in predicting outcomes. The ROX Index (RI), a rapid and straightforward scoring system reflecting respiratory status in acute respiratory failure patients, has shown promise in predicting outcomes for COVID-19 patients. The 24 h difference in the RI accurately gauges mortality and the need for invasive mechanical ventilation (IMV) among patients with COVID-19. Methods: Study design: Prospective cohort study. A total of 204 patients were admitted to the emergency department from May to August 2020. Data were collected from the clinical records. The RI was calculated at admission and 24 h later, and the difference was used to predict the association with mortality and the need for IMV, a logistic regression model was used to adjust for age, sex, presence of comorbidities, and disease severity. Finally, the data were analyzed using ROC. Results: The difference in respiratory RI between admission and 24 h is a good predictor for death (AUC 0.92) and for mechanic ventilation (AUC: 0.75). Each one-unit decrease in the RI difference at 24 h was associated with an odds ratio of 1.48 for the risk of death (95%CI: 1.31-1.67) and an odds ratio of 1.16 for IMV (95% IC: 1.1-1.23). Conclusions: The 24 h variation of RI is a good prediction tool to allow healthcare professionals to identify the patients who will benefit from invasive treatment, especially in low-resource settings.

The novel use of diaphragmatic excursion on hospital admission to predict the need for ventilatory support in patients with coronavirus disease 2019

Background

We aimed to evaluate the ability of diaphragmatic excursion at hospital admission to predict outcomes in patients with coronavirus disease-2019 (COVID-19).

Methods

In this prospective observational study, we included adult patients with severe COVID-19 admitted to a tertiary hospital. Ultrasound examination of the diaphragm was performed within 12 h of admission. Other collected data included peripheral oxygen saturation (SpO₂), respiratory rate, and computed tomography (CT) score. The outcomes included the ability of diaphragmatic excursion, respiratory rate, SpO₂, and CT score at admission to predict the need for ventilatory support (need for non-invasive or invasive ventilation) and patient mortality using the area under the receiver operating characteristic curve (AUC) analysis. Univariate and multivariable analyses about the need for ventilatory support and mortality were performed.

Results

Diaphragmatic excursion showed an excellent ability to predict the need for ventilatory support, which was the highest among respiratory rate, SpO₂, and CT score; the AUCs (95% confidence interval [CI]) was 0.96 (0.85–1.00) for the right diaphragmatic excursion and 0.94 (0.82–0.99) for the left diaphragmatic excursion. The right diaphragmatic excursion also had the highest AUC for predicting mortality in relation to respiratory rate, SpO₂, and CT score. Multivariable analysis revealed that low diaphragmatic excursion was an independent predictor of mortality with an odds ratio (95% CI) of 0.55 (0.31–0.98).

Conclusion

Diaphragmatic excursion on hospital admission can accurately predict the need for ventilatory support and mortality in patients with severe COVID-19. Low diaphragmatic excursion was an independent risk factor for in-hospital mortality.

Admission SpO2 and ROX index predict outcome in patients with COVID-19

Background

This study aimed to evaluate the accuracy of pulse oximetry-derived oxygen saturation (SpO₂) on room air, determined at hospital admission, as a predictor for the need for mechanical ventilatory support in patients with Coronavirus Disease-2019 (COVID-19).

Methods

In this retrospective observational study, demographic and clinical details of the patients were obtained during ICU admission. SpO₂ and respiratory rate (RR) on room air were determined within the first 6 h of hospital admission. As all measurements were obtained on room air, we calculated the simplified respiratory rate‑oxygenation (ROX) index by dividing the SpO₂ by the RR. Based on the use of any assistance of mechanical ventilator (invasive or noninvasive), patients were divided into mechanical ventilation (MV) group and oxygen therapy group. The accuracy of the SpO₂, CT score, and ROX index to predict the need to MV were determined using the Area under receiver operating curve (AUC).

Results

We included 72 critically ill patients who tested COVID-19-positive. SpO₂ on the room air could predict any MV requirement (AUC [95% confidence interval]: 0.9 [0.8–0.96], sensitivity: 70%, specificity 100%, cut-off value ≤78%, P < 0.001). Within the MV group, the use of noninvasive ventilation (NIV) was successful in 37 (74%) patients, whereas 13 patients (26%) required endotracheal intubation. The cut-off ROX value for predicting early NIV failure was ≤1.4, with a sensitivity of 85%, a specificity of 86%, and an AUC of 0.86 (95% confidence interval of 0.73–0.94, P < 0.0001).

Conclusions

A baseline SpO₂ ≤78% is an excellent predictor of MV requirement with a positive predictive value of 100%. Moreover, the ROX index measured within the first 6 h of hospital admission is a good indicator of early NIV failure.