ABSTRACT
BACKGROUND: COVID-19 patients developing the acute respiratory distress syndrome (ARDS) show increased production of pro-inflammatory cytokines, including interleukin-6 (IL-6). The use of humanized monoclonal antibody against interleukin-6 receptor (IL-6R) may represent a potential treatment strategy. We analyzed the effects of compassionate use of tocilizumab and sarilumab on clinical outcome of patients affected by ARDS due COVID-19. METHODS: This single-center, observational, exploratory study was performed during the acute phase of COVID-19 outbreak, between March 7th and April 21st, 2020 in a University Hospital in Rome, Italy. All consecutive adult patients admitted to the intensive care unit with laboratory-confirmed COVID-19 and fulfilling ARDS criteria were enrolled. Patients who were treated with anti-IL-6R therapy were compared to those who were not, as per clinical decision. Inverse probability weights were applied to weight individual's contribution to survival curves and in the multivariate regression model. RESULTS: Among 105 ARDS patients, 65 received compassionate treatment with anti-IL-6R therapy (43 [66%] Tocilizumab [Hoffmann-La Roche, Basel, Switzerland] and 22 [34%] Sarilumab, respectively], with oxygenation improvement. In the multivariable Cox proportional regression hazards model with propensity score inverse probability weighting, patients who received anti-IL-6R treatment had lower risk of death compared to those who did not, with a hazard ration of 0.34 [95% confidence interval 0.17-0.74], P=0.001. CONCLUSIONS: Our data suggested that immune modulator therapy based on anti-human IL-6 receptor monoclonal antibodies might lead to improved outcome in patients with ARDS due to COVID-19. These data support the need for confirmatory randomized trials to assess the effect of immune modulator therapies on mortality.
Subject(s)
COVID-19 , Respiratory Distress Syndrome , Adult , Compassionate Use Trials , Critical Illness , Humans , Respiratory Distress Syndrome/drug therapy , SARS-CoV-2ABSTRACT
OBJECTIVES: We aimed to develop and validate a risk score to predict severe respiratory failure (SRF) among patients hospitalized with coronavirus disease-2019 (COVID-19). METHODS: We performed a multicentre cohort study among hospitalized (>24 hours) patients diagnosed with COVID-19 from 22 February to 3 April 2020, at 11 Italian hospitals. Patients were divided into derivation and validation cohorts according to random sorting of hospitals. SRF was assessed from admission to hospital discharge and was defined as: Spo2 <93% with 100% Fio2, respiratory rate >30 breaths/min or respiratory distress. Multivariable logistic regression models were built to identify predictors of SRF, ß-coefficients were used to develop a risk score. Trial Registration NCT04316949. RESULTS: We analysed 1113 patients (644 derivation, 469 validation cohort). Mean (±SD) age was 65.7 (±15) years, 704 (63.3%) were male. SRF occurred in 189/644 (29%) and 187/469 (40%) patients in the derivation and validation cohorts, respectively. At multivariate analysis, risk factors for SRF in the derivation cohort assessed at hospitalization were age ≥70 years (OR 2.74; 95% CI 1.66-4.50), obesity (OR 4.62; 95% CI 2.78-7.70), body temperature ≥38°C (OR 1.73; 95% CI 1.30-2.29), respiratory rate ≥22 breaths/min (OR 3.75; 95% CI 2.01-7.01), lymphocytes ≤900 cells/mm3 (OR 2.69; 95% CI 1.60-4.51), creatinine ≥1 mg/dL (OR 2.38; 95% CI 1.59-3.56), C-reactive protein ≥10 mg/dL (OR 5.91; 95% CI 4.88-7.17) and lactate dehydrogenase ≥350 IU/L (OR 2.39; 95% CI 1.11-5.11). Assigning points to each variable, an individual risk score (PREDI-CO score) was obtained. Area under the receiver-operator curve was 0.89 (0.86-0.92). At a score of >3, sensitivity, specificity, and positive and negative predictive values were 71.6% (65%-79%), 89.1% (86%-92%), 74% (67%-80%) and 89% (85%-91%), respectively. PREDI-CO score showed similar prognostic ability in the validation cohort: area under the receiver-operator curve 0.85 (0.81-0.88). At a score of >3, sensitivity, specificity, and positive and negative predictive values were 80% (73%-85%), 76% (70%-81%), 69% (60%-74%) and 85% (80%-89%), respectively. CONCLUSION: PREDI-CO score can be useful to allocate resources and prioritize treatments during the COVID-19 pandemic.