Favipiravir In Adults with Moderate to Severe COVID-19: A Phase 3 Multicentre, Randomized, Double-Blind, Placebo-Controlled Trial.

AimTo assess the efficacy and safety of favipiravir in adults with moderate to severe coronavirus disease 2019 (COVID-19). MethodsIn this randomized, double-blind, multicenter, phase 3 trial, adults (21-80 years) with real-time reverse transcriptase polymerase chain reaction (rRT-PCR) confirmed SARS-CoV-2 infection and presenting with moderate to severe COVID-19 and requiring hospitalization were randomized 1:1 to oral favipiravir (day 1: 1800 mg BID and days 2-10: 800 mg BID) (FPV) plus standard supportive care (SoC) versus placebo plus SoC (placebo). The primary endpoint was time to resolution of hypoxia. ResultsIn total, 353 patients were randomized to receive either FPV or placebo (175 and 178 in the FPV and placebo groups, respectively). Overall, 76% of the patients (240/315, 78% in FPV vs. 75% in placebo group) reached resolution of hypoxia on or before day 28. The median time to resolution of hypoxia was 7 days in the FPV group and 8 days in the placebo group. Treatment effect was not significant [Hazard ratio (HR) (95% CI): 0.991 (0.767, 1.280) (p=0.94)]. Patients in the lower NEWS-2 clinical risk subgroup were more likely to achieve shorter time to resolution of hypoxia with the median time to resolution of hypoxia of 6 days in FPV and 7 days in placebo group [HR (95% CI): 1.21 (0.847, 1.731) (p=0.29)]; shorter time to hospital discharge with a median time to discharge of 8 and 10 days in the FPV and placebo group, respectively [HR (95% CI): 1.47 (1.081, 1.997) (p=0.014)]; and shorter time to improvement by 1-point improvement over baseline in WHO 10-point clinical status score with the median time to improvement by 1-point from baseline of 6 and 7 days in the FPV and placebo group, respectively [HR (95% CI): 1.16 (0.830, 1.624) (p=0.38)] than higher NEWS-2 clinical risk subgroup. Treatment emergent adverse event (TEAEs) were experienced by 62/334 (19%) patients [35/168 (21%) patients in FPV and 27/166 (16%) in placebo group]. Hyperuricaemia/increased blood uric acid was reported in 9 (3%)/2 (1%) patients [8 (5%)/1(1%) patients in FPV and 1 (1%)/1(1%) in placebo group], which were of mild intensity and transient. Overall, 36 serious adverse events (SAEs) were reported, 20 in FPV and 16 in placebo group. ConclusionThe trial did not find favipiravir to be effective in moderate to severe, hospitalized COVID-19 patients; favourable clinical trends were observed in patients with lower NEWS-2 risk when early administration of favipiravir could be achieved.

COVID-19: Impact of Obesity and Diabetes in Disease Severity

BackgroundThe Coronavirus disease 2019 (COVID-19) pandemic is straining the healthcare system, particularly for patients with severe outcomes who require admittance to the intensive care unit (ICU). This study aimed to investigate the potential associations of obesity and diabetes with COVID-19 severe outcomes, assessed as ICU admittance. SubjectsDemographic and patient characteristics from a retrospective cohort of 1158 patients hospitalized with COVID-19 in a single center in Kuwait, along with their medical history, were analyzed. Univariate and multivariate analyses were performed to explore the associations between different variables and ICU admittance. ResultsFrom the 1158 hospitalized patients, 271 (23.4%) had diabetes, 236 (20.4%) had hypertension and 104 (9%) required admittance into the ICU. From patients with available measurements, 157 (21.6%) had body mass index (BMI)[≥]25 kg/m2. Univariate analysis showed that overweight (BMI=25.0-29.9 kg/m2), obesity class I (BMI=30-34.9 kg/m2) and morbid obesity (BMI[≥]40 kg/m2) associated with ICU admittance (odds ratio (OR) [95% confidence intervals (CI)]: 2.45 [1.26-4.74] p-value=0.008; OR [95% CI]: 3.51 [1.60-7.69] p-value=0.002; and OR [95% CI]: 5.18 [1.50-17.85] p-value=0.009], respectively). Patients with diabetes were more likely to be admitted to ICU (OR [95% CI]: 9.38 [5.49-16.02]). Two models for multivariate regression analysis were used, assessing either BMI or diabetes on ICU outcomes. In the BMI model, class I obesity and morbid obesity were associated with ICU admittance (adjusted OR (AOR) [95% CI]: 2.7 [1.17-6.20] p-value=0.019 and AOR [95% CI]: 3.95 [1.00-15.20] p-value=0.046, respectively). In the diabetes model, diabetes was associated with higher ICU admittance (AOR [95% CI]: 5.49 [3.13-9.65] p-value<0.001) whereas hypertension had a protective effect on ICU admittance (AOR [95% CI]: 0.51 (0.28-0.91). ConclusionsIn our cohort, overweight, obesity and diabetes in patients with COVID-19 were associated with ICU admittance, putting these patients at higher risk of poor outcomes.

Validation of the Kuwait Progression Indicator Score for predicting progression of severity in COVID19

IntroductionIdentifying patients with COVID-19, at risk of having a severe clinical course during their hospitalization is important for appropriate allocation of clinical resources. We recently described the Kuwait Progression Indicator based on laboratory findings, in an initial training cohort derived from the first series of 1096 consecutive patients admitted to Jaber Al-Ahmad Al-Sabah Hospital in Kuwait. The aim of this study was to validate the KPI scoring system in an independent cohort of patients with COVID-19. MethodologyData was collected prospectively for consecutive patients admitted to Jaber Al-Ahmad Al-Sabah Hospital in Kuwait between 24th February - 28th April 2020. Patients were grouped according to the severity of their clinical course as their main outcome, based on clinical and radiological parameters, with ICU admission and death as secondary outcomes. Model discrimination was assessed through the area under the receiver operating characteristic curve (AUC) while model calibration was assessed through a calibration plot and measures of slope and calibration in the large (CITL). ResultsOf 752 patients not used in model development previously, 414 met the criteria for inclusion in this validation study. The baseline characteristics for these 752 patients were similar to the patients that were included in our validation cohort. The area under the curve was equal to 0.904 (95% CI, 0.867-0.942), indicating good model discrimination. The calibration plot and CITL confirmed reasonably good model calibration. Sensitivity and specificity were above 90% for the low and high risk levels respectively. ConclusionsWe were able to validate our previously described laboratory based prognostic scoring system for COVID-19 patients, to predict which patients progressed to a severe clinical course.

Clinical Characteristics, Risk Factors and Outcomes Among the First Consecutive 1,096 Patients Diagnosed with COVID-19: The Kuwait Experience

BackgroundIn Kuwait, prior to the first case of COVID-19 being reported in the country, mass screening of incoming travelers from countries with known outbreaks was performed and resulted in the first identified cases in the country. All COVID-19 cases at the time and subsequently after, were transferred to a single center, Jaber Al-Ahmad Al-Sabah Hospital, where the patients received standardized investigations and treatments. The objective of this study was to characterize the demographics, clinical manifestations and outcomes in this unique patient population. MethodsThis retrospective cohort study was conducted between 24th February 2020 and 20th April 2020. All consecutive patients in the entire State of Kuwait diagnosed with COVID-19 according to WHO guidelines and admitted to Jaber Al-Ahmad Al-Sabah Hospital were recruited. Patients received standardized investigations and treatments. Multivariable analysis was used to determine the associations between risk factors and outcomes. FindingsOf 1096 patients, the median age was 41 years and 81% of patients were male. Most patients were asymptomatic on admission (49.5%), 69.4% had no signs of infection and 94.6% were afebrile. Only 3.6% of patients required an ICU admission and 1.7% were dead at the studys cutoff date. On multivariate analysis, the risk factors found to be significantly associated with admission to intensive care were age above 50 years old, a qSOFA score above 0, smoking, elevated CRP and elevated procalcitonin levels. Asthma, smoking and elevated procalcitonin levels correlated significantly with mortality in our cohort.To our knowledge, this is the first large retrospective cohort study observing the characteristics of the initial consecutive COVID-19 patients of an entire country. Further, large proportion of asymptomatic patients provides novel insights into the clinical features of patients with milder disease. FundingResearch Grant Awarded by the Kuwait Foundation for the Advancement of Science.

Predicting Disease Progression in COVID19: A Score Based On Lab Tests At Time Of Diagnosis

BackgroundCOVID19 is worldwide pandemic that is mild in the majority of patients but can result in a pneumonia like illness with progression to acute respiratory distress syndrome and death. Predicting the disease severity at time of diagnosis can be helpful in prioritizing hospital admission and resources. MethodsWe prospectively recruited 1096 consecutive patients with COVID19 from the Jaber Hospital, a COVID19 facility in Kuwait, between 24 February and 20 April 2020. The primary endpoint of interest was disease severity defined algorithmically. Predefined risk variables were collected at the time of PCR based diagnosis of the infection. Prognostic model development used 5-fold cross-validated regularized logit regression. The cohort was divided into a training and validation cohort and all model development proceeded on the training cohort. ResultsThere were 643 patients with clinical course data of whom 94 developed severe COVID19. In the final model, age, CRP, procalcitonin, lymphocyte and monocyte percentages and serum albumin were independent predictors of a more severe illness course. The final prognostic model demonstrated good discrimination, calibration and internal validity. ConclusionWe developed and validated a simple score calculated at time of diagnosis that can predict patients with severe COVID19 disease.