Adult Coronavirus Disease 2019 Patients Research Articles

Clinical Profile and Predictors of Mortality in Patients admitted with COVID-19 in a Tertiary Care Hospital

Hospitalization and survival rate in patients with coronavirus disease 2019 (COVID-19) is affected by pre-existing chronic medical conditions and the disease severity. The objectives of the study were to describe the baseline clinical profile, co-morbidities, disease severity and to assess the predictors of mortality in hospitalized adult patients with COVID-19 in a tertiary care hospital in Nepal. A cross-sectional study was conducted for two months on 168 adult COVID-19 patients admitted to Nobel Medical College Teaching Hospital Biratnagar. Demographics, comorbidities, disease severity, oxygen requirement, and treatment outcomes were studied. The mean age of the patients was 57.1 years and 56.5% were male. Out of 168, 16.7% and 10.1% of the participants had currently or in the past used alcohol or tobacco products respectively. Hypertension (28.6%) and chronic lung disease (16.1%) were the most common co-morbidities. The overall case-fatality rate was 17.9%, with 32.1% and 56.3% in the severe and critical COVID-19 subgroup respectively. The mortality rate for patients without co-morbidities was 2.4% which increased to 63.6% for those with three or more co-morbidities. Age, disease severity, and the number of co-morbidities were found to be associated with increased mortality (P<0.05), whereas gender was not. The pre-existing chronic diseases and increased severity of the disease were associated with increased mortality in hospitalized COVID-19 adult patients.

Comparison of four different threshold values of shock index in predicting mortality of COVID-19 patients.

The object of this study was to examine the accuracy in pre-hospital shock index (SI) for predicting intensive care unit (ICU) requirement and 30-day mortality among from COVID-19 patients transported to the hospital by ambulance. All consecutive patients who were the age ≥18 years, transported to the emergency department (ED) by ambulance with a suspected or confirmed COVID-19 in the pre-hospital frame were included in the study. Four different cut-off points were compared (0.7, 0.8, 0.9, and 1.0) to examine the predictive performance of both the mortality and ICU requirement of the SI. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) was employed to evaluate each cut-off value discriminatory for predicting 30-day mortality and ICU admission. The total of 364 patients was included in this study. The median age in the study population was 69 (55-80), of which 196 were men and 168 were women. AUC values for 30-day mortality outcome were calculated as 0.672, 0.674, 0.755, and 0.626, respectively, for threshold values of 0.7, 0.8, 0.9 and 1.0. ICU admission was more likely for the patients with pre-hospital SI> 0.9. Similarly, the mortality rate was higher in patients with pre-hospital SI> 0.9. Early triage of COVID-19 patients will ensure efficient use of healthcare resources. The SI could be a helpful, fast and powerful tool for predicting mortality status and ICU requirements of adult COVID-19 patients. It was concluded that the most useful threshold value for the shock index in predicting the prognosis of COVID-19 patients is 0.9.

Digestive system involvement and clinical outcomes among COVID-19 patients: A retrospective cohort study from Qatar.

BACKGROUNDCoronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 virus most commonly presents with respiratory symptoms. While gastrointestinal (GI) manifestations either at presentation or during hospitalization are also common, their impact on clinical outcomes is controversial. Some studies have described worse outcomes in COVID-19 patients with GI symptoms, while others have shown either no association or a protective effect. There is a need for consistent standards to describe GI symptoms in COVID-19 patients and to assess their effect on clinical outcomes, including mortality and disease severity.AIMTo investigate the prevalence of GI symptoms in hospitalized COVID-19 patients and their correlation with disease severity and clinical outcomes.METHODSWe retrospectively reviewed 601 consecutive adult COVID-19 patients requiring hospitalization between May 1-15, 2020. GI symptoms were recorded at admission and during hospitalization. Demographic, clinical, laboratory, and treatment data were retrieved. Clinical outcomes included all-cause mortality, disease severity at presentation, need for intensive care unit (ICU) admission, development of acute respiratory distress syndrome, and need for mechanical ventilation. Multivariate logistic regression model was used to identify independent predictors of the adverse outcomes. RESULTSThe prevalence of any GI symptom at admission was 27.1% and during hospitalization was 19.8%. The most common symptoms were nausea (98 patients), diarrhea (76 patients), vomiting (73 patients), and epigastric pain or discomfort (69 patients). There was no difference in the mortality between the two groups (6.21% vs 5.5%, P = 0.7). Patients with GI symptoms were more likely to have severe disease at presentation (33.13% vs 22.5%, P < 0.001) and prolonged hospital stay (15 d vs 14 d, P = 0.04). There was no difference in other clinical outcomes, including ICU admission, development of acute respiratory distress syndrome, or need for mechanical ventilation. Drugs associated with the development of GI symptoms during hospitalization were ribavirin (diarrhea 26.37% P < 0.001, anorexia 17.58%, P = 0.02), hydroxychloroquine (vomiting 28.52%, P = 0.009) and lopinavir/ritonavir (nausea 32.65% P = 0.049, vomiting 31.47% P = 0.004, and epigastric pain 12.65% P = 0.048). In the multivariate regression analysis, age > 65 years was associated with increased mortality risk [odds ratio (OR) 7.53, confidence interval (CI): 3.09-18.29, P < 0.001], ICU admission (OR: 1.79, CI: 1.13-2.83, P = 0.012), and need for mechanical ventilation (OR: 1.89, CI:1.94-2.99, P = 0.007). Hypertension was an independent risk factor for ICU admission (OR: 1.82, CI:1.17-2.84, P = 0.008) and need for mechanical ventilation (OR: 1.66, CI: 1.05-2.62, P = 0.028).CONCLUSIONPatients with GI symptoms are more likely to have severe disease at presentation; however, mortality and disease progression is not different between the two groups.

Longitudinal Cytokine Profile in Patients With Mild to Critical COVID-19.

The cytokine release syndrome has been proposed as the driver of inflammation in coronavirus disease 2019 (COVID-19). However, studies on longitudinal cytokine profiles in patients across the whole severity spectrum of COVID-19 are lacking. In this prospective observational study on adult COVID-19 patients admitted to two Hong Kong public hospitals, cytokine profiling was performed on blood samples taken during early phase (within 7 days of symptom onset) and late phase (8 to 12 days of symptom onset). The primary objective was to evaluate the difference in early and late cytokine profiles among patient groups with different disease severity. The secondary objective was to assess the associations between cytokines and clinical endpoints in critically ill patients. A total of 40 adult patients (mild = 8, moderate = 15, severe/critical = 17) hospitalized with COVID-19 were included in this study. We found 22 cytokines which were correlated with disease severity, as proinflammatory Th1-related cytokines (interleukin (IL)-18, interferon-induced protein-10 (IP-10), monokine-induced by gamma interferon (MIG), and IL-10) and ARDS-associated cytokines (IL-6, monocyte chemoattractant protein-1 (MCP-1), interleukin-1 receptor antagonist (IL-1RA), and IL-8) were progressively elevated with increasing disease severity. Furthermore, 11 cytokines were consistently different in both early and late phases, including seven (growth-regulated oncogene-alpha (GRO-α), IL-1RA, IL-6, IL-8, IL-10, IP-10, and MIG) that increased and four (FGF-2, IL-5, macrophage-derived chemokine (MDC), and MIP-1α) that decreased from mild to severe/critical patients. IL-8, followed by IP-10 and MDC were the best performing early biomarkers to predict disease severity. Among critically ill patients, MCP-1 predicted the duration of mechanical ventilation, highest norepinephrine dose administered, and length of intensive care stay.

Estimation of Coronavirus Disease 2019 Hospitalization Costs From a Large Electronic Administrative Discharge Database, March 2020-July 2021.

BackgroundInformation on the costs of inpatient care for patients with coronavirus disease 2019 (COVID-19) is very limited. This study estimates the per-patient cost of inpatient care for adult COVID-19 patients seen at >800 US hospitals.MethodsPatients aged ≥18 years with ≥1 hospitalization during March 2020–July 2021 with a COVID-19 diagnosis code in a large electronic administrative discharge database were included. We used validated costs when reported; otherwise, costs were calculated using charges multiplied by cost-to-charge ratios. We estimated costs of inpatient care per patient overall and by severity indicator, age, sex, underlying medical conditions, and acute complications of COVID-19 using a generalized linear model with log link function and gamma distribution.ResultsThe overall cost among 654673 patients hospitalized with COVID-19 was $16.2 billion. Estimated per-patient hospitalization cost was $24 826. Among surviving patients, estimated per-patient cost was $13 090 without intensive care unit (ICU) admission or invasive mechanical ventilation (IMV), $21 222 with ICU admission alone, and $59 742 with IMV. Estimated per-patient cost among patients who died was $27 017. Adjusted cost differential was higher among patients with certain underlying conditions (eg, chronic kidney disease [$12 391], liver disease [$8878], cerebrovascular disease [$7267], and obesity [$5933]) and acute complications (eg, acute respiratory distress syndrome [$43 912], pneumothorax [$25 240], and intracranial hemorrhage [$22 280]).ConclusionsThe cost of inpatient care for COVID-19 patients was substantial through the first 17 months of the pandemic. These estimates can be used to inform policy makers and planners and cost-effectiveness analysis of public health interventions to alleviate the burden of COVID-19.

Abstract 9489: Echocardiographic Characteristics, Cardiovascular Factors, and Disease-Directed Therapy Do Not Explain Differences in Covid-19 Related Hispanic Outcomes

Introduction: Severe coronavirus disease 2019 (COVID-19) is associated with cardiovascular injury and disparate outcomes in different ethnic groups. However, the reason for this difference has not been elucidated. Methods: A retrospective cross-sectional study was done on adult COVID-19 patients at a single center from April 2020 to January 2021. Mortality, length of stay, mechanical ventilation use, and intensive care unit (ICU) status were compared across demographic groups, echocardiographic indices, and COVID-19-specific treatments. Results: One hundred fifty patients were included. In univariate analysis, elevated cardiac biomarkers, COVID-19 directed therapies, and elevated right-sided pressures were associated with higher mortality, mechanical ventilation use, length of stay, and ICU admission. Multivariable logistic regression predicted higher mortality for Hispanic ethnicity (odds ratio, OR, 6.7) even when adjusting for advanced age (OR 5.3), mechanical ventilation use (OR 18), and right ventricular systolic pressure (OR 1.1 per 1mmHg). There were no differences in underlying comorbidities, echocardiographic indices, cardiac biomarkers, or treatments between Hispanic and non-Hispanic patients. Conclusions: Despite being a younger cohort, Hispanic patients had a higher rate of mortality even when controlling for age, biomarkers, and echocardiographic indices. This suggests Hispanic ethnicity is an independent risk factor for mortality in COVID-19 infection, highlighting an important health inequity that warrants further investigation.

Risk Factors for Invasive Aspergillosis in Patients Admitted to the Intensive Care Unit With Coronavirus Disease 2019: A Multicenter Retrospective Study.

Background: Invasive pulmonary aspergillosis (IPA) is a life-threatening complication in coronavirus disease 2019 (COVID-19) patients admitted to intensive care units (ICUs), but risk factors for COVID-19-associated IPA (CAPA) have not been fully characterized. The aim of the current study was to identify factors associated with CAPA, and assess long-term mortality.Methods: A retrospective cohort study of adult COVID-19 patients admitted to ICUs from six hospitals was conducted in Hubei, China. CAPA was diagnosed via composite clinical criteria. Demographic information, clinical variables, and 180-day outcomes after the diagnosis of CAPA were analyzed.Results: Of 335 critically ill patients with COVID-19, 78 (23.3%) developed CAPA within a median of 20.5 days (range 13.0–42.0 days) after symptom onset. Compared to those without CAPA, CAPA patients were more likely to have thrombocytopenia (50 vs. 19.5%, p < 0.001) and secondary bacterial infection prior to being diagnosed with CAPA (15.4 vs. 6.2%, p = 0.013), and to receive vasopressors (37.2 vs. 8.6%, p < 0.001), higher steroid dosages (53.9 vs. 34.2%, p = 0.002), renal replacement therapy (37.2 vs. 13.6%, p < 0.001), and invasive mechanical ventilation (57.7 vs. 35.8%, p < 0.001). In multivariate analysis incorporating hazard ratios (HRs) and confidence intervals (CIs), thrombocytopenia (HR 1.98, 95% CI 1.16–3.37, p = 0.012), vasopressor use (HR 3.57, 95% CI 1.80–7.06, p < 0.001), and methylprednisolone use at a daily dose ≥ 40 mg (HR 1.69, 95% CI 1.02–2.79, p = 1.02–2.79) before CAPA diagnosis were independently associated with CAPA. Patients with CAPA had longer median ICU stays (17 days vs. 12 days, p = 0.007), and higher 180-day mortality (65.4 vs. 33.5%, p < 0.001) than those without CAPA.Conclusions: Thrombocytopenia, vasopressor use, and corticosteroid treatment were significantly associated with increased risk of incident IPA in COVID-19 patients admitted to ICUs. The occurrence of CAPA may increase the likelihood of long-term COVID-19 mortality.

Association between non-alcoholic fatty liver disease with the susceptibility and outcome of COVID-19: A retrospective study.

This study aims to evaluate the effect of non‐alcoholic fatty liver disease (NAFLD) on the susceptibility and consequences of coronavirus disease 2019 (COVID‐19). We retrospectively collected data from 218 adult COVID‐19 patients who showed no evidence of excessive alcohol consumption and underwent abdominal ultrasound examinations. Of these patients, 39.4% patients had been diagnosed with NAFLD, which indicates a much higher prevalence of NAFLD than that reported in the general population. Significantly elevated white blood cell count (p = 0.008), alanine aminotransferase (p = 0.000), aspartate aminotransferase (p = 0.006) and C reactive protein (p = 0.012) were found in the patients with NAFLD. These patients also had significantly higher proportions of hypertension (p = 0.006) and diabetes (p = 0.049) than the non‐NAFLD cases. No significant differences existed in the severity, mortality, viral shedding time and length of hospital stay between patients with or without NAFLD in the sample population. However, subgroup analyses found that in patients with normal body mass index (BMI), NAFLD sufferers were more likely to experience a severe event (30.0% vs 11.5%, p = 0.021). Kaplan‐Meier curve (log‐rank p = 0.017) and Cox regression (HR = 3.26, 95% CI: 1.17–9.04, p = 0.023) analyses confirmed that before and after adjusting for gender, age and comorbidities, NAFLD patients with normal BMI had a higher incidence of suffering severe events. People with NAFLD may have a higher proportion of COVID‐19. NAFLD may be correlated with the severity of COVID‐19 patients in the normal BMI group.

Implications of left ventricular function on short-term outcomes in COVID-19 patients with myocardial injury

Abstract Background/Introduction Myocardial injury is a complication of coronavirus disease 2019 (COVID-19). Purpose We sought to describe a large multi-centre experience of COVID-19 patients with myocardial injury, examining the prognostic role left ventricular function plays on short-term outcomes. Methods We included adult COVID-19 patients admitted to our health system with evidence of myocardial injury and who underwent a transthoracic echocardiogram (TTE) during index admission. Patients were dichotomized into those with reduced ejection fraction (EF; &amp;lt;50%) and preserved EF (&amp;gt;50%). Results Across our 11-hospital system, 5032 adult patients were admitted with COVID-19 from March-September 2020. Of these, 235 had evidence of myocardial injury (troponin &amp;gt;1 ng/mL). Included were 134 patients who underwent TTE, of whom 43.3% (n=58) had reduced EF and 56.7% (n=76) preserved EF (Figure 1). A subset of 6 patients had newly reduced EF, with 5 demonstrating evidence of stress cardiomyopathy and subsequently dying. Overall, mortality was high in those with reduced EF and preserved EF (in-hospital: 34.5% vs. 28.9%; p=0.494; 6 months: 63.6% vs. 50.0%; p=0.167; Kaplan-Meier estimates: p=0.2886). Readmissions were frequent in both groups (30 days: 22.2% vs. 26.0%; p=0.162; 6 months: 52.0% vs. 54.5%; p=0.839) (Figure 2). Conclusions Many COVID-19 patients admitted with evidence of myocardial injury did not undergo TTE. For those who did, short-term mortality was high. Patients who survived hospitalisation had frequent readmissions. In patients with newly reduced EF, most had evidence of stress cardiomyopathy and expired. Larger studies are needed to fully evaluate the prognosis of COVID-19 patients with evidence of myocardial injury and left ventricular dysfunction. Funding Acknowledgement Type of funding sources: None. Figure 1Figure 2

Haematological and radiological-based prognostic markers of COVID-19

BackgroundAcute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has emerged in 2019 and caused a global pandemic in 2020, manifesting in the coronavirus disease 2019 (COVID-19). The majority of patients exhibit a mild form of the disease with no major complications; however, moderate to severe and fatal cases are of public health concerns. Predicting the potential prognosis of COVID-19 could assist healthcare workers in managing cases and controlling the pandemic in an effective way. Therefore, the objectives of the study were to search for biomarkers associated with COVID-19 mortality and predictors of the overall survival (OS). MethodsHere, clinical data of 6026 adult COVID-19 patients admitted to two large centers in Saudi Arabia (Riyadh and Hafar Al-Batin cities) between April and June 2020 were retrospectively analysed. ResultsMore than 23% of the study subjects with available data have died, enabling the prediction of mortality in our cohort. Markers that were significantly associated with mortality in this study were older age, increased d-dimer in the blood, higher counts of WBCs, higher percentage of neutrophil, and a higher chest X-ray (CXR) score. The CXR scores were also positively associated with age, d-dimer, WBC count, and percentage of neutrophil. This supports the utility of CXR scores in the absence of blood testing. Predicting mortality based on Ct values of RT-PCR was not successful, necessitating a more quantitative RT-PCR to determine virus quantity in samples. Our work has also identified age, d-dimer concentration, leukocyte parameters and CXR score to be prognostic markers of the OS of COVID-19 patients. ConclusionOverall, this retrospective study on hospitalised cohort of COVID-19 patients presents that age, haematological, and radiological data at the time of diagnosis are of value and could be used to guide better clinical management of COVID-19 patients.

Altered Lipid Profile Is a Risk Factor for the Poor Progression of COVID-19: From Two Retrospective Cohorts.

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has spread worldwide. However, the impact of baseline lipid profile on clinical endpoints in COVID-19 and the potential effect of COVID-19 on lipid profile remain unclear.MethodsIn this retrospective cohort study, we consecutively enrolled 430 adult COVID-19 patients from two Chinese hospitals (one each in Chengdu and Wuhan). The lipid profile before admission and during the disease course and the clinical endpoint including in-hospital death or oropharyngeal swab test positive again (OSTPA) after discharge were collected. We used Kaplan–Meier and Cox regression to explore the lipid risk factors before admission associated with endpoints. Then, we assessed the lipid level change along with the disease course to determine the relationship between pathology alteration and the lipid change.ResultsIn the Chengdu cohort, multivariable Cox regression showed that low-density lipoprotein cholesterol (LDL-C) dyslipidemia before admission was associated with OSTPA after discharge for COVID-19 patients (RR: 2.51, 95% CI: 1.19, 5.29, p = 0.006). In the Wuhan cohort, the patients with triglyceride (TG) dyslipidemia had an increased risk of in-hospital death (RR: 1.92, 95% CI: 1.08, 3.60, p = 0.016). In addition, in both cohorts, the lipid levels gradually decreased in the in-hospital death or OSTPA subgroups since admission. On admission, we also noticed the relationship between the biomarkers of inflammation and the organ function measures and this lipid level in both cohorts. For example, after adjusting for age, sex, comorbidities, smoking, and drinking status, the C-reactive protein level was negatively associated with the TC lipid level [β (SE) = -0.646 (0.219), p = 0.005]. However, an increased level of alanine aminotransferase, which indicates impaired hepatic function, was positively associated with total cholesterol (TC) lipid levels in the Chengdu cohort [β (SE) = 0.633 (0.229), p = 0.007].ConclusionsThe baseline dyslipidemia should be considered as a risk factor for poor prognosis of COVID-19. However, lipid levels may be altered during the COVID-19 course, since lipidology may be distinctly affected by both inflammation and organic damage for SARS-CoV-2.

Outcomes of COVID-19 patients intubated after failure of non-invasive ventilation: a multicenter observational study

The efficacy of non-invasive ventilation (NIV) in acute respiratory failure secondary to SARS-CoV-2 infection remains controversial. Current literature mainly examined efficacy, safety and potential predictors of NIV failure provided out of the intensive care unit (ICU). On the contrary, the outcomes of ICU patients, intubated after NIV failure, remain to be explored. The aims of the present study are: (1) investigating in-hospital mortality in coronavirus disease 2019 (COVID-19) ICU patients receiving endotracheal intubation after NIV failure and (2) assessing whether the length of NIV application affects patient survival. This observational multicenter study included all consecutive COVID-19 adult patients, admitted into the twenty-five ICUs of the COVID-19 VENETO ICU network (February–April 2020), who underwent endotracheal intubation after NIV failure. Among the 704 patients admitted to ICU during the study period, 280 (40%) presented the inclusion criteria and were enrolled. The median age was 69 [60–76] years; 219 patients (78%) were male. In-hospital mortality was 43%. Only the length of NIV application before ICU admission (OR 2.03 (95% CI 1.06–4.98), p = 0.03) and age (OR 1.18 (95% CI 1.04–1.33), p < 0.01) were identified as independent risk factors of in-hospital mortality; whilst the length of NIV after ICU admission did not affect patient outcome. In-hospital mortality of ICU patients intubated after NIV failure was 43%. Days on NIV before ICU admission and age were assessed to be potential risk factors of greater in-hospital mortality.

Favipiravir Versus Arbidol for Clinical Recovery Rate in Moderate and Severe Adult COVID-19 Patients: A Prospective, Multicenter, Open-Label, Randomized Controlled Clinical Trial.

Background: In addition to supportive therapy, antiviral therapy is an effective treatment for coronavirus disease 2019 (COVID-19).Objective: To compare the efficacy and safety of favipiravir and umifenovir (Arbidol) to treat COVID-19 patients.Methods: We conducted a prospective, randomized, controlled, open-label multicenter trial involving adult patients with COVID-19. Enrolled patients with initial symptoms within 12 days were randomly assigned in a 1:1 ratio to receive conventional therapy plus Arbidol (200 mg*3/day) or favipiravir (1600 mg*2/first day followed by 600 mg*2/day) for 7 days. The primary outcome was the clinical recovery rate at day 7 of drug administration (relief for pyrexia and cough, respiratory frequency ≤24 times/min; oxygen saturation ≥98%). Latency to relief for pyrexia and cough and the rate of auxiliary oxygen therapy (AOT) or noninvasive mechanical ventilation (NMV)/mechanical ventilation (MV) were the secondary outcomes. Safety data were collected for 17 days.Results: A total of 240 enrolled COVID-19 patients underwent randomization; 120 patients were assigned to receive favipiravir (116 assessed), and 120 patients were assigned to receive Arbidol (120 assessed). The clinical recovery rate at day 7 of drug administration did not significantly differ between the favipiravir group (71/116) and Arbidol group (62/120) (p = 0.1396, difference in recovery rate: 0.0954; 95% CI: −0.0305∼0.2213). Favipiravir contributed to relief for both pyrexia (difference: 1.70 days, p < 0.0001) and cough (difference: 1.75 days, p < 0.0001). No difference was observed in the AOT or NMV/MV rate (both p > 0.05). The most frequently observed favipiravir-associated adverse event was increased serum uric acid (16/116, OR: 5.52, p = 0.0014).Conclusion: Among patients with COVID-19, favipiravir, compared to Arbidol, did not significantly improve the clinical recovery rate at day 7. Favipiravir significantly improved the latency to relieve pyrexia and cough. Adverse effects caused by favipiravir are mild and manageable.

Prediction of mortality in COVID-19 through combing CT severity score with NEWS, qSOFA, or peripheral perfusion index.

IntroductionThe assessment of disease severity and the prediction of clinical outcomes at early disease stages can contribute to decreased mortality in patients with Coronavirus disease 2019 (COVID-19). This study was conducted to develop and validate a multivariable risk prediction model for mortality with using a combination of computed tomography severity score (CT-SS), national early warning score (NEWS), and quick sequential (sepsis-related) organ failure assessment (qSOFA) in COVID-19 patients.MethodsWe retrospectively collected medical data from 655 adult COVID-19 patients admitted to our hospital between July and November 2020. Data on demographics, clinical characteristics, and laboratory and radiological findings measured as part of standard care at admission were used to calculate NEWS, qSOFA score, CT-SS, peripheral perfusion index (PPI) and shock index (SI). Logistic regression and Cox proportional hazard models were used to predict mortality, which was our primary outcome. The predictive accuracy of distinct scoring systems was evaluated by the receiver-operating characteristic (ROC) curve analysis.ResultsThe median age was 50.0 years [333 males (50.8%), 322 females (49.2%)]. Higher NEWS and SI was associated with time-to-death within 90-days, whereas higher age, CT-SS and lower PPI were significantly associated with time-to-death within both 14 days and 90 days in the adjusted Cox regression model. The CT-SS predicted different mortality risk levels within each stratum of NEWS and qSOFA and improved the discrimination of mortality prediction models. Combining CT-SS with NEWS score yielded more accurate 14 days (DBA: −0.048, p = 0.002) and 90 days (DBA: −0.066, p < 0.001) mortality prediction.ConclusionCombining severity tools such as CT-SS, NEWS and qSOFA improves the accuracy of predicting mortality in patients with COVID-19. Inclusion of these tools in decision strategies might provide early detection of high-risk groups, avoid delayed medical attention, and improve patient outcomes.

Visual and Quantitative Assessment of COVID-19 Pneumonia on Chest CT: The Relationship with Disease Severity and Clinical Findings.

Lungs are the primary organ involved in COVID-19, and the severity of pneumonia in COVID-19 patients is an important cause of morbidity and mortality. We aimed to evaluate the pneumonia severity through the visual and quantitative assessment on chest computed tomography (CT) in patients with coronavirus disease 2019 (COVID-19) and compare the CT findings with clinical and laboratory findings. We retrospectively evaluated adult COVID-19 patients who underwent chest CT along with theirclinical scores, laboratory findings, and length of hospital stay. Two independent radiologists visually evaluated the pneumonia severity on chest CT (VSQS). Quantitative CT (QCT) assessment was performed using a free DICOM viewer, and the percentage of the well-aerated lung (%WAL), high-attenuation areas (%HAA) at different threshold values, and mean lung attenuation (MLA) values were calculated. The relationship between CT scores and the clinical, laboratory data, and the length of hospital stay were evaluated in this cross-sectional study. The student's t-test and chi-square test were used to analyze the differences between the variables. The Pearson correlation test analyzed the correlation between the variables. The diagnostic performance of the variables was assessed using the receiver operating characteristic (ROC) analysis. The VSQS and QCT scores were significantly correlated with procalcitonin, d-dimer, ferritin, and C-reactive protein levels. Both VSQ and QCT scores were significantly correlated with the disease severity (p < 0.001). Among the QCT parameters, the %HAA-600 value showed the best correlation with the VSQS (r = 730, p < 0.001). VSQS and QCT scores had high sensitivity and specificity in distinguishing disease severity and predicting prolonged hospitalization. The VSQS and QCT scores can help manage the COVID-19 and predict the duration of the hospitalization.

COVID-19 ICU mortality prediction: a machine learning approach using SuperLearner algorithm

BackgroundSince the beginning of coronavirus disease 2019 (COVID-19), the development of predictive models has sparked relevant interest due to the initial lack of knowledge about diagnosis, treatment, and prognosis. The present study aimed at developing a model, through a machine learning approach, to predict intensive care unit (ICU) mortality in COVID-19 patients based on predefined clinical parameters.ResultsObservational multicenter cohort study. All COVID-19 adult patients admitted to 25 ICUs belonging to the VENETO ICU network (February 28th 2020-april 4th 2021) were enrolled. Patients admitted to the ICUs before 4th March 2021 were used for model training (“training set”), while patients admitted after the 5th of March 2021 were used for external validation (“test set 1”). A further group of patients (“test set 2”), admitted to the ICU of IRCCS Ca’ Granda Ospedale Maggiore Policlinico of Milan, was used for external validation. A SuperLearner machine learning algorithm was applied for model development, and both internal and external validation was performed. Clinical variables available for the model were (i) age, gender, sequential organ failure assessment score, Charlson Comorbidity Index score (not adjusted for age), Palliative Performance Score; (ii) need of invasive mechanical ventilation, non-invasive mechanical ventilation, O2 therapy, vasoactive agents, extracorporeal membrane oxygenation, continuous venous-venous hemofiltration, tracheostomy, re-intubation, prone position during ICU stay; and (iii) re-admission in ICU.One thousand two hundred ninety-three (80%) patients were included in the “training set”, while 124 (8%) and 199 (12%) patients were included in the “test set 1” and “test set 2,” respectively. Three different predictive models were developed. Each model included different sets of clinical variables. The three models showed similar predictive performances, with a training balanced accuracy that ranged between 0.72 and 0.90, while the cross-validation performance ranged from 0.75 to 0.85. Age was the leading predictor for all the considered models.ConclusionsOur study provides a useful and reliable tool, through a machine learning approach, for predicting ICU mortality in COVID-19 patients. In all the estimated models, age was the variable showing the most important impact on mortality.

Impact of prone position on outcomes of COVID-19 patients with spontaneous breathing.

Background In this study, we explored whether early application of the prone position (PP) can improve severe hypoxemia and respiratory failure in coronavirus disease 2019 (COVID-19) patients with spontaneous breathing.Methods This is a prospective observational study of severe, critically ill adult COVID-19 patients admitted to the intensive care unit. All vital parameters were recorded in real time for all patients. Moreover, the results of chest computed tomography (CT), when available, were analyzed.Results PP was applied in 21 patients who were breathing spontaneously. The application of PP was associated with a significant increase in oxygen saturation measured by pulse oximetry (SpO2) from 82%±12% to 96%±3% (P<0.001) 1 hour later. Moreover, PP was associated with a significant reduction in respiratory rate from 31±10 to 21±4 breaths/min (P<0.001). Furthermore, the number of patients who exhibited signs of respiratory distress after PP was reduced from 10 (47%) to 3 (14%) (P=0.04). Early PP application also led to a clear improvement on CT imaging. It was not, however, associated with a reduction in mortality rate or in the use of invasive mechanical ventilation (P>0.05 for both).Conclusions Our study confirmed that the early application of PP can improve hypoxemia and tachypnea in COVID-19 patients with spontaneous breathing. Randomized controlled trials are needed to confirm the beneficial effects of PP in COVID-19 patients with spontaneous breathing.

Clinical characteristics and outcomes of critically ill COVID-19 patients in Sfax, Tunisia.

BackgroundAfrica, like the rest of the world, has been impacted by the coronavirus disease 2019 (COVID-19) pandemic. However, only a few studies covering this subject in Africa have been published.MethodsWe conducted a retrospective study of critically ill adult COVID-19 patients—all of whom had a confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection—admitted to the intensive care unit (ICU) of Habib Bourguiba University Hospital (Sfax, Tunisia).ResultsA total of 96 patients were admitted into our ICU for respiratory distress due to COVID-19 infection. Mean age was 62.4±12.8 years and median age was 64 years. Mean arterial oxygen tension (PaO2)/fractional inspired oxygen (FiO2) ratio was 105±60 and ≤300 in all cases but one. Oxygen support was required for all patients (100%) and invasive mechanical ventilation for 38 (40%). Prone positioning was applied in 67 patients (70%). Within the study period, 47 of the 96 patients died (49%). Multivariate analysis showed that the factors associated with poor outcome were the development of acute renal failure (odds ratio [OR], 6.7; 95% confidence interval [CI], 1.75–25.9), the use of mechanical ventilation (OR, 5.8; 95% CI, 1.54–22.0), and serum cholinesterase (SChE) activity lower than 5,000 UI/L (OR, 5.0; 95% CI, 1.34–19).ConclusionsIn this retrospective cohort study of critically ill patients admitted to the ICU in Sfax, Tunisia, for acute respiratory failure following COVID-19 infection, the mortality rate was high. The development of acute renal failure, the use of mechanical ventilation, and SChE activity lower than 5,000 UI/L were associated with a poor outcome.

Clinical characteristics and a decision tree model to predict death outcome in severe COVID-19 patients

BackgroundThe novel coronavirus disease 2019 (COVID-19) spreads rapidly among people and causes a pandemic. It is of great clinical significance to identify COVID-19 patients with high risk of death.MethodsA total of 2169 adult COVID-19 patients were enrolled from Wuhan, China, from February 10th to April 15th, 2020. Difference analyses of medical records were performed between severe and non-severe groups, as well as between survivors and non-survivors. In addition, we developed a decision tree model to predict death outcome in severe patients.ResultsOf the 2169 COVID-19 patients, the median age was 61 years and male patients accounted for 48%. A total of 646 patients were diagnosed as severe illness, and 75 patients died. An older median age and a higher proportion of male patients were found in severe group or non-survivors compared to their counterparts. Significant differences in clinical characteristics and laboratory examinations were found between severe and non-severe groups, as well as between survivors and non-survivors. A decision tree, including three biomarkers, neutrophil-to-lymphocyte ratio, C-reactive protein and lactic dehydrogenase, was developed to predict death outcome in severe patients. This model performed well both in training and test datasets. The accuracy of this model were 0.98 in both datasets.ConclusionWe performed a comprehensive analysis of COVID-19 patients from the outbreak in Wuhan, China, and proposed a simple and clinically operable decision tree to help clinicians rapidly identify COVID-19 patients at high risk of death, to whom priority treatment and intensive care should be given.

Laboratory parameters predicting mortality of adult in-patients with COVID-19 associated cytokine release syndrome treated with high-dose tocilizumab.

Large randomized clinical trials in severe Coronavirus Disease 2019 (COVID-19) patients have proven efficacy of intravenous tocilizumab. Our aim was to describe the laboratory parameters predicting in-hospital mortality of patients with tocilizumab administration in COVID-19 associated cytokine release syndrome (CRS).We evaluated high-dose (8 mg/kg) intravenous tocilizumab administration in severe and critically ill COVID-19 adult patients fulfilling predefined strict CRS criteria. A single-centre, prospective, observational cohort study was carried out among consecutive adult (≥18 years of age) in-patients with COVID-19 between April 1 and December 31, 2020. The primary endpoint was 28-day all-cause mortality. The changes in laboratory parameters from baseline on day 7 and 14 after administration of tocilizumab were analysed.In total, 1801 patients were admitted to our centre during the study period. One hundred and six patients received tocilizumab, and among them 62 (58.5%) required intensive care unit admittance while 25 (23.6%) deceased. At day 7 after tocilizumab administration, inflammatory markers (CRP, IL-6, ferritin) and lactate dehydrogenase (LDH) values were significantly lower among survivors. Subsequently, at day 14, differences of IL-6 and LDH levels has become more pronounced between subgroups. Restoration of absolute lymphocyte count (ALC) by day 7 and 14 was insufficient among patients who died.In our cohort, administration of high-dose tocilizumab for COVID-19 patients with CRS demonstrated clinical and sustained biochemical parameter improvement in 76.4%. In this patient population high and increasing LDH, IL-6, and low ALC levels had a predictive role for mortality.