Comparison of the clinical characteristics and outcomes of hospitalized adult COVID-19 and influenza patients - a prospective observational study

Comparative Analysis of Clinical Outcomes Using Propensity Score Matching: Coronavirus Disease 2019 vs. Seasonal Influenza in Korea

BACKGROUND

The advent of the omicron variant and the formulation of diverse therapeutic strategies marked a new epoch in the realm of coronavirus disease 2019 (COVID-19). Studies have compared the clinical outcomes between COVID-19 and seasonal influenza, but such studies were conducted during the early stages of the pandemic when effective treatment strategies had not yet been developed, which limits the generalizability of the findings. Therefore, an updated evaluation of the comparative analysis of clinical outcomes between COVID-19 and seasonal influenza is requisite.

METHODS

This study used data from the severe acute respiratory infection surveillance system of South Korea. We extracted data for influenza patients who were infected between 2018 and 2019 and COVID-19 patients who were infected in 2021 (pre-omicron period) and 2022 (omicron period). Comparisons of outcomes were conducted among the pre-omicron, omicron, and influenza cohorts utilizing propensity score matching. The adjusted covariates in the propensity score matching included age, sex, smoking, and comorbidities.

RESULTS

The study incorporated 1,227 patients in the pre-omicron cohort, 1,948 patients in the omicron cohort, and 920 patients in the influenza cohort. Following propensity score matching, 491 patients were included in each respective group. Clinical presentations exhibited similarities between the pre-omicron and omicron cohorts; however, COVID-19 patients demonstrated a higher prevalence of dyspnea and pulmonary infiltrates compared to their influenza counterparts. Both COVID-19 groups exhibited higher in-hospital mortality and longer hospital length of stay than the influenza group. The omicron group showed no significant improvement in clinical outcomes compared to the pre-omicron group.

CONCLUSION

The omicron group did not demonstrate better clinical outcomes than the pre-omicron group, and exhibited significant disease severity compared to the influenza group. Considering the likely persistence of COVID-19 infections, it is imperative to sustain comprehensive studies and ongoing policy support for the virus to enhance the prognosis for individuals affected by COVID-19.

A Comparison of the Epidemiological Characteristics Between Influenza and COVID-19 Patients: A Retrospective, Observational Cohort Study

Background and objective It is crucial to make early differentiation between coronavirus disease 2019 (COVID-19) and seasonal influenza infections at the time of a patient's presentation to the emergency department (ED). In light of this, this study aimed to identify key epidemiological, initial laboratory, and radiological differences that would enable early recognition during co-circulation. Methods This was a retrospective, observational cohort study. All adult patients presenting to our ED at the Watford General Hospital, UK, with a laboratory-confirmed diagnosis of COVID-19 (2019/20) or influenza (2018/19) infection were included in this study. Demographic, laboratory, and radiological data were collected. Binary logistic regression was employed to determine features associated with COVID-19 infection rather than influenza. Results Chest radiographs suggestive of viral pneumonitis and older age (≥80 years) were associated with increased odds of having COVID-19 [odds ratio (OR): 47.00, 95% confidence interval (CI): 21.63-102.13 and OR: 64.85, 95% CI: 19.96-210.69 respectively]. Low eosinophils (<0.02 x 109/L) were found to increase the odds of COVID-19 (OR: 2.12, 95% CI: 1.44-3.10, p<0.001). Conclusions Gaining awareness about the epidemiological, biological, and radiologic presentation of influenza-like illness can be useful for clinicians in ED to differentiate between COVID-19 and influenza. This study showed that older age, eosinopenia, and radiographic evidence of viral pneumonitis significantly increase the odds of having COVID-19 compared to influenza. Further research is needed to determine if these findings are affected by acquired or natural immunity.

Cost-Benefit of Real-Time Multiplex PCR Testing of SARS-CoV-2 in German Hospitals

BACKGROUND

The current Omicron COVID-19 pandemic has significant morbidity worldwide.

OBJECTIVE

Assess the cost-benefit relation of implementing PCR point-of-care (POCT) COVID-19 testing in the emergency rooms (ERs) of German hospitals and in the case of inpatient admission due to other acute illnesses.

METHODS

A deterministic decision-analytic model simulated the incremental costs of using the Savanna® Multiplex RT-PCR test compared to using clinical judgement alone to confirm or exclude COVID-19 in adult patients in German ERs prior to hospitalization or just prior to discharge. Direct and indirect costs were evaluated from the hospital perspective. Nasal or nasopharyngeal swabs of patients suspected to have COVID-19 by clinical judgement, but without POCT, were sent to external labs for RT-PCR testing.

RESULTS

In probabilistic sensitivity analysis, assuming a COVID-19 prevalence ranging between 15.6-41.2% and a hospitalization rate between 4.3-64.3%, implementing the Savanna® test saved, on average, €107 as compared to applying the clinical-judgement-only strategy. A revenue loss of €735 can be avoided when SARS-CoV-2 infection in patients coming unplanned to the hospital due to other acute illnesses are excluded immediately by POCT.

CONCLUSIONS

Using highly sensitive and specific PCR-POCT in patients suspected of COVID-19 infection at German ERs may significantly reduce hospital expenditures.

Mortality in cancer patients with SARS-CoV-2 or seasonal influenza: an observational cohort study from a German-wide hospital network

PURPOSE

At the beginning of the COVID-19 pandemic, SARS-CoV-2 was often compared to seasonal influenza. We aimed to compare the outcome of hospitalized patients with cancer infected by SARS-CoV-2 or seasonal influenza including intensive care unit admission, mechanical ventilation and in-hospital mortality.

METHODS

We analyzed claims data of patients with a lab-confirmed SARS-CoV-2 or seasonal influenza infection admitted to one of 85 hospitals of a German-wide hospital network between January 2016 and August 2021.

RESULTS

29,284 patients with COVID-19 and 7442 patients with seasonal influenza were included. Of these, 360 patients with seasonal influenza and 1625 patients with COVID-19 had any kind of cancer. Cancer patients with COVID-19 were more likely to be admitted to the intensive care unit than cancer patients with seasonal influenza (29.4% vs 24.7%; OR 1.31, 95% CI 1.00-1.73 p < .05). No statistical significance was observed in the mechanical ventilation rate for cancer patients with COVID-19 compared to those with seasonal influenza (17.2% vs 13.6% OR 1.34, 95% CI 0.96-1.86 p = .09). 34.9% of cancer patients with COVID-19 and 17.9% with seasonal influenza died (OR 2.45, 95% CI 1.81-3.32 p < .01). Risk factors among cancer patients with COVID-19 or seasonal influenza for in-hospital mortality included the male gender, age, a higher Elixhauser comorbidity index and metastatic cancer.

CONCLUSION

Among cancer patients, SARS-CoV-2 was associated with a higher risk for in-hospital mortality than seasonal influenza. These findings underline the need of protective measurements to prevent an infection with either COVID-19 or seasonal influenza, especially in this high-risk population.

Difference between SARS-CoV-2, seasonal coronavirus, influenza, and respiratory syncytial virus infection in solid organ transplant recipients

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been raging since the end of 2019 and has shown worse outcomes in solid organ transplant (SOT) recipients. The clinical differences as well as outcomes between respiratory viruses have not been well defined in this population.

METHODS

This is a retrospective cohort study of adult SOT recipients with nasopharyngeal swab or bronchoalveolar lavage PCR positive for either SARS-CoV-2, seasonal coronavirus, respiratory syncytial virus (RSV) or influenza virus from January 2017 to October 2020. The follow up period was 3 months. Clinical characteristics and outcomes were evaluated.

RESULTS

A total of 377 recipients including 157 SARS-CoV-2, 70 seasonal coronavirus, 50 RSV and 100 influenza infections were identified. The most common transplanted organ was kidney 224/377 (59.4%). Lower respiratory tract infection (LRTI) was found in 210/377 (55.7%) and the risk factors identified with multivariable analysis were SARS-CoV-2 infection, steroid use, and older age. Co- and secondary infections were seen in 77/377 (20.4%) recipients with bacterial pathogens as dominant. Hospital admission was seen in 266/377 (67.7%) recipients without significant statistical difference among viruses, however, ICU admission, mechanical ventilation and mortality were higher with SARS-CoV-2 infection. In the multivariable model, the risk factors for mortality were SARS-CoV-2 infection and older age.

CONCLUSIONS

We found higher incidence of ICU admission, mechanical ventilation, and mortality among SARS-CoV-2 infected recipients. Older age was found to be the risk factor for lower respiratory tract infection and mortality for SARS-CoV-2, coronaviruses, RSV and influenza virus groups.

Bacterial Pulmonary Co-Infections on ICU Admission: Comparison in Patients with SARS-CoV-2 and Influenza Acute Respiratory Failure: A Multicentre Cohort Study

Background: Few data are available on the impact of bacterial pulmonary co-infection (RespCoBact) during COVID-19 (CovRespCoBact). The aim of this study was to compare the prognosis of patients admitted to an ICU for influenza pneumonia and for SARS-CoV-2 pneumonia with and without RespCoBact. Methods: This was a multicentre (n = 11) observational study using the Outcomerea© database. Since 2008, all patients admitted with influenza pneumonia or SARS-CoV-2 pneumonia and discharged before 30 June 2021 were included. Risk factors for day-60 death and for ventilator-associated-pneumonia (VAP) in patients with influenza pneumonia or SARS-CoV-2 pneumonia with or without RespCoBact were determined. Results: Of the 1349 patients included, 157 were admitted for influenza and 1192 for SARS-CoV-2. Compared with the influenza patients, those with SARS-CoV-2 had lower severity scores, were more often under high-flow nasal cannula, were less often under invasive mechanical ventilation, and had less RespCoBact (8.2% for SARS-CoV-2 versus 24.8% for influenza). Day-60 death was significantly higher in patients with SARS-CoV-2 pneumonia with no increased risk of mortality with RespCoBact. Patients with influenza pneumonia and those with SARS-CoV-2 pneumonia had no increased risk of VAP with RespCoBact. Conclusions: SARS-CoV-2 pneumonia was associated with an increased risk of mortality compared with Influenza pneumonia. Bacterial pulmonary co-infections on admission were not associated with patient survival rates nor with an increased risk of VAP.

Impact of frailty on clinical outcomes in patients with and without COVID-19 pneumonitis admitted to intensive care units in Australia and New Zealand: a retrospective registry data analysis

BACKGROUND

It is unclear if the impact of frailty on mortality differs between patients with viral pneumonitis due to COVID-19 or other causes. We aimed to determine if a difference exists between patients with and without COVID-19 pneumonitis.

METHODS

This multicentre, retrospective, cohort study using the Australian and New Zealand Intensive Care Society Adult Patient Database included patients aged ≥ 16 years admitted to 153 ICUs between 01/012020 and 12/31/2021 with admission diagnostic codes for viral pneumonia or acute respiratory distress syndrome, and Clinical Frailty Scale (CFS). The primary outcome was hospital mortality.

RESULTS

A total of 4620 patients were studied, and 3077 (66.6%) had COVID-19. The patients with COVID-19 were younger (median [IQR] 57.0 [44.7-68.3] vs. 66.1 [52.0-76.2]; p < 0.001) and less frail (median [IQR] CFS 3 [2-4] vs. 4 [3-5]; p < 0.001) than non-COVID-19 patients. The overall hospital mortality was similar between the patients with and without COVID-19 (14.7% vs. 14.9%; p = 0.82). Frailty alone as a predictor of mortality showed only moderate discrimination in differentiating survivors from those who died but was similar between patients with and without COVID-19 (AUROC 0.68 vs. 0.66; p = 0.42). Increasing frailty scores were associated with hospital mortality, after adjusting for Australian and New Zealand Risk of Death score and sex. However, the effect of frailty was similar in patients with and without COVID-19 (OR = 1.29; 95% CI: 1.19-1.41 vs. OR = 1.24; 95% CI: 1.11-1.37).

CONCLUSION

The presence of frailty was an independent risk factor for mortality. However, the impact of frailty on outcomes was similar in COVID-19 patients compared to other causes of viral pneumonitis.

Patient outcomes following emergency admission to hospital for COVID-19 compared with influenza: retrospective cohort study

BACKGROUND

We examine differences in posthospitalisation outcomes, and health system resource use, for patients hospitalised with COVID-19 during the UK's first pandemic wave in 2020, and influenza during 2018 and 2019.

METHODS

This retrospective cohort study used routinely collected primary and secondary care data. Outcomes, measured for 90 days follow-up after discharge were length of stay in hospital, mortality, emergency readmission and primary care activity.

RESULTS

The study included 5132 patients admitted to hospital as an emergency, with COVID-19 and influenza cohorts comprising 3799 and 1333 patients respectively. Patients in the COVID-19 cohort were more likely to stay in hospital longer than 10 days (OR 3.91, 95% CI 3.14 to 4.65); and more likely to die in hospital (OR 11.85, 95% CI 8.58 to 16.86) and within 90 days of discharge (OR 7.92, 95% CI 6.20 to 10.25). For those who survived, rates of emergency readmission within 90 days were comparable between COVID-19 and influenza cohorts (OR 1.07, 95% CI 0.89 to 1.29), while primary care activity was greater among the COVID-19 cohort (incidence rate ratio 1.30, 95% CI 1.23 to 1.37).

CONCLUSIONS

Patients admitted for COVID-19 were more likely to die, more likely to stay in hospital for over 10 days and interact more with primary care after discharge, than patients admitted for influenza. However, readmission rates were similar for both groups. These findings, while situated in the context of the first wave of COVID-19, with the associated pressures on the health system, can inform health service planning for subsequent waves of COVID-19, and show that patients with COVID-19 interact more with healthcare services as well as having poorer outcomes than those with influenza.

Differential diagnosis of COVID-19 and influenza

This study uses two existing data sources to examine how patients' symptoms can be used to differentiate COVID-19 from other respiratory diseases. One dataset consisted of 839,288 laboratory-confirmed, symptomatic, COVID-19 positive cases reported to the Centers for Disease Control and Prevention (CDC) from March 1, 2019, to September 30, 2020. The second dataset provided the controls and included 1,814 laboratory-confirmed influenza positive, symptomatic cases, and 812 cases with symptomatic influenza-like-illnesses. The controls were reported to the Influenza Research Database of the National Institute of Allergy and Infectious Diseases (NIAID) between January 1, 2000, and December 30, 2018. Data were analyzed using case-control study design. The comparisons were done using 45 scenarios, with each scenario making different assumptions regarding prevalence of COVID-19 (2%, 4%, and 6%), influenza (0.01%, 3%, 6%, 9%, 12%) and influenza-like-illnesses (1%, 3.5% and 7%). For each scenario, a logistic regression model was used to predict COVID-19 from 2 demographic variables (age, gender) and 10 symptoms (cough, fever, chills, diarrhea, nausea and vomiting, shortness of breath, runny nose, sore throat, myalgia, and headache). The 5-fold cross-validated Area under the Receiver Operating Curves (AROC) was used to report the accuracy of these regression models. The value of various symptoms in differentiating COVID-19 from influenza depended on a variety of factors, including (1) prevalence of pathogens that cause COVID-19, influenza, and influenza-like-illness; (2) age of the patient, and (3) presence of other symptoms. The model that relied on 5-way combination of symptoms and demographic variables, age and gender, had a cross-validated AROC of 90%, suggesting that it could accurately differentiate influenza from COVID-19. This model, however, is too complex to be used in clinical practice without relying on computer-based decision aid. Study results encourage development of web-based, stand-alone, artificial Intelligence model that can interview patients and help clinicians make quarantine and triage decisions.

COVID-19 versus seasonal influenza: myocardial injury and prognostic importance

Background

Acute myocardial injury is associated with poor prognosis in respiratory tract infections. We aimed to highlight the differences in prevalence of myocardial injury and its impact on prognosis in patients with COVID-19 compared to those with seasonal influenza.

Methods

This was a single-center prospective cohort study with a historical control group. 300 age-/sex-matched SARS-CoV-2 and seasonal influenza positive patients were enrolled. Myocardial injury was assessed by electrocardiogram (ECG), transthoracic echocardiography and biomarkers including high-sensitivity troponin-I. All patients were followed-up for 30 days after enrollment for all-cause mortalitiy, admission to the intensive care unit (ICU) and mechanical ventilation.

Results

Right ventricular distress was more common in COVID-19 whereas pathological ECG findings and impaired left ventricular function were more prevalent among influenza patients. COVID-19 patients suffered from a higher percentage of hypertension and dyslipidaemia. Contrary to COVID-19, pericardial effusion at admission was associated with poor outcome in the influenza group. Severe course of disease and respiratory failure resulted in significantly higher rates of ICU treatment and mechanical ventilation in COVID-19 patients. Although distribution of myocardial injury was similar, significantly fewer cardiac catheterizations were performed in COVID-19 patients. However, number of cardiac catheterizations was low in both groups. Finally, 30-day mortality was significantly higher in COVID-19 compared to influenza patients.

Conclusions

In adults requiring hospitalization due to COVID-19 or seasonal influenza, cardiovascular risk factors and signs of myocardial distress differ significantly. Furthermore, cardiovascular comorbidities may impair prognosis in COVID-19 patients to a higher degree than in their influenza counterparts.

Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19

BACKGROUND

COVID-19 illness is highly variable, ranging from infection with no symptoms through to pneumonia and life-threatening consequences. Symptoms such as fever, cough, or loss of sense of smell (anosmia) or taste (ageusia), can help flag early on if the disease is present. Such information could be used either to rule out COVID-19 disease, or to identify people who need to go for COVID-19 diagnostic tests. This is the second update of this review, which was first published in 2020.

OBJECTIVES

To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID-19 clinics, has COVID-19.

SEARCH METHODS

We undertook electronic searches up to 10 June 2021 in the University of Bern living search database. In addition, we checked repositories of COVID-19 publications. We used artificial intelligence text analysis to conduct an initial classification of documents. We did not apply any language restrictions.

SELECTION CRITERIA

Studies were eligible if they included people with clinically suspected COVID-19, or recruited known cases with COVID-19 and also controls without COVID-19 from a single-gate cohort. Studies were eligible when they recruited people presenting to primary care or hospital outpatient settings. Studies that included people who contracted SARS-CoV-2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards.

DATA COLLECTION AND ANALYSIS

Pairs of review authors independently selected all studies, at both title and abstract, and full-text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and assessed risk of bias using the QUADAS-2 checklist, and resolved disagreements by discussion with a third review author. Analyses were restricted to prospective studies only. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic (ROC) space and in dumbbell plots. We estimated summary parameters using a bivariate random-effects meta-analysis whenever five or more primary prospective studies were available, and whenever heterogeneity across studies was deemed acceptable.

MAIN RESULTS

We identified 90 studies; for this update we focused on the results of 42 prospective studies with 52,608 participants. Prevalence of COVID-19 disease varied from 3.7% to 60.6% with a median of 27.4%. Thirty-five studies were set in emergency departments or outpatient test centres (46,878 participants), three in primary care settings (1230 participants), two in a mixed population of in- and outpatients in a paediatric hospital setting (493 participants), and two overlapping studies in nursing homes (4007 participants). The studies did not clearly distinguish mild COVID-19 disease from COVID-19 pneumonia, so we present the results for both conditions together. Twelve studies had a high risk of bias for selection of participants because they used a high level of preselection to decide whether reverse transcription polymerase chain reaction (RT-PCR) testing was needed, or because they enrolled a non-consecutive sample, or because they excluded individuals while they were part of the study base. We rated 36 of the 42 studies as high risk of bias for the index tests because there was little or no detail on how, by whom and when, the symptoms were measured. For most studies, eligibility for testing was dependent on the local case definition and testing criteria that were in effect at the time of the study, meaning most people who were included in studies had already been referred to health services based on the symptoms that we are evaluating in this review. The applicability of the results of this review iteration improved in comparison with the previous reviews. This version has more studies of people presenting to ambulatory settings, which is where the majority of assessments for COVID-19 take place. Only three studies presented any data on children separately, and only one focused specifically on older adults. We found data on 96 symptoms or combinations of signs and symptoms. Evidence on individual signs as diagnostic tests was rarely reported, so this review reports mainly on the diagnostic value of symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. RT-PCR was the most often used reference standard (40/42 studies). Only cough (11 studies) had a summary sensitivity above 50% (62.4%, 95% CI 50.6% to 72.9%)); its specificity was low (45.4%, 95% CI 33.5% to 57.9%)). Presence of fever had a sensitivity of 37.6% (95% CI 23.4% to 54.3%) and a specificity of 75.2% (95% CI 56.3% to 87.8%). The summary positive likelihood ratio of cough was 1.14 (95% CI 1.04 to 1.25) and that of fever 1.52 (95% CI 1.10 to 2.10). Sore throat had a summary positive likelihood ratio of 0.814 (95% CI 0.714 to 0.929), which means that its presence increases the probability of having an infectious disease other than COVID-19. Dyspnoea (12 studies) and fatigue (8 studies) had a sensitivity of 23.3% (95% CI 16.4% to 31.9%) and 40.2% (95% CI 19.4% to 65.1%) respectively. Their specificity was 75.7% (95% CI 65.2% to 83.9%) and 73.6% (95% CI 48.4% to 89.3%). The summary positive likelihood ratio of dyspnoea was 0.96 (95% CI 0.83 to 1.11) and that of fatigue 1.52 (95% CI 1.21 to 1.91), which means that the presence of fatigue slightly increases the probability of having COVID-19. Anosmia alone (7 studies), ageusia alone (5 studies), and anosmia or ageusia (6 studies) had summary sensitivities below 50% but summary specificities over 90%. Anosmia had a summary sensitivity of 26.4% (95% CI 13.8% to 44.6%) and a specificity of 94.2% (95% CI 90.6% to 96.5%). Ageusia had a summary sensitivity of 23.2% (95% CI 10.6% to 43.3%) and a specificity of 92.6% (95% CI 83.1% to 97.0%). Anosmia or ageusia had a summary sensitivity of 39.2% (95% CI 26.5% to 53.6%) and a specificity of 92.1% (95% CI 84.5% to 96.2%). The summary positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.55 (95% CI 3.46 to 5.97) and 4.99 (95% CI 3.22 to 7.75) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The summary positive likelihood ratio of ageusia alone was 3.14 (95% CI 1.79 to 5.51). Twenty-four studies assessed combinations of different signs and symptoms, mostly combining olfactory symptoms. By combining symptoms with other information such as contact or travel history, age, gender, and a local recent case detection rate, some multivariable prediction scores reached a sensitivity as high as 90%.

AUTHORS' CONCLUSIONS

Most individual symptoms included in this review have poor diagnostic accuracy. Neither absence nor presence of symptoms are accurate enough to rule in or rule out the disease. The presence of anosmia or ageusia may be useful as a red flag for the presence of COVID-19. The presence of cough also supports further testing. There is currently no evidence to support further testing with PCR in any individuals presenting only with upper respiratory symptoms such as sore throat, coryza or rhinorrhoea. Combinations of symptoms with other readily available information such as contact or travel history, or the local recent case detection rate may prove more useful and should be further investigated in an unselected population presenting to primary care or hospital outpatient settings. The diagnostic accuracy of symptoms for COVID-19 is moderate to low and any testing strategy using symptoms as selection mechanism will result in both large numbers of missed cases and large numbers of people requiring testing. Which one of these is minimised, is determined by the goal of COVID-19 testing strategies, that is, controlling the epidemic by isolating every possible case versus identifying those with clinically important disease so that they can be monitored or treated to optimise their prognosis. The former will require a testing strategy that uses very few symptoms as entry criterion for testing, the latter could focus on more specific symptoms such as fever and anosmia.

Comparison of Hospitalized Coronavirus Disease 2019 and Influenza Patients Requiring Supplemental Oxygen in a Cohort Study: Clinical Impact and Resource Consumption

BACKGROUND

To compare clinical characteristics, outcomes, and resource consumption of patients with coronavirus disease 2019 (COVID-19) and seasonal influenza requiring supplemental oxygen.

METHODS

Retrospective cohort study conducted at a tertiary-care hospital. Patients admitted because of seasonal influenza between 2017 and 2019, or with COVID-19 between March and May 2020 requiring supplemental oxygen were compared. Primary outcome: 30-day mortality. Secondary outcomes: 90-day mortality and hospitalization costs. Attempted sample size to detect an 11% difference in mortality was 187 patients per group.

RESULTS

COVID-19 cases were younger (median years of age, 67; interquartile range [IQR] 54-78 vs 76 [IQR 64-83]; P < .001) and more frequently overweight, whereas influenza cases had more hypertension, immunosuppression, and chronic heart, respiratory, and renal disease. Compared with influenza, COVID-19 cases had more pneumonia (98% vs 60%, <.001), higher Modified Early Warning Score (MEWS) and CURB-65 (confusion, blood urea nitrogen, respiratory rate, systolic blood pressure, and age >65 years) scores and were more likely to show worse progression on the World Health Organization ordinal scale (33% vs 4%; P < .001). The 30-day mortality rate was higher for COVID-19 than for influenza: 15% vs 5% (P = .001). The median age of nonsurviving cases was 81 (IQR 74-88) and 77.5 (IQR 65-84) (P = .385), respectively. COVID-19 was independently associated with 30-day (hazard ratio [HR], 4.6; 95% confidence interval [CI], 2-10.4) and 90-day (HR, 5.2; 95% CI, 2.4-11.4) mortality. Sensitivity and subgroup analyses, including a subgroup considering only patients with pneumonia, did not show different trends. Regarding resource consumption, COVID-19 patients had longer hospital stays and higher critical care, pharmacy, and complementary test costs.

CONCLUSIONS

Although influenza patients were older and had more comorbidities, COVID-19 cases requiring supplemental oxygen on admission had worse clinical and economic outcomes.

Severe COVID‐19 pneumonia in an intensive care setting and comparisons with historic severe viral pneumonia due to other viruses

Purpose

Severe viral pneumonia is associated with significant morbidity and mortality. Recent COVID‐19 pandemic continues to impose significant health burden worldwide, and individual pandemic waves often lead to a large surge in the intensive care unit (ICU) admissions for respiratory support. Comparisons of severe SARS‐CoV‐2 pneumonia with other seasonal and nonseasonal severe viral infections are rarely studied in an intensive care setting.

Methods

A retrospective cohort study comparing patients admitted to ICU with COVID‐19 between March and June 2020 and those with viral pneumonias between January and December 2019. We compared patient specific demographic variables, duration of illness, ICU organ supportive measures and outcomes between both groups.

Results

Analysis of 93 COVID‐19 (Group 1) and 52 other viral pneumonia patients (Group 2) showed an increased proportion of obesity (42% vs. 23%, p = 0.02), non‐White ethnicities (41% vs. 6%, p < 0.001) and diabetes mellitus (30% vs. 13%, p = 0.03) in Group 1, with lower prevalence of chronic obstructive pulmonary disease (COPD)/asthma (16% vs. 34%, p = 0.02). In Group 1, the neutrophil to lymphocyte ratio was much lower (6.7 vs. 10, p = 0.006), and invasive mechanical ventilation (58% vs. 26%, p < 0.001) was more common. Length of ICU (8 vs. 4, p < 0.001) and hospital stay (22 vs. 11, p < 0.001) was prolonged in Group 1, with no significant difference in mortality. Influenza A and rhinovirus were the most common pathogens in Group 2 (26% each).

Conclusions

Key differences were identified within demographics (obesity, ethnicity, age, ICU scores, comorbidities) and organ support. Despite these variations, there were no significant differences in mortality between both groups. Further studies with larger sample sizes would allow for further assessment of clinical parameters in these patients.

Comparison of the clinical parameters of patients with COVID-19 and influenza using blood test data: a retrospective cross-sectional survey

Objective

The characteristic features, including blood test data, of the novel coronavirus disease 2019 (COVID-19) versus influenza have not been defined. We therefore compared the clinical parameters, including blood test data, of COVID-19 and influenza.

Methods

This retrospective cross-sectional survey was conducted at Juntendo University Nerima Hospital. We recruited patients diagnosed with COVID-19 between 1 January 2020 and 31 December 2020 who underwent blood tests. For comparison, we recruited an equivalent number of patients who were diagnosed with influenza and who underwent blood tests.

Results

During the study period, 228 patients (male:female, 123 [54.0%]:105 [46.0%]; age, 54.68 ± 18.98 years) were diagnosed with COVID-19. We also recruited 228 patients with influenza (male:female, 129 [56.6%]:99 [43.4%]; age, 69.6 ± 21.25 years). An age of 15 to 70 years (vs. 71 years), breathing difficulty, and malaise were significantly more common in patients with COVID-19 than in those with influenza. However, nausea, body temperature >38.1°C, and white blood cell count >9000/μL were more common in patients with influenza.

Conclusions

Our results are useful for differentiating COVID-19 from influenza, and these findings will be extremely helpful for future practice as we learn to coexist with COVID-19.

Increased 30-day mortality in very old ICU patients with COVID-19 compared to patients with respiratory failure without COVID-19

Purpose

The number of patients ≥ 80 years admitted into critical care is increasing. Coronavirus disease 2019 (COVID-19) added another challenge for clinical decisions for both admission and limitation of life-sustaining treatments (LLST). We aimed to compare the characteristics and mortality of very old critically ill patients with or without COVID-19 with a focus on LLST.

Methods

Patients 80 years or older with acute respiratory failure were recruited from the VIP2 and COVIP studies. Baseline patient characteristics, interventions in intensive care unit (ICU) and outcomes (30-day survival) were recorded. COVID patients were matched to non-COVID patients based on the following factors: age (± 2 years), Sequential Organ Failure Assessment (SOFA) score (± 2 points), clinical frailty scale (± 1 point), gender and region on a 1:2 ratio. Specific ICU procedures and LLST were compared between the cohorts by means of cumulative incidence curves taking into account the competing risk of discharge and death.

Results

693 COVID patients were compared to 1393 non-COVID patients. COVID patients were younger, less frail, less severely ill with lower SOFA score, but were treated more often with invasive mechanical ventilation (MV) and had a lower 30-day survival. 404 COVID patients could be matched to 666 non-COVID patients. For COVID patients, withholding and withdrawing of LST were more frequent than for non-COVID and the 30-day survival was almost half compared to non-COVID patients.

Conclusion

Very old COVID patients have a different trajectory than non-COVID patients. Whether this finding is due to a decision policy with more active treatment limitation or to an inherent higher risk of death due to COVID-19 is unclear.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00134-022-06642-z.

Symptom Clustering Patterns and Population Characteristics of COVID-19 Based on Text Clustering Method

Background

Descriptions of single clinical symptoms of coronavirus disease 2019 (COVID-19) have been widely reported. However, evidence of symptoms associations was still limited. We sought to explore the potential symptom clustering patterns and high-frequency symptom combinations of COVID-19 to enhance the understanding of people of this disease.

Methods

In this retrospective cohort study, a total of 1,067 COVID-19 cases were enrolled. Symptom clustering patterns were first explored by a text clustering method. Then, a multinomial logistic regression was applied to reveal the population characteristics of different symptom groups. In addition, time intervals between symptoms onset and the first visit were analyzed to consider the effect of time interval extension on the progression of symptoms.

Results

Based on text clustering, the symptoms were summarized into four groups. Group 1: no-obvious symptoms; Group 2: mainly fever and/or dry cough; Group 3: mainly upper respiratory tract infection symptoms; Group 4: mainly cardiopulmonary, systemic, and/or gastrointestinal symptoms. Apart from Group 1 with no obvious symptoms, the most frequent symptom combinations were fever only (64 cases, 47.8%), followed by dry cough only (42 cases, 31.3%) in Group 2; expectoration only (21 cases, 19.8%), followed by expectoration complicated with fever (10 cases, 9.4%) in Group 3; fatigue complicated with fever (12 cases, 4.2%), followed by headache complicated with fever was also high (11 cases, 3.8%) in Group 4. People aged 45–64 years were more likely to have symptoms of Group 4 than those aged 65 years or older (odds ratio [OR] = 2.66, 95% CI: 1.21–5.85) and at the same time had longer time intervals.

Conclusions

Symptoms of COVID-19 could be divided into four clustering groups with different symptom combinations. The Group 4 symptoms (i.e., mainly cardiopulmonary, systemic, and/or gastrointestinal symptoms) happened more frequently in COVID-19 than in influenza. This distinction could help deepen the understanding of this disease. The middle-aged people have a longer time interval for medical visit and was a group that deserve more attention, from the perspective of medical delays.

Comparison of patient characteristics and in-hospital mortality between patients with COVID-19 in 2020 and those with influenza in 2017-2020: a multicenter, retrospective cohort study in Japan

Background

COVID-19 has worse mortality than influenza in American and European studies, but evidence from the Western Pacific region is scarce.

Methods

Using a large-scale multicenter inpatient claims data in Japan, we identified individuals hospitalised with COVID-19 in 2020 or influenza in 2017–2020. We compared patient characteristics, supportive care, and in-hospital mortality, with multivariable logistic regression analyses for in-hospital mortality overall, by age group, and among patients with mechanical ventilation.

Findings

We identified 16,790 COVID-19 patients and 27,870 influenza patients, with the different age distribution (peak at 70–89 years in COVID-19 vs. bimodal peaks at 0–9 and 80–89 years in influenza). On admission, the use of mechanical ventilation was similar in both groups (1·4% vs. 1·4%) but higher in the COVID-19 group (3·3% vs. 2·5%; p<0·0001) during the entire hospitalisation. The crude in-hospital mortality was 5·1% (856/16,790) for COVID-19 and 2·8% (791/27,870) for influenza. Adjusted for potential confounders, the in-hospital mortality was higher for COVID-19 than for influenza (adjusted odds ratio [aOR] 1·83, 95% confidence interval [CI] 1·64–2·04). In age-stratified analyses, the aOR (95%CI) were 0·78 (0·56–1·08) and 2·05 (1·83–2·30) in patients aged 20–69 years and ≥70 years, respectively (p-for-interaction<0·0001). Among patients with mechanical ventilation, the aOR was 0·79 (0·59–1·05).

Interpretation

Patients hospitalised with COVID-19 in Japan were more likely to die than those with influenza. However, this was mainly driven by findings in older people, and there was no difference once mechanical ventilation was started.

Funding

Ministry of Health, Labour and Welfare of Japan (21AA2007).

Comparison of Clinical Characteristics for Distinguishing COVID-19 From Influenza During the Early Stages in Guangdong, China

Background: To explore the differences in clinical manifestations and infection marker determination for early diagnosis of coronavirus disease-2019 (COVID-19) and influenza (A and B).

Methods: A hospital-based retrospective cohort study was designed. Patients with COVID-19 and inpatients with influenza at a sentinel surveillance hospital were recruited. Demographic data, medical history, laboratory findings, and radiographic characteristics were summarized and compared between the two groups. The chi-square test or Fisher's exact test was used for categorical variables, and Kruskal–Wallis H-test was used for continuous variables in each group. Receiver operating characteristic curve (ROC) was used to differentiate the intergroup characteristics. The Cox proportional hazards model was used to analyze the predisposing factors.

Results: About 23 patients with COVID-19 and 74 patients with influenza were included in this study. Patients with influenza exhibited more symptoms of cough and sputum production than COVID-19 (p < 0.05). CT showed that consolidation and pleural effusion were more common in influenza than COVID-19 (p < 0.05). Subgroup analysis showed that patients with influenza had high values of infection and coagulation function markers, but low values of blood routine and biochemical test markers than patients with COVID-19 (mild or moderate groups) (p < 0.05). In patients with COVID-19, the ROC analysis showed positive predictions of albumin and hematocrit, but negative predictions of C-reactive protein (CRP), procalcitonin (PCT), lactate dehydrogenase (LDH), hydroxybutyrate dehydrogenase (HBDH), and erythrocyte sedimentation rate. Multivariate analysis revealed that influenza might associate with risk of elevated CRP, PCT, and LDH, whereas COVID-19 might associated with high HBDH.

Conclusion: Patients with influenza had more obvious clinical symptoms but less common consolidation lesions and pleural effusion than those with COVID-19. These findings suggested that influenza likely presents with stronger inflammatory reactions than COVID-19, which provides some insights into the pathogenesis of these two contagious respiratory illnesses.

Prognostic value of neutrophil-to-lymphocyte ratio in COVID-19 compared with Influenza and respiratory syncytial virus infection

A high neutrophil to lymphocyte ratio (NLR) is considered an unfavorable prognostic factor in various diseases, including COVID-19. The prognostic value of NLR in other respiratory viral infections, such as Influenza, has not hitherto been extensively studied. We aimed to compare the prognostic value of NLR in COVID-19, Influenza and Respiratory Syncytial Virus infection (RSV). A retrospective cohort of COVID-19, Influenza and RSV patients admitted to the Tel Aviv Medical Center from January 2010 to October 2020 was analyzed. Laboratory, demographic, and clinical parameters were collected. Two way analyses of variance (ANOVA) was used to compare the association between NLR values and poor outcomes among the three groups. ROC curve analyses for each virus was applied to test the discrimination ability of NLR. 722 COVID-19, 2213 influenza and 482 RSV patients were included. Above the age of 50, NLR at admission was significantly lower among COVID-19 patients (P < 0.001). NLR was associated with poor clinical outcome only in the COVID-19 group. ROC curve analysis was performed; the area under curve of poor outcomes for COVID-19 was 0.68, compared with 0.57 and 0.58 for Influenza and RSV respectively. In the COVID-19 group, multivariate logistic regression identified a high NLR (defined as a value above 6.82) to be a prognostic factor for poor clinical outcome, after adjusting for age, sex and Charlson comorbidity score (odds ratio of 2.9, P < 0.001). NLR at admission is lower and has more prognostic value in COVID-19 patients, when compared to Influenza and RSV.

Clinical characteristics and population-based attack rates of respiratory syncytial virus versus influenza hospitalizations among adults-An observational study

Background

The clinical significance of respiratory syncytial virus (RSV) among adults remains underinvestigated. We compared the characteristics and population‐based attack rates of RSV and influenza hospitalizations.

Methods

During 2018–2020, we recruited hospitalized adults with respiratory infection to our prospective substudy at a tertiary care hospital in Finland and compared the characteristics of RSV and influenza patients. In our retrospective substudy, we calculated the attack rates of all RSV and influenza hospitalizations among adults in the same geographic area during 2016–2020.

Results

Of the 537 prospective substudy patients, 31 (6%) had RSV, and 106 (20%) had influenza. Duration of hospitalization, need for intensive care or outcome did not differ significantly between RSV and influenza patients. RSV was more often missed or its diagnosis omitted from medical record (13% vs 1% p = 0.016 and 48% vs 15%, p > 0.001). In the retrospective substudy, the mean attack rates of RSV, influenza A, and influenza B hospitalizations rose with age from 4.1 (range by season 1.9–5.9), 15.4 (12.3–23.3), and 4.7 (0.5–16.2) per 100,000 persons among 18‐ to 64‐year‐olds to 58.3 (19.3–117.6), 204.1 (31.0–345.0), and 60.4 (0.0–231.0) per 100,000 persons among 65+‐year‐olds and varied considerably between seasons.

Discussion

While the attack rates of influenza hospitalizations were higher compared with RSV, RSV and influenza hospitalizations were similar in severity. Missing or underreporting of RSV infections may lead to underestimating its disease burden. Both RSV and influenza caused a substantial amount of hospitalizations among the elderly, stressing the need for more effective interventions.

Lower antibiotic prescription rates in hospitalized COVID-19 patients than influenza patients, a prospective study

BACKGROUND

COVID-19 patients are extensively treated with antibiotics despite few bacterial complications. We aimed to study antibiotic use in hospitalized COVID-19 patients compared to influenza patients in two consecutive years. Furthermore, we investigated changes in antibiotic use from the first to second pandemic wave.

METHODS

This prospective study included both patients from two referral hospitals in Bergen, Norway, admitted with influenza (n = 215) during the 2018/2019 epidemic and with COVID-19 (n = 82) during spring/summer 2020, and national data on registered Norwegian COVID-19 hospital admissions from March 2020 to January 2021 (n = 2300). Patient characteristics were compared, and logistic regression analysis was used to identify risk factors for antibiotic use.

RESULTS

National and local COVID-19 patients received significantly less antibiotics (53% and 49%) than influenza patients (69%, p < .001). Early antibiotics contributed to >90% of antibiotic prescriptions in the two local hospitals, and >70% of prescriptions nationally. When adjusted for age, comorbidities, symptom duration, chest X-ray infiltrates and oxygen treatment, local COVID-19 patients still had significantly lower odds of antibiotic prescription than influenza patients (aOR 0.21, 95%CI 0.09-0.50). At the national level, we observed a significant reduction in antibiotic prescription rates in the second pandemic wave compared to the first (aOR 0.35, 95% CI 0.29-0.43).

CONCLUSION

Fewer COVID-19 patients received antibiotics compared to influenza patients admitted to the two local hospitals one year earlier. The antibiotic prescription rate was lower during the second pandemic wave, possibly due to increased clinical experience and published evidence refuting the efficacy of antibiotics in treating COVID-19 pneumonia.

Co-infection of SARS-CoV-2 and influenza viruses: A systematic review and meta-analysis

We conducted this meta-analysis to determine the proportion of co-infection with influenza viruses in SARS-CoV-2 positive patients and to investigate the severity of COVID-19 in these patients. We included studies with SARS-CoV-2 infection confirmed by qRT-PCR and influenza virus infection (A and/or B) by nucleic acid tests. The proportion of co-infection was compared between children and adults, and between critically ill or deceased patients compared to overall patients. Fifty-four articles were included. The overall proportion of co-infection was 0.7%, 95%CI = [0.4 – 1.3]. Most influenza co-infections were due to the influenza A virus (74.4%). The proportion of co-infection with influenza viruses among children (3.2%, 95% CI = [0.9 – 10.9]) was significantly higher than that in adult patients (0.3%, 95% CI = [0.1 – 1.2]), p-value <0.01. The proportion of co-infection with influenza viruses among critically ill patients tended to be higher than that in overall patients (2.2%, 95% CI = [0.3 – 22.4] versus 0.6%, 95% CI = [0.3 – 1.2], respectively, p-value = 0.22). Screening for pathogens in co-infection, particularly influenza viruses in patients infected with SARS-CoV-2, is necessary. This warrants close surveillance and investigation of the co-incidences and interactions of SARS-CoV-2 and other respiratory viruses, which is facilitated by the expansion of syndromic diagnosis approaches through the use of multiplex PCR assays.

Pneumonia Caused by Severe Acute Respiratory Syndrome Coronavirus 2 and Influenza Virus: A Multicenter Comparative Study

Background

Detailed differences in clinical information between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia (CP), which is the main phenotype of SARS-CoV-2 disease, and influenza pneumonia (IP) are still unclear.

Methods

A prospective, multicenter cohort study was conducted by including patients with CP who were hospitalized between January and June 2020 and a retrospective cohort of patients with IP hospitalized from 2009 to 2020. We compared the clinical presentations and studied the prognostic factors of CP and IP.

Results

Compared with the IP group (n = 66), in the multivariate analysis, the CP group (n = 362) had a lower percentage of patients with underlying asthma or chronic obstructive pulmonary disease (P < .01), lower neutrophil-to-lymphocyte ratio (P < .01), lower systolic blood pressure (P < .01), higher diastolic blood pressure (P < .01), lower aspartate aminotransferase level (P < .05), higher serum sodium level (P < .05), and more frequent multilobar infiltrates (P < .05). The diagnostic scoring system based on these findings showed excellent differentiation between CP and IP (area under the receiver operating characteristic curve, 0.889). Moreover, the prognostic predictors were different between CP and IP.

Conclusions

Comprehensive differences between CP and IP were revealed, highlighting the need for early differentiation between these 2 pneumonias in clinical settings.

Performance of Diagnostic Model for Differentiating Between COVID-19 and Influenza: A 2-Center Retrospective Study

Background

COVID-19 and influenza share many similarities, such as mode of transmission and clinical symptoms. Failure to distinguish the 2 diseases may increase the risk of transmission. A fast and convenient differential diagnosis between COVID-19 and influenza has significant clinical value, especially for low- and middle-income countries with a shortage of nucleic acid detection kits. We aimed to establish a diagnostic model to differentiate COVID-19 and influenza based on clinical data.

Material/Methods

A total of 493 patients were enrolled in the study, including 282 with COVID-19 and 211 with influenza. All data were collected and reviewed retrospectively. The clinical and laboratory characteristics of all patients were analyzed and compared. We then randomly divided all patients into development sets and validation sets to establish a diagnostic model using multivariate logistic regression analysis. Finally, we validated the diagnostic model using the validation set.

Results

We preliminarily established a diagnostic model for differentiating COVID-19 from influenza that consisted of 5 variables: age, dry cough, fever, white cell count, and D-dimer. The model showed good performance for differential diagnosis.

Conclusions

This initial model including clinical features and laboratory indices effectively differentiated COVID-19 from influenza. Patients with a high score were at a high risk of having COVID-19, while patients with a low score were at a high risk of having influenza. This model could help clinicians quickly identify and isolate cases in the absence of nucleic acid tests, especially during the cocirculation of COVID-19 and influenza. Owing to the study’s retrospective nature, further prospective study is needed to validate the accuracy of the model.

Just a bad flu? Tackling the "infodemic" in Ireland through a comparative analysis of hospitalised cases of COVID-19 and influenza

OBJECTIVES

COVID-19 infection has been compared to seasonal influenza as an argument against non-pharmacological population-based infection control measures known as "lockdowns". Our study sought to compare disease severity measures for patients in Ireland hospitalised with COVID-19 against those hospitalised with seasonal influenza.

STUDY DESIGN

This is a retrospective population-based cohort study.

METHODS

COVID-19 hospital episodes and seasonal influenza hospital episodes were identified using relevant International Classification of Disease (ICD-10) codes from the Irish national hospitalisation dataset. The occurrences of key metrics of disease severity, length of stay, intensive care admission, ventilatory support, haemodialysis and in-hospital mortality were measured and compared between the two groups using odds ratios with 95% confidence intervals (CIs), stratified by age.

RESULTS

Hospitalised COVID-19 episodes had a mean length of stay more than twice as long as hospitalised influenza episodes (17.7 days vs 8.3 days). The likelihood of all measures of disease severity was greater in COVID-19 episodes, and the odds of in-hospital mortality were five-fold higher in this group compared with seasonal influenza episodes (OR 5.07, 95% CI 4.29-5.99, P < 0.001). Greater likelihood of increased disease severity was observed for COVID-19 episodes in most age groups.

CONCLUSIONS

COVID-19 is a more severe illness than seasonal influenza in hospitalised cohorts. It is imperative that public health professionals ensure that evidence-based advocacy is part of the response to COVID-19 to tackle a dangerous "infodemic" that can undermine public health control measures.

Asthma in Adult Patients with COVID-19. Prevalence and Risk of Severe Disease

Rationale: Health outcomes of people with coronavirus disease (COVID-19) range from no symptoms to severe illness and death. Asthma, a common chronic lung disease, has been considered likely to increase the severity of COVID-19, although data addressing this hypothesis have been scarce until very recently.Objectives: To review the epidemiologic literature related to asthma's potential role in COVID-19 severity.Methods: Studies were identified through the PubMed (MEDLINE) and medRxiv (preprint) databases using the search terms "asthma," "SARS-CoV-2" (severe acute respiratory syndrome coronavirus 2), and "COVID-19," and by cross-referencing citations in identified studies that were available in print or online before December 22, 2020.Measurements and Main Results: Asthma prevalence data were obtained from studies of people with COVID-19 and regional health statistics. We identified 150 studies worldwide that allowed us to compare the prevalence of asthma in patients with COVID-19 by region, disease severity, and mortality. The results of our analyses do not provide clear evidence of increased risk of COVID-19 diagnosis, hospitalization, severity, or mortality due to asthma.Conclusions: These findings could provide some reassurance to people with asthma regarding its potential to increase their risk of severe morbidity from COVID-19.

A Comparative Systematic Review of COVID-19 and Influenza

Background: Both SARS-CoV-2 and influenza virus share similarities such as clinical features and outcome, laboratory, and radiological findings. Methods: Literature search was done using PubMed to find MEDLINE indexed articles relevant to this study. As of 25 November 2020, the search has been conducted by combining the MeSH words “COVID-19” and “Influenza”. Results: Eighteen articles were finally selected in adult patients. Comorbidities such as cardiovascular diseases, diabetes, and obesity were significantly higher in COVID-19 patients, while pulmonary diseases and immunocompromised conditions were significantly more common in influenza patients. The incidence rates of fever, vomiting, ocular and otorhinolaryngological symptoms were found to be significantly higher in influenza patients when compared with COVID-19 patients. However, neurologic symptoms and diarrhea were statistically more frequent in COVID-19 patients. The level of white cell count and procalcitonin was significantly higher in influenza patients, whereas thrombopenia and elevated transaminases were significantly more common in COVID-19 patients. Ground-grass opacities, interlobular septal thickening, and a peripheral distribution were more common in COVID-19 patients than in influenza patients where consolidations and linear opacities were described instead. COVID-19 patients were significantly more often transferred to intensive care unit with a higher rate of mortality. Conclusions: This study estimated differences of COVID-19 and influenza patients which can help clinicians during the co-circulation of the two viruses.

COVID-19 Disease Course in Former Smokers, Smokers and COPD Patients

The severe respiratory and systemic disease named coronavirus disease-2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, the COVID-19 pandemic presents a huge social and health challenge worldwide. Many different risk factors are associated with disease severity, such as systemic arterial hypertension, diabetes mellitus, obesity, older age, and other co-infections. Other respiratory diseases such as chronic obstructive pulmonary disease (COPD) and smoking are common comorbidities worldwide. Previous investigations have identified among COVID-19 patients smokers and COPD patients, but recent investigations have questioned the higher risk among these populations. Nevertheless, previous reports failed to isolate smokers and COPD patients without other comorbidities. We performed a longitudinal evaluation of the disease course of smokers, former smokers, and COPD patients with COVID-19 without other comorbidities, from hospitalization to hospital discharge. Although no difference between groups was observed during hospital admission, smokers and COPD patients presented an increase in COVID-19-associated inflammatory markers during the disease course in comparison to non-smokers and former smokers. Our results demonstrated that smoking and COPD are risk factors for severe COVID-19 with possible implications for the ongoing pandemic.

Challenges and Adaptation of a European Influenza Vaccine Effectiveness Study Platform in Response to the COVID-19 Emergence: Experience from the DRIVE Project

The Development of Robust and Innovative Vaccine Effectiveness (DRIVE) project is a public-private partnership aiming to build capacity in Europe for yearly estimation of brand-specific influenza vaccine effectiveness (IVE). DRIVE is a five-year project funded by IMI (Innovative Medicines Initiative). It was initiated as a response to the guidance on influenza vaccines by EMA (European Medicines Agency), which advised vaccine manufacturers to work with public health institutes to set up a joint IVE study platform. The COVID-19 pandemic reached Europe in February 2020 and overlapped with the 2019/2020 influenza season only in the last weeks. However, several elements of the DRIVE study network were impacted. The pandemic specifically affected the study sites' routines and the subsequent assessment of the 2019/20 influenza season. Moreover, the current social distancing measures and lockdown policies across Europe are expected to also limit the circulation of influenza for the 2020/21 season, and therefore the impact of COVID-19 will be higher than in the season 2019/20. Consequently, DRIVE has planned to adapt its study platform to the COVID-19 challenge, encompassing several COVID-19 particularities in the study procedures, data collection and IVE analysis for the 2020/21 season. DRIVE will study the feasibility of implementing these COVID-19 components and establish the foundations of future COVID-19 vaccine effectiveness studies.

A rapid screening classifier for diagnosing COVID-19

Rationale: Coronavirus disease 2019 (COVID-19) has caused a global pandemic. A classifier combining chest X-ray (CXR) with clinical features may serve as a rapid screening approach. Methods: The study included 512 patients with COVID-19 and 106 with influenza A/B pneumonia. A deep neural network (DNN) was applied, and deep features derived from CXR and clinical findings formed fused features for diagnosis prediction. Results: The clinical features of COVID-19 and influenza showed different patterns. Patients with COVID-19 experienced less fever, more diarrhea, and more salient hypercoagulability. Classifiers constructed using the clinical features or CXR had an area under the receiver operating curve (AUC) of 0.909 and 0.919, respectively. The diagnostic efficacy of the classifier combining the clinical features and CXR was dramatically improved and the AUC was 0.952 with 91.5% sensitivity and 81.2% specificity. Moreover, combined classifier was functional in both severe and non-serve COVID-19, with an AUC of 0.971 with 96.9% sensitivity in non-severe cases, which was on par with the computed tomography (CT)-based classifier, but had relatively inferior efficacy in severe cases compared to CT. In extension, we performed a reader study involving three experienced pulmonary physicians, artificial intelligence (AI) system demonstrated superiority in turn-around time and diagnostic accuracy compared with experienced pulmonary physicians. Conclusions: The classifier constructed using clinical and CXR features is efficient, economical, and radiation safe for distinguishing COVID-19 from influenza A/B pneumonia, serving as an ideal rapid screening tool during the COVID-19 pandemic.