Comparative evaluation of clinical manifestations and risk of death in patients admitted to hospital with covid-19 and seasonal influenza: cohort study.
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SUBMITTER: Xie Y
PROVIDER: S-EPMC7735416 | biostudies-literature | 2020 Dec
REPOSITORIES: biostudies-literature
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Comparative evaluation of clinical manifestations and risk of death in patients admitted to hospital with covid-19 and seasonal influenza: cohort study.
Xie Yan Y Bowe Benjamin B Maddukuri Geetha G Al-Aly Ziyad Z
BMJ (Clinical research ed.) 20201215
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Project description:As coronavirus disease 2019 (COVID-19) crashed into the influenza season, clinical characteristics of both infectious diseases were compared to make a difference. We reported 211 COVID-19 patients and 115 influenza patients as two separate cohorts at different locations. Demographic data, medical history, laboratory findings, and radiological characters were summarized and compared between two cohorts, as well as between patients at the intensive care unit (ICU) andnon-ICU within the COVID-19 cohort. For all 326 patients, the median age was 57.0 (interquartile range: 45.0-69.0) and 48.2% was male, while 43.9% had comorbidities that included hypertension, diabetes, bronchitis, and heart diseases. Patients had cough (75.5%), fever (69.3%), expectoration (41.1%), dyspnea (19.3%), chest pain (18.7%), and fatigue (16.0%), etc. Both viral infections caused substantial blood abnormality, whereas the COVID-19 cohort showed a lower frequency of leukocytosis, neutrophilia, or lymphocytopenia, but a higher chance of creatine kinase elevation. A total of 7.7% of all patients possessed no abnormal sign in chest computed tomography (CT) scans. For both infections, pulmonary lesions in radiological findings did not show any difference in their location or distribution. Nevertheless, compared to the influenza cohort, the COVID-19 cohort presented more diversity in CT features, where certain specific CT patterns showed significantly more frequency, including consolidation, crazy paving pattern, rounded opacities, air bronchogram, tree-in-bud sign, interlobular septal thickening, and bronchiolar wall thickening. Differentiable clinical manifestations and CT patterns may help diagnose COVID-19 from influenza and gain a better understanding of both contagious respiratory illnesses.
| S-EPMC7461066 | biostudies-literature
Project description:ObjectiveTo quantify rates of organ specific dysfunction in individuals with covid-19 after discharge from hospital compared with a matched control group from the general population.DesignRetrospective cohort study.SettingNHS hospitals in England.Participants47 780 individuals (mean age 65, 55% men) in hospital with covid-19 and discharged alive by 31 August 2020, exactly matched to controls from a pool of about 50 million people in England for personal and clinical characteristics from 10 years of electronic health records.Main outcome measuresRates of hospital readmission (or any admission for controls), all cause mortality, and diagnoses of respiratory, cardiovascular, metabolic, kidney, and liver diseases until 30 September 2020. Variations in rate ratios by age, sex, and ethnicity.ResultsOver a mean follow-up of 140 days, nearly a third of individuals who were discharged from hospital after acute covid-19 were readmitted (14 060 of 47 780) and more than 1 in 10 (5875) died after discharge, with these events occurring at rates four and eight times greater, respectively, than in the matched control group. Rates of respiratory disease (P<0.001), diabetes (P<0.001), and cardiovascular disease (P<0.001) were also significantly raised in patients with covid-19, with 770 (95% confidence interval 758 to 783), 127 (122 to 132), and 126 (121 to 131) diagnoses per 1000 person years, respectively. Rate ratios were greater for individuals aged less than 70 than for those aged 70 or older, and in ethnic minority groups compared with the white population, with the largest differences seen for respiratory disease (10.5 (95% confidence interval 9.7 to 11.4) for age less than 70 years v 4.6 (4.3 to 4.8) for age ≥70, and 11.4 (9.8 to 13.3) for non-white v 5.2 (5.0 to 5.5) for white individuals).ConclusionsIndividuals discharged from hospital after covid-19 had increased rates of multiorgan dysfunction compared with the expected risk in the general population. The increase in risk was not confined to the elderly and was not uniform across ethnicities. The diagnosis, treatment, and prevention of post-covid syndrome requires integrated rather than organ or disease specific approaches, and urgent research is needed to establish the risk factors.
| S-EPMC8010267 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (COVID-19) is often compared with seasonal influenza and the two diseases have similarities, including the risk of systemic manifestations such as AKI. The aim of this study was to perform a comparative analysis of the prevalence, risk factors, and outcomes of AKI in patients who were hospitalized with COVID-19 and influenza.MethodsRetrospective cohort study of patients who were hospitalized with COVID-19 (n=325) or seasonal influenza (n=433). AKI was defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Baseline characteristics and hospitalization data were collected, and multivariable analysis was performed to determine the independent predictors for AKI.ResultsAKI occurred in 33% of COVID-19 hospitalizations (COV-AKI) and 33% of influenza hospitalizations (FLU-AKI). After adjusting for age, sex, and comorbidity count, the risk of stage 3 AKI was significantly higher in COV-AKI (OR, 3.46; 95% CI, 1.63 to 7.37). Pre-existing CKD was associated with a six- to seven-fold increased likelihood for FLU-AKI and COV-AKI. Mechanical ventilation was associated with a higher likelihood of developing AKI in the COVID-19 cohort (OR, 5.85; 95% CI, 2.30 to 15.63). Black race, after adjustment for comorbidities, was an independent risk for COV-AKI.ConclusionsPre-existing CKD was a major risk factor for AKI in both cohorts. Black race (independent of comorbidities) and mechanical ventilation were associated with a higher risk of developing COV-AKI, which is characterized by a higher burden of stage 3 AKI and overall poorer prognosis.
| S-EPMC8791326 | biostudies-literature
Project description:BackgroundIn the future, co-circulation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses A/B is likely. From a clinical point of view, differentiation of the two disease entities is crucial for patient management. We therefore aim to detect clinical differences between Coronavirus Disease 2019 (COVID-19) and seasonal influenza patients at time of hospital admission.MethodsIn this single-center observational study, we included all consecutive patients hospitalized for COVID-19 or influenza between November 2019 and May 2020. Data were extracted from a nationwide surveillance program and from electronic health records. COVID-19 and influenza patients were compared in terms of baseline characteristics, clinical presentation and outcome. We used recursive partitioning to generate a classification tree to discriminate COVID-19 from influenza patients.ResultsWe included 96 COVID-19 and 96 influenza patients. Median age was 68 vs. 70 years (p = 0.90), 72% vs. 56% (p = 0.024) were males, and median Charlson Comorbidity Index (CCI) was 1 vs. 2 (p = 0.027) in COVID-19 and influenza patients, respectively. Time from symptom onset to hospital admission was longer for COVID-19 (median 7 days, IQR 3-10) than for influenza patients (median 3 days, IQR 2-5, p < 0.001). Other variables favoring a diagnosis of COVID-19 in the classification tree were higher systolic blood pressure, lack of productive sputum, and lack of headache. The tree classified 86/192 patients (45%) into two subsets with ≥80% of patients having influenza or COVID-19, respectively. In-hospital mortality was higher for COVID-19 patients (16% vs. 5%, p = 0.018).ConclusionDiscriminating COVID-19 from influenza patients based on clinical presentation is challenging. Time from symptom onset to hospital admission is considerably longer in COVID-19 than in influenza patients and showed the strongest discriminatory power in our classification tree. Although they had fewer comorbidities, in-hospital mortality was higher for COVID-19 patients.
| S-EPMC7968573 | biostudies-literature
Project description:The aim of this study was to gain insights into the epidemiology, spatial trends, spatial structure evolution, and spatiotemporal aggregation characteristics of influenza epidemics during seasonal influenza and COVID-19 pandemic in Fuzhou from 2013 to 2022. Utilizing influenza case report data from Fuzhou spanning 2013 to 2022, we applied descriptive epidemiological methods to analyze the epidemiological characteristics and distribution patterns of reported influenza cases across various time periods, populations, and regions. Furthermore, we employed trend-surface analysis, kernel density estimation, and space-time scanning statistics to investigate the evolution of spatial trends, changes in spatial structure, and the spatiotemporal aggregation characteristics of the reported influenza incidence rate at the county level. A total of 19,135 influenza cases were reported in Fuzhou during the period of 2013-2022. The male-to-female ratio of cases was 1.31:1. The age group most affected by influenza was 0-19 years, accounting for 13,600 cases (71.07%), and the occupations mostly affected were children in the diaspora (6,570 cases, 34.33%), students (4,402 cases, 23.00%), and preschool children (2,595 cases, 13.56%). Areas with a high number of reported influenza cases were mainly located in the central part of Fuzhou City. On the overall trend of Fuzhou, the reported incidence rate of influenza exhibits a spatial trend characterized by a "high in the middle" pattern. Its spatial structure has evolved from a "triple nucleus - double nucleus" configuration and demonstrates the contraction trend of "clustering in the central urban area". Simultaneously, the spatial structure has transitioned from a "triple nucleus" to a "double nucleus" pattern, reflecting a trend of contraction towards "central city clustering." The results of space-time scanning identified Class I clusters of influenza cases in the Gulou and Jinan districts (RR = 47.99, LLR = 6917.94, P < 0.01), predominantly occurring during June and July 2022. The average annual reported incidence of influenza in Fuzhou was notably higher during the COVID-19 pandemic than the levels recorded during seasonal influenza outbreaks. Additionally, the concentration of influenza cases in central Fuzhou reflects a significant degree of spatiotemporal clustering of the epidemic.
| S-EPMC11904194 | biostudies-literature
Project description:BackgroundProcalcitonin is a biomarker that may be able to identify patients with COVID-19 pneumonia who do not require antimicrobials for bacterial respiratory tract co-infections.ObjectivesTo evaluate the safety and effectiveness of a procalcitonin-guided algorithm in rationalizing empirical antimicrobial prescriptions in non-critically ill patients with COVID-19 pneumonia.MethodsRetrospective, single-site, cohort study in adults hospitalized with confirmed or suspected COVID-19 pneumonia and receiving empirical antimicrobials for potential bacterial respiratory tract co-infection. Regression models were used to compare the following outcomes in patients with and without procalcitonin testing within 72 h of starting antimicrobials: antimicrobial consumption (DDD); antimicrobial duration; a composite safety outcome of death, admission to HDU/ICU or readmission to hospital within 30 days; and length of admission. Procalcitonin levels of ≤0.25 ng/L were interpreted as negatively predictive of bacterial co-infection. Effects were expressed as ratios of means (ROM) or prevalence ratios (PR) accordingly.Results259 patients were included in the final analysis. Antimicrobial use was lower in patients who had procalcitonin measured within 72 h of starting antimicrobials: mean antimicrobial duration 4.4 versus 5.4 days, adjusted ROM 0.7 (95% CI 0.6-0.9); mean antimicrobial consumption 6.8 versus 8.4 DDD, adjusted ROM 0.7 (95% CI 0.6-0.8). Both groups had similar composite safety outcomes (adjusted PR 0.9; 95% CI 0.6-1.3) and lengths of admission (adjusted ROM 1.3; 95% CI 0.9-1.6).ConclusionsA procalcitonin-guided algorithm may allow for the safe reduction of antimicrobial usage in hospitalized non-critically ill patients with COVID-19 pneumonia.
| S-EPMC8378277 | biostudies-literature
Project description:ObjectiveTo examine whether acute dysglycaemia predicts death in people admitted to hospital with community acquired pneumonia.DesignMulticentre prospective cohort study.SettingHospitals and private practices in Germany, Switzerland, and Austria.Participants6891 patients with community acquired pneumonia included in the German community acquired pneumonia competence network (CAPNETZ) study between 2003 and 2009.Main outcome measuresUnivariable and multivariable hazard ratios adjusted for sex, age, current smoking status, severity of community acquired pneumonia using the CRB-65 score (confusion, respiratory rate >30/min, systolic blood pressure ≤ 90 mm Hg or diastolic blood pressure ≤ 60 mm Hg, and age ≥ 65 years), and various comorbidities for death at 28, 90, and 180 days according to serum glucose levels on admission.ResultsAn increased serum glucose level at admission to hospital in participants with community acquired pneumonia and no pre-existing diabetes was a predictor of death at 28 and 90 days. Compared with participants with normal serum glucose levels on admission, those with mild acute hyperglycaemia (serum glucose concentration 6-10.99 mmol/L) had a significantly increased risk of death at 90 days (1.56, 95% confidence interval 1.22 to 2.01; P<0.001), and this risk increased to 2.37 (1.62 to 3.46; P<0.001) when serum glucose concentrations were ≥ 14 mmol/L. In sensitivity analyses the predictive value of serum glucose levels on admission for death was confirmed at 28 days and 90 days. Patients with pre-existing diabetes had a significantly increased overall mortality compared with those without diabetes (crude hazard ratio 2.47, 95% confidence interval 2.05 to 2.98; P<0.001). This outcome was not significantly affected by serum glucose levels on admission (P = 0.18 for interaction).ConclusionsSerum glucose levels on admission to hospital can predict death in patients with community acquired pneumonia without pre-existing diabetes. Acute hyperglycaemia may therefore identify patients in need of intensified care to reduce the risk of death from community acquired pneumonia.
| S-EPMC3362658 | biostudies-literature
Project description:BackgroundCOVID-19 can induce a hyperinflammatory state, which might lead to poor clinical outcomes. We aimed to assess whether patients with a systemic rheumatic disease might be at increased risk for hyperinflammation and respiratory failure from COVID-19.MethodsWe did a retrospective, comparative cohort study of patients aged 18 years or older admitted to hospital with PCR-confirmed COVID-19 at Mass General Brigham (Boston, USA). We identified patients by a search of electronic health records and matched patients with a systemic rheumatic disease 1:5 to comparators. We compared individual laboratory results by case status and extracted laboratory results and COVID-19 outcomes for each participant. We calculated the COVID-19-associated hyperinflammation score (cHIS), a composite of six domains (a score of ≥2 indicating hyperinflammation) and used logistic regression to estimate odds ratios (ORs) for COVID-19 outcomes by hyperinflammation and case status.FindingsWe identified 57 patients with a systemic rheumatic disease and 232 matched comparators who were admitted to hospital with COVID-19 between Jan 30 and July 7, 2020; 38 (67%) patients with a rheumatic disease were female compared with 158 (68%) matched comparators. Patients with a systemic rheumatic disease had higher peak median neutrophil-to-lymphocyte ratio (9·6 [IQR 6·4-22·2] vs 7·8 [4·5-16·5]; p=0·021), lactate dehydrogenase concentration (421 U/L [297-528] vs 345 U/L [254-479]; p=0·044), creatinine concentration (1·2 mg/dL [0·9-2·0] vs 1·0 mg/dL [0·8-1·4], p=0·014), and blood urea nitrogen concentration (31 mg/dL [15-61] vs 23 mg/dL [13-37]; p=0·033) than comparators, but median C-reactive protein concentration (149·4 mg/L [76·4-275·3] vs 116·3 mg/L [58·8-225·9]; p=0·11) was not significantly different. Patients with a systemic rheumatic disease had higher peak median cHIS than comparators (3 [1-5] vs 2 [1-4]; p=0·013). All patients with a peak cHIS of 2 or more had higher odds of admission to intensive care (OR 3·45 [95% CI 1·98-5·99]), mechanical ventilation (66·20 [8·98-487·80]), and in-hospital mortality (16·37 [4·75-56·38]) than patients with a peak cHIS of less than 2. In adjusted analyses, patients with a rheumatic disease had higher odds of admission to intensive care (2·08 [1·09-3·96]) and mechanical ventilation (2·60 [1·32-5·12]) than comparators, but not in-hospital mortality (1.78 [0·79-4·02]). Among patients who were discharged from hospital, risk of rehospitalisation (1·08 [0·37-3·16]) and mortality within 60 days (1·20 [0·58-2·47]) was similar in patients and comparators.InterpretationPatients with a systemic rheumatic disease who were admitted to hospital for COVID-19 had increased risk for hyperinflammation, kidney injury, admission to intensive care, and mechanical ventilation compared with matched comparators. However, among patients who survived, post-discharge outcomes were not significantly different. The cHIS identified patients with hyperinflammation, which was strongly associated with poor COVID-19 outcomes in both patients with a rheumatic disease and comparators. Clinicians should be aware that patients with systemic rheumatic diseases and COVID-19 could be susceptible to hyperinflammation and poor hospital outcomes.FundingNone.
| S-EPMC8163294 | biostudies-literature
Project description:IntroductionCurrently, COVID-19 contributes to mortality and morbidity in developed as well as in developing countries since December 2019. However, there is scarcity of evidence regarding the incidence and predictors of death among patients admitted with COVID-19 in developing country including Ethiopia, where the numbers of deaths are under-reported. Hence, this study aimed to assess the incidence and predictors of death among patients admitted with COVID-19 in Wollega University Referral Hospital (WURH), western Ethiopia.MethodsAn institution based retrospective cohort study design was conducted among 318 patients admitted with COVID-19 in WURH treatment center. Patients who were tested positive for COVID-19 by using rRT-PCR test and admitted with the diagnosis of severe COVID-19 cases from September 30, 2020 to June 10, 2021 were a source population. Epidata version 3.2 was used for data entry, and STATA version 14 for analysis. A Cox proportional hazard regression analysis was used to determine factors associated with mortality from COVID-19. Multivariable Cox regression model with 95% CI and Adjusted Hazard Ratio (AHR) was used to identify a significant predictor of mortality from COVID-19 at p-value < 0.05.ResultsA total of 318 patients were included in final analysis with mean age of 44 (SD±16.7) years and about two third (67.9%) were males. More than half (55.7%) of patients had no comorbidity on admission. The majority, 259 (81.45%) of patients recovered from COVID-19 and 267 (84%) of patients were censored at the end of follow up. The incidence rate of mortality was 14.1 per/1000 (95%CI: 10.7, 18.5) person days observation. Age ≥ 59 years (AHR: 5.76, 95%CI: 2.58, 12.84), low oxygen saturation (AHR: 2.34, 95% CI: (2.34, 4.17), and delayed presentation (AHR: 5.60, 95%CI: 2.97, 10.56) were independent predictors of mortality among COVID-19 patients.ConclusionThe mortality rate of COVID-19 pandemic was high in the study area, and most of death was happened during the first 10 days. Being old age, low oxygen saturation and delayed presentation were factors which predict mortality due to COVID-19. Hence, strengthening the health care delivery system to satisfy the need of the patients should get due attention to reduce the incidence of mortality from COVID-19 cases.
| S-EPMC9328505 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread around the world. However, approaches to distinguish COVID-19 from pneumonia caused by other pathogens have not yet been reported. We retrospectively analyzed the clinical data of 97 children with probable COVID-19. A total of 13 (13.4%) patients were confirmed positive for SARS-CoV-2 infection by nucleic acid RT-PCR testing, and 41 (42.3%) patients were found to be infected with other pathogens. Notably, no pathogen was detected in 43 (44.3%) patients. Among all patients, 25 (25.8%) had familial cluster exposure history, and 52 (53.6%) had one or more coexisting conditions. Fifteen (15.5%) patients were admitted or transferred to the PICU. In the 11 confirmed COVID-19 cases, 5 (45.5%) and 7 (63.6%) were positive for IgM and IgG against SARS-CoV-2, respectively. In 22 patients with suspected COVID-19, 1 (4.5%) was positive for IgG but negative for IgM. The most frequently detected pathogen was Mycoplasma pneumonia (29, 29.9%). One patient with confirmed COVID-19 died. Our results strongly indicated that the detection of asymptomatic COVID-19 or coexisting conditions must be strengthened in pediatric patients. These cases may be difficult to diagnose as COVID-19 unless etiologic analysis is conducted. A serologic test can be a useful adjunctive diagnostic tool in cases where SARS-CoV-2 infection is highly suspected but the nucleic acid test is negative.
| S-EPMC7587538 | biostudies-literature