scholarly journals Differences in the clinical characteristics and outcomes of COVID-19 patients in the epicenter and peripheral areas of the pandemic from China: a retrospective, large-sample, comparative analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Gang Wang ◽  
◽  
Feng Ming Luo ◽  
Dan Liu ◽  
Jia Sheng Liu ◽  
...  
Keyword(s):  
Clinical Characteristics ◽  
Lower Airway ◽  
Limited Information ◽  
Illness Onset ◽  
Icu Admission ◽  
Risk Of Death ◽  
Airway Symptoms ◽  
Peripheral Area ◽  
Prolonged Duration ◽  
Peripheral Areas

Abstract Background There is limited information on the difference in epidemiology, clinical characteristics and outcomes of the initial outbreak of the coronavirus disease (COVID-19) in Wuhan (the epicenter) and Sichuan (the peripheral area) in the early phase of the COVID-19 pandemic. This study was conducted to investigate the differences in the epidemiological and clinical characteristics of patients with COVID-19 between the epicenter and peripheral areas of pandemic and thereby generate information that would be potentially helpful in formulating clinical practice recommendations to tackle the COVID-19 pandemic. Methods The Sichuan & Wuhan Collaboration Research Group for COVID-19 established two retrospective cohorts that separately reflect the epicenter and peripheral area during the early pandemic. The epidemiology, clinical characteristics and outcomes of patients in the two groups were compared. Multivariate regression analyses were used to estimate the adjusted odds ratios (aOR) with regard to the outcomes. Results The Wuhan (epicenter) cohort included 710 randomly selected patients, and the peripheral (Sichuan) cohort included 474 consecutive patients. A higher proportion of patients from the periphery had upper airway symptoms, whereas a lower proportion of patients in the epicenter had lower airway symptoms and comorbidities. Patients in the epicenter had a higher risk of death (aOR=7.64), intensive care unit (ICU) admission (aOR=1.66), delayed time from illness onset to hospital and ICU admission (aOR=6.29 and aOR=8.03, respectively), and prolonged duration of viral shedding (aOR=1.64). Conclusions The worse outcomes in the epicenter could be explained by the prolonged time from illness onset to hospital and ICU admission. This could potentially have been associated with elevated systemic inflammation secondary to organ dysfunction and prolonged duration of virus shedding independent of age and comorbidities. Thus, early supportive care could achieve better clinical outcomes.

scholarly journals Differences in the clinical characteristics and outcomes of COVID-19 patients in the epicenter and peripheral areas of the pandemic from China: a retrospective, large-sample, comparative analysis

2020 ◽  
Author(s):  
Gang Wang ◽  
Feng Ming Luo ◽  
Dan Liu ◽  
Jia Shen Liu ◽  
Ye Wang ◽  
...  
Keyword(s):  
Clinical Characteristics ◽  
Lower Airway ◽  
Limited Information ◽  
Illness Onset ◽  
Icu Admission ◽  
Risk Of Death ◽  
Airway Symptoms ◽  
Peripheral Area ◽  
Prolonged Duration ◽  
Peripheral Areas

Abstract Background: There is limited information on difference of epidemiology, clinical characteristics and outcomes of the initial outbreak of the coronavirus disease (COVID-19) in Wuhan (the epicenter) and Sichuan (the peripheral area) in the early phase of the COVID-19 pandemic. This study was conducted to investigate the differences in the epidemiological and clinical characteristics of patients with COVID-19 between the epicenter and peripheral areas of pandemic and thereby generate information that would be potentially helpful in formulating clinical practice recommendations to tackle the COVID-19 pandemic.Methods: The Sichuan & Wuhan Collaboration Research Group for COVID-19 established two retrospective cohorts that separately reflect the epicenter and peripheral area during the early pandemic. The epidemiology, clinical characteristics and outcomes of patients in the two groups were compared. Multivariate regression analyses were used to estimate the adjusted odds ratios (aOR) with regard to the outcomes.Results: The Wuhan (epicenter) cohort included 710 randomly selected patients, and the peripheral (Sichuan) cohort included 474 consecutive patients. A higher proportion of patients from the periphery had upper airway symptoms, whereas a lower proportion of patients in the epicenter had lower airway symptoms and comorbidities. Patients in the epicenter had a higher risk of death (aOR=7.64), intensive care unit (ICU) admission (aOR=1.66), delayed time from illness onset to hospital and ICU admission (aOR=6.29 and aOR=8.03, respectively), and prolonged duration of viral shedding (aOR=1.64). Conclusions: The worse outcomes in the epicenter could be explained by the prolonged time from illness onset to hospital and ICU admission. This could potentially have been associated with elevated systemic inflammation secondary to organ dysfunction and prolonged duration of virus shedding independent of age and comorbidities. Thus, early supportive care could achieve better clinical outcomes.

scholarly journals Differences in the clinical characteristics and outcomes of COVID-19 patients in the epicenter and peripheral areas of the pandemic from China: a retrospective, large-sample, comparative analysis

2021 ◽  
Author(s):  
Gang Wang ◽  
Feng Ming Luo ◽  
Dan Liu ◽  
Jia Sheng Liu ◽  
Ye Wang ◽  
...  
Keyword(s):  
Clinical Characteristics ◽  
Lower Airway ◽  
Limited Information ◽  
Illness Onset ◽  
Icu Admission ◽  
Risk Of Death ◽  
Airway Symptoms ◽  
Peripheral Area ◽  
Prolonged Duration ◽  
Peripheral Areas

Abstract Background: There is limited information on the difference in epidemiology, clinical characteristics and outcomes of the initial outbreak of the coronavirus disease (COVID-19) in Wuhan (the epicenter) and Sichuan (the peripheral area) in the early phase of the COVID-19 pandemic. This study was conducted to investigate the differences in the epidemiological and clinical characteristics of patients with COVID-19 between the epicenter and peripheral areas of pandemic and thereby generate information that would be potentially helpful in formulating clinical practice recommendations to tackle the COVID-19 pandemic.Methods: The Sichuan & Wuhan Collaboration Research Group for COVID-19 established two retrospective cohorts that separately reflect the epicenter and peripheral area during the early pandemic. The epidemiology, clinical characteristics and outcomes of patients in the two groups were compared. Multivariate regression analyses were used to estimate the adjusted odds ratios (aOR) with regard to the outcomes.Results: The Wuhan (epicenter) cohort included 710 randomly selected patients, and the peripheral (Sichuan) cohort included 474 consecutive patients. A higher proportion of patients from the periphery had upper airway symptoms, whereas a lower proportion of patients in the epicenter had lower airway symptoms and comorbidities. Patients in the epicenter had a higher risk of death (aOR=7.64), intensive care unit (ICU) admission (aOR=1.66), delayed time from illness onset to hospital and ICU admission (aOR=6.29 and aOR=8.03, respectively), and prolonged duration of viral shedding (aOR=1.64). Conclusions: The worse outcomes in the epicenter could be explained by the prolonged time from illness onset to hospital and ICU admission. This could potentially have been associated with elevated systemic inflammation secondary to organ dysfunction and prolonged duration of virus shedding independent of age and comorbidities. Thus, early supportive care could achieve better clinical outcomes.

scholarly journals A Head-To-Head Comparative Study of Covid-19 Patients Between Epicenter and Peripheral Areas of Pandemic From China

2020 ◽  
Author(s):  
Gang Wang ◽  
Feng Min Luo ◽  
Dan Liu ◽  
Jia Shen Liu ◽  
Ye Wang ◽  
...  
Keyword(s):  
Clinical Characteristics ◽  
Lower Airway ◽  
Virus Shedding ◽  
Illness Onset ◽  
Icu Admission ◽  
Risk Of Death ◽  
Airway Symptoms ◽  
Prolonged Duration ◽  
Peripheral Areas ◽  
Delayed Time

Abstract Background: There has been little information on difference of epidemiology, clinical characteristics and outcomes between epicenter and peripheral areas of Covid-19 pandemic. Methods: Based on Sichuan & Wuhan collaboration research group for Covid-19, we established two retrospective cohorts reflecting the epicenter and peripheral area of pandemic. Epidemiology, clinical characteristics and outcomes of patients were compared. Multivariate regression analyses were used to estimate adjusted odds ratios (aOR) to identify clinical variables associated with outcomes.Results: Upon March 12, 2020, Wuhan cohort consisted of 710 patients using random sampling, and 474 consecutive cases constituted Sichuan cohort. Sichuan cohort had more upper airway symptoms, while Wuhan cohort is elder, has more lower airway symptoms and comorbidities. Wuhan cohort had higher risk of death (aOR=7.64), ICU admission (aOR=1.66), delayed time from illness onset to hospital and ICU admission (aOR=6.29 and aOR=8.03) and prolonged duration of viral shedding (aOR=1.64). Conclusions: Worse outcomes in the epicenter would be explained by delayed time from illness onset to hospital and ICU admission associated with elevated systemic inflammation reflecting organ dysfunction and prolonged duration of virus shedding except for age and comorbidities. It indicates potentially clinical implications of Covid-19 that early supportive care would achieve better clinical outcome.

scholarly journals Cross-sectional observational study of epidemiology of COVID-19 and clinical outcomes of hospitalised patients in North West London during March and April 2020

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e044384
Author(s):  
Guduru Gopal Rao ◽  
Alexander Allen ◽  
Padmasayee Papineni ◽  
Liyang Wang ◽  
Charlotte Anderson ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Clinical Outcomes ◽  
Severe Infection ◽  
Older Age ◽  
Cross Sectional ◽  
North West ◽  
Icu Admission ◽  
Risk Of Death ◽  
Hospitalised Patients ◽  
Increased Risk

ObjectiveThe aim of this paper is to describe evolution, epidemiology and clinical outcomes of COVID-19 in subjects tested at or admitted to hospitals in North West London.DesignObservational cohort study.SettingLondon North West Healthcare NHS Trust (LNWH).ParticipantsPatients tested and/or admitted for COVID-19 at LNWH during March and April 2020Main outcome measuresDescriptive and analytical epidemiology of demographic and clinical outcomes (intensive care unit (ICU) admission, mechanical ventilation and mortality) of those who tested positive for COVID-19.ResultsThe outbreak began in the first week of March 2020 and reached a peak by the end of March and first week of April. In the study period, 6183 tests were performed in on 4981 people. Of the 2086 laboratory confirmed COVID-19 cases, 1901 were admitted to hospital. Older age group, men and those of black or Asian minority ethnic (BAME) group were predominantly affected (p<0.05). These groups also had more severe infection resulting in ICU admission and need for mechanical ventilation (p<0.05). However, in a multivariate analysis, only increasing age was independently associated with increased risk of death (p<0.05). Mortality rate was 26.9% in hospitalised patients.ConclusionThe findings confirm that men, BAME and older population were most commonly and severely affected groups. Only older age was independently associated with mortality.

The economic burden of vertigo and dizziness in the United States

2020 ◽  
pp. 1-10
Author(s):  
Jeremy S. Ruthberg ◽  
Chandruganesh Rasendran ◽  
Armine Kocharyan ◽  
Sarah E. Mowry ◽  
Todd D. Otteson
Keyword(s):  
United States ◽  
Health Care ◽  
Economic Burden ◽  
Clinical Characteristics ◽  
Care Service ◽  
Adult Population ◽  
Health Care Service ◽  
The United States ◽  
Medical Expenditures ◽  
Limited Information

BACKGROUND: Vertigo and dizziness are extremely common conditions in the adult population and therefore place a significant social and economic burden on both patients and the healthcare system. However, limited information is available for the economic burden of vertigo and dizziness across various health care settings. OBJECTIVE: Estimate the economic burden of vertigo and dizziness, controlling for demographic, socioeconomic, and clinical comorbidities. METHODS: A retrospective analysis of data from the Medical Expenditures Panel Survey (2007–2015) was performed to analyze individuals with vertigo or dizziness from a nationally representative sample of the United States. Participants were included via self-reported data and International Classification of Diseases, 9th Revision Clinical Modification codes. A cross-validated 2-component generalized linear model was utilized to assess vertigo and dizziness expenditures across demographic, socioeconomic and clinical characteristics while controlling for covariates. Costs and utilization across various health care service sectors, including inpatient, outpatient, emergency department, home health, and prescription medications were evaluated. RESULTS: Of 221,273 patients over 18 years, 5,275 (66% female, 34% male) reported either vertigo or dizziness during 2007–2015. More patients with vertigo or dizziness were female, older, non-Hispanic Caucasian, publicly insured, and had significant clinical comorbidities compared to patients without either condition. Furthermore, each of these demographic, socioeconomic, and clinical characteristics lead to significantly elevated costs due to having these conditions for patients. Significantly higher medical expenditures and utilization across various healthcare sectors were associated with vertigo or dizziness (p <  0.001). The mean incremental annual healthcare expenditure directly associated with vertigo or dizziness was $2,658.73 (95% CI: 1868.79, 3385.66) after controlling for socioeconomic and demographic characteristics. Total annual medical expenditures for patients with dizziness or vertigo was $48.1 billion. CONCLUSION: Vertigo and dizziness lead to substantial expenses for patients across various healthcare settings. Determining how to limit costs and improve the delivery of care for these patients is of the utmost importance given the severe morbidity, disruption to daily living, and major socioeconomic burden associated with these conditions.

scholarly journals Early Prediction of Seven-Day Mortality in Intensive Care Unit Using a Machine Learning Model: Results from the SPIN-UTI Project

2021 ◽  
Vol 10 (5) ◽  
pp. 992
Author(s):  
Martina Barchitta ◽  
Andrea Maugeri ◽  
Giuliana Favara ◽  
Paolo Marco Riela ◽  
Giovanni Gallo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care ◽  
Intensive Care Units ◽  
Learning Algorithm ◽  
Area Under The Curve ◽  
Support Vector ◽  
Icu Admission ◽  
Risk Of Death ◽  
Saps Ii ◽  
Svm Algorithm

Patients in intensive care units (ICUs) were at higher risk of worsen prognosis and mortality. Here, we aimed to evaluate the ability of the Simplified Acute Physiology Score (SAPS II) to predict the risk of 7-day mortality, and to test a machine learning algorithm which combines the SAPS II with additional patients’ characteristics at ICU admission. We used data from the “Italian Nosocomial Infections Surveillance in Intensive Care Units” network. Support Vector Machines (SVM) algorithm was used to classify 3782 patients according to sex, patient’s origin, type of ICU admission, non-surgical treatment for acute coronary disease, surgical intervention, SAPS II, presence of invasive devices, trauma, impaired immunity, antibiotic therapy and onset of HAI. The accuracy of SAPS II for predicting patients who died from those who did not was 69.3%, with an Area Under the Curve (AUC) of 0.678. Using the SVM algorithm, instead, we achieved an accuracy of 83.5% and AUC of 0.896. Notably, SAPS II was the variable that weighted more on the model and its removal resulted in an AUC of 0.653 and an accuracy of 68.4%. Overall, these findings suggest the present SVM model as a useful tool to early predict patients at higher risk of death at ICU admission.

scholarly journals Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Espen Jimenez-Solem ◽  
Tonny S. Petersen ◽  
Casper Hansen ◽  
Christian Hansen ◽  
Christina Lioma ◽  
...  
Keyword(s):  
Prediction Models ◽  
Severe Disease ◽  
External Validation ◽  
Area Under The Curve ◽  
Predictive Performance ◽  
Mortality Prediction ◽  
Icu Admission ◽  
Risk Of Death ◽  
Online Risk ◽  
The United Kingdom

AbstractPatients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic markers of disease progression and death. From a cohort of approx. 2.6 million citizens in Denmark, SARS-CoV-2 PCR tests were performed on subjects suspected for COVID-19 disease; 3944 cases had at least one positive test and were subjected to further analysis. SARS-CoV-2 positive cases from the United Kingdom Biobank was used for external validation. The ML models predicted the risk of death (Receiver Operation Characteristics—Area Under the Curve, ROC-AUC) of 0.906 at diagnosis, 0.818, at hospital admission and 0.721 at Intensive Care Unit (ICU) admission. Similar metrics were achieved for predicted risks of hospital and ICU admission and use of mechanical ventilation. Common risk factors, included age, body mass index and hypertension, although the top risk features shifted towards markers of shock and organ dysfunction in ICU patients. The external validation indicated fair predictive performance for mortality prediction, but suboptimal performance for predicting ICU admission. ML may be used to identify drivers of progression to more severe disease and for prognostication patients in patients with COVID-19. We provide access to an online risk calculator based on these findings.

scholarly journals 910. A Comprehensive, One Year, Hospital-Wide Snapshot of All Serious Infectious Complications in People Who Inject Drugs

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S489-S490
Author(s):  
John T Henderson ◽  
Evelyn Villacorta Cari ◽  
Nicole Leedy ◽  
Alice Thornton ◽  
Donna R Burgess ◽  
...  
Keyword(s):  
Multivariable Analysis ◽  
Vertebral Osteomyelitis ◽  
The United States ◽  
Infectious Complications ◽  
Data Set ◽  
Cumulative Impact ◽  
Mortality And Morbidity ◽  
Icu Admission ◽  
Risk Of Death ◽  
The Impact

Abstract Background There has been a dramatic rise in IV drug use (IVDU) and its associated mortality and morbidity, however, the scope of this effect has not been described. Kentucky is at the epicenter of this epidemic and is an ideal place to better understand the health complications of IVDU in order to improve outcomes. Methods All adult in-patient admissions to University of Kentucky hospitals in 2018 with an Infectious Diseases (ID) consult and an ICD 9/10 code associated with IVDU underwent thorough retrospective chart review. Demographic, descriptive, and outcome data were collected and analyzed by standard statistical analysis. Results 390 patients (467 visits) met study criteria. The top illicit substances used were methamphetamine (37.2%), heroin (38.2%), and cocaine (10.3%). While only 4.1% of tested patients were HIV+, 74.2% were HCV antibody positive. Endocarditis (41.1%), vertebral osteomyelitis (20.8%), bacteremia without endocarditis (14.1%), abscess (12.4%), and septic arthritis (10.4%) were the most common infectious complications. The in-patient death rate was 3.0%, and 32.2% of patients were readmitted within the study period. The average length of stay was 26 days. In multivariable analysis, infectious endocarditis was associated with a statistically significant increase in risk of death, ICU admission, and hospital readmission. Although not statistically significant, trends toward mortality and ICU admission were identified for patients with prior endocarditis and methadone was correlated with decreased risk of readmission and ICU stay. FIGURE 1: Reported Substances Used FIGURE 2: Comorbidities FIGURE 3: Types of Severe Infectious Complications Conclusion We report on a novel, comprehensive perspective on the serious infectious complications of IVDU in an attempt to measure its cumulative impact in an unbiased way. This preliminary analysis of a much larger dataset (2008-2019) reveals some sobering statistics about the impact of IVDU in the United States. While it confirms the well accepted mortality and morbidity associated with infective endocarditis and bacteremia, there is a significant unrecognized impact of other infectious etiologies. Additional analysis of this data set will be aimed at identifying key predictive factors in poor outcomes in hopes of mitigating them. Disclosures All Authors: No reported disclosures

scholarly journals Clinical characteristics and outcomes of people living with HIV hospitalized with COVID-19: a nationwide experience

2021 ◽  
Vol 32 (5) ◽  
pp. 435-443
Author(s):  
Maria Elena Ceballos ◽  
Patricio Ross ◽  
Martin Lasso ◽  
Isabel Dominguez ◽  
Marcela Puente ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Intensive Care ◽  
General Population ◽  
Clinical Characteristics ◽  
Cd4 Count ◽  
People Living With Hiv ◽  
Hiv Diagnosis ◽  
Hiv Viral Load ◽  
Risk Of Death ◽  
Living With Hiv

In this prospective, multicentric, observational study, we describe the clinical characteristics and outcomes of people living with HIV (PLHIV) requiring hospitalization due to COVID-19 in Chile and compare them with Chilean general population admitted with SARS-CoV-2. Consecutive PLHIV admitted with COVID-19 in 23 hospitals, between 16 April and 23 June 2020, were included. Data of a temporally matched-hospitalized general population were used to compare demography, comorbidities, COVID-19 symptoms, and major outcomes. In total, 36 PLHIV subjects were enrolled; 92% were male and mean age was 44 years. Most patients (83%) were on antiretroviral therapy; mean CD4 count was 557 cells/mm3. Suppressed HIV viremia was found in 68% and 56% had, at least, one comorbidity. Severe COVID-19 occurred in 44.4%, intensive care was required in 22.2%, and five patients died (13.9%). No differences were seen between recovered and deceased patients in CD4 count, HIV viral load, or time since HIV diagnosis. Hypertension and cardiovascular disease were associated with a higher risk of death ( p = 0.02 and 0.006, respectively). Compared with general population, the HIV cohort had significantly more men (OR 0.15; IC 95% 0.07–0.31) and younger age (OR 8.68; IC 95% 2.66–28.31). In PLHIV, we found more intensive care unit admission (OR 2.31; IC 95% 1.05–5.07) but no differences in the need for mechanical ventilation or death. In this cohort of PLHIV hospitalized with COVID-19, hypertension and cardiovascular comorbidities, but not current HIV viro-immunologic status, were the most important risk factors for mortality. No differences were found between PLHIV and general population in the need for mechanical ventilation and death.

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