Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 4 de 4
Filter
1.
N Engl J Med ; 382(18): 1708-1720, 2020 04 30.
Article in English | MEDLINE | ID: covidwho-1428982

ABSTRACT

BACKGROUND: Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. METHODS: We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. RESULTS: The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. CONCLUSIONS: During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.).


Subject(s)
Betacoronavirus , Coronavirus Infections , Disease Outbreaks , Pandemics , Pneumonia, Viral , Adolescent , Adult , Aged , COVID-19 , Child , China/epidemiology , Coronavirus Infections/complications , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/therapy , Female , Fever/etiology , Humans , Male , Middle Aged , Patient Acuity , Pneumonia, Viral/complications , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Pneumonia, Viral/therapy , SARS-CoV-2 , Young Adult
2.
Cardiovasc Diagn Ther ; 10(4): 678-686, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-792021

ABSTRACT

BACKGROUND: Cardiac injury is a common condition among hospitalized coronavirus disease 2019 (COVID-19) patients, and is associated with a higher risk of mortality. However, the mechanism of myocardial injury in COVID-19 remains unclear. In this retrospective study, we compared the clinical characteristics of COVID-19 patients with different troponin I (TnI) levels during hospitalization to provide a clinical reference for the identification of those at high-risk. METHODS: In total, 218 patients diagnosed with COVID-19 in Yichang Central People's Hospital and Yichang Third People's Hospital between January 23 and February 19, 2020 were initially included. Of these patients, 89 underwent TnI testing during hospitalization and were finally included in the study. The medical history, clinical signs and symptoms at the time of admission, and laboratory test results were recorded. The patients were assigned to the normal TnI group (TnI <0.01 µg/L; n=67) or the elevated TnI group (TnI >0.01 µg/L; n=22). RESULTS: The incidence of elevated TnI in our patient cohort was 24.7%. There were significant differences between the two groups in the following factors: history of coronary heart disease (CHD), age, lymphocyte count, prothrombin time (PT), activated partial thromboplastin time (APTT), and levels of interleukin (IL)-6, C-reactive protein (CRP), myoglobin (MYO), lactate dehydrogenase (LDH), and albumin (all P<0.05). Binary logistic analysis showed that a history of CHD, age, lymphocyte count, IL-6, APTT, and MYO were influencing factors of elevated serum TnI. CONCLUSIONS: A history of CHD, advanced age, decreased lymphocyte count, increased IL-6, increased MYO, and prolonged APTT were independent influencing factors of elevated TnI in COVID-19 patients. COVID-19 patients with these characteristics are prone to myocardial injury.

3.
Eur Respir J ; 55(6)2020 06.
Article in English | MEDLINE | ID: covidwho-622479

ABSTRACT

BACKGROUND: During the outbreak of coronavirus disease 2019 (COVID-19), consistent and considerable differences in disease severity and mortality rate of patients treated in Hubei province compared to those in other parts of China have been observed. We sought to compare the clinical characteristics and outcomes of patients being treated inside and outside Hubei province, and explore the factors underlying these differences. METHODS: Collaborating with the National Health Commission, we established a retrospective cohort to study hospitalised COVID-19 cases in China. Clinical characteristics, the rate of severe events and deaths, and the time to critical illness (invasive ventilation or intensive care unit admission or death) were compared between patients within and outside Hubei. The impact of Wuhan-related exposure (a presumed key factor that drove the severe situation in Hubei, as Wuhan is the epicentre as well the administrative centre of Hubei province) and the duration between symptom onset and admission on prognosis were also determined. RESULTS: At the data cut-off (31 January 2020), 1590 cases from 575 hospitals in 31 provincial administrative regions were collected (core cohort). The overall rate of severe cases and mortality was 16.0% and 3.2%, respectively. Patients in Hubei (predominantly with Wuhan-related exposure, 597 (92.3%) out of 647) were older (mean age 49.7 versus 44.9 years), had more cases with comorbidity (32.9% versus 19.7%), higher symptomatic burden, abnormal radiologic manifestations and, especially, a longer waiting time between symptom onset and admission (5.7 versus 4.5 days) compared with patients outside Hubei. Patients in Hubei (severe event rate 23.0% versus 11.1%, death rate 7.3% versus 0.3%, HR (95% CI) for critical illness 1.59 (1.05-2.41)) have a poorer prognosis compared with patients outside Hubei after adjusting for age and comorbidity. However, among patients outside Hubei, the duration from symptom onset to hospitalisation (mean 4.4 versus 4.7 days) and prognosis (HR (95%) 0.84 (0.40-1.80)) were similar between patients with or without Wuhan-related exposure. In the overall population, the waiting time, but neither treated in Hubei nor Wuhan-related exposure, remained an independent prognostic factor (HR (95%) 1.05 (1.01-1.08)). CONCLUSION: There were more severe cases and poorer outcomes for COVID-19 patients treated in Hubei, which might be attributed to the prolonged duration of symptom onset to hospitalisation in the epicentre. Future studies to determine the reason for delaying hospitalisation are warranted.


Subject(s)
Coronavirus Infections/mortality , Hospitalization , Pneumonia, Viral/mortality , Adult , Aged , Betacoronavirus , COVID-19 , Cardiovascular Diseases/epidemiology , China , Cohort Studies , Comorbidity , Coronavirus Infections/complications , Coronavirus Infections/diagnostic imaging , Cough/etiology , Diabetes Mellitus/epidemiology , Disease Outbreaks , Dyspnea/etiology , Fatigue/etiology , Female , Fever/etiology , Geography , Humans , Hypertension/epidemiology , Intensive Care Units/statistics & numerical data , Lung/diagnostic imaging , Male , Middle Aged , Pandemics , Pharyngitis/etiology , Pneumonia, Viral/complications , Pneumonia, Viral/diagnostic imaging , Prognosis , Proportional Hazards Models , Respiration, Artificial/statistics & numerical data , Retrospective Studies , SARS-CoV-2 , Severity of Illness Index , Time Factors , Time-to-Treatment/statistics & numerical data , Tomography, X-Ray Computed
4.
Eur Respir J ; 55(5)2020 05.
Article in English | MEDLINE | ID: covidwho-18269

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. OBJECTIVE: To evaluate the risk of serious adverse outcomes in patients with COVID-19 by stratifying the comorbidity status. METHODS: We analysed data from 1590 laboratory confirmed hospitalised patients from 575 hospitals in 31 provinces/autonomous regions/provincial municipalities across mainland China between 11 December 2019 and 31 January 2020. We analysed the composite end-points, which consisted of admission to an intensive care unit, invasive ventilation or death. The risk of reaching the composite end-points was compared according to the presence and number of comorbidities. RESULTS: The mean age was 48.9 years and 686 (42.7%) patients were female. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached the composite end-points. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD (HR (95% CI) 2.681 (1.424-5.048)), diabetes (1.59 (1.03-2.45)), hypertension (1.58 (1.07-2.32)) and malignancy (3.50 (1.60-7.64)) were risk factors of reaching the composite end-points. The hazard ratio (95% CI) was 1.79 (1.16-2.77) among patients with at least one comorbidity and 2.59 (1.61-4.17) among patients with two or more comorbidities. CONCLUSION: Among laboratory confirmed cases of COVID-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Adult , COVID-19 , China/epidemiology , Comorbidity , Coronavirus Infections/diagnosis , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/diagnosis , Prognosis , Risk Factors , SARS-CoV-2
SELECTION OF CITATIONS
SEARCH DETAIL