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Author

Wenhua Liang

Other affiliations: Sun Yat-sen University
Bio: Wenhua Liang is a academic researcher from Guangzhou Medical University. The author has contributed to research in topic(s): Lung cancer & Survival rate. The author has an hindex of 38, co-authored 234 publication(s) receiving 29620 citation(s). Previous affiliations of Wenhua Liang include Sun Yat-sen University.

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Papers
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Open accessJournal ArticleDOI: 10.1056/NEJMOA2002032
Wei-jie Guan1, Zhengyi Ni1, Yu Hu1, Wenhua Liang1  +33 moreInstitutions (1)
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...

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16,855 Citations


Open accessJournal ArticleDOI: 10.1016/S1470-2045(20)30096-6
Wenhua Liang1, Wei-jie Guan1, Ruchong Chen1, Wei Wang1  +8 moreInstitutions (1)
01 Mar 2020-Lancet Oncology

2,594 Citations


Open accessJournal ArticleDOI: 10.1183/13993003.00547-2020
Wei Jie Guan1, Wenhua Liang1, Yi Zhao1, Heng Rui Liang1  +43 moreInstitutions (7)
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 coronavirus disease 2019 (Covid-19) by stratifying the comorbidity status. Methods We analysed the data from 1590 laboratory-confirmed hospitalised patients 575 hospitals in 31 province/autonomous regions/provincial municipalities across mainland China between December 11th, 2019 and January 31st, 2020. We analyse the composite endpoints, which consisted of admission to intensive care unit, or invasive ventilation, or death. The risk of reaching to the composite endpoints was compared according to the presence and number of comorbidities. Results The mean age was 48.9 years. 686 patients (42.7%) were females. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached to the composite endpoints. 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 [hazards ratio (HR) 2.681, 95% confidence interval (95%CI) 1.424–5.048], diabetes (HR 1.59, 95%CI 1.03–2.45), hypertension (HR 1.58, 95%CI 1.07–2.32) and malignancy (HR 3.50, 95%CI 1.60–7.64) were risk factors of reaching to the composite endpoints. The HR was 1.79 (95%CI 1.16–2.77) among patients with at least one comorbidity and 2.59 (95%CI 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.

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Topics: Comorbidity (58%), Hazard ratio (50%)

2,029 Citations


Open accessPosted ContentDOI: 10.1101/2020.02.06.20020974
Wei-jie Guan1, Zhengyi Ni1, Yu Hu2, Wenhua Liang1  +33 moreInstitutions (12)
09 Feb 2020-medRxiv
Abstract: Background Since December 2019, acute respiratory disease (ARD) due to 2019 novel coronavirus (2019-nCoV) emerged in Wuhan city and rapidly spread throughout China. We sought to delineate the clinical characteristics of these cases. Methods We extracted the data on 1,099 patients with laboratory-confirmed 2019-nCoV ARD from 552 hospitals in 31 provinces/provincial municipalities through January 29th, 2020. Results The median age was 47.0 years, and 41.90% were females. Only 1.18% of patients had a direct contact with wildlife, whereas 31.30% had been to Wuhan and 71.80% had contacted with people from Wuhan. Fever (87.9%) and cough (67.7%) were the most common symptoms. Diarrhea is uncommon. The median incubation period was 3.0 days (range, 0 to 24.0 days). On admission, ground-glass opacity was the typical radiological finding on chest computed tomography (50.00%). Significantly more severe cases were diagnosed by symptoms plus reverse-transcriptase polymerase-chain-reaction without abnormal radiological findings than non-severe cases (23.87% vs. 5.20%, P Conclusions The 2019-nCoV epidemic spreads rapidly by human-to-human transmission. Normal radiologic findings are present among some patients with 2019-nCoV infection. The disease severity (including oxygen saturation, respiratory rate, blood leukocyte/lymphocyte count and chest X-ray/CT manifestations) predict poor clinical outcomes.

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1,239 Citations


Open accessJournal ArticleDOI: 10.21037/JTD.2020.02.64
Zifeng Yang1, Zifeng Yang2, Zhiqi Zeng1, Ke Wang  +25 moreInstitutions (4)
Abstract: Background: The coronavirus disease 2019 (COVID-19) outbreak originating in Wuhan, Hubei province, China, coincided with chunyun, the period of mass migration for the annual Spring Festival. To contain its spread, China adopted unprecedented nationwide interventions on January 23 2020. These policies included large-scale quarantine, strict controls on travel and extensive monitoring of suspected cases. However, it is unknown whether these policies have had an impact on the epidemic. We sought to show how these control measures impacted the containment of the epidemic. Methods: We integrated population migration data before and after January 23 and most updated COVID-19 epidemiological data into the Susceptible-Exposed-Infectious-Removed (SEIR) model to derive the epidemic curve. We also used an artificial intelligence (AI) approach, trained on the 2003 SARS data, to predict the epidemic. Results: We found that the epidemic of China should peak by late February, showing gradual decline by end of April. A five-day delay in implementation would have increased epidemic size in mainland China three-fold. Lifting the Hubei quarantine would lead to a second epidemic peak in Hubei province in mid-March and extend the epidemic to late April, a result corroborated by the machine learning prediction. Conclusions: Our dynamic SEIR model was effective in predicting the COVID-19 epidemic peaks and sizes. The implementation of control measures on January 23 2020 was indispensable in reducing the eventual COVID-19 epidemic size.

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771 Citations


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Open accessJournal ArticleDOI: 10.1148/RADIOL.2020200642
Tao Ai1, Zhenlu Yang, Hongyan Hou2, Chenao Zhan1  +5 moreInstitutions (2)
26 Feb 2020-Radiology
Abstract: Chest CT had higher sensitivity for diagnosis of COVID-19 as compared with initial reverse-transcription polymerase chain reaction from swab samples in the epidemic area of China.

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3,596 Citations


Open accessJournal ArticleDOI: 10.1001/JAMANEUROL.2020.1127
Ling Mao1, Huijuan Jin1, Mengdie Wang1, Yu Hu1  +9 moreInstitutions (2)
01 Jan 2020-JAMA Neurology
Abstract: Importance The outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, is serious and has the potential to become an epidemic worldwide. Several studies have described typical clinical manifestations including fever, cough, diarrhea, and fatigue. However, to our knowledge, it has not been reported that patients with COVID-19 had any neurologic manifestations. Objective To study the neurologic manifestations of patients with COVID-19. Design, Setting, and Participants This is a retrospective, observational case series. Data were collected from January 16, 2020, to February 19, 2020, at 3 designated special care centers for COVID-19 (Main District, West Branch, and Tumor Center) of the Union Hospital of Huazhong University of Science and Technology in Wuhan, China. The study included 214 consecutive hospitalized patients with laboratory-confirmed diagnosis of severe acute respiratory syndrome coronavirus 2 infection. Main Outcomes and Measures Clinical data were extracted from electronic medical records, and data of all neurologic symptoms were checked by 2 trained neurologists. Neurologic manifestations fell into 3 categories: central nervous system manifestations (dizziness, headache, impaired consciousness, acute cerebrovascular disease, ataxia, and seizure), peripheral nervous system manifestations (taste impairment, smell impairment, vision impairment, and nerve pain), and skeletal muscular injury manifestations. Results Of 214 patients (mean [SD] age, 52.7 [15.5] years; 87 men [40.7%]) with COVID-19, 126 patients (58.9%) had nonsevere infection and 88 patients (41.1%) had severe infection according to their respiratory status. Overall, 78 patients (36.4%) had neurologic manifestations. Compared with patients with nonsevere infection, patients with severe infection were older, had more underlying disorders, especially hypertension, and showed fewer typical symptoms of COVID-19, such as fever and cough. Patients with more severe infection had neurologic manifestations, such as acute cerebrovascular diseases (5 [5.7%] vs 1 [0.8%]), impaired consciousness (13 [14.8%] vs 3 [2.4%]), and skeletal muscle injury (17 [19.3%] vs 6 [4.8%]). Conclusions and Relevance Patients with COVID-19 commonly have neurologic manifestations. During the epidemic period of COVID-19, when seeing patients with neurologic manifestations, clinicians should suspect severe acute respiratory syndrome coronavirus 2 infection as a differential diagnosis to avoid delayed diagnosis or misdiagnosis and lose the chance to treat and prevent further transmission.

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3,518 Citations


Open accessJournal ArticleDOI: 10.1001/JAMA.2020.5394
28 Apr 2020-JAMA
Abstract: Importance In December 2019, a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) emerged in China and has spread globally, creating a pandemic. Information about the clinical characteristics of infected patients who require intensive care is limited. Objective To characterize patients with coronavirus disease 2019 (COVID-19) requiring treatment in an intensive care unit (ICU) in the Lombardy region of Italy. Design, Setting, and Participants Retrospective case series of 1591 consecutive patients with laboratory-confirmed COVID-19 referred for ICU admission to the coordinator center (Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy) of the COVID-19 Lombardy ICU Network and treated at one of the ICUs of the 72 hospitals in this network between February 20 and March 18, 2020. Date of final follow-up was March 25, 2020. Exposures SARS-CoV-2 infection confirmed by real-time reverse transcriptase–polymerase chain reaction (RT-PCR) assay of nasal and pharyngeal swabs. Main Outcomes and Measures Demographic and clinical data were collected, including data on clinical management, respiratory failure, and patient mortality. Data were recorded by the coordinator center on an electronic worksheet during telephone calls by the staff of the COVID-19 Lombardy ICU Network. Results Of the 1591 patients included in the study, the median (IQR) age was 63 (56-70) years and 1304 (82%) were male. Of the 1043 patients with available data, 709 (68%) had at least 1 comorbidity and 509 (49%) had hypertension. Among 1300 patients with available respiratory support data, 1287 (99% [95% CI, 98%-99%]) needed respiratory support, including 1150 (88% [95% CI, 87%-90%]) who received mechanical ventilation and 137 (11% [95% CI, 9%-12%]) who received noninvasive ventilation. The median positive end-expiratory pressure (PEEP) was 14 (IQR, 12-16) cm H2O, and Fio2was greater than 50% in 89% of patients. The median Pao2/Fio2was 160 (IQR, 114-220). The median PEEP level was not different between younger patients (n = 503 aged ≤63 years) and older patients (n = 514 aged ≥64 years) (14 [IQR, 12-15] vs 14 [IQR, 12-16] cm H2O, respectively; median difference, 0 [95% CI, 0-0];P = .94). Median Fio2was lower in younger patients: 60% (IQR, 50%-80%) vs 70% (IQR, 50%-80%) (median difference, −10% [95% CI, −14% to 6%];P = .006), and median Pao2/Fio2was higher in younger patients: 163.5 (IQR, 120-230) vs 156 (IQR, 110-205) (median difference, 7 [95% CI, −8 to 22];P = .02). Patients with hypertension (n = 509) were older than those without hypertension (n = 526) (median [IQR] age, 66 years [60-72] vs 62 years [54-68];P Conclusions and Relevance In this case series of critically ill patients with laboratory-confirmed COVID-19 admitted to ICUs in Lombardy, Italy, the majority were older men, a large proportion required mechanical ventilation and high levels of PEEP, and ICU mortality was 26%.

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Topics: Intensive care (53%)

3,154 Citations


Open accessJournal ArticleDOI: 10.1016/J.IJANTIMICAG.2020.105924
Chih-Cheng Lai, Tzu Ping Shih, Wen Chien Ko1, Hung-Jen Tang  +1 moreInstitutions (2)
Abstract: The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; previously provisionally named 2019 novel coronavirus or 2019-nCoV) disease (COVID-19) in China at the end of 2019 has caused a large global outbreak and is a major public health issue. As of 11 February 2020, data from the World Health Organization (WHO) have shown that more than 43 000 confirmed cases have been identified in 28 countries/regions, with >99% of cases being detected in China. On 30 January 2020, the WHO declared COVID-19 as the sixth public health emergency of international concern. SARS-CoV-2 is closely related to two bat-derived severe acute respiratory syndrome-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21. It is spread by human-to-human transmission via droplets or direct contact, and infection has been estimated to have mean incubation period of 6.4 days and a basic reproduction number of 2.24-3.58. Among patients with pneumonia caused by SARS-CoV-2 (novel coronavirus pneumonia or Wuhan pneumonia), fever was the most common symptom, followed by cough. Bilateral lung involvement with ground-glass opacity was the most common finding from computed tomography images of the chest. The one case of SARS-CoV-2 pneumonia in the USA is responding well to remdesivir, which is now undergoing a clinical trial in China. Currently, controlling infection to prevent the spread of SARS-CoV-2 is the primary intervention being used. However, public health authorities should keep monitoring the situation closely, as the more we can learn about this novel virus and its associated outbreak, the better we can respond.

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Topics: Pneumonia (59%), Outbreak (50%)

3,083 Citations


Book ChapterDOI: 10.1007/978-0-387-78665-0_6445
01 Jan 2010-

3,037 Citations


Performance
Metrics

Author's H-index: 38

No. of papers from the Author in previous years
YearPapers
202149
202057
201927
201818
201712
201618

Top Attributes

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Author's top 5 most impactful journals

Journal of Thoracic Disease

31 papers, 1.1K citations

Translational lung cancer research

23 papers, 104 citations

Annals of Translational Medicine

18 papers, 37 citations

PLOS ONE

10 papers, 328 citations

Journal of Clinical Oncology

8 papers, 587 citations

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