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R E S E A R C H A R T I C L E Open Access
Clinical characteristics of 276 hospitalized
patients with coronavirus disease 2019 in
Zengdu District, Hubei Province: a single-
center descriptive study
Yiping Wei
1†
, Weibiao Zeng
1†
, Xiangyun Huang
2
, Junyu Li
3
, Xingting Qiu
4
, Huadong Li
5
, Dinghua Liu
6
,
Zhaofeng He
7
, Wenzhong Yao
8
, Ping Huang
9
, Chao Li
10
, Min Zhu
11
, Chunlan Zhong
12
, Xingen Zhu
13†
and
Jiansheng Liu
14*
Abstract
Background: We aimed to report the epidemiological and clinical characteristics of hospitalized patients with
coronavirus disease-19 (COVID-19) in Zengdu District, Hubei Province, China.
Methods: Clinical data on COVID-19 inpatients in Zengdu Hospital from January 27 to March 11, 2020 were
collected; this is a community hospital in an area surrounding Wuhan and supported by volunteer doctors. All
hospitalized patients with COVID-19 were included in this study. The epidemiological findings, clinical features,
laboratory findings, radiologic manifestations, and clinical outcomes of these patients were analyzed. The patients
were followed up for clinical outcomes until March 22, 2020. Severe COVID-19 cases include severe and critical
cases diagnosed according to the seventh edition of China’s COVID-19 diagnostic guidelines. Severe and critical
COVID-19 cases were diagnosed according to the seventh edition of China’s COVID-19 diagnostic guidelines.
Results: All hospitalized COVID-19 patients, 276 (median age: 51.0 years), were enrolled, including 262 non-severe
and 14 severe patients. The proportion of patients aged over 60 years was higher in the severe group (78.6%) than
in the non-severe group (18.7%, p< 0.01). Approximately a quarter of the patients (24.6%) had at least one
comorbidity, such as hypertension, diabetes, or cancer, and the proportion of patients with comorbidities was
higher in the severe group (85.7%) than in the non-severe group (21.4%, p< 0.01). Common symptoms included
fever (82.2% [227/276]) and cough (78.0% [218/276]). 38.4% (106/276) of the patients had a fever at the time of
admission. Most patients (94.9% [204/276]) were cured and discharged; 3.6% (10/276) deteriorated to a critical
condition and were transferred to another hospital. The median COVID-19 treatment duration and hospital stay
were 14.0 and 18.0 days, respectively.
(Continued on next page)
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* Correspondence: gzliujs@126.com
†
Yiping Wei, Weibiao Zeng and Xingen Zhu contributed equally to this work.
14
Department of Respiratory Medicine, Ganzhou People’s Hospital, No.17
Hongqi Avenue, Ganzhou City 341000, Jiangxi Province, China
Full list of author information is available at the end of the article
Wei et al. BMC Infectious Diseases (2020) 20:549
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(Continued from previous page)
Conclusions: Most of the COVID-19 patients in Zengdu had mild disease. Older patients with underlying diseases
were at a higher risk of progression to severe disease. The length of hospital-stay and antiviral treatment duration
for COVID-19 were slightly longer than those in Wuhan. This work will contribute toward an understanding of
COVID-19 characteristics in the areas around the core COVID-19 outbreak region and serve as a reference for
decision-making for epidemic prevention and control in similar areas.
Keywords: COVID-19, SARS-CoV-2, Echocardiography, Clinical characteristics
Background
In December 2019, a series of pneumonia cases with
similar symptoms were reported in Wuhan, Hubei Prov-
ince, China [1]. That pneumonia was later named cor-
onavirus disease 2019 (COVID-19) by the World Health
Organization (WHO) [2]. The causative pathogen was
identified as a novel enveloped RNA beta coronavirus
named severe acute respiratory syndrome coronavirus 2
(SARS-CoV-2) [3]. COVID-19 is highly contagious and
spreads rapidly through human-to-human transmission
[4–6]. As of March 29, 2020, there were 81,470 con-
firmed COVID-19 cases and 3304 deaths in China, in-
cluding 67,801 confirmed cases and 3186 deaths in
Hubei Province, and 721,584 confirmed cases and 33,
958 deaths worldwide. However, many infected people
have not been counted owing to a lack of timely diagno-
sis. COVID-19 is a global pandemic. Therefore, a com-
prehensive and in-depth understanding of the
epidemiological and clinical characteristics of COVID-19
is imperative for controlling the pandemic as soon as
possible.
The number of COVID-19 cases in Wuhan was large,
the spread was fast, and the fatality rate was high. Most
of the clinical characteristics of COVID-19 have been
summarized from the samples of patients in Wuhan [7].
Controlling the epidemic in the areas around the core
COVID-19 outbreak region is an important link in
blocking the spread of the disease. The Chinese govern-
ment has enlisted many volunteer doctors to support
hospitals in these key areas. However, there are few re-
ports on the clinical characteristics of COVID-19 inpa-
tients in these areas [8,9]. Thus, this study collected
clinical data for COVID-19 inpatients in Zengdu Hos-
pital, a community hospital supported by 95 volunteer
doctors and nurses from Jiangxi Province (about 300
miles from Zengdu District). We describe the epidemi-
ology, clinical features, laboratory findings, imaging fea-
tures, and outcomes of COVID-19 inpatients in Zengdu
District, which is a 3-h drive from Wuhan City. We
hope that our work will contribute toward an under-
standing of COVID-19 characteristics in the areas
around the core COVID-19 outbreak region and provide
a decision-making reference for epidemic prevention
and control in similar areas.
Methods
Data sources
The study was approved by the institutional ethics board
of Suizhou Zengdu Hospital, which was established by
the Chinese government to treat COVID-19 patients in
Zengdu District. All the patients diagnosed with
COVID-19, according to the interim guidance from the
WHO [10], in Zengdu Hospital from January 27 to
March 11 were admitted and included in this study. The
patients were followed up for clinical outcomes until
March 22, 2020. Only laboratory-confirmed cases that
were defined as positive based on the results of high-
throughput sequencing or real-time reverse-
transcriptase–polymerase chain reaction (RT-PCR) assay
of nasal and pharyngeal swab samples were included.
These confirmatory assays for SARS-CoV-2 were per-
formed at the Suizhou CDC in accordance with the
guidelines developed by the WHO [11]. Medication and
treatment measures were selected according to the
scheme recommended in the guidelines and each pa-
tient’s condition [12].
A team of doctors who had treated these patients ex-
tracted the recent exposure history, clinical symptoms,
laboratory findings, radiologic manifestations, and clin-
ical outcomes from patients’medical records. All pa-
tients underwent at least one chest computed
tomography (CT) scan, and data were extracted after the
scans were reviewed by a dedicated imaging physician.
All laboratory tests were performed according to treat-
ment needs. The researchers obtained the outcome data
of transferred patients by contacting the hospitals that
received these patients, and also contacted the patients
by phone if anything was unclear or information neces-
sary for the study was missing from the medical record.
Study definitions
According to the national treatment guideline, COVID-
19 severity was defined as mild, moderate, severe, or
critical [13]. The mild type was defined as mild clinical
symptoms and no radiological manifestations of pneu-
monia. The moderate type was defined as respiratory
symptoms and pneumonia on imaging. The disease was
defined as severe if one of the following criteria was met:
respiratory rate of ≥30 beats per minute; finger oxygen
Wei et al. BMC Infectious Diseases (2020) 20:549 Page 2 of 10
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saturation of ≤93% at resting state; and arterial blood
oxygen partial pressure (PaO
2
)/oxygen concentration
(FiO
2
)of≤300 mmHg. The critical type was defined as
respiratory failure or shock and requirement of mechan-
ical ventilation or intensive care unit (ICU) monitoring
and treatment. Accordingly, the patients were divided
into a non-severe group (mild or moderate disease type)
and severe group (severe or critical disease type). Due to
limited medical facilities at the Zengdu Hhospital, crit-
ical patients were transferred to hospitals with superior
treatment facilities. The incubation period was defined
as the interval between the patient’s earliest date of ex-
posure to the transmission source and the date of the
initial symptom. For patients who had recently visited
Wuhan, the earliest date of exposure was estimated as
the median date of their stay in Wuhan; for patients
who had been in contact with people returning from
Wuhan, the earliest date of exposure was considered to
be the earliest contact date, the earliest date of exposure
was considered to be the earliest contact date. Fever was
defined as an axillary temperature of ≥37.5 °C. Lympho-
penia, eosinopenia, and thrombocytopenia were defined
as lymphocyte, eosinophil, and platelet counts of less
than 1500, 100, and 150,000 of the corresponding cells
per cubic millimeter. The smoking index was equal to
the product of the number of cigarettes per day and
smoking years. The length of COVID-19 treatment was
defined as the time interval from patient admission to
the meeting of the cure and discharge criteria of the
Chinese management guidelines for COVID-19 (version
6.0) [12]. The cure and discharge criteria were as fol-
lows: Normal body temperature for more than 3 days;
significantly improved respiratory symptoms; signifi-
cantly improved acute exudative lesions on pulmonary
imaging; and two consecutive negative results of the nu-
cleic acid tests of sputum, nasopharyngeal swabs, and
other respiratory tract samples.
Study outcomes
The primary composite end points were discharge from
the hospital owing to being cured and transfer to an-
other hospital because of condition deterioration. The
secondary end points were cure or discharge rate and
the length of hospital stay.
Statistical analyses
Statistical analyses were performed with SPSS (v.18.0;
SPSS Inc., Chicago, IL, USA). Continuous variables are
described as median values and interquartile ranges
(IQRs), and categorical variables are reported as num-
bers and percentages. We used the Mann-Whitney U
test, χ
2
test, or Fisher’s exact test to compare differences
between the two groups. A two-sided αof less than 0.05
was considered statistically significant.
Results
Demographic and clinical characteristics
We obtained data on the demographic characteristics,
symptoms, and outcomes for 276 patients hospitalized
in Suizhou Zengdu Hhospital as of March 11, 2020. The
severe group included 14 (5.1%) patients while the non-
severe group included 262 (94.9%) patients. The demo-
graphic and clinical characteristics of the patients are
shown in Table 1. Forty-three (15.6%) of the 276 pa-
tients had visited Wuhan within 14 days before the study
enrollment; 60.1% (166/276) of the patients had come
into contact with people who had travelled to Wuhan or
were diagnosed with COVID-19. The remaining 67 pa-
tients reported they had not been to Wuhan, and it was
unclear how these patients had been exposed to the
transmission source; none of the patients had a history
of exposure to the Huanan seafood wholesale market or
a wild animal. The incubation period calculated based
on the data from 71 patients with a known exposure
time was 6 days (IQR, 4–7 days). The longest incubation
period was 20 days. A nurse in the fever clinic of Suiz-
hou Zengdu Hhospital was the only medical staff in-
cluded in the study.
The median age of the patients was 51 years (IQR,
41–58 years). The patients in the severe group were
significantly older than those in the non-severe pa-
tients (median age: 65 years [IQR, 60.0–72.8 years] vs
50 years [IQR, 39.0–57.0 years], p< 0.01). Male pa-
tients accounted for 56.2% of all patients. A history of
smoking was noted for 12.8% of the 220 patients with
smoking index data. The median body mass index
(BMI) of all the patients included was 23.7 (IQR,
22.0–25.4). The most common symptom of COVID-
19 was fever, which was observed in 82.2% (227/276)
of the patients. The other common symptoms were
cough (78.0%, 218/276), fatigue (51.1%, 141/276), spu-
tum production (49.6%, 137/276), and shortness of
breath (15.2%, 42/276). Fever at the time of admission
was noted in 38.4% (42/276) of the patients, while
fever during hospitalization was noted in 75.0% (207/
276) of the patients. At least one comorbidity was re-
ported in 24.6% (68/276) of the patients, with the
most common comorbidity being hypertension (17.0%,
47/276). Most of the severe patients (85.7%, 12/14)
had at least one comorbidity; this percentage was sig-
nificantly higher than that among the non-severe pa-
tients (21.4%, 56/262).
Radiologic and laboratory findings
Table 2shows the results of radiology and laboratory
tests at admission. All 276 patients underwent CT at
admission, and abnormal results were obtained for
95.7% (264/276) of the patients. The most common
chest CT findings were bilateral patchy shadows
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Table 1 Clinical characteristics of 276 patients with COVID-19 on admission
Characteristic All Patients Disease Severity
a
pvalue
(N= 276) Non-severe (N= 262) Severe (N= 14)
Age
Median (IQR) —yr 51.0 (41.0–58.0) 50.0 (39.0–57.0) 65.0 (60.0–72.8) < 0.01
Distribution —no./total no. (%)
0–19 yr 4/276 (1.4) 4/262 (1.5) 0 0.50
20–59 yr 212/276 (76.8) 209/262 (79.8) 3/14 (21.4) < 0.01
> 60 yr 60/276 (21.7) 49/262 (18.7) 11/14 (78.6) < 0.01
Male sex-no./total no. (%) 155/276 (56.2) 145/262 (55.3) 10/14 (71.4) 0.24
Smoking Index
b
—no./total no. (%) 0.57
0 192/220 (87.2) 182/208 (87.5) 10/12 (83.3)
1–199 7/220 (3.2) 7/208 (3.4) 0/12 (0)
200–399 6/220 (2.7) 5/208 (2.4) 1/12 (8.3)
≥400 15/220 (6.8) 14/208 (6.7) 1/12 (8.3)
Median BMI (IQR) 23.7 (22.0–25.4) 23.7 (21.8–25.4) 24.2 (22.5–25.5) 0.55
Exposure to source of transmission within past 14 days —no./total no.
c
Recently visited Wuhan 43/276 (15.6) 42/262 (16.0) 1/14 (7.1) 0.37
Had contact with people who visited Wuhan or were diagnosed with COVID-19 166/276 (60.1) 157/262 (59.9) 9/14 (64.3) 0.75
Contact with wildlife 0 0 0
Median incubation period (IQR) —days
d
6.0 (4.0–9.0) 6.0 (4.0–9.0) 6.0 (5.0–9.0) 0.54
Fever on admission
Patients —no./total no. (%) 106/276 (38.4) 99/262 (37.8) 7/14 (50.0) 0.36
Median temperature (IQR)—°C 37.2 (36.6–37.9) 37.2 (36.6–37.9) 37.6 (36.6–38.1) 0.56
Distribution of temperature —no./total no. (%)
< 37.5 °C 170/276 (61.6) 163/262 (62.2) 7/14 (50.0) 0.37
37.5–38.0 °C 54/276 (19.6) 51/262 (19.5) 3/14 (21.4) 0.86
38.1–39.0 °C 41/276 (14.9) 39/262 (14.9) 2/14 (14.3) 0.95
> 39.0 °C 11/276 (4.0) 9/262 (3.4) 2/14 (14.3) 0.04
Fever during hospitalization
Patients —no./total no. (%) 207/276 (75.0) 195 /262 (74.4) 12/14 (85.7) 0.34
Median highest temperature (IQR)—°C 38.2 (37.5–38.9) 38.2 (37.4–38.9) 38.9 (8.3–39.6) 0.47
Distribution of temperature —no./total no. (%)
< 37.5 °C 69/276 (25.0) 67/262 (25.6) 2/14 (14.3) 0.34
37.5–38.0 °C 57/276 (20.7) 56/262 (21.4) 1/14 (7.1) 0.20
38.1–39.0 °C 107/276 (38.8) 103/262 (39.3) 4/14 (28.6) 0.41
> 39.0 °C 43/276 (15.6) 36/262 (13.7) 7/14 (50.0) < 0.01
Symptoms —no./total no. (%)
Fever 227/276 (82.2) 219/262 (84.4) 8/14 (57.1) 0.01
Conjunctival congestion 2/276 (0.7) 2/262 (0.8) 0/14 (0) 0.90
Nasal congestion 8/276 (2.9) 8/262 (3.1) 0/14 (0) 0.66
Headache 24/276 (8.7) 22/262 (8.4) 2/14 (14.3) 0.78
Cough 218/276 (78.0) 204/262 (77.9) 14/14 (100.0) 0.02
Sore throat 26/276 (9.4) 23/262 (8.8) 3/14 (21.4) 0.27
Sputum production 137/276 (49.6) 127/262 (48.5) 10/14 (71.4) 0.16
Fatigue 141/276 (51.1) 133/262 (50.8) 8/14 (57.1) 0.64
Wei et al. BMC Infectious Diseases (2020) 20:549 Page 4 of 10
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(84.1%, 232/276) and ground-glass–like shadows
(80.1%, 221/276). Figure 1shows typical ground-glass
shadows and bilateral patchy shadows in two patients.
According to the results of the first examination after
admission, 30.1% (83/276), 75.0% (204/276), and 31.5%
(87/276) of the patients had leukopenia, lymphocytope-
nia, and thrombocytopenia, respectively. Lymphocytope-
nia and thrombocytopenia were more obvious in the
severe group compared to that in the non-severe group.
The C-reactive protein levels were elevated in 60.9%
(162/266) of the patients; the erythrocyte sedimentation
rate of 90.0% (180/201) of patients and D-dimer levels of
53.7% (123/229) of patients were also elevated. Elevated
procalcitonin, creatine kinase, alanine aminotransferase,
aspartate aminotransferase, and myoglobin levels were
observed in 2.5, 11.1, 14.2, 22.3, and 8.0% of patients,
respectively.
Clinical outcomes
As shown in Table 3, most of the patients (94.9%, 262/
276) were cured and discharged from the hospital. Ten
out of 276 (3.6%) patients, all of whom belonged to the
severe group, showed condition deterioration to a crit-
ical status and were transferred to Suizhou Central Hos-
pital, a superior hospital. Eventually, five of them died
and five survived. All five people who died received
endotracheal intubation; one of the five survivors re-
ceived endotracheal intubation, which was removed 20
days later. The remaining four only received non-
invasive ventilator treatment; 1.4% (4/276) of the pa-
tients were transferred to Suizhou Central Hospital for
non-COVID-19 reasons and were shortly discharged
from the hospital. The median lengths of COVID-19
treatment and hospital stay were 14.0 days (IQR, 11.0–
18.0 days) and 18.0 days (IQR, 15.0–24.0 days),
respectively.
Discussion
Understanding the clinical characteristics of COVID-19
inpatients in the areas around the core COVID-19 out-
break region is very important for controlling the spread
of COVID-19 and decision-making for epidemic control.
Our study on 276 inpatients in Zengdu Hhospital con-
firms that COVID-19 patients in the areas surrounding
the core COVID-19 outbreak region showed mainly
mild and moderate illness with fever and lymphocytope-
nia as the main clinical features. Older patients (age > 60
years) or those with underlying comorbidities are at
higher risk of deteriorating to critical status. The length
of hospital-stay and antiviral treatment duration for
COVID-19 were slightly longer than those in Wuhan.
All patients who tested positive for COVID-19 by RT-
PCR in the study region were admitted to the hospital,
regardless of the severity of the patients’condition.
There were several reasons why our hospital established
such an admission standard. First, at that time, the out-
break was still in the early stage. The understanding of
the epidemic situation in Zengdu District, a residential
Table 1 Clinical characteristics of 276 patients with COVID-19 on admission (Continued)
Characteristic All Patients Disease Severity
a
pvalue
(N= 276) Non-severe (N= 262) Severe (N= 14)
Hemoptysis 1/276 (0.4) 0/262 (0) 1/14 (7.1) 0.06
Shortness of breath 42/276 (15.2) 36/262 (13.7) 6/14 (42.9) < 0.01
Nausea or vomiting 23/276 (8.3) 20/262 (7.6) 3/14 (21.4) 0.10
Diarrhea 6/276 (2.2) 5/262 (1.9) 1/14 (7.1) 0.71
Myalgia or arthralgia 26/276 (9.4) 24/262 (9.2) 2/14 (14.3) 0.84
Comorbidities —no./total no. (%)
Any 68/276 (24.6) 56/262 (21.4) 12/14 (85.7) < 0.01
Hypertension 47/276 (17.0) 39/262 (14.9) 8/14 (57.1) < 0.01
Chronic obstructive pulmonary disease 7/276 (2.5) 5/262 (1.93) 2/14 (14.3) 0.04
Diabetes 14/276 (5.1) 12/262 (4.6) 2/14 (14.3) 0.32
Coronary heart disease 12/276 (4.0) 8/262 (5.2) 4/14 (28.6) < 0.01
Cerebrovascular disease 6/276 (2.2) 5/262 (2.0) 1/14 (7.1) 0.71
Cancer
e
3/276 (1.1) 2/262 (0.8) 1/14 (7.1) 0.36
IQR interquartile range; BMI body mass index; Covid-19 coronavirus disease 2019
a
Severe group needs to meet one of the following criteria: respiratory rate ≥30 beats per minute; finger oxygen saturation ≤93% at resting state; arterial blood
oxygen partial pressure (PaO
2
)/oxygen concentration (FiO
2
)≤300 mmHg; has respiratory failure or shock; required mechanical ventilation or intensive care unit
monitoring and treatment
b
Smoking index was equal to the product of the number of cigarettes per day and years of smoking
c
95 patients were unsure if they had been exposed to a source of transmission
d
Incubation period for 205 people could not be determined
e
Included any kind of cancer
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area approximately 3 h away from the core COVID-19
outbreak region, was very limited, and there was no clear
evidence to determine which patients could be treated at
home. Second, the representative area of Zengdu District
was a key area to control the spread of the epidemic;
therefore, it was necessary to treat as many diagnosed
patients as possible. Third, at that time, Zengdu Hhospi-
tal was supported by 98 Jiangxi volunteer doctors (in-
cluding most of the authors of this article) and extensive
medical equipment. Hence, there were sufficient medical
Table 2 Radiographic and laboratory findings of 276 patients with COVID-19 on admission to hospital
a
Variable All Patients Disease Severity p
value
(N = 276) Non-severe (N = 262) Severe (N = 14)
Abnormalities on chest CT —no./total no. (%) 264/276 (95.7%) 250/262 (95.4%) 14/14 (100.0%) 0.53
Ground-glass opacity 221/276 (80.1%) 209/262 (79.8%) 12/14 (85.7%) 0.45
Local patchy shadowing 17/276 (6.4%) 17/262 (6.5%) 0 0.40
Bilateral patchy shadowing 232/276 (84.1%) 220/262 (84.0%) 12/14 (85.7%) 0.41
Interstitial abnormalities 40/276 (14.5%) 37/262 (14.1%) 3/14 (21.4%) 0.54
Laboratory findings
White-cell count
Median (IQR) —per mm
3
4700 (3800–6100) 4700 (3800–6000) 6000 (4000–7100) 0.27
Distribution —no./total no. (%)
> 10,000 per mm
3
16/276 (5.8) 15/262 (5.7) 1/14 (7.1) 0.70
< 4000 per mm
3
83/276 (30.1) 79/262 (30.2) 4 /14 (28.6) 0.67
Lymphocyte count
Median (IQR) —per mm
3
1100 (800–1500) 1100 (800–1500) 700 (400–800) < 0.01
Distribution —no./total no. (%)
< 1500 per mm
3
204/276 (75.0) 193/262 (73.7) 11/14 (78.6) 0.72
Eosinocyte count
Median (IQR) —per mm
3
0.01 (0–0.03 0.01 (0–0.03) 0 (0–0.01) 0.19
Distribution —no./total no. (%)
< 100 per mm
3
126/276 (45.7) 117/262 (44.7) 9/14 (64.3) 0.33
Platelet count
Median (IQR) —per mm
3
177,000 (140000–221,000) 177,000 (141000–222,000) 136,000 (112000–196,000) 0.03
Distribution —no./total no. (%)
< 150,000 per mm
3
87/276 (31.5) 80/262 (30.5) 7/14 (50.0) < 0.01
Median hemoglobin (IQR) —g/dl 131.5 (123.0–143.0) 132.0 (124.0–143.0) 130.0 (100.0–139.0) 0.19
Distribution of other findings —no./total no. (%)
C-reactive protein ≥10 mg/L 162/266 (60.9) 152/252 (60.3) 10/14 (71.4) 0.30
Procalcitonin ≥0.5 ng/ml 6/240 (2.5) 5/226 (2.2) 1/14 (7.1) 0.31
Lactate dehydrogenase ≥250 U/L 31/93 (33.3) 27/88 (30.7) 4/14 (28.6) 0.57
Aspartate aminotransferase > 40 U/L 39/274 (14.2) 34/260 (13.1) 5/14 (35.7) 0.03
Alanine aminotransferase > 40 U/L 61/274 (22.3) 58/260 (22.3) 3/14 (21.4) 0.62
Total bilirubin > 17.1 μmol/L 43/274 (15.7) 42/260 (16.2) 1/14 (7.1) 0.32
Creatine kinase ≥200 U/L 9/81 (11.1) 7/78 (9.0) 2/3 (66.7) 0.03
Creatinine ≥115 μmol/L 6/274 (2.2) 3/260 (1.2) 3/14 (21.4) < 0.01
D-dimer > 0.5mg/L 123/229 (53.7) 115/219 (52.5) 8/10 (80.0) 0.08
Myohemoglobin > 80 μg/L 18/204 (8.0) 13/191 (6.8) 5/13 (38.5) < 0.01
Erythrocyte sedimentation rate > 20 mm/h 180/201 (90.0) 169/190 (88.9) 11/ 11 (100.0) 0.29
a
Lymphocytopenia was defined as a lymphocyte count less than 1500 per cubic millimeter. Eosinopenia was defined as an eosinocyte count of less than 100 per
cubic millimeter. Thrombocytopenia was defined as a platelet count of less than 150,000 per cubic millimeter. These are results of the first examination
after admission
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resources to treat all the diagnosed patients. Our admis-
sion criteria were formulated under such special circum-
stances, although this admission standard was different
from the current international standard. Moreover, com-
pared to studies in which only seriously ill COVID-19
patients were admitted, our admission criteria better re-
flect the disease characteristics in the area around the
outbreak point, so as to provide a decision-making refer-
ence for hospitals in the residential area to decide which
patients should stay at home for observation and which
high-risk patients should be hospitalized in a timely
manner.
The patients in Zengdu area show mainly showed mild
and moderate illness, with a few patients showing severe
Fig. 1 Typical chest computed tomography imaging of COVID-19 patients. Panels aand bshow chest computed tomography images from a
middle-aged male with non-severe COVID-19 at time of admission, showing several scattered ground-glass opacities (A, B the red arrow point).
Panel cand dshow chest computed tomography imaging findings from a middle-aged male with severe COVID-19 at time of admission,
showing bilateral patchy shadows and consolidation (C, D the blue arrow point). COVID-19: coronavirus disease 2019
Table 3 Clinical outcomes of patients with COVID-19
Variable All Patients Disease Severity pvalue
(N = 276) Non-severe (N = 262) Severe (N = 14)
Clinical outcomes —no. (%)
Cured and discharged from hospital 262/276 (94.9) 258/262 (98.5) 4/14 (28.6) < 0.01
Deteriorated to critical and transferred to a hospital 10/276 (3.6) 0/262 (0) 10/14 (71.4) < 0.01
Transferred to a hospital for other reasons 4/276 (1.4) 4/262 (1.5) 0/14 (0) 0.81
Median length of treatment for COVID-19 (IQR) —days
a
14.0 (11.0–18.0) 14.0 (11.0–18.0) 16.0 (15.0–17.0) 0.15
Median length of hospitalization (IQR) —days
a
18.0 (15.0–24.0) 18.0 (15.0–24.0) 21.5 (14.0–21.0) 0.44
a
10 patients who deteriorated to critical status and 4 patients who were transferred to other hospital for other reasons were not included
Wei et al. BMC Infectious Diseases (2020) 20:549 Page 7 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
and critical illness. In Wuhan, as the site with the most
serious COVID-19 infection in China, many patients did
not get timely diagnosis and treatment initially, and
medical resources were insufficient to accommodate the
sudden burst of patients. As a result, the proportion of
severe cases reached 15.0–30.0% [14,15], while the rate
of severe disease in other regions was 3–10% [16,17],
similar to 5.1% in this study. This may be because, with
the deepening of the understanding of COVID-19 and
the formulation of relevant guidelines [18,19], many pa-
tients were diagnosed and treated in a timely manner
without deteriorating into severe disease. Besides, the
difference in admission criteria was also a reason why
the rate of severe disease in this study was significantly
lower than that in Wuhan or abroad.
The early common symptoms of COVID-19 patients
include fever, cough, sputum, and other symptoms of
lower respiratory tract infection. As the most common
symptom, in general, more than 80% of patients have a
fever, but only 38.4% of the patients had a fever at the
time of admission, which shows that the fever in many
patients was intermittent. It also means a large number
of patients with intermittent fever will be set free if in-
stant body temperature readings are the only measure
used for screening [2,20]. The proportion of fever in
critically ill patients increases significantly after
hospitalization, and most of these new fever cases may
be caused by secondary infection, so it is necessary for
severe patients to receive antibiotics to prevent second-
ary infection [13].
COVID-19 patients over 60 years old were more likely
to show deterioration into critical illness. Previous stud-
ies on severe acute respiratory syndrome (SARS) and
Middle East Respiratory Syndrome (MERS) have con-
firmed that age was an important predictor of poor
prognosis [20,21], and similar conclusions were ob-
tained for COVID-19 [22]. Data obtained by Nanshan
Zhong et al. [23] and Zhongliang Wang et al. [14]
showed that the age of severe patients was significantly
older than that of non-severe patients. Consistent with
these findings, among the patients we collected, the me-
dian age of severe patients was 65 years, while that of
non-severe patients was 50 years. In addition, about
78.6% of the severe patients were more than 60 years
old. These studies have shown that older COVID-19 pa-
tients have a poor prognosis.
COVID-19 patients with comorbidities were also likely
to show deterioration [24]. The studies by Nanshan
Zhong et al. and DaweiWang et al. [22] both showed
high proportions of comorbidities in severe patients. A
WHO survey reported that people with comorbidities
had a higher risk of severe disease [25]. In a recent retro-
spective study of 25 death cases with COVID-19 [24], all
of the deceased patients have comorbidities, which were
considered to be one of the most important risk factors
for death. In this study, 85.7% of the severe patients had
comorbidities. This may be due to abnormal immune
function and increased susceptibility to SARS-CoV-2 in
patients with comorbidities [26,27]. In addition,
COVID-19 damage to the lungs can aggravate some co-
morbidities, such as chronic obstructive pulmonary dis-
ease. Antiviral drugs and glucocorticoids also have
limited benefits for patients with comorbidities.
In terms of laboratory tests, 75% of patients had lym-
phopenia, and more obvious findings were noted in severe
patients. The novel coronavirus can induce a cytokine
storm and inhibit the generation of lymphocytes [28,29],
so lymphopenia is very common in patients with COVID-
19. The low absolute value of lymphocytes can be used as
a reference indicator for clinical diagnosis of novel corona-
virus infections [6]. Lymphocytes showed a pronounced
decline in severe patients than in non-severe patients, in-
dicating that the degree of lymphocyte decline can be used
to assess the severity of the disease [30], and that continu-
ous decline of lymphocytes is also one of the indicators of
disease deterioration [13]. In the absence of nucleic acid
detection and CT, this can be an important tool for deter-
mining the severity of the disease. The length of hospital
stay in this study was slightly longer than that in Wuhan,
which was 11–12 days [23,31]. This contradicted the find-
ing that the length of hospitalization is positively related
to disease severity because COVID-19 severity in this
study was significantly lower than that in Wuhan. How-
ever, the allocation of medical resources is also an import-
ant factor affecting the length of hospitalization. The
number of infected patients in Wuhan was large and med-
ical resources were scarce, so the hospital had to discharge
inpatients as soon as possible to treat newly admitted pa-
tients. The inpatient data collected in this study were from
a community hospital that was supported by many Jiangxi
doctor volunteers and medical supplies, which ensured
sufficient medical resources. The characteristics of inpa-
tients under this special medical setup were different from
those at other hospitals. In particular, after the local epi-
demic is mostly controlled, some wastage of medical re-
sources may be inevitable. For example, patients were
allowed to stay in the hospital for some time to recover
even after meeting the discharge criteria for COVID-19,
which was not possible in the hospital in Wuhan. This
was also the reason why the length of treatment for
COVID-19 (14 days) is significantly shorter than the
length of hospitalization (18 days). In addition, hospitals in
Wuhan only accept patients who have been diagnosed as
showing COVID-19, while hospitals outside Wuhan ad-
mitted many patients who were not diagnosed at admis-
sion and were also hospitalized for the 1–3daysit tookfor
nucleic acid test results to arrive. Three studies from re-
gions with sufficient medical resources [32–34], namely
Wei et al. BMC Infectious Diseases (2020) 20:549 Page 8 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Taizhou, Guangdong, and Shenzhen, can support our hy-
potheses since their median hospital stays were 18 days,
20 days, and 20 days, respectively, which were close to the
results of this study.
This study has several limitations. First, since it is a retro-
spective study with a limited number of patients, some con-
clusions need to be verified by studies with more rigorous
design and larger samples. Second, Zengdu Hhospital was a
community hospital, and most of the critically ill patients
had to be transferred to superior hospitals for treatment.
we are temporarily unable to get information on the follow-
up treatment and complications of these patients. Third,
when calculating the incubation period, we excluded the
unclear contact date, resulting in fewer patients included,
and the potential memory bias will also affect our results.
Fourth, our admission criteria were different from the
current internationally recognized criteria, which limits
comparability with other studies. However, our admission
criteria were set in high-risk areas at the early stage of the
epidemic to avoid the spread of the epidemic, which was
essential and important. In addition, only PCR-confirmed
COVID-19 patients were included in this study and asymp-
tomatic infections without PCR confirmation were omitted,
so the characteristics we described are only suitable for
PCR-confirmed COVID-19 patients.
Conclusions
Most of the COVID-19 patients in Zengdu area had
mild disease. Older patients with underlying comorbidi-
ties had a high risk of progressing to severe disease. A
large number of patients with intermittent fever will be
omitted by the temperature checks that are currently
widely being deployed. The length of hospitalization and
antiviral treatment for COVID-19 were slightly longer
than those in the Wuhan area. This work will contribute
to our understanding of the disease characteristics in the
areas around the COVID-19 core outbreak point and
provide reference data for decision-making for epidemic
prevention and control in such special areas.
Abbreviations
COVID-19: Coronavirus disease-19; SARS-CoV-2: Severe acute respiratory
syndrome coronavirus 2; CDC: Centers for Disease Control and Prevention;
WHO: World Health Organization; RT-PCR: Real-time reverse-transcriptase–
polymerase chain reaction; CT: Computed tomography; BMI: Median body
mass index; IQR: Interquartile ranges; SARS: Severe acute respiratory
syndrome; MERS: Middle East Respiratory Syndrome; ACE: Angiotensin-
converting enzyme
Acknowledgements
We thank all the medical staff who participated in treating patients and all
the patients enrolled in this study. The data of these patients have been
published for the first time. All the authors who are not from Zengdu
Hospital are volunteers from different hospitals in Jiangxi Province, and these
volunteers work with doctors and nurses from Zengdu Hospital to fight
against COVID-19. Special thanks to the 82 other volunteers from Jiangxi
Province for their contributions.
Declarations
Not applicable.
Authors’contributions
LJS, ZXG, WYP and HXY designed the study. HP, LC, ZM, LHD, and LDH were
responsible for collecting the epidemiological and clinical data; QXT
examined the CT images and extracted the data; HZF, LJY, and ZCL were
responsible for processing the statistical data; and ZWB, YWZ, and LHD wrote
the paper. ZXG participated in the design and revision of the manuscript. All
authors read and approved the final manuscript.
Funding
This research did not receive any specific grant from funding agencies in the
public, commercial, or not-for-profit sectors.
Availability of data and materials
The datasets used and/or analyzed during the current study are available
from the corresponding author on reasonable request.
Ethics approval and consent to participate
This study was approved by the Ethics Committee of Suizhou Zengdu
Hospital. Written informed consent has been obtained from all participants.
The data used in this study was anonymized before its use.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests to disclose.
Author details
1
Department of Thoracic Surgery, The Second Affiliated Hospital of
Nanchang University, Nanchang, China.
2
Suizhou Zengdu Hospital, Suizhou,
China.
3
Department of Radiotherapy, Jiangxi Cancer Hospital, NanChang,
China.
4
Department of CT&MRI, The First Affiliated Hospital of Gannan
Medical University, Ganzhou, China.
5
Department of Respiratory Medicine,
Chongyi County People’s Hospital, Ganzhou, China.
6
Department of Critical
Medicine, Ganzhou Tumor Hospital, Ganzhou, China.
7
Department of Critical
Care Medicine, Dingnan People’s Hospital, Dingnan, China.
8
Department of
Critical Medicine, Anyuan People’s Hospital, Ganzhou, China.
9
Department of
Infectious Disease, Xingguo People’s Hospital, Ganzhou, China.
10
Department
of Respiratory Medicine, Jiangxi Province Hospital of Integrated Chinese and
Western Medicine, Nanchang, China.
11
Department of General Practice, The
First People’s Hospital of Fuzhou, Fuzhou, China.
12
Department of Pediatric
Neurology, Ganzhou Women’s and Children’s Hospital of Jiangxi Province,
Ganzhou, China.
13
Neurosurgery Department, The Second Affiliated Hospital
of Nanchang University, Nanchang, China.
14
Department of Respiratory
Medicine, Ganzhou People’s Hospital, No.17 Hongqi Avenue, Ganzhou City
341000, Jiangxi Province, China.
Received: 2 May 2020 Accepted: 14 July 2020
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