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1.
Epidemiol Infect ; 148: e168, 2020 08 04.
Article in English | MEDLINE | ID: covidwho-1537262

ABSTRACT

This study aimed to identify clinical features for prognosing mortality risk using machine-learning methods in patients with coronavirus disease 2019 (COVID-19). A retrospective study of the inpatients with COVID-19 admitted from 15 January to 15 March 2020 in Wuhan is reported. The data of symptoms, comorbidity, demographic, vital sign, CT scans results and laboratory test results on admission were collected. Machine-learning methods (Random Forest and XGboost) were used to rank clinical features for mortality risk. Multivariate logistic regression models were applied to identify clinical features with statistical significance. The predictors of mortality were lactate dehydrogenase (LDH), C-reactive protein (CRP) and age based on 500 bootstrapped samples. A multivariate logistic regression model was formed to predict mortality 292 in-sample patients with area under the receiver operating characteristics (AUROC) of 0.9521, which was better than CURB-65 (AUROC of 0.8501) and the machine-learning-based model (AUROC of 0.4530). An out-sample data set of 13 patients was further tested to show our model (AUROC of 0.6061) was also better than CURB-65 (AUROC of 0.4608) and the machine-learning-based model (AUROC of 0.2292). LDH, CRP and age can be used to identify severe patients with COVID-19 on hospital admission.


Subject(s)
Coronavirus Infections/mortality , Coronavirus Infections/therapy , Logistic Models , Machine Learning , Pneumonia, Viral/mortality , Pneumonia, Viral/therapy , Adolescent , Adult , Aged , COVID-19 , China/epidemiology , Female , Hospitalization , Humans , Male , Middle Aged , Pandemics , Prognosis , ROC Curve , Reproducibility of Results , Retrospective Studies , Risk Assessment/methods , Young Adult
2.
Evid Based Complement Alternat Med ; 2021: 4303380, 2021.
Article in English | MEDLINE | ID: covidwho-1455773

ABSTRACT

Background: In view of the global efforts to develop effective treatments for the current worldwide coronavirus 2019 (COVID-19) pandemic, Qingfei Paidu decoction (QPD), a novel traditional Chinese medicine (TCM) prescription, was formulated as an optimized combination of constituents of classic prescriptions used to treat numerous febrile and respiratory-related diseases. This prescription has been used to treat patients with COVID-19 pneumonia in Wuhan, China. Hypothesis/Purpose. We hypothesized that QPD would have beneficial effects on patients with COVID-19. We aimed to prove this hypothesis by evaluating the efficacy of QPD in patients with COVID-19 pneumonia. Methods: In this single-center, retrospective, observational study, we identified eligible participants who received a laboratory diagnosis of COVID-19 between January 15 and March 15, 2020, in the west campus of Union Hospital in Wuhan, China. QPD was supplied as an oral liquid packaged in 200-mL containers, and patients were orally administered one package twice daily 40 minutes after a meal. The primary outcome was death, which was compared between patients who did and did not receive QPD (QPD and NoQPD groups, respectively). Propensity score matching (PSM) was used to identify cohorts. Results: In total, 239 and 522 participants were enrolled in the QPD and NoQPD groups, respectively. After PSM at a 1 : 1 ratio, 446 patients meeting the criteria were included in the analysis with 223 in each arm. In the QPD and NoQPD groups, 7 (3.2%) and 29 (13.0%) patients died, and those in the QPD group had a significantly lower risk of death (hazard ratio (HR) 0.29, 95% CI: 0.13-0.67) than those in the NoQPD group (p = 0.004). Furthermore, the survival time was significantly longer in the QPD group than in the NoQPD group (p < 0.001). Conclusion: The use of QPD may reduce the risk of death in patients with COVID-19 pneumonia.

3.
Open Forum Infect Dis ; 7(7): ofaa283, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-846713

ABSTRACT

Background: Clinical manifestation and neonatal outcomes of pregnant women with coronavirus disease 2019 (COVID-19) were unclear in Wuhan, China. Methods: We retrospectively analyzed clinical characteristics of pregnant and nonpregnant women with COVID-19 aged from 20 to 40, admitted between January 15 and March 15, 2020 at Union Hospital, Wuhan, and symptoms of pregnant women with COVID-19 and compared the clinical characteristics and symptoms to historic data previously reported for H1N1. Results: Among 64 patients, 34 (53.13%) were pregnant, with higher proportion of exposure history (29.41% vs 6.67%) and more pulmonary infiltration on computed tomography test (50% vs 10%) compared to nonpregnant women. Of pregnant patients, 27 (79.41%) completed pregnancy, 5 (14.71%) had natural delivery, 18 (52.94%) had cesarean section, and 4 (11.76%) had abortion; 5 (14.71%) patients were asymptomatic. All 23 newborns had negative reverse-transcription polymerase chain results, and an average 1-minute Apgar score was 8-9 points. Pregnant and nonpregnant patients show differences in symptoms such as fever, expectoration, and fatigue and on laboratory tests such as neurophils, fibrinogen, D-dimer, and erythrocyte sedimentation rate. Pregnant patients with COVID-19 tend to have more milder symptoms than those with H1N1. Conclusions: Clinical characteristics of pregnant patients with COVID-19 are less serious than nonpregnant. No evidence indicated that pregnant women may have fetal infection through vertical transmission of COVID-19. Pregnant patients with H1N1 had more serious condition than those with COVID-19.

4.
Resuscitation ; 151: 18-23, 2020 06.
Article in English | MEDLINE | ID: covidwho-46293

ABSTRACT

OBJECTIVE: To describe the characteristics and outcomes of patients with severe COVID-19 and in-hospital cardiac arrest (IHCA) in Wuhan, China. METHODS: The outcomes of patients with severe COVID-19 pneumonia after IHCA over a 40-day period were retrospectively evaluated. Between January 15 and February 25, 2020, data for all cardiopulmonary resuscitation (CPR) attempts for IHCA that occurred in a tertiary teaching hospital in Wuhan, China were collected according to the Utstein style. The primary outcome was restoration of spontaneous circulation (ROSC), and the secondary outcomes were 30-day survival, and neurological outcome. RESULTS: Data from 136 patients showed 119 (87.5%) patients had a respiratory cause for their cardiac arrest, and 113 (83.1%) were resuscitated in a general ward. The initial rhythm was asystole in 89.7%, pulseless electrical activity (PEA) in 4.4%, and shockable in 5.9%. Most patients with IHCA were monitored (93.4%) and in most resuscitation (89%) was initiated <1 min. The average length of hospital stay was 7 days and the time from illness onset to hospital admission was 10 days. The most frequent comorbidity was hypertension (30.2%), and the most frequent symptom was shortness of breath (75%). Of the patients receiving CPR, ROSC was achieved in 18 (13.2%) patients, 4 (2.9%) patients survived for at least 30 days, and one patient achieved a favourable neurological outcome at 30 days. Cardiac arrest location and initial rhythm were associated with better outcomes. CONCLUSION: Survival of patients with severe COVID-19 pneumonia who had an in-hospital cardiac arrest was poor in Wuhan.


Subject(s)
Betacoronavirus , Cardiopulmonary Resuscitation/methods , Coronavirus Infections/complications , Heart Arrest/mortality , Hospital Mortality , Pneumonia, Viral/therapy , Adult , Aged , Aged, 80 and over , COVID-19 , China , Cohort Studies , Female , Heart Arrest/etiology , Heart Arrest/therapy , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Pneumonia, Viral/etiology , Pneumonia, Viral/mortality , Prognosis , Retrospective Studies , Risk Assessment , SARS-CoV-2 , Survival Analysis , Treatment Outcome
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