Time series analysis of the number of tuberculosis cases in tangshan area

Objective The time series analysis model was used to predict and warn the number of tuberculosis (TB) cases in Tangshan area in different time, which provided a reference for scientific prevention and control of TB epidemic in this area. Methods The number of monthly TB cases in Tangshan from January 2005 to December 2021 was collected, and the seasonal autoregressive integrated moving average (SARIMA) model was used to predict the number of TB cases in 2022. Meanwhile, the difference between the predicted number of TB cases and the actual observed number of TB cases in the area was explored during the period of COVID-19 in 2020 by this model and rank test. Results From January 2005 to December 2021, the ARIMA (1, 1, 0) (1, 1, 2)s model was fitted well with the actual observed number of TB cases (AR =-0. 530, ARs =-0.967, MAs = 0. 861, P0. 05;Stationary R2 = 0. 558, R2 = 0. 634, BIC = 7. 887;Ljung-Box Q = 25. 605, P 0. 05), with peaks TB incidence in March, April, and December every year, and the predicted number of TB cases in 2020 was 1 800. From 2005 to 2019, ARIMA (1, 1, 0) (0, 1, 2)s model was fitted well with the actual number of cases (AR =-0. 544, ARs =-0. 840, MAs = 0. 697, P 0. 05;Stationary R2 = 0. 582, R2 = 0. 621, BIC = 7. 939;Ljung-Box Q = 24. 211, P 0. 05), with peaks TB incidence in March, April, and December every year, and the predicted number of TB cases in 2020 was 1 985. The observed and predicted number of TB cases from January 2020 to May 2020 were statistically significant (Z =-2. 023, P0. 05). Conclusion It is necessary to increase the intensity of early warning of TB in March, April, and December every year in Tangshan to prevent the epidemic of TB. At the same time, the coordination of the staff of TB prevention institutions and the emergency system should be strengthened during the epidemic situation of COVID-19, and effectively ensure the registration and medical treatment of TB patients during the epidemic situation. © 2023, Editorial Department of Medical Pest Control. All rights reserved.

Impact of the COVID-19 pandemic on maternal mental health during pregnancy: The CONCEPTION study - Phase I

Introduction: Mental health regional differences during pregnancy through the COVID-19 pandemic is understudied. Objective(s): We aimed to quantify the impact of the COVID-19 pandemic on maternal mental health during pregnancy. Method(s): A cohort study with a web-based recruitment strategy and electronic data collection was initiated in 06/2020. Although Canadian women, >18 years were primarily targeted, pregnant women worldwide were eligible. The current analysis includes data on women enrolled 06/2020-11/2020. Self-reported data included mental health measures (Edinburgh Perinatal Depression Scale (EPDS), Generalized Anxiety Disorders (GAD-7)), stress. We compared maternal mental health stratifying on country/continents of residence, and identified determinants of mental health using multivariable regression models. Result(s): Of 2,109 pregnant women recruited, 1,932 were from Canada, 48 the United States (US), 73 Europe, 35 Africa, and 21 Asia/Oceania. Mean depressive symptom scores were lower in Canada (EPDS 8.2, SD 5.2) compared to the US (EPDS 10.5, SD 4.8) and Europe (EPDS 10.4, SD 6.5) (p<0.05), regardless of being infected or not. Maternal anxiety, stress, decreased income and access to health care due to the pandemic were increasing maternal depression. The prevalence of severe anxiety was similar across country/continents. Maternal depression, stress, and earlier recruitment during the pandemic (June/July) were associated with increased maternal anxiety. Conclusion(s): In this first international study on the impact of the COVID-19 pandemic, CONCEPTION has shown significant country/continent-specific variations in depressive symptoms during pregnancy, whereas severe anxiety was similar regardless of place of residence. Strategies are needed to reduce COVID-19's mental health burden in pregnancy.

[Comparison of severity classification of Chinese protocol, pneumonia severity index and CURB-65 in risk stratification and prognostic assessment of coronavirus disease 2019].

Objective: To investigate the application of severity classification according to the protocol on the Diagnosis and Treatment of coronavirus disease 2019(COVID-19)by the National Health Commission of China, pneumonia severity index(PSI) and CURB-65　in risk stratification and prognostic assessment of COVID-19. Methods: Clinical data of 234 in-hospital patients with COVID-19 were collected and retrospectively reviewed in Wuhan Tongji Hospital. Patients were divided into 3 groups (common, severe, and critical type) at admission according to the sixth version of the protocol issued by the National Health Commission of China on Diagnosis and Treatment of COVID-19. At the same time, the severity of pneumonia was calculated by PSI and CURB-65, and the patients were stratified into 3 risk groups, namely mild, moderate, and severe groups. The hospital mortality rate was evaluated in each group. Sensitivity, specificity, positive predictive values, negative predictive values, and the area under the receiver operating characteristic(ROC) curve(AUC) for predicting hospital mortality in each rule were assessed. Results: According to the severity classification of Chinese protocol, the proportion of patients with common type, severe type, and the critical type was 15.8%, 75.6%, and 8.5%, respectively. No in-hospital death occurred in the common type. As for PSI and CURB-65, greater proportions of patients were classified as low risk(79.1% and 75.6%, respectively), while smaller proportions of patients were classified as moderate and high risk(16.2%, 15.0%; 4.7%, 9.4%, respectively). In-hospital death occurred in low and moderate risk patients identified by these 2 scoring systems. The mortality of the critical group of the Chinese protocol was 65%, and the sensitivity and specificity of predicting in-hospital mortality were 36.4% and 97.0%, respectively. The mortality in the high risk group of PSI and CURB-65 was 100% and 77.3%. The risk class V of PSI and CURB-65 score 3-5 had high specificity(100% and 97.4%, respectively)but low sensitivity(33.3% and 51.5%, respectively)in predicting in-hospital mortality. The AUC of the Chinese protocol severity classification, PSI, and CURB-65 was 0.735, 0.951, and 0.912. The optimal cut-off point of PSI was risk class Ⅳ, and the sensitivity and specificity for predicting mortality were 90.9% and 90.5%. The optimal cut-off point of CURB-65 was score 2, and the corresponding sensitivity and specificity were 84.8% and 85.6%. Conclusions: PSI and CURB-65 can be used for risk stratification and prognostic assessment in patients with COVID-19.

Clinical characteristics of COVID-19-infected cancer patients: a retrospective case study in three hospitals within Wuhan, China.

BACKGROUND: Cancer patients are regarded as a highly vulnerable group in the current Coronavirus Disease 2019 (COVID-19) pandemic. To date, the clinical characteristics of COVID-19-infected cancer patients remain largely unknown. PATIENTS AND METHODS: In this retrospective cohort study, we included cancer patients with laboratory-confirmed COVID-19 from three designated hospitals in Wuhan, China. Clinical data were collected from medical records from 13 January 2020 to 26 February 2020. Univariate and multivariate analyses were carried out to assess the risk factors associated with severe events defined as a condition requiring admission to an intensive care unit, the use of mechanical ventilation, or death. RESULTS: A total of 28 COVID-19-infected cancer patients were included; 17 (60.7%) patients were male. Median (interquartile range) age was 65.0 (56.0-70.0) years. Lung cancer was the most frequent cancer type (n = 7; 25.0%). Eight (28.6%) patients were suspected to have hospital-associated transmission. The following clinical features were shown in our cohort: fever (n = 23, 82.1%), dry cough (n = 22, 81%), and dyspnoea (n = 14, 50.0%), along with lymphopaenia (n = 23, 82.1%), high level of high-sensitivity C-reactive protein (n = 23, 82.1%), anaemia (n = 21, 75.0%), and hypoproteinaemia (n = 25, 89.3%). The common chest computed tomography (CT) findings were ground-glass opacity (n = 21, 75.0%) and patchy consolidation (n = 13, 46.3%). A total of 15 (53.6%) patients had severe events and the mortality rate was 28.6%. If the last antitumour treatment was within 14 days, it significantly increased the risk of developing severe events [hazard ratio (HR) = 4.079, 95% confidence interval (CI) 1.086-15.322, P = 0.037]. Furthermore, patchy consolidation on CT on admission was associated with a higher risk of developing severe events (HR = 5.438, 95% CI 1.498-19.748, P = 0.010). CONCLUSIONS: Cancer patients show deteriorating conditions and poor outcomes from the COVID-19 infection. It is recommended that cancer patients receiving antitumour treatments should have vigorous screening for COVID-19 infection and should avoid treatments causing immunosuppression or have their dosages decreased in case of COVID-19 coinfection.

[Analysis of myocardial injury in patients with COVID-19 and association between concomitant cardiovascular diseases and severity of COVID-19].

Objective: To evaluate the cardiovascular damage of patients with COVID-19, and determine the correlation of serum N-terminal pro B-type natriuretic peptide (NT-proBNP） and cardiac troponin-I (cTnI） with the severity of COVID-19, and the impact of concomitant cardiovascular disease on severity of COVID-19 was also evaluated. Methods: A cross-sectional study was designed on 150 consecutive patients with COVID-19 in the fever clinic of Tongji Hospital in Wuhan from January 19 to February 13 in 2020, including 126 mild cases and 24 cases in critical care. Both univariate and multivariate logistic regression were used to analyze the correlation of past medical history including hypertension, diabetes and coronary heart disease (CHD）, as well as the levels of serum NT-proBNP and cTnI to the disease severity of COVID-19 patients. Results: Age, hypersensitive C-reactive protein(hs-CRP) and serum creatinine levels of the patients were higher in critical care cases than in mild cases(all P<0.05). Prevalence of male, elevated NT-proBNP and cTnI, hypertension and coronary heart disease were significantly higher in critical cases care patients than in the mild cases(all P<0.05). Univariate logistic regression analysis showed that age, male, elevated NT-proBNP, elevated cTnI, elevated hs-CRP, elevated serum creatinine, hypertension, and CHD were significantly correlated with critical disease status(all P<0.05). Multivariate logistic regression analysis showed that elevated cTnI(OR=26.909，95%CI 4.086-177.226，P=0.001) and CHD (OR=16.609，95%CI 2.288-120.577，P=0.005) were the independent risk factors of critical disease status. Conclusions: COVID-19 can significantly affect the heart function and lead to myocardial injury. The past medical history of CHD and increased level of cTnI are 2 independent determinants of clinical disease status in patients with COVID-19.