COVID-19 Treatment Hospital Research Articles

Management of COVID-19 patients of CT Severity 15/25 and above with Ayurveda drugs as add-on therapy – A Case Series

Ayurveda, which is the oldest life science in the world, has yet to be fully accepted as the only or even an additional therapy for severe diseases. It is a common perception that Ayurveda has a significant role in the preventive aspect of diseases, and the drugs of Ayurveda are more effective in chronic ailments. Most publications are also limited to these areas only, as use of Ayurveda in acute or severe cases is not yet justified scientifically because of the lack of significant scientific clinical data as very few case reports are published about the use of Ayurveda in acute cases. Here we present a case series of treatment of five COVID-19 patients with CT Severity 15/25 and above with Ayurveda drugs as add-on therapy admitted to tertiary care, a Level-3 COVID-19 treatment hospital. These five patients sought Ayurveda opinion and consented to Ayurveda treatment along with the ongoing treatment regime. All the patients showed improvement with Ayurveda treatment as an add-on therapy, and none of the patients needed ICU, and all patients were discharged when they started maintaining oxygen saturation at room air. This report addresses the clinical effectiveness of Ayurveda drugs as add-on therapy in severe cases of COVID -19. It also attempts to invite the attention of researchers towards the use of Ayurveda concepts and drugs in severe or acute cases of diseases.

Co-infections and secondary infections amid COVID-19 outbreaks in Vietnam

BackgroundThe mortality risk of co-infections/secondary infections (CoI/ScI) is under-reported in patients with non-critical COVID-19, leading to the under-management of CoI/ScI and publication bias in the medical literature. We aimed to investigate the association between CoI/ScI and mortality in patients hospitalised with mild-to-severe COVID-19.MethodsWe conducted a retrospective cohort study at a COVID-19 treatment hospital in Vietnam and collected all eligible medical records, with CoI/ScI status as the exposure (non-CoI/ScI and CoI/ScI, with the latter including nature of pathogen [bacterial, fungal, or bacterial + fungal] and multidrug-resistance pathogen [no MDRp or ≥ 1 MDRp]). The outcome was all-cause mortality, defined as in-hospital death by all causes or being discharged under critical illness. We used time-dependent analysis to report rates of mortality with 95% confidence intervals (95% CI, Poisson regression) and hazard ratios (HR) with 95% CI (Cox proportional hazards regression with Holm’s method for multiplicity control).ResultsWe followed 1466 patients (median age 61, 56.4% being female) for a median of 9 days. We recorded 387 (26.4%) deaths (95/144 [66.0%] in the CoI/ScI group and 292/1322 [22.1%] in the non-CoI/ScI group). Adjusted mortality rates (per 100 person-days) of the CoI/ScI (6.4, 95% CI 5.3 to 7.8), including bacterial (8.0, 95% CI 7.2 to 8.9), no MDRp (5.9, 95% CI 4.8 to 7.4), and ≥ 1 MDRp (9.0, 95% CI 8.2 to 10.0) groups were higher than that of the non-CoI/ScI group (2.0, 95% CI 1.8 to 2.2). These corresponded to higher risks of mortality in the overall CoI/ScI (HR 3.27, 95% CI 2.58 to 4.13, adjusted p < 0.001), bacterial CoI/ScI (HR 3.79, 95% CI 2.97 to 4.83, adjusted p < 0.001), no MDRp CoI/ScI (HR 3.13, 95% CI 2.42 to 4.05, adjusted p < 0.001), and ≥ 1 MDRp CoI/ScI group (HR 3.89, 95% CI 2.44 to 6.21, adjusted p < 0.001). We could not attain reliable estimates for fungal and bacterial + fungal CoI/ScI.ConclusionCompared with the non-CoI/ScI group, patients with CoI/ScI had a significantly higher risk of all-cause mortality, regardless of resistance status. More evidence is needed to confirm the mortality risks in patients with fungal or bacterial + fungal CoI/ScI.

Clinical Characteristics and Patterns of Immune Responses in COVID-19 Patients From a Rural Community Hospital.

Background Although demographic and clinical factors such as age, certain comorbidities, and sex have been associated with COVID-19 outcomes, these studies were largely conducted in urban populations affiliated with large academic medical centers. There have been very few studies focusing on rural populations that also characterize broader changes in inflammatory cytokines and chemokines. Methodology A single-center study was conducted between June 2020 and March 2021 in Abilene, Texas, USA.Patients were included if they presented to the hospital for treatment of COVID-19, had extra biological materials from routine care available, and were between the ages of 0 to 110 years. There were no exclusion criteria. Patient characteristics, symptom presentation, and clinical laboratory results were extracted from electronic health records. Blood specimens were analyzed by protein microarray to quantitate 40 immunological biomarkers. Results A total of 122 patients were enrolled, of whom 81 (66%) were admitted to the general non-critical inpatient unit, 37 (30%) were admitted to the intensive or critical care units, and four (3.2%) were treated outpatient. Most hospitalized COVID-19 patients in this rural population were elderly, male, obese, and retired individuals. Predominant symptoms for non-critical patients were shortness of breath, fever, and fatigue. Ferritin levels for outpatient patients were lower on average than those in an inpatient setting and lactate dehydrogenase (LDH) levels were noted to be lower in non-critical and outpatient than those in the intensive care unit setting. Inflammatory biomarkers were positively correlated and consistent with inflammatory cascade. Interleukin (IL)-10 was positively correlated while platelet-derived growth factor was negatively correlated with inflammatory biomarkers. Patients ≥65 years had significantly higher levels of LDH and seven cytokines/chemokines (granulocyte-macrophage colony-stimulating factor (GM-CSF), interleukin IL-1b, IL-6, IL-10, IL-11, macrophage inflammatory protein (MIP)-1d, and IL-8) while levels of five other immune molecules (intercellular adhesion molecule 1 (ICAM-1), monocyte chemoattractant protein 1 (MCP-1), tissue inhibitor of metalloproteinase 2 (TIMP-2), IL-2, and IL-4) were significantly lower compared to those <65 years. Females had significantly higher levels of LDH and 10 cytokines/chemokines (GM-CSF, IL-1b, IL-6, IL-10, IL-11, IL-15, IL-16, MIP-1a, MIP-1d, and IL-8) while levels of TIMP-2 and IL-4 were significantly lower than male patients. Conclusions The clinical characteristics of this rural cohort of hospitalized patients differed somewhat from nationally reported data. The contributions of social, environmental, and healthcare access factors should be investigated. We identified age and sex-associated differences in immunological response markers that warrant further investigation to identify the underlying molecular mechanisms and impact on COVID-19 pathogenesis.

Identification and Prediction of Clinical Phenotypes in Hospitalized Patients With COVID-19: Machine Learning From Medical Records.

There is significant heterogeneity in disease progression among hospitalized patients with COVID-19. The pathogenesis of SARS-CoV-2 infection is attributed to a complex interplay between virus and host immune response that in some patients unpredictably and rapidly leads to "hyperinflammation" associated with increased risk of mortality. The early identification of patients at risk of progression to hyperinflammation may help inform timely therapeutic decisions and lead to improved outcomes. The primary objective of this study was to use machine learning to reproducibly identify specific risk-stratifying clinical phenotypes across hospitalized patients with COVID-19 and compare treatment response characteristics and outcomes. A secondary objective was to derive a predictive phenotype classification model using routinely available early encounter data that may be useful in informing optimal COVID-19 bedside clinical management. This was a retrospective analysis of electronic health record data of adult patients (N=4379) who were admitted to a Johns Hopkins Health System hospital for COVID-19 treatment from 2020 to 2021. Phenotypes were identified by clustering 38 routine clinical observations recorded during inpatient care. To examine the reproducibility and validity of the derived phenotypes, patient data were randomly divided into 2 cohorts, and clustering analysis was performed independently for each cohort. A predictive phenotype classifier using the gradient-boosting machine method was derived using routine clinical observations recorded during the first 6 hours following admission. A total of 2 phenotypes (designated as phenotype 1 and phenotype 2) were identified in patients admitted for COVID-19 in both the training and validation cohorts with similar distributions of features, correlations with biomarkers, treatments, comorbidities, and outcomes. In both the training and validation cohorts, phenotype-2 patients were older; had elevated markers of inflammation; and were at an increased risk of requiring intensive care unit-level care, developing sepsis, and mortality compared with phenotype-1 patients. The gradient-boosting machine phenotype prediction model yielded an area under the curve of 0.89 and a positive predictive value of 0.83. Using machine learning clustering, we identified and internally validated 2 clinical COVID-19 phenotypes with distinct treatment or response characteristics consistent with similar 2-phenotype models derived from other hospitalized populations with COVID-19, supporting the reliability and generalizability of these findings. COVID-19 phenotypes can be accurately identified using machine learning models based on readily available early encounter clinical data. A phenotype prediction model based on early encounter data may be clinically useful for timely bedside risk stratification and treatment personalization.

Myth or coverage: experience and expectation of policyholders from health insurance during COVID-19 in the NCR region of India

This study intends to determine whether and to what extent policyholders admitted to the hospital for COVID-19 treatment receive financial support from their health insurance. The researcher interviewed 67 health insurance claimants in the NCR region's several cities—some in Uttar Pradesh, Delhi, Haryana, and Rajasthan. They also interviewed various insurance system participants, including branch managers, agents, and hospital staff, to obtain an overview of policyholder experiences and insurer challenges. For analysis, qualitative research techniques have been used. This research is helpful in various situations when people are hospitalised for planned and unanticipated reasons by recommending what insurance companies should do to protect the interests of their customers. For the Indian insurance industry and regulator/supervisory authorities, the COVID-19 pandemic incidents can be a lesson about their strengths and weaknesses. According to this research, service-level agreement violations, procedural bottlenecks, and lack of clarity and awareness are the problems policyholders face when pursuing claims. The challenges insurers confront in serving their client's needs are maintaining operations in the face of financial stress and changing regulatory compliances, on the one hand, and helping policyholders by resolving their claims and raising awareness, on the other.

The Levels and Influencing Factors of Compassion Fatigue among New Nurses during the COVID-19 Pandemic

Aim. To investigate the levels and influencing factors of compassion fatigue among new nurses during the COVID-19 pandemic. Background. New nurses are often unable to cope with the escalating nursing problems during the COVID-19 epidemic because of their lack of work experience, which may reduce their level of compassion satisfaction and cause compassion fatigue. However, there is little research on compassion fatigue and compassion satisfaction among new nurses during the COVID-19 epidemic. Methods. This was a cross-sectional study. From June to October 2021, 520 new nurses were selected from eight designated hospital for treatment of COVID-19 in China for electronic survey. Questions elicited social-demographics, work-related information, lifestyle factors, and the Chinese version Professional Quality of Life Scale. Results. The scores of compassion satisfaction, burnout, and secondary traumatic stress of new nurses were 31.85 ± 6.18, 27.94 ± 5.04, and 27.17 ± 4.87, respectively. In addition, regression analysis showed that nurses’ compassion satisfaction, burnout, and secondary traumatic stress were affected by social-demographics, work-related information, and lifestyle factors. Conclusions. During the COVID-19 epidemic, compassion satisfaction, burnout, and secondary traumatic stress of new nurses were at a moderate level, which were relatively affected by work-related information and lifestyle, and had little correlation with social-demographics. Implications for Nursing Management. Hospital administrators can promote new nurses’ compassion satisfaction and alleviate their compassion fatigue by improving job satisfaction, encouraging smoking cessation, arranging work hours reasonably, ensuring sleep hours, reducing workplace violence, and strengthening the reporting of violence incidents.

Vaccination and Factors Related to the Clinical Outcome of COVID-19 in Healthcare Workers-A Romanian Front-Line Hospital's Experience.

The study aims to describe the frequency of COVID-19 in healthcare workers (HCWs) in a designated hospital for COVID-19 treatment in Bucharest, Romania, and to explore COVID-19 vaccination and other factors associated with the clinical outcome. We actively surveyed all HCWs from 26 February 2020 to 31 December 2021. Cases were laboratory-confirmed with RT-PCR or rapid test antigen. Epidemiological, demographic, clinical outcomes, vaccination status, and co-morbidities data were collected. Data were analyzed using Microsoft Excel, SPSS, and MedCalc. A total of 490 cases of COVID-19 in HCWs were diagnosed. The comparison groups were related to the severity of the clinical outcome: the non-severe group (279, 64.65%) included mild and asymptomatic cases, and the potentially severe group included moderate and severe cases. Significant differences between groups were registered for high-risk departments (p = 0.0003), exposure to COVID-19 patients (p = 0.0003, vaccination (p = 0.0003), and the presence of co-morbidities (p < 0.0001). Age, obesity, anemia, and exposure to COVID-19 patients predicted the severity of the clinical outcomes (χ2 (4, n = 425) = 65.69, p < 0.001). The strongest predictors were anemia and obesity (OR 5.82 and 4.94, respectively). In HCWs, mild COVID-19 cases were more frequent than severe cases. Vaccination history, exposure, and individual risk influenced the clinical outcome suggesting that measures to protect HCWs and occupational medicine are important for pandemic preparedness.

Depression, Anxiety and Associated Factors among Frontline Hospital Healthcare Workers in the Fourth Wave of COVID-19: Empirical Findings from Vietnam.

(1) Background: This study aims to assess the magnitude of, and factors associated with, depression and anxiety among Vietnamese frontline hospital healthcare workers in the fourth wave of COVID-19; (2) Methods: A hospital based cross-sectional study was carried out within two weeks, October 2020, at a central COVID-19 treatment hospital. Depression and anxiety were measured with PHQ-9 and GAD-7, respectively. Bivariate and multivariate logistic regression analysis were applied to recognize variables related to depression and anxiety, respectively; (3) Results: Among 208 frontline hospital healthcare workers, overall prevalence of depressive symptoms, anxiety symptoms, and both symptoms of depression and anxiety was 38.94%, 25.48% and 24.04%, respectively, in healthcare workers. In a reduced model after using multivariate stepwise logistic regression, age (OR = 0.9, p = 0.001), marital status (OR = 7.84, p = 0.027), profession (OR = 0.39, p = 0.028), having experienced traumatic stress following a work event (OR = 46.24, p < 0.001), feeling at very high risk for COVID-19 (OR = 0.02, p < 0.04), and affected by workplace conditions (OR = 5.36, p < 0.001) were associated with the symptoms of depression. With regard to symptoms of anxiety, single status (OR: 12.18, p = 0.002), being medical technician (OR: 68.89, p < 0.001), alcohol use (OR: 6.83, p = 0.014), using pain relief medications (OR: 25.50, p = 0.047), having experienced traumatic stress following a family event (OR: 130.32, p = 0.001), having experienced traumatic stress following a work event (OR: 181.55, p = 0.002), reporting at very high risk for COVID-19 (OR: 29.64, p = 0.011), treating moderate (OR: 6.46, p = 0.038) and severe (OR: 18.96, p = 0.004) COVID-19 patients, and being significantly affected by the community (OR: 6.33, p = 0.003) were increased risk factors for the symptoms of anxiety. Meanwhile, those living with 4–5 people (OR: 0.15, p = 0.011), specializing in infectious disease (OR: 0.13, p = 0.044)/resuscitation and emergency medicine (OR: 0.04, p = 0.046), and having knowledge preparation before participating in COVID-19 (OR: 0.008, p = 0.014) were less associated with the symptoms of anxiety; (4) Conclusions: There was a relatively high prevalence among Vietnamese hospital healthcare workers exhibiting symptoms of depression and anxiety during the ongoing pandemic. Greater attention to training in psychological skills should be suggested for those belonging to a younger age group, being single/widowed/divorced, treating moderate and severe COVID-19 patients, feeling at very high risk for COVID-19, being significantly affected a lot the community or workplace conditions, or experiencing traumatic stress following a family/work event in the past week.

Abstract 14483: Correlating Blood Type, Infection Risk, and Illness Severity in Patients With COVID-19

Introduction: There have been over 13 million cases of COVID-19 cases with a 2% mortality rate [1]. Over the past year there has been a significant progress in the understanding and management of COVID-19 infections. There are still many factors and complications of COVID-19 that have yet to be elucidated. There have been multiple studies looking at the possible link between ABO group type and increased risk of mortality. Many studies from China, Europe and Canada indicate that blood group “O” had lower risk of susceptibility and severe infection[2-4]. We wanted to identify weather this trend was applicable within our hospital network in Eastern Pennsylvania. We wanted to identify through retrospective analysis if there is an association between ABO type, Race, Gender, and mortality at 30-day or 90 days. Methods: We identified n=568 patients between February 2020 to June 2020 that were admitted to the hospital for treatment of COVID-19 that also had historical data regarding ABO grouping. Demographics, length of stay, intubations, and smoking history. Once data was collected, statistical analysis was conducted with SPSS for means, standard deviations, and Chi-squared test for non-parametric testing. Results: The breakdown of blood groups in our populations was [ A: 35.1%, B: 11.6%, AB: 7.9%, O:45.3% ]. The average age of patients by blood group was [A:70.9±6 , B: 68.6±15, AB:66.3±12, O: 65±17], The percentage of females in each group is [A:45%, B: 35%, AB:67%, O:50%]. The mean BMI for all groups were 31±7 (p&gt;0.05) and there was no significant difference between blood groups with length of stay [A:8±6.1 , B: 10.5±9.6, AB:8.3±6.7, O: 9±8 (p&gt;0.05)] There was no significant difference in mortality rate among the blood groups during admission [ A: 26%, B: 16%, AB: 13%, O:24% (p=0.17)] or the rate of intubation [ A: 10%, B: 15%, AB: 11%, O:12% (p=0.72)]. Conclusion: Our findings indicate there is no significant difference between mortality, inpatient length of stay, or proportion of intubations between different blood groups. Our population of blood groups was distributed close to distribution of blood group in the general population. While there have been studies that indicate there is a protective nature of type O blood group, we did not see this in our cohort.

Job Burnout Status andAnd its Relationship with Resilience Level of Healthcare Workers during Covid-19 Pandemic: A Case of Southern Iran

Background and Purpose: COVID-19 could be a threat to healthcare workers' mental health. This study was conducted to investigate job burnout and its relationship with the resilience level of the personnel in the COVID-19 treatment hospital in southern Iran.&#x0D; Methods: This descriptive-analytical cross-sectional study was conducted in 2021 on 496 personnel of Hazrat Ali Asghar (AS) Hospital selected as the center of COVID-19 in southern Iran. The participants of the study were selected using the census. Data collection tools were the standard Maslach Burnout Inventory (MBI) and Connor-Davidson Resilience Scale (CD-RISC). Data analysis was performed using t-test, ANOVA, Pearson correlation coefficient, and multiple linear regression in SPSS23 at a significance level of 0.05.&#x0D; Results: The mean scores of job burnout and resilience were 76.95 ± 14.36 (of 132) and 71.21 ± 8.24 (of 125), respectively which indicated the moderate level of these two variables. There was a significant inverse correlation between job burnout and resilience (P&lt;0.001, r= - 0.514). Spiritual influences (P&lt;0.001), perception of competence (P=0.001), positive acceptance of change and secure relationships (P= 0.001), trust in individual instincts (P= 0.02), and control (P= 0.03) of resilience aspects were identified as predictors of job burnout. Additionally, there was a statistically significant relationship between job burnout and gender (P=0.001) and occupational group (P= 0.04); and between resilience and gender (P= 0.02) and with marital status (P= 0.03).&#x0D; Conclusion: Job burnout status and personnel resilience were at a moderate level. It was recommended to train employees with resilience-enhancing skills employees according to each of their dimensions.

Assessing the Correlation Between the Level of Depressive Disorder and Quality of life in Employees Working in Covid-19 Reference Hospital in 2020

Background and Objectives: The widespread prevalence of new coronavirus (COVID-19) worldwide can lead to many mental disorders. COVID-19 Care Frontline Staff, are one of the groups most strongly affected by the mental disorders caused by this disease. This study aimed to assess the correlation between the level of depressive disorder and quality of life in employees working in Covid-19 reference hospital in 2020. Methods: This was descriptive-correlation census study performed on 496 employees of Hazrat Ali Asghar (AS) Hospital in Shiraz as the reference hospital for treatment of COVID-19 in southern Iran. Data collection tools were standard Beck Depression Inventory (BDI) and WHOQOL-BREF quality of life questionnaires. Data were analyzed using descriptive and inferential statistical methods, Pearson correlation coefficient and t-test and ANOVA by SPSS v. 23 software at a significance level of α=0.05. Results: The Mean±SD score of depression and quality of life of the studied employees were 35.8±9.2 (out of 63), 60.7±14.8 (out of 120) respectively. 49.6% and 87.5% of the employees had moderate levels of depression and quality of life, respectively. There was a significant and inverse correlation between depression and employees' quality of life (r=-0.612, P&lt;0.001). Also between depression with education level (P=0.04), marital status (P=0.01), and type of occupation (P=0.03), and between quality of life and marital status (P=0.03) were observed a statistically significant relation. Conclusion: Depression and quality of life of the employees were moderate level. Planning is recommended to improve the mental health of employees, use psychotherapy techniques such as cognitive behavioral therapy and mindfulness, develop and implement stress and anxiety management programs, and provide counseling services.

Survival prediction algorithms for COVID-19 patients admitted to a UK district general hospital.

ObjectiveTo collect and review data from consecutive patients admitted to Queen’s Hospital, Burton on Trent for treatment of Covid‐19 infection, with the aim of developing a predictive algorithm that can help identify those patients likely to survive.DesignConsecutive patient data were collected from all admissions to hospital for treatment of Covid‐19. Data were manually extracted from the electronic patient record for statistical analysis.ResultsData, including outcome data (discharged alive/died), were extracted for 487 consecutive patients, admitted for treatment. Overall, patients who died were older, had very significantly lower Oxygen saturation (SpO2) on admission, required a higher inspired Oxygen concentration (IpO2) and higher CRP as evidenced by a Bonferroni‐corrected (P < 0.0056). Evaluated individually, platelets and lymphocyte count were not statistically significant but when used in a logistic regression to develop a predictive score, platelet count did add predictive value. The 5‐parameter prediction algorithm we developed was: P(death)=11+e‐1(‐22.8449+4.1124LN(age)+2.0421LN(IpO2)+0.2770LN(CRP)‐0.7738LN(Plt)+0.7625#consolidated_lungs) ConclusionAge, IpO2 on admission, CRP, platelets and number of lungs consolidated were effective marker combinations that helped identify patients who would be likely to survive. The AUC under the ROC Plot was 0.8129 (95% confidence interval 0.0.773 ‐ 0.853; P < .001).

The Application of the “3 + 1” Mode in the COVID-19 Epidemic Prevention and Control at the Infection Ward of a Designated Comprehensive Hospital for COVID-19 Treatment

Objective: We assess the application effect of the “3 + 1” mode in the COVID-19 epidemic prevention and control at the infection ward of a designated comprehensive hospital for COVID-19 treatment. Method: Based on the features of the inpatients of the infection ward and their relatives, a “3 + 1” mode for the COVID-19 prevention and control is developed to conform to the demands for epidemic prevention and control and the overall prevention and control scheme of the whole hospital. Here, “3” stands for the epidemic prevention and control system, personnel management, and prevention and control measures; “1” stands for COVID-19 testing. Result: From March 1, 2020 to March 31, 2021, a total of 3056 patients were hospitalized in the three infection wards. Among them, 265 patients had a fever, and 113 patients had respiratory symptoms. None of them were infected with COVID-19. The participation rate of the test about the knowledge related to COVID-19 and the knowledge mastery rate were both 100% among the medical staff. None of the inpatients and their companions or the medical staff was diagnosed with COVID-19. Conclusion: Thus the “3 + 1” mode proves successful for avoiding nosocomial infection and the spread of the epidemic.

Analytical methods for the determination of remdesivir as a promising antiviral candidate drug for the COVID-19 pandemic.

Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is undoubtedly the most challenging pandemic in the current century. A total of 73,953,702 confirmed cases of COVID-19 and 1,644,416 deaths were reported globally up to December 17, 2020. Therefore, in the absence of a safe and effective vaccine, it is urgent to identify a novel antiviral drug to effectively treat patients with COVID-19. On October 22, the U.S. Food and Drug Administration approved remdesivir, a nucleotide analog prodrug with broad antiviral activity, for adults and children (12 years of age and older and weighing at least 40 kg) who need to be admitted to hospital for covid-19 treatment. In order to monitor the optimization of patient clinical response profile, as well as address the challenges associated with remdesivir metabolism, highly sensitive, selective and accurate analytical methods are necessary. This review clearly covers all the analytical methods developed for the identification and quantitative determination of remdesivir and its metabolites in biological matrices, which helps the researchers in developing new methods for the analysis of remdesivir by considering the pros and cons of the previously reported methods.

Experience in Prevention and Control Work of Anti-COVID-19 in People's Hospital of Tongchuan City in China

Objective: To explore the prevention and control strategies and effects of COVID-19 in People's Hospital of Tongchuan so as to provide evidence for prevention and control of COVID-19 in Tongchuan.&#x0D; Methods: The measures taken by People's Hospital of Tongchuan from the aspects of sound organization, new coronavirus knowledge training, prevention of nosocomial infection, establishment of elite medical team, scientific and precise treatment and internet application as well as medical treatment were reviewed.&#x0D; Results: Between 23 January 2020 and 15 April 2020, the hospital had received a total of 6 patients with confirmed COVID-19, among which 3 patients have been discharged. More than 31,000 persons were given pre-examination triage, 2,605 persons were treated for fever at clinics, 596 persons were under isolation and observation, and 184 persons had nucleic acid test, so as to achieve the requirements of no missed diagnosis, no death and no infection goal, which were prioritized by the national, provincial and municipal health inspection teams.&#x0D; Conclusion: The effective prevention and control strategies against COVID-19 in People’s Hospital of Tongchuan have significantly achieved the "three zeros" goal namely zero infection, zero transmission and zero death.&#x0D; People's Hospital of Tongchuan, founded in 1949, is a comprehensive level-III first-class hospital. It has two hospitals located in the north and the south, with 1,700 beds and 2,044 employees. It is the first designated hospital for treatment of COVID-19 [1] in the province.

Contingency Nursing Management in Designated Hospitals During COVID-19 Outbreak.

Background:In December 2019, early cases of COVID-19 were identified in Wuhan, China. By late January 2020, it was evident that COVID-19 was rapidly spreading and represented a national health emergency. In order to contain the spread of COVID-19, China adopted a centralized treatment plan by appointing designated hospitals in each region. Shantou Central Hospital is a Grade A Class A general hospital in Guangdong Province. It was appointed as a provincial COVID-19 designated treatment hospital on January 21, 2020, to provide all COVID-19-related treatments for the city of Shantou. The nursing department at Shantou Central Hospital is fully responsible for hospital nursing administration, nursing human resource management, nursing quality management, and all nursing tasks related to hospital medical care, nursing, teaching, scientific research, preventive healthcare, and so on.Objective:To summarize the role of nursing management in transforming a general hospital into a designated hospital for treatment of COVID-19 patients.Methods:We undertook a series of nursing management measures in the strategic phase and the implementation phase.Findings:Through a series of nursing management measures, all COVID-19 patients admitted to our hospital were cured and discharged. All non-COVID-19 patients and staff hospitalized during the same period were not infected with the virus. During this period, our hospital completed 7,466 operations. Hence, our nursing management measures were effective.Conclusions:Our efficient nursing management system, first of all, effectively mobilized all available manpower; secondly, up-skilled and trained personnel within a very short period of time; thirdly, provided reliable logistical support for front-line protection equipments; and finally, motivated nurses during this very difficult time to make a significant positive contribution to the fight against COVID-19 pandemic.

An assessment of the possible protective effect of allopurinol in acute stroke.

Allopurinol has been shown to have a protective effect on ischaemic tissue by the indirect prevention of excessive purine loss. This property was tested in the gerbil model of acute stroke. A total of 69 animals were pretreated with an intraperitoneal injection of either allopurinol (50 mg/kg) or sterile water and then subjected to unilateral ligation of the left common carotid artery under general anaesthesia. The clinical effect of the ligation was grouped into three categories of normal, mild to moderate defect (splayed leg, turning behaviour) and severe defect (death, nonresponsiveness and seizures). More normal animals and fewer severely affected animals were present in the allopurinol treated group compared to controls, but only at 2 to 4 hours after carotid ligation (p less than 0.05). Histological examination of brain tissue from the normal category failed to reveal any difference in subclinical ischaemic damage between the two groups. It was concluded that allopurinol may have a protective effect in acute stroke and that this property warrants further elucidation.