Bats, monkeys and plants in the time of Covid-19 pandemic at Angkor monuments.

Knowledge of biodeterioration and protection of cultural heritage depends on the scientific understanding of the substratum materials, the ambient environment, the fauna and flora including the microorganisms so an overall picture can be constructed to serve as a basis for protection and management. Over the past more than 20 years of survey and research, an accumulated dataset is available on the mechanisms on the (bio)deterioration of stone monuments in Cambodia, involving interactions among water cycling and salt dynamics with the presence of a rich surface microbiome, the biofilms. However, during the Covid-19 period (2020-2022), because of a drastic drop on tourist population, the number of bats and monkeys are on the rising, which have an impact on the on-going protection efforts. At the same time, large trees around and on the cultural heritage sites are being managed by trimming and removal to decrease the potential risk and negative impacts from them. The new management scheme needs scientific results for the long-term successful protection of these cultural heritage. A close examination of these issues is also meaningful and important to the research new initiatives and policy to be implemented not only in Cambodia but also elsewhere.

Changes in inpatient admissions before and during COVID-19 outbreak in a large tertiary hospital in Shanghai.

Background: The coronavirus disease 2019 (COVID-19) outbreak caused a significant strain on healthcare resources and utilization worldwide. However, the impact of COVID-19 outbreak on patient hospitalization was barely known. This study aimed to determine the impact of the outbreak on the pattern of inpatient hospital admissions to help allocate health care resources during a pandemic. Methods: This retrospective study included patients who were hospitalized in a tertiary teaching hospital in Shanghai between 1 January and 30 April across the years 2017 to 2020. The number of hospitalizations during the study period from 2017 to 2020 were 30,605, 31,464, 32,812 and 24,163, respectively. Changes in patient volumes and the frequency of the International Classification of Diseases and Related Health Problem Tenth Edition (ICD-10) codes before and after the onset of the COVID-19 outbreak were analyzed and presented as absolute and relative differences with 95% confidence intervals between periods of different years. Results: Overall inpatient hospital admissions decreased by 26.35% between January and April 2020, compared to the same period in 2019. The average age of patients in 2020 was higher compared to those from 2017 to 2019. Conversely, the proportions of self-paying patients and non-local patients were significantly lower between January and April 2020 compared to the same period in the previous three years. The top five ICD-10 codes remained common before and during the pandemic. Admissions associated with antineoplastic radiation therapy, chemotherapy, and immunotherapy increased in frequency and proportion by 2020 (difference, 5.6%, 95% CI: 4.4% to 6.8%), and increased proportions were observed for liver and intrahepatic bile duct malignancies (2.18%, 95% CI: 1.15% to 3.21%), cerebral infarction (2.27%, 95% CI: 0.54% to 4.00%), and chronic kidney disease (3.56%, 95% CI: 1.79% to 5.33%). Conclusions: There was a significant reduction in the number of inpatients and a marked change in admission diagnoses during the COVID-19 outbreak. Our findings are useful for making informed decisions on hospital management and reallocation of available health care resources during a pandemic.

Effect of COVID-19 on patients with compensated chronic liver diseases.

BACKGROUND AND AIM: Cytokine storm has been reported in patients with coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. We examine the incidence of acute on chronic liver failure (ACLF) in COVID-19 patients with pre-existing compensated chronic liver disease (CLD). METHODS: From 20 Jan 2020 to 7 Feb 2020, we studied 140 consecutive COVID-19 patients admitted to either Fuyang Second People's Hospital (FYSPH), Anhui or the Fifth Medical Center of Chinese PLA General Hospital (PLAGH) in Beijing, China. Pre-existing CLD includes those with liver cirrhosis assessed by APRI/FIB-4 score and /or ultrasound; NAFLD as identified by either ultrasound or hepatic steatosis index with significant liver fibrosis and chronic hepatitis B (CHB) or hepatitis C (CHC) infection. The diagnosis, grading of severity and clinical management of COVID-19 patients complied to the guideline and clinical protocol issued by the China National Health Commission. All patients had liver function test at least twice weekly till discharge with full recovery or death. RESULTS: In total, 3 had liver cirrhosis, 6 patients had CHB, 13 had NAFLD with significant liver fibrosis (one also had CHB). On admission, none had liver decompensation. COVID-19 disease progression was significantly less frequent in non-CLD patients (10/118 8.5%) than CLD patients (13/22 59.1%, p < 0.001). One patient with CLD had acute-on-chronic liver failure (ACLF). CONCLUSION: Disease progression is significantly higher in those COVID-19 patients with CLD as compared to those with no CLD. ACLF can also occur in patient with pre-existing compensated CLD who had severe COVID-19.

Pre-existing liver disease is associated with poor outcome in patients with SARS CoV2 infection; The APCOLIS Study (APASL COVID-19 Liver Injury Spectrum Study).

BACKGROUND AND AIMS: COVID-19 is a dominant pulmonary disease, with multisystem involvement, depending upon comorbidities. Its profile in patients with pre-existing chronic liver disease (CLD) is largely unknown. We studied the liver injury patterns of SARS-Cov-2 in CLD patients, with or without cirrhosis. METHODS: Data was collected from 13 Asian countries on patients with CLD, known or newly diagnosed, with confirmed COVID-19. RESULTS: Altogether, 228 patients [185 CLD without cirrhosis and 43 with cirrhosis] were enrolled, with comorbidities in nearly 80%. Metabolism associated fatty liver disease (113, 61%) and viral etiology (26, 60%) were common. In CLD without cirrhosis, diabetes [57.7% vs 39.7%, OR = 2.1 (1.1-3.7), p = 0.01] and in cirrhotics, obesity, [64.3% vs. 17.2%, OR = 8.1 (1.9-38.8), p = 0.002] predisposed more to liver injury than those without these. Forty three percent of CLD without cirrhosis presented as acute liver injury and 20% cirrhotics presented with either acute-on-chronic liver failure [5 (11.6%)] or acute decompensation [4 (9%)]. Liver related complications increased (p < 0.05) with stage of liver disease; a Child-Turcotte Pugh score of 9 or more at presentation predicted high mortality [AUROC 0.94, HR = 19.2 (95 CI 2.3-163.3), p < 0.001, sensitivity 85.7% and specificity 94.4%). In decompensated cirrhotics, the liver injury was progressive in 57% patients, with 43% mortality. Rising bilirubin and AST/ALT ratio predicted mortality among cirrhosis patients. CONCLUSIONS: SARS-Cov-2 infection causes significant liver injury in CLD patients, decompensating one fifth of cirrhosis, and worsening the clinical status of the already decompensated. The CLD patients with diabetes and obesity are more vulnerable and should be closely monitored.

Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score.

BACKGROUND: We aimed to clarify high-risk factors for coronavirus disease 2019 (COVID-19) with multivariate analysis and establish a predictive model of disease progression to help clinicians better choose a therapeutic strategy. METHODS: All consecutive patients with COVID-19 admitted to Fuyang Second People's Hospital or the Fifth Medical Center of Chinese PLA General Hospital between 20 January and 22 February 2020 were enrolled and their clinical data were retrospectively collected. Multivariate Cox regression was used to identify risk factors associated with progression, which were then were incorporated into a nomogram to establish a novel prediction scoring model. ROC was used to assess the performance of the model. RESULTS: Overall, 208 patients were divided into a stable group (n = 168, 80.8%) and a progressive group (n = 40,19.2%) based on whether their conditions worsened during hospitalization. Univariate and multivariate analyses showed that comorbidity, older age, lower lymphocyte count, and higher lactate dehydrogenase at presentation were independent high-risk factors for COVID-19 progression. Incorporating these 4 factors, the nomogram achieved good concordance indexes of .86 (95% confidence interval [CI], .81-.91) and well-fitted calibration curves. A novel scoring model, named as CALL, was established; its area under the ROC was .91 (95% CI, .86-.94). Using a cutoff of 6 points, the positive and negative predictive values were 50.7% (38.9-62.4%) and 98.5% (94.7-99.8%), respectively. CONCLUSIONS: Using the CALL score model, clinicians can improve the therapeutic effect and reduce the mortality of COVID-19 with more accurate and efficient use of medical resources.