Validation of ISARIC 4C Mortality and Deterioration Scores in a Mixed Vaccination Status Cohort of Hospitalized Coronavirus Disease 2019 (COVID-19) Patients in Singapore.

In this cross-sectional study, we studied performance of the International Severe Acute Respiratory and Emerging Infections Consortium mortality and deterioration scores in a cohort of 410 hospitalized patients (51.2% fully vaccinated). area under the receiver operating characteristic curves were 0.778 and 0.764, respectively, comparable to originally published validation cohorts. Subgroup analysis showed equally good performance in vaccinated and partially or unvaccinated patients.

Clinical and Virological Features of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants of Concern: A Retrospective Cohort Study Comparing B.1.1.7 (Alpha), B.1.351 (Beta), and B.1.617.2 (Delta).

BACKGROUND: The impact of SARS-CoV-2 variants of concern (VOCs) on disease severity is unclear. In this retrospective study, we compared the outcomes of patients infected with B.1.1.7, B.1.351, and B.1.617.2 with wild-type strains from early 2020. METHODS: National surveillance data from January to May 2021 were obtained and outcomes in relation to VOCs were explored. Detailed patient-level data from all patients with VOC infection admitted to our center between December 2020 and May 2021 were analyzed. Clinical outcomes were compared with a cohort of 846 patients admitted from January to April 2020. RESULTS: A total of 829 patients in Singapore in the study period were infected with these 3 VOCs. After adjusting for age and sex, B.1.617.2 was associated with higher odds of oxygen requirement, intensive care unit admission, or death (adjusted odds ratio [aOR], 4.90; 95% confidence interval [CI]: 1.43-30.78). Of these patients, 157 were admitted to our center. After adjusting for age, sex, comorbidities, and vaccination, the aOR for pneumonia with B.1.617.2 was 1.88 (95% CI: .95-3.76) compared with wild-type. These differences were not seen with B.1.1.7 and B.1.351. Vaccination status was associated with decreased severity. B.1.617.2 was associated with significantly lower polymerase chain reaction cycle threshold (Ct) values and longer duration of Ct value ≤30 (median duration 18 days for B.1.617.2, 13 days for wild-type). CONCLUSIONS: B.1.617.2 was associated with increased severity of illness, and with lower Ct values and longer viral shedding. These findings provide impetus for the rapid implementation of vaccination programs.

Accuracy and feasibility in building a personalized 3D printed femoral pseudoaneurysm model for endovascular training.

BACKGROUND: The use of three-dimensional(3D) printing is broadly across many medical specialties. It is an innovative, and rapidly growing technology to produce custom anatomical models and medical conditions models for medical teaching, surgical planning, and patient education. This study aimed to evaluate the accuracy and feasibility of 3D printing in creating a superficial femoral artery pseudoaneurysm model based on CT scans for endovascular training. METHODS: A case of a left superficial femoral artery pseudoaneurysm was selected, and the 3D model was created using DICOM files imported into Materialise Mimics 22.0 and Materialise 3-Matic software, then printed using vat polymerization technology. Two 3D-printed models were created, and a series of comparisons were conducted between the 3D segmented images from CT scans and these two 3D-printed models. Ten comparisons involving internal diameters and angles of the specific anatomical location were measured. RESULTS: The study found that the absolute mean difference in diameter between the 3D segmented images and the 3D printed models was 0.179±0.145 mm and 0.216±0.143mm, respectively, with no significant difference between the two sets of models. Additionally, the absolute mean difference in angle was 0.99±0.65° and 1.00±0.91°, respectively, and the absolute mean difference in angle between the two sets of data was not significant. Bland-Altman analysis confirmed a high correlation in dimension measurements between the 3D-printed models and segmented images. Furthermore, the accuracy of a 3D-printed femoral pseudoaneurysm model was further tested through the simulation of a superficial femoral artery pseudoaneurysm coiling procedure using the Philips Azurion7 in the angiography room. CONCLUSIONS: 3D printing is a reliable technique for producing a high accuracy 3D anatomical model that closely resemble a patient's anatomy based on CT images. Additionally, 3D printing is a feasible and viable option for use in endovascular training and medical education. In general, 3D printing is an encouraging technology with diverse possibilities in medicine, including surgical planning, medical education, and medical device advancement.

Synthesis, DNA-binding abilities and anticancer activities of triazole-pyrrolo[2,1-c][1,4]benzodiazepines hybrid scaffolds.

We synthesized a new series of PBD-hybrid derivatives having tethered triazoles and investigated for their cytotoxicity. The studies indicated that cis-olefin compounds induce higher cytotoxicity with increase in the G1 cell cycle phase compared with the trans-compounds. Quantitative RT-PCR assay indicated that compounds (16a-d) induced G1 phase arrest through down-regulation of cyclin D1 and up-regulation of p21, p27, and p53 mRNA expressions. Compounds 16a-d induced A375 early apoptosis as detected by flow cytometry after double-staining with annexin V and propidium iodide. Moreover, the Western blot analysis showed that A375 treated by compounds (16a-d) resulted in decreased levels of Bcl-2 and Bcl-xL, increased levels of Bax and Bad, and caspase/PARP degradation to identify apoptotic cells.

External validation of the PRIORITY model in predicting COVID-19 critical illness in vaccinated and unvaccinated patients.

OBJECTIVES: Predictive scores are important tools for the triage of patients with coronavirus disease 2019. The PRIORITY score is advantageous because it does not require laboratory and radiologic information. However, the original development and validation cohorts studied only unvaccinated patients in early 2020. We aimed to externally validate the PRIORITY score in a cohort of patients with the novel delta and omicron variants of coronavirus disease 2019 and mixed vaccination status. METHODS: A total of 410 patients were included in a cross-sectional sampling of all patients admitted to the National Centre of Infectious Diseases on October 27, 2021. A further 102 and 136 patients with vaccine-breakthrough Delta and Omicron variant infection from April to August and December 2021, respectively, were also included. Variables at the time of admission were collected retrospectively from medical records and used to calculate the probability of deterioration using the PRIORITY model. RESULTS: Of the total 648 included patients, 447 (69.0%) were vaccinated. The mean age was 61.6 years (standard deviation ± 19.0 years), and 268 patients (41.4%) were female. A total of 112 patients (17.3%) met the primary outcome of developing critical illness or mortality. The performance of the score in this cohort was comparable with the original cohorts, with an area under the receiver operating characteristic curve for all patients of 0.794 (95% CI, 0.752-0.835; p < 0.001), regression coefficient of 1.069, and intercept of 0.04. Subgroup analysis of unvaccinated and vaccinated patients showed that performance was superior in vaccinated individuals, with an area under the receiver operating characteristic curve of 0.684 (95% CI, 0.608-0.760; p < 0.0001) and 0.831 (95% CI, 0.772-0.891; p < 0.0001), respectively. DISCUSSION: Our data support the continued use of the PRIORITY score in this era of novel variants and increased vaccination uptake.

Real-World Use of Sotrovimab for Pre-Emptive Treatment in High-Risk Hospitalized COVID-19 Patients: An Observational Cross-Sectional Study.

Data on use of monoclonal antibodies (mAbs) in hospitalized patients are limited. In this cross-sectional study, we evaluated the use of mAbs for early treatment of unvaccinated hospitalized patients with mild-to-moderate COVID-19. All inpatients at our center were screened on 27 October 2021. Primary outcome was in-hospital deterioration as defined by a composite of oxygen requirement, intensive care unit (ICU) admission, or mortality within 28 days of admission. Ninety-four out of 410 COVID-19 inpatients were included in the final analysis, of whom 19 (20.2%) received early treatment with sotrovimab. The median age was 73 years (IQR 61-83), and 35 (37.2%) were female. Although the treatment group was significantly older and had more comorbidities, there was a lower proportion of progression to oxygen requirement (31.6% vs. 54.7%), ICU admission (10.5% vs. 24.0%), or mortality (5.3% vs. 13.3%). Kaplan-Meier curves showed a significant difference in time to in-hospital deterioration (log-rank test, p = 0.043). Cox proportional hazards model for in-hospital deterioration showed that sotrovimab treatment was protective (hazard ratio, 0.41; 95% CI, 0.17-0.99; p = 0.047) after adjustment for baseline ISARIC deterioration score. Our findings support the use of sotrovimab for early treatment in hospitalized patients with mild-to-moderate COVID-19 at a high risk of disease progression.

Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals.

BACKGROUND: The accuracy of estimating microvascular invasion (MVI) preoperatively in hepatocellular carcinoma (HCC) by clinical observers is low. Most recent studies constructed MVI predictive models utilizing radiological and/or radiomics features extracted from computed tomography (CT) images. These methods, however, rely heavily on human experiences and require manual tumor contouring. We developed a deep learning-based framework for preoperative MVI prediction by using CT images of arterial phase (AP) with simple tumor labeling and without the need of manual feature extraction. The model was further validated on CT images that were originally scanned at multiple different hospitals. METHODS: CT images of AP were acquired for 309 patients from China Medical University Hospital (CMUH). Images of 164 patients, who took their CT scanning at 54 different hospitals but were referred to CMUH, were also collected. Deep learning (ResNet-18) and machine learning (support vector machine) models were constructed with AP images and/or patients' clinical factors (CFs), and their performance was compared systematically. All models were independently evaluated on two patient cohorts: validation set (within CMUH) and external set (other hospitals). Subsequently, explainability of the best model was visualized using gradient-weighted class activation map (Grad-CAM). RESULTS: The ResNet-18 model built with AP images and patients' clinical factors was superior than other models achieving a highest AUC of 0.845. When evaluating on the external set, the model produced an AUC of 0.777, approaching its performance on the validation set. Model interpretation with Grad-CAM revealed that MVI relevant imaging features on CT images were captured and learned by the ResNet-18 model. CONCLUSIONS: This framework provide evidence showing the generalizability and robustness of ResNet-18 in predicting MVI using CT images of AP scanned at multiple different hospitals. Attention heatmaps obtained from model explainability further confirmed that ResNet-18 focused on imaging features on CT overlapping with the conditions used by radiologists to estimate MVI clinically.

Environmental contamination in a coronavirus disease 2019 (COVID-19) intensive care unit-What is the risk?

BACKGROUND: The risk of environmental contamination by severe acute respiratory coronavirus virus 2 (SARS-CoV-2) in the intensive care unit (ICU) is unclear. We evaluated the extent of environmental contamination in the ICU and correlated this with patient and disease factors, including the impact of different ventilatory modalities. METHODS: In this observational study, surface environmental samples collected from ICU patient rooms and common areas were tested for SARS-CoV-2 by polymerase chain reaction (PCR). Select samples from the common area were tested by cell culture. Clinical data were collected and correlated to the presence of environmental contamination. Results were compared to historical data from a previous study in general wards. RESULTS: In total, 200 samples from 20 patient rooms and 75 samples from common areas and the staff pantry were tested. The results showed that 14 rooms had at least 1 site contaminated, with an overall contamination rate of 14% (28 of 200 samples). Environmental contamination was not associated with day of illness, ventilatory mode, aerosol-generating procedures, or viral load. The frequency of environmental contamination was lower in the ICU than in general ward rooms. Eight samples from the common area were positive, though all were negative on cell culture. CONCLUSION: Environmental contamination in the ICU was lower than in the general wards. The use of mechanical ventilation or high-flow nasal oxygen was not associated with greater surface contamination, supporting their use and safety from an infection control perspective. Transmission risk via environmental surfaces in the ICUs is likely to be low. Nonetheless, infection control practices should be strictly reinforced, and transmission risk via droplet or airborne spread remains.

The Pandemic Academy: Reflections of Infectious Diseases Fellows During COVID-19.

The COVID-19 pandemic has taken over the world at an unprecedented scale. As Infectious Diseases fellows, this has come straight into the heart of our specialty and created a unique impact on our training progress and perspective. Here, we reflect on our early experiences during the first three months of battling COVID-19 in Singapore and glean some lessons for this pandemic and beyond.

The Effect of Sample Site, Illness Duration, and the Presence of Pneumonia on the Detection of SARS-CoV-2 by Real-time Reverse Transcription PCR.

BACKGROUND: The performance of real-time reverse transcription polymerase chain reaction (rRT-PCR) for SARS-CoV-2 varies with sampling site(s), illness stage, and infection site. METHODS: Unilateral nasopharyngeal, nasal midturbinate, throat swabs, and saliva were simultaneously sampled for SARS-CoV-2 rRT-PCR from suspected or confirmed cases of COVID-19. True positives were defined as patients with at least 1 SARS-CoV-2 detected by rRT-PCR from any site on the evaluation day or at any time point thereafter, until discharge. Diagnostic performance was assessed and extrapolated for site combinations. RESULTS: We evaluated 105 patients; 73 had active SARS-CoV-2 infection. Overall, nasopharyngeal specimens had the highest clinical sensitivity at 85%, followed by throat, 80%, midturbinate, 62%, and saliva, 38%-52%. Clinical sensitivity for nasopharyngeal, throat, midturbinate, and saliva was 95%, 88%, 72%, and 44%-56%, respectively, if taken ≤7 days from onset of illness, and 70%, 67%, 47%, 28%-44% if >7 days of illness. Comparing patients with upper respiratory tract infection (URTI) vs pneumonia, clinical sensitivity for nasopharyngeal, throat, midturbinate, and saliva was 92% vs 70%, 88% vs 61%, 70% vs 44%, 43%-54% vs 26%-45%, respectively. A combination of nasopharyngeal plus throat or midturbinate plus throat specimen afforded overall clinical sensitivities of 89%-92%; this rose to 96% for persons with URTI and 98% for persons ≤7 days from illness onset. CONCLUSIONS: Nasopharyngeal specimens, followed by throat specimens, offer the highest clinical sensitivity for COVID-19 diagnosis in early illness. Clinical sensitivity improves and is similar when either midturbinate or nasopharyngeal specimens are combined with throat specimens. Upper respiratory specimens perform poorly if taken after the first week of illness or if there is pneumonia.

Associations of viral ribonucleic acid (RNA) shedding patterns with clinical illness and immune responses in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection.

OBJECTIVES: A wide range of duration of viral RNA shedding in patients infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been observed. We aimed to investigate factors associated with prolonged and intermittent viral RNA shedding in a retrospective cohort of symptomatic COVID-19 patients. METHODS: Demographic, clinical and laboratory data from hospitalised COVID-19 patients from a single centre with two consecutive negative respiratory reverse transcription-polymerase chain reaction (RT-PCR) results were extracted from electronic medical records. Kaplan-Meier survival curve analysis was used to assess the effect of clinical characteristics on the duration and pattern of shedding. Plasma levels of immune mediators were measured using Luminex multiplex microbead-based immunoassay. RESULTS: There were 201 symptomatic patients included. Median age was 49 years (interquartile range 16-61), and 52.2% were male. Median RNA shedding was 14 days (IQR 9-18). Intermittent shedding was observed in 77 (38.3%). We did not identify any factor associated with prolonged or intermittent viral RNA shedding. Duration of shedding was inversely correlated with plasma levels of T-cell cytokines IL-1ß and IL-17A at the initial phase of infection, and patients had lower levels of pro-inflammatory cytokines during intermittent shedding. CONCLUSIONS: Less active T-cell responses at the initial phase of infection were associated with prolonged viral RNA shedding, suggesting that early immune responses are beneficial to control viral load and prevent viral RNA shedding. Intermittent shedding is common and may explain re-detection of viral RNA in recovered patients.

Detection of air and surface contamination by SARS-CoV-2 in hospital rooms of infected patients.

Understanding the particle size distribution in the air and patterns of environmental contamination of SARS-CoV-2 is essential for infection prevention policies. Here we screen surface and air samples from hospital rooms of COVID-19 patients for SARS-CoV-2 RNA. Environmental sampling is conducted in three airborne infection isolation rooms (AIIRs) in the ICU and 27 AIIRs in the general ward. 245 surface samples are collected. 56.7% of rooms have at least one environmental surface contaminated. High touch surface contamination is shown in ten (66.7%) out of 15 patients in the first week of illness, and three (20%) beyond the first week of illness (p = 0.01, χ2 test). Air sampling is performed in three of the 27 AIIRs in the general ward, and detects SARS-CoV-2 PCR-positive particles of sizes >4 µm and 1-4 µm in two rooms, despite these rooms having 12 air changes per hour. This warrants further study of the airborne transmission potential of SARS-CoV-2.