Illness wellness scale: novel grading system for performance status of patients under surgical care.

BACKGROUND: Grading the illness using clinical parameters is essential for the daily progress of inpatients. Existing systems do not incorporate these parameters holistically. The study was designed to internally validate the illness wellness scale, based upon clinical assessment of the patients requiring surgical care, for their risk stratification and uniformity of communication between health care providers. METHODS: Prospective observational study conducted at a tertiary care hospital. An expert panel devised the scale, and it was modified after feedback from 100 health care providers. A total of 210 patients (150 for internal validation and 60 for inter-observer variability) who required care under the department of surgical disciplines were enrolled. This included patients presenting to surgery OPD, admitted to COVID/non-COVID surgical wards and ICUs, aged ≥16 years. RESULTS: The response rate of the final illness wellness scale was 95% with 86% positive feedback and a mean of 1.7 on the Likert scale for ease of use (one being very easy and five being difficult). It showed excellent consistency and minimal inter-observer variability with the intra-class correlation coefficient (ICC) above 0.9. In the internal validation cohort (n = 150), univariate and multivariable analysis of factors affecting mortality revealed that categorical risk stratification, age ≥ 60 years, presence or absence of co-morbidities especially hypertension and chronic kidney disease significantly affect mortality. CONCLUSIONS: The Illness wellness scale is an effective tool for uniformly communicating between health care professionals and is also a strong predictor of risk stratification and mortality in patients requiring surgical care.

Gut microbiota profile of COVID-19 patients: Prognosis and risk stratification (MicroCOVID-19 study).

Background: Gut microbiota is intrinsically associated with the immune system and can promote or suppress infectious diseases, especially viral infections. This study aims to characterize and compare the microbiota profile of infected patients with SARS-CoV-2 (milder or severe symptoms), non-infected people, and recovered patients. This is a national, transversal, observational, multicenter, and case-control study that analyzed the microbiota of COVID-19 patients with mild or severe symptoms at home, at the hospital, or in the intensive care unit, patients already recovered, and healthy volunteers cohabiting with COVID-19 patients. DNA was isolated from stool samples and sequenced in a NGS platform. A demographic questionnaire was also applied. Statistical analysis was performed in SPSS. Results: Firmicutes/Bacteroidetes ratios were found to be significantly lower in infected patients (1.61 and 2.57) compared to healthy volunteers (3.23) and recovered patients (3.89). Furthermore, the microbiota composition differed significantly between healthy volunteers, mild and severe COVID-19 patients, and recovered patients. Furthermore, Escherichia coli, Actinomyces naeslundii, and Dorea longicatena were shown to be more frequent in severe cases. The most common COVID-19 symptoms were linked to certain microbiome groups. Conclusion: We can conclude that microbiota composition is significantly affected by SARS-CoV-2 infection and may be used to predict COVID-19 clinical evolution. Therefore, it will be possible to better allocate healthcare resources and better tackle future pandemics.

Your Outpatient has Coronavirus Disease 2019: What Are the Treatment Options in the Current Severe Acute Respiratory Syndrome Coronavirus 2 Variant Climate?

Mutations accumulated by novel Severe Acute Respiratory Syndrome Coronavirus 2 Omicron sublineages contribute to evasion of previously effective monoclonal antibodies for treatment or prevention of Coronavirus Disease 2019 (COVID-19). Other authorized or approved antiviral drugs such as nirmatrelvir/ritonavir, remdesivir, and molnupiravir are, however, predicted to maintain activity against these sublineages and are key tools to reduce severe COVID-19 outcomes in vulnerable populations. A stepwise approach may be taken to target the appropriate antiviral drug to the appropriate patient, beginning with identifying whether a patient is at high risk for hospitalization or other complications of COVID-19. Among higher risk individuals, patient profile (including factors such as age, organ function, and comedications) and antiviral drug access inform suitable antiviral drug selection. When applied in targeted fashion, these therapies serve as a complement to vital ongoing nonpharmaceutical interventions and vaccination strategies that reduce morbidity and maximize protection against COVID-19.

Value of increased soluble suppressor tumorigenicity biomarker 2 (sST2) on admission as an indicator of severity in patients with COVID-19.

BACKGROUND: Soluble suppressor of tumorigenicity-2 (sST2) is a biomarker for heart failure and pulmonary injury. We hypothesize that sST2 could help predict severity of SARS-CoV-2 infections. METHODS: sST2 was analyzed in patients consecutively admitted for SARS-CoV-2 pneumonia. Other prognostic markers were also measured. In-hospital complications were registered, including death, ICU admission, and respiratory support requirements. RESULTS: 495 patients were studied (53% male, age: 57.6±17.6). At admission, median sST2 concentrations was 48.5ng/mL [IQR, 30.6-83.1ng/mL] and correlated with male gender, older age, comorbidities, other severity biomarkers, and respiratory support requirements. sST2 levels were higher in patients who died (n=45, 9.1%) (45.6 [28.0, 75.9]ng/mL vs. 144 [82.6, 319] ng/mL, p<0.001) and those admitted to ICU (n=46, 9.3%) (44.7 [27.5, 71.3] ng/mL vs. 125 [69.0, 262]ng/mL, p<0.001). sST2 levels>210ng/mL were a strong predictor of complicated in-hospital courses, with higher risk of death (OR, 39.3, CI95% 15.9, 103) and death/ICU (OR 38.3, CI95% 16.3-97.5) after adjusting for all other risk factors. The addition of sST2 enhanced the predictive capacity of mortality risk models. CONCLUSIONS: sST2 represents a robust severity predictor in COVID-19 and could be an important tool for identifying at-risk patients who may benefit from closer follow-up and specific therapies.

Postoperative surveillance in cranial and spinal tumor neurosurgery: when is this warranted?

OBJECTIVE: The outbreak of COVID-19 and the sudden increase in the number of patients requiring mechanical ventilation significantly affected the management of neurooncological patients. Hospitals were forced to reallocate already scarce human resources to maximize intensive care unit (ICU) capacities, resulting in a significant postponement of elective procedures for patients with brain and spinal tumors, who traditionally require elective postoperative surveillance on ICU or intermediate care wards. This study aimed to characterize those patients in whom postoperative monitoring is required by analyzing early postoperative complications and associated risk factors. METHODS: All patients included in the analysis experienced benign or malignant cerebral or intradural tumors and underwent surgery between September 2017 and May 2019 at University Hospital Münster, Germany. Patient data were generated from a semiautomatic, prospectively designed database. The occurrence of adverse events within 24 hours and 30 days postoperatively-including unplanned reoperation, postoperative hemorrhage, CSF leakage, and pulmonary embolism-was chosen as the primary outcome measure. Furthermore, reasons and risk factors that led to a prolonged stay on the ICU were investigated. By performing multivariable logistic regression modeling, a risk score for early postoperative adverse events was calculated by assigning points based on beta coefficients. RESULTS: Eight hundred eleven patients were included in the study. Eleven patients (1.4%) had an early adverse event within 24 hours, which was either an unplanned reoperation (0.9%, n = 7) or a pulmonary embolism (0.5%, n = 4) within 24 hours. To predict the incidence of early postoperative complications, a score was developed including the number of secondary diagnoses, BMI, and incision closure time, termed the SOS score. According to this score, 0.3% of the patients were at low risk, 2.5% at intermediate risk, and 12% at high risk (p < 0.001). CONCLUSIONS: Postoperative surveillance in cranial and spinal tumor neurosurgery might only be required in a distinct patient collective. In this study, the authors present a new score allowing efficient prediction of the likelihood of early adverse events in patients undergoing neurooncological procedures, thus helping to stratify the necessity for ICU or intermediate care unit beds. Nevertheless, validation of the score in a multicenter prospective setting is needed.

Using NEWS2 to triage newly admitted patients with COVID-19.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has spread globally and caused a major worldwide health crisis. Patients who are affected more seriously by COVID-19 usually deteriorate rapidly and need further intensive care. AIMS AND OBJECTIVES: We aimed to assess the performance of the National Early Warning Score 2 (NEWS2) as a risk stratification tool to discriminate newly admitted patients with COVID-19 at risk of serious events. DESIGN: We conducted a retrospective single-centre case-control study on 200 unselected patients consecutively admitted in March 2020 in a public general hospital in Wuhan, China. METHODS: The following serious events were considered: mortality, unplanned intensive care unit (ICU) admission, and non-invasive ventilation treatment. Receiver operating characteristic (ROC) analysis and logistic regression analysis were used to quantify the association between outcomes and NEWS2. RESULTS: There were 12 patients (6.0%) who had serious events, where 7 patients (3.5%) experienced unplanned ICU admissions. The area under the ROC curve (AUROC) and cut-off of NEWS2 for the composite outcome were 0.83 and 3, respectively. For patients with NEWS2 ≥ 4, the odds of being at risk for serious events was 16.4 (AUROC = 0.74), while for patients with NEWS2 ≥ 7, the odds of being at risk for serious events was 18.2 (AUROC = 0.71). CONCLUSIONS: NEWS2 has an appropriate ability to triage newly admitted patients with COVID-19 into three levels of risk: low risk (NEWS2 = 0-3), medium risk (NEWS2 = 4-6), and high risk (NEWS2 ≥ 7). RELEVANCE TO CLINICAL PRACTICE: Using NEWS2 may help nurses in early identification of at-risk COVID-19 patients and clinical nursing decision-making. Using NEWS2 to triage new patients with COVID-19 may help nurses provide more appropriate level of care and medical resources allocation for patients safety.

Lung Ultrasound Findings Associated With COVID-19 ARDS, ICU Admission, and All-Cause Mortality.

BACKGROUND: As lung ultrasound (LUS) has emerged as a diagnostic tool in patients with COVID-19, we sought to investigate the association between LUS findings and the composite in-hospital outcome of ARDS incidence, ICU admission, and all-cause mortality. METHODS: In this prospective, multi-center, observational study, adults with laboratory-confirmed SARS-CoV-2 infection were enrolled from non-ICU in-patient units. Subjects underwent an LUS evaluating a total of 8 zones. Images were analyzed off-line, blinded to clinical variables and outcomes. A LUS score was developed to integrate LUS findings: ≥ 3 B-lines corresponded to a score of 1, confluent B-lines to a score of 2, and subpleural or lobar consolidation to a score of 3. The total LUS score ranged from 0-24 per subject. RESULTS: Among 215 enrolled subjects, 168 with LUS data and no current signs of ARDS or ICU admission (mean age 59 y, 56% male) were included. One hundred thirty-six (81%) subjects had pathologic LUS findings in ≥ 1 zone (≥ 3 B-lines, confluent B-lines, or consolidations). Markers of disease severity at baseline were higher in subjects with the composite outcome (n = 31, 18%), including higher median C-reactive protein (90 mg/L vs 55, P < .001) and procalcitonin levels (0.35 µg/L vs 0.13, P = .033) and higher supplemental oxygen requirements (median 4 L/min vs 2, P = .001). However, LUS findings and score did not differ significantly between subjects with the composite outcome and those without, and were not associated with outcomes in unadjusted and adjusted logistic regression analyses. CONCLUSIONS: Pathologic findings on LUS were common a median of 3 d after admission in this cohort of non-ICU hospitalized subjects with COVID-19 and did not differ among subjects who experienced the composite outcome of incident ARDS, ICU admission, and all-cause mortality compared to subjects who did not. These findings should be confirmed in future investigations. The study is registered at Clinicaltrials.gov (NCT04377035).

Effective prognostic and clinical risk stratification in COVID-19 using multimodality biomarkers.

In acute coronavirus disease 19 (COVID-19) patients, effective clinical risk stratification has important implications on treatment and therapeutic resource distribution. This article reviews the evidence behind a wide range of biomarkers with prognostic value in COVID-19. Patient characteristics and co-morbidities, such as cardiovascular and respiratory diseases, are associated with increased mortality risk. Peripheral oxygen saturation and arterial oxygenation are predictive of severe respiratory compromise, whereas risk scores such as the 4C-score enable multi-factorial prognostic risk estimation. Blood tests such as markers of inflammation, cardiac injury and d-dimer and abnormalities on electrocardiogram are linked to inpatient prognosis. Of the imaging modalities, lung ultrasound and echocardiography enable the bedside assessment of prognostic abnormalities in COVID-19. Chest radiograph (CXR) and computed tomography (CT) can inform about prognostic pulmonary pathologies, whereas cardiovascular CT detects high-risk features such as coronary artery and aortic calcification. Dynamic changes in biomarkers, such as blood tests, CXR, CT and electrocardiogram findings, can further inform about disease severity and prognosis. Despite the vast volumes of existing evidence, several gaps exist in our understanding of COVID-19 biomarkers. First, the pathophysiological basis on which these markers can foretell prognosis in COVID-19 remains poorly understood. Second, certain under-explored tests such as thoracic impedance assessment and cardiovascular magnetic resonance imaging deserve further investigation. Lastly, the prognostic values of most biomarkers in COVID-19 are derived from retrospective analyses. Prospective studies are required to validate these markers for guiding clinical decision-making and to facilitate their translation into clinical management pathways.

Systematic lung ultrasound in Omicron-type vs. wild-type COVID-19.

AIMS: Preliminary data suggested that patients with Omicron-type-Coronavirus-disease-2019 (COVID-19) have less severe lung disease compared with the wild-type-variant. We aimed to compare lung ultrasound (LUS) parameters in Omicron vs. wild-type COVID-19 and evaluate their prognostic implications. METHODS AND RESULTS: One hundred and sixty-two consecutive patients with Omicron-type-COVID-19 underwent LUS within 48 h of admission and were compared with propensity-matched wild-type patients (148 pairs). In the Omicron patients median, first and third quartiles of the LUS-score was 5 [2-12], and only 9% had normal LUS. The majority had either mild (≤5; 37%) or moderate (6-15; 39%), and 15% (≥15) had severe LUS-score. Thirty-six percent of patients had patchy pleural thickening (PPT). Factors associated with LUS-score in the Omicron patients included ischaemic-heart-disease, heart failure, renal-dysfunction, and C-reactive protein. Elevated left-filling pressure or right-sided pressures were associated with the LUS-score. Lung ultrasound-score was associated with mortality [odds ratio (OR): 1.09, 95% confidence interval (CI): 1.01-1.18; P = 0.03] and with the combined endpoint of mortality and respiratory failure (OR: 1.14, 95% CI: 1.07-1.22; P < 0.0001). Patients with the wild-type variant had worse LUS characteristics than the matched Omicron-type patients (PPT: 90 vs. 34%; P < 0.0001 and LUS-score: 8 [5, 12] vs. 5 [2, 10], P = 0.004), irrespective of disease severity. When matched only to the 31 non-vaccinated Omicron patients, these differences were attenuated. CONCLUSION: Lung ultrasound-score is abnormal in the majority of hospitalized Omicron-type patients. Patchy pleural thickening is less common than in matched wild-type patients, but the difference is diminished in the non-vaccinated Omicron patients. Nevertheless, even in this milder form of the disease, the LUS-score is associated with poor in-hospital outcomes.

Plasma Troponins Identify Patients with Very Low-Risk Acute Pulmonary Embolism.

INTRODUCTION: Although in the non-vitamin K oral anticoagulants (NOAC) era majority of low-risk acute pulmonary embolism (APE) patients can be treated at home, identifying those at very low risk of clinical deterioration may be challenging. We aimed to propose the risk stratification algorithm in sPESI 0 point APE patients, allowing them to select candidates for safe outpatient treatment. MATERIALS AND METHODS: Post hoc analysis of a prospective study of 1151 normotensive patients with at least segmental APE. In the final analysis, we included 409 sPESI 0 point patients. Cardiac troponin assessment and echocardiographic examination were performed immediately after admission. Right ventricular dysfunction was defined as the right ventricle/left ventricle ratio (RV/LV) > 1.0. The clinical endpoint (CE) included APE-related mortality and/or rescue thrombolysis and/or immediate surgical embolectomy in patients with clinical deterioration. RESULTS: CE occurred in four patients who had higher serum troponin levels than subjects with a favorable clinical course (troponin/ULN: 7.8 (6.4-9.4) vs. 0.2 (0-1.36) p = 0.000). Receiver operating characteristic (ROC) analysis showed that the area under the curve for troponin in the prediction of CE was 0.908 (95% CI 0.831-0.984; p < 0.001). We defined the cut-off value of troponin at >1.7 ULN with 100% PPV for CE. In univariate and multivariate analysis, elevated serum troponin level was associated with an increased risk of CE, whereas RV/LV > 1.0 was not. CONCLUSIONS: Solely clinical risk assessment in APE is insufficient, and patients with sPESI 0 points require further assessment based on myocardial damage biomarkers. Patients with troponin levels not exceeding 1.7 ULN constitute the group of "very low risk" with a good prognosis.

Use and Prognostic Implications of Cardiac Troponin in COVID-19.

Myocardial injury is common in patients with COVID-19 and is associated with an adverse prognosis. Cardiac troponin (cTn) is used to detect myocardial injury and assist with risk stratification in this population. SARS-CoV-2 infection can play a role in the pathogenesis of acute myocardial injury due to both direct and indirect damage to the cardiovascular system. Despite the initial concerns about an increased incidence of acute myocardial infarction (MI), most cTn increases are related to chronic myocardial injury due to comorbidities and/or acute nonischemic myocardial injury. This review will discuss the latest findings on this topic.

A Comparison of ICU Mortality Scoring Systems Applied to COVID-19.

Background Over the past three years, COVID-19 has been a major source of mortality in intensive care units around the world. Many scoring systems have been developed to estimate mortality in critically ill patients. Our intent with this study was to compare the efficacy of these systems when applied to COVID-19. Methods The was a multicenter, retrospective cohort study of critically ill patients with COVID-19 admitted to 16 hospitals in Texas from February 2020 to March 2022. The Simplified Acute Physiology Score (SAPS) II, Acute Physiology and Chronic Health Evaluation (APACHE) II, Sequential Organ Failure Assessment (SOFA) score, and 4C Mortality scores were calculated on the initial day of ICU admission. Primary endpoints were all-cause mortality, ICU length of stay, and hospital length of stay. Results Initially, 62,881 patient encounters were assessed, and the cohort of 292 was selected based on the inclusion of the requisite values for each of the scoring systems. The median age was 56 +/- 14.93 years and 61% of patients were male. Mortality was defined as patients who expired or were discharged to hospice and was 78%. The different scoring systems were compared using logistic regression, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) analysis to compare the accuracy of prediction of the mortality and length of stay. The multivariate analysis showed that SOFA, APACHE II, SAPS II, and 4C scores were all significant predictors of mortality. The SOFA score had the highest AUC, though the confidence intervals for all of the models overlap therefore one model could not be considered superior to any of the others. Linear regression was performed to evaluate the models' ability to predict ICU and hospital length of stay, and none of the tested systems were found to be significant predictors of length of stay. Conclusion The SOFA, APACHE II, ISARIC 4-C, and SAPS II scores all accurately predicted mortality in critically ill patients with COVID-19. The SOFA score trended to perform the best.

Risk Stratification Model for Severe COVID-19 Disease: A Retrospective Cohort Study.

BACKGROUND: Risk stratification models have been developed to identify patients that are at a higher risk of COVID-19 infection and severe illness. Objectives To develop and implement a scoring tool to identify COVID-19 patients that are at risk for severe illness during the Omicron wave. METHODS: This is a retrospective cohort study that was conducted in Israel's second-largest healthcare maintenance organization. All patients with a new episode of COVID-19 between 26 November 2021 and 18 January 2022 were included. A model was developed to predict severe illness (COVID-19-related hospitalization or death) based on one-third of the study population (the train group). The model was then applied to the remaining two-thirds of the study population (the test group). Risk score sensitivity, specificity, and positive predictive value rates, and receiver operating characteristics (ROC) were calculated to describe the performance of the model. RESULTS: A total of 409,693 patients were diagnosed with COVID-19 over the two-month study period, of which 0.4% had severe illness. Factors that were associated with severe disease were age (age > 75, OR-70.4, 95% confidence interval [CI] 42.8-115.9), immunosuppression (OR-4.8, 95% CI 3.4-6.7), and pregnancy (5 months or more, OR-82.9, 95% CI 53-129.6). Factors that were associated with a reduced risk for severe disease were vaccination status (patients vaccinated in the previous six months OR-0.6, 95% CI 0.4-0.8) and a prior episode of COVID-19 (OR-0.3, 95% CI 0.2-0.5). According to the model, patients who were in the 10th percentile of the risk severity score were considered at an increased risk for severe disease. The model accuracy was 88.7%. CONCLUSIONS: This model has allowed us to prioritize patients requiring closer follow-up by their physicians and outreach services, as well as identify those that are most likely to benefit from anti-viral treatment during the fifth wave of infection in Israel, dominated by the Omicron variant.

The coronavirus disease pandemic among adult congenital heart disease patients and the lessons learnt - results of a prospective multicenter european registry.

Background: At the beginning of the COVID-19 pandemic, professionals in charge of particularly vulnerable populations, such as adult congenital heart disease (ACHD) patients, were confronted with difficult decision-making. We aimed to assess changes in risk stratification and outcomes of ACHD patients suffering from COVID-19 between March 2020 and April 2021. Methods and results: Risk stratification among ACHD experts (before and after the first outcome data were available) was assessed by means of questionnaires. In addition, COVID-19 cases and the corresponding patient characteristics were recorded among participating centres. Predictors for the outcome of interest (complicated disease course) were assessed by means of multivariable logistic regression models calculated with cluster-robust standard errors. When assessing the importance of general and ACHD specific risk factors for a complicated disease course, their overall importance and the corresponding risk perception among ACHD experts decreased over time. Overall, 638 patients (n = 168 during the first wave and n = 470 during the subsequent waves) were included (median age 34 years, 52% women). Main independent predictors for a complicated disease course were male sex, increasing age, a BMI >25 kg/m2, having ≥2 comorbidities, suffering from a cyanotic heart disease or having suffered COVID-19 in the first wave vs. subsequent waves. Conclusions: Apart from cyanotic heart disease, general risk factors for poor outcome in case of COVID-19 reported in the general population are equally important among ACHD patients. Risk perception among ACHD experts decreased during the course of the pandemic.

The added predictive role of echocardiography in patients with mild or moderate Coronavirus Disease 2019.

AIMS: Recently, several therapeutic agents have decreased the progression to critical disease in patients with mild/moderate COVID-19. However, their use is limited to patients with ≥1 clinical risk factor. We aimed to evaluate echocardiographic features that may aid in risk stratification for patients with mild/moderate COVID-19. METHODS: 278 consecutive patients with mild/moderate COVID-19 underwent prospective clinical and echocardiographic examination, ≤7 days of symptoms, as part of a predefined protocol. Analysis to identify echocardiographic predictors of outcome was performed. RESULTS: In the multivariable risk model, E/e', TAPSE, and pulmonary acceleration time (PAT) were associated with the composite outcome (p = 0.01, 0.005, 0.05, respectively). Stepwise analyses showed that the addition of echocardiography on top of having ≥1 clinical risk factor and even using each parameter separately improved the prediction of outcomes. If patients were re-categorized as high risk only if having both ≥1 clinical and ≥ 1 echocardiography risk parameter (E/e' > 8, TAPSE<1.8 cm, PAT<90 msec), or even one echo parameter separately, then specificity, positive predictive value, and accuracy improved. If patients were re-classified as high risk if having either ≥1 clinical risk factor or ≥ 1 high-risk echocardiography parameter, all five individuals who were missed by the ≥1 risk factor "rule", were correctly diagnosed as high risk. Similar analyses, including only patients with mild disease, showed that the addition of TAPSE improved the prediction of outcomes. CONCLUSIONS: In patients with mild/moderate COVID-19, a very limited echocardiographic exam is sufficient for improved outcome prediction, and may improve resource allocation for new anti-COVID-19 agents. TRANSLATIONAL ASPECT OF THE WORK: We show that among patients with mild/moderate COVID-19, several easily obtained echocardiographic findings are strongly correlated with mortality or progression to the need for invasive/non-invasive mechanical ventilation, even when adjusted for the presence or absence of ≥1 clinical risk factor. Furthermore, even a limited echocardiographic exam is sufficient to develop a strategy of risk stratification. We believe that our data have important implications for the clinicians involved in the acute treatment of patients with COVID-19.

Creating Audio-Visual Content for a Personalized Prevention Programme in Coronary Heart Disease

Coronary heart disease (CHD) remains the leading cause of premature death worldwide. Better risk stratification tools and personalized care of patients are needed for reducing the morbidity and mortality of CHD and the associated economic burden. However, contemporary e-learning solutions lack personalization and shared decision making and as a result, overwhelm patients with large amounts of information. CoroPrevention is a multiyear, EU-funded Horizon 2020 research project aiming to shape and implement a personalized secondary prevention strategy for patients with established CHD. As a part of the project, new digital tools will also be validated. In this paper, we discuss the process of creating audio-visual content for the CoroPrevention mobile application during the challenging COVID-19 pandemic. © 2022 IEEE.

COVID-19 Vaccination Prioritization Strategies in Malaysia: A Retrospective Analysis of Early Evidence.

The coronavirus disease 2019 (COVID-19) that can cause extreme acute respiratory syndrome has posed a catastrophic threat to public health. The vaccines had indeed restored optimism and, after more than two years of battling the pandemic, there is renewed hope for the transition to endemicity. At the start of vaccination efforts, when supply shortages of vaccines were inevitable, every nation determined the high-risk population groups to be given priority for the COVID-19 vaccines. In this paper, the characteristics of the initial COVID-19 vaccine recipients in Malaysia are described. In line with the policies of many other countries, Malaysia firstly inoculated frontline healthcare workers, and subsequently the list of front liners grew to include defense and security personnel and those involved in the provision of essential services. People with disabilities or those with special needs and several underlying medical conditions that increased their risk of developing severe COVID-related illnesses were included in the priority categories. These included patients with severe lung disease, chronic heart disease, chronic kidney disease, chronic liver disease, neurological disease, diabetes mellitus and obesity in adults, splenic dysfunction, and severe mental illness. With little information and under circumstances of great uncertainty, the Health Ministry of a middle-income country had developed a vaccination priority-list based on the disease's epidemiology and clinical data, vaccine type, operational considerations, and risk evaluation. Early evidence was presented and suggested that the full vaccination with any of the three predominant vaccines (AZD1222, BNT162b2, and CoronaVac) in the country had been highly effective in preventing COVID-19 infections, COVID-19-related ICU admissions, and death. As many SARS-CoV-2 variants of concern (VoC), such as the Omicron BA.2/4/5, are emerging, future vaccination strategies may necessitate the need to change the immunogen of the vaccine, as well as considerations for when to give high-risk groups booster injections. These considerations are valuable for future planning by policymakers and healthcare providers to make vaccination policy and decisions, especially for the inclusion of the COVID-19 vaccines into national immunization programs.

Acute phase characteristics and long-term complications of pulmonary embolism in COVID-19 compared to non-COVID-19 cohort: a large single-centre study.

BACKGROUND: To compare the severity of pulmonary embolism (PE) and the long-term complications between patients with and without COVID-19, and to investigate whether the tools for risk stratification of death are valid in this population. METHODS: We retrospectively included hospitalized patients with PE from 1 January 2016 to 31 December 2022. Comparisons for acute episode characteristics, risk stratification of the PE, outcomes, and long-term complications were made between COVID and non-COVID patients. RESULTS: We analyzed 116 (27.5%) COVID patients and 305 (72.4%) non-COVID patients. In patients with COVID-19, the traditional risk factors for PE were absent, and the incidence of deep vein thrombosis was lower. COVID patients showed significantly higher lymphocyte count, lactate dehydrogenase, lactic acid, and D-dimer levels. COVID patients had PE of smaller size (12.3% vs. 25.5% main pulmonary artery, 29.8% vs. 37.1% lobar, 44.7% vs. 29.5% segmental and 13.2% vs. 7.9% subsegmental, respectively; p < 0.001), less right ventricular dysfunction (7.7% vs. 17.7%; p = 0.007) and higher sPESI score (1.66 vs. 1.11; p < 0.001). The need for mechanical ventilation was significantly higher in COVID patients (8.6% vs. 1.3%; p < 0.001); However, the in-hospital death was less (5.2% vs. 10.8%; p = 0.074). The incidence of long-term complications was lower in COVID cohort (p < 0.001). PE severity assessed by high sPESI and intermediate and high-risk categories were independently associated with in-hospital mortality in COVID patients. CONCLUSION: The risk of in-hospital mortality and the incidence of long-term complications were lower in COVID-19. The usual tools for risk stratification of PE are valid in COVID patients.