COVID-19 medical management including World Health Organization (WHO) suggested management strategies

A deep learning-based approach for predicting COVID-19 diagnosis

This paper focuses on forecasting the total count of confirmed COVID-19 cases in Saudi Arabia through a range of methodologies, including ARIMA, mathematical modeling, and deep learning network (DQN) techniques. Its primary aim is to anticipate the verified COVID-19 cases in Saudi Arabia, aiding in decision-making for life-saving interventions by enhancing awareness of COVID-19 infection. Mathematical modeling and ARIMA are employed for their efficacy in forecasting, while DQN approaches, particularly through comparative analysis, are utilized for prediction. This comparative analysis evaluates the predictive capacities of ARIMA, mathematical modeling, and DQN techniques, aiming to pinpoint the most reliable method for forecasting positive COVID-19 cases. The modeling encompasses COVID-19 cases in Saudi Arabia, the United Kingdom (UK), and Tunisia (TU) spanning from 2020 to 2021. Predicting the number of individuals likely to test positive for COVID-19 poses a challenge, requiring adherence to fundamental assumptions in mathematical and ARIMA projections. The proposed methodology was implemented on a local server. The DQN algorithm formulates a reward function to uphold target functional performance while balancing training and testing periods. The findings indicate that DQN technology surpasses conventional approaches in efficiency and accuracy for predictions.

Artificial intelligence in healthcare: combining deep learning and Bayesian optimization to forecast COVID-19 confirmed cases

Healthcare is a topic of significant concern within the academic and business sectors. The COVID-19 pandemic has had a considerable effect on the health of people worldwide. The rapid increase in cases adversely affects a nation's economy, public health, and residents' social and personal well-being. Improving the precision of COVID-19 infection forecasts can aid in making informed decisions regarding interventions, given the pandemic's harmful impact on numerous aspects of human life, such as health and the economy. This study aims to predict the number of confirmed COVID-19 cases in Saudi Arabia using Bayesian optimization (BOA) and deep learning (DL) methods. Two methods were assessed for their efficacy in predicting the occurrence of positive cases of COVID-19. The research employed data from confirmed COVID-19 cases in Saudi Arabia (SA), the United Kingdom (UK), and Tunisia (TU) from 2020 to 2021. The findings from the BOA model indicate that accurately predicting the number of COVID-19 positive cases is difficult due to the BOA projections needing to align with the assumptions. Thus, a DL approach was utilized to enhance the precision of COVID-19 positive case prediction in South Africa. The DQN model performed better than the BOA model when assessing RMSE and MAPE values. The model operates on a local server infrastructure, where the trained policy is transmitted solely to DQN. DQN formulated a reward function to amplify the efficiency of the DQN algorithm. By examining the rate of change and duration of sleep in the test data, this function can enhance the DQN model's training. Based on simulation findings, it can decrease the DQN work cycle by roughly 28% and diminish data overhead by more than 50% on average.

SARS-CoV-2 infection and dysregulation of nuclear factor erythroid-2-related factor 2 (Nrf2) pathway

Coronavirus disease 2019 (COVID-19) is a recent pandemic caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) leading to pulmonary and extra-pulmonary manifestations due to the development of oxidative stress (OS) and hyperinflammation. The underlying cause for OS and hyperinflammation in COVID-19 may be related to the inhibition of nuclear factor erythroid 2-related factor 2 (Nrf2), a master regulator of antioxidative responses and cellular homeostasis. The Nrf2 pathway inhibits the expression of pro-inflammatory cytokines and the development of cytokine storm and OS in COVID-19. Nrf2 activators can attenuate endothelial dysfunction (ED), renin-angiotensin system (RAS) dysregulation, immune thrombosis, and coagulopathy. Hence, this review aimed to reveal the potential role of the Nrf2 pathway and its activators in the management of COVID-19. As well, we tried to revise the mechanistic role of the Nrf2 pathway in COVID-19.

Insights on Covid-19 with superimposed pulmonary histoplasmosis: The possible nexus

A novel coronavirus (CoV) known as severe acute respiratory syndrome CoV type 2 is the causative agent for the development of CoV disease 2019 (Covid-19). Covid-19 may increase the risk of developing pulmonary histoplasmosis due to immune dysregulation. In addition, Covid-19 may enhance the propagation of acute pulmonary histoplasmosis due to lung injury and inflammation, and using corticosteroids in severely affected Covid-19 patients may reactivate latent pulmonary histoplasmosis. Likewise, activation of inflammatory signaling pathways during H. capsulatum infection may increase the severity of Covid-19 and vice versa. Furthermore, lymphopenia in Covid-19 may increase the risk for the progress of pulmonary histoplasmosis besides activation of inflammatory signaling pathways during H. capsulatum infection may increase the severity of Covid-19 and vice versa. Therefore, this critical review aimed to find the potential link between Covid-19 pneumonia and pulmonary histoplasmosis concerning the immunological response.

Knowledge, attitude, and practice (KAP) of antimicrobial prescription and its resistance among health care providers in the COVID-19 era: A cross sectional study

Antimicrobial resistance (AMR) is considered as a global health and development threat. During COVID-19 pandemic, there has been an increase in antimicrobial resistance. Health care providers (HCPs) play the main role in facing antibiotic resistance because they have the authority to prescribe antibiotics during clinical practice as well as in promoting patients' compliance with therapies and avoid self-medication. So, this study will serve as an important source of information in context with Covid19 pandemic in Egypt. The data was collected using a validated standardized self-administered online questionnaire compromised of four sections: socio-demographic data of the HCPs, the general knowledge on antibiotics and AMR, the HCP attitude towards antibiotic prescription and AMR and the practice in applying the appropriate antibiotic prescription. Most of HCPs (93.7%) recorded good knowledge level about antibiotic prescription and antimicrobial resistance with mean score of knowledge13.21 ± 1.83. About 79% of HCPs recorded a positive attitude towards proper antibiotic prescription with mean score of attitudes 63.02 ± 7.68. Fifty four percent of HCPs demonstrated a good level of practice with mean score of practice 9.75 ± 2.17. In conclusion, HCPs in our study have a good level of knowledge and attitude about antibiotics. However lower level of proper practice towards the problem of AMR in COVID19 era was noticed. Implementation of effective policies and guidelines is crucial to evaluate the antimicrobial use especially in the COVID-19 era to reduce the unintended consequences of the misuse of antibiotics and its impact on AMR.

[Functional parameters and affecting factors in post-COVID period]

Introduction

Post-COVID period is considered to be 12 weeks after the COVID-19 infection. Patients in the post-COVID period may have prolonged or newly developed symptoms. Depending on the prolonged effects of the disease, respiratory and functional parameters may be affected. The aim of the study is to investigate the effect of COVID-19 infection on respiratory and functional parameters in the post-COVID period.

Materials and Methods

A cross-sectional study was conducted to evaluate the functional parameters of patients with COVID-19 in the post-COVID period. Subjects with a history of microbiologically proven COVID-19 infection were evaluated with 6-minute walk test results, Borg, and MRC results at least 12 weeks after COVID-19 infection. The relationship between demographic characteristics, comorbidities, vaccination status, and severity of disease with 6-minute walk test results and dyspnea scales in the post-COVID period was investigated.

Result

Two hundred seventeen patients were included in the study. The mean age of the patients was 48.6 ± 14.9 years and 126 (58.1%) of them were female. 142 (65.4%) of the patients were completely vaccinated against COVID-19 and 75 (34.6%) patients were incompletely vaccinated or unvaccinated. 158 (72.8%) patients had mild disease, 51 (23.5%) patients had moderate disease, and eight (3.7%) patients had severe disease. Those with a history of moderate or severe disease had significantly worsened functional parameters in the postCOVID period compared to those with mild COVID-19. The Borg scale and MRC dyspnea scale values were significantly higher in women (p= 0.008, p= 0.002, respectively). Functional parameters of those who were completely vaccinated against COVID-19 and those who were incompletely or unvaccinated individuals in the post-COVID period were similar.

Conclusions

The functional parameters of people with moderate or severe COVID-19 disease were found to be significantly impaired in the post-COVID period. While the effect of smoking and vaccination status on functional parameters in the post-COVID period could not be demonstrated, disease severity and accompanying comorbidity were found to be effective.

Saudi Nurse Interns' Experiences during the COVID-19 Pandemic: A Thematic Approach

BACKGROUND

The learning process for nurses, including internships, was affected during the COVID-19 pandemic, which may have made the nurse internship program more challenging and stressful for participants. Therefore, it is significant to explore the experiences of nurse interns during COVID-19.

AIM

This study aimed to explore Saudi nurse interns' field experiences during the pandemic.

DESIGN

The study utilised descriptive phenomenological qualitative research and a thematic approach.

METHODS

A total of 19 nurse interns participated in the study, which was conducted in Saudi Arabia. Participants undertook an internship program at different government hospitals in five cities in Saudi Arabia. Unstructured individual interviews were conducted to gather data from the participants.

RESULTS

The findings revealed five themes: being passionate, lacking knowledge and skills, being concerned about their families, being cautious, and being unoriented.

CONCLUSION

The study findings document that the struggles of nurse interns in their internship programs during COVID-19 were related to their lack of knowledge, their family, and the working environment.

National IoMT platform strategy portfolio decision model under the COVID-19 environment: based on the financial and non-financial value view

The Internet of Medical Things (IoMT) is an emerging technology in the healthcare revolution which provides real-time healthcare information communication and reasonable medical resource allocation. The COVID-19 pandemic has had a significant effect on people's lives and has affected healthcare capacities. It is important for integrated IoMT platform development to overcome the global pandemic challenges. This study proposed the national IoMT platform strategy portfolio decision-making model from the non-financial (technology, organization, environment) and financial perspectives. As a solution to the decision problem, initially, the decision-making trial and evaluation laboratory (DEMATEL) technology were employed to capture the cause-effect relationship based on the perspectives and criteria obtained from the insight of an expert team. The analytic network process (ANP) and pairwise comparisons were then used to determine the weights for the strategy. Simultaneously, this study incorporated IoMT platform resource limitations into the zero-one goal programming (ZOGP) method to obtain an optimal portfolio selection for IoMT platform strategy planning. The results showed that the integrated MCDM method produced reasonable results for selecting the most appropriate IoMT platform strategy portfolio when considering resource constraints such as system installation costs, consultant fees, infrastructure costs, reduction of medical staff demand, and improvement rates for diagnosis efficiency. The decision-making model of the IoMT platform in this study was conclusive and significantly compelling to aid government decision makers in concentrating their efforts on planning IoMT strategies in response to various pandemic and medical resource allocations.

COVID-19'dan iyileşme sonrası tedavi rejimlerine göre biventriküler miyokard geriliminin karşılaştırılması

Purpose: The effects of different COVID-19 therapeutic strategies on cardiac function are uncertain. Therefore, this study aimed to evaluate the effects of different medical treatments on biventricular function in patients who had recovered from COVID-19. Materials and Methods: Speckle-tracking echocardiography was performed to examine the biventricular myocardial function of patients at follow-up visits after recovery from COVID-19. The patients were divided into two groups based on the medication they used during the active disease: favipiravir (FAV; n = 60) or hydroxychloroquine (HCQ; n = 60). A comparison was made with risk factor–matched controls (n = 41). Results: A total of 161 patients were included in the study. The left ventricular end-diastolic volume, end-systolic volume, end-diastolic diameter, and end-systolic diameter were higher in the HCQ and FAV groups compared to the controls, while the left ventricular ejection fraction was similar between all the groups. The right ventricular diameter was increased, and the systolic pulmonary artery pressure was higher in the HCQ and FAV groups compared to the controls. The left ventricular global longitudinal strain (-18±6.6 vs. -19.7±4.4 vs. -20.4±5, respectively), the right ventricular global longitudinal strain (-19.8±7.5 vs. -22.2±6 vs. -23.4±6.2, respectively), and the right ventricular free wall strain (-16.9±3.6 vs. -18.2±2.4 vs. -19.6±4.7, respectively) were worse in the HCQ group compared to the FAV and control groups. Conclusion: This study found echocardiographic evidence of subclinical cardiac involvement in both the HCQ and FAV groups compared to the controls. However, HCQ treatment was associated with an increased risk of biventricular subclinical systolic dysfunction in COVID-19 survivors compared with FAV treatment.

Evaluation of depression, anxiety, and stress symptoms and their relationship with subclinical myocardial dysfunction by left ventricular global longitudinal

Background

The coronavirus disease 2019 (COVID-19) has had a great impact on patients’ physical problems as well as psychological status. However, there is limited data about the impact of psychological problems on cardiac function during the COVID-19 pandemic. In this study, we aimed to investigate the relationship between mental health disorders and subclinical early myocardial systolic dysfunction by left ventricular global longitudinal strain (LVGLS) imaging in patients recovered from COVID-19.

Methods

Of the 108 participants, 71 patients had recovered from COVID-19; the members of the study group were prospectively recruited to the study after COVID-19 recovery. Comparisons were made with a risk-factor matched control group (n=37). The psychological status of the subjects, namely, Depression, Anxiety and Stress Scale-21 (DASS-21), and the Impact of Events Scale (IES-R) at follow-up visits, were assessed via questionnaire forms. The relationship between the psychological parameters and LVGLS values was subsequently evaluated.

Results

Overall, 45.0% of patients with COVID-19 had some degree of anxiety after recovery. A significant negative correlation was found between LVGLS and DASS-21 total score, DASS-21 anxiety subscale score, IES-R total score, and IES-R intrusion subscale score (r= -0.251, p=0.02; r= -0.285, p=0.008; r= -0.291, p=0.007; and r= -0.367, p=0.001, respectively). Furthermore, the DASS-21 total score was identified as an independent predictor of LVGLS (β= -0.186, p=0.03).

Conclusions

Patients who suffered from the COVID-19 disease may have experienced psychological distress symptoms due to COVID-19, which may be associated with silent impairment in myocardial systolic functions measured by global longitudinal strain analysis.

Hospital-acquired infections in patients hospitalized with COVID-19: First report from Taiwan

BACKGROUND

Coronavirus disease 2019 (COVID-19) inpatients may acquire infections from other pathogens during hospital admission. This is the first research on this subject to be reported from Taiwan.

METHODS

Confirmed COVID-19 inpatients were enrolled in this study from January 1, 2020 to July 31, 2021. Various types of pathogens in COVID-19 inpatients, with hospital-acquired infections, were identified and analyzed. The clinical characteristics of COVID-19 patients with and without hospital-acquired infections were reviewed and compared.

RESULTS

Of the 204 patients included in the study, 32 (15.7%) patients experienced at least one infectious episode. Of 113 recorded episodes of infection, the predominant type was bacterial (88 of 113 infections, 77.9%); the most frequently isolated bacteria were Acinetobacter spp., followed by Stenotrophomonas maltophilia . With regard to viral infections (19 of 113, 16.8%), the Epstein-Barr virus ranked first place among the identified viruses. Four (3.5%) and 2 (1.8%) of 113 infectious episodes were caused by fungi and atypical pathogens. A multivariate analysis revealed that steroid use was an independent factor in hospital-acquired infections (odds ratio [OR], 6.97; 95% confidence interval [CI], 1.15-42.43; p = 0.035). Patients with hospital-acquired infections were associated with increased 28-day and in-hospital mortality (18.8% vs 5.8% and 31.3% and 5.8%; p = 0.023 and <0.01, respectively), and a longer hospital stay (34 vs 19 days; p < 0.001), compared to those without hospital-acquired infections.

CONCLUSION

Our study revealed the unique local epidemiology of hospital-acquired infections among COVID-19 inpatients in Taiwan. These patients were associated with increased mortality and prolonged hospital admissions.

Survival Time to COVID-19 Severity and Its Predictors in South Gondar Zone, North-West Ethiopia: A Prospective Cohort Study

Background

Methods

Results

Conclusion and Recommendation

Transthoracic Echocardiography-Based Prediction Model of Adverse Event Risk in Patients with COVID-19

Cardiopulmonary disorders cause a significant increase in the risk of adverse events in patients with COVID-19. Therefore, the development of new diagnostic and treatment methods for comorbid disorders in COVID-19 patients is one of the main public health challenges. The aim of the study was to analyze patient survival and to develop a predictive model of survival in adults with COVID-19 infection based on transthoracic echocardiography (TTE) parameters. We conducted a prospective, single-center, temporary hospital-based study of 110 patients with moderate to severe COVID-19. All patients underwent TTE evaluation. The predictors of mortality we identified in univariate and multivariable models and the predictive performance of the model were assessed using receiver operating characteristic (ROC) analysis and area under the curve (AUC). The predictive model included three factors: right ventricle (RV)/left ventricle (LV) area (odds ratio (OR) = 1.048 per 1/100 increase, p = 0.03), systolic pulmonary artery pressure (sPAP) (OR = 1.209 per 1 mm Hg increase, p < 0.001), and right ventricle free wall longitudinal strain (RV FW LS) (OR = 0.873 per 1% increase, p = 0.036). The AUC-ROC of the obtained model was 0.925 ± 0.031 (95% confidence interval (95% CI): 0.863−0.986). The sensitivity (Se) and specificity (Sp) measures of the models at the cut-off point of 0.129 were 93.8% and 81.9%, respectively. A binary logistic regression method resulted in the development of a prognostic model of mortality in patients with moderate and severe COVID-19 based on TTE data. It may also have additional implications for early risk stratification and clinical decision making in patients with COVID-19.

Association between Mineralocorticoid Receptor Antagonist and Mortality in SARS-CoV-2 Patients: A Systematic Review and Meta-Analysis

Since the onset of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, various potential targeted therapies for SARS-CoV-2 infection have been proposed. The protective effects of mineralocorticoid receptor antagonists (MRA) against tissue fibrosis, pulmonary and systemic vasoconstriction, and inflammation have been implicated in potentially attenuating the severity of SARS-CoV-2 infection by inhibiting the deleterious effects of aldosterone. Furthermore, spironolactone, a type of MRA, has been suggested to have a beneficial effect on SARS-CoV-2 outcomes through its dual action as an MRA and antiandrogen, resulting in reduced transmembrane protease receptor serine type 2 (TMPRSS2)-related viral entry to host cells. In this study, we sought to investigate the association between MRA antagonist therapy and mortality in SARS-CoV-2 patients via systematic review and meta-analysis. The systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. MEDLINE and EMBASE databases were searched for studies that reported the incidence of mortality in patients on MRA with SARS-CoV-2 infection. Pooled odds ratio (OR) and 95% confidence interval (CI) of the outcome were obtained using the random-effects model. Five studies with a total of 1,388,178 subjects (80,903 subjects receiving MRA therapy) met the inclusion criteria. We included studies with all types of MRA therapy including spironolactone and canrenone and found no association between MRA therapy and mortality in SARS-CoV-2 infection (OR = 0.387, 95% CI: 0.134–1.117, p = 0.079).

Efficacy and Safety of Lianhuaqingwen Capsules for the Prevention of Coronavirus Disease 2019: A Prospective Open-Label Controlled Trial

Coronavirus disease 2019 (COVID-19) has become a global pandemic. Community and close contact exposures continue to drive the COVID-19 pandemic. There is no confirmed effective treatment for suspected cases and close contacts. Lianhuaqingwen (LH) capsules, a repurposed Chinese herbal product that is currently on the market, have proven effective for influenza and COVID-19. To determine the safety and efficacy of LH capsules for the prevention of COVID-19, we conducted a prospective open-label controlled trial of LH capsules on subjects who had close contact with people infected with COVID-19. Subjects received LH capsules (4 capsules, three times daily) or the usual medical observation for 14 days. The primary endpoint was the rate of positive nucleic acid tests of nasal and pharyngeal swabs during the quarantine medical observation period. We included 1976 patients, including 1101 in the treatment group and 875 in the control group. The rate of positive nucleic acid tests in the treatment group was significantly lower than that in the control group (0.27% vs. 1.14%, respectively; mean difference: -0.87%; 95% CI: -1.83 to -0.13; p=0.0174) during the quarantine medical observation period (14 days). Among subjects with different close contact states, there was no significant difference in the rate of positive nucleic acid test results among close contacts in the treatment group and the control group (6.45% vs. 11.43%, respectively; p=0.6762). Among secondary close contacts, the rate of positive nucleic acid tests in the treatment group was significantly lower than that in the control group (0.09% vs. 0.71%, respectively; p=0.0485). No serious adverse events were reported. Taken together, and in light of the safety and effectiveness profiles, these results show that LH capsules can be considered to prevent the progression of COVID-19 after close contact with an infected person. This trial is registered with ChiCTR2100043012.

Coronavirus Disease (COVID-19) Control between Drug Repurposing and Vaccination: A Comprehensive Overview

Respiratory viruses represent a major public health concern, as they are highly mutated, resulting in new strains emerging with high pathogenicity. Currently, the world is suffering from the newly evolving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus is the cause of coronavirus disease 2019 (COVID-19), a mild-to-severe respiratory tract infection with frequent ability to give rise to fatal pneumonia in humans. The overwhelming outbreak of SARS-CoV-2 continues to unfold all over the world, urging scientists to put an end to this global pandemic through biological and pharmaceutical interventions. Currently, there is no specific treatment option that is capable of COVID-19 pandemic eradication, so several repurposed drugs and newly conditionally approved vaccines are in use and heavily applied to control the COVID-19 pandemic. The emergence of new variants of the virus that partially or totally escape from the immune response elicited by the approved vaccines requires continuous monitoring of the emerging variants to update the content of the developed vaccines or modify them totally to match the new variants. Herein, we discuss the potential therapeutic and prophylactic interventions including repurposed drugs and the newly developed/approved vaccines, highlighting the impact of virus evolution on the immune evasion of the virus from currently licensed vaccines for COVID-19.

Characterization of the SARS-CoV-2 genomes in Egypt in first and second waves of infection

At Wuhan, in December 2019, the SRAS-CoV-2 outbreak was detected and it has been the pandemic worldwide. This study aims to investigate the mutations in sequence of the SARS-CoV-2 genome and characterize the mutation patterns in Egyptian COVID-19 patients during different waves of infection. The samples were collected from 250 COVID-19 patients and the whole genome sequencing was conducted using Next Generation Sequencing. The viral sequence analysis showed 1115 different genome from all Egyptian samples in the second wave mutations including 613 missense mutations, 431 synonymous mutations, 25 upstream gene mutations, 24 downstream gene mutations, 10 frame-shift deletions, and 6 stop gained mutation. The Egyptian genomic strains sequenced in second wave of infection are different to that of the first wave. We observe a shift of lineage prevalence from the strain B.1 to B.1.1.1. Only one case was of the new English B.1.1.7. Few samples have one or two mutations of interest from the Brazil and South Africa isolates. New clade 20B appear by March 2020 and 20D appear by May 2020 till January 2021.

Impairment of right ventricular longitudinal strain associated with severity of pneumonia in patients recovered from COVID-19

Myocardial injury caused by COVID-19 was reported in hospitalized patients previously. But the information about cardiac consequences of COVID-19 after recovery is limited. The aim of the study was comprehensive echocardiography assessment of right ventricular (RV) in patients recovered from COVID-19. This is a prospective, single-center study. After recovery from COVID-19, echocardiography was performed in consecutive 79 patients that attended follow-up visits from July 15 to November 30, 2020. According to the recovery at home vs hospital, patients were divided into two groups: home recovery (n = 43) and hospital recovery (n = 36). Comparisons were made with age, sex and risk factor-matched control group (n = 41). In addition to conventional echocardiography parameters, RV global longitudinal strain (RV-GLS) and RV free wall strain (RV-FWS) were determined using 2D speckle-tracking echocardiography (2D STE). Of the 79 patients recovered from COVID-19, 43 (55%) recovered at home, while 36 (45%) required hospitalization. The median follow-up duration was 133  ±  35 (87–184) days. In patients recovered from hospital, RV-GLS and RV-FWS were impaired compared to control group (RV-GLS: −17.3  ±  6.8 vs. −20.4  ±  4.9, respectively [p = 0.042]; RV-FWS: −19.0  ±  8.2 vs. −23.4  ±  6.2, respectively [p = 0.022]). In subgroup analysis, RV-FWS was impaired in patients severe pneumonia (n = 11) compared to mild-moderate pneumonia (n = 28), without pneumonia (n = 40) and control groups (−15.8  ±  7.6 vs. −21.6  ±  7.6 vs. −20.8  ±  7.7 vs. −23.4  ±  6.2, respectively, [p = 0.001 for each]) and RV-GLS was impaired compared to control group (−15.2  ±  6.9 vs. −20.4  ±  4; respectively, [p = 0.013]). A significant correlation was detected between serum CRP level at hospital admission and both RV-GLS and RV-FWS (r = 0.285, p = 0.006; r = 0.294, p = 0.004, respectively). Age (OR 0.948, p = 0.010), male gender (OR 0.289, p = 0.009), pneumonia on CT (OR 0.019, p = 0.004), and need of steroid in treatment (OR 17.424, p = 0.038) were identifed as independent predictors of impaired RV-FWS (> −18) via multivariate analysis. We demonstrated subclinic dysfunction of RV by 2D-STE in hospitalized patients in relation to the severity of pneumonia after recovery from COVID-19. 2D-STE supplies additional information above standard measures of RV in this cohort and can be used in the follow-up of these patients.