Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19

Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care

BACKGROUND

There is a paucity of prognostic models for COVID-19 that are usable for in-office patient assessment in general practice (GP).

OBJECTIVES

To develop and validate a risk prediction model for hospital admission with readily available predictors.

METHODS

A retrospective cohort study linking GP records from 8 COVID-19 centres and 55 general practices in the Netherlands to hospital admission records. The development cohort spanned March to June 2020, the validation cohort March to June 2021. The primary outcome was hospital admission within 14 days. We used geographic leave-region-out cross-validation in the development cohort and temporal validation in the validation cohort.

RESULTS

In the development cohort, 4,806 adult patients with COVID-19 consulted their GP (median age 56, 56% female); in the validation cohort 830 patients did (median age 56, 52% female). In the development and validation cohort respectively, 292 (6.1%) and 126 (15.2%) were admitted to the hospital within 14 days, respectively. A logistic regression model based on sex, smoking, symptoms, vital signs and comorbidities predicted hospital admission with a c-index of 0.84 (95% CI 0.83 to 0.86) at geographic cross-validation and 0.79 (95% CI 0.74 to 0.83) at temporal validation, and was reasonably well calibrated (intercept -0.08, 95% CI -0.98 to 0.52, slope 0.89, 95% CI 0.71 to 1.07 at geographic cross-validation and intercept 0.02, 95% CI -0.21 to 0.24, slope 0.82, 95% CI 0.64 to 1.00 at temporal validation).

CONCLUSION

We derived a risk model using readily available variables at GP assessment to predict hospital admission for COVID-19. It performed accurately across regions and waves. Further validation on cohorts with acquired immunity and newer SARS-CoV-2 variants is recommended.

Toward better pandemic governance and preparedness: South Korea's whole-of-nation approach to COVID-19

BACKGROUND

The profound impact of coronavirus disease (COVID-19) has led to an increased demand for sustainable pandemic governance practices. This study explored emerging hybrid governance practices that provide robust evidence on how to address the complex challenges of pandemics effectively. South Korea, which was severely affected by COVID-19, has implemented a novel governance approach using a whole-of-nation (WoN) model. This hybrid pandemic governance approach, which integrates both whole-of-government and whole-of-society approaches, has enabled synergistic and cohesive multi-sectoral coordination among all stakeholders (public authorities, private enterprises, and civil society) to address multifaceted challenges collectively and strengthen their resilience capacity. This study investigated South Korea's WoN practices and their embedded context and identified key governance enablers facilitating this approach.

METHODS

This study employed a case study design based on an extensive analysis of policy and program documents, drawing on South Korea's publicly available data from January 1, 2020 to March 30, 2023. It assessed six system-level collaborative pandemic governance practices and key enablers, all of which were intended to fortify the country's pandemic response.

RESULTS

The primary areas of the country's WoN governance practices for COVID-19 control were (i) whole-of-government policy-making and response, (ii) COVID-19 testing system, (iii) digital surveillance of COVID-19, (iv) COVID-19 triage and treatment system, (v) domestic vaccine production, and (vi) community engagement. Key governance enablers for implementing the WoN model were establishing a legal foundation, ensuring decisive and strong governance and leadership, increasing public investment, applying a whole-of-health approach with augmented investment in public health, enhancing crisis communication, and mobilizing local leaders and civil society organizations in the national public health response.

CONCLUSIONS

In exploring innovative approaches to pandemic governance for increased efficacy, responsiveness, and impact, the WoN approach emerged as highly relevant. This example of emerging practice allows policy-makers to re-evaluate their governance strategies and initiatives to improve multi-agency partnerships across the country in their pandemic-preparedness planning.

Seawater nasal wash to reduce symptom duration and viral load in COVID-19 and upper respiratory tract infections: a randomized controlled multicenter trial

PURPOSE

The objective was to assess the efficacy of seawater nasal wash on symptom duration, intranasal viral load, household transmission in COVID-19 and URTIs.

METHODS

This prospective, randomized, controlled, multicentric, parallel study included 355 mild/moderate COVID-19 and URTI adults with rhinologic symptoms ≤ 48h. Active group performed 4-daily nasal washes with undiluted isotonic seawater versus control group (without nasal wash). Symptoms were self-assessed daily using the WURSS-21 questionnaire for 3 weeks. Viral load was measured by RT-PCR on nasopharyngeal swabs collected on Day 0, Day 5, Day 14 and Day 21. Digital droplet PCR was additionally performed for SARS-CoV-2.

RESULTS

Overall COVID-19 subjects recovered earlier the ability to accomplish daily activities in the active group (- 1.6 day, p = 0.0487) with earlier improvement of taste (- 2 days, p = 0.0404). COVID-19 subjects with severe nasal symptoms at D0 showed the earliest resolution of anosmia (- 5.2 days, p = 0.0281), post-nasal drip (- 4.1 days, p = 0.0102), face pain/heaviness (- 4.5 days, p = 0.0078), headache (- 3.1 days, p = 0.0195), sore throat (- 3.3 days, p = 0.0319), dyspnea (- 3.1 days, p = 0.0195), chest congestion (- 2.8 days, p = 0.0386) and loss of appetite (- 4.5 days, p = 0.0186) with nasal wash. In URTIs subjects, an earlier resolution of rhinorrhea (- 3.5 days, p = 0.0370), post-nasal drip (- 3.7 days, p = 0.0378), and overall sickness (- 4.3 days, p = 0.0248) was reported with nasal wash. Evolution towards more severe COVID-19 was lower in active vs control, with earlier viral load reduction in youngest subjects (≥ 1.5log10 copies/10000 cells at Day 5: 88.9% vs 62.5%, p = 0.0456). In the active group, a lower percentage of SARS-CoV-2 positive household contacts (0-10.7%) was reported vs controls (3.2-16.1%) among subjects with Delta variant (p = 0.0413).

CONCLUSION

This trial showed the efficacy and safety of seawater nasal wash in COVID-19 and URTIs.

TRIAL REGISTRATION

Trial registry ClinicalTrials.gov: NCT04916639. Registration date: 04.06.2021.

Titers of IgG and IgA against SARS-CoV-2 proteins and their association with symptoms in mild COVID-19 infection

Humoral immunity in COVID-19 includes antibodies (Abs) targeting spike (S) and nucleocapsid (N) SARS-CoV-2 proteins. Antibody levels are known to correlate with disease severity, but titers are poorly reported in mild or asymptomatic cases. Here, we analyzed the titers of IgA and IgG against SARS-CoV-2 proteins in samples from 200 unvaccinated Hospital Workers (HWs) with mild COVID-19 at two time points after infection. We analyzed the relationship between Ab titers and patient characteristics, clinical features, and evolution over time. Significant differences in IgG and IgA titers against N, S1 and S2 proteins were found when samples were segregated according to time T1 after infection, seroprevalence at T1, sex and age of HWs and symptoms at infection. We found that IgM + samples had higher titers of IgG against N antigen and IgA against S1 and S2 antigens than IgM - samples. There were significant correlations between anti-S1 and S2 Abs. Interestingly, IgM + patients with dyspnea had lower titers of IgG and IgA against N, S1 and S2 than those without dyspnea. Comparing T1 and T2, we found that IgA against N, S1 and S2 but only IgG against certain Ag decreased significantly. In conclusion, an association was established between Ab titers and the development of infection symptoms.

Sensitivity of Symptom-Based Screening for COVID-19 in Active Duty Basic Trainees

INTRODUCTION

Symptomatic Coronavirus Disease 2019 (COVID-19) screening has been a cornerstone of case identification during the pandemic. Despite the myriad of COVID-19 symptoms, symptom screens have primarily focused on symptoms of influenza-like illnesses such as fever, cough, and dyspnea. It is unknown how well these symptoms identify cases in a young, healthy military population. This study aims to evaluate the utility of symptom-based screening in identifying COVID-19 through three different COVID-19 waves.

MATERIALS AND METHODS

A convenience sample of 600 military trainees who arrived at Joint Base San Antonio-Lackland in 2021 and 2022 were included. Two hundred trainees with symptomatic COVID-19 before the emergence of the Delta variant (February-April 2021), when Delta variant was predominant (June-August 2021), and when Omicron was the predominant variant (January 2022) had their presenting symptoms compared. At each time point, the sensitivity of a screen for influenza-like illness symptoms was calculated.

RESULTS

Of the 600 symptomatic active duty service members who tested positive for COVID-19, the most common symptoms were sore throat (n = 385, 64%), headache (n = 334, 56%), and cough (n = 314, 52%). Although sore throat was the most prominent symptom during Delta (n = 140, 70%) and Omicron (n = 153, 77%), headache was the most common before Delta (n = 93, 47%). There were significant differences in symptoms by vaccination status; for example, ageusia was more common in patients who were not completely vaccinated (3% vs. 0%, P = .01). Overall, screening for fever, cough, or dyspnea had a 65% sensitivity with its lowest sensitivity in the pre-Delta cases (54%) and highest sensitivity in Omicron cases (78%).

CONCLUSIONS

In this descriptive cross-sectional study evaluating symptomatic military members with COVID-19, symptom prevalence varied based on predominant circulating COVID-19 variant as well as patients' vaccination status. As screening strategies evolve with the pandemic, changing symptom prevalence should be considered.

Analyzing factors affecting positivity in drive-through COVID-19 testing: a cross-sectional study

BACKGROUND

Demand for COVID-19 testing prompted the implementation of drive-through testing systems. However, limited research has examined factors influencing testing positivity in this setting.

METHODS

From October 2020 to March 2023, a total of 1,341 patients, along with their clinical information, were referred from local clinics to the Sasebo City COVID-19 drive-through PCR center for testing. Association between clinical information or factors related to the drive-through center and testing results was analyzed by Fisher's exact test and logistic regression models.

RESULTS

Individuals testing positive exhibited higher frequencies of upper respiratory symptoms; cough (OR 1.5 (95% CI 1.2-1.8), p < 0.001, q = 0.005), sore throat (OR 2.4 (95% CI 1.9-3.0), p < 0.001, q < 0.001), runny nose (OR 1.4 (95% CI 1.1-1.8), p = 0.002, q = 0.009), and systemic symptoms; fever (OR 1.5 (95% CI 1.1-2.0), p = 0.006, q = 0.02), headache (OR 1.9 (95% CI 1.4-2.5), p < 0.001, q < 0.001), and joint pain (OR 2.7 (95% CI 1.8-4.1), p < 0.001, q < 0.001). Conversely, gastrointestinal symptoms; diarrhea (OR 0.2 (95% CI 0.1-0.4), p < 0.001, q < 0.001) and nausea (OR 0.3 (95% CI 0.1-0.6), p < 0.001, q < 0.001) were less prevalent among positives. During omicron strain predominant period, higher testing positivity rate (OR 20 (95% CI 13-31), p < 0.001) and shorter period from symptom onset to testing (3.2 vs. 6.0 days, p < 0.001) were observed compared to pre-omicron period. Besides symptoms, contact history with infected persons at home (OR 4.5 (95% CI 3.1-6.5), p < 0.001, q < 0.001) and in office or school (OR 2.9 (95% CI 2.1-4.1), p < 0.001, q < 0.001), as well as the number of sample collection experiences by collectors (B 7.2 (95% CI 2.8-12), p = 0.002) were also associated with testing results.

CONCLUSIONS

These findings underscore the importance of factors related to drive-through centers, especially contact history interviews and sample collection skills, for achieving higher rates of COVID-19 testing positivity. They also contribute to enhanced preparedness for next infectious disease pandemics.

Identification of the needs of individuals affected by COVID-19

BACKGROUND

The optimal management of COVID-19 symptoms and their sequelae remains an important area of clinical research. Policy makers have little scientific data regarding the effects on the daily life of affected individuals and the identification of their needs. Such data are needed to inform effective care policy.

METHODS

We studied 639 people with COVID-19 resident in France via an online questionnaire. They reported their symptoms, effects on daily life, and resulting needs, with particular focus on olfaction.

RESULTS

The results indicate that a majority of participants viewed their symptoms as disabling, with symptoms affecting their physical and mental health, social and professional lives. 60% of the individuals reported having unmet medical, psychological and socio-professional support needs. Finally, affected individuals were concerned about the risk and invasiveness of possible treatments as shown by a preference for non-invasive intervention over surgery to cure anosmia.

CONCLUSIONS

It is important that policy makers take these needs into consideration in order to assist affected individuals to regain a normal quality of life.

A Comparison of Sensorimotor Integration and Motor Fitness Components between Collegiate Athletes with and without Long COVID: A Cross-Sectional Study with Pair-Matched Controls

Background: Long COVID presents a concern for collegiate athletes, potentially impacting sensorimotor processing and motor fitness. This study aimed to assess these effects. Methods: This cross-sectional study involved 60 athletes diagnosed with Long COVID and 60 controls. Sensorimotor processing and integration were evaluated using neurophysiological variables (N13, P14, N20, P27, and N30), while motor fitness was assessed through balance, agility, and vertical jump testing. T-tests compared groups, and Pearson's correlations explored relationships. Results: Significant differences (p < 0.001) were observed in neurophysiological variables and motor fitness between Long COVID and control groups. Fatigue correlated positively (p < 0.001) with neurophysiological variables in Long COVID cases but not with motor fitness (p = 0.08, p = 0.07, p = 0.09). Conclusions: Collegiate athletes with Long COVID exhibit abnormal sensorimotor processing, integration, and diminished motor fitness compared to uninfected peers. The fatigue severity of Long COVID correlates with neurophysiological changes, suggesting a link between sensorimotor deficits and fatigue. Targeted interventions for sensorimotor deficits and fatigue management are crucial for athletes recovering from Long COVID. This study underscores the importance of addressing these issues to optimize the recovery and performance of collegiate athletes affected by Long COVID.

The role of colchicine in the management of COVID-19: a Meta-analysis

BACKGROUND

The Coronavirus disease 2019 (COVID-19) pandemic has robustly affected the global healthcare and economic systems and it was caused by coronavirus-2 (SARS-CoV-2). The clinical presentation of the disease ranges from a flu-like illness to severe pneumonia and death. Till September 2022, the cumulative number of cases exceeded 600 million worldwide and deaths were more than 6 million. Colchicine is an alkaloid drug that is used in many autoinflammatory conditions e.g., gout, familial Mediterranean fever, and Behçet's syndrome. Colchicine inhibits the production of superoxide and the release of interleukins that stimulate the inflammatory cascade. Colchicine decreases the differentiation of myofibroblast and the release of fibrotic mediators including transforming growth factor (TGF-β1) that are related to the fibrosis. Moreover, colchicine has been used to traet viral myocarditis caused by CMV or EBV, interstitial pneumonia, and pericarditis resulting from influenza B infection. Additionally, colchicine is considered safe and affordable with wide availability.

OBJECTIVE

The aim of the current study was to assess the evidence of colchicine effectiveness in COVID-19 treatment.

METHODS

A comprehensive review of the literature was done till May 2022 and yielded 814 articles after ranking the articles according to authors and year of publication. Only 8 clinical trials and cohort studies fulfilling the inclusion criteria were included for further steps of data collection, analysis, and reporting.

RESULTS

This meta-analysis involved 16,488 patients; 8146 patients in the treatment group and 8342 patients in the control group. The results showed that colchicine resulted in a significant reduction in the mortality rate among patients received colchicine in comparison with placebo or standard care (RR 0.35, 95%CI: 0.15-0.79). Colchicine resulted in a significant decrease in the need for O2 therapy in patients with COVID-19 (RR 0.07, 95%CI 0.02-0.27, P = 0.000024). However, colchicine had no significant effect on the following outcomes among COVID-19 patients: the need for hospitalization, ICU admission, artificial ventilation, and hospital discharge rate. Among the PCR confirmed COVID-19 patients, colchicine decreased the hospitalization rate (RR 0.75, 95%CI 0.57-0.99, P = 0.042). However, colchicine had no effect on mortality and the need for mechanical ventilation among this subgroup.

CONCLUSION

Colchicine caused a significant clinical improvement among COVID-19 patients as compared with the standard care or placebo, in terms of the need for O2, and mortality. This beneficial effect could play a role in the management of COVID-19 especially severe cases to decrease need for oxygen and to decrease mortality among these patients.

COVID-19 diagnostic prediction on chest CT scan images using hybrid quantum-classical convolutional neural network

Notwithstanding the extensive research efforts directed towards devising a dependable approach for the diagnosis of coronavirus disease 2019 (COVID-19), the inherent complexity and capriciousness of the virus continue to pose a formidable challenge to the precise identification of affected individuals. In light of this predicament, it is essential to devise a model for COVID-19 prediction utilizing chest computed tomography (CT) scans. To this end, we present a hybrid quantum-classical convolutional neural network (HQCNN) model, which is founded on stochastic quantum circuits that can discern COVID-19 patients from chest CT images. Two publicly available chest CT image datasets were employed to evaluate the performance of our model. The experimental outcomes evinced diagnostic accuracies of 99.39% and 97.91%, along with precisions of 99.19% and 98.52%, respectively. These findings are indicative of the fact that the proposed model surpasses recently published works in terms of performance, thus providing a superior ability to precisely predict COVID-19 positive instances.Communicated by Ramaswamy H. Sarma.

Impact of COVID-19 on patient experience of kidney care: a rapid review

INTRODUCTION

In March 2020, a pandemic state was declared due to SARS-COV-2 (COVID-19). Patients with kidney disease, especially those on replacement therapies, proved more susceptible to severe infection. This rapid literature review aims to help understand how the pandemic impacted patient experience of kidney care.

METHODS

It was conducted in accordance with Cochrane Rapid Review interim guidance. Search terms, 'coronavirus', 'kidney care', and 'patient-reported experience' and terms with similar semantic meaning, identified 1,117 articles in Medline, Scopus, and Worldwide Science. Seventeen were included in the narrative synthesis.

RESULTS

The findings were summarised into three themes: remote consultation and telemedicine (n = 9); psychosocial impact (n = 2); and patient satisfaction and patient-reported experience (n = 6). Patients were mostly satisfied with remote consultations, describing them as convenient and allowing avoidance of hospital visits. Anxieties included missing potentially important clinical findings due to lack of physical examination, poor digital literacy, and technical difficulties. Psychosocial impact differed between treatment modalities-transplant recipients expressing feelings of instability and dread of having to return to dialysis, and generally, were less satisfied, citing reduced ability to work and difficulty accessing medications. Those on home dialysis treatments tended to feel safer. Findings focused on aspects of patient experience of kidney care during the pandemic rather than a holistic view.

CONCLUSIONS

There was little direct evaluation of modality differences and limited consideration of health inequalities in care experiences. A fuller understanding of these issues would guide policy agendas to support patient experience during future public health crises.

Hand hygiene during the spread of COVID-19: a cross-sectional study of awareness and practices among academic institutions in Lebanon

Introduction

During the pandemic, the World Health Organization has recommended hand hygiene as one of the effective preventive measures to limit the global spread of COVID-19. However, the awareness gap of hand hygiene protocols could increase the spread of COVID-19 and consequently increase the absenteeism rate among academic institutions. This study aims to assess hand hygiene awareness and practices levels among various university communities in Lebanon.

Methods

A cross-sectional study was conducted between December 2021 and June 2022 among 1,291 participants from academic settings in Lebanese universities. An online survey (score-based questionnaire) of hand hygiene was conducted to evaluate the awareness and practices among university communities (faculty, staff, and students). Mann-Whitney and Kruskal-Wallis tests were used to determine whether significant differences exist in the levels of awareness with regard to gender, age, provinces, educational level, and university status. Pearson's chi-squared test was applied to assess differences among the sample characteristics and participants' practice of hand hygiene.

Results

It was found that most of the participants showed a moderate level of awareness (76.4%) with a mean score of 7.59 out of 12 (SD = 1.68). The Mann-Whitney test indicated that females recorded higher levels of awareness than males with a significant difference of 102, 104: p < 0.05. Another notable variable was the educational level of the participants with university degrees holders recording higher scores of awareness than the ones with high school degrees as per the Kruskal-Wallis test (p < 0.05). Significant differences were also shown in awareness scores among the age groups and the university status (p < 0.05). The Pearson's chi-squared test results showed that females used alcohol-based hand rubs or soap and water more frequently than males (p < 0.05). However, males significantly preferred the frequent use of water alone compared to females (p < 0.05).

Conclusion

The study findings highlighted the necessity of awareness campaigns and health educational programs addressing the technical skills of hand hygiene among both genders (especially males) of the academic communities in Lebanon.

The nosocomial infection survey among patients suffering from the Coronavirus disease-2019 hospitalized in Ayatollah Rouhani Hospital, Babol

Background

Having a weakened immune system can make patients easily get nosocomial infection (NI) with multi-drug resistant (MDR) bacteria and put them in a dangerous situation. It causes long hospital stays, disability, economic burden, and even death. The present study aimed to determine the prevalence of NI in patients suffering from COVID-19.

Methods

In this retrospective study, the information on 250 patients suffering from COVID-19 in the intensive care unit (ICU) (2020 to 2021) was considered. For statistical analysis, analysis of variance (ANOVA), paired samples t-test, and chi-square using SPSS-23 software were used (p<0.05).

Results

Two hundred and fifty hospitalized (107 females and 143 males, mean ± standard deviation (SD) of age; 56.50 ± 17.20) patients were considered. The most (97.60%) medicine prescribed was remdesivir. Candida spp. (two females), Escherichia coli (two females), Acinetobacter spp. (one female), Citrobacter spp. (one female), Pseudomonas spp. (one male), Sphingomonas spp. (one male), Stenotrophomonas spp. (one male) and Enterobacter spp. (one male) were isolated from the patient's specimens. Four of seven bacterial isolates were positive for MDR. NI was diagnosed in six patients. There was no significant relationship between the age with the isolated microbes (P=0.154) and MDR (P=0.987) and also between gender with common microbes (P=0.576) and MDR (P=0.143).

Conclusion

The coexistence of bacteria and NI was observed in patients. Remdesivir was prescribed for most patients. Most bacteria were resistant to antibiotics, especially, β-lactams.

Number of initial symptoms of SARS-CoV-2 infection is associated with the risk of otological symptoms: a retrospective study

BACKGROUND

The characteristics of otological symptoms in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are lacking. Almost no research has been conducted to explore the emergence of otological symptoms after coronavirus disease 2019 infection. The aims of this study were to investigate the prevalence and specific clinical characteristics of and risk factors for otological symptoms among patients with SARS-CoV-2 infection.

METHODS

We included two groups to investigate the prevalence and clinical characteristics of otological symptoms among patients with SARS-CoV-2 infection. The first sample (S1) was drawn retrospectively from four communities via questionnaires, and the second sample (S2) from an outpatient clinic.

RESULTS

A total of 189 participants were included in S1 (124 women [65.6%]; mean [standard deviation (SD)] age, 33.66 [13.56] years), and 47 in S2 (25 women [53.2%]; mean [SD] age, 45.28 [14.64] years). The most prevalent otological symptoms in S1 were dizziness (15.9%), tinnitus (7.9%), aural fullness (6.9%), otalgia (5.3%), hearing loss (1.6%), and otopyorrhoea (1.1%). Moreover, for each additional typical symptom of SARS-CoV-2 infection, the risk (odds ratio) of otological symptoms increased by 1.33 (95% confidence interval: 1.10-1.61, p = 0.003). The prevalence of aural fullness was higher in the unvaccinated group than that in the group receiving two or three vaccinations (p = 0.018).

CONCLUSIONS

Various otological symptoms may occur in patients with SARS-CoV-2 infection. The number of typical symptoms of SARS-CoV-2 infection is positively associated with the probability of otological symptoms. However, vaccination may reduce the probability of certain otological symptoms.

Symptoms, symptom severity, and contact with primary health care among nonhospitalized COVID-19 patients: a Norwegian web-based survey

OBJECTIVE

Dependent on clinical setting, geography and timing during the pandemic, variable symptoms of COVID-19 have been reported. Our aim was to describe self-reported symptom intensity and contact with primary health care among nonhospitalized COVID-19 patients.

DESIGN

Web-based survey.

SETTING

Norway between March 2020 and July 2021.

SUBJECTS

Adults in home isolation.

MAIN OUTCOME MEASURES

Participants reported possible COVID-19 symptoms, duration of symptoms, score of symptom severity (Likert scale 0-3), risk factors, comorbidity, and questions regarding follow-up and information from primary health care.

RESULTS

Of 477 participants, 379 (79%) had PCR-confirmed COVID-19, 324 (68%) were females, and 90% were younger than 60 years. Most common symptoms were "fatigue and/or muscle ache" (80%), nasal symptoms (79%), and headache (73%). The mean severity of symptoms was generally low. Symptoms with the highest mean scores were "fatigue and/or muscle ache" (1.51, SD 1.02) and headache (1.27 (SD 1.00). Mean scores for severity ranged from 0.28 (nausea) to 1.51 (fatigue and/or muscle ache). Women reported higher symptom scores than men. For "affected sense of smell and/or taste", patients either reported a high symptom score (24%) or no affliction at all (49%). A third of the participants (32%) were followed-up by primary care health personnel, and almost 40% had sought or received information about COVID-19 from general practitioners.

CONCLUSION

The mean severity of symptoms among nonhospitalized adult COVID-19 patients was generally low. We found large variations in the occurrence and severity of symptoms between patients.

Postoperative Complications in Patients With the Preoperative COVID-19 Infection at King Fahad Specialist Hospital: A Retrospective Cohort Study

BACKGROUND

Coronavirus disease (COVID-19) is an infectious disease caused by a new coronavirus strain. Indeed, the timing of COVID-19 infection before surgery plays an important role in the surgery outcomes and complications.

OBJECTIVE

In this study, we aimed to assess the prevalence and predictors of postoperative complications for patients who underwent surgery with previous COVID-19 infection.

METHODOLOGY

This was a retrospective hospital-based study which was conducted on 75 patients who had been infected with COVID-19 and underwent surgery.

RESULTS

We included 75 patients. The time between COVID-19 infection and the surgery was from one to six months in 52% of patients, 24% of patients were more than six months, and 24% of patients were less than one month. In this study, most of the patients had no complications (77.3%) while 22.7% of patients had complications that were mainly respiratory (n= 13). The overall mortality in our study was 5.3%. There was a significant association between comorbidity and postoperative complications, and the status of COVID-19 preoperative and postoperative complications (p < 0.01) but not patients' age as well as the type of anesthesia and postoperative complication (p > 0.05).

CONCLUSION

Respiratory complications were the most common postoperative complications in patients who had surgery after COVID-19 infection. Comorbidity and COVID-19 status were significantly associated with higher postoperative complications. Mortality was relatively small. We recommend extreme care to patients with COVID-19 infection prior to surgery to decrease the COVID-19 hazards that develop post-surgery.

A Danish questionnaire study of acute symptoms of SARS-CoV-2 infection by variant, vaccination status, sex and age

It is not well-described how the acute symptoms of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) differ by variant, vaccination, sex and age. A cross-sectional questionnaire study linked to national testing- and registry data was conducted among 148,874 SARS-CoV-2 first time reverse transcription polymerase chain reaction (RT-PCR) test-positive individuals and corresponding date-matched symptomatic test-negative controls. Major SARS-CoV-2 variants (Index/wild type, Alpha, Delta and Omicron) were defined using periods of predominance. Risk differences (RDs) were estimated for each of 21 predefined acute symptoms comparing: (1) test-positive and -negative individuals, by variant period, (2) vaccinated and unvaccinated test-positives, by variant period, (3) individuals tested positive during the Omicron and Delta periods, by vaccination status, and (4) vaccinated Omicron test-positive and -negative individuals, by age and sex. Compared to pre-Omicron, RDs between test-positive and test-negative individuals during the Omicron period were lower for most symptoms. RDs for altered sense of smell (dysosmia) and taste (dysgeusia) were highest for Delta (RD = 50.8 (49.4-52.0) and RD = 54.7 (53.4-56.0), respectively) and lowest for Omicron (RD = 12.8 (12.1-13.5) and RD = 11.8 (11.1-12.4), respectively). Across variants, vaccinated individuals reported fewer symptoms. During Omicron, females and 30-59 year-old participants reported more symptoms.

Coinfection of SARS-CoV-2 and influenza A (H3N2) detected in bronchoalveolar lavage fluid of a patient with long COVID using metagenomic next-generation sequencing: a case report

The growing number of long COVID cases has drawn clinical attention to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has been spreading worldwide since winter 2019. Its symptoms are not limited to fatigue and shortness of breath but also affect daily life. We report the use of metagenomic next-generation sequencing (mNGS) to detect coinfection with SARS-CoV-2 and influenza A virus in a patient with long COVID. The patient was admitted with fever, expectoration, fatigue, and shortness of breath. The PCR test was negative due to possible clearance of SARS-Cov-2 in the upper respiratory tract of patients with long COVID. Other routine microbiological tests were also negative, making the clinical diagnosis difficult. Bronchoalveolar lavage fluid (BALF) samples were tested using mNGS. The patient was diagnosed and treated promptly, recovered quickly, and continued taking azvudine after discharge; his condition was stable. This study illustrates that mNGS may be valuable for the timely diagnosis of patients with long COVID and their mixed infections.

Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing

We used social media data from "covid19positive" subreddit, from 03/2020 to 03/2022 to identify COVID-19 cases and extract their reported symptoms automatically using natural language processing (NLP). We trained a Bidirectional Encoder Representations from Transformers classification model with chunking to identify COVID-19 cases; also, we developed a novel QuadArm model, which incorporates Question-answering, dual-corpus expansion, Adaptive rotation clustering, and mapping, to extract symptoms. Our classification model achieved a 91.2% accuracy for the early period (03/2020-05/2020) and was applied to the Delta (07/2021-09/2021) and Omicron (12/2021-03/2022) periods for case identification. We identified 310, 8794, and 12,094 COVID-positive authors in the three periods, respectively. The top five common symptoms extracted in the early period were coughing (57%), fever (55%), loss of sense of smell (41%), headache (40%), and sore throat (40%). During the Delta period, these symptoms remained as the top five symptoms with percent authors reporting symptoms reduced to half or fewer than the early period. During the Omicron period, loss of sense of smell was reported less while sore throat was reported more. Our study demonstrated that NLP can be used to identify COVID-19 cases accurately and extracted symptoms efficiently.

Impact of COVID-19 in individuals with and without pre-existent digestive disorders with a particular focus on elderly patients

Coronavirus disease 2019 (COVID-19) has several extrapulmonary symptoms. Gastrointestinal (GI) symptoms are among the most frequent clinical manifestations of COVID-19, with severe consequences reported in elderly patients. Furthermore, the impact of COVID-19 on patients with pre-existing digestive diseases still needs to be fully elucidated, particularly in the older population. This review aimed to investigate the impact of COVID-19 on the GI tract, liver, and pancreas in individuals with and without previous digestive diseases, with a particular focus on the elderly, highlighting the distinctive characteristics observed in this population. Finally, the effectiveness and adverse events of the anti-COVID-19 vaccination in patients with digestive disorders and the peculiarities found in the elderly are discussed.

Diagnostic accuracy of clinical signs and symptoms of COVID-19: A systematic review and meta-analysis to investigate the different estimates in a different stage of the pandemic outbreak

Background

The coronavirus (COVID-19) pandemic caused enormous adverse socioeconomic impacts worldwide. Evidence suggests that the diagnostic accuracy of clinical features of COVID-19 may vary among different populations.

Methods

We conducted a systematic review and meta-analysis of studies from PubMed, Embase, Cochrane Library, Google Scholar, and the WHO Global Health Library for studies evaluating the accuracy of clinical features to predict and prognosticate COVID-19. We used the National Institutes of Health Quality Assessment Tool to evaluate the risk of bias, and the random-effects approach to obtain pooled prevalence, sensitivity, specificity, and likelihood ratios.

Results

Among the 189 included studies (53 659 patients), fever, cough, diarrhoea, dyspnoea, and fatigue were the most reported predictors. In the later stage of the pandemic, the sensitivity in predicting COVID-19 of fever and cough decreased, while the sensitivity of other symptoms, including sputum production, sore throat, myalgia, fatigue, dyspnoea, headache, and diarrhoea, increased. A combination of fever, cough, fatigue, hypertension, and diabetes mellitus increases the odds of having a COVID-19 diagnosis in patients with a positive test (positive likelihood ratio (PLR) = 3.06)) and decreases the odds in those with a negative test (negative likelihood ratio (NLR) = 0.59)). A combination of fever, cough, sputum production, myalgia, fatigue, and dyspnea had a PLR = 10.44 and an NLR = 0.16 in predicting severe COVID-19. Further updating the umbrella review (1092 studies, including 3 342 969 patients) revealed the different prevalence of symptoms in different stages of the pandemic.

Conclusions

Understanding the possible different distributions of predictors is essential for screening for potential COVID-19 infection and severe outcomes. Understanding that the prevalence of symptoms may change with time is important to developing a prediction model.

Investigating the Relationship Between Spiritual Health, Meaning in Life, and Death Attitudes among COVID-19 Patients Discharged from ICUs: A Cross-Sectional Study in Iran

The COVID-19 pandemic has been shown to affect both physical and mental health. Because of this mental health burden, it is important to pay attention to issues such as the relationship between spiritual health, death attitudes and meaning in life - all issues made more prominent during the pandemic. This study was conducted to determine the correlation between these three factors - spiritual health, meaning in life, and death attitudes, among patients with COVID-19 discharged from the intensive care units of hospitals affiliated with Tehran University of Medical Sciences, Tehran, Iran.This cross-sectional, descriptive-analytical study was conducted between April 2020 and August 2021 with 260 participants. The data collection instruments were a demographic characteristics questionnaire, Polotzin and Ellison's Spiritual Health Questionnaire, The Meaning in Life Questionnaire (MLQ), and Death Attitude Profile-Revised (DAP-R).The correlation between meaning in life, spiritual health, and death attitudes was determined by Spearman's correlation coefficient. The research results showed that there is an inverse and significant correlation between spiritual health and death attitudes (p = 0.01); an inverse, but insignificant correlation between existential health and subscales of death attitudes, except for the subscales of approach acceptance and neutral acceptance (p > 0.05); and an inverse, but insignificant, correlation between spiritual health and death attitudes, (p > 0.05). In addition, there was an inverse and significant correlation between the presence of meaning in life and escape acceptance (p = 0.002); an inverse and significant correlation between the search for meaning in life and neutral acceptance (p = 0.007); and an inverse and significant correlation between the meaning in life and death attitudes (p = 0.04). Besides, the findings showed an inverse but insignificant correlation between all spiritual health subscales and the meaning in life subscales (p > 0.05). Spiritual health has an inverse correlation with death attitudes.Also, there is an inverse correlation between the total score of spiritual health and death attitudes. Regarding the subscales of spiritual health, there is an inverse correlation between existential health and death attitudes subscales, except for approach acceptance and neutral acceptance. Also, the results showed an inverse and significant correlation between meaning in life and death acceptance and avoidance subscales, and there was an inverse and significant correlation between the meaning in life and death attitudes. Finally, the increase in spiritual health reduces patients' risks of thinking about death. The research results double the significance of the role of nurses, especially those dealing with critically ill patients and those who have experienced severe disease conditions.

Generation of a SARS-CoV-2 Reverse Genetics System and Novel Human Lung Cell Lines That Exhibit High Virus-Induced Cytopathology

The global COVID-19 pandemic continues with continued cases worldwide and the emergence of new SARS-CoV-2 variants. In our study, we have developed novel tools with applications for screening antivirals, identifying virus-host dependencies, and characterizing viral variants. Using reverse genetics, we rescued SARS-CoV-2 Wuhan1 (D614G variant) wild type (WTFL) and reporter virus (NLucFL) using molecular BAC clones. The replication kinetics, plaque morphology, and titers were comparable between viruses rescued from molecular clones and a clinical isolate (VIDO-01 strain). Furthermore, the reporter SARS-CoV-2 NLucFL virus exhibited robust luciferase values over the time course of infection and was used to develop a rapid antiviral assay using remdesivir as proof-of-principle. In addition, as a tool to study lung-relevant virus-host interactions, we established novel human lung cell lines that support SARS-CoV-2 infection with high virus-induced cytopathology. Six lung cell lines (NCI-H23, A549, NCI-H1703, NCI-H520, NCI-H226, and HCC827) and HEK293T cells were transduced to stably express ACE2 and tested for their ability to support virus infection. A549ACE2 B1 and HEK293TACE2 A2 cell lines exhibited more than 70% virus-induced cell death, and a novel lung cell line, NCI-H23ACE2 A3, showed about ~99% cell death post-infection. These cell lines are ideal for assays relying on live-dead selection, such as CRISPR knockout and activation screens.

Use of machine learning to assess the prognostic utility of radiomic features for in-hospital COVID-19 mortality

As portable chest X-rays are an efficient means of triaging emergent cases, their use has raised the question as to whether imaging carries additional prognostic utility for survival among patients with COVID-19. This study assessed the importance of known risk factors on in-hospital mortality and investigated the predictive utility of radiomic texture features using various machine learning approaches. We detected incremental improvements in survival prognostication utilizing texture features derived from emergent chest X-rays, particularly among older patients or those with a higher comorbidity burden. Important features included age, oxygen saturation, blood pressure, and certain comorbid conditions, as well as image features related to the intensity and variability of pixel distribution. Thus, widely available chest X-rays, in conjunction with clinical information, may be predictive of survival outcomes of patients with COVID-19, especially older, sicker patients, and can aid in disease management by providing additional information.

Physical Impact of SARS-CoV-2 Infection in a Population of Italian Healthcare Workers

SARS-CoV-2 infection often causes symptoms and illness that can last for months after the acute phase, i.e., so-called "Long COVID" or Post-acute COVID-19. Due to the high prevalence of SARS-CoV-2 infection among Healthcare Workers (HCWs), post-COVID-19 symptoms can be common and threaten workers' occupational health and healthcare systems' functioning. The aim of this cross-sectional, observational study was to present data related to post-COVID-19 outcomes in a population of HCWs infected by COVID-19 from October 2020 to April 2021, and to identify possible factors associated with the persistence of illness, such as gender, age, previous medical conditions, and features of acute illness. A total of 318 HCWs who had become infected by COVID-19 were examined and interviewed approximately two months after their recovery from the infection. The clinical examinations were performed by Occupational Physicians in accordance with a specific protocol at the Occupational Medicine Unit of a tertiary hospital in Italy. The mean age of the participants was 45 years old, and 66.7% of the workers were women while 33.3% were men; the sample mainly consisted of nurses (44.7%). During the medical examination, more than half of the workers mentioned that they had experienced multiple residual bouts of illness after the acute phase of infection. Men and women were similarly affected. The most reported symptom was fatigue (32.1%), followed by musculoskeletal pain (13.6%) and dyspnea (13.2%). In the multivariate analysis, dyspnea (p < 0.001) and fatigue (p < 0.001) during the acute stage of illness and the presence of any limitation in working activities, in the context of fitness for a work evaluation performed while the occupational medicine surveillance program was being conducted (p = 0.025), were independently associated with any post-COVID-19 symptoms, which were considered final outcomes. The main post-COVID-19 symptoms-dyspnea, fatigue, and musculoskeletal pain-showed significant associations with dyspnea, fatigue, and musculoskeletal pain experienced during the acute stage of infection, with the presence of limitations in working activities, and pre-existing pneumological diseases. A normal weight according to body mass index was a protective factor. The identification of vulnerable workers as those with limitations in working activities, pneumological diseases, a high BMI, and of an older age and the implementation of preventive measures are key factors for preserving Occupational Health. Fitness-to-work evaluations performed by Occupational Physicians can be considered a complex index of overall health and functionality that can identify workers who may suffer from relevant post-COVID-19 symptoms.

In silico analysis of genomic landscape of SARS-CoV-2 and its variant of concerns (Delta and Omicron) reveals changes in the coding potential of miRNAs and their target genes

COVID-19 related morbidities and mortalities are still continued due to the emergence of new variants of SARS-CoV-2. In the last few years, viral miRNAs have been the centre of study to understand the disease pathophysiology. In this work, we aimed to predict the change in coding potential of the viral miRNAs in SARS-CoV-2's VOCs, Delta and Omicron compared to the Reference (Wuhan origin) strain using bioinformatics tools. After ab-intio based screening by the Vmir tool and validation, we retrieved 22, 6, and 6 pre-miRNAs for Reference, Delta, and Omicron. Most of the predicted unique pre-miRNAs of Delta and Omicron were found to be encoded from the terminal and origin of the genomic sequence, respectively. Mature miRNAs identified by MatureBayes from the unique pre-miRNAs were used for target identification using miRDB. A total of 1786, 216, and 143 high-confidence target genes were captured for GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis. The GO and KEGG pathways terms analysis revealed the involvement of Delta miRNAs targeted genes in the pathways such as Human cytomegalovirus infection, Breast cancer, Apoptosis, Neurotrophin signaling, and Axon guidance whereas the Sphingolipid signaling pathway was found for the Omicron. Furthermore, we focussed our analysis on target genes that were validated through GEO's (Gene Expression Omnibus) DEGs (Differentially Expressed Genes) dataset, in which FGL2, TNSF12, OGN, GDF11, and BMP11 target genes were found to be down-regulated by Reference miRNAs and YAE1 and RSU1 by Delta. Few genes were also observed to be validated among in up-regulated gene set of the GEO dataset, in which MMP14, TNFRSF21, SGMS1, and TMEM192 were related to Reference whereas ZEB2 was detected in all three strains. This study thus provides an in-silico based analysis that deciphered the unique pre-miRNAs in Delta and Omicron compared to Reference. However, the findings need future wet lab studies for validation.

The prognostic value of the Barthel Index for mortality in patients with COVID-19: A cross-sectional study

Objective

This study aimed to analyze the association between the activity of daily living (ADL), coronavirus disease (COVID-19), and the value of the Barthel Index in predicting the prognosis of patients.

Methods

This study included 398 patients with COVID-19, whose ADL at admission to hospital were assessed with the Barthel Index. The relationship between the index and the mortality risk of the patients was analyzed. Several regression models and a decision tree were established to evaluate the prognostic value of the index in COVID-19 patients.

Results

The Barthel Index scores of deceased patients were significantly lower than that of discharged patients (median: 65 vs. 90, P < 0.001), and its decrease indicated an increased risk of mortality in patients (P < 0.001). After adjusting models for age, gender, temperature, pulse, respiratory rate, mean arterial pressure, oxygen saturation, etc., the Barthel Index could still independently predict prognosis (OR = 0.809; 95% CI: 0.750-0.872). The decision tree showed that patients with a Barthel Index of below 70 had a higher mortality rate (33.3-40.0%), while those above 90 were usually discharged (mortality: 2.7-7.2%).

Conclusion

The Barthel Index is of prognostic value for mortality in COVID-19 patients. According to their Barthel Index, COVID-19 patients can be divided into emergency, observation, and normal groups (0-70; 70-90; 90-100), with different treatment strategies.

The Prevalence of COVID-19 in Europe by the End of November 2022: A Cross-Sectional Study

Background The world has been affected differently by the coronavirus disease 2019 (COVID-19), and Europe reaped the largest number of cases and deaths. Moreover, COVID-19 statistics are dynamic. Objectives The current study aimed to use COVID-19 data to examine the COVID-19 prevalence in Europe by the end of November 2022 and compare the findings globally. Methods The primary data on COVID-19 for each European country were obtained from the "Worldometer" website. The data include the cumulative incidence of COVID-19 per country, the cumulative number of deaths, the total number of tests performed, the number of cases per million population, the number of deaths per million, the number of tests per million, and the total population. The case-fatality rate was calculated (number of deaths/number of cases). In addition, the median age and the vaccination coverage rate (people who received two doses) for each European country were extracted from the "United Nations" website and the "Our World in Data" website, respectively. To compare European countries to the globe, COVID-19 data for each continent were obtained. The analysis of variance (ANOVA) test was used to compare variances across the means of the four parts of Europe based on the geographic division. An independent sample t-test was also used to compare the means between the European Union (EU) states and non-EU states. The Spearman correlation coefficient was used to determine the relationship between different variables across Europe. Results As of December 1, 2022, about 648 million COVID-19 cases and 6.6 million deaths have been recorded worldwide. Europe accounted for nearly 36.8% and 29.5% of all cases and deaths, respectively. Based on the number of deaths per million, Europe was the most affected continent after South America. Nearly 6.8 billion tests have been conducted worldwide, 41% done in Europe; 43 European countries have performed tests more than their population. However, COVID-19 statistics were inconsistent across the four parts of Europe. A significant difference was noticed between Eastern Europe and others, especially Northern Europe and Western Europe. By affiliation with the EU, there was no significant difference. For global comparison, the mean deaths per million, the mean cases per million, and the mean tests per population for European countries were higher than those of the world's countries, although they recorded a lower mean case-fatality rate (CFR). Thirteen European countries were among the 15 most affected countries worldwide based on the number of deaths per million, most located in Eastern and Southern Europe. The number of cases and the number of deaths were significantly proportional to the number of tests performed. Conclusions By the end of November 2022, Europe had the most cases of COVID-19, the most deaths, and the most tests performed, even though it accounts for 9.4% of the world's population. However, COVID-19 data were inconsistent across the four parts of Europe, especially between Eastern Europe and others. Given the natural immunity acquired during the three years and the excellent vaccine coverage in Europe, it is essential to reconsider the definition of a suspected case and establish more specific criteria for testing.

Supervised Machine Learning Models to Identify Early-Stage Symptoms of SARS-CoV-2

The coronavirus disease (COVID-19) pandemic was caused by the SARS-CoV-2 virus and began in December 2019. The virus was first reported in the Wuhan region of China. It is a new strain of coronavirus that until then had not been isolated in humans. In severe cases, pneumonia, acute respiratory distress syndrome, multiple organ failure or even death may occur. Now, the existence of vaccines, antiviral drugs and the appropriate treatment are allies in the confrontation of the disease. In the present research work, we utilized supervised Machine Learning (ML) models to determine early-stage symptoms of SARS-CoV-2 occurrence. For this purpose, we experimented with several ML models, and the results showed that the ensemble model, namely Stacking, outperformed the others, achieving an Accuracy, Precision, Recall and F-Measure equal to 90.9% and an Area Under Curve (AUC) of 96.4%.

Evaluation of clinical outcomes, laboratory and imaging data of patients with solid tumor infected with COVID-19 infection

BACKGROUND

COVID-19 is associated with higher mortality rates in patients with cancer. In this study, we aimed to evaluate the clinical outcomes, and laboratory and imaging data of patients with solid tumor infected with COVID-19 infection.

METHODS

This is a cross-sectional retrospective study performed in 2020-2022 on 85 patients with a previous diagnosis of solid tumors infected with COVID-19. We included all patients with tumors of solid organs that were diagnosed with COVID-19 infection and required hospitalization those patients previously hospitalized for treatments and were infected with COVID-19 during hospitalization. Demographic data of patients were collected using a checklist. We collected data regarding clinical outcome (discharge, hospitalization or death), duration of hospitalization, requiring ICU admission, duration of hospitalization divided by received drugs and type of tumor and mean survival time. Furthermore, we collected laboratory data from all patients. The radiologic characteristics of patients were also extracted from their data.

RESULTS

Breast cancer was the most common solid tumor (34.9%), followed by lung cancer (19.3%). The mortality rate was 24.1% (20 patients). The highest mortality rate in this study was for metastatic intestinal cancer to the lung (100%, one patient), followed by metastatic prostatic cancer to lung (50%, three patients). The highest hospitalization duration was for patients with glioblastoma multiform (GBM) (30 days). The mean survival time among patients with mortality was 19.15±1.80 days. The mean CT severity score of all patients was 27.53±22.90. Patient's most common radiologic sign was air space consolidation (89.1%). The highest CT severity score was found in patients with stomach cancer (46.67±5.77).

CONCLUSION

The mortality rate in this study was 24.1%. Based on the results of our study and previous research, special care should be provided to patients with solid tumors during the COVID-19 pandemic and in infected cases.

COVID19 biomarkers: What did we learn from systematic reviews?

The coronavirus disease 2019 (COVID19) pandemic continues to represent a substantial public health concern. It can rapidly progress to severe disease, with poor prognosis and a high mortality risk. An early diagnosis and specific prognostic tools can help healthcare providers to start interventions promptly, understand the likely prognosis and to identify and treat timely individuals likely to develop severe disease with enhanced mortality risk. Here we focused on an impressive set of systematic reviews and meta-analyses that were performed since the start of the COVID19 pandemic and summarized their results related to the levels of hematologic, inflammatory, immunologic biomarkers as well as markers of cardiac, respiratory, hepatic, gastrointestinal and renal systems and their association with the disease progression, severity and mortality. The evidence outlines the significance of specific biomarkers, including inflammatory and immunological parameters (C-reactive protein, procalcitonin, interleukin-6), hematological (lymphocytes count, neutrophil-to-lymphocyte ratio, D-dimer, ferritin, red blood cell distribution width), cardiac (troponin, CK-MB, myoglobin), liver (AST, ALT, total bilirubin, albumin) and lung injury (Krebs von den Lungen-6) that can be used as prognostic biomarkers to aid the identification of high-risk patients and the prediction of serious outcomes, including mortality, in COVID19. Thus, these parameters should be used as essential tools for an early risk stratification and adequate intervention in improving disease outcomes in COVID19 patients.

Associations between Depression and Self-Reported COVID-19 Symptoms among Adults: Results from Two Population-Based Seroprevalence Studies in Switzerland

(1) Mental health may modulate the perceived risk of SARS-CoV-2 infection. However, it is unclear how psychological symptoms may distort symptom perception of COVID-19 and SARS-CoV-2 infection. We assessed whether depressive symptoms predicted self-reported COVID-19 symptoms, independently of serologically confirmed SARS-CoV-2 infection. (2) Participants (aged 20-64) in the Geneva (N = 576) and Ticino (N = 581) Swiss regions completed the Patient Health Questionnaire before being tested for anti-SARS-CoV-2 IgG antibodies and recalled COVID-19-compatible symptoms on two occasions: April-July 2020 (baseline), and January-February 2021 (follow-up). We estimated prevalence ratios for COVID-19 symptoms by depression scores in interaction with serological status. (3) At baseline, in Geneva, higher depression predicted higher probability of reporting systemic, upper airways, and gastro-intestinal symptoms, and fever and/or cough; in Ticino, higher depression predicted systemic, upper airways, and gastro-intestinal symptoms, fever and/or cough, dyspnea, and headache. At follow-up, in Geneva, higher depression predicted higher probability of reporting systemic symptoms and dyspnea; in Ticino, higher depression predicted higher probability of reporting systemic and upper airways symptoms, dyspnea and headache (all p values < 0.05). (4) We found positive associations between depressive symptoms and COVID-19-compatible symptoms, independently of seropositivity. Mental wellbeing has relevant public health implications because it modulates self-reported infection symptoms that inform testing, self-medication, and containment measures, including quarantine and isolation.

Psychological Status of College Students During COVID-19 Pandemic: A Cross-Sectional Study in Saudi Arabia

PURPOSE

This study aimed to assess the prevalence and associated factors of depression, anxiety, and stress among college students in Saudi Arabia during the COVID-19 outbreak.

METHODS

This cross-sectional study was conducted between February 10th to April 10th, 2021. An online self-administered questionnaire was emailed to college students at a large institution in Saudi Arabia. The questionnaire consisted of sociodemographic, educational backgrounds, and the Depression Anxiety Stress Scale-21 (DASS-21).

RESULTS

The study included 311 university students (62.7% female and 39.3% male). The prevalence of higher than moderate level in each of the depression, anxiety, and stress were (n= 164, 52.7%), (n= 222, 71.4%), and (n= 112, 36%), respectively. Further analysis revealed that females, younger age, history of depression, history of being quarantined by a health authority, and having contact with a confirmed case of COVID-19 were associated with a greater level of depression, anxiety, and stress.

CONCLUSION

Depression, anxiety, and stress were highly prevalent among college students during the outbreak. There was a significant association between demographic characteristics and the DASS 21 score. Researchers are recommended to concentrate their future studies on establishing strategies to enhance students' flexibility and adaptability in the face of future catastrophes.

COVID-19 Statistics in the Arab World by the End of October 2022: A Cross-Sectional Study

Background The coronavirus disease 2019 (COVID-19) has affected almost all world countries, including all 22 Arab countries. However, over the last 34 months, the world has suffered from the pandemic unevenly, and COVID-19 statistics are dynamic. Objectives The current study aimed to use COVID-19 data to examine COVID-19 statistics (including the number of cases/deaths/tests) in Arab countries by the end of October 2022 and compare the findings with global statistics. This study was also used to determine the extent to which statistics vary across Arab countries. Methods The primary data on COVID-19 for each Arab country were obtained from the "Worldometer" website. The data include the cumulative incidence of COVID-19 per country, the cumulative number of deaths, the total number of tests performed, the number of cases per million population, the number of deaths per million, the number of tests per million, and the total population. The case-fatality rate (CFR) was calculated (number of deaths/number of cases). In addition, the median age for each Arab country was extracted from the United Nations website. The rate of vaccination coverage (people who received two doses) was extracted from the "Our World in Data" website. COVID-19 statistics were further analyzed in Arab countries in Asia compared to those in Africa at the end of 2020, 2021, and October 2022. To compare the Arab countries to the globe, COVID-19 data for each continent were obtained. The Spearman correlation coefficient was used to determine the relationship between different variables across Arab countries. Results As of November 1, 2022, about 636 million COVID-19 cases and 6.6 million deaths had been recorded worldwide. Arab countries accounted for nearly 2.21% and 2.62% of all cases and deaths, respectively. In general, the mean deaths per million and the mean cases per million for Arab countries were lower than those of the world's countries, although Arab countries recorded a higher mean case-fatality rate. Alternatively, Arab countries in aggregate recorded fewer deaths per million (381) than the world (830). However, statistics across Arab countries have been inconsistent; Arab countries in Africa were less affected. Arab countries have performed approximately 359 million tests (5.29% of all tests), 93% of which were performed by Arab countries in Asia. Moreover, 54.4% of all tests were performed in the United Arab Emirates. Yemen, Somalia, Sudan, Algeria, Syria, Comoros, and Djibouti were the least affected Arab countries based on the number of deaths per million. With the exception of Comoros, these countries were among the least vaccinated in the Arab world. Conclusions In general, Arab countries have been less affected by the COVID-19 pandemic than the rest of the world. However, statistics vary across Arab countries, especially regarding the number of tests performed. Given the natural immunity acquired during the three years and the relatively good vaccine coverage in the Arab world, it is important to reconsider the definition of a suspected case and establish more specific criteria for testing.

Clinical and Epidemiological Presentation of COVID-19 among Children in Conflict Setting

Background: This study aims to describe the observable symptoms of children with COVID-19 infection and analyze access to real-time polymerase chain reaction (RT-PCR) testing among children seeking care in Yemen. Method: In the period of March 2020−February 2022, data were obtained from 495 children suspected to have been infected with COVID-19 (from a larger register of 5634 patients) from the Diseases Surveillance and Infection Control Department at the Ministry of Public Health and Population in Aden, Yemen. Results: Overall, 21.4% of the children with confirmed COVID-19 infection were asymptomatic. Fever (71.4%) and cough (67.1%) were the most frequently reported symptoms among children, and children were less likely to have fever (p < 0.001), sore throat (p < 0.001) and cough (p < 0.001) compared to adults. A lower frequency of COVID-19-associated symptoms was reported among children with positive RT-PCR tests compared to children with negative tests. A lower rate of testing was conducted among children (25%) compared to adults (61%). Fewer tests were carried out among children <5 years (11%) compared to other age groups (p < 0.001), for children from other nationalities (4%) compared to Yemeni children (p < 0.001) and for girls (21%) compared to boys (30%) (p < 0.031). Conclusion: Understanding and addressing the cause of these disparities and improving guidelines for COVID-19 screening among children will improve access to care and control of the COVID-19 pandemic.

Validation of the T-Lymphocyte Subset Index (TLSI) as a Score to Predict Mortality in Unvaccinated Hospitalized COVID-19 Patients

Lymphopenia has been consistently reported as associated with severe coronavirus disease 2019 (COVID-19). Several studies have described a profound decline in all T-cell subtypes in hospitalized patients with severe and critical COVID-19. The aim of this study was to assess the role of T-lymphocyte subset absolute counts measured at ward admission in predicting 30-day mortality in COVID-19 hospitalized patients, validating a new prognostic score, the T-Lymphocyte Subset Index (TLSI, range 0−2), based on the number of T-cell subset (CD4+ and CD8+) absolute counts that are below prespecified cutoffs. These cutoff values derive from a previously published work of our research group at Policlinico Tor Vergata, Rome, Italy: CD3+CD4+ < 369 cells/μL, CD3+CD8+ < 194 cells/μL. In the present single-center retrospective study, T-cell subsets were assessed on admission to the infectious diseases ward. Statistical analysis was performed using JASP (Version 0.16.2. JASP Team, 2022, Amsterdam, The Netherlands) and Prism8 (version 8.2.1. GraphPad Software, San Diego, CA, USA). Clinical and laboratory parameters of 296 adult patients hospitalized because of COVID-19 were analyzed. The overall mortality rate was 22.3% (66/296). Survivors (S) had a statistically significant lower TLSI score compared to non-survivors (NS) (p < 0.001). Patients with increasing TLSI scores had proportionally higher rates of 30-day mortality (p < 0.0001). In the multivariable logistic analysis, the TLSI was an independent predictor of in-hospital 30-day mortality (OR: 1.893, p = 0.003). Survival analysis showed that patients with a TLSI > 0 had an increased risk of death compared to patients with a TLSI = 0 (hazard ratio: 2.83, p < 0.0001). The TLSI was confirmed as an early and independent predictor of COVID-19 in-hospital 30-day mortality.

COVID-19 Pneumonia: Clinical Manifestations

Coronavirus disease-2019 (COVID-19) pneumonia has diverse clinical manifestations, which have shifted throughout the pandemic. Formal classifications include presymptomatic infection and mild, moderate, severe, and critical illness. Social risk factors are numerous, with Black, Hispanic, and Native American populations in the United States having suffered disproportionately. Biological risk factors such as age, sex, underlying comorbid burden, and certain laboratory metrics can assist the clinician in triage and management. Guidelines for classifying radiographic findings have been proposed and may assist in prognosis. In this article, we review the risk factors, clinical course, complications, and imaging findings of COVID-19 pneumonia.

Effect of COVID-19 vaccines for the treatment of people with post-COVID-19 condition: a rapid review

Background: Vaccination for coronavirus disease 2019 (COVID-19) has demonstrated reduced risk of hospitalisation and death against more recent variants of COVID-19. Some studies suggested improvements in patients with post-COVID-19 condition (PCC) following vaccination. We systematically explored available evidence on the effect of COVID-19 vaccines for the treatment of people with PCC. Methods: We conducted a rapid review of the literature following systematic approaches. We searched Medline (OVID), EMBASE (Elsevier), ClinicalTrials.gov, and the International Clinical Trials Registry Platform (ICTRP) for randomised trials, non-randomised trials, controlled before-after studies, and interrupted time-series studies of the effect of COVID-19 vaccines for treating people with PCC. Two independent review authors screened citations. Two review authors  extracted data independently. We had planned to assess the risk of bias and use the GRADE approach (Grading of Recommendations, Assessment, Development, and Evaluation) to assess the certainty of evidence if there were completed studies. Results: We identified two ongoing randomised controlled trials. Both trials examine the effectiveness of therapeutic vaccines on PCC. The anticipated completion date of the CIMAvax-EGFA trial is January 2023, and the completion date of the COVID-19 mRNA vaccine trial is not stated. Conclusions: There is currently an absence of high‐quality evidence evaluating the effectiveness of COVID-19 vaccines for treating people with post-COVID-19 condition. The absence of published studies and only two ongoing trials highlight the need for additional studies on the effectiveness of vaccines for PCC. We recommend that researchers consider PCC as per the definition provided by the World Health Organization and use the available core outcome set for PCC in deciding which outcomes to measure and report in the trials. PROPSERO registration: CRD42022330821 (20/06/2022)

A Hitchhiker's Guide to Worldwide COVID-19 Vaccinations: A Detailed Review of Monovalent and Bivalent Vaccine Schedules, COVID-19 Vaccine Side Effects, and Effectiveness Against Omicron and Delta Variants

For the primary prevention of coronavirus disease 2019 (COVID-19), there are currently four different vaccines available in the USA. These are Pfizer (messenger RNA [mRNA]), Moderna (mRNA), Novavax (recombinant protein), and Jansen/Johnson & Johnson (adenoviral vector). All individuals should get vaccinated, and the Centers for Disease Control and Prevention (CDC) has provided comprehensive guidelines on recommended doses, their frequency by age group, and vaccine types, all discussed in detail in this article. Vaccines are a critical and cost-effective tool for preventing the disease. Prior to receiving a vaccine, patients should get adequate counseling regarding any potential adverse effects post vaccination. Appropriate safety precautions must be taken for those more likely to experience adverse consequences. Healthcare professionals should be aware of the symptoms, indicators, and treatment of any adverse event post-vaccination. We have provided a comprehensive review of the different characteristics of COVID-19 vaccines available in the United States, including their effectiveness against various variants, adverse effects, and precautions necessary for healthcare professionals and the general population. This article also briefly covers COVID-19 vaccines available worldwide, specifically their mode of action and effectiveness.

Artificial intelligence model on chest imaging to diagnose COVID-19 and other pneumonias: A systematic review and meta-analysis

Objectives

When diagnosing Coronavirus disease 2019(COVID‐19), radiologists cannot make an accurate judgments because the image characteristics of COVID‐19 and other pneumonia are similar. As machine learning advances, artificial intelligence(AI) models show promise in diagnosing COVID-19 and other pneumonias. We performed a systematic review and meta-analysis to assess the diagnostic accuracy and methodological quality of the models.

Methods

We searched PubMed, Cochrane Library, Web of Science, and Embase, preprints from medRxiv and bioRxiv to locate studies published before December 2021, with no language restrictions. And a quality assessment (QUADAS-2), Radiomics Quality Score (RQS) tools and CLAIM checklist were used to assess the quality of each study. We used random-effects models to calculate pooled sensitivity and specificity, I² values to assess heterogeneity, and Deeks' test to assess publication bias.

Results

We screened 32 studies from the 2001 retrieved articles for inclusion in the meta-analysis. We included 6737 participants in the test or validation group. The meta-analysis revealed that AI models based on chest imaging distinguishes COVID-19 from other pneumonias: pooled area under the curve (AUC) 0.96 (95 % CI, 0.94–0.98), sensitivity 0.92 (95 % CI, 0.88–0.94), pooled specificity 0.91 (95 % CI, 0.87–0.93). The average RQS score of 13 studies using radiomics was 7.8, accounting for 22 % of the total score. The 19 studies using deep learning methods had an average CLAIM score of 20, slightly less than half (48.24 %) the ideal score of 42.00.

Conclusions

The AI model for chest imaging could well diagnose COVID-19 and other pneumonias. However, it has not been implemented as a clinical decision-making tool. Future researchers should pay more attention to the quality of research methodology and further improve the generalizability of the developed predictive models.

Prevalence of Malaria and Covid-19 in Febrile Patients in Lomé, Togo in 2020

Purpose

The objective of this study was to estimate the prevalence of malaria and Covid-19 by PCR and serological tests in febrile patients in Lomé.

Methods

A cross-sectional study was conducted from September 1 to October 31, 2020 in febrile patients ≥ 10 years in three health facilities in Lomé. Finger stick blood was collected to detect Plasmodium spp. using thin/thick smear and venous blood on EDTA tubes to test for malaria Histidin-Rich-Protein-2 antigen using rapid diagnostic tests (RDT) and SARS-CoV-2 antibodies specific immunoglobulin (Ig) M and G. Detection of SARS-CoV-2 in nasopharyngeal samples was performed by rRT-PCR using GeneXpert.

Results

A total of 243 participants (61.7% of female) with median age 28 years (IQR 18–41) were included in the study. Prevalence of malaria was 25.1%, 95% CI [19.8–31.0] and 30.4%, 95% CI [24.7–36.7] for thin/thick smear and rapid malaria test, respectively. Eighteen patients (7.4%, 95% CI [4.4–11.5]) were positive for SARS-CoV-2 and forty-two (17.3%, 95% CI [12.8–22.6]) were positive for IgM and/or IgG against SARS-CoV-2. SARS-CoV-2 IgM seroprevalence was significantly higher in malaria RDT positive participants (33.8% vs. 10.1%, p < 0.001).

Conclusion

This study confirms a possible cross-reactivity between Covid-19 and malaria in case of single use of rapid tests, suggesting a possible past contamination. In case of clinical signs related to Covid-19 in malaria-endemic areas, PCR screening should be requested in order to identify and isolate patients.

Accuracy of the Traditional COVID-19 Phone Triaging System and Phone Triage-Driven Deep Learning Model

Objectives:

During the COVID-19 pandemic, a quick and reliable phone-triage system is critical for early care and efficient distribution of hospital resources. The study aimed to assess the accuracy of the traditional phone-triage system and phone triage-driven deep learning model in the prediction of positive COVID-19 patients.

Setting:

This is a retrospective study conducted at the family medicine department, Cairo University.

Methods:

The study included a dataset of 943 suspected COVID-19 patients from the phone triage during the first wave of the pandemic. The accuracy of the phone triaging system was assessed. PCR-dependent and phone triage-driven deep learning model for automated classifications of natural human responses was conducted.

Results:

Based on the RT-PCR results, we found that myalgia, fever, and contact with a case with respiratory symptoms had the highest sensitivity among the symptoms/ risk factors that were asked during the phone calls (86.3%, 77.5%, and 75.1%, respectively). While immunodeficiency, smoking, and loss of smell or taste had the highest specificity (96.9%, 83.6%, and 74.0%, respectively). The positive predictive value (PPV) of phone triage was 48.4%. The classification accuracy achieved by the deep learning model was 66%, while the PPV was 70.5%.

Conclusion:

Phone triage and deep learning models are feasible and convenient tools for screening COVID-19 patients. Using the deep learning models for symptoms screening will help to provide the proper medical care as early as possible for those at a higher risk of developing severe illness paving the way for a more efficient allocation of the scanty health resources.

Is Coronavirus Infection Associated With Musculoskeletal Health Complaints? Results From a Comprehensive Case-Control Study

Objective:

This case-control study investigated the association between SARS-CoV-2 infection and musculoskeletal health complaints (MHC). The specific aims of the study were (1) to compare the 1-month prevalence of MHC among post-acute COVID-19 patients and participants who never tested positive for COVID-19 matched by the former group’s age and gender; (2) to identify the predictors of MHC among all participants, and (3) define the factors independently associated with MHC in post-acute COVID-19 patients.

Methods and Analysis:

The study was conducted in Bangladesh from February 24 to April 7, 2022. The face-to-face interview was taken using a paper-based semi-structured questionnaire. MHC was measured using the musculoskeletal subscale of subjective health complaints produced by Eriksen et al. Descriptive analysis was conducted to compute MHC prevalence and compare them across groups. Multiple logistic analyses were employed to identify MHC predictors for the participants.

Results:

The prevalence of MHC was 38.7%. Adjusted analysis suggested that the SARS-CoV-2 infection was independently associated with MHC (AOR = 3.248,95% CI = 2.307-4.571). Furthermore, unemployment (AOR = 4.156, 95% CI = 1.308-13.208), moderate illness (AOR = 2.947,95% CI = 1.216-7.144), treatment in hospitals’ general word (AOR = 4.388,95% CI = 1.878-10.254) and health complaints after COVID-19 (AOR = 4.796,95% CI = 2.196-10.472) were found to be the predictors of MHC among post-acute COVID-19 patients.

Conclusion:

Our study found a robust association between SARS-CoV-2 infection and MHC and recommends that healthcare authorities be prepared to deal with the high burden of MHC among post-acute COVID-19 patients.