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This study aims to reveal the strengths and limitations of the WhatsApp application as a support service in distance education, conducted through a learning management system during the Covid-19 pandemic, and make suggestions on improving its use in this capacity. Despite the lack of readiness on the part of the students and the lack of sufficient knowledge regarding distance education during the pandemic, many universities had to revert to emergency remote teaching. This situation necessitated the intensive use of various support services for the students to get the most out of their emergency remote teaching However, their lack of experience with distance education prevented them from using the support services offered by learning management systems. Due to the increasingly widespread use of mobile technologies, one of the support services used by course instructors became the WhatsApp application. The following research is a qualitative case study. The sample for the study was determined through purposive sampling. The data was analyzed using the content analysis method. Nvivo qualitative data analysis software was used to contribute to the detailed and versatile data analysis. The most important results of the study were that the application supported and strengthened distance learning by allowing instant communication, but that the absence of a moderator caused various limitations in this communication. In addition, it was concluded that incorporating natural language processing techniques into learning management systems and clearly stated rules by course instructors improved the use of such instant communication applications as a support service for distance education © 2023,Turkish Online Journal of Distance Education. All Rights Reserved.
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Background Investigating the people who suffer from post-COVID health conditions is necessary to accommodate the demand for accessing healthcare. This study aims to describe post-COVID health conditions within six months after diagnosis. Methods This study was conducted at Dokuz Eylul University Hospital, a tertiary care hospital in Ä°zmir-Turkey. Participants aged ≥18 years who were diagnosed as SARS-CoV-2 RNA positive in the hospital from November 1st, 2020 to May 31st were interviewed by phone at one, three and six months after diagnosis. Symptom frequencies were stratified by demographic and clinical characteristics. The dependent variable was having post-COVID condition according to World Health Organization's definition. We estimated logistic regression models to identify associated factors for post-COVID condition in the patients who had symptoms at baseline. Results A total of 5083 people completed the third month's interview. The prevalence of post-COVID condition was 21.8% (n = 1108). Tiredness/fatigue (10.2%), muscle or body aches (7.3%) and dyspnea/difficulty breathing (4.8%) were the most common symptoms. Older age (65-74 aged groups versus 18-24 aged group, odds ratio-OR:1.57, 95% confidence interval: 1.10-2.25), female gender (OR: 1.97, 1.71-2.28), bad economic status (OR: 1.44, 1.13-1.84), having more health conditions (≥3 conditions, OR: 1.82, 1.28-2.55), having more symptoms (>5 symptoms, OR: 2.59, 2.20-3.07) and hospitalization (intensive care unit, OR: 1.98, 1.13-3.37) were found to be associated with reporting of post-COVID condition. Conclusions This study identifies the prevalence and risk factors for post-COVID conditions in a large cohort of patients. The results of the study would guide the healthcare organizations in the planning of post-COVID management strategies. Key messages • The prevalence of post-COVID conditions was 21.8%. Older age, female gender, having more health conditions, disease severity in the acute phase and bad economic status were risk factors. • Clinical management strategies and country-specific healthcare planning should be devised for the post-COVID condition burden.
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Objective: All equipment and personnel used in the healthcare field during the COVID-19 pandemic may need to be used for the isolation, diagnosis and treatment of pandemic patients. So we think that there may have been some delays in surgical treatment in the oncological patient group during the pandemic period. For this reason, we aimed to compare the demographic and clinicopathological characteristics of patients who were operated with the diagnosis of breast cancer before and during the pandemic in our center. Material and Method: The study was retrospectively designed at Eskisehir Osmangazi University Hospital General Surgery Clinic. Demographic and clinicopathological data of all patients who were operated for breast cancer 9 months before and 9 months after the declaration of the pandemic were retrospectively analyzed and compared statistically.
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Introduction: Since the beginning of the pandemic, factors associated with mortality in patients with corona virus infection disease 2019 (COVID-19) have been investigated. Comorbidities and increased age have been frequently reported to be associated with mortality. We aimed to evaluate the factors associated with unfavorable outcome of patients with COVID-19 at an early period of the pandemic. Methodology: This single center, retrospective, observational study was conducted among laboratory confirmed COVID-19 patients hospitalized between March 11 and May 5, 2020, at Umraniye Training and Research Hospital, Istanbul, Turkey. The effects of the severity of illness, comorbidities, symptoms, and laboratory findings on the clinical outcome were evaluated. Factors associated with unfavorable outcome (necessity of mechanical ventilation or death) were examined using Cox proportional hazards models. Results: Out of a total of 728 patients, 53.8% were men and median age 54 years. The 30-day mortality rate was 4.9% among all hospitalized patients. A logistic regression model identified six predictors of unfavorable clinical outcome: age, severity of illness, the numbers of comorbidities, lymphopenia, high levels of C-reactive protein, and procalcitonin. Conclusions: The mortality rate was lower among the patients with COVID-19, hospitalized during the early period of the pandemic. Older age, higher severity score on admission, the numbers of comorbidities, higher levels of C-reactive protein, procalcitonin, and lymphopenia were identified to be associated with unfavorable outcome of the hospitalized patients with COVID-19. Copyright © 2022 Ozel et al.
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Objective The frequency of coinfections in pediatric Coronavirus disease 2019 (COVID-19) cases and their impact on the clinical course are not fully understood. We aimed to investigate the viral and bacterial respiratory pathogens in children admitted to the pediatric emergency department (PED), their clinical course, and the presence of coinfections during the early months of the COVID-19 pandemic. Methods Clinical, laboratory and radiological findings, viral and bacterial pathogens detected by multiplex polymerase chain reaction (PCR) tests in nasopharyngeal swabs, clinical course, and treatments of all children who were tested for severe acute respiratory coronavirus 2 (SARS-CoV-2) at the PED between March 16 and May 15, 2020, were recorded. SARS-CoV-2 PCR-positive and negative groups were compared. Results Out of 570 patients tested for SARS-CoV-2 during the study period, 43 were found positive (7.5%). Non-SARS-CoV-2 viral pathogens were more common in the SARS-CoV-2 PCR-negative group than the SARS-CoV-2 PCR-positive group (13.2%, n=68 versus 4.7%, n=2), but this result was not statistically significant. Leukocyte, neutrophil, lymphocyte, and platelet counts were lower in SARS-CoV-2 PCR-positive group. Bacterial panel positivity was significantly higher in the SARS-CoV-2 PCR-positive group compared with the SARS-CoV-2 PCR-negative group (52%, n=12 versus 28%, n=91;p<0.05). The presence of coinfection did not alter the course of therapy in SARS-CoV-2 PCR-positive cases. Conclusion While viral coinfections were rare, bacterial panel positivity was common in children with COVID-19, but this had not influenced management decisions. The limitations of the tests should be kept in mind while interpreting the results.
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Introduction: The management of the patients with COVID-19 is depend on the clinical presentation. We aimed to evaluate the hospitalization rates due to the progression of the illness in the fist month, the mortality and reinfection rates of the patients with mild COVID-19 during the six months follow-up. Materials and Methods: The study with retrospective design included all SARS CoV-2 PCR positive patients presenting with mild disease to our hospital and who were recommended at-home follow-up during the first month of the COVID-19 pandemic. Demographic characteristics, baseline symptoms, laboratory results and the treatments administered were recorded. The patients were called by phone at six months after the diagnosis. Patients were asked to report hospitalisation at first month, hospitalisation due to any reason and possi- ble reinfections and current symptoms at six month. We noted the mortality rates at first month and at six months from hospital records. Results: The study included 210 patients;130 patients were male. The mean age was 42.3 +/- 15.7 (16-96) years. At baseline, 168 patients (80%) were symptomatic. Fifty-two patients (75.2%) had comorbidities. Thorax computed tomography (CT) was congruent with COVID-19 infection in 46 patients (26%). Twenty-seven patients (16.5%) were hospitalised due to the progression of clinical condition and four (2.4%) needed intensive care transmission. In multivariate analysis, those with comorbidity had having 8.2 fold (95%CI 2.2933.12) D-dimer >= 1 ug/mL had 17.8 fold (OR: 17.8, %95 GA: 3.42-113.3), and diffuse infiltrations in thorax CT scan had 5.36-fold (95% CI 1.46-21.76) higher relative risk for post-COVID hospitalisation. Two (4.1%) out of 48 patients younger than 50 years old and with no risk factors and a normal thorax CT needed hospitalisation. There was no mortality at first month. Four patients (1.9%) died due to deterioration of underlying condition during the six-month follow up. Six patients (3.6%) were considered to be reinfected six months after the first episode. Twenty-six patients (15.6%) had current symptoms which they belived had occured after COVID-19 infection. Conclusion: In the case of the presence of comorbidities, high D-dimer value and diffuse infiltration in thorax CT scan in mild COVID-19 patients, hospitalisation may be the optimal approach.
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Background and aim There is limited research on how common the longer-term effects of COVID-19. This study aimed to describe changes in symptoms of COVID-19 patients at the 1st and 3rd months after diagnosis. Methods Patients older than 18-years who tested positive for SARS-CoV-2 RNA in Dokuz Eylül University Hospital-Turkey in December 2020 (n = 1434) were included in this prospective cohort study. Overall, 1029 patients (71.8%) completed the 1st month and 3rd-month follow-up. Data on demographic characteristics, chronic disease history, symptom history and hospitalization were collected via telephone interviews. Based on the relapsing nature of the disease, the presence or absence of any COVID-19 related symptoms within a week before the 1st and 3rd-month interview was questioned. Categorical variables (n, %) were compared using the chi-square test. Results Of the 1029 patients, 92.8% were symptomatic. The most common initial symptoms were muscle or body aches (58.5%), fatigue (57.8%) and loss of smell (53.1%). Among the symptomatic patients, 40.8% and 27.6% reported at least one symptom in the 1st and 3rd months, respectively. Mean number of symptoms was 4.5±2.6 at diagnosis, 2.3±1.7 at the 1st month and 2.5±2.3 at the 3rd month. The most common persistent symptoms by the 1st month were muscle or body aches (11.1%), heart palpitations (6.4%), and shortness of breath (5.8%). Muscle or body aches (9.5%), shortness of breath (4.2%) and fatigue (4.2%) were reported as persistent by the 3rd month. Persistent symptoms up to the 3rd month were more common in women (33.3% vs 21.3%, p < 0.001), in the patients aged >50 years (32.8% vs 25%, p = 0.01) and in the patients with comorbidities (31.8% vs 25.1%, p = 0.03). Conclusions Over a quarter of patients (27.6%) reported persistent symptoms even after 3 months of diagnosis. Rehabilitation and long-term monitoring programs for patients aged >50 years with comorbidities could be useful in responding to this problem. Key messages Over a quarter of patients report persisting symptoms even after 3 months of initial diagnosis. Follow-up programs could be useful in appropriately managing any persistent or emerging long-term sequelae.
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Background There is limited research on children infected with Covid-19 after initial diagnosis. The aim of this study was to describe changes in symptoms in children infected by Covid-19 after 1st and 3rd months of diagnosis. Methods Covid-19 patients age under 18 admitted to the Dokuz Eylul University Hospital, Izmir, Turkey during December 2020 (n = 144) and completed three months follow-up (n = 123) were included in this prospective cohort study. Data on age, sex, parents' educational status, perceived economic status, presence of Covid-19 patient at household, chronic diseases history, initial and existing symptoms and perception of recovery were collected via telephone interviews. Persistent symptom was defined as any symptom reported within a week of the interview. Chi-square and Mann-Whitney U Test were used for univariate analyses. Results Out of 124 patients, 89.3% reported a symptom at time of diagnosis, 21.0% at 1st month and 11.4% at the 3rd-month follow-up. Median number of symptoms was 2 at diagnosis, 0 at 1st and the 3rd month. The most common initial symptoms were fever (52.4%), weakness (40.3%), flu like symptoms (25.8%) and cough (24.4%). The most common persistent symptoms by the 1st month were fatigue (5.7%), cough (4.1%) and gastrointestinal symptoms (4.1%), and by the 3rd month were fatigue (2.4%), weakness (2.4%), respiratory symptoms and chest pain (2.4%). 10.6% of the patients were not fully recovered by the 3rd month. Persistent symptoms at the end of 1st month were more common in children with chronic diseases (36.6% vs 13.3%, p = 0.003) and who were not recovered fully (63.6% vs 15.5%, p = 0.001). Parents' education level, perceived economic status, and presence of Covid-19 patients at household were not associated with persisting symptoms. Conclusions COVID-19 symptoms may persist by three months of infection, especially in children with chronic conditions. Health care providers should consider following up those children with special care. Key messages COVID-19 symptoms may persist by three months of infection, especially in children with chronic conditions. Health care providers should consider following up those children with special care.
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BACKGROUND: Early recognition of the severe illness is critical in coronavirus disease-19 (COVID-19) to provide best care and optimize the use of limited resources. OBJECTIVES: We aimed to determine the predictive properties of common community-acquired pneumonia (CAP) severity scores and COVID-19 specific indices. METHODS: In this retrospective cohort, COVID-19 patients hospitalized in a teaching hospital between 18 March-20 May 2020 were included. Demographic, clinical, and laboratory characteristics related to severity and mortality were measured and CURB-65, PSI, A-DROP, CALL, and COVID-GRAM scores were calculated as defined previously in the literature. Progression to severe disease and in-hospital/overall mortality during the follow-up of the patients were determined from electronic records. Kaplan-Meier, log-rank test, and Cox proportional hazard regression model was used. The discrimination capability of pneumonia severity indices was evaluated by receiver-operating-characteristic (ROC) analysis. RESULTS: Two hundred ninety-eight patients were included in the study. Sixty-two patients (20.8%) presented with severe COVID-19 while thirty-one (10.4%) developed severe COVID-19 at any time from the admission. In-hospital mortality was 39 (13.1%) while the overall mortality was 44 (14.8%). The mortality in low-risk groups that were identified to manage outside the hospital was 0 in CALL Class A, 1.67% in PSI low risk, and 2.68% in CURB-65 low-risk. However, the AUCs for the mortality prediction in COVID-19 were 0.875, 0.873, 0.859, 0.855, and 0.828 for A-DROP, PSI, CURB-65, COVID-GRAM, and CALL scores respectively. The AUCs for the prediction of progression to severe disease was 0.739, 0.711, 0,697, 0.673, and 0.668 for CURB-65, CALL, PSI, COVID-GRAM, A-DROP respectively. The hazard ratios (HR) for the tested pneumonia severity indices demonstrated that A-DROP and CURB-65 scores had the strongest association with mortality, and PSI, and COVID-GRAM scores predicted mortality independent from age and comorbidity. CONCLUSION: Community-acquired pneumonia (CAP) scores can predict in COVID-19. The indices proposed specifically to COVID-19 work less than nonspecific scoring systems surprisingly. The CALL score may be used to decide outpatient management in COVID-19.