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1.
SSRN; 2022.
Preprint in English | SSRN | ID: ppcovidwho-334460

ABSTRACT

Background: The long-term consequences of the coronavirus disease 19 (COVID-19) are likely to be frequent but results hitherto are inconclusive. Therefore, we aimed to summarize the state-of-the-art literature in relation to long COVID symptomatology, using a systematic review and meta-analysis of observational studies. Methods: A systematic search in several databases was carried out up to 12 January 2022 for observational studies reporting the incidence rate of long COVID signs and symptoms divided according to body systems affected and defined using the World Health Organization criteria. Data are reported as incidence and 95% confidence intervals (CIs). Several sensitivity and meta-regression analyses were moreover performed. Findings: Among 11,162 papers initially screened, 196 studies were included, consisting of 120,970 participants (mean age: 52.3 years;48.8% females) who were followed-up for a median of six months. The incidence of any long COVID symptomatology was 56.9% (95%CI: 52.2-61.6). General long COVID signs and symptoms were the most frequent (incidence of 31%), digestive issues the less frequent (7.7%). Higher percentage of females moderated the onset of any, neurological, general and cardiovascular long COVID symptomatology, whilst higher mean age was associated with higher incidence of psychiatric, respiratory, general, digestive and skin conditions. The incidence of long COVID symptomatology was different according to continent, age and follow-up length. Interpretation: Long COVID is a common condition in patients who have been infected with SARS-CoV-2, whether symptomatically or asymptomatically, and often regardless of the severity of the acute illness indicating the need for more cohort studies on this topic.

2.
Commun Dis Intell (2018) ; 462022 Apr 26.
Article in English | MEDLINE | ID: covidwho-1812120

ABSTRACT

Effective control of coronavirus disease 2019 (COVID-19) has been challenging, in part due to significant asymptomatic and pre-symptomatic transmission of disease. Reducing the time between symptom onset and COVID-19 testing and isolation allows enhanced outbreak control. The purpose of this study is to describe the time taken by participants to present to general practitioner-led (GP) respiratory clinics for assessment following the development of symptoms, and to explore associations between demographic and geographic characteristics and the time to presentation. A total of 314,148 participants, who were assessed in GP respiratory clinics between 1 February and 31 August 2021, were included in the analysis. The median age of participants at presentation was 33 years (interquartile range, IQR: 15-49). The median time from development of symptoms to presentation for assessment at GP respiratory clinics was 2 days (IQR: 1-3). Participants were more likely to present within one day of symptom onset if they were aged between 15 and 64 years (43.4%), lived in urban areas (40.9%) or were non-Indigenous (40.2%). Participants in New South Wales and Victoria had twice the odds (OR 2.01; 95% confidence interval (CI): 1.95, 2.08) of presenting at a GP respiratory clinic within one day of symptom onset in August 2021, when there was a COVID-19 outbreak in those states, than they did in March 2021, when there was no COVID-19 outbreak in Australia. The number of days from symptom onset to presentation at a GP respiratory clinic was strongly associated with the presence of a COVID-19 outbreak. Participant age, location of the clinic, and Indigenous status of participants were also associated with the time to presentation. This study highlights the importance of recognising COVID-19 as a potential cause of symptoms, as well as the importance of providing easily accessible, and culturally appropriate, testing facilities for the population.


Subject(s)
COVID-19 , General Practitioners , Adolescent , Adult , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19 Testing , Humans , Middle Aged , Primary Health Care , SARS-CoV-2 , Victoria , Young Adult
3.
Front Neurol ; 13: 820864, 2022.
Article in English | MEDLINE | ID: covidwho-1809450

ABSTRACT

Background: Severe coronavirus disease 2019 (COVID-19) is characterized, in part, by an excessive inflammatory response. Evidence from animal and human studies suggests that vagus nerve stimulation can lead to reduced levels of various biomarkers of inflammation. We conducted a prospective randomized controlled study (SAVIOR-I) to assess the feasibility, efficacy, and safety of non-invasive vagus nerve stimulation (nVNS) for the treatment of respiratory symptoms and inflammatory markers among patients who were hospitalized for COVID-19 (ClinicalTrials.gov identifier: NCT04368156). Methods: Participants were randomly assigned in a 1:1 allocation to receive either the standard of care (SoC) alone or nVNS therapy plus the SoC. The nVNS group received 2 consecutive 2-min doses of nVNS 3 times daily as prophylaxis. Efficacy and safety were evaluated via the incidence of specific clinical events, inflammatory biomarker levels, and the occurrence of adverse events. Results: Of the 110 participants who were enrolled and randomly assigned, 97 (nVNS, n = 47; SoC, n = 50) had sufficient available data and comprised the evaluable population. C-reactive protein (CRP) levels decreased from baseline to a significantly greater degree in the nVNS group than in the SoC group at day 5 and overall (i.e., all postbaseline data points collected through day 5, combined). Procalcitonin level also showed significantly greater decreases from baseline to day 5 in the nVNS group than in the SoC group. D-dimer levels were decreased from baseline for the nVNS group and increased from baseline for the SoC group at day 5 and overall, although the difference between the treatment groups did not reach statistical significance. No significant treatment differences were seen for clinical respiratory outcomes or any of the other biochemical markers evaluated. No serious nVNS-related adverse events occurred during the study. Conclusions: nVNS therapy led to significant reductions in levels of inflammatory markers, specifically CRP and procalcitonin. Because nVNS has multiple mechanisms of action that may be relevant to COVID-19, additional research into its potential use earlier in the course of COVID-19 and its potential to mitigate some of the symptoms associated with post-acute sequelae of COVID-19 is warranted.

4.
Am J Obstet Gynecol ; 2022 Apr 19.
Article in English | MEDLINE | ID: covidwho-1797270

ABSTRACT

BACKGROUND: The effect of COVID-19 in pregnancy on maternal outcomes and its association with preeclampsia and gestational diabetes mellitus have been reported; however, a detailed understanding of the effects of maternal positivity, delivery mode, and perinatal practices on fetal and neonatal outcomes is urgently needed. OBJECTIVE: To evaluate the impact of COVID-19 on fetal and neonatal outcomes and the role of mode of delivery, breastfeeding, and early neonatal care practices on the risk of mother-to-child transmission. STUDY DESIGN: In this cohort study that took place from March 2020 to March 2021, involving 43 institutions in 18 countries, 2 unmatched, consecutive, unexposed women were concomitantly enrolled immediately after each infected woman was identified, at any stage of pregnancy or delivery, and at the same level of care to minimize bias. Women and neonates were followed up until hospital discharge. COVID-19 in pregnancy was determined by laboratory confirmation and/or radiological pulmonary findings or ≥2 predefined COVID-19 symptoms. The outcome measures were indices of neonatal and perinatal morbidity and mortality, neonatal positivity and its correlation with mode of delivery, breastfeeding, and hospital neonatal care practices. RESULTS: A total of 586 neonates born to women with COVID-19 diagnosis and 1535 neonates born to women without COVID-19 diagnosis were enrolled. Women with COVID-19 diagnosis had a higher rate of cesarean delivery (52.8% vs 38.5% for those without COVID-19 diagnosis, P<.01) and pregnancy-related complications, such as hypertensive disorders of pregnancy and fetal distress (all with P<.001), than women without COVID-19 diagnosis. Maternal diagnosis of COVID-19 carried an increased rate of preterm birth (P≤.001) and lower neonatal weight (P≤.001), length, and head circumference at birth. In mothers with COVID-19 diagnosis, the length of in utero exposure was significantly correlated to the risk of the neonate testing positive (odds ratio, 4.5; 95% confidence interval, 2.2-9.4 for length of in utero exposure >14 days). Among neonates born to mothers with COVID-19 diagnosis, birth via cesarean delivery was a risk factor for testing positive for COVID-19 (odds ratio, 2.4; 95% confidence interval, 1.2-4.7), even when severity of maternal conditions was considered and after multivariable logistic analysis. In the subgroup of neonates born to women with COVID-19 diagnosis, the outcomes worsened when the neonate also tested positive, with higher rates of neonatal intensive care unit admission, fever, gastrointestinal and respiratory symptoms, and death, even after adjusting for prematurity. Breastfeeding by mothers with COVID-19 diagnosis and hospital neonatal care practices, including immediate skin-to-skin contact and rooming-in, were not associated with an increased risk of newborn positivity. CONCLUSION: In this multinational cohort study, COVID-19 in pregnancy was associated with increased maternal and neonatal complications. Cesarean delivery was significantly associated with newborn COVID-19 diagnosis. Vaginal delivery should be considered the safest mode of delivery if obstetrical and health conditions allow it. Mother-to-child skin-to-skin contact, rooming-in, and direct breastfeeding were not risk factors for newborn COVID-19 diagnosis, thus well-established best practices can be continued among women with COVID-19 diagnosis.

5.
5th International Conference on Electrical Information and Communication Technology, EICT 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1788662

ABSTRACT

Sentiment analysis can largely influence the people to get the update of the current situation. Coronavirus (COVID-19) is a contagious illness caused by the SARS-CoV-2 virus that causes severe respiratory symptoms. The lives of millions have continued to be affected by this pandemic, several countries have resorted to a full lockdown. During this lockdown, people have taken social networks to express their emotions to find a way to calm themselves down. People are spreading their sentiments through microblogging websites as one of the most preventive steps of this disease is the socialization to gain people's awareness to stay home and keep their distance when they are outside home. Twitter is a popular online social media platform for exchanging ideas. People can post their different sentiments, which can be used to aware people. But, some people want to spread fake news to frighten the people. So, it is necessary to identify the positive, negative, and neutral thoughts so that the positive opinions can be delivered to the mass people for spreading awareness to the people. Moreover, a huge volume of data is floating on Twitter. So, it is also important to identify the context of the dataset. In this paper, we have analyzed the twitter dataset for evaluating the sentiment using several machine learning algorithms, where the random forest algorithm achieved the highest accuracy of 93%. Later, we have found out the context learning of the dataset based on the sentiments. © 2021 IEEE.

6.
3rd International Conference on Research and Academic Community Services, ICRACOS 2021 ; : 166-170, 2021.
Article in English | Scopus | ID: covidwho-1759083

ABSTRACT

COVID-19 spreads from person to person in communities (local transmission). Symptoms experienced vary from one person to another. Some may be asymptomatic, while others can experience mild to severe respiratory illness. Adults with existing medical problems are said to have more severe respiratory symptoms. As SARS-Cov-2 cases continually increase in the Philippines, hospitals and quarantine facilities can no longer accommodate new patients. People exposed to the virus are considered Person Under Investigation (PUI). And those experiencing COVID-like symptoms are Person Under Monitoring (PUM). Patients assessed as PUI/PUM are no longer admitted to the hospitals but observe their condition at home. In this study, the researchers developed a System that will closely monitor the symptoms of the probable SARS-COV-2 patients. It aims to assist healthcare professionals, including Barangay health workers, in tracking the patient's condition and informing them once the System evaluates the severity of the patient's symptoms. A clinical symptom dataset was used in this analysis to identify the COVID-like symptoms using the Decision Tree algorithm. The result shows that the System could determine if the patient's symptoms are severe or not. © 2021 IEEE.

7.
2021 IEEE International Conference on Big Data, Big Data 2021 ; : 5620-5625, 2021.
Article in English | Scopus | ID: covidwho-1730883

ABSTRACT

The COVID-19 pandemic has brought a devastating impact on human health across the globe, and people are still observing face-masking as a preventive measure to contain the spread of COVID-19. Coughing is one of the major transmission mediums of COVID-19, and early cough detection could play a significant r ole i n p reventing t he s pread o f t his life-threatening virus. Many approaches have been proposed for developing systems to detect coughing and other respiratory symptoms in literature, but earable devices are not well-studied and investigated for respiratory symptom detection. In this work, we posited an acoustic research prototype (earable device) - eSense that has acoustic and IMU sensors embedded into user-convenient earbuds to address the following issues: (i) feasibility of the earables in detecting respiratory symptoms, and (ii) scalability of trained machine learning models in the presence of unseen data samples. We performed experimentation with both shallow and deep learning models on the eSense collected data samples. We observed that the deep learning model outperforms the shallow learning models achieving 97% accuracy. Furthermore, we investigated the scalability of the deep learning model on unseen datasets and noticed that the performance of the deep learning model deteriorates when trained on a particular dataset and tested on an unseen dataset. To mitigate such challenges, we postulated an adversarial domain adaptation technique that helps improve the performance of our respiratory symptoms detection framework by a substantial margin. © 2021 IEEE.

8.
2020 IEEE MIT Undergraduate Research Technology Conference, URTC 2020 ; 2020.
Article in English | Scopus | ID: covidwho-1722962

ABSTRACT

COVID-19 is a highly contagious infection that has now reached almost all countries in the world infecting over 33M and killing 1M people as of the time of writing. Therefore, it is essential to diagnose it early so that health care professionals can prevent the chance of a person spreading the virus. Because the disease often presents with respiratory symptoms, one method for detecting it is by radiology examination using chest radiography. Healthcare professionals examine the chest X-ray for abnormalities that are characteristics of those infected with COVID-19, which must be distinguished from other conditions with similar presentation such as pneumonia. This requires significant expertise, which may not be available in all parts of the world, so computer assisted diagnosis would be highly beneficial. We propose a deep neural network for extracting those abnormalities as features and classifying the infection. In this study, we examine the efficiency of small-sized deep neural network tailored for the detection of COVID-19 infection from chest X-ray (CXR) images. We designed a modified version of SqueezeNet and Capsule Network and show that even with a relatively small number of free parameters, it can achieve a competitive result while having modest hardware requirements. We use a modified version of fire modules to ensure better convergence. For our Capsule network, we used fire modules as two of its upper layers. To our knowledge, this is the first time that a fire module has been used in conjunction with capsules. Without any pretraining or transfer learning, our SqueezeNet was able to achieve an accuracy of 94.8 %, sensitivity of 88.0 %, and specificity of 98.4%. Additionally, our CapsNet achieved an accuracy of 93.8 %, sensitivity of 88.0 %, and specificity of 96.9 %. © 2020 IEEE.

9.
4th IEEE International Conference on Electronics and Communication Engineering, ICECE 2021 ; : 277-281, 2021.
Article in English | Scopus | ID: covidwho-1722912

ABSTRACT

Since the outbreak COVID-19 in Wuhan, China in December 2019, a large number of patients have been seen worldwide, and the number of infections continues to show an increasing trend. The vast majority of COVID-19 patients will have fever, headache, and mild respiratory symptoms, but a small number of severely ill patients will experience respiratory distress and related complications, which seriously endanger their lives. The large number of patients also puts the healthcare system to the test. To maximize the protection of patients' lives and the effective use of medical resources, this study collected blood data from 313 patients by machine learning, used 7 blood test items as the feature quantity, established an effective linear SVM prediction model for severe/non-severe disease (recall: 93.55%, specificity: 93.22%), and for 3 stages evaluation of the degree of severe level in severe patients was developed for patients with critical illness. The abnormal increase in Ferritin values was also found to be closely related to the development of severity. ©2021 IEEE

10.
J Infect Dis ; 225(8): 1308-1316, 2022 04 19.
Article in English | MEDLINE | ID: covidwho-1705456

ABSTRACT

BACKGROUND: To quantify the potential decline in dynamic lung volumes following coronavirus disease 2019 (COVID-19) in the general population. METHODS: A prospective matched cohort study of adult Copenhagen General Population Study (CGPS) participants with a prepandemic spirometry available. CGPS individuals with positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) test performed repeat spirometry, a questionnaire regarding respiratory symptoms, and diffusing capacity test for carbon monoxide. A matched uninfected CGPS control sample was used, and simple regression and linear mixed effect models were computed to study lung function decline. RESULTS: A total of 606 individuals were included; 92/107 (85.9%) with positive SARS-CoV-2 PCR test experienced coronavirus disease 2019 (COVID-19) symptoms and 12 (11.2%) were hospitalized. Spirometry was performed at median 5.6 months (interquartile range, 3.9-12.8) after positive SARS-CoV-2 PCR test. COVID-19 was associated with adjusted 7.3 mL (95% confidence interval [CI], .3-14.3) and 22.6 mL (95% CI, 13.1-32.0) steeper decline in annual forced expiratory volume in first second (FEV1) and FVC or total 113.8 and 301.3 mL lower FEV1 and FVC from baseline to follow-up. Results were robust in analyses restricted to individuals not requiring hospitalization. CONCLUSIONS: COVID-19-related declines of dynamic lung volume in the general population not requiring hospitalization were small but measurable.


Subject(s)
COVID-19 , Adult , Cohort Studies , Humans , Lung , Prospective Studies , SARS-CoV-2 , Vital Capacity
11.
Infection ; 50(2): 513-517, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1641037

ABSTRACT

PURPOSE: During a follow-up program of patients admitted for COVID-19 at our non-ICU Unit, we found that 37% of them had decreased diffusing lung capacity for carbon monoxide (DLCO) 3-6 months after discharge. This prospective observational study aimed to evaluate the evolution of changes in DLCO and respiratory symptoms at the 1-year follow-up visit. METHODS: Seventeen (mean age 71 years; 8 males) of 19 eligible patients (DLCO < 80% of predicted at the 3-6 months follow-up visit) completed the 1-year follow-up visit. One patient refused to participate and 1 patient had died 3 months earlier from myocardial infarction. The visit included a self-reported structured questionnaire, physical exam, blood tests, ECG, and spirometry with DLCO. RESULTS: Mean DLCO was significantly improved at the 1-year visit (from 64% of predicted at 3-6 months to 74% of predicted at 1 year; P = 0.003). A clinically significant increase in DLCO (10% or greater) was observed in 11 patients (65%) with complete normalization (> 80% of predicted) in 6 (35%); in the other 6 (35%) it remained unchanged. The prevalence of exertional dyspnea (65-35%, P = 0.17), cough (24-18%, P = 1), and fatigue (76-35%, P = 0.04) decreased at the 1-year visit. CONCLUSION: These results suggest that DLCO and respiratory symptoms tend to normalize or improve 1 year after hospitalization for COVID-19 in most patients. However, there is also a non-negligible number of patients (about one-third) in whom respiratory changes persist and will need prolonged follow-up.


Subject(s)
COVID-19 , Aged , COVID-19/complications , Hospitalization , Humans , Lung/diagnostic imaging , Male , Patient Discharge , Spirometry
12.
Front Immunol ; 12: 767376, 2021.
Article in English | MEDLINE | ID: covidwho-1556073

ABSTRACT

Evidence supports a role of complement anaphylatoxin C5a in the pathophysiology of COVID-19. However, information about the evolution and impact of C5a levels after hospital discharge is lacking. We analyzed the association between circulating C5a levels and the clinical evolution of hospitalized patients infected with SARS-CoV-2. Serum C5a levels were determined in 32 hospitalized and 17 non-hospitalized patients from Clinica Universidad de Navarra. One hundred and eighty eight serial samples were collected during the hospitalization stay and up to three months during the follow-up. Median C5a levels were 27.71 ng/ml (25th to 75th percentile: 19.35-34.96) for samples collected during hospitalization, versus 16.76 ng/ml (12.90-25.08) for samples collected during the follow-up (p<0.001). There was a negative correlation between serum C5a levels and the number of days from symptom onset (p<0.001). C5a levels also correlated with a previously validated clinical risk score (p<0.001), and was associated with the severity of the disease (p<0.001). An overall reduction of C5a levels was observed after hospital discharge. However, elevated C5a levels persisted in those patients with high COVID-19 severity (i.e. those with a longest stay in the hospital), even after months from hospital discharge (p=0.020). Moreover, high C5a levels appeared to be associated with the presence of long-term respiratory symptoms (p=0.004). In conclusion, serum C5a levels remain high in severe cases of COVID-19, and are associated with the presence of respiratory symptoms after hospital discharge. These results may suggest a role for C5a in the long-term effects of COVID-19 infection.


Subject(s)
COVID-19/blood , Complement C5a/metabolism , Patient Discharge/statistics & numerical data , Aged , COVID-19/complications , COVID-19/immunology , Female , Follow-Up Studies , Hospitalization , Humans , Immunity, Innate , Male , Middle Aged , Respiration Disorders/blood , Respiration Disorders/etiology , Respiration Disorders/immunology , Risk Factors , SARS-CoV-2 , Severity of Illness Index
13.
Infect Drug Resist ; 14: 5035-5040, 2021.
Article in English | MEDLINE | ID: covidwho-1547064

ABSTRACT

The patient had several close contacts with friends from Wuhan, the epicenter of the epidemic. His mother and father had close contact with him. His father was later diagnosed with COVID-19 infection after a positive reverse transcription PCR test for SARS-CoV-2 RNA. The patient and his mother were diagnosed as suspected cases of COVID-19 based on a history of exposure, clinical manifestation, and imaging examination. However, the patient was tested more than three times with the reverse transcription PCR test for SARS-CoV-2 RNA, and the results were negative each time. COVID-19 should be suspected, regardless of SARS-CoV-2 test negativity, for recent close contact with a confirmed case and respiratory symptoms.

14.
Viruses ; 13(12)2021 11 25.
Article in English | MEDLINE | ID: covidwho-1542796

ABSTRACT

Children with COVID-19 develop moderate symptoms in most cases. Thus, a proportion of children requires hospital admission. The study aimed to assess the history, clinical and laboratory parameters in children with COVID-19 concerning the severity of respiratory symptoms. The study included 332 children (median age 57 months) with COVID-19. History data, clinical findings, laboratory parameters, treatment, and outcome, were evaluated. Children were compared in the groups that varied in the severity of symptoms of respiratory tract involvement. Children who required oxygen therapy represented 8.73%, and intensive care 1.5% of the whole cohort. Comorbidities were present in 126 patients (37.95%). Factors increasing the risk of oxygen therapy included comorbidities (odds ratio (OR) = 92.39; 95% confidence interval (95% CI) = (4.19; 2036.90); p < 0.00001), dyspnea (OR = 45.81; 95% CI (4.05; 518.21); p < 0.00001), auscultation abnormalities (OR = 34.33; 95% CI (2.59; 454.64); p < 0.00001). Lactate dehydrogenase (LDH) > 280 IU/L and creatinine kinase > 192 IU/L were parameters with a good area under the curve (0.804-LDH) and a positive predictive value (42.9%-CK). The clinical course of COVID-19 was mild to moderate in most patients. Children with comorbidities, dyspnea, or abnormalities on auscultation are at risk of oxygen therapy. Laboratory parameters potentially useful in patients evaluated for the severe course are LDH > 200 IU/L and CK > 192 IU/L.


Subject(s)
COVID-19/physiopathology , Respiratory System/physiopathology , Adolescent , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/therapy , Child , Child, Preschool , Comorbidity , Female , Hospitalization , Humans , Infant , Male , Respiration, Artificial , Respiratory System/diagnostic imaging , Risk Factors , SARS-CoV-2 , Severity of Illness Index
15.
Int J Environ Res Public Health ; 18(21)2021 10 28.
Article in English | MEDLINE | ID: covidwho-1488565

ABSTRACT

The overall unemployment rate in South Africa was impacted by the coronavirus (COVID-19) pandemic, which led many people to resort to informal work such as street trading opportunities in big cities. However, this work is located in the same cities where air pollution is of concern. Furthermore, literature has indicated the lack of regulation of the informal trading sector as compared to the formal sector. An analytical cross-sectional study is proposed to be conducted amongst all of the informal food street vendors (indoor/inside buildings and outdoor/street pavements stalls) in the inner city of Johannesburg, South Africa. By adopting a total sampling method of 746 vendor stalls, this study's key focus is on inhalation as an occupational exposure. In addition, the study aims to assess the respiratory risk factors amongst informal food street vendors' stalls and their impact on vendors' respiratory health. The risk factors to be assessed include the five common air pollutants: street vendor's infrastructure; socioeconomic factors; personal behavior such as tobacco smoking and handwashing practices; wearing of respiratory protective equipment; and vendors' exposure duration. The data collection will follow three phases using quantitative methods. In the pre-assessment phase, it will include a pilot study to test the walkthrough survey checklist and the respiratory symptoms and diseases questionnaire. The assessment phase includes a total of eight area samples, which will be taken in a 1-day event over four yearly seasons, as well as thirty personal samples taken in winter over an 8-h work shift. The post-assessment phase will be the development of a risk impact assessment and a risk management model. The study is essential for healthy occupational conditions as indicated in the Occupational Health and Safety (OHS) Act (no. 85 of 1993) and the Regulations governing general hygiene requirements for food premises, the transport of food, and related matters (no. R638 of 22 June 2018).


Subject(s)
COVID-19 , Cross-Sectional Studies , Humans , Pilot Projects , SARS-CoV-2 , South Africa/epidemiology
16.
Front Microbiol ; 12: 743048, 2021.
Article in English | MEDLINE | ID: covidwho-1485075

ABSTRACT

The factors affecting the dynamics of lengthening of symptoms and serologic responses are not well known. In order to see how the serologic responses change in relation to the clinical features, we selected a group of 472 adults with a positive IgM/IgG antibody test result from a baseline study of the anti-SARS-CoV-2 seropositivity, assessed their COVID-19 and past medical histories, and followed them up in about 3 months. Nearly one-fourth of the subjects were asymptomatic at the baseline; 12.8% subjects became symptomatic at the follow-up (FU) when 39.8% of the subjects had some persisting symptoms. At the baseline, 6.1% showed anti-SARS-CoV-2 IgM positive, 59.3% only for IgG, and 34.5% for both. At the FU, these figures declined to 0.6, 54.0, and 4.4%, respectively, with the mean IgM and IgG levels declining about 6.3 and 2.5 folds. Blood group A was consistently linked to both sustaining and flipping of the gastrointestinal (GI) and respiratory symptoms. The baseline IgM level was associated with GI symptoms and pre-existing cirrhosis in multivariate models. Both of the baseline and FU IgG levels were strongly associated with age, male, and lung involvement seen in chest computed tomography (CT)-scan. Finally, as compared with antibody decayers, IgM sustainers were found to be more anosmic [mean difference (MD): 11.5%; P = 0.047] with lower body mass index (BMI) (MD: 1.30 kg/m2; P = 0.002), while IgG sustainers were more commonly females (MD: 19.2%; P = 0.042) with shorter diarrhea duration in the FU (MD: 2.8 days; P = 0.027). Our findings indicate how the anti-SARS-CoV-2 serologic response and COVID-19 clinical presentations change in relation to each other and basic characteristics.

17.
Integr Med Res ; 10: 100798, 2021.
Article in English | MEDLINE | ID: covidwho-1472010

ABSTRACT

BACKGROUND: We aimed to investigate use of infection control behaviours, preventative and therapeutic interventions, and outcomes among respondents to an online survey during the COVID-19 pandemic in China. METHODS: The survey was designed by an international team, translated and adapted to simplified Chinese, including 132 kinds of traditional Chinese medicine (TCM) preparation recommended by guidelines. It was distributed and collected from February to May 2021, with data analysed by WPS spreadsheet and wjx.cn. Descriptive statistics were used to describe demographics and clinical characteristics, diagnosis, treatments, preventative behaviours and interventions, and their associated outcomes. RESULTS: The survey was accessed 503 times with 341 (67.8%) completions covering 23 provinces and four municipalities in China. Most (282/341, 82.7%) respondents reported no symptoms during the pandemic and the majority (290/341, 85.0%) reported having a SARS-CoV-2 PCR test at some point. Forty-five (13.2%) reported having a respiratory infection, among which 19 (42.2%) took one or more categories of modern medicine, e.g. painkillers, antibiotics; 16 (35.6%) used TCM interventions(s); while seven respondents combined TCM with modern medicine. All respondents reported using at least one behavioural or medical approach to prevention, with 22.3% taking TCM and 5.3% taking modern medicines. No respondents reported having a critical condition related to COVID-19. CONCLUSION: We found evidence of widespread use of infection control behaviours, modern medicines and TCM for treatment and prevention of COVID-19 and other respiratory symptoms. Larger scale studies are warranted, including a more representative sample exploring TCM preparations recommended in clinical guidelines.

18.
Pulm Pharmacol Ther ; : 102083, 2021 Oct 08.
Article in English | MEDLINE | ID: covidwho-1458516

ABSTRACT

SARS-CoV-2 pandemic has contributed to implement telemedicine, allowing clinicians to follow the patient remotely, therefore minimizing the risk of any exposure to positive COVID-19 patients. We summarize the approaches adopted to treat and monitor severe asthmatic patients during the lockdown phase of the pandemic. Our experience supports the strategy that every effort should be made to minimize patient contact with the health-care system, planning a pathway that allows patients to receive appropriate medical care and continue the biological therapies, thus preventing the loss of disease control and acute severe exacerbations.

19.
Biomedicines ; 9(8)2021 Jul 27.
Article in English | MEDLINE | ID: covidwho-1334997

ABSTRACT

BACKGROUND: The long-term impact of COVID-19 is still unknown. This study aimed to explore post COVID-19 effects on patients chest computed tomography (CT), lung function, respiratory symptoms, fatigue, functional capacity, health-related quality of life (HRQoL), and the ability to return to work beyond 3 months post infection. METHODS: A systematic search was performed on PubMed, Web of Science, and Ovid MEDLINE on 22 May 2021, to identify studies that reported persistent effects of COVID-19 beyond 3 months follow-up. Data on the proportion of patients who had the outcome were collected and analyzed using a one-group meta-analysis. RESULTS: Data were extracted from 24 articles that presented information on a total of 5323 adults, post-infection, between 3 to 6 months after symptom onset or hospital discharge. The pooled prevalence of CT abnormalities was 59% (95% CI 44-73, I2 = 96%), abnormal lung function was 39% (95% CI 24-55, I2 = 94%), fatigue was 38% (95% CI 27-49, I2 = 98%), dyspnea was 32% (95% CI 24-40, I2 = 98%), chest paint/tightness was 16% (95% CI 12-21, I2 = 94%), and cough was 13%, (95% CI 9-17, I2 = 94%). Decreased functional capacity and HRQoL were found in 36% (95% CI 22-49, I2 = 97%) and 52% (95% CI 33-71, I2 = 94%), respectively. On average, 8 out of 10 of the patients had returned to work or reported no work impairment. CONCLUSION: Post-COVID-19 patients may experience persistent respiratory symptoms, fatigue, decreased functional capacity and decreased quality of life up to 6 months after infection. Further studies are needed to establish the extent to which post-COVID-19 effects continue beyond 6 months, how they interact with each other, and to clarify their causes and their effective management.

20.
Epidemiol Infect ; 149: e92, 2021 04 05.
Article in English | MEDLINE | ID: covidwho-1169347

ABSTRACT

Case identification is an ongoing issue for the COVID-19 epidemic, in particular for outpatient care where physicians must decide which patients to prioritise for further testing. This paper reports tools to classify patients based on symptom profiles based on 236 severe acute respiratory syndrome coronavirus 2 positive cases and 564 controls, accounting for the time course of illness using generalised multivariate logistic regression. Significant symptoms included abdominal pain, cough, diarrhoea, fever, headache, muscle ache, runny nose, sore throat, temperature between 37.5 and 37.9 °C and temperature above 38 °C, but their importance varied by day of illness at assessment. With a high percentile threshold for specificity at 0.95, the baseline model had reasonable sensitivity at 0.67. To further evaluate accuracy of model predictions, leave-one-out cross-validation confirmed high classification accuracy with an area under the receiver operating characteristic curve of 0.92. For the baseline model, sensitivity decreased to 0.56. External validation datasets reported similar result. Our study provides a tool to discern COVID-19 patients from controls using symptoms and day from illness onset with good predictive performance. It could be considered as a framework to complement laboratory testing in order to differentiate COVID-19 from other patients presenting with acute symptoms in outpatient care.


Subject(s)
Ambulatory Care , COVID-19 Testing/methods , COVID-19/diagnosis , Abdominal Pain/physiopathology , Adolescent , Adult , COVID-19/physiopathology , Case-Control Studies , Clinical Decision Rules , Cough/physiopathology , Diarrhea/physiopathology , Disease Progression , Dyspnea/physiopathology , Female , Fever/physiopathology , Headache/physiopathology , Humans , Logistic Models , Male , Middle Aged , Multivariate Analysis , Myalgia/physiopathology , Odds Ratio , Patient Selection , Pharyngitis/physiopathology , Rhinorrhea/physiopathology , SARS-CoV-2 , Sensitivity and Specificity , Severity of Illness Index , Young Adult
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