Exploring Diagnostic Strategies for Streptococcal Throat Infection Remotely: A Feasibility Study.

Context: Acute sore throat is a common presentation in primary care and often results in antibiotic prescription. The Covid pandemic has driven changes in consultation with less face to face visits. Scoring tools are available to target antibiotics and widely used in the UK but it is not clear whether patient self assessment is feasible and sufficiently precise to enable remote use of scoring tools. Objective: A feasibility study to develop and test remote assessment of acute sore throat. Design: Observational study Setting: UK primary care Population: Adults and children with sore throat were asked to use the online tool and report their clinical findings directly Intervention: An online tool was developed that could help patients or parents of children with sore throat assess the clinical features that make up clinical prediction rules and to take a photograph of the throat Results: 221 patients with sore throat were screened and 45 (33 adults and 12 children) were recruited. 44/45 (97.8%) participants were able to complete all elements of the clinical assessment. It was possible to calculate a FeverPAIN score for 25 (75.8%) adults and 10 (83.3%) children. 35 participants (25 (75.8%) adults and 10 (83.3%) children) provided a throat photograph but many of these were not of sufficient quality to enable assessment of throat pus and inflammation. Poor lighting and focus were the main problems. Photos that were of sufficient quality were available from 13 (39.4%) adults and 5 (41.7%) children. Three GPs independently assessed these photographs to assess for inflammation and pus. Using the clinician assessment as the reference standard, self/parent/carer assessment of inflammation had a sensitivity of 100%, specificity of 46.7%, positive predictive value (PPV) of 27.3% and negative predictive value (NPV) of 100%. The sensitivity, specificity, PPV and NPV for pus were 76.5%, 100%, 71.4%, 42.9% and 100%. Conclusions: Self assessment of sore throat was possible. Photographs were of sufficient quality for clinical assessment less than half the time. Patients/parents/carers are very good at ruling out pus and inflammation, but have a tendency to overcall these findings, especially inflammation. Further implications for self assessment and future work will be described.

Self-sampling to identify pathogens and inflammatory markers in patients with acute sore throat: Feasibility study.

Introduction: Sore throat is a common reason for overuse of antibiotics. The value of inflammatory or biomarkers in throat swab or saliva samples in predicting benefit from antibiotics is unknown. Methods: We used the 'person-based approach' to develop an online tool to support self-swabbing and recruited adults and children with sore throats through participating general practices and social media. Participants took bacterial and viral swabs and a saliva sponge swab and passive drool sample. Bacterial swabs were cultured for streptococcus (Group A, B, C, F and G). The viral swab and saliva samples were tested using a routine respiratory panel PCR and Covid-19 PCR testing. We used remaining viral swab and saliva sample volume for biomarker analysis using a panel of 13 biomarkers. Results: We recruited 11 asymptomatic participants and 45 symptomatic participants. From 45 symptomatic participants, bacterial throat swab, viral throat swab, saliva sponge and saliva drool samples were returned by 41/45 (91.1%), 43/45 (95.6%), 43/45 (95.6%) and 43/45 (95.6%) participants respectively. Three saliva sponge and 6 saliva drool samples were of insufficient quantity. Two adult participants had positive bacterial swabs. Six participants had a virus detected from at least one sample (swab or saliva). All of the biomarkers assessed were detectable from all samples where there was sufficient volume for testing. For most biomarkers we found higher concentrations in the saliva samples. Due to low numbers, we were not able to compare biomarker concentrations in those who did and did not have a bacterial pathogen detected. We found no evidence of a difference between biomarker concentrations between the symptomatic and asymptomatic participants but the distributions were wide. Conclusions: We have demonstrated that it is feasible for patients with sore throat to self-swab and provide saliva samples for pathogen and biomarker analysis. Typical bacterial and viral pathogens were detected but at low prevalence rates. Further work is needed to determine if measuring biomarkers using oropharyngeal samples can help to differentiate between viral and bacterial pathogens in patients classified as medium or high risk using clinical scores, in order to better guide antibiotic prescribing and reduce inappropriate prescriptions.

To swab or not to swab? Using point-of-care tests to detect Group A Streptococcus infections as part of a Sore Throat Test and Treat service in community pharmacy.

BACKGROUND: The community pharmacy-led Sore Throat Test and Treat (STTT) service in Wales allowed pharmacists to undertake a structured clinical assessment with FeverPAIN/Centor scores and a point-of-care test (POCT) for Group A Streptococcus (GAS) infection. A new service model was temporarily agreed as a result of COVID-19, without routine use of POCT. OBJECTIVES: To explore the impact of removing the requirement for GAS POCT from a community pharmacy STTT service on antibiotic supply. METHODS: Analysis of STTT consultation data, obtained for two periods: November 2018 (date the service went live) to September 2019 (pre-pandemic); and November 2020 (date the new service model was introduced) to May 2021. RESULTS: For consultations eligible for POCT, the antibiotic supply rate increased from 27% (922/3369) (95% CI: 26%-29%) with the pre-pandemic service model (FeverPAIN/Centor + POCT) to 63% (93/147) (95% CI: 55%-71%) with the new model (FeverPAIN/Centor only); the percentage of patients who were not issued an antibiotic, despite their high clinical score, decreased from 56% (646/1154) to 9.3% (8/86). CONCLUSIONS: Preliminary data suggest that for every 100 STTT consultations with patients with a Centor score of ≥3 or a FeverPAIN score of ≥2, the use of POCT may spare up to 36 courses of antibiotics, increasing to 47 for patients with higher clinical scores, suggesting that the pre-COVID delivery model (FeverPAIN/Centor + POCT) is the optimal pathway and POCT in addition to clinical scores may result in fewer antibiotic prescriptions for sore throat symptoms. These findings have implications for STTT service delivery during and beyond the COVID-19 pandemic.

Use of the McIsaac Score to Predict Group A Streptococcal Pharyngitis in Outpatient Nurse Phone Triage and Electronic Visits Compared With In-Person Visits: Retrospective Observational Study.

BACKGROUND: The McIsaac criteria are a validated scoring system used to determine the likelihood of an acute sore throat being caused by group A streptococcus (GAS) to stratify patients who need strep testing. OBJECTIVE: We aim to compare McIsaac criteria obtained during face-to-face (f2f) and non-f2f encounters. METHODS: This retrospective study compared the percentage of positive GAS tests by McIsaac score for scores calculated during nurse protocol phone encounters, e-visits (electronic visits), and in person f2f clinic visits. RESULTS: There was no difference in percentages of positive strep tests between encounter types for any of the McIsaac scores. There were significantly more phone and e-visit encounters with any missing score components compared with f2f visits. For individual score components, there were significantly fewer e-visits missing fever and cough information compared with phone encounters and f2f encounters. F2f encounters were significantly less likely to be missing descriptions of tonsils and lymphadenopathy compared with phone and e-visit encounters. McIsaac scores of 4 had positive GAS rates of 55% to 68% across encounter types. There were 4 encounters not missing any score components with a McIsaac score of 0. None of these 4 encounters had a positive GAS test. CONCLUSIONS: McIsaac scores of 4 collected during non-f2f care could be used to consider empiric treatment for GAS without testing if significant barriers to testing exist such as the COVID-19 pandemic or geographic barriers. Future studies should evaluate further whether non-f2f encounters with McIsaac scores of 0 can be safely excluded from GAS testing.

Clinical decision support tool for diagnosis of COVID-19 in hospitals.

BACKGROUND: The coronavirus infectious disease 19 (COVID-19) pandemic has resulted in significant morbidities, severe acute respiratory failures and subsequently emergency departments' (EDs) overcrowding in a context of insufficient laboratory testing capacities. The development of decision support tools for real-time clinical diagnosis of COVID-19 is of prime importance to assist patients' triage and allocate resources for patients at risk. METHODS AND PRINCIPAL FINDINGS: From March 2 to June 15, 2020, clinical patterns of COVID-19 suspected patients at admission to the EDs of Liège University Hospital, consisting in the recording of eleven symptoms (i.e. dyspnoea, chest pain, rhinorrhoea, sore throat, dry cough, wet cough, diarrhoea, headache, myalgia, fever and anosmia) plus age and gender, were investigated during the first COVID-19 pandemic wave. Indeed, 573 SARS-CoV-2 cases confirmed by qRT-PCR before mid-June 2020, and 1579 suspected cases that were subsequently determined to be qRT-PCR negative for the detection of SARS-CoV-2 were enrolled in this study. Using multivariate binary logistic regression, two most relevant symptoms of COVID-19 were identified in addition of the age of the patient, i.e. fever (odds ratio [OR] = 3.66; 95% CI: 2.97-4.50), dry cough (OR = 1.71; 95% CI: 1.39-2.12), and patients older than 56.5 y (OR = 2.07; 95% CI: 1.67-2.58). Two additional symptoms (chest pain and sore throat) appeared significantly less associated to the confirmed COVID-19 cases with the same OR = 0.73 (95% CI: 0.56-0.94). An overall pondered (by OR) score (OPS) was calculated using all significant predictors. A receiver operating characteristic (ROC) curve was generated and the area under the ROC curve was 0.71 (95% CI: 0.68-0.73) rendering the use of the OPS to discriminate COVID-19 confirmed and unconfirmed patients. The main predictors were confirmed using both sensitivity analysis and classification tree analysis. Interestingly, a significant negative correlation was observed between the OPS and the cycle threshold (Ct values) of the qRT-PCR. CONCLUSION AND MAIN SIGNIFICANCE: The proposed approach allows for the use of an interactive and adaptive clinical decision support tool. Using the clinical algorithm developed, a web-based user-interface was created to help nurses and clinicians from EDs with the triage of patients during the second COVID-19 wave.

Diagnostic value of symptoms for pediatric SARS-CoV-2 infection in a primary care setting.

PURPOSE: To evaluate the diagnostic value of symptoms used by daycares and schools to screen children and adolescents for SARS-CoV-2 infection, we analyzed data from a primary care setting. METHODS: This cohort study included all patients ≤17 years old who were evaluated at Providence Community Health Centers (PCHC; Providence, U.S.), for COVID-19 symptoms and/or exposure, and received SARS-CoV-2 polymerase chain reaction (PCR) testing between March-June 2020. Participants were identified from PCHC electronic medical records. For three age groups- 0-4, 5-11, and 12-17 years-we estimated the sensitivity, specificity, and area under the receiver operating curve (AUC) of individual symptoms and three symptom combinations: a case definition published by the Rhode Island Department of Health (RIDOH), and two novel combinations generated by different statistical approaches to maximize sensitivity, specificity, and AUC. We evaluated symptom combinations both with and without consideration of COVID-19 exposure. Myalgia, headache, sore throat, abdominal pain, nausea, anosmia, and ageusia were not assessed in 0-4 year-olds due to the lower reliability of these symptoms in this group. RESULTS: Of 555 participants, 217 (39.1%) were SARS-CoV-2-infected. Fever was more common among 0-4 years-olds (p = 0.002); older children more frequently reported fatigue (p = 0.02). In children ≥5 years old, anosmia or ageusia had 94-98% specificity. In all ages, exposure history most accurately predicted infection. With respect to individual symptoms, cough most accurately predicted infection in <5 year-olds (AUC 0.69) and 12-17 year-olds (AUC 0.62), while headache was most accurate in 5-11 year-olds (AUC 0.62). In combination with exposure history, the novel symptom combinations generated statistically to maximize test characteristics had sensitivity >95% but specificity <30%. No symptom or symptom combination had AUC ≥0.70. CONCLUSIONS: Anosmia or ageusia in children ≥5 years old should raise providers' index of suspicion for COVID-19. However, our overall findings underscore the limited diagnostic value of symptoms.

Broadening symptom criteria improves early case identification in SARS-CoV-2 contacts.

BACKGROUND: The success of case isolation and contact tracing for the control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission depends on the accuracy and speed of case identification. We assessed whether inclusion of additional symptoms alongside three canonical symptoms (CS), i.e. fever, cough and loss or change in smell or taste, could improve case definitions and accelerate case identification in SARS-CoV-2 contacts. METHODS: Two prospective longitudinal London (UK)-based cohorts of community SARS-CoV-2 contacts, recruited within 5 days of exposure, provided independent training and test datasets. Infected and uninfected contacts completed daily symptom diaries from the earliest possible time-points. Diagnostic information gained by adding symptoms to the CS was quantified using likelihood ratios and area under the receiver operating characteristic curve. Improvements in sensitivity and time to detection were compared with penalties in terms of specificity and number needed to test. RESULTS: Of 529 contacts within two cohorts, 164 (31%) developed PCR-confirmed infection and 365 (69%) remained uninfected. In the training dataset (n=168), 29% of infected contacts did not report the CS. Four symptoms (sore throat, muscle aches, headache and appetite loss) were identified as early-predictors (EP) which added diagnostic value to the CS. The broadened symptom criterion "≥1 of the CS, or ≥2 of the EP" identified PCR-positive contacts in the test dataset on average 2 days earlier after exposure (p=0.07) than "≥1 of the CS", with only modest reduction in specificity (5.7%). CONCLUSIONS: Broadening symptom criteria to include individuals with at least two of muscle aches, headache, appetite loss and sore throat identifies more infections and reduces time to detection, providing greater opportunities to prevent SARS-CoV-2 transmission.

Predictive symptoms for COVID-19 in the community: REACT-1 study of over 1 million people.

BACKGROUND: Rapid detection, isolation, and contact tracing of community COVID-19 cases are essential measures to limit the community spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to identify a parsimonious set of symptoms that jointly predict COVID-19 and investigated whether predictive symptoms differ between the B.1.1.7 (Alpha) lineage (predominating as of April 2021 in the US, UK, and elsewhere) and wild type. METHODS AND FINDINGS: We obtained throat and nose swabs with valid SARS-CoV-2 PCR test results from 1,147,370 volunteers aged 5 years and above (6,450 positive cases) in the REal-time Assessment of Community Transmission-1 (REACT-1) study. This study involved repeated community-based random surveys of prevalence in England (study rounds 2 to 8, June 2020 to January 2021, response rates 22%-27%). Participants were asked about symptoms occurring in the week prior to testing. Viral genome sequencing was carried out for PCR-positive samples with N-gene cycle threshold value < 34 (N = 1,079) in round 8 (January 2021). In univariate analysis, all 26 surveyed symptoms were associated with PCR positivity compared with non-symptomatic people. Stability selection (1,000 penalized logistic regression models with 50% subsampling) among people reporting at least 1 symptom identified 7 symptoms as jointly and positively predictive of PCR positivity in rounds 2-7 (June to December 2020): loss or change of sense of smell, loss or change of sense of taste, fever, new persistent cough, chills, appetite loss, and muscle aches. The resulting model (rounds 2-7) predicted PCR positivity in round 8 with area under the curve (AUC) of 0.77. The same 7 symptoms were selected as jointly predictive of B.1.1.7 infection in round 8, although when comparing B.1.1.7 with wild type, new persistent cough and sore throat were more predictive of B.1.1.7 infection while loss or change of sense of smell was more predictive of the wild type. The main limitations of our study are (i) potential participation bias despite random sampling of named individuals from the National Health Service register and weighting designed to achieve a representative sample of the population of England and (ii) the necessary reliance on self-reported symptoms, which may be prone to recall bias and may therefore lead to biased estimates of symptom prevalence in England. CONCLUSIONS: Where testing capacity is limited, it is important to use tests in the most efficient way possible. We identified a set of 7 symptoms that, when considered together, maximize detection of COVID-19 in the community, including infection with the B.1.1.7 lineage.

The Identification of First COVID-19 Cluster in Indonesia.

We describe the first 11 detected COVID-19 cases in Indonesia, resulting from a local transmission occurring in a club and a restaurant. The virus was detected until an average of 21.3 days (range: 11-25, SD: 4.1) after the onset of illness, and the partial N gene sequences (28,321-28,707 nucleotide position) had 100% similarity with the SARS-CoV-2 sequence from Wuhan. Two subjects were asymptomatic, and one subject has died.

COVID-19 in cancer patients can be challenging to screen in a resource limited setting.

During this COVID-19 pandemic, patients with symptoms such as fever, cough, sore throat, and coryza were advised to have RT-PCR testing for SARS-CoV-2 infection. We described here an elderly female with chronic lymphocytic leukemia, who presented with atypical symptoms that were not directly attributable to COVID-19. This patient was admitted to the non-COVID-19 ward for supportive care. Later, her chest x-ray revealed pneumonia that was confirmed to be COVID-19 by RT-PCR testing several days later. In resource-poor settings where molecular testing results suffered from delays or were altogether unavailable, the use of diagnostic imaging such as a chest x-ray could serve as a quick guide in the assessment and management of these patients especially if the imaging results suggest COVID-19 infection.

Comparison of influenza type A and B with COVID-19: A global systematic review and meta-analysis on clinical, laboratory and radiographic findings.

We compared clinical symptoms, laboratory findings, radiographic signs and outcomes of COVID-19 and influenza to identify unique features. Depending on the heterogeneity test, we used either random or fixed-effect models to analyse the appropriateness of the pooled results. Overall, 540 articles included in this study; 75,164 cases of COVID-19 (157 studies), 113,818 influenza type A (251 studies) and 9266 influenza type B patients (47 studies) were included. Runny nose, dyspnoea, sore throat and rhinorrhoea were less frequent symptoms in COVID-19 cases (14%, 15%, 11.5% and 9.5%, respectively) in comparison to influenza type A (70%, 45.5%, 49% and 44.5%, respectively) and type B (74%, 33%, 38% and 49%, respectively). Most of the patients with COVID-19 had abnormal chest radiology (84%, p < 0.001) in comparison to influenza type A (57%, p < 0.001) and B (33%, p < 0.001). The incubation period in COVID-19 (6.4 days estimated) was longer than influenza type A (3.4 days). Likewise, the duration of hospitalization in COVID-19 patients (14 days) was longer than influenza type A (6.5 days) and influenza type B (6.7 days). Case fatality rate of hospitalized patients in COVID-19 (6.5%, p < 0.001), influenza type A (6%, p < 0.001) and influenza type B was 3%(p < 0.001). The results showed that COVID-19 and influenza had many differences in clinical manifestations and radiographic findings. Due to the lack of effective medication or vaccine for COVID-19, timely detection of this viral infection and distinguishing from influenza are very important.

Prognostic value of serum amyloid A in patients with COVID-19.

OBJECTIVE: To investigate the prognostic value of serum amyloid A (SAA) in the patients with Corona Virus Disease 2019 (COVID-19). METHODS: The medical data of 89 COVID-19 patients admitted to Renmin Hospital of Wuhan University from January 3, 2020 to February 26, 2020 were collected. Eighty-nine cases were divided into survival group (53 cases) and non-survival group (36 cases) according to the results of 28-day follow-up. The SAA levels of all patients were recorded and compared on 1 day after admission (before treatment) and 3 days, 5 days, and 7 days after treatment. The ROC curve was drawn to analyze the prognosis of patients with COVID-19 by SAA. RESULTS: The difference of comparison of SAA between survival group and non-survival group before treatment was not statistically significant, Z1 = - 1.426, P = 0.154. The Z1 values (Z1 is the Z value of the rank sum test) of the two groups of patients at 3 days, 5 days, and 7 days after treatment were - 5.569, - 6.967, and - 7.542, respectively. The P values were all less than 0.001, and the difference was statistically significant. The ROC curve results showed that SAA has higher sensitivity to the prognostic value of 1 day (before treatment), 3 days, 5 days, and 7 days after treatment, with values of 0.806, 0.972, 0.861, and 0.961, respectively. Compared with SAA on the 7th day and C-reactive protein, leukocyte count, neutrophil count, lymphocyte count, and hemoglobin on the 7th day, the sensitivities were: 96.1%, 83.3%, 88.3%, 83.3%, 67.9%, and 83.0%, respectively, of which SAA has the highest sensitivity. CONCLUSION: SAA can be used as a predictor of the prognosis in patients with COVID-19.

Clinical features of COVID-19 and influenza: a comparative study on Nord Franche-Comte cluster.

Clinical descriptions about influenza-like illnesses (ILI) in COVID-19 seem non-specific. We aimed to compare the clinical features of COVID-19 and influenza. We retrospectively investigated the clinical features and outcomes of confirmed cases of COVID-19 and influenza in Nord Franche-Comté Hospital between February 26th and March 14th 2020. We used SARS-CoV-2 RT-PCR and influenza virus A/B RT-PCR in respiratory samples to confirm the diagnosis. We included 124 patients. The mean age was 59 (±19 [19-98]) years with 69% female. 70 patients with COVID-19 and 54 patients with influenza A/B. Regarding age, sex and comorbidities, no differences were found between the two groups except a lower Charlson index in COVID-19 group (2 [±2.5] vs 3 [±2.4],p = 0.003). Anosmia (53% vs 17%,p < 0.001), dysgeusia (49% vs 20%,p = 0.001), diarrhea (40% vs 20%,p = 0.021), frontal headache (26% vs 9%,p = 0.021) and bilateral cracklings sounds (24% vs 9%,p = 0.034) were statistically more frequent in COVID-19. Sputum production (52% vs 29%,p = 0.010), dyspnea (59% vs 34%,p = 0.007), sore throat (44% vs 20%,p = 0.006), conjunctival hyperhemia (30% vs 4%,p < 0.001), tearing (24% vs 6%,p = 0.004), vomiting (22% vs 3%,p = 0.001) and rhonchi sounds (17% vs 1%,p = 0.002) were more frequent with influenza infection. We described several clinical differences which can help the clinicians during the co-circulation of influenza and SARS-CoV-2.

Clinical characteristics of 194 cases of COVID-19 in Huanggang and Taian, China.

PURPOSE: We aimed to report the clinical characteristics of 194 cases coronavirus disease-19 (COVID-19) in Huanggang, Hubei and Taian, Shandong. METHODS: We retrospectively investigated the clinical, laboratory characteristics and CT imaging of confirmed cases of COVID-19 from January 22 to February 28, 2020 in Huanggang Central Hospital and The Second Affiliated Hospital of Shandong First Medical University. Real time PCR was used to detect the new coronavirus in respiratory samples. Immunohistochemical staining was used to detect the expressions of ACE2 in tissues. RESULTS: Among the 194 patients infected with COVID-19, 108 patients were male, with a median age of 48.3 years. The average preclinical period was 7.44 day. Except for 37 severe or critically ill patients, the rest of the 157 patients exhibited mild or moderate symptoms. 190 (97.94%) patients were confirmed during the three times nucleic acid test. The main clinical symptom of the patients were fever, sore throat and cough, which accounted for 146 cases (75.26%), 98 (50.52%) and 86 cases (44.33%), respectively. 30 patients (15.46%) showed liver dysfunction. Imaging examination showed that 141 patients (72.68%) showed abnormal density shadow, while 53 cases (27.32%) had no obvious abnormality in the parenchyma of both lungs. Up to now, 109 cases have been discharged from the hospital, and 9 patients died. The ACE2 expression levels were up-regulated in patients of severe type and critically ill type. CONCLUSION: Clinical symptoms, laboratory tests and CT imaging should be combined for comprehensive analysis to diagnose COVID-19. ACE2 may be the receptor of COVID-19.