ArticleCureus2021
Development and Validation of a Clinical Symptom-based Scoring System for Diagnostic Evaluation of COVID-19 Patients Presenting to Outpatient Department in a Pandemic Situation.
Article in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19.The Cochrane database of systematic reviews · 2022Pooled it
- Validation of a Nepali version of the questionnaire to assess preventive practices against the COVID-19 pandemic in the general population.BMC public health · 2024Article
- Diagnosis of COVID-19: Is Fever the Best Indicator of COVID-19 in Vaccinated SARS-CoV-2-Positive Adults?Cureus · 2024Article
- Performance and explainability of feature selection-boosted tree-based classifiers for COVID-19 detection.Heliyon · 2024Article
- Genomic surveillance and serological profile of SARS-CoV-2 variants circulating in Macaé and nearby cities, southeastern Brazil.Frontiers in microbiology · 2024Article
- Simple Symptom-Based Prediction of COVID-19: A Single-Center Study of Outpatient Fever Clinic in Japan.Cureus · 2023Article
- Development of an Item Bank to Assess Patient-Reported Outcomes: Signs, Symptoms, and Impacts of COVID-19.The patient · 2022Review
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Preventive strategies in the form of early identification and isolation of patients are the cornerstones in the control of COVID-19 pandemic. We have conducted this study to develop a clinical symptom-based scoring system (CSBSS) for the diagnostic evaluation of COVID-19. Methods In this study, 378 patients presenting to screening outpatient clinic with clinical suspicion of COVID-19 were evaluated for various clinical symptoms. Statistical associations between presenting symptoms and reverse transcription-polymerase chain reaction (RT-PCR) results were analysed to select statistically significant clinical symptoms to design a scoring formula. CSBSS was developed by evaluating clinical symptoms in 70% of the total patients. The cut-off score of the CSBSS was determined from ROC (receiver operating characteristics) curve analysis to obtain a cut-off for optimum sensitivity and specificity. Subsequently, developed CSBSS was validated in the external validation dataset comprising 30% of patients. Results Clinical symptoms like fever >100
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