Using Social Media to Help Understand Patient-Reported Health Outcomes of Post-COVID-19 Condition: Natural Language Processing Approach.

BACKGROUND: While scientific knowledge of post-COVID-19 condition (PCC) is growing, there remains significant uncertainty in the definition of the disease, its expected clinical course, and its impact on daily functioning. Social media platforms can generate valuable insights into patient-reported health outcomes as the content is produced at high resolution by patients and caregivers, representing experiences that may be unavailable to most clinicians. OBJECTIVE: In this study, we aimed to determine the validity and effectiveness of advanced natural language processing approaches built to derive insight into PCC-related patient-reported health outcomes from social media platforms Twitter and Reddit. We extracted PCC-related terms, including symptoms and conditions, and measured their occurrence frequency. We compared the outputs with human annotations and clinical outcomes and tracked symptom and condition term occurrences over time and locations to explore the pipeline's potential as a surveillance tool. METHODS: We used bidirectional encoder representations from transformers (BERT) models to extract and normalize PCC symptom and condition terms from English posts on Twitter and Reddit. We compared 2 named entity recognition models and implemented a 2-step normalization task to map extracted terms to unique concepts in standardized terminology. The normalization steps were done using a semantic search approach with BERT biencoders. We evaluated the effectiveness of BERT models in extracting the terms using a human-annotated corpus and a proximity-based score. We also compared the validity and reliability of the extracted and normalized terms to a web-based survey with more than 3000 participants from several countries. RESULTS: UmlsBERT-Clinical had the highest accuracy in predicting entities closest to those extracted by human annotators. Based on our findings, the top 3 most commonly occurring groups of PCC symptom and condition terms were systemic (such as fatigue), neuropsychiatric (such as anxiety and brain fog), and respiratory (such as shortness of breath). In addition, we also found novel symptom and condition terms that had not been categorized in previous studies, such as infection and pain. Regarding the co-occurring symptoms, the pair of fatigue and headaches was among the most co-occurring term pairs across both platforms. Based on the temporal analysis, the neuropsychiatric terms were the most prevalent, followed by the systemic category, on both social media platforms. Our spatial analysis concluded that 42% (10,938/26,247) of the analyzed terms included location information, with the majority coming from the United States, United Kingdom, and Canada. CONCLUSIONS: The outcome of our social media-derived pipeline is comparable with the results of peer-reviewed articles relevant to PCC symptoms. Overall, this study provides unique insights into patient-reported health outcomes of PCC and valuable information about the patient's journey that can help health care providers anticipate future needs. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1101/2022.12.14.22283419.

Figure Correction: Using Social Media to Help Understand Patient-Reported Health Outcomes of Post-COVID-19 Condition: Natural Language Processing Approach.

[This corrects the article DOI: 10.2196/45767.].

Evaluation of SARS-CoV-2 antigen-based rapid diagnostic kits in Pakistan: formulation of COVID-19 national testing strategy.

Rapid diagnosis of SARS-CoV-2 during pandemic enables timely treatment and prevention of COVID-19. Evaluating the accuracy and reliability of rapid diagnostic testing kits is crucial for surveillance and diagnosis of SARS-CoV-2 infections in general population, injection drug users, multi-transfused populations, healthcare workers, prisoners, barbers and other high risk populations. The aim of this study was to evaluate performance and effectiveness of nasopharyngeal swab (NSP) and saliva based rapid antigen detection testing kits in comparison with USFDA approved triple target gold standard real-time polymerase chain reaction. A cross-sectional study was conducted on 33,000 COVID-19 suspected patients. From RT-PCR positive patients, nasopharyngeal swab (NSP) and saliva samples were obtained for evaluation of rapid COVID-19 testing kits (RDT). 100/33,000 (0.3%) of specimens were RT-PCR positive for SARS-CoV-2. Among RT-PCR positive, 62% were males, 34% were females, and 4% were children. The NSP-RDT (Lepu Medical China) analysis revealed 53% reactivity among males, 58% reactivity among females, and 25% reactivity among children. However saliva based RDT (Lepu Medical China) analysis showed 21% reactivity among males and 23% among females, and no reactivity in children. False negative results were significantly more pronounced in saliva based RDT as compared to NSP-RDT. The sensitivity of these NSP-RDT and saliva based RDT were 52% and 21% respectively. The RDTs evaluated in this study showed limited sensitivities in comparison to gold standard RT-PCR, indicating that there is a dire need in Pakistan for development of suitable testing to improve accurate COVID-19 diagnosis in line with national demands.

SARS-CoV-2 induced hepatic injuries and liver complications.

Background: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which is resilient, highly pathogenic, and rapidly transmissible. COVID-19 patients have been reported to have underlying chronic liver abnormalities linked to hepatic dysfunction. Discussion: Viral RNAs are detectable in fecal samples by RT-PCR even after negative respiratory samples, which suggests that SARS-CoV-2 can affect the gastrointestinal tract and the liver. The case fatality rates are higher among the elderly and those with underlying comorbidities such as hypertension, diabetes, liver abnormality, and heart disease. There is insufficient research on signaling pathways. Identification of molecular mechanisms involved in SARS-CoV-2-induced damages to hepatocytes is challenging. Herein, we demonstrated the multifactorial effects of SARS-CoV-2 on liver injury such as psychological stress, immunopathogenesis, systemic inflammation, ischemia and hypoxia, drug toxicity, antibody-dependent enhancement (ADE) of infection, and several others which can significantly damage the liver. Conclusion: During the COVID-19 pandemic, it is necessary for clinicians across the globe to pay attention to SARS-CoV-2-mediated liver injury to manage the rising burden of hepatocellular carcinoma. To face the challenges during the resumption of clinical services for patients with pre-existing liver abnormalities and HCC, the impact of SARS-CoV-2 on hepatocytes should be investigated both in vitro and in vivo.