PASCLex: A comprehensive post-acute sequelae of COVID-19 (PASC) symptom lexicon derived from electronic health record clinical notes

Wang, Liqin; Foer, Dinah; MacPhaul, Erin; Lo, Ying-Chih; Bates, David W.; Zhou, Li

doi:10.1016/j.jbi.2021.103951

Cited by 39 publications

(44 citation statements)

References 39 publications

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“…A recent systematic review of 38 papers reported that one-third or more of surviving COVID-19 patients experienced at least one PASC symptom during the 2-5 months after the onset of acute infection 1 . PASC symptoms are numerous and varied, impacting virtually every major organ system (https://www.cdc.gov/coronavirus/2019-ncov/long-term-effects/index.html) 2,3 and can last for weeks or months. Despite the large number of individuals affected, the lack of consensus diagnostic criteria or standardized outcome measures impede efforts to effectively group persons to establish clinical etiologies or to evaluate outcomes for therapeutic trials 4 .…”

Section: Main Textmentioning

confidence: 99%

Persistent serum protein signatures define an inflammatory subset of long COVID

Talla

Vasaikar

Szeto

et al. 2022

Preprint

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Long COVID or post-acute sequelae of SARS-CoV-2 (PASC) is a clinical syndrome featuring diverse symptoms that can persist for months after acute SARS-CoV-2 infection. The etiologies are unknown but may include persistent inflammation, unresolved tissue damage, or delayed clearance of viral protein or RNA. Attempts to classify subsets of PASC by symptoms alone have been unsuccessful. To molecularly define PASC, we evaluated the serum proteome in longitudinal samples from 55 PASC individuals with symptoms lasting ≥60 days after onset of acute infection and compared this to symptomatically recovered SARS-CoV-2 infected and uninfected individuals. We identified subsets of PASC with distinct signatures of persistent inflammation. Type II interferon signaling and canonical NF-κB signaling (particularly associated with TNF), were the most differentially enriched pathways. These findings help to resolve the heterogeneity of PASC, identify patients with molecular evidence of persistent inflammation, and highlight dominant pathways that may have diagnostic or therapeutic relevance.One Sentence SummarySerum proteome profiling identifies subsets of long COVID patients with evidence of persistent inflammation including key immune signaling pathways that may be amenable to therapeutic intervention.

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Section: Main Textmentioning

confidence: 99%

Persistent serum protein signatures define an inflammatory subset of long COVID

Talla

Vasaikar

Szeto

et al. 2022

Preprint

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“…Although not much research has investigated the issue, the use of electronic health systems may make it more difficult for patients and physicians to interact with one another. According to the findings of Shachak's study, 92 percent of doctors think that the growing usage of the electronic health system has decreased the amount of face-to-face time that is spent between patients and their doctors [20]. The completion of electronic documentation requires the use of a computer, which may be timeconsuming for physicians, particularly if they are not proficient in its usage.…”

Section: Interference With Doctor-patient Relationshipmentioning

confidence: 99%

“…According to research conducted by Pizziferri and other academics who have focused their attention on this topic, the majority of medical professionals have avoided "sacrificing time with patients or total clinic time, but they do spend more time on paperwork outside of clinic sessions" both before and after the implementation of an electronic health system [20]. According to the same research, electronic health systems do increase the amount of labor that physicians have to perform; but, given the absence of further studies to back up these statements, we should proceed with caution.…”

Section: More Time and Attention Are Spent On Each Individual Patientmentioning

confidence: 99%

Barriers of Utilizing an Electronic Health System in Sub-Saharan Africa

Kuffour¹

2022

AJESS

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Objective: Accessing data information of patients has been a challenge for years due to the use of paper recording, some essential data are either lost or mistakenly thrown away and cannot be retrieved. This is a major public health concern to ensure the effective provision of healthcare to patients. The purpose of the study focuses on the barriers to utilizing an electronic health system in sub-Saharan Africa. Methods: A systematic review was carried out with the aid of online research journal websites as well as other in-context articles. While conducting this study, the keywords in the search query were directed toward the barriers to the implementation of an electronic health system in Sub-Saharan Africa. Areas noted in relation to this study were the use of electronic health systems among health professionals. Therefore, there was a linkage of papers pointing out the barriers hindering the implementation of the e-health system. Results: According to Kemper and other researchers more than half (58.1%) of the physicians without an electronic medical system doubt that an electronic medical system can improve patient care or clinical outcomes. In Shachak’s research, where this issue was considered, 92% of physicians felt electronic medical system use did disturb communication with their patients. Conclusion: The findings of this study can be used as an overview of barriers that physicians might possibly see in the electronic medical system implementation process and, as such, could be valuable for electronic medical system policymakers and implementers. The study indicates that policymakers should be more aware of the reality that removing technical, financial, and legal barriers is not sufficient to ensure the realization of the promises of electronic medical system.

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“…Current understandings of COVID-19 symptoms are primarily established on clinical data from medical institutions [20][21][22] , such as electronic health records (EHRs). However, nearly 80% of patients with asymptomatic or mild symptoms are not promptly or never clinically diagnosed and treated [23][24][25] , leading to potential missing information for mild and early symptoms.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Trend and co-occurrence network study of symptoms through social media: an example of COVID-19

Hua

et al. 2022

Preprint

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Importance: COVID-19 is a multi-organ disease with broad-spectrum manifestations. Clinical data-driven research can be difficult because many patients do not receive prompt diagnoses, treatment, and follow-up studies. Social medias accessibility, promptness, and rich information provide an opportunity for large-scale and long-term analyses, enabling a comprehensive symptom investigation to complement clinical studies. Objective: Present an efficient workflow to identify and study the characteristics and co-occurrences of COVID-19 symptoms using social media. Design, Setting, and Participants: This retrospective cohort study analyzed 471,553,966 COVID-19-related tweets from February 1, 2020, to April 30, 2022. A comprehensive lexicon of symptoms was used to filter tweets through rule-based methods. 948,478 tweets with self-reported symptoms from 689,551 Twitter users were identified for analysis. Main Outcomes and Measures: The overall trends of COVID-19 symptoms reported on Twitter were analyzed (separately by the Delta strain and the Omicron strain) using weekly new numbers, overall frequency, and temporal distribution of reported symptoms. A co-occurrence network was developed to investigate relationships between symptoms and affected organ systems. Results: The weekly quantity of self-reported symptoms has a high consistency (0.8528, P<0.0001) and one-week leading trend (0. 8802, P<0.0001) with new infections in four countries. We grouped 201 common symptoms (mentioned ≥ 10 times) into 10 affected systems. The frequency of symptoms showed dynamic changes as the pandemic progressed, from typical respiratory symptoms in the early stage to more musculoskeletal and nervous symptoms at later stages. When comparing symptoms reported during the Delta strain versus the Omicron variant, significant changes were observed, with dropped odd ratios of coma (95%CI 0.55-0.49, P<0.01) and anosmia (95%CI, 0.6-0.56), and more pain in the throat (95%CI, 1.86-1.96) and concentration problems (95%CI, 1.58-1.70). The co-occurrence network characterizes relationships among symptoms and affected systems, both intra-systemic, such as cough and sneezing (respiratory), and inter-systemic, such as alopecia (integumentary) and impotence (reproductive). Conclusions and Relevance: We found dynamic COVID-19 symptom evolution through self-reporting on social media and identified 201 symptoms from 10 affected systems. This demonstrates that social medias prevalence trends and co-occurrence networks can efficiently identify and study public health problems, such as common symptoms during pandemics.

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PASCLex: A comprehensive post-acute sequelae of COVID-19 (PASC) symptom lexicon derived from electronic health record clinical notes

Cited by 39 publications

References 39 publications

Persistent serum protein signatures define an inflammatory subset of long COVID

Persistent serum protein signatures define an inflammatory subset of long COVID

Barriers of Utilizing an Electronic Health System in Sub-Saharan Africa

Trend and co-occurrence network study of symptoms through social media: an example of COVID-19

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