Conectar
Fatigue, headache, problems sleeping and numerous other symptoms have been reported to be associated with long COVID. However, many of these symptoms coincide with symptoms reported by the general population, possibly exacerbated by restrictions/precautions experienced during the COVID-19 pandemic. This study examines the symptoms reported by individuals who tested positive for COVID-19 compared with those who tested negative.
Observational study.
The study was conducted on adult residents in Alberta, Canada, from October 2021 to February 2023.
We evaluated self-reported symptoms in 7623 adults with positive COVID-19 tests and 1520 adults who tested negative, using surveys adapted from the internationally standardised International Severe Acute Respiratory and emerging Infection Consortium (ISARIC)-developed COVID-19 long-term follow-up tools. These individuals had an index COVID-19 test date between 1 March 2020 and 31 December 2022 and were over 28 days post-COVID-19 testing.
The primary outcomes were to identify the symptoms associated with COVID-19 positivity and risk factors for reporting symptoms.
Fatigue was the top reported symptom (42%) among COVID-19-positive respondents, while headache was the top reported symptom (32%) in respondents who tested negative. Compared with those who tested negative, COVID-19-positive individuals reported 1.5 times more symptoms and had higher odds of experiencing 31 out of the 40 listed symptoms during the postinfectious period. These symptoms included olfactory dysfunction, menstruation changes, cardiopulmonary and neurological symptoms. Female sex, middle age (41–55 years), Indigeneity, unemployment, hospital/intensive care unit (ICU) admission at the time of testing and pre-existing health conditions independently predicted a greater number and variety of symptoms.
Our results provide evidence that COVID-19 survivors continue to experience a significant number and variety of symptoms. These findings can help inform targeted strategies for the unequally affected population. It is important to offer appropriate management for symptom relief to those who have survived the acute COVID-19 illness.
Knowledge models inform organizational behavior through the logical association of documentation processes, definitions, data elements, and value sets. The development of a well-designed knowledge model allows for the reuse of electronic health record data to promote efficiency in practice, data interoperability, and the extensibility of data to new capabilities or functionality such as clinical decision support, quality improvement, and research. The purpose of this article is to describe the development and validation of a knowledge model for healthcare-associated venous thromboembolism prevention. The team used FloMap, an Internet-based survey resource, to compare metadata from six healthcare organizations to an initial draft model. The team used consensus decision-making over time to compare survey results. The resulting model included seven panels, 41 questions, and 231 values. A second validation step included completion of an Internet-based survey with 26 staff nurse respondents representing 15 healthcare organizations, two electronic health record vendors, and one academic institution. The final knowledge model contained nine Logical Observation Identifiers Names and Codes panels, 32 concepts, and 195 values representing an additional six panels (groupings), 15 concepts (questions), and the specification of 195 values (answers). The final model is useful for consistent documentation to demonstrate the contribution of nursing practice to the prevention of venous thromboembolism. 
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