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1.
JMIR Ment Health ; 2022 Jan 06.
Article in English | MEDLINE | ID: covidwho-1613483

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic triggered a seismic shift in education, to online learning. With nearly 20 million students enrolled in colleges across the U.S., the long-simmering mental health crisis in college students was likely further exacerbated by the pandemic. OBJECTIVE: This study leveraged mobile health (mHealth) technology and sought to: i) characterize self-reported outcomes of physical, mental, and social health by COVID-19 status; ii) assess physical activity through consumer-grade wearable sensors (Fitbit®); and iii) identify risk factors associated with COVID-19 positivity in a population of college students prior to release of the vaccine. METHODS: Detailed methods were previously published in JMIR Res Protocols (Cislo et al). After completing a baseline assessment (i.e., Time 0 [T0]) of demographics, mental, and social health constructs through the Roadmap 2.0 app, participants were instructed to use the app freely, to wear the Fitbit®, and complete subsequent assessments at T1, T2 and T3, followed by a COVID-19 assessment of history and timing of COVID-19 testing and diagnosis (T4: ~14 days after T3). Continuous measures were described using means (M) and standard deviations (SD), while categorical measures were summarized using frequencies and proportions. Formal comparisons were made based on COVID-19 status. The multivariate model was determined by entering all statistically significant variables (P<.05) in univariable associations at once and then removing one variable at a time by backward selection until the optimal model was obtained. RESULTS: During the fall 2020 semester, 1,997 participants consented, enrolled, and met criteria for data analyses. There was a high prevalence of anxiety, as assessed by the State Trait Anxiety Index (STAI), with moderate and severe levels in N=465 (24%) and N=970 (49%) students, respectively. Approximately, one-third of students reported having a mental health disorder (N=656, 33%). The average daily steps recorded in this student population was approximately 6500 (M=6474, SD=3371). Neither reported mental health nor step count were significant based on COVID-19 status (P=.52). Our analyses revealed significant associations of COVID-positivity with use of marijuana and alcohol (P =.020 and .046, respectively) and lower belief in public health measures (P=.003). In addition, graduate students were less likely and those with ≥20 roommates were more likely to report a COVID-19 diagnosis (P=.009). CONCLUSIONS: Mental health problems were common in this student population. Several factors, including substance use, were associated with risk of COVID-19. These data highlight important areas for further attention, such as prioritizing innovative strategies that address health and well-being, considering the potential long-term effects of COVID-19 on college students. CLINICALTRIAL: ClinicalTrials.gov NCT04766788. INTERNATIONAL REGISTERED REPORT: RR2-10.2196/29561.

2.
EBioMedicine ; 74: 103722, 2021 Nov 25.
Article in English | MEDLINE | ID: covidwho-1536517

ABSTRACT

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. METHODS: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. FINDINGS: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. INTERPRETATION: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. FUNDING: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411 .

3.
BMJ Open ; 11(11): e051065, 2021 11 15.
Article in English | MEDLINE | ID: covidwho-1518146

ABSTRACT

OBJECTIVES: The COVID-19 pandemic has resulted in widespread morbidity and mortality with the consequences expected to be felt for many years. Significant variation exists in the care even of similar patients with COVID-19, including treatment practices within and between institutions. Outcome measures vary among clinical trials on the same therapies. Understanding which therapies are of most value is not possible unless consensus can be reached on which outcomes are most important to measure. Furthermore, consensus on the most important outcomes may enable patients to monitor and track their care, and may help providers to improve the care they offer through quality improvement. To develop a standardised minimum set of outcomes for clinical care, the International Consortium for Health Outcomes Measurement (ICHOM) assembled a working group (WG) of 28 volunteers, including health professionals, patients and patient representatives. DESIGN: A list of outcomes important to patients and professionals was generated from a systematic review of the published literature using the MEDLINE database, from review of outcomes being measured in ongoing clinical trials, from a survey distributed to patients and patient networks, and from previously published ICHOM standard sets in other disease areas. Using an online-modified Delphi process, the WG selected outcomes of greatest importance. RESULTS: The outcomes considered by the WG to be most important were selected and categorised into five domains: (1) functional status and quality of life, (2) mental functioning, (3) social functioning, (4) clinical outcomes and (5) symptoms. The WG identified demographic and clinical variables for use as case-mix risk adjusters. These included baseline demographics, clinical factors and treatment-related factors. CONCLUSION: Implementation of these consensus recommendations could help institutions to monitor, compare and improve the quality and delivery of care to patients with COVID-19. Their consistent definition and collection could also broaden the implementation of more patient-centric clinical outcomes research.


Subject(s)
COVID-19 , Quality of Life , Humans , Outcome Assessment, Health Care , Pandemics , SARS-CoV-2
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